Peer Review #1 of "Slower EEG alpha generation, synchronization and “flow”—possible biomarkers of cognitive impairment and neuropathology of minor stroke (v0.2)"
Bibliographic record
Abstract
Background: We investigated EEG rhythms, particularly alpha activity, and their relationship to post-stroke neuropathology and cognitive functions in the subacute and chronic stages of minor strokes.Methods: We included 10 patients with right middle cerebral artery (MCA) ischemic strokes and 11 healthy controls.All the assessments of stroke patients were done both in the subacute and chronic stages.Neurological impairment was measured using the National Institute of Health Stroke Scale (NIHSS), whereas cognitive functions were assessed using the Montreal Cognitive Assessment (MoCA) and MoCA memory index (MoCA-MIS).The EEG was recorded using a 19 channel EEG system with standard EEG electrode placement.In particular, we analyzed the EEGs derived from the four lateral frontal (F3,F7,F4,F8), and corresponding lateral posterior (P3,P4,T5,T6) electrodes.Quantitative EEG analysis included: the group FFT spectra, the weighted average of alpha frequency (ɑAVG), the group probability density distributions of all conventional EEG frequency band relative amplitudes (EEG microstructure), the interand intra-hemispheric coherences, and the topographic distribution of alpha carrier frequency phase potentials (PPs).Statistical analysis was done using a Kruskal-Wallis ANOVA with a post-hoc Mann-Whitney U two-tailed test, and Spearman's correlation.Results: We demonstrated transient cognitive impairment alongside a slower alpha frequency (αAVG) in the subacute right MCA stroke patients vs. the controls.This slower alpha frequency showed no amplitude change, but was highly synchronized intrahemispherically, overlying the ipsi-lesional hemisphere, and inter-hemispherically, overlying the frontal cortex.In addition, the disturbances in EEG alpha activity in subacute stroke patients were expressed as a decrease in alpha PPs over the frontal cortex and an
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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 | 0.011 | 0.097 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.255 | 0.148 |
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".