WIP - started a page for opm coregistration

getting_started/fieldline.md

@@ -171,4 +171,4 @@ Since channels in a FieldTrip data structure are required have a unique channel
 
 # Coregistration
 
-FIXME: in this section we will document (or link to) the different methods to coregister the OPM sensors with the head and with the anatomical MRI.
+There is a dedicated [tutorial](/tutorial/coregistration_opm) that deals with various ways to coregister the OPM sensors with the head and the anatomical MRI. 

tutorial.md

@@ -26,6 +26,7 @@ When adding or contributing to the tutorials please consider the [documentation
 - [Visual or manual artifact rejection](/tutorial/visual_artifact_rejection)
 - [Automatic artifact rejection](/tutorial/automatic_artifact_rejection)
 - [Cleaning artifacts using ICA](/tutorial/ica_artifact_cleaning)
+- [Coregistration of optically pumped magnetometer (OPM) data](/tutorial/coregistration_opm)
 
 ## Sensor-level analyses
 

tutorial/preprocessing_opm.md

@@ -42,7 +42,7 @@ In this tutorial we will take the following steps:
 - Compute the averaged ERFs using **[ft_timelockanalysis](/reference/ft_timelockanalysis)**
 - Concatenate the data over the three positions using **[ft_appendtimelock](/reference/ft_appendtimelock)**
 - Improve the whole-head ERF topoplot using **[ft_prepare_layout](/reference/ft_prepare_layout)**
-- Plotting the OPM sensor positions in 3D using **[ft_plot_sens]()/reference/plotting/ft_plot_sens)**
+- Plotting the OPM sensor positions in 3D using **[ft_plot_sens](/reference/plotting/ft_plot_sens)**
 
 ## Initial look at the data
 
@@ -572,7 +572,7 @@ Again it makes sense to look at the specific selection of OPM sensors that was u
 
 This tutorial gave an introduction on processing OPM data, specifically dealing with a small OPM array that was used to record activity sequentially over multiple locations that together cover the region-of-interest. Furthermore, it showed how to plot the data topographically, given that not the whole head was covered by the measurement.  
 
-You may want to continue with the more general [tutorials](/tutorial/) on processing MEG (and EEG) data, or have a look at the [system specific details](/getting_started) for the OPM data that you are working with.
+You may want to continue with the more general [tutorials](/tutorial/) on processing MEG (and EEG) data, or have a look at the [system specific details](/getting_started) for the OPM data that you are working with. Also, you could have a look at the tutorial about [coregistration of OPM data](/tutorial/coregistration_opm).
 
 Furthermore, you can explore example scripts that deal with OPMs:
 

tutorial/sourcemodel.md

@@ -33,7 +33,7 @@ Content is coming soon!
 
 ### Preprocessing of the anatomical MRI, reslicing and coregistration
 
-The anatomical preprocessing is done in MATLAB with FieldTrip. The goal of this step is to create a file with a T1w anatomical image that can be used for the creation of two 'geometric objects': a volume conduction model of the head (not covered in this tutorial), and a cortical sheet based source model. Moreover, this image will be used to create coregistration information to the different coordinate systems involved. One annoying thing to be aware of, and to think about in advance, is the fact that typically different parts of the pipeline assume (or require) different conventions of coordinate systems. Specifically, geometric information (sensor locations) in MEG/EEG (MEEG) data is typically expressed in a coordinate system that is defined based on external anatomical landmarks, whereas software used for processing of structural data usually requires coordinates to be expressed according to brain-anatomy related landmarks, such as the anterior and posterior commissures. More information about coordinate systems can be found at the [frequently asked question about coordinate systems](/faq/coordsys). To make a long story short, for now it suffices to know that you're safe if you know how to convert back and forth between the different relevant coordinate systems. The least error-prone and most convenient way to do this, is to create a well-defined reference anatomical image, which will be created with the following step
+The anatomical preprocessing is done in MATLAB with FieldTrip. The goal of this step is to create a file with a T1w anatomical image that can be used for the creation of two 'geometric objects': a volume conduction model of the head (not covered in this tutorial), and a cortical sheet based source model. Moreover, this image will be used to create coregistration information to the different coordinate systems involved. One annoying thing to be aware of, and to think about in advance, is the fact that typically different parts of the pipeline assume (or require) different conventions of coordinate systems. Specifically, geometric information (sensor locations) in MEG/EEG (MEEG) data is typically expressed in a coordinate system that is defined based on external anatomical landmarks, whereas software used for processing of structural data usually requires coordinates to be expressed according to brain-anatomy related landmarks, such as the anterior and posterior commissures. More information about coordinate systems can be found at the [frequently asked question about coordinate systems](/faq/coordsys). To make a long story short, for now it suffices to know that you're safe if you know how to convert back and forth between the different relevant coordinate systems. The least error-prone and most convenient way to do this, is to create a well-defined reference anatomical image, which will be created with the following steps
 
 - read the anatomical images into MATLAB with **[ft_read_mri](/reference/fileio/ft_read_mri)**.
 - ensure that the coordinate system of the mri is defined according to the M/EEG device's coordinate system, which can be checked with **[ft_determine_coordsys](/reference/utilities/ft_determine_coordsys)** and imposed with **[ft_volumerealign](/reference/ft_volumerealign)**.