Data architecture and visualization for a large-scale neuroscience collaboration

The International Brain Laboratory,; Bonacchi, N.; Chapuis, G.; Churchland, A. K.; Harris, K. D.; Rossant, C.; Sasaki, M.; Shen, S.; Steinmetz, N. A.; Walker, E. Y.; Winter, O.; Wells, M.

doi:10.1101/827873

bioRxiv · 10.1101/827873

Data architecture and visualization for a large-scale neuroscience collaboration

The International Brain Laboratory,·Bonacchi, N.·Chapuis, G.·Churchland, A. K.·Harris, K. D.·Rossant, C.·Sasaki, M.·Shen, S.·Steinmetz, N. A.·Walker, E. Y.·Winter, O.·Wells, M.

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Abstract

Effective data management is a major challenge for neuroscience labs, and even greater for collaborative projects. In the International Brain laboratory (IBL), ten experimental labs spanning 7 geographically distributed sites measure neural activity across the brains of mice making perceptual decisions. Here, we report a novel, modular architecture that allows users to contribute, access, and analyze data across this collaboration. Users contribute data using a web-based electronic lab notebook (Alyx), which automatically registers recorded data files and uploads them to a central server. Users access data with a lightweight interface, the Open Neurophysiology Environment (ONE), which searches data from all labs and loads it into MATLAB or Python. To analyze data, we have developed pipelines based on DataJoint, which automatically populate a website displaying a graphical summary of results to date. This architecture provides a new framework to contribute, access and analyze data, surmounting many challenges currently faced by neuroscientists.

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The International Brain Laboratory,, Bonacchi, N., Chapuis, G., Churchland, A. K., Harris, K. D., Rossant, C., Sasaki, M., Shen, S., Steinmetz, N. A., Walker, E. Y., Winter, O., Wells, M.. 2019-11-02. Data architecture and visualization for a large-scale neuroscience collaboration. https://doi.org/10.1101/827873

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