An empirical evaluation of functional alignment using inter-subject decoding.

ABSTRACT: Inter-individual variability in the functional organization of the brain presents a major obstacle to identifying generalizable neural coding principles. Functional alignment-a class of methods that matches subjects' neural signals based on their functional similarity-is a promising strategy for addressing this variability. To date, however, a range of functional alignment methods have been proposed and their relative performance is still unclear. In this work, we benchmark five functional alignment methods for inter-subject decoding on four publicly available datasets. Specifically, we consider three existing methods: piecewise Procrustes, searchlight Procrustes, and piecewise Optimal Transport. We also introduce and benchmark two new extensions of functional alignment methods: piecewise

SUBMITTER: Bazeille T 

PROVIDER: S-EPMC11653789 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature