Answering the Call: The Influence of Neuroimaging and Electrophysiological Evidence on Rehabilitation
Bibliographic record
Abstract
Functional recovery after brain damage or disease is dependent on the neuroplastic capability of the cortex and the nonaffected brain. Following cortical injury in the motor and sensory regions, the adjacent spared neural tissues and related areas undergo modifications that are required in order to drive more normal motor control. Current rehabilitation models seek to stimulate functional recovery by capitalizing on the inherent potential of the brain for positive reorganization after neurological injury or disease. This article discusses how neuroimaging and electrophysiological data can inform clinical practice; representative data from the modalities of functional magnetic resonance imaging, diffusion tensor imaging, magnetoencephalography, electroencephalography, and positron emission tomography are cited. Data from a variety of central nervous system disease and damage models are presented to illustrate how rehabilitation practices are beginning to be shaped and informed by neuroimaging and electrophysiological data.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".