Temporal embedding and spatiotemporal feature selection boost multi-voxel pattern analysis decoding accuracy.

ABSTRACT:

Background

In fMRI decoding, temporal embedding of spatial features of the brain allows the incorporation of brain activity dynamics into the multivariate pattern classification process, and provides enriched information about stimulus-specific response patterns and potentially improved prediction accuracy.

New method

This study investigates the possibility of enhancing the classification performance by exploring temporal embedding, to identify the optimum combination of spatiotemporal features based on their classification performance. We investigated the importance of spatiotemporal feature selection using a slow event-related design adapted from the classic Haxby study (Haxby et al., 2001). Data were collected using a multiband fMRI sequence with temporal resolution of 0.

SUBMITTER: Choupan J 

PROVIDER: S-EPMC9419668 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature