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