Information-based functional brain mapping

TLDR

High‑resolution neuroimaging and multielectrode recordings generate vast multivariate data, yet conventional local‑averaging approaches risk masking the most informative neural patterns, prompting a shift from activation‑based to information‑driven brain mapping. The study asks where in the brain the activity pattern contains information about the experimental condition. A searchlight scans the brain volume, applying multivariate analysis at each location to identify informative patterns.

Abstract

The development of high-resolution neuroimaging and multielectrode electrophysiological recording provides neuroscientists with huge amounts of multivariate data. The complexity of the data creates a need for statistical summary, but the local averaging standardly applied to this end may obscure the effects of greatest neuroscientific interest. In neuroimaging, for example, brain mapping analysis has focused on the discovery of activation, i.e., of extended brain regions whose average activity changes across experimental conditions. Here we propose to ask a more general question of the data: Where in the brain does the activity pattern contain information about the experimental condition? To address this question, we propose scanning the imaged volume with a "searchlight," whose contents are analyzed multivariately at each location in the brain.