DataJoint-NWB Showcase

This project showcases published datasets with matching DataJoint pipelines and NWB 2.0 export capability.

Each showcase comprises the following:

• Basic project summary
• The DataJoint pipeline to ingest the data
• Notebook demonstration of working with the data pipeline to query, extract data and recreate some representative figures
• Scripts to export the data from the DataJoint pipeline into NWB 2.0 files.

License

This code and documentation can be distributed under the Creative Commons Attribution-ShareAlike 4.0 (CC-BY-SA-4.0) International License

Prerequisite

The materials presented in the following projects assume basic familiarity with DataJoint, and the DataJoint languague in Python. An introduction to DataJoint is available here, with a short getting-started tutorial here.

To setup and execute the projects in this repository, MySQL database is required. The MySQL database can be a local database setup or on cloud, for more details on setting up database server administration, see here, more conveniently, a Docker image for DataJoint-compatible MySQL can be found here.

The Datasets

1. Chen et al Neuron 2017

Publication: http://dx.doi.org/10.1016/j.neuron.2017.05.005

Data: https://dx.doi.org/10.6080/K0S180F9 (Not available)

Data repository: https://www.dropbox.com/sh/i5kqq99wq4qbr5o/AABagZ8a9uIiZKxrw9MK7OYIa/nwb2/tsai_wen_nwb2?dl=0&subfolder_nav_tracking=1

Project repository: https://github.com/vathes/DJ-NWB-Chen-2017

2. Guo/Inagaki et al Nature 2017

Publication: https://dx.doi.org/10.1038/nature22324

Data: https://dx.doi.org/10.6080/K03F4MH (Not available)

Data repository:

Project repository: https://github.com/vathes/DJ-NWB-Guo-Inagaki-2017

3. Yu/Gutnisky et al Nat Neurosci 2016

Publication: https://dx.doi.org/10.1038/nn.4412

Data: https://doi.org/10.6080/K0T43R01

Data repository: http://crcns.org/data-sets/ssc/ssc-7

Project repository: https://github.com/vathes/DJ-NWB-Yu-Gutnisky-2016

4. Li/Daie et al Nature 2016

Publication: https://dx.doi.org/10.1038/nature17643

Data: https://dx.doi.org/10.6080/K04M92GX (Incorrect)

Data repository: https://crcns.org/data-sets/motor-cortex/alm-3

Project repository: https://github.com/vathes/DJ-NWB-Li-Daie-2015-2016

5. Li et al Nature 2015 (a)

Publication: https://dx.doi.org/10.1038/nature14178, PMID 25731172

Data: https://dx.doi.org/10.6080/K0MS3QNT

Data repository: https://crcns.org/data-sets/motor-cortex/alm-1

Project repository: https://github.com/vathes/DJ-NWB-Li-Daie-2015-2016

6. Li et al Nature 2015 (b)

Publication: https://doi.org/10.1038/nature14178

Data: http://dx.doi.org/10.6080/K04M92GX

Data repository: http://crcns.org/data-sets/motor-cortex/alm-2

Project repository: https://github.com/vathes/DJ-NWB-Li-2015b

7. Hires, Gutnisky et al Elife 2015.

Publication: https://dx.doi.org/10.7554/eLife.06619

Data: http://dx.doi.org/10.6080/K0MG7MDV

Data repository: https://crcns.org/data-sets/ssc/ssc-5

Project repository: https://github.com/vathes/DJ-NWB-Hires-Gutnisky-2015

8. Inagaki et al Nature 2019

Publication: https://doi.org/10.1038/s41586-019-0919-7

Data:

Data repository:

Project repository: https://github.com/vathes/DJ-NWB-Inagaki-2018-2019

9. Inagaki et al JNS 2018

Publication: https://doi.org/10.1523/JNEUROSCI.3152-17.2018

Data:

Data repository:

Project repository: https://github.com/vathes/DJ-NWB-Inagaki-2018-2019

10. Gao-2018

Publication: https://www.nature.com/articles/s41586-018-0633-x

Data: https://dx.doi.org/10.6080/K03F4MH2

Data repository: http://crcns.org/data-sets/motor-cortex/alm-4/

Project repository: https://github.com/vathes/DJ-NWB-Gao-2018

11. Economo et al 2018

Publication: https://doi.org/10.1038/s41586-018-0642-9

Data: 10.25378/janelia.7007846

Data repository:

Project repository: https://github.com/vathes/DJ-NWB-Economo-2018