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+   "id": "6242b563-faf9-411b-b61e-ff6d5d802609",
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+   "source": [
+    "# Widefield tutorial\n",
+    "\n",
+    "This tutorial demonstraces how to access the *Widefield dataset* using `pynwb`. \n",
+    "\n",
+    "This dataset contains the Widefield imaging from multiple cortical visual areas and behavior measurements from the ViRMEN system.\n",
+    "\n",
+    "Contents:\n",
+    "\n",
+    "- [Reading an NWB file](#read-nwb)\n",
+    "- [Access subject and task metadata](#access-subject)\n",
+    "- [Access Imaging](#access-imaging)\n",
+    "- [Access Behavior](#access-behavior)\n",
+    "- [View NWB files](#view-nwb)\n",
+    "\n",
+    "![Alt text](data_types.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6bc8942c-2b51-4bd9-9e87-51cdd58f25ef",
+   "metadata": {},
+   "source": [
+    "# Reading an NWB file <a name=\"read-nwb\"></a>\n",
+    "\n",
+    "This section demonstrates how to read an NWB file using `pynwb`.\n",
+    "\n",
+    "Based on the [NWB File Basics](https://pynwb.readthedocs.io/en/stable/tutorials/general/plot_file.html#sphx-glr-tutorials-general-plot-file-py) tutorial from [PyNWB](https://pynwb.readthedocs.io/en/stable/#).\n",
+    "\n",
+    "Reading is carried out using the [NWBHDF5IO](https://pynwb.readthedocs.io/en/stable/pynwb.html#pynwb.NWBHDF5IO) class. To read the NWB file use the read mode (\"r\") to retrieve an NWBFile object.\n"
+   ]
+  },
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+   "execution_count": 7,
+   "id": "b2968627-3cdd-4c65-825c-4e239cf9a5ea",
+   "metadata": {},
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+       "        <div class='container-wrap'><div class='container-header'><div class='xr-obj-type'><h3>root (NWBFile)</h3></div></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['session_description']\">session_description:</span> <span class=\"field-value\">A rich text description of the experiment. Can also just be the abstract of the publication.</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['identifier']\">identifier:</span> <span class=\"field-value\">35b7de81-5636-47d8-8bb2-6ce5db2af37e</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['session_start_time']\">session_start_time:</span> <span class=\"field-value\">2023-04-19 10:57:31.591000-07:00</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['timestamps_reference_time']\">timestamps_reference_time:</span> <span class=\"field-value\">2023-04-19 10:57:31.591000-07:00</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['file_create_date']\"><b>file_create_date</b></summary><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-value\" title=\".fields['file_create_date'][0]\">2023-11-30 15:52:45.875965+01:00</span></div></details><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['experimenter']\">experimenter:</span> <span class=\"field-value\">('Luo, Jiaqi',)</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['acquisition']\"><b>acquisition (2)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue']\"><b>OnePhotonSeriesBlue</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['description']\">description:</span> <span class=\"field-value\">Imaging data from one-photon excitation microscopy.</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['unit']\">unit:</span> <span class=\"field-value\">n.a.</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['dimension']\"><b>dimension</b></summary></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['imaging_plane']\"><b>imaging_plane</b></summary><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['imaging_plane'].fields['optical_channel']\"><b>optical_channel</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-value\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['imaging_plane'].fields['optical_channel'][0]\">OpticalChannelBlue pynwb.ophys.OpticalChannel at 0x5353898512\n",
+       "Fields:\n",
+       "  description: An optical channel of the microscope.\n",
+       "  emission_lambda: nan\n",
+       "</span></div></details><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['imaging_plane'].fields['description']\">description:</span> <span class=\"field-value\">The plane or volume being imaged by the microscope.</span></div><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['imaging_plane'].fields['device']\"><b>device</b></summary></details><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['imaging_plane'].fields['excitation_lambda']\">excitation_lambda:</span> <span class=\"field-value\">nan</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['imaging_plane'].fields['imaging_rate']\">imaging_rate:</span> <span class=\"field-value\">10.0</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['imaging_plane'].fields['indicator']\">indicator:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['imaging_plane'].fields['location']\">location:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['imaging_plane'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesBlue'].fields['imaging_plane'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div></details></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet']\"><b>OnePhotonSeriesViolet</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['description']\">description:</span> <span class=\"field-value\">Imaging data from one-photon excitation microscopy.</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['unit']\">unit:</span> <span class=\"field-value\">n.a.</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['dimension']\"><b>dimension</b></summary></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['imaging_plane']\"><b>imaging_plane</b></summary><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['imaging_plane'].fields['optical_channel']\"><b>optical_channel</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-value\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['imaging_plane'].fields['optical_channel'][0]\">OpticalChannelViolet pynwb.ophys.OpticalChannel at 0x5353908304\n",
+       "Fields:\n",
+       "  description: An optical channel of the microscope.\n",
+       "  emission_lambda: nan\n",
+       "</span></div></details><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['imaging_plane'].fields['description']\">description:</span> <span class=\"field-value\">The plane or volume being imaged by the microscope.</span></div><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['imaging_plane'].fields['device']\"><b>device</b></summary></details><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['imaging_plane'].fields['excitation_lambda']\">excitation_lambda:</span> <span class=\"field-value\">nan</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['imaging_plane'].fields['imaging_rate']\">imaging_rate:</span> <span class=\"field-value\">10.0</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['imaging_plane'].fields['indicator']\">indicator:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['imaging_plane'].fields['location']\">location:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['imaging_plane'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['acquisition']['OnePhotonSeriesViolet'].fields['imaging_plane'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div></details></details></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['processing']\"><b>processing (2)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior']\"><b>behavior</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['description']\">description:</span> <span class=\"field-value\">contains processed behavioral data</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']\"><b>data_interfaces (9)</b></summary><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position']\"><b>Position</b></summary><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']\"><b>spatial_series (2)</b></summary><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries']\"><b>SpatialSeries</b></summary><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['description']\">description:</span> <span class=\"field-value\">The x, y, z position of the animal by ViRMEN iteration.</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['conversion']\">conversion:</span> <span class=\"field-value\">0.01</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div><details><summary style=\"display: list-item; margin-left: 120px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 120px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['reference_frame']\">reference_frame:</span> <span class=\"field-value\">(0,0) is the start of the 'sample' region (or 'cue' region) which varies by maze and task.</span></div></details><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame']\"><b>SpatialSeriesByImFrame</b></summary><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['description']\">description:</span> <span class=\"field-value\">The position of the animal averaged over the iterations for each frame.</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div><details><summary style=\"display: list-item; margin-left: 120px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 120px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['reference_frame']\">reference_frame:</span> <span class=\"field-value\">(0,0) is the start of the 'sample' region (or 'cue' region) which varies by maze and task.</span></div></details></details></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDots']\"><b>SensorDots</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDots'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDots'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDots'].fields['description']\">description:</span> <span class=\"field-value\">The sensordots by ViRMEN iteration.</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDots'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDots'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDots'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDots'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDots'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDots'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDots'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDotsByImFrame']\"><b>SensorDotsByImFrame</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDotsByImFrame'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDotsByImFrame'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDotsByImFrame'].fields['description']\">description:</span> <span class=\"field-value\">The sensordots averaged over the iterations for each frame.</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDotsByImFrame'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDotsByImFrame'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDotsByImFrame'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDotsByImFrame'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDotsByImFrame'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDotsByImFrame'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['SensorDotsByImFrame'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Velocity']\"><b>Velocity</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Velocity'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Velocity'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Velocity'].fields['description']\">description:</span> <span class=\"field-value\">The velocity of the animal by ViRMEN iteration.</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Velocity'].fields['conversion']\">conversion:</span> <span class=\"field-value\">0.01</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Velocity'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Velocity'].fields['unit']\">unit:</span> <span class=\"field-value\">m/s</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Velocity'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Velocity'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Velocity'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['Velocity'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityByImFrame']\"><b>VelocityByImFrame</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityByImFrame'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityByImFrame'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityByImFrame'].fields['description']\">description:</span> <span class=\"field-value\">The velocity of the animal averaged over the iterations for each frame.</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityByImFrame'].fields['conversion']\">conversion:</span> <span class=\"field-value\">0.01</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityByImFrame'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityByImFrame'].fields['unit']\">unit:</span> <span class=\"field-value\">m/s</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityByImFrame'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityByImFrame'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityByImFrame'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityByImFrame'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityGain']\"><b>VelocityGain</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityGain'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityGain'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityGain'].fields['description']\">description:</span> <span class=\"field-value\">The velocity gain by ViRMEN iteration.</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityGain'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityGain'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityGain'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityGain'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityGain'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityGain'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['VelocityGain'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle']\"><b>ViewAngle</b></summary><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']\"><b>spatial_series (4)</b></summary><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle']\"><b>PositionViewAngle</b></summary><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['description']\">description:</span> <span class=\"field-value\">The view angle of the animal by ViRMEN iteration.</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div><details><summary style=\"display: list-item; margin-left: 120px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 120px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['reference_frame']\">reference_frame:</span> <span class=\"field-value\">(0,0) is the start of the 'sample' region (or 'cue' region) which varies by maze and task.</span></div></details><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame']\"><b>PositionViewAngleByImFrame</b></summary><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['description']\">description:</span> <span class=\"field-value\">The view angle averaged over the iterations for each frame.</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div><details><summary style=\"display: list-item; margin-left: 120px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 120px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['reference_frame']\">reference_frame:</span> <span class=\"field-value\">(0,0) is the start of the 'sample' region (or 'cue' region) which varies by maze and task.</span></div></details><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle']\"><b>VelocityViewAngle</b></summary><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['description']\">description:</span> <span class=\"field-value\">The velocity view angle of the animal by ViRMEN iteration.</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div><details><summary style=\"display: list-item; margin-left: 120px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 120px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['reference_frame']\">reference_frame:</span> <span class=\"field-value\">(0,0) is the start of the 'sample' region (or 'cue' region) which varies by maze and task.</span></div></details><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame']\"><b>VelocityViewAngleByImFrame</b></summary><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['description']\">description:</span> <span class=\"field-value\">The view angle averaged over the iterations for each frame.</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div><details><summary style=\"display: list-item; margin-left: 120px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 120px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['reference_frame']\">reference_frame:</span> <span class=\"field-value\">(0,0) is the start of the 'sample' region (or 'cue' region) which varies by maze and task.</span></div></details></details></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['licks']\"><b>licks</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['licks'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['licks'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['licks'].fields['description']\">description:</span> <span class=\"field-value\">The lick response measured over time.</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['licks'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['licks'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['licks'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['licks'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['licks'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['licks'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['licks'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['TTLs']\"><b>TTLs</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['TTLs'].fields['description']\">description:</span> <span class=\"field-value\">The times when the eye tracking and/or imaging was on determined from the ViRMEN system.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['TTLs'].fields['id']\"><b>id</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['TTLs'].fields['colnames']\">colnames:</span> <span class=\"field-value\">('event_times', 'label', 'event_description')</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['behavior'].fields['data_interfaces']['TTLs'].fields['columns']\">columns:</span> <span class=\"field-value\">(<hdmf.common.table.VectorIndex object at 0x13fb8d950>, <hdmf.common.table.VectorData object at 0x13fb8fe90>, <hdmf.common.table.VectorData object at 0x13fb8ebd0>, <hdmf.common.table.VectorData object at 0x13fb8d4d0>)</span></div></details></details></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys']\"><b>ophys</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['description']\">description:</span> <span class=\"field-value\">No description.</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']\"><b>data_interfaces (8)</b></summary><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['ImageSegmentation']\"><b>ImageSegmentation</b></summary><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']\"><b>plane_segmentations (1)</b></summary><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue']\"><b>PlaneSegmentationProcessedBlue</b></summary><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['description']\">description:</span> <span class=\"field-value\">Segmented ROIs</span></div><details><summary style=\"display: list-item; margin-left: 120px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['id']\"><b>id</b></summary></details><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['colnames']\">colnames:</span> <span class=\"field-value\">('image_mask', 'ROICentroids', 'Accepted', 'Rejected', 'location')</span></div><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['columns']\">columns:</span> <span class=\"field-value\">(<hdmf.common.table.VectorData object at 0x13f21c2d0>, <hdmf.common.table.VectorData object at 0x13f21c250>, <hdmf.common.table.VectorData object at 0x13f21eb90>, <hdmf.common.table.VectorData object at 0x13f21f510>, <hdmf.common.table.VectorData object at 0x13f21f590>)</span></div><details><summary style=\"display: list-item; margin-left: 120px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane']\"><b>imaging_plane</b></summary><details><summary style=\"display: list-item; margin-left: 140px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['optical_channel']\"><b>optical_channel</b></summary><div style=\"margin-left: 160px;\" class=\"container-fields\"><span class=\"field-value\" title=\".fields['processing']['ophys'].fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['optical_channel'][0]\">OpticalChannelBlue pynwb.ophys.OpticalChannel at 0x5353898512\n",
+       "Fields:\n",
+       "  description: An optical channel of the microscope.\n",
+       "  emission_lambda: nan\n",
+       "</span></div></details><div style=\"margin-left: 140px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['description']\">description:</span> <span class=\"field-value\">The plane or volume being imaged by the microscope.</span></div><details><summary style=\"display: list-item; margin-left: 140px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['device']\"><b>device</b></summary></details><div style=\"margin-left: 140px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['excitation_lambda']\">excitation_lambda:</span> <span class=\"field-value\">nan</span></div><div style=\"margin-left: 140px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['imaging_rate']\">imaging_rate:</span> <span class=\"field-value\">10.0</span></div><div style=\"margin-left: 140px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['indicator']\">indicator:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 140px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['location']\">location:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 140px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 140px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div></details></details></details></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesBlue']\"><b>MotionCorrectionSeriesBlue</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['description']\">description:</span> <span class=\"field-value\">The x, y shifts for the OnePhotonSeriesBlue imaging data.</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['unit']\">unit:</span> <span class=\"field-value\">px</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesViolet']\"><b>MotionCorrectionSeriesViolet</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['description']\">description:</span> <span class=\"field-value\">The x, y shifts for the OnePhotonSeriesViolet imaging data.</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['unit']\">unit:</span> <span class=\"field-value\">px</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue']\"><b>OnePhotonSeriesProcessedBlue</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['description']\">description:</span> <span class=\"field-value\">Processed imaging data from one-photon excitation microscopy.</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['unit']\">unit:</span> <span class=\"field-value\">n.a.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['dimension']\"><b>dimension</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane']\"><b>imaging_plane</b></summary><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['optical_channel']\"><b>optical_channel</b></summary><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-value\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['optical_channel'][0]\">OpticalChannelBlue pynwb.ophys.OpticalChannel at 0x5353898512\n",
+       "Fields:\n",
+       "  description: An optical channel of the microscope.\n",
+       "  emission_lambda: nan\n",
+       "</span></div></details><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['description']\">description:</span> <span class=\"field-value\">The plane or volume being imaged by the microscope.</span></div><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['device']\"><b>device</b></summary></details><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['excitation_lambda']\">excitation_lambda:</span> <span class=\"field-value\">nan</span></div><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['imaging_rate']\">imaging_rate:</span> <span class=\"field-value\">10.0</span></div><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['indicator']\">indicator:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['location']\">location:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['binning']\">binning:</span> <span class=\"field-value\">64</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet']\"><b>OnePhotonSeriesProcessedViolet</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['description']\">description:</span> <span class=\"field-value\">Processed imaging data from one-photon excitation microscopy.</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['unit']\">unit:</span> <span class=\"field-value\">n.a.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['dimension']\"><b>dimension</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane']\"><b>imaging_plane</b></summary><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['optical_channel']\"><b>optical_channel</b></summary><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-value\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['optical_channel'][0]\">OpticalChannelViolet pynwb.ophys.OpticalChannel at 0x5353908304\n",
+       "Fields:\n",
+       "  description: An optical channel of the microscope.\n",
+       "  emission_lambda: nan\n",
+       "</span></div></details><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['description']\">description:</span> <span class=\"field-value\">The plane or volume being imaged by the microscope.</span></div><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['device']\"><b>device</b></summary></details><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['excitation_lambda']\">excitation_lambda:</span> <span class=\"field-value\">nan</span></div><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['imaging_rate']\">imaging_rate:</span> <span class=\"field-value\">10.0</span></div><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['indicator']\">indicator:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['location']\">location:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['binning']\">binning:</span> <span class=\"field-value\">64</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['SegmentationImages']\"><b>SegmentationImages</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['SegmentationImages'].fields['description']\">description:</span> <span class=\"field-value\">The summary images of the segmentation.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['SegmentationImages'].fields['images']\"><b>images (2)</b></summary><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['SegmentationImages'].fields['images']['pca_blue']\"><b>pca_blue</b></summary></details><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['SegmentationImages'].fields['images']['vasculature']\"><b>vasculature</b></summary></details></details></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['SegmentationImagesBlue']\"><b>SegmentationImagesBlue</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['SegmentationImagesBlue'].fields['description']\">description:</span> <span class=\"field-value\">Contains the manual mask and the contrast based vasculature mask for the blue channel in the full size session image.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['SegmentationImagesBlue'].fields['images']\"><b>images (2)</b></summary><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['SegmentationImagesBlue'].fields['images']['manual']\"><b>manual</b></summary></details><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['SegmentationImagesBlue'].fields['images']['vasculature']\"><b>vasculature</b></summary></details></details></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['SegmentationImagesProcessedViolet']\"><b>SegmentationImagesProcessedViolet</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['SegmentationImagesProcessedViolet'].fields['description']\">description:</span> <span class=\"field-value\">Contains the PCA mask for the violet channel on the binned session image.</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['SegmentationImagesProcessedViolet'].fields['images']\"><b>images (1)</b></summary><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['processing']['ophys'].fields['data_interfaces']['SegmentationImagesProcessedViolet'].fields['images']['pca_violet']\"><b>pca_violet</b></summary></details></details></details></details></details></details><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['epoch_tags']\">epoch_tags:</span> <span class=\"field-value\">set()</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['devices']\"><b>devices (1)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['devices']['Microscope']\"><b>Microscope</b></summary></details></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['imaging_planes']\"><b>imaging_planes (2)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['imaging_planes']['ImagingPlaneBlue']\"><b>ImagingPlaneBlue</b></summary><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['imaging_planes']['ImagingPlaneBlue'].fields['optical_channel']\"><b>optical_channel</b></summary><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-value\" title=\".fields['imaging_planes']['ImagingPlaneBlue'].fields['optical_channel'][0]\">OpticalChannelBlue pynwb.ophys.OpticalChannel at 0x5353898512\n",
+       "Fields:\n",
+       "  description: An optical channel of the microscope.\n",
+       "  emission_lambda: nan\n",
+       "</span></div></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_planes']['ImagingPlaneBlue'].fields['description']\">description:</span> <span class=\"field-value\">The plane or volume being imaged by the microscope.</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['imaging_planes']['ImagingPlaneBlue'].fields['device']\"><b>device</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_planes']['ImagingPlaneBlue'].fields['excitation_lambda']\">excitation_lambda:</span> <span class=\"field-value\">nan</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_planes']['ImagingPlaneBlue'].fields['imaging_rate']\">imaging_rate:</span> <span class=\"field-value\">10.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_planes']['ImagingPlaneBlue'].fields['indicator']\">indicator:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_planes']['ImagingPlaneBlue'].fields['location']\">location:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_planes']['ImagingPlaneBlue'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_planes']['ImagingPlaneBlue'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['imaging_planes']['ImagingPlaneViolet']\"><b>ImagingPlaneViolet</b></summary><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['imaging_planes']['ImagingPlaneViolet'].fields['optical_channel']\"><b>optical_channel</b></summary><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-value\" title=\".fields['imaging_planes']['ImagingPlaneViolet'].fields['optical_channel'][0]\">OpticalChannelViolet pynwb.ophys.OpticalChannel at 0x5353908304\n",
+       "Fields:\n",
+       "  description: An optical channel of the microscope.\n",
+       "  emission_lambda: nan\n",
+       "</span></div></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_planes']['ImagingPlaneViolet'].fields['description']\">description:</span> <span class=\"field-value\">The plane or volume being imaged by the microscope.</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['imaging_planes']['ImagingPlaneViolet'].fields['device']\"><b>device</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_planes']['ImagingPlaneViolet'].fields['excitation_lambda']\">excitation_lambda:</span> <span class=\"field-value\">nan</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_planes']['ImagingPlaneViolet'].fields['imaging_rate']\">imaging_rate:</span> <span class=\"field-value\">10.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_planes']['ImagingPlaneViolet'].fields['indicator']\">indicator:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_planes']['ImagingPlaneViolet'].fields['location']\">location:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_planes']['ImagingPlaneViolet'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_planes']['ImagingPlaneViolet'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div></details></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['intervals']\"><b>intervals (1)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['intervals']['trials']\"><b>trials</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['intervals']['trials'].fields['description']\">description:</span> <span class=\"field-value\">experimental trials</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['intervals']['trials'].fields['id']\"><b>id</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['intervals']['trials'].fields['colnames']\">colnames:</span> <span class=\"field-value\">('start_time', 'stop_time', 'InterTrial', 'SetupTrial', 'InitializeTrial', 'WithinTrial', 'WithinContext', 'WithinCue', 'WithinDelay', 'WithinArms', 'ChoiceMade', 'DuringReward', 'trial_type', 'choice', 'stimulus_type', 'antitrial', 'duration', 'visibleAt', 'probability', 'densityPerM', 'nCueSlots', 'minSeparation', 'lCue', 'meanCount', 'meanSalient', 'meanDistract', 'ProbR', 'ProbStim2', 'salientVisible', 'distractVisible', 'salientInRange', 'distractInRange', 'salientBeenOn', 'distractBeenOn', 'salientTime', 'distractTime', 'nSalient', 'nDistract', 'posSalient', 'posDistract', 'startIdx', 'mazeID', 'mainMazeID', 'distanceTraveled', 'excessTravel', 'rewardFactor', 'reward')</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['intervals']['trials'].fields['columns']\">columns:</span> <span class=\"field-value\">(<hdmf.common.table.VectorData object at 0x13f10ae50>, <hdmf.common.table.VectorData object at 0x13f109e10>, <hdmf.common.table.VectorData object at 0x13f1098d0>, <hdmf.common.table.VectorData object at 0x13f10bf10>, <hdmf.common.table.VectorData object at 0x13f108ad0>, <hdmf.common.table.VectorData object at 0x13f108350>, <hdmf.common.table.VectorData object at 0x13f108990>, <hdmf.common.table.VectorData object at 0x13f10a010>, <hdmf.common.table.VectorData object at 0x13f108150>, <hdmf.common.table.VectorData object at 0x13f10b690>, <hdmf.common.table.VectorData object at 0x13f10aa50>, <hdmf.common.table.VectorData object at 0x13f108210>, <hdmf.common.table.VectorData object at 0x13f18d7d0>, <hdmf.common.table.VectorData object at 0x13f109490>, <hdmf.common.table.VectorData object at 0x13f18d010>, <hdmf.common.table.VectorData object at 0x13f109990>, <hdmf.common.table.VectorData object at 0x13f0dbe90>, <hdmf.common.table.VectorData object at 0x13f18c9d0>, <hdmf.common.table.VectorData object at 0x13fef8710>, <hdmf.common.table.VectorData object at 0x13f109fd0>, <hdmf.common.table.VectorData object at 0x13fefabd0>, <hdmf.common.table.VectorData object at 0x13fef9550>, <hdmf.common.table.VectorData object at 0x13f0db3d0>, <hdmf.common.table.VectorData object at 0x13fefa4d0>, <hdmf.common.table.VectorData object at 0x13fefa390>, <hdmf.common.table.VectorData object at 0x13fef94d0>, <hdmf.common.table.VectorData object at 0x13f109710>, <hdmf.common.table.VectorData object at 0x13f108950>, <hdmf.common.table.VectorIndex object at 0x13fefbd10>, <hdmf.common.table.VectorData object at 0x13fef9590>, <hdmf.common.table.VectorIndex object at 0x13f0d84d0>, <hdmf.common.table.VectorData object at 0x13f0d85d0>, <hdmf.common.table.VectorIndex object at 0x13fefb210>, <hdmf.common.table.VectorData object at 0x13fefb690>, <hdmf.common.table.VectorIndex object at 0x13f0db990>, <hdmf.common.table.VectorData object at 0x13f0db390>, <hdmf.common.table.VectorIndex object at 0x13fefb4d0>, <hdmf.common.table.VectorData object at 0x13fef9390>, <hdmf.common.table.VectorIndex object at 0x13f0db2d0>, <hdmf.common.table.VectorData object at 0x13f0d95d0>, <hdmf.common.table.VectorIndex object at 0x13fef9290>, <hdmf.common.table.VectorData object at 0x13fef8510>, <hdmf.common.table.VectorIndex object at 0x13f0dac50>, <hdmf.common.table.VectorData object at 0x13f0da590>, <hdmf.common.table.VectorData object at 0x13fef85d0>, <hdmf.common.table.VectorData object at 0x13fefb0d0>, <hdmf.common.table.VectorIndex object at 0x13fef9ed0>, <hdmf.common.table.VectorData object at 0x13fef8990>, <hdmf.common.table.VectorIndex object at 0x13fef9710>, <hdmf.common.table.VectorData object at 0x13fef8a50>, <hdmf.common.table.VectorData object at 0x13f18ddd0>, <hdmf.common.table.VectorData object at 0x13fef89d0>, <hdmf.common.table.VectorData object at 0x13f0d9510>, <hdmf.common.table.VectorData object at 0x13f0d9910>, <hdmf.common.table.VectorData object at 0x13f0d9c90>, <hdmf.common.table.VectorData object at 0x13fef93d0>, <hdmf.common.table.VectorData object at 0x13fefb410>)</span></div></details></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['subject']\"><b>subject</b></summary><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject'].fields['age__reference']\">age__reference:</span> <span class=\"field-value\">birth</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject'].fields['genotype']\">genotype:</span> <span class=\"field-value\">ChAT-Ai96</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject'].fields['sex']\">sex:</span> <span class=\"field-value\">M</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject'].fields['species']\">species:</span> <span class=\"field-value\">Mus musculus</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject'].fields['subject_id']\">subject_id:</span> <span class=\"field-value\">DrChicken</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject'].fields['date_of_birth']\">date_of_birth:</span> <span class=\"field-value\">2022-12-10 00:00:00-08:00</span></div></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['lab_meta_data']\"><b>lab_meta_data (1)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['lab_meta_data']['LabMetaData']\"><b>LabMetaData</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['experiment_name']\">experiment_name:</span> <span class=\"field-value\">TowersTaskSwitchEasy</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['experiment_code']\">experiment_code:</span> <span class=\"field-value\">TowersTaskSwitchEasy</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['session_index']\">session_index:</span> <span class=\"field-value\">41</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['total_reward']\">total_reward:</span> <span class=\"field-value\">1.6560000000000012</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['rig']\">rig:</span> <span class=\"field-value\">VR_Widefield</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['num_trials']\">num_trials:</span> <span class=\"field-value\">336</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['num_iterations']\">num_iterations:</span> <span class=\"field-value\">407877</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['session_duration']\">session_duration:</span> <span class=\"field-value\">3754.9149446</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['advance']\">advance:</span> <span class=\"field-value\">0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['surface_quality']\">surface_quality:</span> <span class=\"field-value\">70.18</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['mazes']\"><b>mazes</b></summary><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['mazes'].fields['description']\">description:</span> <span class=\"field-value\">The parameters for the mazes in TowersTaskSwitchEasy.