A data-driven network decomposition of the temporal, spatial, and spectral dynamics underpinning visual-verbal working memory processes.

ABSTRACT: The brain dynamics underlying working memory (WM) unroll via transient frequency-specific large-scale brain networks. This multidimensionality (time, space, and frequency) challenges traditional analyses. Through an unsupervised technique, the time delay embedded-hidden Markov model (TDE-HMM), we pursue a functional network analysis of magnetoencephalographic data from 38 healthy subjects acquired during an n-back task. Here we show that this model inferred task-specific networks with unique temporal (activation), spectral (phase-coupling connections), and spatial (power spectral density distribution) profiles. A theta frontoparietal network exerts attentional control and encodes the stimulus, an alpha temporo-occipital network rehearses the verbal information, and a broad-band frontoparie

SUBMITTER: Rossi C 

PROVIDER: S-EPMC10593846 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature