Predicting brain activation maps for arbitrary tasks with cognitive encoding models.

ABSTRACT: A deep understanding of the neural architecture of mental function should enable the accurate prediction of a specific pattern of brain activity for any psychological task, based only on the cognitive functions known to be engaged by that task. Encoding models (EMs), which predict neural responses from known features (e.g., stimulus properties), have succeeded in circumscribed domains (e.g., visual neuroscience), but implementing domain-general EMs that predict brain-wide activity for arbitrary tasks has been limited mainly by availability of datasets that 1) sufficiently span a large space of psychological functions, and 2) are sufficiently annotated with such functions to allow robust EM specification. We examine the use of EMs based on a formal specification of psychological function, t

SUBMITTER: Walters J 

PROVIDER: S-EPMC9981816 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature