Brain dynamics and temporal trajectories during task and naturalistic processing.

ABSTRACT: Human functional Magnetic Resonance Imaging (fMRI) data are acquired while participants engage in diverse perceptual, motor, cognitive, and emotional tasks. Although data are acquired temporally, they are most often treated in a quasi-static manner. Yet, a fuller understanding of the mechanisms that support mental functions necessitates the characterization of dynamic properties. Here, we describe an approach employing a class of recurrent neural networks called reservoir computing, and show the feasibility and potential of using it for the analysis of temporal properties of brain data. We show that reservoirs can be used effectively both for condition classification and for characterizing lower-dimensional "trajectories" of temporal data. Classification accuracy was approximately 90% for

SUBMITTER: Venkatesh M 

PROVIDER: S-EPMC6545598 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature