Linear gain effect of theta-burst and 15 Hz rTMS on intra-cortically measured neuronal responses to oriented grating visual stimuli
Bibliographic record
Abstract
Abstract Transcranial magnetic stimulation (TMS) involves the application of time-pulsed magnetic fields to cortical tissue through a coil positioned near the head. TMS is widely used for studying the mechanisms underlying perception and behaviour and is considered a potential therapeutic technique for various conditions. However, the application of TMS has been hindered by the lack of understanding of its mechanism of action. Here we studied the effects of three repetitive TMS (rTMS) paradigms on intra-cortical neuronal responses to oriented gratings in cat area 18. Each of stimulation protocols, including continuous theta-burst, intermittent theta-burst, and 15 Hz rTMS, consisted of 600 pulses. Application of continuous theta-burst and 15 Hz rTMS suppressed the action potential response to oriented grating stimuli for 1.5-6 minutes. In contrast, application of intermittent theta-burst stimulation was associated with enhancement of the action potential response ∼15 minutes following TMS. Neuronal assemblies that were more responsive before the application of rTMS, were affected more than neurons that were less responsive before rTMS. In spite of these changes, the preferred orientation, the orientation tuning of the multi-unit activity and the spatial pattern of the responses recorded from assemblies neurons remained unaffected. Our findings demonstrate that rTMS does not modify the functional selectivities of ensembles of neurons; rather, it has a linear gain effect on their responses.
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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) | 0.001 | 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".