Evaluating the Relationship between Long Interval Cortical Inhibition, Working Memory and Gamma Band Activity in the Dorsolateral Prefrontal Cortex
Bibliographic record
Abstract
Recent reports have demonstrated that long interval cortical inhibition (LICI) can be indexed in the dorsolateral prefrontal cortex (DLPFC) in healthy controls. LICI is a neurophysiologic process indexed using transcranial magnetic stimulation and is closely associated with cortical GABA(B) receptor mediated inhibitory neurotransmission. Several previous studies have also reported that gamma band activity represents a neurophysiological process that is mediated, in part, through GABAergic inhibitory neurotransmission and may subserve several cognitive operations including working memory (WM) in the DLPFC. The intension of the current study, therefore, was to directly evaluate the relationship between these neurophysiological processes in healthy subjects. Eleven right-handed healthy subjects participated in this experiment in which gamma band activity was measured through simultaneous recording of electroencephalography (EEG) during the N-back task, a cognitive task designed to index WM. LICI was recorded through EEG from the left DLFPC, left motor cortex and through EMG of peripheral hand muscles in a separate session according to previously published methods. There was no evidence for a relationship in the DLPFC between LICI and gamma band activity elicited during the N-back task, though there was a significant relationship between LICI and performance on the 3-back condition, the N-back condition of greatest difficulty. In conclusion these data provide evidence to suggest that in the DLPFC, there is no direct relationship between GABA(B) receptor mediated inhibitory neurotransmission and gamma band activity. However, our data does suggest that LICI was related to 3-back performance providing evidence implicating DLPFC GABAergic inhibitory neurotransmission in WM 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 | 0.001 |
| 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) | 0.001 | 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".