A right convergence area of the prefrontal lobe is involved in the improvement of semantic fluency in patients with post-stroke aphasia
Bibliographic record
Abstract
Objectives This study aimed to longitudinally observe the improvement mechanism of semantic fluency in subacute post-stroke aphasia (PSA) patients using resting-state functional magnetic resonance imaging (rs-fMRI).Methods Twelve PSA patients, about one month after onset, were enrolled in this study and received speech-language therapy (SLT) for one month. Auditory comprehension and semantic fluency were evaluated using the Western Aphasia Battery (WAB) and the Animal Fluency Test. Before and after treatment, rs-fMRI data were collected, and the dice similarity coefficient was used to measure the spatial similarity between each patient’s lesion and a reference lesion. The left posterior inferior temporal gyrus (pITG) was used as a seed to calculate the normalized functional connectivity in whole-brain voxel analysis using DPABI software for statistical analysis.Results The dice similarity coefficient between each patient’s lesion and the reference lesion showed moderate to high intensity (0.57 ± 0.14) in the Montreal Neurological Institute space. After treatment, we found a significant increase in functional connectivity between the left pITG and the right prefrontal lobe convergence area (peak t = 8.219, Gaussian random field multiple comparison correction, voxel p < 0.001, cluster p < 0.05). The increase in functional connectivity was negatively correlated with the improvement in auditory comprehension (r =–0.707, p = 0.033) and positively correlated with the improvement in semantic fluency (r = 0.79, p = 0.02).Conclusion The improvement of semantic fluency in subacute PSA patients may require the participation of the right convergence area of the prefrontal lobe.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".