Extracting representations of cognition across neuroimaging studies improves brain decoding.

ABSTRACT: Cognitive brain imaging is accumulating datasets about the neural substrate of many different mental processes. Yet, most studies are based on few subjects and have low statistical power. Analyzing data across studies could bring more statistical power; yet the current brain-imaging analytic framework cannot be used at scale as it requires casting all cognitive tasks in a unified theoretical framework. We introduce a new methodology to analyze brain responses across tasks without a joint model of the psychological processes. The method boosts statistical power in small studies with specific cognitive focus by analyzing them jointly with large studies that probe less focal mental processes. Our approach improves decoding performance for 80% of 35 widely-different functional-imaging studies.

SUBMITTER: Mensch A 

PROVIDER: S-EPMC8118532 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature