Left-hemisphere brain damage commonly affects patients' abilities to produce and comprehend syntactic structures, a condition typically referred to as “agrammatism.” The neural correlates of agrammatism remain disputed in the literature, and distributed areas have been implicated as important predictors of performance, for example, Broca's area, anterior temporal areas, and temporo-parietal areas. We examined the association between damage to specific language-related ROIs and impaired syntactic processing in acute aphasia. We hypothesized that damage to the posterior middle temporal gyrus, and not Broca's area, would predict syntactic processing abilities. One hundred four individuals with acute aphasia (<20 days poststroke) were included in the study. Structural MRI scans were obtained, and all participants completed a 45-item sentence–picture matching task. We performed an ROI-based stepwise regression analyses to examine the relation between cortical brain damage and impaired comprehension of canonical and noncanonical sentences. Damage to the posterior middle temporal gyrus was the strongest predictor for overall task performance and performance on noncanonical sentences. Damage to the angular gyrus was the strongest predictor for performance on canonical sentences, and damage to the posterior superior temporal gyrus predicted noncanonical scores when performance on canonical sentences was included as a cofactor. Overall, our models showed that damage to temporo-parietal and posterior temporal areas was associated with impaired syntactic comprehension. Our results indicate that the temporo-parietal area is crucially implicated in complex syntactic processing, whereas the role of Broca's area may be complementary.
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The association between age and language recovery in stroke remains unclear. Here, we used neuroimaging data to estimate brain age, a measure of structural integrity, and examined the extent to which brain age at stroke onset is associated with (1) cross-sectional language performance, and (2) longitudinal recovery of language function, beyond chronological age alone. A total of 49 participants (age: 65.2 +/- 12.2 years, 25 female) underwent routine clinical neuroimaging (T1) and a bedside evaluation of language performance (Bedside Evaluation Screening Test-2) at onset of left hemisphere stroke. Brain age was estimated from enantiomorphically reconstructed brain scans using a machine learning algorithm trained on a large sample of healthy adults. A subsample of 30 participants returned for follow-up language assessments at least two years after stroke onset. To account for variability in age at stroke, we calculated proportional brain age difference, i.e., the proportional difference between brain age and chronological age. Multiple regression models were constructed to test the effects of proportional brain age difference on language outcomes. Lesion volume and chronological age were included as covariates in all models. Accelerated brain age compared to age was associated with worse overall aphasia severity (F(1, 48) = 5.65, p = .022), naming (F(1, 48) = 5.13, p = .028), and speech repetition (F(1, 48) = 8.49, p = .006) at stroke onset. Follow-up assessments were carried out ≥2 years after onset; Decelerated brain age relative to age was significantly associated with reduced overall aphasia severity (F(1, 26) = 5.45, p = .028) and marginally failed to reach statistical significance for auditory comprehension (F (1, 26) = 2.87, p = .103). Proportional brain age difference was not found to be associated with changes in naming (F(1, 26) = .23, p = .880) and speech repetition (F(1, 26) = .00, p = .978). Chronological age was only associated with naming performance at stroke onset (F(1, 48) = 4.18, p = .047). These results indicate that brain age as estimated based on routine clinical brain scans may be a strong biomarker for language function and recovery after stroke.
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