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. 2022 Jun 23;16:835772. doi: 10.3389/fninf.2022.835772

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Copyright © 2022 Fang, Poskanzer and Anzellotti.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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PyMVPD workflow. Analyzing data with the PyMVPD toolbox consists of three steps: (1) analysis specification; (2) data loading; and (3) analysis execution. In step 1, users are required to specify the functional data, masks for both the predictor and the target region, as well as the type of MVPD model to perform the following analyses. These details can be specified by editing the Python script run_MVPD.py. Next, users can proceed with step 2, which loads neuroimaging data and converts it to a suitable format. Finally, step 3 runs the MVPD model and generates the analysis results, which are saved in a user-specified directory.