Dissociation of Broca’s area from Broca’s aphasia in patients undergoing neurosurgical resections
Bibliographic record
Abstract
OBJECTIVE: Broca's aphasia is a syndrome of impaired fluency with retained comprehension. The authors used an unbiased algorithm to examine which neuroanatomical areas are most likely to result in Broca's aphasia following surgical lesions. METHODS: Patients were prospectively evaluated with standardized language batteries before and after surgery. Broca's area was defined anatomically as the pars opercularis and triangularis of the inferior frontal gyrus. Broca's aphasia was defined by the Western Aphasia Battery language assessment. Resections were outlined from MRI scans to construct 3D volumes of interest. These were aligned using a nonlinear transformation to Montreal Neurological Institute brain space. A voxel-based lesion-symptom mapping (VLSM) algorithm was used to test for areas statistically associated with Broca's aphasia when incorporated into a resection, as well as areas associated with deficits in fluency independent of Western Aphasia Battery classification. Postoperative MRI scans were reviewed in blinded fashion to estimate the percentage resection of Broca's area compared to areas identified using the VLSM algorithm. RESULTS: A total of 289 patients had early language evaluations, of whom 19 had postoperative Broca's aphasia. VLSM analysis revealed an area that was highly correlated (p < 0.001) with Broca's aphasia, spanning ventral sensorimotor cortex and supramarginal gyri, as well as extending into subcortical white matter tracts. Reduced fluency scores were significantly associated with an overlapping region of interest. The fluency score was negatively correlated with fraction of resected precentral, postcentral, and supramarginal components of the VLSM area. CONCLUSIONS: Broca's aphasia does not typically arise from neurosurgical resections in Broca's area. When Broca's aphasia does occur after surgery, it is typically in the early postoperative period, improves by 1 month, and is associated with resections of ventral sensorimotor cortex and supramarginal gyri.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".