Assessing the Longitudinal Relationship between Theta-Gamma Coupling and Working Memory Performance in Older Adults
Bibliographic record
Abstract
Theta-gamma coupling (TGC) is a neurophysiologic mechanism that supports working memory (WM). TGC is associated with N-back performance, a WM task. Similar to TGC, theta and alpha event-related synchronization (ERS) and desynchronization (ERD) are also associated with WM. Few studies have examined the longitudinal relationship between WM performance and TGC, ERS, or ERD. This study aimed to determine if changes in WM performance are associated with changes in TGC (primary aim), as well as theta and alpha ERS or ERD over 6 to 12 weeks. Participants included 62 individuals aged 60 and older with no neuropsychiatric conditions or with remitted Major Depressive Disorder (MDD) and no cognitive disorders. TGC, ERS, and ERD were assessed using electroencephalography (EEG) during the N-back task (3-back condition). There was an association between changes in 3-back performance and changes in TGC, alpha ERD and ERS, and theta ERS in the control group. In contrast, there was only a significant association between changes in 3-back performance and changes in TGC in the subgroup with remitted MDD. Our results suggest that the relationship between WM performance and TGC is stable over time, while this is not the case for changes in theta and alpha ERS and ERD.
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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 | 0.001 | 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 | 0.000 |
| 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".