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Updated: Mar 11, 2026

Utilizing Repetitive Transcranial Magnetic Stimulation to Improve Language Function in Stroke Patients with Chronic Non-fluent Aphasia
Published on: July 2, 2013
Patterns of neural activity predict picture-naming performance of a patient with chronic aphasia
Yune Sang Lee1, Jihad T Zreik2, Roy H Hamilton2
1Department of Speech and Hearing Science, The Ohio State University, Columbus, OH, USA.
Abstract:
Naming objects represents a substantial challenge for patients with chronic aphasia. This could be in part because the reorganized compensatory language networks of persons with aphasia may be less stable than the intact language systems of healthy individuals. Here, we hypothesized that the degree of stability would be instantiated by spatially differential neural patterns rather than either increased or diminished amplitudes of neural activity within a putative compensatory language system. We recruited a chronic aphasic patient (KL; 66 year-old male) who exhibited a semantic deficit (e.g., often said "milk" for "cow" and "pillow" for "blanket"). Over the course of four behavioral sessions involving a naming task performed in a mock scanner, we identified visual objects that yielded an approximately 50% success rate. We then conducted two fMRI sessions in which the patient performed a naming task for multiple exemplars of those objects. Multivoxel pattern analysis (MVPA) searchlight revealed differential activity patterns associated with correct and incorrect trials throughout intact brain regions. The most robust and largest cluster was found in the right occipito-temporal cortex encompassing fusiform cortex, lateral occipital cortex (LOC), and middle occipital cortex, which may account for the patient's propensity for semantic naming errors. None of these areas were found by a conventional univariate analysis. By using an alternative approach, we extend current evidence for compensatory naming processes that operate through spatially differential patterns within the reorganized language system.
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