DataJoint Workflow - Array Electrophysiology

Workflow for extracellular array electrophysiology data acquired with a polytrode probe (e.g. Neuropixels, Neuralynx) using the SpikeGLX or OpenEphys acquisition software and processed with MATLAB-based Kilosort or python-based Kilosort spike sorting software.

A complete electrophysiology workflow can be built using the DataJoint Elements.

• element-lab
• element-animal
• element-session
• element-array-ephys

This repository provides demonstrations for:

1. Set up a workflow using DataJoint Elements (see workflow_array_ephys/pipeline.py)

2. Ingestion of data/metadata based on a predefined file structure, file naming convention, and directory lookup methods (see workflow_array_ephys/paths.py).

3. Ingestion of clustering results.

4. Export of no_curation schema to NWB and DANDI (see notebooks/09-NWB-export.ipynb).

See the Element Array Electrophysiology documentation for the background information and development timeline.

For more information on the DataJoint Elements project, please visit https://elements.datajoint.org. This work is supported by the National Institutes of Health.

Workflow architecture

The electrophysiology workflow presented here uses components from 4 DataJoint Elements (element-lab, element-animal, element-session, element-array-ephys) assembled together to form a fully functional workflow. Note that element-array-ephys offers three schema options, selected via the DataJoint config file, with dj.config['custom']['ephys_mode']

• acute probe insertion, with curated clustering
• chronic probe insertion, with curated clustering
• no-curation, acute probe insertion with kilosort triggered clustering and supported NWB export
• precluster, acute probe insertion with pre-processing steps prior to clustering and curated clustering

Optionally, this can be used in conjunction with element-event and element-electrode-localization.

Installation instructions

The installation instructions can be found at the DataJoint Elements documentation.

Interacting with the DataJoint workflow

Please refer to the workflow-specific Jupyter notebooks for an in-depth explanation of how to ...

1. Run the workflow (03-process.ipynb).

2. Explore the data (05-explore.ipynb).

3. Examine trialized analyses, and establish downstream analyses (07-downstream-analysis.ipynb)

4. Locate probes within the Common Coordinate Framework (08-electrode-localization.ipynb)

5. Export to NWB and DANDI (09-NWB-export.ipynb)

See our YouTube tutorial for a walkthrough of the schemas and functions:

Citation

If your work uses DataJoint and DataJoint Elements, please cite the respective Research Resource Identifiers (RRIDs) and manuscripts.

• 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 Array Electrophysiology (version <Enter version number>)