Using limb movements to improve spatial neglect: The role of functional electrical stimulation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Spatial neglect is common after right-hemisphere stroke and has proven resilient to a number of therapeutic interventions. Both active and experimenter-induced passive movements of the left limb in left hemispace have been shown to ameliorate neglect in subsets of patients by improving performance on tasks requiring attention to the left side of space. However, the high incidence of contralesional hemiparesis and poor motor recovery in neglect makes active limb movement therapies applicable to only a small subset of patients. The purpose of our studies was to investigate the effects of passive movements of the left hand by functional electrical stimulation (FES), a common and portable motor rehabilitation technique, on performance in a visual scanning task. METHODS: The effect of FES-induced passive movement on target detection in a visual scanning task was compared to no movement and active movement conditions and also investigated in scanning tasks in both near and far space. RESULTS: Passive limb movement effects in neglect were variable across and within studies, reference spaces, and individuals, with a subset of positive responders differing from non-responders in regard to constructional deficits and lesion location. CONCLUSIONS: The potential viability of FES as a therapy for neglect deserves further investigation and directions for future research in this area are discussed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 it