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DataJoint Elements for Neurophysiology

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DataJoint Elements provides an efficient approach for neuroscience labs to create and manage scientific data workflows: the complex multi-step methods for data collection, preparation, processing, analysis, and modeling that researchers must perform in the course of an experimental study. The work is derived from the developments in leading neuroscience projects and uses the DataJoint framework for defining, deploying, and sharing their data workflows.

DataJoint

the open-source framework for data pipelines and automated computational workflows + related documentation, tools, and utilities.

DataJoint Elements

a collection of curated modules for assembling workflows for the major modalities of neurophysiology experiments + related documentation, tools, and utilities.

An overview of the principles of DataJoint workflows and the goals of DataJoint Elements are described in the position paper "DataJoint Elements: Data Workflows for Neurophysiology".

Project Structure

DataJoint Elements

DataJoint Element Example workflow Background, Features, and Status Tutorial Video
Lab management See Session Link See Session
Animal management See Session Link See Session
Experiment Session management Lab, subject and session management Link Link
Extracellular array electrophysiology Neuropixels Link Link
Calcium imaging Multiphoton laser scanning Link Link
Miniscope imaging UCLA Miniscope Link Link
DeepLabCut Workflow for pose tracking Link Link
Event- and trial-based experiments Workflow for Neuropixels
Workflow for multiphoton laser scanning
Link Link
Electrode localization for Neuropixels Workflow for Neuropixels Link Link
Facemap Link
Visual Stimulation Link Link

DataJoint framework

DataJoint Interfaces

DataJoint Online Training

Feedback

DataJoint and DataJoint Elements are supported by NIH grant U24 NS116470 for disseminating open-source software for neuroscience research. Your feedback is essential for continued funding. Your feedback also helps shape the technology development roadmap for the DataJoint ecosystem. Please tell us about your projects by filling out the DataJoint Census.

Citation

DataJoint for Python or MATLAB

Yatsenko D, Reimer J, Ecker AS, Walker EY, Sinz F, Berens P, Hoenselaar A, Cotton RJ, Siapas AS, Tolias AS. DataJoint: managing big scientific data using MATLAB or Python. bioRxiv. 2015 Jan 1:031658. doi: https://doi.org/10.1101/031658


DataJoint (RRID:SCR_014543) - DataJoint for <Select Python or MATLAB> (version <Enter version number>)

DataJoint Elements

Yatsenko D, Nguyen T, Shen S, Gunalan K, Turner CA, Guzman R, Sasaki M, Sitonic D, Reimer J, Walker EY, Tolias AS. DataJoint Elements: Data Workflows for Neurophysiology. bioRxiv. 2021 Jan 1. doi: https://doi.org/10.1101/2021.03.30.437358


DataJoint Elements (RRID:SCR_021894) - Element Enter Element name (version <Enter version number>)