Dynamic network coding of working-memory domains and working-memory processes.

ABSTRACT: The classic mapping of distinct aspects of working memory (WM) to mutually exclusive brain areas is at odds with the distributed processing mechanisms proposed by contemporary network science theory. Here, we use machine-learning to determine how aspects of WM are dynamically coded in the human brain. Using cross-validation across independent fMRI studies, we demonstrate that stimulus domains (spatial, number and fractal) and WM processes (encode, maintain, probe) are classifiable with high accuracy from the patterns of network activity and connectivity that they evoke. This is the case even when focusing on 'multiple demands' brain regions, which are active across all WM conditions. Contrary to early neuropsychological perspectives, these aspects of WM do not map exclusively to brain area

SUBMITTER: Soreq E 

PROVIDER: S-EPMC6389921 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature