Download PDFOpen PDF in browserChanges in Effective Connectivity Following Language Treatment for Post-Stroke Patients with AphasiaEasyChair Preprint 64483 pages•Date: August 28, 2021AbstractBackground: In recent years, many studies focused on the mechanisms underlying language rehabilitation after left hemisphere (LH) stroke. Examining changes in brain connectivity in patients with aphasia (PWA) during language therapy can shed new light on this question. Methods: Four PWA following LH stroke and eight healthy controls (HC) participated in the study. Two fMRI scans were administered to all participants, with a 3.5-month interval on average. The fMRI included phonological and semantic tasks, with linguistic and perceptual matching control conditions in each. Between the two scans, PWA underwent phonological component analysis (PCA) treatment. Analysis: Dynamic Causal Modelling was used to examine effective connectivity in three RH regions. Analysis was conducted separately for the two tasks. We identified connections averaged across the linguistic and perceptual conditions in each task (A matrix) and connections that were modulated only by the linguistic condition (B matrix). We asked which changed from pre- to post-treatment in PWA but not in HC. Results: Following PCA treatment: 1) changes in averaged connectivity in PWA increased resemblance to HC. Because these conditions share common lexical access components, typically associated with bilateral activation, it may reflect normalization of connectivity in the intact RH. 2) One extrinsic connection in the phonological linguistic condition was modulated in PWA, decreasing resemblance to HC. Because phonological processing is typically left-lateralized, this might reflect compensation. Conclusions Following language treatment, we found changes in the connectivity in RH among PWA. The results indicate that both compensatory and normalization processes play a role in language recovery. Keyphrases: DCM, Language treatment, PCA, aphasia, effective connectivity, fMRI
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