</span></div><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['mazes'].fields['id']\"><b>id</b></summary></details><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['mazes'].fields['colnames']\">colnames:</span> <span class=\"field-value\">('lStart', 'lCue', 'lMemory', 'lContext', 'turnHint', 'hideHintUntil', 'cueDuration', 'cueVisibleAt', 'cueProbability', 'cueDensityPerM', 'antiFraction', 'maxTrialDuration', 'blockPerform', 'criteriaNTrials', 'easyBlock', 'easyBlockNTrials', 'geoDistP', 'geoDistPEasy', 'maxBias', 'nTrialRange', 'nTrialRangeEasy', 'numBlockTrials', 'numSessions', 'numTrials', 'numTrialsPerMin', 'performance', 'warmupBias', 'warmupMaxNTrials', 'warmupMaze', 'warmupMotor', 'warmupNTrials', 'warmupPerform')</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['mazes'].fields['columns']\">columns:</span> <span class=\"field-value\">(<hdmf.common.table.VectorData object at 0x14c354750>, <hdmf.common.table.VectorData object at 0x14c354dd0>, <hdmf.common.table.VectorData object at 0x14c356710>, <hdmf.common.table.VectorData object at 0x14c355fd0>, <hdmf.common.table.VectorData object at 0x13f109a10>, <hdmf.common.table.VectorData object at 0x14c357f10>, <hdmf.common.table.VectorData object at 0x14c355a10>, <hdmf.common.table.VectorData object at 0x14c357cd0>, <hdmf.common.table.VectorData object at 0x14c355ad0>, <hdmf.common.table.VectorData object at 0x14c354110>, <hdmf.common.table.VectorData object at 0x14c355b10>, <hdmf.common.table.VectorData object at 0x14c3578d0>, <hdmf.common.table.VectorData object at 0x14c3553d0>, <hdmf.common.table.VectorData object at 0x14c356e10>, <hdmf.common.table.VectorData object at 0x14c355bd0>, <hdmf.common.table.VectorData object at 0x14c356590>, <hdmf.common.table.VectorData object at 0x14c355d50>, <hdmf.common.table.VectorData object at 0x14c356d10>, <hdmf.common.table.VectorData object at 0x14c3577d0>, <hdmf.common.table.VectorIndex object at 0x14c357190>, <hdmf.common.table.VectorData object at 0x14c357910>, <hdmf.common.table.VectorIndex object at 0x14c355190>, <hdmf.common.table.VectorData object at 0x14c354510>, <hdmf.common.table.VectorData object at 0x14c356510>, <hdmf.common.table.VectorData object at 0x14c357210>, <hdmf.common.table.VectorData object at 0x14c3556d0>, <hdmf.common.table.VectorData object at 0x14c354d90>, <hdmf.common.table.VectorData object at 0x13f109ad0>, <hdmf.common.table.VectorIndex object at 0x13f1094d0>, <hdmf.common.table.VectorData object at 0x13f10b190>, <hdmf.common.table.VectorIndex object at 0x13f10bed0>, <hdmf.common.table.VectorData object at 0x13f10b790>, <hdmf.common.table.VectorIndex object at 0x13f10ad90>, <hdmf.common.table.VectorData object at 0x13f108f90>, <hdmf.common.table.VectorIndex object at 0x13f10a5d0>, <hdmf.common.table.VectorData object at 0x13f109a50>, <hdmf.common.table.VectorIndex object at 0x13f10b0d0>, <hdmf.common.table.VectorData object at 0x13f108c10>, <hdmf.common.table.VectorIndex object at 0x13f108c90>, <hdmf.common.table.VectorData object at 0x13f10b350>)</span></div></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['stimulus_protocol']\"><b>stimulus_protocol</b></summary><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['stimulus_protocol'].fields['description']\">description:</span> <span class=\"field-value\">Holds information about the stimulus protocol.</span></div><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['stimulus_protocol'].fields['id']\"><b>id</b></summary></details><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['stimulus_protocol'].fields['colnames']\">colnames:</span> <span class=\"field-value\">('numMazesInProtocol', 'trialDraw', 'stimDraw', 'cueMinSeparation', 'totalRepeatProbability', 'numRepeatTrials', 'visualcolor', 'memorycolor', 'princetonImplementation', 'stimulus_code')</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['lab_meta_data']['LabMetaData'].fields['stimulus_protocol'].fields['columns']\">columns:</span> <span class=\"field-value\">(<hdmf.common.table.VectorData object at 0x14c356c50>, <hdmf.common.table.VectorData object at 0x14c3566d0>, <hdmf.common.table.VectorData object at 0x14c3544d0>, <hdmf.common.table.VectorData object at 0x13fb9c490>, <hdmf.common.table.VectorData object at 0x14c357790>, <hdmf.common.table.VectorData object at 0x14c355010>, <hdmf.common.table.VectorData object at 0x14c3551d0>, <hdmf.common.table.VectorData object at 0x13fb9c350>, <hdmf.common.table.VectorData object at 0x14c357750>, <hdmf.common.table.VectorData object at 0x14c357d90>)</span></div></details></details></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['trials']\"><b>trials</b></summary><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['trials'].fields['description']\">description:</span> <span class=\"field-value\">experimental trials</span></div><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['trials'].fields['id']\"><b>id</b></summary></details><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['trials'].fields['colnames']\">colnames:</span> <span class=\"field-value\">('start_time', 'stop_time', 'InterTrial', 'SetupTrial', 'InitializeTrial', 'WithinTrial', 'WithinContext', 'WithinCue', 'WithinDelay', 'WithinArms', 'ChoiceMade', 'DuringReward', 'trial_type', 'choice', 'stimulus_type', 'antitrial', 'duration', 'visibleAt', 'probability', 'densityPerM', 'nCueSlots', 'minSeparation', 'lCue', 'meanCount', 'meanSalient', 'meanDistract', 'ProbR', 'ProbStim2', 'salientVisible', 'distractVisible', 'salientInRange', 'distractInRange', 'salientBeenOn', 'distractBeenOn', 'salientTime', 'distractTime', 'nSalient', 'nDistract', 'posSalient', 'posDistract', 'startIdx', 'mazeID', 'mainMazeID', 'distanceTraveled', 'excessTravel', 'rewardFactor', 'reward')</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['trials'].fields['columns']\">columns:</span> <span class=\"field-value\">(<hdmf.common.table.VectorData object at 0x13f10ae50>, <hdmf.common.table.VectorData object at 0x13f109e10>, <hdmf.common.table.VectorData object at 0x13f1098d0>, <hdmf.common.table.VectorData object at 0x13f10bf10>, <hdmf.common.table.VectorData object at 0x13f108ad0>, <hdmf.common.table.VectorData object at 0x13f108350>, <hdmf.common.table.VectorData object at 0x13f108990>, <hdmf.common.table.VectorData object at 0x13f10a010>, <hdmf.common.table.VectorData object at 0x13f108150>, <hdmf.common.table.VectorData object at 0x13f10b690>, <hdmf.common.table.VectorData object at 0x13f10aa50>, <hdmf.common.table.VectorData object at 0x13f108210>, <hdmf.common.table.VectorData object at 0x13f18d7d0>, <hdmf.common.table.VectorData object at 0x13f109490>, <hdmf.common.table.VectorData object at 0x13f18d010>, <hdmf.common.table.VectorData object at 0x13f109990>, <hdmf.common.table.VectorData object at 0x13f0dbe90>, <hdmf.common.table.VectorData object at 0x13f18c9d0>, <hdmf.common.table.VectorData object at 0x13fef8710>, <hdmf.common.table.VectorData object at 0x13f109fd0>, <hdmf.common.table.VectorData object at 0x13fefabd0>, <hdmf.common.table.VectorData object at 0x13fef9550>, <hdmf.common.table.VectorData object at 0x13f0db3d0>, <hdmf.common.table.VectorData object at 0x13fefa4d0>, <hdmf.common.table.VectorData object at 0x13fefa390>, <hdmf.common.table.VectorData object at 0x13fef94d0>, <hdmf.common.table.VectorData object at 0x13f109710>, <hdmf.common.table.VectorData object at 0x13f108950>, <hdmf.common.table.VectorIndex object at 0x13fefbd10>, <hdmf.common.table.VectorData object at 0x13fef9590>, <hdmf.common.table.VectorIndex object at 0x13f0d84d0>, <hdmf.common.table.VectorData object at 0x13f0d85d0>, <hdmf.common.table.VectorIndex object at 0x13fefb210>, <hdmf.common.table.VectorData object at 0x13fefb690>, <hdmf.common.table.VectorIndex object at 0x13f0db990>, <hdmf.common.table.VectorData object at 0x13f0db390>, <hdmf.common.table.VectorIndex object at 0x13fefb4d0>, <hdmf.common.table.VectorData object at 0x13fef9390>, <hdmf.common.table.VectorIndex object at 0x13f0db2d0>, <hdmf.common.table.VectorData object at 0x13f0d95d0>, <hdmf.common.table.VectorIndex object at 0x13fef9290>, <hdmf.common.table.VectorData object at 0x13fef8510>, <hdmf.common.table.VectorIndex object at 0x13f0dac50>, <hdmf.common.table.VectorData object at 0x13f0da590>, <hdmf.common.table.VectorData object at 0x13fef85d0>, <hdmf.common.table.VectorData object at 0x13fefb0d0>, <hdmf.common.table.VectorIndex object at 0x13fef9ed0>, <hdmf.common.table.VectorData object at 0x13fef8990>, <hdmf.common.table.VectorIndex object at 0x13fef9710>, <hdmf.common.table.VectorData object at 0x13fef8a50>, <hdmf.common.table.VectorData object at 0x13f18ddd0>, <hdmf.common.table.VectorData object at 0x13fef89d0>, <hdmf.common.table.VectorData object at 0x13f0d9510>, <hdmf.common.table.VectorData object at 0x13f0d9910>, <hdmf.common.table.VectorData object at 0x13f0d9c90>, <hdmf.common.table.VectorData object at 0x13fef93d0>, <hdmf.common.table.VectorData object at 0x13fefb410>)</span></div></details><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['session_id']\">session_id:</span> <span class=\"field-value\">20230419-20hz</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['lab']\">lab:</span> <span class=\"field-value\">Pinto</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['institution']\">institution:</span> <span class=\"field-value\">Northwestern University</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['protocol']\">protocol:</span> <span class=\"field-value\">IS00016447</span></div></div>"
+      ],
+      "text/plain": [
+       "root pynwb.file.NWBFile at 0x5366782288\n",
+       "Fields:\n",
+       "  acquisition: {\n",
+       "    OnePhotonSeriesBlue <class 'pynwb.ophys.OnePhotonSeries'>,\n",
+       "    OnePhotonSeriesViolet <class 'pynwb.ophys.OnePhotonSeries'>\n",
+       "  }\n",
+       "  devices: {\n",
+       "    Microscope <class 'pynwb.device.Device'>\n",
+       "  }\n",
+       "  experimenter: ['Luo, Jiaqi']\n",
+       "  file_create_date: [datetime.datetime(2023, 11, 30, 15, 52, 45, 875965, tzinfo=tzoffset(None, 3600))]\n",
+       "  identifier: 35b7de81-5636-47d8-8bb2-6ce5db2af37e\n",
+       "  imaging_planes: {\n",
+       "    ImagingPlaneBlue <class 'pynwb.ophys.ImagingPlane'>,\n",
+       "    ImagingPlaneViolet <class 'pynwb.ophys.ImagingPlane'>\n",
+       "  }\n",
+       "  institution: Northwestern University\n",
+       "  intervals: {\n",
+       "    trials <class 'pynwb.epoch.TimeIntervals'>\n",
+       "  }\n",
+       "  lab: Pinto\n",
+       "  lab_meta_data: {\n",
+       "    LabMetaData <class 'abc.LabMetaDataExtension'>\n",
+       "  }\n",
+       "  processing: {\n",
+       "    behavior <class 'pynwb.base.ProcessingModule'>,\n",
+       "    ophys <class 'pynwb.base.ProcessingModule'>\n",
+       "  }\n",
+       "  protocol: IS00016447\n",
+       "  session_description: A rich text description of the experiment. Can also just be the abstract of the publication.\n",
+       "  session_id: 20230419-20hz\n",
+       "  session_start_time: 2023-04-19 10:57:31.591000-07:00\n",
+       "  subject: subject pynwb.file.Subject at 0x5573526416\n",
+       "Fields:\n",
+       "  age__reference: birth\n",
+       "  date_of_birth: 2022-12-10 00:00:00-08:00\n",
+       "  genotype: ChAT-Ai96\n",
+       "  sex: M\n",
+       "  species: Mus musculus\n",
+       "  subject_id: DrChicken\n",
+       "\n",
+       "  timestamps_reference_time: 2023-04-19 10:57:31.591000-07:00\n",
+       "  trials: trials <class 'pynwb.epoch.TimeIntervals'>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from pynwb import NWBHDF5IO\n",
+    "\n",
+    "# The file path to a .nwb file\n",
+    "nwbfile_path = \"/Users/weian/data/210944/sub-DrChicken/sub-DrChicken_ses-20230419-20hz_behavior+ophys.nwb\"\n",
+    "io = NWBHDF5IO(path=nwbfile_path, mode=\"r\", load_namespaces=True)\n",
+    "nwbfile = io.read()\n",
+    "\n",
+    "nwbfile"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8d247090-5cfb-47b1-a1a4-8a7c87921a38",
+   "metadata": {},
+   "source": [
+    "# Access subject and task related metadata <a name=\"access-subject\"></a>\n",
+    "\n",
+    "## Access subject metadata\n",
+    "\n",
+    "This section demonstrates how to access the [Subject](https://pynwb.readthedocs.io/en/stable/pynwb.file.html#pynwb.file.Subject) field in an NWB file.\n",
+    "\n",
+    "The [Subject](https://pynwb.readthedocs.io/en/stable/pynwb.file.html#pynwb.file.Subject) field can be accessed as `nwbfile.subject`.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "483b9a74-c5f0-4f59-b422-1a3a7a9c5002",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <style>\n",
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+       "                font-family: \"Open Sans\", Arial, sans-serif;\n",
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+       "            .container-fields .field-value {\n",
+       "                color: #00788E;\n",
+       "            }\n",
+       "            .container-fields details > summary {\n",
+       "                cursor: pointer;\n",
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+       "            .container-fields details > summary:hover {\n",
+       "                color: #0A6EAA;\n",
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+       "        </style>\n",
+       "        \n",
+       "        <script>\n",
+       "            function copyToClipboard(text) {\n",
+       "                navigator.clipboard.writeText(text).then(function() {\n",
+       "                    console.log('Copied to clipboard: ' + text);\n",
+       "                }, function(err) {\n",
+       "                    console.error('Could not copy text: ', err);\n",
+       "                });\n",
+       "            }\n",
+       "\n",
+       "            document.addEventListener('DOMContentLoaded', function() {\n",
+       "                let fieldKeys = document.querySelectorAll('.container-fields .field-key');\n",
+       "                fieldKeys.forEach(function(fieldKey) {\n",
+       "                    fieldKey.addEventListener('click', function() {\n",
+       "                        let accessCode = fieldKey.getAttribute('title').replace('Access code: ', '');\n",
+       "                        copyToClipboard(accessCode);\n",
+       "                    });\n",
+       "                });\n",
+       "            });\n",
+       "        </script>\n",
+       "        <div class='container-wrap'><div class='container-header'><div class='xr-obj-type'><h3>subject (Subject)</h3></div></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['age__reference']\">age__reference:</span> <span class=\"field-value\">birth</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['genotype']\">genotype:</span> <span class=\"field-value\">ChAT-Ai96</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['sex']\">sex:</span> <span class=\"field-value\">M</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['species']\">species:</span> <span class=\"field-value\">Mus musculus</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['subject_id']\">subject_id:</span> <span class=\"field-value\">DrChicken</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['date_of_birth']\">date_of_birth:</span> <span class=\"field-value\">2022-12-10 00:00:00-08:00</span></div></div>"
+      ],
+      "text/plain": [
+       "subject pynwb.file.Subject at 0x5573526416\n",
+       "Fields:\n",
+       "  age__reference: birth\n",
+       "  date_of_birth: 2022-12-10 00:00:00-08:00\n",
+       "  genotype: ChAT-Ai96\n",
+       "  sex: M\n",
+       "  species: Mus musculus\n",
+       "  subject_id: DrChicken"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nwbfile.subject"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "47277bac-d8a0-4ce0-a20b-79721eac0e7a",
+   "metadata": {},
+   "source": [
+    "## Access ViRMEN experimental metadata (mazes table, stimulus protocol parameters)\n",
+    "\n",
+    "This section demonstrates how to access the task related metadata in an NWB file.\n",
+    "\n",
+    "The ViRMEN experimental metadata is stored in a [LabMetaData](https://pynwb.readthedocs.io/en/stable/pynwb.file.html#pynwb.file.LabMetaData) extension ([ndx-pinto-metadata](https://github.com/catalystneuro/ndx-pinto-metadata)). \n",
+    "\n",
+    "The LabMetaData](https://pynwb.readthedocs.io/en/stable/pynwb.file.html#pynwb.file.LabMetaData) object can be accessed as `nwbfile.lab_meta_data[\"LabMetaData\"]`.\n",
+    "\n",
+    "The parameters for the mazes is added to the `mazes` table within `nwbfile.lab_meta_data[\"LabMetaData\"]` which can be accessed as `nwbfile.lab_meta_data[\"LabMetaData\"].mazes`. \n",
+    "\n",
+    "Data arrays are read passively from the file. Accessing the data attribute of the `mazes` object does not read the data values, but presents an HDF5 object that can be indexed to read data. You can use the [:] operator to read the entire data array into memory as `nwbfile.lab_meta_data[\"LabMetaData\"].mazes[:]`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "07caff60-9c9e-4963-936a-0222ad597d4b",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <style>\n",
+       "            .container-fields {\n",
+       "                font-family: \"Open Sans\", Arial, sans-serif;\n",
+       "            }\n",
+       "            .container-fields .field-value {\n",
+       "                color: #00788E;\n",
+       "            }\n",
+       "            .container-fields details > summary {\n",
+       "                cursor: pointer;\n",
+       "                display: list-item;\n",
+       "            }\n",
+       "            .container-fields details > summary:hover {\n",
+       "                color: #0A6EAA;\n",
+       "            }\n",
+       "        </style>\n",
+       "        \n",
+       "        <script>\n",
+       "            function copyToClipboard(text) {\n",
+       "                navigator.clipboard.writeText(text).then(function() {\n",
+       "                    console.log('Copied to clipboard: ' + text);\n",
+       "                }, function(err) {\n",
+       "                    console.error('Could not copy text: ', err);\n",
+       "                });\n",
+       "            }\n",
+       "\n",
+       "            document.addEventListener('DOMContentLoaded', function() {\n",
+       "                let fieldKeys = document.querySelectorAll('.container-fields .field-key');\n",
+       "                fieldKeys.forEach(function(fieldKey) {\n",
+       "                    fieldKey.addEventListener('click', function() {\n",
+       "                        let accessCode = fieldKey.getAttribute('title').replace('Access code: ', '');\n",
+       "                        copyToClipboard(accessCode);\n",
+       "                    });\n",
+       "                });\n",
+       "            });\n",
+       "        </script>\n",
+       "        <div class='container-wrap'><div class='container-header'><div class='xr-obj-type'><h3>LabMetaData (LabMetaDataExtension)</h3></div></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['experiment_name']\">experiment_name:</span> <span class=\"field-value\">TowersTaskSwitchEasy</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['experiment_code']\">experiment_code:</span> <span class=\"field-value\">TowersTaskSwitchEasy</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['session_index']\">session_index:</span> <span class=\"field-value\">41</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['total_reward']\">total_reward:</span> <span class=\"field-value\">1.6560000000000012</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['rig']\">rig:</span> <span class=\"field-value\">VR_Widefield</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['num_trials']\">num_trials:</span> <span class=\"field-value\">336</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['num_iterations']\">num_iterations:</span> <span class=\"field-value\">407877</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['session_duration']\">session_duration:</span> <span class=\"field-value\">3754.9149446</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['advance']\">advance:</span> <span class=\"field-value\">0</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['surface_quality']\">surface_quality:</span> <span class=\"field-value\">70.18</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['mazes']\"><b>mazes</b></summary><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['mazes'].fields['description']\">description:</span> <span class=\"field-value\">The parameters for the mazes in TowersTaskSwitchEasy.</span></div><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['mazes'].fields['id']\"><b>id</b></summary></details><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['mazes'].fields['colnames']\">colnames:</span> <span class=\"field-value\">('lStart', 'lCue', 'lMemory', 'lContext', 'turnHint', 'hideHintUntil', 'cueDuration', 'cueVisibleAt', 'cueProbability', 'cueDensityPerM', 'antiFraction', 'maxTrialDuration', 'blockPerform', 'criteriaNTrials', 'easyBlock', 'easyBlockNTrials', 'geoDistP', 'geoDistPEasy', 'maxBias', 'nTrialRange', 'nTrialRangeEasy', 'numBlockTrials', 'numSessions', 'numTrials', 'numTrialsPerMin', 'performance', 'warmupBias', 'warmupMaxNTrials', 'warmupMaze', 'warmupMotor', 'warmupNTrials', 'warmupPerform')</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['mazes'].fields['columns']\">columns:</span> <span class=\"field-value\">(<hdmf.common.table.VectorData object at 0x14c354750>, <hdmf.common.table.VectorData object at 0x14c354dd0>, <hdmf.common.table.VectorData object at 0x14c356710>, <hdmf.common.table.VectorData object at 0x14c355fd0>, <hdmf.common.table.VectorData object at 0x13f109a10>, <hdmf.common.table.VectorData object at 0x14c357f10>, <hdmf.common.table.VectorData object at 0x14c355a10>, <hdmf.common.table.VectorData object at 0x14c357cd0>, <hdmf.common.table.VectorData object at 0x14c355ad0>, <hdmf.common.table.VectorData object at 0x14c354110>, <hdmf.common.table.VectorData object at 0x14c355b10>, <hdmf.common.table.VectorData object at 0x14c3578d0>, <hdmf.common.table.VectorData object at 0x14c3553d0>, <hdmf.common.table.VectorData object at 0x14c356e10>, <hdmf.common.table.VectorData object at 0x14c355bd0>, <hdmf.common.table.VectorData object at 0x14c356590>, <hdmf.common.table.VectorData object at 0x14c355d50>, <hdmf.common.table.VectorData object at 0x14c356d10>, <hdmf.common.table.VectorData object at 0x14c3577d0>, <hdmf.common.table.VectorIndex object at 0x14c357190>, <hdmf.common.table.VectorData object at 0x14c357910>, <hdmf.common.table.VectorIndex object at 0x14c355190>, <hdmf.common.table.VectorData object at 0x14c354510>, <hdmf.common.table.VectorData object at 0x14c356510>, <hdmf.common.table.VectorData object at 0x14c357210>, <hdmf.common.table.VectorData object at 0x14c3556d0>, <hdmf.common.table.VectorData object at 0x14c354d90>, <hdmf.common.table.VectorData object at 0x13f109ad0>, <hdmf.common.table.VectorIndex object at 0x13f1094d0>, <hdmf.common.table.VectorData object at 0x13f10b190>, <hdmf.common.table.VectorIndex object at 0x13f10bed0>, <hdmf.common.table.VectorData object at 0x13f10b790>, <hdmf.common.table.VectorIndex object at 0x13f10ad90>, <hdmf.common.table.VectorData object at 0x13f108f90>, <hdmf.common.table.VectorIndex object at 0x13f10a5d0>, <hdmf.common.table.VectorData object at 0x13f109a50>, <hdmf.common.table.VectorIndex object at 0x13f10b0d0>, <hdmf.common.table.VectorData object at 0x13f108c10>, <hdmf.common.table.VectorIndex object at 0x13f108c90>, <hdmf.common.table.VectorData object at 0x13f10b350>)</span></div></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['stimulus_protocol']\"><b>stimulus_protocol</b></summary><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['stimulus_protocol'].fields['description']\">description:</span> <span class=\"field-value\">Holds information about the stimulus protocol.</span></div><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['stimulus_protocol'].fields['id']\"><b>id</b></summary></details><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['stimulus_protocol'].fields['colnames']\">colnames:</span> <span class=\"field-value\">('numMazesInProtocol', 'trialDraw', 'stimDraw', 'cueMinSeparation', 'totalRepeatProbability', 'numRepeatTrials', 'visualcolor', 'memorycolor', 'princetonImplementation', 'stimulus_code')</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['stimulus_protocol'].fields['columns']\">columns:</span> <span class=\"field-value\">(<hdmf.common.table.VectorData object at 0x14c356c50>, <hdmf.common.table.VectorData object at 0x14c3566d0>, <hdmf.common.table.VectorData object at 0x14c3544d0>, <hdmf.common.table.VectorData object at 0x13fb9c490>, <hdmf.common.table.VectorData object at 0x14c357790>, <hdmf.common.table.VectorData object at 0x14c355010>, <hdmf.common.table.VectorData object at 0x14c3551d0>, <hdmf.common.table.VectorData object at 0x13fb9c350>, <hdmf.common.table.VectorData object at 0x14c357750>, <hdmf.common.table.VectorData object at 0x14c357d90>)</span></div></details></div>"
+      ],
+      "text/plain": [
+       "LabMetaData abc.LabMetaDataExtension at 0x5354296080\n",
+       "Fields:\n",
+       "  advance: 0\n",
+       "  experiment_code: TowersTaskSwitchEasy\n",
+       "  experiment_name: TowersTaskSwitchEasy\n",
+       "  mazes: mazes <class 'abc.MazeExtension'>\n",
+       "  num_iterations: 407877\n",
+       "  num_trials: 336\n",
+       "  rig: VR_Widefield\n",
+       "  session_duration: 3754.9149446\n",
+       "  session_index: 41\n",
+       "  stimulus_protocol: stimulus_protocol <class 'hdmf.common.table.DynamicTable'>\n",
+       "  surface_quality: 70.18\n",
+       "  total_reward: 1.6560000000000012"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nwbfile.lab_meta_data[\"LabMetaData\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "09d880cd-ef57-454e-85d4-5cc3df1ce3f1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>lStart</th>\n",
+       "      <th>lCue</th>\n",
+       "      <th>lMemory</th>\n",
+       "      <th>lContext</th>\n",
+       "      <th>turnHint</th>\n",
+       "      <th>hideHintUntil</th>\n",
+       "      <th>cueDuration</th>\n",
+       "      <th>cueVisibleAt</th>\n",
+       "      <th>cueProbability</th>\n",
+       "      <th>cueDensityPerM</th>\n",
+       "      <th>...</th>\n",
+       "      <th>numSessions</th>\n",
+       "      <th>numTrials</th>\n",
+       "      <th>numTrialsPerMin</th>\n",
+       "      <th>performance</th>\n",
+       "      <th>warmupBias</th>\n",
+       "      <th>warmupMaxNTrials</th>\n",
+       "      <th>warmupMaze</th>\n",
+       "      <th>warmupMotor</th>\n",
+       "      <th>warmupNTrials</th>\n",
+       "      <th>warmupPerform</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>id</th>\n",
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+       "      <td>3</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>30</td>\n",
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+       "      <td>20</td>\n",
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+       "      <td>0.60</td>\n",
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+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
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+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>30</td>\n",
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+       "      <td>[30.0]</td>\n",
+       "      <td>[0.8]</td>\n",
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+       "      <th>5</th>\n",
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+       "      <td>190</td>\n",
+       "      <td>60</td>\n",
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+       "      <td>...</td>\n",
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+       "      <td>80</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.80</td>\n",
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+       "      <td>[0.0]</td>\n",
+       "      <td>[30.0]</td>\n",
+       "      <td>[0.8]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>30</td>\n",
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+       "      <td>...</td>\n",
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+       "      <td>[4.0]</td>\n",
+       "      <td>[0.0]</td>\n",
+       "      <td>[30.0]</td>\n",
+       "      <td>[0.8]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>30</td>\n",
+       "      <td>150</td>\n",
+       "      <td>100</td>\n",
+       "      <td>50</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10</td>\n",
+       "      <td>2.5</td>\n",
+       "      <td>4</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>80</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.75</td>\n",
+       "      <td>[0.1, 0.1]</td>\n",
+       "      <td>[20.0, 30.0]</td>\n",
+       "      <td>[4.0, 7.0]</td>\n",
+       "      <td>[0.75, 0.75]</td>\n",
+       "      <td>[10.0, 15.0]</td>\n",
+       "      <td>[0.85, 0.8]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>30</td>\n",
+       "      <td>150</td>\n",
+       "      <td>100</td>\n",
+       "      <td>50</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>4</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>80</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.70</td>\n",
+       "      <td>[0.1]</td>\n",
+       "      <td>[20.0]</td>\n",
+       "      <td>[4.0]</td>\n",
+       "      <td>[0.75]</td>\n",
+       "      <td>[10.0]</td>\n",
+       "      <td>[0.85]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>30</td>\n",
+       "      <td>150</td>\n",
+       "      <td>100</td>\n",
+       "      <td>50</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>4</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>80</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.70</td>\n",
+       "      <td>[0.1]</td>\n",
+       "      <td>[20.0]</td>\n",
+       "      <td>[4.0]</td>\n",
+       "      <td>[0.75]</td>\n",
+       "      <td>[10.0]</td>\n",
+       "      <td>[0.85]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>30</td>\n",
+       "      <td>150</td>\n",
+       "      <td>100</td>\n",
+       "      <td>50</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1.2</td>\n",
+       "      <td>4</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>80</td>\n",
+       "      <td>2</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>[0.1]</td>\n",
+       "      <td>[20.0]</td>\n",
+       "      <td>[13.0]</td>\n",
+       "      <td>[0.75]</td>\n",
+       "      <td>[10.0]</td>\n",
+       "      <td>[0.85]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>30</td>\n",
+       "      <td>150</td>\n",
+       "      <td>100</td>\n",
+       "      <td>50</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>80</td>\n",
+       "      <td>2</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>[0.1]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[0.75]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[0.85]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>30</td>\n",
+       "      <td>150</td>\n",
+       "      <td>100</td>\n",
+       "      <td>50</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>80</td>\n",
+       "      <td>2</td>\n",
+       "      <td>inf</td>\n",
+       "      <td>[0.1]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[0.75]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[0.85]</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>13 rows × 32 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    lStart  lCue  lMemory  lContext  turnHint  hideHintUntil  cueDuration  \\\n",
+       "id                                                                          \n",
+       "0        5    45       10        10         1            -15          NaN   \n",
+       "1       30   100       20        20         1            -50          NaN   \n",
+       "2       30   190       20        30         1            -60          NaN   \n",
+       "3       30   230       20        50         1              0          NaN   \n",
+       "4       30   230       20        50         0              0          NaN   \n",
+       "5       30   190       60        50         0              0          NaN   \n",
+       "6       30   150      100        50         0              0          NaN   \n",
+       "7       30   150      100        50         0              0          NaN   \n",
+       "8       30   150      100        50         0              0          NaN   \n",
+       "9       30   150      100        50         0              0          0.2   \n",
+       "10      30   150      100        50         0              0          0.2   \n",
+       "11      30   150      100        50         1              0          NaN   \n",
+       "12      30   150      100        50         1              0          NaN   \n",
+       "\n",
+       "    cueVisibleAt  cueProbability  cueDensityPerM  ...  numSessions  numTrials  \\\n",
+       "id                                                ...                           \n",
+       "0             10             inf               3  ...            0         10   \n",
+       "1             10             inf               3  ...            0         40   \n",
+       "2             10             inf               3  ...            0         80   \n",
+       "3             10             inf               4  ...            2         80   \n",
+       "4             10             inf               4  ...            1         80   \n",
+       "5             10             inf               4  ...            1         80   \n",
+       "6             10             inf               4  ...            1         80   \n",
+       "7             10             2.5               4  ...            1         80   \n",
+       "8             10             1.6               4  ...            1         80   \n",
+       "9             10             1.6               4  ...            1         80   \n",
+       "10            10             1.2               4  ...            1         80   \n",
+       "11            10             inf               0  ...            1         80   \n",
+       "12            10             inf               0  ...            1         80   \n",
+       "\n",
+       "    numTrialsPerMin  performance  warmupBias  warmupMaxNTrials  warmupMaze  \\\n",
+       "id                                                                           \n",
+       "0                 2         0.00       [nan]             [nan]       [nan]   \n",
+       "1                 2         0.00       [nan]             [nan]       [nan]   \n",
+       "2                 2         0.60       [nan]             [nan]       [nan]   \n",
+       "3                 2         0.90       [nan]             [nan]       [nan]   \n",
+       "4                 2         0.80       [0.1]            [60.0]       [4.0]   \n",
+       "5                 2         0.80       [0.1]            [60.0]       [4.0]   \n",
+       "6                 2         0.80       [0.1]            [60.0]       [4.0]   \n",
+       "7                 2         0.75  [0.1, 0.1]      [20.0, 30.0]  [4.0, 7.0]   \n",
+       "8                 2         0.70       [0.1]            [20.0]       [4.0]   \n",
+       "9                 2         0.70       [0.1]            [20.0]       [4.0]   \n",
+       "10                2          inf       [0.1]            [20.0]      [13.0]   \n",
+       "11                2          inf       [0.1]             [nan]       [nan]   \n",
+       "12                2          inf       [0.1]             [nan]       [nan]   \n",
+       "\n",
+       "     warmupMotor  warmupNTrials warmupPerform  \n",
+       "id                                             \n",
+       "0          [nan]          [nan]         [nan]  \n",
+       "1          [nan]          [nan]         [nan]  \n",
+       "2          [nan]          [nan]         [nan]  \n",
+       "3          [nan]          [nan]         [nan]  \n",
+       "4          [0.0]         [30.0]         [0.8]  \n",
+       "5          [0.0]         [30.0]         [0.8]  \n",
+       "6          [0.0]         [30.0]         [0.8]  \n",
+       "7   [0.75, 0.75]   [10.0, 15.0]   [0.85, 0.8]  \n",
+       "8         [0.75]         [10.0]        [0.85]  \n",
+       "9         [0.75]         [10.0]        [0.85]  \n",
+       "10        [0.75]         [10.0]        [0.85]  \n",
+       "11        [0.75]          [nan]        [0.85]  \n",
+       "12        [0.75]          [nan]        [0.85]  \n",
+       "\n",
+       "[13 rows x 32 columns]"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nwbfile.lab_meta_data[\"LabMetaData\"].mazes[:]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "8adbdb8b-13da-43a2-b26a-b579edc57ae8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>numMazesInProtocol</th>\n",
+       "      <th>trialDraw</th>\n",
+       "      <th>stimDraw</th>\n",
+       "      <th>cueMinSeparation</th>\n",
+       "      <th>totalRepeatProbability</th>\n",
+       "      <th>numRepeatTrials</th>\n",
+       "      <th>visualcolor</th>\n",
+       "      <th>memorycolor</th>\n",
+       "      <th>princetonImplementation</th>\n",
+       "      <th>stimulus_code</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>id</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>11</td>\n",
+       "      <td>EradeCapped</td>\n",
+       "      <td>LeftOneOnly</td>\n",
+       "      <td>12</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>2</td>\n",
+       "      <td>[0, 0, 1]</td>\n",
+       "      <td>[1, 1, 0]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>TowersTaskSwitchStimulusTrain</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    numMazesInProtocol    trialDraw     stimDraw  cueMinSeparation  \\\n",
+       "id                                                                   \n",
+       "0                   11  EradeCapped  LeftOneOnly                12   \n",
+       "\n",
+       "    totalRepeatProbability  numRepeatTrials visualcolor memorycolor  \\\n",
+       "id                                                                    \n",
+       "0                     0.05                2   [0, 0, 1]   [1, 1, 0]   \n",
+       "\n",
+       "    princetonImplementation                  stimulus_code  \n",
+       "id                                                          \n",
+       "0                         1  TowersTaskSwitchStimulusTrain  "
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nwbfile.lab_meta_data[\"LabMetaData\"].stimulus_protocol[:]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "709c01f6-b254-4cdb-9a9e-e18ff67fe771",
+   "metadata": {},
+   "source": [
+    "## Access trials\n",
+    "\n",
+    "Behavior trials are stored in `nwbfile.trials`. The `start_time` denotes the start time of each trial in seconds relative to the global session start time (using the \"StartOfTrial\" column from ViRMEN `.mat` file).\n",
+    "The `stop_time` denotes the end time of each trial in seconds relative to the global session start time\n",
+    "(using the \"EndOfTrial\" column from the ViRMEN `.mat` file).\n",
+    "\n",
+    "`nwbfile.trials` can be converted to a pandas DataFrame for convenient analysis using `nwbfile.trials.to_dataframe`.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "27bd3de0-7d11-432c-a9cc-32e21ce63a8e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>start_time</th>\n",
+       "      <th>stop_time</th>\n",
+       "      <th>InterTrial</th>\n",
+       "      <th>SetupTrial</th>\n",
+       "      <th>InitializeTrial</th>\n",
+       "      <th>WithinTrial</th>\n",
+       "      <th>WithinContext</th>\n",
+       "      <th>WithinCue</th>\n",
+       "      <th>WithinDelay</th>\n",
+       "      <th>WithinArms</th>\n",
+       "      <th>...</th>\n",
+       "      <th>nDistract</th>\n",
+       "      <th>posSalient</th>\n",
+       "      <th>posDistract</th>\n",
+       "      <th>startIdx</th>\n",
+       "      <th>mazeID</th>\n",
+       "      <th>mainMazeID</th>\n",
+       "      <th>distanceTraveled</th>\n",
+       "      <th>excessTravel</th>\n",
+       "      <th>rewardFactor</th>\n",
+       "      <th>reward</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>id</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.909966</td>\n",
+       "      <td>7.271522</td>\n",
+       "      <td>8.583685</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>6.450284</td>\n",
+       "      <td>1.358135</td>\n",
+       "      <td>2.166536</td>\n",
+       "      <td>4.641668</td>\n",
+       "      <td>6.458506</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>350.353220</td>\n",
+       "      <td>-0.166818</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>10.814495</td>\n",
+       "      <td>18.314169</td>\n",
+       "      <td>19.626610</td>\n",
+       "      <td>102.490120</td>\n",
+       "      <td>10.775707</td>\n",
+       "      <td>16.609617</td>\n",
+       "      <td>11.667454</td>\n",
+       "      <td>12.484078</td>\n",
+       "      <td>15.042678</td>\n",
+       "      <td>16.617932</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>1102.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>355.420683</td>\n",
+       "      <td>-0.154767</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>21.743707</td>\n",
+       "      <td>27.903475</td>\n",
+       "      <td>29.219161</td>\n",
+       "      <td>111.852504</td>\n",
+       "      <td>21.710063</td>\n",
+       "      <td>26.685581</td>\n",
+       "      <td>22.360060</td>\n",
+       "      <td>23.101868</td>\n",
+       "      <td>25.243717</td>\n",
+       "      <td>26.693910</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>2362.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>352.031584</td>\n",
+       "      <td>-0.162826</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>31.322219</td>\n",
+       "      <td>37.632828</td>\n",
+       "      <td>38.953310</td>\n",
+       "      <td>120.488884</td>\n",
+       "      <td>31.302666</td>\n",
+       "      <td>36.094812</td>\n",
+       "      <td>31.752710</td>\n",
+       "      <td>32.394347</td>\n",
+       "      <td>34.602882</td>\n",
+       "      <td>36.103057</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>3461.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>357.422186</td>\n",
+       "      <td>-0.150007</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>41.075315</td>\n",
+       "      <td>46.084046</td>\n",
+       "      <td>47.404256</td>\n",
+       "      <td>136.962611</td>\n",
+       "      <td>41.036849</td>\n",
+       "      <td>45.545664</td>\n",
+       "      <td>41.461924</td>\n",
+       "      <td>42.020375</td>\n",
+       "      <td>43.937248</td>\n",
+       "      <td>45.554195</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>4580.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>345.586712</td>\n",
+       "      <td>-0.178153</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>49.547212</td>\n",
+       "      <td>54.684280</td>\n",
+       "      <td>56.013430</td>\n",
+       "      <td>155.345215</td>\n",
+       "      <td>49.521185</td>\n",
+       "      <td>54.138277</td>\n",
+       "      <td>49.929496</td>\n",
+       "      <td>50.521363</td>\n",
+       "      <td>52.563017</td>\n",
+       "      <td>54.146616</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>5541.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>345.630288</td>\n",
+       "      <td>-0.178049</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>58.108839</td>\n",
+       "      <td>63.149754</td>\n",
+       "      <td>64.472509</td>\n",
+       "      <td>164.816137</td>\n",
+       "      <td>58.096967</td>\n",
+       "      <td>62.872325</td>\n",
+       "      <td>58.472001</td>\n",
+       "      <td>59.071988</td>\n",
+       "      <td>61.230530</td>\n",
+       "      <td>62.880761</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>6520.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>346.368546</td>\n",
+       "      <td>-0.176294</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>66.567484</td>\n",
+       "      <td>72.458560</td>\n",
+       "      <td>73.773566</td>\n",
+       "      <td>173.978186</td>\n",
+       "      <td>66.556058</td>\n",
+       "      <td>71.589923</td>\n",
+       "      <td>67.056115</td>\n",
+       "      <td>67.747934</td>\n",
+       "      <td>69.964713</td>\n",
+       "      <td>71.598314</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>7487.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>351.158302</td>\n",
+       "      <td>-0.164903</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>75.868855</td>\n",
+       "      <td>81.534504</td>\n",
+       "      <td>82.849307</td>\n",
+       "      <td>183.373662</td>\n",
+       "      <td>75.857036</td>\n",
+       "      <td>81.224259</td>\n",
+       "      <td>76.290304</td>\n",
+       "      <td>76.973813</td>\n",
+       "      <td>79.423986</td>\n",
+       "      <td>81.232587</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>8556.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>346.586614</td>\n",
+       "      <td>-0.175775</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>84.951920</td>\n",
+       "      <td>91.718480</td>\n",
+       "      <td>93.033739</td>\n",
+       "      <td>192.879341</td>\n",
+       "      <td>84.932914</td>\n",
+       "      <td>89.766764</td>\n",
+       "      <td>85.433002</td>\n",
+       "      <td>86.233040</td>\n",
+       "      <td>88.191617</td>\n",
+       "      <td>89.775102</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>9597.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>357.552212</td>\n",
+       "      <td>-0.149697</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>10 rows × 47 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    start_time  stop_time  InterTrial  SetupTrial  InitializeTrial  \\\n",
+       "id                                                                   \n",
+       "0     0.909966   7.271522    8.583685    0.000000         0.000000   \n",
+       "1    10.814495  18.314169   19.626610  102.490120        10.775707   \n",
+       "2    21.743707  27.903475   29.219161  111.852504        21.710063   \n",
+       "3    31.322219  37.632828   38.953310  120.488884        31.302666   \n",
+       "4    41.075315  46.084046   47.404256  136.962611        41.036849   \n",
+       "5    49.547212  54.684280   56.013430  155.345215        49.521185   \n",
+       "6    58.108839  63.149754   64.472509  164.816137        58.096967   \n",
+       "7    66.567484  72.458560   73.773566  173.978186        66.556058   \n",
+       "8    75.868855  81.534504   82.849307  183.373662        75.857036   \n",
+       "9    84.951920  91.718480   93.033739  192.879341        84.932914   \n",
+       "\n",
+       "    WithinTrial  WithinContext  WithinCue  WithinDelay  WithinArms  ...  \\\n",
+       "id                                                                  ...   \n",
+       "0      6.450284       1.358135   2.166536     4.641668    6.458506  ...   \n",
+       "1     16.609617      11.667454  12.484078    15.042678   16.617932  ...   \n",
+       "2     26.685581      22.360060  23.101868    25.243717   26.693910  ...   \n",
+       "3     36.094812      31.752710  32.394347    34.602882   36.103057  ...   \n",
+       "4     45.545664      41.461924  42.020375    43.937248   45.554195  ...   \n",
+       "5     54.138277      49.929496  50.521363    52.563017   54.146616  ...   \n",
+       "6     62.872325      58.472001  59.071988    61.230530   62.880761  ...   \n",
+       "7     71.589923      67.056115  67.747934    69.964713   71.598314  ...   \n",
+       "8     81.224259      76.290304  76.973813    79.423986   81.232587  ...   \n",
+       "9     89.766764      85.433002  86.233040    88.191617   89.775102  ...   \n",
+       "\n",
+       "    nDistract  posSalient posDistract startIdx mazeID  mainMazeID  \\\n",
+       "id                                                                  \n",
+       "0           0       [nan]       [nan]      1.0   13.0        11.0   \n",
+       "1           0       [nan]       [nan]   1102.0   13.0        11.0   \n",
+       "2           0       [nan]       [nan]   2362.0   13.0        11.0   \n",
+       "3           0       [nan]       [nan]   3461.0   13.0        11.0   \n",
+       "4           0       [nan]       [nan]   4580.0   13.0        11.0   \n",
+       "5           0       [nan]       [nan]   5541.0   13.0        11.0   \n",
+       "6           0       [nan]       [nan]   6520.0   13.0        11.0   \n",
+       "7           0       [nan]       [nan]   7487.0   13.0        11.0   \n",
+       "8           0       [nan]       [nan]   8556.0   13.0        11.0   \n",
+       "9           0       [nan]       [nan]   9597.0   13.0        11.0   \n",
+       "\n",
+       "    distanceTraveled  excessTravel  rewardFactor  reward  \n",
+       "id                                                        \n",
+       "0         350.353220     -0.166818           1.5     1.0  \n",
+       "1         355.420683     -0.154767           1.5     1.0  \n",
+       "2         352.031584     -0.162826           1.5     1.0  \n",
+       "3         357.422186     -0.150007           1.5     1.0  \n",
+       "4         345.586712     -0.178153           1.5     1.0  \n",
+       "5         345.630288     -0.178049           1.5     1.0  \n",
+       "6         346.368546     -0.176294           1.5     1.0  \n",
+       "7         351.158302     -0.164903           1.5     1.0  \n",
+       "8         346.586614     -0.175775           1.5     1.0  \n",
+       "9         357.552212     -0.149697           1.5     1.0  \n",
+       "\n",
+       "[10 rows x 47 columns]"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "trials = nwbfile.trials.to_dataframe()\n",
+    "\n",
+    "trials[:10]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "129757c1-a387-4c28-be56-7d5317525a37",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>start_time</th>\n",
+       "      <th>stop_time</th>\n",
+       "      <th>InterTrial</th>\n",
+       "      <th>SetupTrial</th>\n",
+       "      <th>InitializeTrial</th>\n",
+       "      <th>WithinTrial</th>\n",
+       "      <th>WithinContext</th>\n",
+       "      <th>WithinCue</th>\n",
+       "      <th>WithinDelay</th>\n",
+       "      <th>WithinArms</th>\n",
+       "      <th>...</th>\n",
+       "      <th>nDistract</th>\n",
+       "      <th>posSalient</th>\n",
+       "      <th>posDistract</th>\n",
+       "      <th>startIdx</th>\n",
+       "      <th>mazeID</th>\n",
+       "      <th>mainMazeID</th>\n",
+       "      <th>distanceTraveled</th>\n",
+       "      <th>excessTravel</th>\n",
+       "      <th>rewardFactor</th>\n",
+       "      <th>reward</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>id</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.909966</td>\n",
+       "      <td>7.271522</td>\n",
+       "      <td>8.583685</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>6.450284</td>\n",
+       "      <td>1.358135</td>\n",
+       "      <td>2.166536</td>\n",
+       "      <td>4.641668</td>\n",
+       "      <td>6.458506</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>350.353220</td>\n",
+       "      <td>-0.166818</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>10.814495</td>\n",
+       "      <td>18.314169</td>\n",
+       "      <td>19.626610</td>\n",
+       "      <td>102.490120</td>\n",
+       "      <td>10.775707</td>\n",
+       "      <td>16.609617</td>\n",
+       "      <td>11.667454</td>\n",
+       "      <td>12.484078</td>\n",
+       "      <td>15.042678</td>\n",
+       "      <td>16.617932</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>1102.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>355.420683</td>\n",
+       "      <td>-0.154767</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>21.743707</td>\n",
+       "      <td>27.903475</td>\n",
+       "      <td>29.219161</td>\n",
+       "      <td>111.852504</td>\n",
+       "      <td>21.710063</td>\n",
+       "      <td>26.685581</td>\n",
+       "      <td>22.360060</td>\n",
+       "      <td>23.101868</td>\n",
+       "      <td>25.243717</td>\n",
+       "      <td>26.693910</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>[nan]</td>\n",
+       "      <td>2362.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>352.031584</td>\n",
+       "      <td>-0.162826</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>3 rows × 47 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    start_time  stop_time  InterTrial  SetupTrial  InitializeTrial  \\\n",
+       "id                                                                   \n",
+       "0     0.909966   7.271522    8.583685    0.000000         0.000000   \n",
+       "1    10.814495  18.314169   19.626610  102.490120        10.775707   \n",
+       "2    21.743707  27.903475   29.219161  111.852504        21.710063   \n",
+       "\n",
+       "    WithinTrial  WithinContext  WithinCue  WithinDelay  WithinArms  ...  \\\n",
+       "id                                                                  ...   \n",
+       "0      6.450284       1.358135   2.166536     4.641668    6.458506  ...   \n",
+       "1     16.609617      11.667454  12.484078    15.042678   16.617932  ...   \n",
+       "2     26.685581      22.360060  23.101868    25.243717   26.693910  ...   \n",
+       "\n",
+       "    nDistract  posSalient posDistract startIdx mazeID  mainMazeID  \\\n",
+       "id                                                                  \n",
+       "0           0       [nan]       [nan]      1.0   13.0        11.0   \n",
+       "1           0       [nan]       [nan]   1102.0   13.0        11.0   \n",
+       "2           0       [nan]       [nan]   2362.0   13.0        11.0   \n",
+       "\n",
+       "    distanceTraveled  excessTravel  rewardFactor  reward  \n",
+       "id                                                        \n",
+       "0         350.353220     -0.166818           1.5     1.0  \n",
+       "1         355.420683     -0.154767           1.5     1.0  \n",
+       "2         352.031584     -0.162826           1.5     1.0  \n",
+       "\n",
+       "[3 rows x 47 columns]"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "trials[trials[\"trial_type\"] == \"right\"][:3]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fdc72048-3dc7-4b35-a411-e5507176ef35",
+   "metadata": {},
+   "source": [
+    "# Access Widefield Imaging <a name=\"access-imaging\"></a>\n",
+    "\n",
+    "This section demonstraces how to access the raw and processed Widefield imaging data.\n",
+    "\n",
+    "`NWB` organizes data into different groups depending on the type of data. Groups can be thought of as folders within the file. Here are some of the groups within an NWBFile and the types of data they are intended to store:\n",
+    "\n",
+    "- `acquisition`: raw, acquired data that should never change\n",
+    "- `processing`: processed data, typically the results of preprocessing algorithms and could change\n",
+    "\n",
+    "## Raw Widefield Imaging\n",
+    "\n",
+    "The raw Widefield imaging data is stored in `pynwb.ophys.OnePhotonSeries` objects (blue and violet separately) which is added to `nwbfile.acquisition`. The blue frames can be accessed as `nwbfile.acquisition['OnePhotonSeriesBlue']`, the violet frames as `nwbfile.acquisition['OnePhotonSeriesViolet']`.\n",
+    "\n",
+    "The data in [OnePhotonSeries](https://pynwb.readthedocs.io/en/stable/pynwb.ophys.html#pynwb.ophys.OnePhotonSeries) is stored as a three dimensional array: the first dimension is time (frame), the second and third dimensions represent x and y (width by height). "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "e9621b78-2c39-49fa-8106-d3e277252468",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "photon_series_blue = nwbfile.acquisition['OnePhotonSeriesBlue']\n",
+    "photon_series_violet = nwbfile.acquisition['OnePhotonSeriesViolet']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "id": "1ef00fe3-cb56-4efe-89bb-946bb9bc42b5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Visualize the imaging data.\n",
+    "\n",
+    "from matplotlib import pyplot as plt\n",
+    "\n",
+    "plt.imshow(photon_series_blue.data[2200].T, aspect=\"auto\", cmap=\"Greys\")\n",
+    "plt.title(\"Blue\")\n",
+    "plt.show()\n",
+    "\n",
+    "plt.imshow(photon_series_violet.data[2200].T, aspect=\"auto\", cmap=\"Greys\")\n",
+    "plt.title(\"Violet\")\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "03d7bcda-7c49-4d8c-8e16-84775a4e4b88",
+   "metadata": {},
+   "source": [
+    "The timestamps for the blue frames can be accessed as `nwbfile.acquisition['OnePhotonSeriesBlue'].timestamps`.\n",
+    "\n",
+    "The blue frame timestamps that are aligned with the behavior clock are added from the `wf_behav_sync.mat` file.\n",
+    "The violet frame timestamps are aligned to the blue frame timestamps by interpolation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "id": "19879672-07e2-443c-ac36-3952200eb33f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ 0.99890178,  1.09832287,  1.19802403,  1.29878521,  1.3985163 ,\n",
+       "        1.4982475 ,  1.59895861,  1.69868982,  1.79842091,  1.89919209,\n",
+       "        1.99928319,  2.09900427,  2.19871545,  2.29944658,  2.39937782,\n",
+       "        2.49893904,  2.59863997,  2.69940114,  2.79914236,  2.89887357,\n",
+       "        2.99961472,  3.0995059 ,  3.19917703,  3.29977798,  3.39953923,\n",
+       "        3.49995041,  3.6000514 ,  3.69978261,  3.79951382,  3.89927483,\n",
+       "        3.99958611,  4.10017729,  4.1993084 ,  4.30006933,  4.39934063,\n",
+       "        4.50018167,  4.60018301,  4.69991398,  4.80001545,  4.90021658,\n",
+       "        4.9998374 ,  5.10053873,  5.2001996 ,  5.29972076,  5.40045214,\n",
+       "        5.50018311,  5.59991455,  5.70064545,  5.80070686,  5.90044785,\n",
+       "        6.00041914,  6.10015011,  6.20031118,  6.30104256,  6.40080357,\n",
+       "        6.50087452,  6.60110569,  6.70098686,  6.80102825,  6.90059948,\n",
+       "        7.00133038,  7.10057163,  7.20130253,  7.30085373,  7.40109491,\n",
+       "        7.50086594,  7.60156727,  7.70132828,  7.80102968,  7.9008007 ,\n",
+       "        8.00150204,  8.10142326,  8.20099449,  8.30169487,  8.40146637,\n",
+       "        8.50119781,  8.60190868,  8.70193005,  8.80167103,  8.90122223,\n",
+       "        9.00152302,  9.10198402,  9.20171547,  9.30125713,  9.40198803,\n",
+       "        9.50172901,  9.60245991,  9.70232105,  9.80231285,  9.90223312,\n",
+       "       10.00203514, 10.1020155 , 10.20255661, 10.30228806, 10.40256882,\n",
+       "       10.5026207 , 10.60226154, 10.70275307, 10.80281353, 10.90209484])"
+      ]
+     },
+     "execution_count": 77,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "photon_series_blue.timestamps[:100]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "65632247-717f-43da-bd24-3a6b738b4e73",
+   "metadata": {},
+   "source": [
+    "The processed imaging data is stored in the \"ophys\" processing module, which can be accessed as `nwbfile.processing[\"ophys\"]`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "id": "a91c5601-ddca-4336-829c-f2b42bd07828",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "        <div class='container-wrap'><div class='container-header'><div class='xr-obj-type'><h3>ophys (ProcessingModule)</h3></div></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['description']\">description:</span> <span class=\"field-value\">No description.</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']\"><b>data_interfaces (8)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ImageSegmentation']\"><b>ImageSegmentation</b></summary><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']\"><b>plane_segmentations (1)</b></summary><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue']\"><b>PlaneSegmentationProcessedBlue</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['description']\">description:</span> <span class=\"field-value\">Segmented ROIs</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['id']\"><b>id</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['colnames']\">colnames:</span> <span class=\"field-value\">('image_mask', 'ROICentroids', 'Accepted', 'Rejected', 'location')</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['columns']\">columns:</span> <span class=\"field-value\">(<hdmf.common.table.VectorData object at 0x13f21c2d0>, <hdmf.common.table.VectorData object at 0x13f21c250>, <hdmf.common.table.VectorData object at 0x13f21eb90>, <hdmf.common.table.VectorData object at 0x13f21f510>, <hdmf.common.table.VectorData object at 0x13f21f590>)</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane']\"><b>imaging_plane</b></summary><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['optical_channel']\"><b>optical_channel</b></summary><div style=\"margin-left: 120px;\" class=\"container-fields\"><span class=\"field-value\" title=\".fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['optical_channel'][0]\">OpticalChannelBlue pynwb.ophys.OpticalChannel at 0x5353898512\n",
+       "Fields:\n",
+       "  description: An optical channel of the microscope.\n",
+       "  emission_lambda: nan\n",
+       "</span></div></details><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['description']\">description:</span> <span class=\"field-value\">The plane or volume being imaged by the microscope.</span></div><details><summary style=\"display: list-item; margin-left: 100px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['device']\"><b>device</b></summary></details><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['excitation_lambda']\">excitation_lambda:</span> <span class=\"field-value\">nan</span></div><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['imaging_rate']\">imaging_rate:</span> <span class=\"field-value\">10.0</span></div><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['indicator']\">indicator:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['location']\">location:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 100px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ImageSegmentation'].fields['plane_segmentations']['PlaneSegmentationProcessedBlue'].fields['imaging_plane'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div></details></details></details></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesBlue']\"><b>MotionCorrectionSeriesBlue</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['description']\">description:</span> <span class=\"field-value\">The x, y shifts for the OnePhotonSeriesBlue imaging data.</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['unit']\">unit:</span> <span class=\"field-value\">px</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesBlue'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesViolet']\"><b>MotionCorrectionSeriesViolet</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['description']\">description:</span> <span class=\"field-value\">The x, y shifts for the OnePhotonSeriesViolet imaging data.</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['unit']\">unit:</span> <span class=\"field-value\">px</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['MotionCorrectionSeriesViolet'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue']\"><b>OnePhotonSeriesProcessedBlue</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['description']\">description:</span> <span class=\"field-value\">Processed imaging data from one-photon excitation microscopy.</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['unit']\">unit:</span> <span class=\"field-value\">n.a.</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['dimension']\"><b>dimension</b></summary></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane']\"><b>imaging_plane</b></summary><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['optical_channel']\"><b>optical_channel</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-value\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['optical_channel'][0]\">OpticalChannelBlue pynwb.ophys.OpticalChannel at 0x5353898512\n",
+       "Fields:\n",
+       "  description: An optical channel of the microscope.\n",
+       "  emission_lambda: nan\n",
+       "</span></div></details><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['description']\">description:</span> <span class=\"field-value\">The plane or volume being imaged by the microscope.</span></div><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['device']\"><b>device</b></summary></details><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['excitation_lambda']\">excitation_lambda:</span> <span class=\"field-value\">nan</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['imaging_rate']\">imaging_rate:</span> <span class=\"field-value\">10.0</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['indicator']\">indicator:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['location']\">location:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['imaging_plane'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedBlue'].fields['binning']\">binning:</span> <span class=\"field-value\">64</span></div></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet']\"><b>OnePhotonSeriesProcessedViolet</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['description']\">description:</span> <span class=\"field-value\">Processed imaging data from one-photon excitation microscopy.</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['unit']\">unit:</span> <span class=\"field-value\">n.a.</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['dimension']\"><b>dimension</b></summary></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane']\"><b>imaging_plane</b></summary><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['optical_channel']\"><b>optical_channel</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-value\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['optical_channel'][0]\">OpticalChannelViolet pynwb.ophys.OpticalChannel at 0x5353908304\n",
+       "Fields:\n",
+       "  description: An optical channel of the microscope.\n",
+       "  emission_lambda: nan\n",
+       "</span></div></details><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['description']\">description:</span> <span class=\"field-value\">The plane or volume being imaged by the microscope.</span></div><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['device']\"><b>device</b></summary></details><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['excitation_lambda']\">excitation_lambda:</span> <span class=\"field-value\">nan</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['imaging_rate']\">imaging_rate:</span> <span class=\"field-value\">10.0</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['indicator']\">indicator:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['location']\">location:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 60px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['imaging_plane'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['OnePhotonSeriesProcessedViolet'].fields['binning']\">binning:</span> <span class=\"field-value\">64</span></div></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['SegmentationImages']\"><b>SegmentationImages</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SegmentationImages'].fields['description']\">description:</span> <span class=\"field-value\">The summary images of the segmentation.</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['SegmentationImages'].fields['images']\"><b>images (2)</b></summary><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['SegmentationImages'].fields['images']['pca_blue']\"><b>pca_blue</b></summary></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['SegmentationImages'].fields['images']['vasculature']\"><b>vasculature</b></summary></details></details></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['SegmentationImagesBlue']\"><b>SegmentationImagesBlue</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SegmentationImagesBlue'].fields['description']\">description:</span> <span class=\"field-value\">Contains the manual mask and the contrast based vasculature mask for the blue channel in the full size session image.</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['SegmentationImagesBlue'].fields['images']\"><b>images (2)</b></summary><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['SegmentationImagesBlue'].fields['images']['manual']\"><b>manual</b></summary></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['SegmentationImagesBlue'].fields['images']['vasculature']\"><b>vasculature</b></summary></details></details></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['SegmentationImagesProcessedViolet']\"><b>SegmentationImagesProcessedViolet</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SegmentationImagesProcessedViolet'].fields['description']\">description:</span> <span class=\"field-value\">Contains the PCA mask for the violet channel on the binned session image.</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['SegmentationImagesProcessedViolet'].fields['images']\"><b>images (1)</b></summary><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['SegmentationImagesProcessedViolet'].fields['images']['pca_violet']\"><b>pca_violet</b></summary></details></details></details></details></div>"
+      ],
+      "text/plain": [
+       "ophys pynwb.base.ProcessingModule at 0x5363661904\n",
+       "Fields:\n",
+       "  data_interfaces: {\n",
+       "    ImageSegmentation <class 'pynwb.ophys.ImageSegmentation'>,\n",
+       "    MotionCorrectionSeriesBlue <class 'pynwb.base.TimeSeries'>,\n",
+       "    MotionCorrectionSeriesViolet <class 'pynwb.base.TimeSeries'>,\n",
+       "    OnePhotonSeriesProcessedBlue <class 'pynwb.ophys.OnePhotonSeries'>,\n",
+       "    OnePhotonSeriesProcessedViolet <class 'pynwb.ophys.OnePhotonSeries'>,\n",
+       "    SegmentationImages <class 'pynwb.base.Images'>,\n",
+       "    SegmentationImagesBlue <class 'pynwb.base.Images'>,\n",
+       "    SegmentationImagesProcessedViolet <class 'pynwb.base.Images'>\n",
+       "  }\n",
+       "  description: No description."
+      ]
+     },
+     "execution_count": 81,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nwbfile.processing[\"ophys\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "982ff4d7-4953-4bea-a20b-c4db5d00d984",
+   "metadata": {},
+   "source": [
+    "## Motion Correction\n",
+    "\n",
+    "The x,y shifts for the blue and violet frames is added as [TimeSeries](https://pynwb.readthedocs.io/en/stable/pynwb.base.html#pynwb.base.TimeSeries) objects.\n",
+    "\n",
+    "The motion correction series for the blue frames can be accessed as `nwbfile.processing[\"ophys\"][\"MotionCorrectionSeriesBlue\"]`.\n",
+    "\n",
+    "The timestamps for the motion correction series references the same timestamps as for the raw imaging data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "id": "bf4ae122-b92e-465d-9e09-cc813f79388b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "        <script>\n",
+       "            function copyToClipboard(text) {\n",
+       "                navigator.clipboard.writeText(text).then(function() {\n",
+       "                    console.log('Copied to clipboard: ' + text);\n",
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+       "                    console.error('Could not copy text: ', err);\n",
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+       "\n",
+       "            document.addEventListener('DOMContentLoaded', function() {\n",
+       "                let fieldKeys = document.querySelectorAll('.container-fields .field-key');\n",
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+       "                        copyToClipboard(accessCode);\n",
+       "                    });\n",
+       "                });\n",
+       "            });\n",
+       "        </script>\n",
+       "        <div class='container-wrap'><div class='container-header'><div class='xr-obj-type'><h3>MotionCorrectionSeriesBlue (TimeSeries)</h3></div></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['description']\">description:</span> <span class=\"field-value\">The x, y shifts for the OnePhotonSeriesBlue imaging data.</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['unit']\">unit:</span> <span class=\"field-value\">px</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></div>"
+      ],
+      "text/plain": [
+       "MotionCorrectionSeriesBlue pynwb.base.TimeSeries at 0x5364092496\n",
+       "Fields:\n",
+       "  comments: no comments\n",
+       "  conversion: 1.0\n",
+       "  data: <HDF5 dataset \"data\": shape (37341, 2), type \"<u2\">\n",
+       "  description: The x, y shifts for the OnePhotonSeriesBlue imaging data.\n",
+       "  interval: 1\n",
+       "  offset: 0.0\n",
+       "  resolution: -1.0\n",
+       "  timestamps: <HDF5 dataset \"timestamps\": shape (37341,), type \"<f8\">\n",
+       "  timestamps_unit: seconds\n",
+       "  unit: px"
+      ]
+     },
+     "execution_count": 84,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "motion_correction_blue = nwbfile.processing[\"ophys\"][\"MotionCorrectionSeriesBlue\"]\n",
+    "motion_correction_blue"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "id": "fd1f9bd0-daf8-43d3-a14c-2dd25a658bd8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([[0, 0],\n",
+       "        [0, 0],\n",
+       "        [0, 0],\n",
+       "        [0, 0],\n",
+       "        [0, 0],\n",
+       "        [0, 0],\n",
+       "        [0, 0],\n",
+       "        [0, 0],\n",
+       "        [0, 0],\n",
+       "        [0, 0]], dtype=uint16),\n",
+       " array([0.99890178, 1.09832287, 1.19802403, 1.29878521, 1.3985163 ,\n",
+       "        1.4982475 , 1.59895861, 1.69868982, 1.79842091, 1.89919209]))"
+      ]
+     },
+     "execution_count": 91,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "motion_correction_blue.data[:10], motion_correction_blue.timestamps[:10]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c4558f6d-e9ac-4bba-8e70-0f80ea4b0c29",
+   "metadata": {},
+   "source": [
+    "## Processed Widefield Imaging\n",
+    "\n",
+    "The downsampled imaging data for the blue frames can accessed as `nwbfile.processing[\"ophys\"][\"OnePhotonSeriesProcessedBlue\"]`.\n",
+    "\n",
+    "The data in [OnePhotonSeries](https://pynwb.readthedocs.io/en/stable/pynwb.ophys.html#pynwb.ophys.OnePhotonSeries) is stored as a three dimensional array: the first dimension is time (frame), the second and third dimensions represent x and y (width by height). \n",
+    "\n",
+    "The binned image size is (128, 128) which can be accessed with the \"dimension\" attribute in `nwbfile.processing[\"ophys\"][\"OnePhotonSeriesProcessedBlue\"]`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "id": "98f7592b-1235-4d97-8f63-a09747f9d205",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
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+       "            .container-fields {\n",
+       "                font-family: \"Open Sans\", Arial, sans-serif;\n",
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+       "                color: #0A6EAA;\n",
+       "            }\n",
+       "        </style>\n",
+       "        \n",
+       "        <script>\n",
+       "            function copyToClipboard(text) {\n",
+       "                navigator.clipboard.writeText(text).then(function() {\n",
+       "                    console.log('Copied to clipboard: ' + text);\n",
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+       "                    console.error('Could not copy text: ', err);\n",
+       "                });\n",
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+       "\n",
+       "            document.addEventListener('DOMContentLoaded', function() {\n",
+       "                let fieldKeys = document.querySelectorAll('.container-fields .field-key');\n",
+       "                fieldKeys.forEach(function(fieldKey) {\n",
+       "                    fieldKey.addEventListener('click', function() {\n",
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+       "                        copyToClipboard(accessCode);\n",
+       "                    });\n",
+       "                });\n",
+       "            });\n",
+       "        </script>\n",
+       "        <div class='container-wrap'><div class='container-header'><div class='xr-obj-type'><h3>OnePhotonSeriesProcessedBlue (OnePhotonSeries)</h3></div></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['description']\">description:</span> <span class=\"field-value\">Processed imaging data from one-photon excitation microscopy.</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['unit']\">unit:</span> <span class=\"field-value\">n.a.</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['dimension']\"><b>dimension</b></summary></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['imaging_plane']\"><b>imaging_plane</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['imaging_plane'].fields['optical_channel']\"><b>optical_channel</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-value\" title=\".fields['imaging_plane'].fields['optical_channel'][0]\">OpticalChannelBlue pynwb.ophys.OpticalChannel at 0x5353898512\n",
+       "Fields:\n",
+       "  description: An optical channel of the microscope.\n",
+       "  emission_lambda: nan\n",
+       "</span></div></details><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_plane'].fields['description']\">description:</span> <span class=\"field-value\">The plane or volume being imaged by the microscope.</span></div><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['imaging_plane'].fields['device']\"><b>device</b></summary></details><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_plane'].fields['excitation_lambda']\">excitation_lambda:</span> <span class=\"field-value\">nan</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_plane'].fields['imaging_rate']\">imaging_rate:</span> <span class=\"field-value\">10.0</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_plane'].fields['indicator']\">indicator:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_plane'].fields['location']\">location:</span> <span class=\"field-value\">unknown</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_plane'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 20px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['imaging_plane'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div></details><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['binning']\">binning:</span> <span class=\"field-value\">64</span></div></div>"
+      ],
+      "text/plain": [
+       "OnePhotonSeriesProcessedBlue pynwb.ophys.OnePhotonSeries at 0x5353908944\n",
+       "Fields:\n",
+       "  binning: 64\n",
+       "  comments: no comments\n",
+       "  conversion: 1.0\n",
+       "  data: <HDF5 dataset \"data\": shape (37341, 128, 128), type \"<f8\">\n",
+       "  description: Processed imaging data from one-photon excitation microscopy.\n",
+       "  dimension: <HDF5 dataset \"dimension\": shape (2,), type \"<i8\">\n",
+       "  imaging_plane: ImagingPlaneBlue pynwb.ophys.ImagingPlane at 0x5353906320\n",
+       "Fields:\n",
+       "  conversion: 1.0\n",
+       "  description: The plane or volume being imaged by the microscope.\n",
+       "  device: Microscope pynwb.device.Device at 0x5353899984\n",
+       "  excitation_lambda: nan\n",
+       "  imaging_rate: 10.0\n",
+       "  indicator: unknown\n",
+       "  location: unknown\n",
+       "  optical_channel: (\n",
+       "    OpticalChannelBlue <class 'pynwb.ophys.OpticalChannel'>\n",
+       "  )\n",
+       "  unit: meters\n",
+       "\n",
+       "  interval: 1\n",
+       "  offset: 0.0\n",
+       "  resolution: -1.0\n",
+       "  timestamps: <HDF5 dataset \"timestamps\": shape (37341,), type \"<f8\">\n",
+       "  timestamps_unit: seconds\n",
+       "  unit: n.a."
+      ]
+     },
+     "execution_count": 94,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nwbfile.processing[\"ophys\"][\"OnePhotonSeriesProcessedBlue\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "id": "06080884-70d2-4bbe-b4cf-5ab4607e9578",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([128, 128])"
+      ]
+     },
+     "execution_count": 97,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nwbfile.processing[\"ophys\"][\"OnePhotonSeriesProcessedBlue\"].dimension[:]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "087d0ef1-a474-48fc-9106-3a80a188834a",
+   "metadata": {},
+   "source": [
+    "## Accessing the segmentation data\n",
+    "\n",
+    "The segmentation output for the Widefield Imaging data is stored in `nwbfile.processing[\"ophys\"]`. \n",
+    "\n",
+    "In NWB, the [PlaneSegmentation](https://pynwb.readthedocs.io/en/stable/pynwb.ophys.html#pynwb.ophys.PlaneSegmentation) class stores the detected regions of interest in the [OnePhotonSeries](https://pynwb.readthedocs.io/en/stable/pynwb.ophys.html#pynwb.ophys.OnePhotonSeries) data. The [ImageSegmentation](https://pynwb.readthedocs.io/en/stable/pynwb.ophys.html#pynwb.ophys.ImageSegmentation) can contain multiple `PlaneSegmentation` tables, so that we can store results of different segmentation algorithms or different segmentation classes.\n",
+    "\n",
+    "We can access the plane segmentation for the processed [OnePhotonSeries](https://pynwb.readthedocs.io/en/stable/pynwb.ophys.html#pynwb.ophys.OnePhotonSeries) data (blue frames) as \n",
+    "`nwbfile.processing[\"ophys\"][\"ImageSegmentation\"][\"PlaneSegmentationProcessedBlue\"]`.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "id": "f0618a5c-85c1-4a22-b80e-c8dff5942800",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>image_mask</th>\n",
+       "      <th>ROICentroids</th>\n",
+       "      <th>Accepted</th>\n",
+       "      <th>Rejected</th>\n",
+       "      <th>location</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>id</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...</td>\n",
+       "      <td>[14.705515088449532, 112.51925078043705]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>VISp-L</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...</td>\n",
+       "      <td>[106.82650142993327, 114.68255481410867]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>VISp-R</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...</td>\n",
+       "      <td>[30.074074074074073, 107.95833333333333]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>VISpm-L</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...</td>\n",
+       "      <td>[88.71363636363637, 110.15]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>VISpm-R</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...</td>\n",
+       "      <td>[29.676855895196507, 92.2882096069869]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>VISam-L</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...</td>\n",
+       "      <td>[90.1889400921659, 94.58986175115207]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>VISam-R</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...</td>\n",
+       "      <td>[21.92622950819672, 83.87158469945355]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>VISa-L</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...</td>\n",
+       "      <td>[98.55342465753425, 86.38356164383562]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>VISa-R</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...</td>\n",
+       "      <td>[5.009615384615385, 90.4326923076923]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>VISrl-L</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...</td>\n",
+       "      <td>[119.74090909090908, 98.00454545454545]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>VISrl-R</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                           image_mask  \\\n",
+       "id                                                      \n",
+       "0   [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...   \n",
+       "1   [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...   \n",
+       "2   [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...   \n",
+       "3   [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...   \n",
+       "4   [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...   \n",
+       "5   [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...   \n",
+       "6   [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...   \n",
+       "7   [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...   \n",
+       "8   [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...   \n",
+       "9   [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...   \n",
+       "\n",
+       "                                ROICentroids  Accepted  Rejected location  \n",
+       "id                                                                         \n",
+       "0   [14.705515088449532, 112.51925078043705]         1         0   VISp-L  \n",
+       "1   [106.82650142993327, 114.68255481410867]         1         0   VISp-R  \n",
+       "2   [30.074074074074073, 107.95833333333333]         1         0  VISpm-L  \n",
+       "3                [88.71363636363637, 110.15]         1         0  VISpm-R  \n",
+       "4     [29.676855895196507, 92.2882096069869]         1         0  VISam-L  \n",
+       "5      [90.1889400921659, 94.58986175115207]         1         0  VISam-R  \n",
+       "6     [21.92622950819672, 83.87158469945355]         1         0   VISa-L  \n",
+       "7     [98.55342465753425, 86.38356164383562]         1         0   VISa-R  \n",
+       "8      [5.009615384615385, 90.4326923076923]         1         0  VISrl-L  \n",
+       "9    [119.74090909090908, 98.00454545454545]         1         0  VISrl-R  "
+      ]
+     },
+     "execution_count": 105,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plane_segmentation = nwbfile.processing[\"ophys\"][\"ImageSegmentation\"][\"PlaneSegmentationProcessedBlue\"][:]\n",
+    "plane_segmentation[:10]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "da4faa4c-9d0f-473d-b441-4f5e1fef2bb2",
+   "metadata": {},
+   "source": [
+    "The summary images of the segmentation are stored in [Images](https://pynwb.readthedocs.io/en/stable/pynwb.base.html#pynwb.base.Images) container in NWB. \n",
+    "\n",
+    "The manual mask and contrast based vasculature mask for the blue channel (full size image) can be accessed \n",
+    "as `nwbfile.processing[\"ophys\"][\"SegmentationImagesBlue\"]`.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 174,
+   "id": "e4974b7a-c2e5-4e75-b19c-1bc3d13ad27a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <style>\n",
+       "            .container-fields {\n",
+       "                font-family: \"Open Sans\", Arial, sans-serif;\n",
+       "            }\n",
+       "            .container-fields .field-value {\n",
+       "                color: #00788E;\n",
+       "            }\n",
+       "            .container-fields details > summary {\n",
+       "                cursor: pointer;\n",
+       "                display: list-item;\n",
+       "            }\n",
+       "            .container-fields details > summary:hover {\n",
+       "                color: #0A6EAA;\n",
+       "            }\n",
+       "        </style>\n",
+       "        \n",
+       "        <script>\n",
+       "            function copyToClipboard(text) {\n",
+       "                navigator.clipboard.writeText(text).then(function() {\n",
+       "                    console.log('Copied to clipboard: ' + text);\n",
+       "                }, function(err) {\n",
+       "                    console.error('Could not copy text: ', err);\n",
+       "                });\n",
+       "            }\n",
+       "\n",
+       "            document.addEventListener('DOMContentLoaded', function() {\n",
+       "                let fieldKeys = document.querySelectorAll('.container-fields .field-key');\n",
+       "                fieldKeys.forEach(function(fieldKey) {\n",
+       "                    fieldKey.addEventListener('click', function() {\n",
+       "                        let accessCode = fieldKey.getAttribute('title').replace('Access code: ', '');\n",
+       "                        copyToClipboard(accessCode);\n",
+       "                    });\n",
+       "                });\n",
+       "            });\n",
+       "        </script>\n",
+       "        <div class='container-wrap'><div class='container-header'><div class='xr-obj-type'><h3>SegmentationImagesBlue (Images)</h3></div></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['description']\">description:</span> <span class=\"field-value\">Contains the manual mask and the contrast based vasculature mask for the blue channel in the full size session image.</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['images']\"><b>images (2)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['images']['manual']\"><b>manual</b></summary></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['images']['vasculature']\"><b>vasculature</b></summary></details></details></div>"
+      ],
+      "text/plain": [
+       "SegmentationImagesBlue pynwb.base.Images at 0x5364044880\n",
+       "Fields:\n",
+       "  description: Contains the manual mask and the contrast based vasculature mask for the blue channel in the full size session image.\n",
+       "  images: {\n",
+       "    manual <class 'pynwb.image.GrayscaleImage'>,\n",
+       "    vasculature <class 'pynwb.image.GrayscaleImage'>\n",
+       "  }"
+      ]
+     },
+     "execution_count": 174,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "images_blue = nwbfile.processing[\"ophys\"][\"SegmentationImagesBlue\"]\n",
+    "images_blue"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 175,
+   "id": "4e7e3f92-8c66-4108-b1d6-930bfb3a6ae1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.imshow(photon_series_blue.data[2200].T, aspect=\"auto\", cmap=\"Greys\")\n",
+    "plt.title(\"Blue\")\n",
+    "plt.show()\n",
+    "\n",
+    "plt.imshow(images_blue.images[\"manual\"].data[:].T, aspect=\"auto\", cmap=\"Greys\")\n",
+    "plt.title(\"Manual mask\")\n",
+    "plt.show()\n",
+    "\n",
+    "plt.imshow(images_blue.images[\"vasculature\"].data[:].T, aspect=\"auto\", cmap=\"Greys\")\n",
+    "plt.title(\"Vasculature mask\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e85b126d-4cf9-44ad-9f81-5f2b4c5dec84",
+   "metadata": {},
+   "source": [
+    "The PCA mask and the vasculature mask for the blue channel on the binned session image can be accessed from \n",
+    "`nwbfile.processing[\"ophys\"][\"SegmentationImages\"]`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 165,
+   "id": "c2e33b68-ac51-4159-8d1e-a77868f1ca27",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <style>\n",
+       "            .container-fields {\n",
+       "                font-family: \"Open Sans\", Arial, sans-serif;\n",
+       "            }\n",
+       "            .container-fields .field-value {\n",
+       "                color: #00788E;\n",
+       "            }\n",
+       "            .container-fields details > summary {\n",
+       "                cursor: pointer;\n",
+       "                display: list-item;\n",
+       "            }\n",
+       "            .container-fields details > summary:hover {\n",
+       "                color: #0A6EAA;\n",
+       "            }\n",
+       "        </style>\n",
+       "        \n",
+       "        <script>\n",
+       "            function copyToClipboard(text) {\n",
+       "                navigator.clipboard.writeText(text).then(function() {\n",
+       "                    console.log('Copied to clipboard: ' + text);\n",
+       "                }, function(err) {\n",
+       "                    console.error('Could not copy text: ', err);\n",
+       "                });\n",
+       "            }\n",
+       "\n",
+       "            document.addEventListener('DOMContentLoaded', function() {\n",
+       "                let fieldKeys = document.querySelectorAll('.container-fields .field-key');\n",
+       "                fieldKeys.forEach(function(fieldKey) {\n",
+       "                    fieldKey.addEventListener('click', function() {\n",
+       "                        let accessCode = fieldKey.getAttribute('title').replace('Access code: ', '');\n",
+       "                        copyToClipboard(accessCode);\n",
+       "                    });\n",
+       "                });\n",
+       "            });\n",
+       "        </script>\n",
+       "        <div class='container-wrap'><div class='container-header'><div class='xr-obj-type'><h3>SegmentationImages (Images)</h3></div></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['description']\">description:</span> <span class=\"field-value\">The summary images of the segmentation.</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['images']\"><b>images (2)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['images']['pca_blue']\"><b>pca_blue</b></summary></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['images']['vasculature']\"><b>vasculature</b></summary></details></details></div>"
+      ],
+      "text/plain": [
+       "SegmentationImages pynwb.base.Images at 0x5364042192\n",
+       "Fields:\n",
+       "  description: The summary images of the segmentation.\n",
+       "  images: {\n",
+       "    pca_blue <class 'pynwb.image.GrayscaleImage'>,\n",
+       "    vasculature <class 'pynwb.image.GrayscaleImage'>\n",
+       "  }"
+      ]
+     },
+     "execution_count": 165,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nwbfile.processing[\"ophys\"][\"SegmentationImages\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 170,
+   "id": "12c9fb0b-d1b2-454a-9513-cd2d455acce0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "images_blue = nwbfile.processing[\"ophys\"][\"SegmentationImages\"]\n",
+    "\n",
+    "plt.imshow(nwbfile.processing[\"ophys\"][\"OnePhotonSeriesProcessedBlue\"].data[2200].T, aspect=\"auto\", cmap=\"Greys\")\n",
+    "plt.title(\"Blue\")\n",
+    "plt.show()\n",
+    "\n",
+    "plt.imshow(images_blue.images[\"pca_blue\"].data[:].T, aspect=\"auto\", cmap=\"Greys\")\n",
+    "plt.title(\"PCA mask\")\n",
+    "plt.show()\n",
+    "\n",
+    "plt.imshow(images_blue.images[\"vasculature\"].data[:].T, aspect=\"auto\", cmap=\"Greys\")\n",
+    "plt.title(\"Vasculature mask\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5b8067a7-7cc8-4d39-89e2-1845e0528b2d",
+   "metadata": {},
+   "source": [
+    "The PCA mask for the violet channel on the binned session image can be accessed from \n",
+    "`nwbfile.processing[\"ophys\"][\"SegmentationImagesProcessedViolet\"]`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 178,
+   "id": "71eb574d-ad37-4754-b7ff-83fba91b7622",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <style>\n",
+       "            .container-fields {\n",
+       "                font-family: \"Open Sans\", Arial, sans-serif;\n",
+       "            }\n",
+       "            .container-fields .field-value {\n",
+       "                color: #00788E;\n",
+       "            }\n",
+       "            .container-fields details > summary {\n",
+       "                cursor: pointer;\n",
+       "                display: list-item;\n",
+       "            }\n",
+       "            .container-fields details > summary:hover {\n",
+       "                color: #0A6EAA;\n",
+       "            }\n",
+       "        </style>\n",
+       "        \n",
+       "        <script>\n",
+       "            function copyToClipboard(text) {\n",
+       "                navigator.clipboard.writeText(text).then(function() {\n",
+       "                    console.log('Copied to clipboard: ' + text);\n",
+       "                }, function(err) {\n",
+       "                    console.error('Could not copy text: ', err);\n",
+       "                });\n",
+       "            }\n",
+       "\n",
+       "            document.addEventListener('DOMContentLoaded', function() {\n",
+       "                let fieldKeys = document.querySelectorAll('.container-fields .field-key');\n",
+       "                fieldKeys.forEach(function(fieldKey) {\n",
+       "                    fieldKey.addEventListener('click', function() {\n",
+       "                        let accessCode = fieldKey.getAttribute('title').replace('Access code: ', '');\n",
+       "                        copyToClipboard(accessCode);\n",
+       "                    });\n",
+       "                });\n",
+       "            });\n",
+       "        </script>\n",
+       "        <div class='container-wrap'><div class='container-header'><div class='xr-obj-type'><h3>SegmentationImagesProcessedViolet (Images)</h3></div></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['description']\">description:</span> <span class=\"field-value\">Contains the PCA mask for the violet channel on the binned session image.</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['images']\"><b>images (1)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['images']['pca_violet']\"><b>pca_violet</b></summary></details></details></div>"
+      ],
+      "text/plain": [
+       "SegmentationImagesProcessedViolet pynwb.base.Images at 0x5354146128\n",
+       "Fields:\n",
+       "  description: Contains the PCA mask for the violet channel on the binned session image.\n",
+       "  images: {\n",
+       "    pca_violet <class 'pynwb.image.GrayscaleImage'>\n",
+       "  }"
+      ]
+     },
+     "execution_count": 178,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "images_violet = nwbfile.processing[\"ophys\"][\"SegmentationImagesProcessedViolet\"]\n",
+    "images_violet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 179,
+   "id": "6d75150a-f546-49e5-802f-dc05d74902cd",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.imshow(nwbfile.processing[\"ophys\"][\"OnePhotonSeriesProcessedViolet\"].data[2200].T, aspect=\"auto\", cmap=\"Greys\")\n",
+    "plt.title(\"Violet\")\n",
+    "plt.show()\n",
+    "\n",
+    "plt.imshow(images_violet.images[\"pca_violet\"].data[:].T, aspect=\"auto\", cmap=\"Greys\")\n",
+    "plt.title(\"PCA mask\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bf6d3c4f-db70-4168-9631-dc844719954a",
+   "metadata": {},
+   "source": [
+    "# Access Behavior <a name=\"access-behavior\"></a>\n",
+    "\n",
+    "This section demonstrates how to access behavioral data from the [pynwb.behavior](https://pynwb.readthedocs.io/en/stable/pynwb.behavior.html#module-pynwb.behavior) module.\n",
+    "\n",
+    "The behavior data is stored in the \"behavior\" processing module, which can be accessed as `nwbfile.processing[\"behavior\"]`.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 183,
+   "id": "82dc9045-0ae2-4515-ab56-f8344623c905",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <style>\n",
+       "            .container-fields {\n",
+       "                font-family: \"Open Sans\", Arial, sans-serif;\n",
+       "            }\n",
+       "            .container-fields .field-value {\n",
+       "                color: #00788E;\n",
+       "            }\n",
+       "            .container-fields details > summary {\n",
+       "                cursor: pointer;\n",
+       "                display: list-item;\n",
+       "            }\n",
+       "            .container-fields details > summary:hover {\n",
+       "                color: #0A6EAA;\n",
+       "            }\n",
+       "        </style>\n",
+       "        \n",
+       "        <script>\n",
+       "            function copyToClipboard(text) {\n",
+       "                navigator.clipboard.writeText(text).then(function() {\n",
+       "                    console.log('Copied to clipboard: ' + text);\n",
+       "                }, function(err) {\n",
+       "                    console.error('Could not copy text: ', err);\n",
+       "                });\n",
+       "            }\n",
+       "\n",
+       "            document.addEventListener('DOMContentLoaded', function() {\n",
+       "                let fieldKeys = document.querySelectorAll('.container-fields .field-key');\n",
+       "                fieldKeys.forEach(function(fieldKey) {\n",
+       "                    fieldKey.addEventListener('click', function() {\n",
+       "                        let accessCode = fieldKey.getAttribute('title').replace('Access code: ', '');\n",
+       "                        copyToClipboard(accessCode);\n",
+       "                    });\n",
+       "                });\n",
+       "            });\n",
+       "        </script>\n",
+       "        <div class='container-wrap'><div class='container-header'><div class='xr-obj-type'><h3>behavior (ProcessingModule)</h3></div></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['description']\">description:</span> <span class=\"field-value\">contains processed behavioral data</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']\"><b>data_interfaces (9)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['Position']\"><b>Position</b></summary><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']\"><b>spatial_series (2)</b></summary><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries']\"><b>SpatialSeries</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['description']\">description:</span> <span class=\"field-value\">The x, y, z position of the animal by ViRMEN iteration.</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['conversion']\">conversion:</span> <span class=\"field-value\">0.01</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeries'].fields['reference_frame']\">reference_frame:</span> <span class=\"field-value\">(0,0) is the start of the 'sample' region (or 'cue' region) which varies by maze and task.</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame']\"><b>SpatialSeriesByImFrame</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['description']\">description:</span> <span class=\"field-value\">The position of the animal averaged over the iterations for each frame.</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Position'].fields['spatial_series']['SpatialSeriesByImFrame'].fields['reference_frame']\">reference_frame:</span> <span class=\"field-value\">(0,0) is the start of the 'sample' region (or 'cue' region) which varies by maze and task.</span></div></details></details></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['SensorDots']\"><b>SensorDots</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SensorDots'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SensorDots'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SensorDots'].fields['description']\">description:</span> <span class=\"field-value\">The sensordots by ViRMEN iteration.</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SensorDots'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SensorDots'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SensorDots'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['SensorDots'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['SensorDots'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SensorDots'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SensorDots'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['SensorDotsByImFrame']\"><b>SensorDotsByImFrame</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SensorDotsByImFrame'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SensorDotsByImFrame'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SensorDotsByImFrame'].fields['description']\">description:</span> <span class=\"field-value\">The sensordots averaged over the iterations for each frame.</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SensorDotsByImFrame'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SensorDotsByImFrame'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SensorDotsByImFrame'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['SensorDotsByImFrame'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['SensorDotsByImFrame'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SensorDotsByImFrame'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['SensorDotsByImFrame'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['Velocity']\"><b>Velocity</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Velocity'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Velocity'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Velocity'].fields['description']\">description:</span> <span class=\"field-value\">The velocity of the animal by ViRMEN iteration.</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Velocity'].fields['conversion']\">conversion:</span> <span class=\"field-value\">0.01</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Velocity'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Velocity'].fields['unit']\">unit:</span> <span class=\"field-value\">m/s</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['Velocity'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['Velocity'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Velocity'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['Velocity'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['VelocityByImFrame']\"><b>VelocityByImFrame</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['VelocityByImFrame'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['VelocityByImFrame'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['VelocityByImFrame'].fields['description']\">description:</span> <span class=\"field-value\">The velocity of the animal averaged over the iterations for each frame.</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['VelocityByImFrame'].fields['conversion']\">conversion:</span> <span class=\"field-value\">0.01</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['VelocityByImFrame'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['VelocityByImFrame'].fields['unit']\">unit:</span> <span class=\"field-value\">m/s</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['VelocityByImFrame'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['VelocityByImFrame'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['VelocityByImFrame'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['VelocityByImFrame'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['VelocityGain']\"><b>VelocityGain</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['VelocityGain'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['VelocityGain'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['VelocityGain'].fields['description']\">description:</span> <span class=\"field-value\">The velocity gain by ViRMEN iteration.</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['VelocityGain'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['VelocityGain'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['VelocityGain'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['VelocityGain'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['VelocityGain'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['VelocityGain'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['VelocityGain'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ViewAngle']\"><b>ViewAngle</b></summary><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']\"><b>spatial_series (4)</b></summary><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle']\"><b>PositionViewAngle</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['description']\">description:</span> <span class=\"field-value\">The view angle of the animal by ViRMEN iteration.</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngle'].fields['reference_frame']\">reference_frame:</span> <span class=\"field-value\">(0,0) is the start of the 'sample' region (or 'cue' region) which varies by maze and task.</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame']\"><b>PositionViewAngleByImFrame</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['description']\">description:</span> <span class=\"field-value\">The view angle averaged over the iterations for each frame.</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['PositionViewAngleByImFrame'].fields['reference_frame']\">reference_frame:</span> <span class=\"field-value\">(0,0) is the start of the 'sample' region (or 'cue' region) which varies by maze and task.</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle']\"><b>VelocityViewAngle</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['description']\">description:</span> <span class=\"field-value\">The velocity view angle of the animal by ViRMEN iteration.</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngle'].fields['reference_frame']\">reference_frame:</span> <span class=\"field-value\">(0,0) is the start of the 'sample' region (or 'cue' region) which varies by maze and task.</span></div></details><details><summary style=\"display: list-item; margin-left: 60px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame']\"><b>VelocityViewAngleByImFrame</b></summary><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['description']\">description:</span> <span class=\"field-value\">The view angle averaged over the iterations for each frame.</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 80px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><div style=\"margin-left: 80px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['ViewAngle'].fields['spatial_series']['VelocityViewAngleByImFrame'].fields['reference_frame']\">reference_frame:</span> <span class=\"field-value\">(0,0) is the start of the 'sample' region (or 'cue' region) which varies by maze and task.</span></div></details></details></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['licks']\"><b>licks</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['licks'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['licks'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['licks'].fields['description']\">description:</span> <span class=\"field-value\">The lick response measured over time.</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['licks'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['licks'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['licks'].fields['unit']\">unit:</span> <span class=\"field-value\">a.u.</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['licks'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['licks'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['licks'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['licks'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['TTLs']\"><b>TTLs</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['TTLs'].fields['description']\">description:</span> <span class=\"field-value\">The times when the eye tracking and/or imaging was on determined from the ViRMEN system.</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['data_interfaces']['TTLs'].fields['id']\"><b>id</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['TTLs'].fields['colnames']\">colnames:</span> <span class=\"field-value\">('event_times', 'label', 'event_description')</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['data_interfaces']['TTLs'].fields['columns']\">columns:</span> <span class=\"field-value\">(<hdmf.common.table.VectorIndex object at 0x13fb8d950>, <hdmf.common.table.VectorData object at 0x13fb8fe90>, <hdmf.common.table.VectorData object at 0x13fb8ebd0>, <hdmf.common.table.VectorData object at 0x13fb8d4d0>)</span></div></details></details></div>"
+      ],
+      "text/plain": [
+       "behavior pynwb.base.ProcessingModule at 0x5303248656\n",
+       "Fields:\n",
+       "  data_interfaces: {\n",
+       "    Position <class 'pynwb.behavior.Position'>,\n",
+       "    SensorDots <class 'pynwb.base.TimeSeries'>,\n",
+       "    SensorDotsByImFrame <class 'pynwb.base.TimeSeries'>,\n",
+       "    TTLs <class 'abc.AnnotatedEventsTable'>,\n",
+       "    Velocity <class 'pynwb.base.TimeSeries'>,\n",
+       "    VelocityByImFrame <class 'pynwb.base.TimeSeries'>,\n",
+       "    VelocityGain <class 'pynwb.base.TimeSeries'>,\n",
+       "    ViewAngle <class 'pynwb.behavior.CompassDirection'>,\n",
+       "    licks <class 'pynwb.base.TimeSeries'>\n",
+       "  }\n",
+       "  description: contains processed behavioral data"
+      ]
+     },
+     "execution_count": 183,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nwbfile.processing[\"behavior\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1f2545d3-55d2-4a3e-a8e0-fe046331bc72",
+   "metadata": {},
+   "source": [
+    "## Access Position\n",
+    "\n",
+    "[SpatialSeries](https://pynwb.readthedocs.io/en/stable/pynwb.behavior.html#pynwb.behavior.SpatialSeries) is a subclass of [TimeSeries](https://pynwb.readthedocs.io/en/stable/pynwb.base.html#pynwb.base.TimeSeries) that represents data in space, such as the spatial direction, e.g., of gaze or travel, or position of an animal over time.\n",
+    "\n",
+    "The x, y (z) position of the animal is stored stored in `SpatialSeries` object inside the [Position](https://pynwb.readthedocs.io/en/stable/pynwb.behavior.html#pynwb.behavior.Position) container.\n",
+    "\n",
+    "The Position container can be accessed as `nwbfile.processing[\"behavior\"][\"Position\"]`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 184,
+   "id": "62f8542f-fa13-49d6-9478-85601f3d8c7c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "        <style>\n",
+       "            .container-fields {\n",
+       "                font-family: \"Open Sans\", Arial, sans-serif;\n",
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+       "            .container-fields .field-value {\n",
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+       "            }\n",
+       "            .container-fields details > summary {\n",
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+       "                color: #0A6EAA;\n",
+       "            }\n",
+       "        </style>\n",
+       "        \n",
+       "        <script>\n",
+       "            function copyToClipboard(text) {\n",
+       "                navigator.clipboard.writeText(text).then(function() {\n",
+       "                    console.log('Copied to clipboard: ' + text);\n",
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+       "                    console.error('Could not copy text: ', err);\n",
+       "                });\n",
+       "            }\n",
+       "\n",
+       "            document.addEventListener('DOMContentLoaded', function() {\n",
+       "                let fieldKeys = document.querySelectorAll('.container-fields .field-key');\n",
+       "                fieldKeys.forEach(function(fieldKey) {\n",
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+       "                        let accessCode = fieldKey.getAttribute('title').replace('Access code: ', '');\n",
+       "                        copyToClipboard(accessCode);\n",
+       "                    });\n",
+       "                });\n",
+       "            });\n",
+       "        </script>\n",
+       "        <div class='container-wrap'><div class='container-header'><div class='xr-obj-type'><h3>Position</h3></div></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['spatial_series']\"><b>spatial_series (2)</b></summary><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['spatial_series']['SpatialSeries']\"><b>SpatialSeries</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['spatial_series']['SpatialSeries'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['spatial_series']['SpatialSeries'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['spatial_series']['SpatialSeries'].fields['description']\">description:</span> <span class=\"field-value\">The x, y, z position of the animal by ViRMEN iteration.</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['spatial_series']['SpatialSeries'].fields['conversion']\">conversion:</span> <span class=\"field-value\">0.01</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['spatial_series']['SpatialSeries'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['spatial_series']['SpatialSeries'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['spatial_series']['SpatialSeries'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['spatial_series']['SpatialSeries'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['spatial_series']['SpatialSeries'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['spatial_series']['SpatialSeries'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['spatial_series']['SpatialSeries'].fields['reference_frame']\">reference_frame:</span> <span class=\"field-value\">(0,0) is the start of the 'sample' region (or 'cue' region) which varies by maze and task.</span></div></details><details><summary style=\"display: list-item; margin-left: 20px;\" class=\"container-fields field-key\" title=\".fields['spatial_series']['SpatialSeriesByImFrame']\"><b>SpatialSeriesByImFrame</b></summary><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['spatial_series']['SpatialSeriesByImFrame'].fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['spatial_series']['SpatialSeriesByImFrame'].fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['spatial_series']['SpatialSeriesByImFrame'].fields['description']\">description:</span> <span class=\"field-value\">The position of the animal averaged over the iterations for each frame.</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['spatial_series']['SpatialSeriesByImFrame'].fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['spatial_series']['SpatialSeriesByImFrame'].fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['spatial_series']['SpatialSeriesByImFrame'].fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['spatial_series']['SpatialSeriesByImFrame'].fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 40px;\" class=\"container-fields field-key\" title=\".fields['spatial_series']['SpatialSeriesByImFrame'].fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['spatial_series']['SpatialSeriesByImFrame'].fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['spatial_series']['SpatialSeriesByImFrame'].fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><div style=\"margin-left: 40px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['spatial_series']['SpatialSeriesByImFrame'].fields['reference_frame']\">reference_frame:</span> <span class=\"field-value\">(0,0) is the start of the 'sample' region (or 'cue' region) which varies by maze and task.</span></div></details></details></div>"
+      ],
+      "text/plain": [
+       "Position pynwb.behavior.Position at 0x5353902800\n",
+       "Fields:\n",
+       "  spatial_series: {\n",
+       "    SpatialSeries <class 'pynwb.behavior.SpatialSeries'>,\n",
+       "    SpatialSeriesByImFrame <class 'pynwb.behavior.SpatialSeries'>\n",
+       "  }"
+      ]
+     },
+     "execution_count": 184,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nwbfile.processing[\"behavior\"][\"Position\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "21e02705-d97c-4d4d-bdf8-ed4b5feb40c3",
+   "metadata": {},
+   "source": [
+    "The x, y, z position of the animal by ViRMEN iteration can be accessed as `nwbfile.processing[\"behavior\"][\"Position\"][\"SpatialSeries\"]`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 192,
+   "id": "d9202caa-01e4-4307-a281-61f23c187774",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <style>\n",
+       "            .container-fields {\n",
+       "                font-family: \"Open Sans\", Arial, sans-serif;\n",
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+       "                color: #0A6EAA;\n",
+       "            }\n",
+       "        </style>\n",
+       "        \n",
+       "        <script>\n",
+       "            function copyToClipboard(text) {\n",
+       "                navigator.clipboard.writeText(text).then(function() {\n",
+       "                    console.log('Copied to clipboard: ' + text);\n",
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+       "                    console.error('Could not copy text: ', err);\n",
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+       "\n",
+       "            document.addEventListener('DOMContentLoaded', function() {\n",
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+       "            });\n",
+       "        </script>\n",
+       "        <div class='container-wrap'><div class='container-header'><div class='xr-obj-type'><h3>SpatialSeries</h3></div></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['description']\">description:</span> <span class=\"field-value\">The x, y, z position of the animal by ViRMEN iteration.</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['conversion']\">conversion:</span> <span class=\"field-value\">0.01</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['reference_frame']\">reference_frame:</span> <span class=\"field-value\">(0,0) is the start of the 'sample' region (or 'cue' region) which varies by maze and task.</span></div></div>"
+      ],
+      "text/plain": [
+       "SpatialSeries pynwb.behavior.SpatialSeries at 0x5364042576\n",
+       "Fields:\n",
+       "  comments: no comments\n",
+       "  conversion: 0.01\n",
+       "  data: <HDF5 dataset \"data\": shape (407877, 3), type \"<f8\">\n",
+       "  description: The x, y, z position of the animal by ViRMEN iteration.\n",
+       "  interval: 1\n",
+       "  offset: 0.0\n",
+       "  reference_frame: (0,0) is the start of the 'sample' region (or 'cue' region) which varies by maze and task.\n",
+       "  resolution: -1.0\n",
+       "  timestamps: <HDF5 dataset \"timestamps\": shape (407877,), type \"<f8\">\n",
+       "  timestamps_unit: seconds\n",
+       "  unit: meters"
+      ]
+     },
+     "execution_count": 192,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "position_by_virmen = nwbfile.processing[\"behavior\"][\"Position\"][\"SpatialSeries\"]\n",
+    "position_by_virmen"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dc79bfb0-b8c6-40ac-8932-e44b98071440",
+   "metadata": {},
+   "source": [
+    "The x, y, position of the animal averaged over the iterations for each frame can be accessed as `nwbfile.processing[\"behavior\"][\"Position\"][\"SpatialSeriesByImFrame\"]`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 195,
+   "id": "f7ea6032-e450-4a41-a2cf-4383afa0c679",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <style>\n",
+       "            .container-fields {\n",
+       "                font-family: \"Open Sans\", Arial, sans-serif;\n",
+       "            }\n",
+       "            .container-fields .field-value {\n",
+       "                color: #00788E;\n",
+       "            }\n",
+       "            .container-fields details > summary {\n",
+       "                cursor: pointer;\n",
+       "                display: list-item;\n",
+       "            }\n",
+       "            .container-fields details > summary:hover {\n",
+       "                color: #0A6EAA;\n",
+       "            }\n",
+       "        </style>\n",
+       "        \n",
+       "        <script>\n",
+       "            function copyToClipboard(text) {\n",
+       "                navigator.clipboard.writeText(text).then(function() {\n",
+       "                    console.log('Copied to clipboard: ' + text);\n",
+       "                }, function(err) {\n",
+       "                    console.error('Could not copy text: ', err);\n",
+       "                });\n",
+       "            }\n",
+       "\n",
+       "            document.addEventListener('DOMContentLoaded', function() {\n",
+       "                let fieldKeys = document.querySelectorAll('.container-fields .field-key');\n",
+       "                fieldKeys.forEach(function(fieldKey) {\n",
+       "                    fieldKey.addEventListener('click', function() {\n",
+       "                        let accessCode = fieldKey.getAttribute('title').replace('Access code: ', '');\n",
+       "                        copyToClipboard(accessCode);\n",
+       "                    });\n",
+       "                });\n",
+       "            });\n",
+       "        </script>\n",
+       "        <div class='container-wrap'><div class='container-header'><div class='xr-obj-type'><h3>SpatialSeriesByImFrame (SpatialSeries)</h3></div></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['resolution']\">resolution:</span> <span class=\"field-value\">-1.0</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['comments']\">comments:</span> <span class=\"field-value\">no comments</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['description']\">description:</span> <span class=\"field-value\">The position of the animal averaged over the iterations for each frame.</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['conversion']\">conversion:</span> <span class=\"field-value\">1.0</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['offset']\">offset:</span> <span class=\"field-value\">0.0</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['unit']\">unit:</span> <span class=\"field-value\">meters</span></div><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['data']\"><b>data</b></summary></details><details><summary style=\"display: list-item; margin-left: 0px;\" class=\"container-fields field-key\" title=\".fields['timestamps']\"><b>timestamps</b></summary></details><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['timestamps_unit']\">timestamps_unit:</span> <span class=\"field-value\">seconds</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['interval']\">interval:</span> <span class=\"field-value\">1</span></div><div style=\"margin-left: 0px;\" class=\"container-fields\"><span class=\"field-key\" title=\".fields['reference_frame']\">reference_frame:</span> <span class=\"field-value\">(0,0) is the start of the 'sample' region (or 'cue' region) which varies by maze and task.</span></div></div>"
+      ],
+      "text/plain": [
+       "SpatialSeriesByImFrame pynwb.behavior.SpatialSeries at 0x5364040336\n",
+       "Fields:\n",
+       "  comments: no comments\n",
+       "  conversion: 1.0\n",
+       "  data: <HDF5 dataset \"data\": shape (37341, 2), type \"<f4\">\n",
+       "  description: The position of the animal averaged over the iterations for each frame.\n",
+       "  interval: 1\n",
+       "  offset: 0.0\n",
+       "  reference_frame: (0,0) is the start of the 'sample' region (or 'cue' region) which varies by maze and task.\n",
+       "  resolution: -1.0\n",
+       "  timestamps: <HDF5 dataset \"timestamps\": shape (37341,), type \"<f8\">\n",
+       "  timestamps_unit: seconds\n",
+       "  unit: meters"
+      ]
+     },
+     "execution_count": 195,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "position_by_frame = nwbfile.processing[\"behavior\"][\"Position\"][\"SpatialSeriesByImFrame\"]\n",
+    "position_by_frame"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "48edfe90-2521-490d-82a5-0bffec26d241",
+   "metadata": {},
+   "source": [
+    "The \"SpatialSeriesByImFrame\" has the same time basis as the imaging data (blue frames):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 199,
+   "id": "6a95a1a4-032a-4c2c-8491-eb6da66a2640",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "((37341,), (37341,))"
+      ]
+     },
+     "execution_count": 199,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "position_by_frame.timestamps.shape, photon_series_blue.timestamps.shape,"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "85c109d2-5d11-4a79-9596-a601a9afce6b",
+   "metadata": {},
+   "source": [
+    "# View NWB <a name=\"view-nwb\"></a>\n",
+    "\n",
+    "This section demonstrates how to visualise the contents of an NWB file interactively using `NWBWidgets`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 202,
+   "id": "36ffd849-5e5a-4837-a032-8ea966d9c1da",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "607a9c203521452fb6caa35b849175e2",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "VBox(children=(HBox(children=(Label(value='session_description:', layout=Layout(max_height='40px', max_width='…"
+      ]
+     },
+     "execution_count": 202,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from nwbwidgets import nwb2widget\n",
+    "\n",
+    "nwb2widget(nwbfile)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "53208589-a659-433c-a699-1c693b0446e3",
+   "metadata": {},
+   "source": [
+    "We also use [Neurosift](https://github.com/flatironinstitute/neurosift), a platform for the visualization of neuroscience data in the web browser."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cfeec2d3-0ea4-463d-93ca-627484937649",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}