Effects of brain activity, morning salivary cortisol, and emotion regulation on cognitive impairment in elderly people
Bibliographic record
Abstract
OBJECTIVE: Cognitive impairment subjects exhibit high cortisol levels that are associated with low brain activity, but negative emotions with high cortisol are associated with high brain activity and reduced cognition. Emotion regulation, glucocorticoid hormones, and brain activity all interact with cognitive impairment. Therefore, we aimed to investigate cognitive impairment differences related to sex, morning salivary cortisol, emotion regulation, and brain activity in elderly people. METHODS: A total of 64 participants (19 males and 45 females) were tested by the Montreal cognitive assessment. Next, morning saliva was collected from each participant and analyzed by enzyme-linked immunosorbent assay, and the brain activity of the participants was subsequently recorded. Finally, emotion regulation was assessed via the Brunel mood scale questionnaire. RESULTS: The results revealed that attention was significantly lower in elderly females than in elderly males. Depression and vigor were significantly higher in elderly females than in elderly males. Brain activity of the slow (delta and theta) and fast (beta and high beta) waves was significantly higher in elderly females than in elderly males. Moreover, attention was negatively correlated with the theta wave, whereas delayed recall was positively correlated with the theta wave and salivary cortisol. Depression was positively correlated with the high beta wave and language skill, whereas the high beta wave was negatively correlated with visuoconstructional skill. CONCLUSION: The brain activity, emotion, and cortisol were influenced by cognitive impairments, although the relation of brain activity with glucocorticoid hormones remains inconclusive. This finding may be useful to the brain aging process, promote healthy brain aging, and prevent neurodegenerative conditions.
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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".