EEG coherence as a marker of functional connectivity disruption in Alzheimer's disease
Bibliographic record
Abstract
Progressive deterioration of connectivity between neurons is a neurophysiological hallmark of brain ageing and has been linked to the severity of dementia. We explored the possibility of utilizing electroencephalographic evidence of functional connectivity disruption as a potential marker of Alzheimer's disease. This study examined group differences in EEG coherence within global cortical networks at rest and during executive challenges among patients with Alzheimer's dementia, individuals with mild cognitive impairment, and healthy controls. Four promising EEG coherence markers were identified as (i) F3-F4 Beta in visual-spatial orientation task ( p = 0.019), (ii) P7-P8 Beta in writing task ( p = 0.001), (iii) T7-T8 Gamma in speech understanding task ( p = 0.008) and (iv) O1-O2 Alpha in space orientation task ( p = 0.020). More research is needed to identify the sensitivity and specificity of the markers.
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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 | 0.001 |
| 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".