DataJoint Element - Experimental trials

• element-event features a DataJoint pipeline design for event, trial, and block management.

• element-event is not a complete workflow by itself, but rather a modular design of tables and dependencies.

• element-event can be flexibly attached to any DataJoint workflow.

• See the Element Event documentation for the background information and development timeline.

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

Element architecture

In diagram below, BehaviorRecording table starts immediately downstream from Session. Recordings can be segmented into both trials, which are assumed to have duration, and events, which may be instantaneous. Researchers may find one or both appropriate for their particular paradigm. A set of trials can be further organized into blocks, representing a larger span of time. We provide an example workflow with a pipeline script that models combining this Element with the corresponding Element-Session.

Trial & Event Schemas

Installation

• Install element-event

  pip install element-event
  

• Upgrade element-event previously installed with pip

  pip install --upgrade element-event
  

Usage

Element activation

To activate the element-event, one need to provide:

1. Schema names for the event or trial module
2. Upstream Session table: A set of keys identifying a recording session (see Element-Session).
3. Utility functions. See example definitions here

For more detail, check the docstring of the element-event:

from element_event import event, trial

help(event.activate)
help(trial.activate)

Element usage

• See the workflow-calcium-imaging, workflow-array-ephys, and workflow-miniscope repositories for example usages of element-event.

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 Event (version <Enter version number>)