Naming impairments evoked by focal cortical electrical stimulation in the ventral temporal cortex correlate with increased functional connectivity
Bibliographic record
Abstract
BACKGROUND: High-frequency cortical electrical stimulations (HF-CES) are the gold standard for presurgical functional mapping. In the dominant ventral temporal cortex (VTC) HF-CES can elicit transient naming impairment (eloquent sites), defining a basal temporal language area (BTLA). OBJECTIVE: Whether naming impairments induced by HF-CES within the VTC are related to a specific pattern of connectivity of the BTLA within the temporal lobe remains unknown. We addressed this issue by comparing the connectivity of eloquent and non-eloquent sites from the VTC using cortico-cortical evoked potentials (CCEP). METHODS: Low frequency cortical electrical stimulations (LF-CES) were used to evoke CCEP in nine individual brains explored with Stereo-Electroencephalography. We compared the connectivity of eloquent versus non eloquent sites within the VTC using Pearson's correlation matrix. RESULTS: Overall, within the VTC, eloquent sites were associated with increased functional connectivity compared to non-eloquent sites. Among the VTC structures, this pattern holds true for the inferior temporal gyrus and the parahippocampal gyrus while the fusiform gyrus specifically showed a high connectivity in both non eloquent and eloquent sites. CONCLUSIONS: Our findings suggest that the cognitive effects of focal HF-CES are related to the functional connectivity properties of the stimulated sites, and therefore to the disturbance of a wide cortical network. They further suggest that functional specialization of a cortical region emerges from its specific pattern of functional connectivity. Cortical electrical stimulation functional mapping protocols including LF coupled to HF-CES could provide valuable data characterizing both local and distant functional architecture.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".