A combined TMS-EEG study of short-latency afferent inhibition in the motor and dorsolateral prefrontal cortex
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Combined transcranial magnetic stimulation and electroencephalography (TMS-EEG) enables noninvasive neurophysiological investigation of the human cortex. A TMS paradigm of short-latency afferent inhibition (SAI) is characterized by attenuation of the motor-evoked potential (MEP) and modulation of N100 of the TMS-evoked potential (TEP) when TMS is delivered to motor cortex (M1) following median nerve stimulation. SAI is a marker of cholinergic activity in the motor cortex; however, the SAI has not been tested from the prefrontal cortex. We aimed to explore the effect of SAI in dorsolateral prefrontal cortex (DLPFC). SAI was examined in 12 healthy subjects with median nerve stimulation and TMS delivered to M1 and DLPFC at interstimulus intervals (ISIs) relative to the individual N20 latency. SAI in M1 was tested at the optimal ISI of N20 + 2 ms. SAI in DLPFC was investigated at a range of ISI from N20 + 2 to N20 + 20 ms to explore its temporal profile. For SAI in M1, the attenuation of MEP amplitude was correlated with an increase of TEP N100 from the left central area. A similar spatiotemporal neural signature of SAI in DLPFC was observed with a marked increase of N100 amplitude. SAI in DLPFC was maximal at ISI N20 + 4 ms at the left frontal area. These findings establish the neural signature of SAI in DLPFC. Future studies could explore whether DLPFC-SAI is neurophysiological marker of cholinergic dysfunction in cognitive disorders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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 it