Abstract TMP46: EEG is a Useful Biomarker of Motor Recovery in Early Stroke Rehabilitation
Bibliographic record
Abstract
Introduction: The application of biomarkers to study and monitor stroke recovery mechanisms can potentially advance rehabilitation practice and research. This study examined the utility of dense-array electroencephalography (EEG) for predicting and capturing changes in brain function in early stroke rehabilitation. Hypothesis: Changes in EEG measures involving ipsi- and contralesional motor cortices (iM1 and cM1) in delta (1-3Hz) and high beta (20-30Hz) frequency bands [1] parallel and [2] predict motor recovery. Methods: Individuals with recent ischemic or hemorrhagic stroke admitted to an inpatient rehabilitation facility (IRF) completed a 3-minute resting-state EEG recording and behavioral testing (Upper Extremity Fugl-Meyer (FM) and Functional Independence Measurement motor subscale (FIM-motor)) during hospitalization and 90-days post-stroke. EEG power and coherence (connectivity) measures were computed from leads overlying iM1 and cM1. Results: Twenty-seven subjects (20 males, age 58.3±14.6 years, 14.7±12.8 days post-stroke) participated. Greater decrease in iM1-cM1 coherence in the delta band correlated significantly with larger (a) FIM-motor score improvement from IRF admission to discharge (r=-0.70, p=0.001, n=18) and (b) FM score improvement from IRF admission to 90-days post-stroke (r=-0.57, p=0.02, n=17). Baseline EEG measures did not predict motor recovery when examined across the entire group. Performance of biomarkers varies according to stroke severity, and so prediction was further examined in relation to baseline FM. In subjects with moderate-severe impairment (FM≤40), delta iM1-cM1 coherence at baseline correlated with FIM-motor gains (r=0.72, p=0.03, n=9), and delta power in leads over iM1 positively correlated with FM gains (a) from IRF admission to discharge (r=0.75, p=0.03, n=8) and (b) from IRF admission to 90-days post-stroke (r=0.73, p=0.04, n=8). Conclusions: Bedside EEG recording in the IRF provides neurophysiological insights that predict and parallel motor recovery, and so may be a valuable bedside tool in early stroke rehabilitation. EEG measures can predict motor recovery in individuals with moderate-severe motor impairment.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".