Functional connectivity and graph theory of impaired central visual pathways in acute ischemic stroke based on functional magnetic resonance imaging.

ABSTRACT:

Background

Stroke represents a major contributor to disability, resulting in functional impairments and imposing a societal burden. Resting-state functional connectivity (FC) indicates brain interactions, with dynamic alterations offering insights into cerebral function. This study used static and dynamic functional connectivity (sFC/dFC) and machine learning (ML) models to assess FC alterations in patients with acute ischemic stroke (AIS), aiming to identify connections that distinguish patients from healthy controls (HCs) and study their potential as biomarkers.

Methods

A clinical trial took place at the Stroke Center of Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University from March 2021 to September 2022 (trial registration date: 26 May 2021). A t

SUBMITTER: Chu X 

PROVIDER: S-EPMC12514717 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature