A precise language network revealed by the independent component-based lesion mapping in post-stroke aphasia.

ABSTRACT: Brain lesion mapping studies have provided the strongest evidence regarding the neural basis of cognition. However, it remained a problem to identify symptom-specific brain networks accounting for observed clinical and neuroanatomical heterogeneity. Independent component analysis (ICA) is a statistical method that decomposes mixed signals into multiple independent components. We aimed to solve this issue by proposing an independent component-based lesion mapping (ICLM) method to identify the language network in patients with moderate to severe post-stroke aphasia. Lesions were first extracted from 49 patients with post-stroke aphasia as masks applied to fMRI data in a cohort of healthy participants to calculate the functional connectivity (FC) within the masks and non-mask brain voxels. IC

SUBMITTER: Ren W 

PROVIDER: S-EPMC9561861 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature