EEG-TMS revealing top-down cortical interactions underlying episodic memory
Bibliographic record
Abstract
neuronal activity across perceptual, attentional and inhibitory control networks.Preliminary data from our group suggest that this synchronization is influenced by the phase of frontal theta oscillations at the onset of the behaviorally relevant cue.Deficits in inhibitory control are seen across a variety of psychiatric disorders.Repetitive transcranial magnetic stimulation (rTMS) over the presupplementary motor area (preSMA) has shown promise to alleviate these deficits, but results have been mixed.EEG-TMS triggered by frontal theta phase has successfully been used to modulate working memory in a phase-dependent manner and might prove useful for inhibitory control modulation.GOAL: The aim of this work is to assess the influence of frontal theta phase at stimulation on inhibitory control performance modulation by EEG-rTMS.METHOD: Twenty-three righthanded healthy participants underwent three weekly sessions of frontal theta phase-triggered anatomically neuronavigated EEG-rTMS targeting the right preSMA during an auditory Go/NoGo task.Inhibitory control was assessed pre-and post-intervention using the Stop Signal Response Time (SSRT) in a motor response inhibition auditory Stop Signal Task.On each session, subjects received 400 triplet bursts (100 Hz) of biphasic pulses (110% motor threshold) triggered on 1 of 3 predetermined frontal theta phase angles based on previous work (in preparation): 45 , 225 or random (randomized order).RESULTS: Preliminary results based on 11 participants suggest that 45 -triggered or randomly triggered EEG-rTMS may decrease the SSRT, indicative of better inhibitory control, whereas 225 -triggered EEG-rTMS might increase the SSRT.CONCLUSIONS: EEG-rTMS triggered by ongoing frontal theta oscillations might modulate inhibitory control performance in a phase-dependent manner.While EEG-rTMS delivered on most frontal theta oscillations phases might improve inhibitory control, some phases might be detrimental.
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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 | 0.001 |
| 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) | 0.005 | 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".