Functional reorganization of language networks for semantics and syntax in chronic stroke: Evidence from MEG
Bibliographic record
Abstract
Using magnetoencephalography, we investigated the potential of perilesional and contralesional activity to support language recovery in patients with poststroke aphasia. In healthy young controls, left-lateralized ventral frontotemporal regions responded to semantic anomalies during sentence comprehension and bilateral dorsal frontoparietal regions responded to syntactic anomalies. Older adults showed more extensive bilateral responses to the syntactic anomalies and less lateralized responses to the semantic anomalies, with decreased activation in the left occipital and parietal regions for both semantic and syntactic anomalies. In aphasic participants, we observed compensatory recruitment in the right hemisphere (RH), which varied depending on the type of linguistic information that was processed. For semantic anomalies, aphasic patients activated some preserved left hemisphere regions adjacent to the lesion, as well as homologous parietal and temporal RH areas. Patients also recruited right inferior and dorsolateral frontal cortex that was not activated in the healthy participants. Responses for syntactic anomalies did not reach significance in patients. Correlation analyses indicated that recruitment of homologous temporoparietal RH areas is associated with better semantic performance, whereas higher accuracy on the syntactic task was related to bilateral superior temporoparietal and right frontal activity. The results suggest that better recovery of semantic processing is associated with a shift to ventral brain regions in the RH. In contrast, preservation of syntactic processing is mediated by dorsal areas, bilaterally, although recovery of syntactic processing tends to be poorer than semantic. Hum Brain Mapp 37:2869-2893, 2016. © 2016 Wiley Periodicals, Inc.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".