PyMVPD: A Toolbox for Multivariate Pattern Dependence.

ABSTRACT: Cognitive tasks engage multiple brain regions. Studying how these regions interact is key to understand the neural bases of cognition. Standard approaches to model the interactions between brain regions rely on univariate statistical dependence. However, newly developed methods can capture multivariate dependence. Multivariate pattern dependence (MVPD) is a powerful and flexible approach that trains and tests multivariate models of the interactions between brain regions using independent data. In this article, we introduce PyMVPD: an open source toolbox for multivariate pattern dependence. The toolbox includes linear regression models and artificial neural network models of the interactions between regions. It is designed to be easily customizable. We demonstrate example applications of Py

SUBMITTER: Fang M 

PROVIDER: S-EPMC9262406 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature