RESTING STATE ELECTROENCEPHALOGRAPHY AND INHIBITORY CONTROL IN COGNITIVELY UNIMPAIRED OLDER ADULTS
Bibliographic record
Abstract
Abstract Resting state electroencephalography (EEG) activity captures spontaneous neural activity while at rest. Mounting evidence suggests that resting state EEG activity is linked to cognitive performance and event-related potentials in young adults. However, little is known on the relationship between resting state EEG activity and event-related spectral perturbations (ERSPs) and/or behavioral performance linked to inhibitory control in cognitively unimpaired older adults (OA). This study examined the relationship between resting state alpha power and 1) alpha-band ERSPs and 2) behavioral measures during a Go/NoGo inhibitory control task in 22 OA (Age: M = 64.04, SD = 6.18 years; Montreal Cognitive Assessment score: M = 28.43, SD = 0.99). Participants’ EEG data were collected during eyes-open resting state and a Go/NoGo task. Fourier transformation-based spectral analysis was used to calculate power in the alpha frequency band (8-12 Hz), with absolute power spectral density for the resting state condition and event-related desynchronization (ERD) for the Go/NoGo task. Behavioral performance was assessed using reaction time on Go trials (M = 340.27 ms, SD = 33.71) and accuracy on Go (M = 0.92, SD = 0.13) and NoGo trials (M = 0.92, SD = 0.06). Based on preliminary analyses, lower absolute alpha power in resting state was correlated with better accuracy (r(4) = -0.995, p =.005) and lower alpha ERD (r(4) = -0.96, p =.005) on Go trials. These preliminary results suggest that resting state brain oscillations may predict brain dynamics and performance linked to inhibitory control in OA.
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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".