Interhemispheric Connectivity Influences the Degree of Modulation of TMS-Induced Effects during Auditory Processing
Bibliographic record
Abstract
Repetitive transcranial magnetic stimulation (rTMS) has been shown to interfere with many components of language processing, including semantic, syntactic, and phonologic. However, not much is known about its effects on nonlinguistic auditory processing, especially its action on Heschl's gyrus (HG). We aimed to investigate the behavioral and neural basis of rTMS during a melody processing task, while targeting the left HG, the right HG, and the Vertex as a control site. Response times (RT) were normalized relative to the baseline-rTMS (Vertex) and expressed as percentage change from baseline (%RT change). We also looked at sex differences in rTMS-induced response as well as in functional connectivity during melody processing using rTMS and functional magnetic resonance imaging (fMRI). fMRI results showed an increase in the right HG compared with the left HG during the melody task, as well as sex differences in functional connectivity indicating a greater interhemispheric connectivity between left and right HG in females compared with males. TMS results showed that 10 Hz-rTMS targeting the right HG induced differential effects according to sex, with a facilitation of performance in females and an impairment of performance in males. We also found a differential correlation between the %RT change after 10 Hz-rTMS targeting the right HG and the interhemispheric functional connectivity between right and left HG, indicating that an increase in interhemispheric functional connectivity was associated with a facilitation of performance. This is the first study to report a differential rTMS-induced interference with melody processing depending on sex. In addition, we showed a relationship between the interference induced by rTMS on behavioral performance and the neural activity in the network connecting left and right HG, suggesting that the interhemispheric functional connectivity could determine the degree of modulation of behavioral performance.
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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 | 0.000 |
| 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) | 0.002 | 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".