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This repository features DataJoint pipeline design for facial behavior tracking of head-fixed rodent with MouseLand's Facemap.
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The pipeline presented here is not a complete pipeline by itself, but rather a modular design of tables and dependencies specific to the Facemap workflow.
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This modular pipeline element can be flexibly attached downstream to any particular design of experiment session, thus assembling a fully functional facemap pipeline.
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See the Element Facemap documentation for the background information and development timeline.
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For more information on the DataJoint Elements project, please visit https://elements.datajoint.org. This work is supported by the National Institutes of Health.
As the diagram depicts, the facemap element starts immediately downstream from Session and Device. We provide an example workflow with a pipeline script that models combining this Element with the corresponding Element-Session.
- VideoRecording: All recordings from a given session.
- RecordingInfo: Meta information of each video recording (number of frames, pixel lengths, fps, etc.)
- FacialSignal: Set of results from SVD of user defined regions.
- FacialSignal.Region: Information about each region (region name, pixel indices, etc)
- FacialSignal.MovieSVD: Principle components, projections, singular values for each movie region
- FacialSignal.MotionSVD: Principle components, projections, singular values for each motion region
- FacialSignal.Summary: Average frame, average motion, spatial binning factor
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Install
element-facemap
pip install element-facemap
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Upgrade
element-facemap
previously installed withpip
pip install --upgrade element-facemap
To activate the element-facemap
, ones need to provide:
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Schema names
- schema name for the facial behavior estimation module
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Upstream tables
- Session table: A set of keys identifying a recording session (see Element-Session).
- Device table: A Device table to specify a video recording.
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Utility functions
- get_facemap_root_data_dir(): Returns your root data directory.
- get_facemap_processed_data_dir(): Returns your output root data directory
- get_facemap_video_files(): Returns your video files
See the workflow-facemap repository for an example usage of this Facemap Element.
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If your work uses DataJoint and DataJoint Elements, please cite the respective Research Resource Identifiers (RRIDs) and manuscripts.
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DataJoint for Python or MATLAB
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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
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DataJoint (RRID:SCR_014543) - DataJoint for
<Select Python or MATLAB>
(version<Enter version number>
)
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DataJoint Elements
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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
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DataJoint Elements (RRID:SCR_021894) - Element Facemap (version
<Enter version number>
)
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