Ordering Information in Working Memory and Modulation of Gamma by Theta Oscillations in Humans
Bibliographic record
Abstract
Ordering information is a critical process underlying several cognitive functions, especially working memory. Theta phase-gamma amplitude coupling is regarded as a neurophysiological representation of ordering information during working memory performance. However, direct evidence has been lacking in humans. Seventy healthy subjects performed the N-back task, a working memory task that tests ordering information at 3 different levels of difficulties and with 3 different types of trials. Using electroencephalography (EEG) during N-back performance, theta-gamma coupling was assessed during response trials. Multivariate general linear model (GLM) and discriminant analysis were used to assess coupling and theta and gamma power across the N-back conditions and the trial types. During the N-back trials that required ordering of information, N-back condition had independent effects on coupling and on theta and gamma power, with equal contributions among these 3 variables. Theta-gamma coupling contribution declined significantly on the trials that did not require ordering and was intermediate on trials that favored but not necessarily required ordering. Our findings demonstrate for the first time the role of theta-gamma coupling as a mechanism that supports ordering information. They also highlight the potential of using theta-gamma coupling as a neurophysiological marker of brain function in health or disease states.
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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 | 0.002 |
| 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 | 0.001 |
| 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".