Combining Functional Neuroimaging with Off-line Brain Stimulation: Modulation of Task-related Activity in Language Areas
Bibliographic record
Abstract
Repetitive TMS (rTMS) provides a noninvasive tool for modulating neural activity in the human brain. In healthy participants, rTMS applied over the language-related areas in the left hemisphere, including the left posterior temporal area of Wernicke (LTMP) and inferior frontal area of Broca, have been shown to affect performance on word recognition tasks. To investigate the neural substrate of these behavioral effects, off-line rTMS was combined with fMRI acquired during the performance of a word recognition task. Twenty right-handed healthy men underwent fMRI scans before and after a session of 10-Hz rTMS applied outside the magnetic resonance scanner. Functional magnetic resonance images were acquired during the performance of a word recognition task that used English or foreign-language words. rTMS was applied over the LTMP in one group of 10 participants (LTMP group), whereas the homologue region in the right hemisphere was stimulated in another group of 10 participants (RTMP group). Changes in task-related fMRI response (English minus foreign languages) and task performances (response time and accuracy) were measured in both groups and compared between pre-rTMS and post-rTMS. Our results showed that rTMS increased task-related fMRI response in the homologue areas contralateral to the stimulated sites. We also found an effect of rTMS on response time for the LTMP group only. These findings provide insights into changes in neural activity in cortical regions connected to the stimulated site and are consistent with a hypothesis raised in a previous review about the role of the homologue areas in the contralateral hemisphere for preserving behavior after neural interference.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".