Theta phase‐gamma amplitude coupling during working memory and its relationships with demographic, clinical, genetic, neurochemical, and neurostructural measures in older adults at risk for dementia
Bibliographic record
Abstract
Abstract Background Theta phase‐gamma amplitude coupling (TGC) is a neurophysiological mechanism that underlies working memory (WM)1. WM is also associated with demographic, clinical, genetic and neuroimaging measures. However, the relative contributions of TGC and these measures to WM, and the relationship between TGC and these measures, remains unclear. We examined the relative contributions of TGC and these measures to WM performance in a group of participants at‐risk for Alzheimer’s dementia. Method Older participants (age=71.2±6.0, N = 206) with Mild Cognitive Impairment (MCI), Major Depressive Disorder (MDD), or MCI+MDD completed clinical assessment, N‐back WM task with EEG to measure TGC, genetic testing, PET with [11C]‐Pittsburgh Compound B ([11C]‐PIB PET) and brain 3T MRI. Linear regressions were used to assess the relationships among 2‐back WM performance; demographic and clinical variables; TGC; ApoE4 carrier status; total beta‐amyloid SUVR ([11C]‐PIB PET); and regional cortical thickness, subcortical volumes, and white matter fractional anisotropy (MRI). Result 2‐back WM performance was associated with age and TGC after controlling for all other measures (Age: β=‐0.253; p=0.039, TGC: β=0.300; p=0.005). TGC was not associated with any other measures after correction for multiple comparisons. Conclusion TGC predicts WM performance in contrast to demographic, clinical, genetic, and PET and MRI imaging measures. Our findings underline the strong association between WM and TGC, a dynamic time‐based neurophysiological measure that is capturing a functional process which may not be captured by these static measures. Future studies could explore other dynamic measures with other imaging modalities and their relationships with TGC or other neurophysiological measures. 1. Rajji, T.K., et al., Ordering Information in Working Memory and Modulation of Gamma by Theta Oscillations in Humans. Cerebral Cortex, 2017. 27(2): p. 1482‐1490.
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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 | 0.001 | 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".