Changes in task-based effective connectivity in language networks following rehabilitation in post-stroke patients with aphasia
Meier, Erin L.
Kapse, Kushal J.
Glynn, Peter A.
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Citation (published version)Swathi Kiran, Erin L Meier, Kushal J Kapse, Peter A Glynn. 2015. "Changes in task-based effective connectivity in language networks following rehabilitation in post-stroke patients with aphasia." FRONTIERS IN HUMAN NEUROSCIENCE, Volume 9, 20 pp. https://doi.org/10.3389/fnhum.2015.00316
In this study, we examined regions in the left and right hemisphere language network that were altered in terms of the underlying neural activation and effective connectivity subsequent to language rehabilitation. Eight persons with chronic post-stroke aphasia and eight normal controls participated in the current study. Patients received a 10 week semantic feature-based rehabilitation program to improve their skills. Therapy was provided on atypical examples of one trained category while two control categories were monitored; the categories were counterbalanced across patients. In each fMRI session, two experimental tasks were conducted: (a) picture naming and (b) semantic feature verification of trained and untrained categories. Analysis of treatment effect sizes revealed that all patients showed greater improvements on the trained category relative to untrained categories. Results from this study show remarkable patterns of consistency despite the inherent variability in lesion size and activation patterns across patients. Across patients, activation that emerged as a function of rehabilitation on the trained category included bilateral IFG, bilateral SFG, LMFG, and LPCG for picture naming; and bilateral IFG, bilateral MFG, LSFG, and bilateral MTG for semantic feature verification. Analysis of effective connectivity using Dynamic Causal Modeling (DCM) indicated that LIFG was the consistently significantly modulated region after rehabilitation across participants. These results indicate that language networks in patients with aphasia resemble normal language control networks and that this similarity is accentuated by rehabilitation.
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