Spatio-temporal dynamics of resting-state brain networks improve single-subject prediction of schizophrenia diagnosis.

ABSTRACT: Correlation in functional MRI activity between spatially separated brain regions can fluctuate dynamically when an individual is at rest. These dynamics are typically characterized temporally by measuring fluctuations in functional connectivity between brain regions that remain fixed in space over time. Here, dynamics in functional connectivity were characterized in both time and space. Temporal dynamics were mapped with sliding-window correlation, while spatial dynamics were characterized by enabling network regions to vary in size (shrink/grow) over time according to the functional connectivity profile of their constituent voxels. These temporal and spatial dynamics were evaluated as biomarkers to distinguish schizophrenia patients from controls, and compared to current biomarkers based

SUBMITTER: Kottaram A 

PROVIDER: S-EPMC6866493 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature