Cerebral changes after injury to the median nerve: A long-term follow up
Bibliographic record
Abstract
Injury to the peripheral nerves in the upper extremity results in changes in the nerve, and at multiple sites throughout the central nervous system (CNS). We studied the long-term effects of an injury to the median nerve in the forearm with a focus on changes in the CNS. Four patients with isolated injuries of the median nerve in their 20s were examined a mean of 14 years after the injury. Cortical activation was monitored during tactile stimulation of the fingers of the injured and healthy hand using functional magnetic resonance imaging at 3 Tesla. The neurophysiological state and clinical outcome were also examined. Activation in the primary somatosensory cortex was substantially larger during tactile stimulation of the injured hand than with stimulation of the uninjured hand. We also saw a redistribution of hemispheric dominance. Stimulation of the injured median nerve resulted in a substantially increased dominance of the contralateral hemisphere. However, stimulation of the healthy ulnar nerve resulted in a decreased dominance of the contralateral hemisphere. Neurophysiology showed low sensory amplitudes, velocity, and increased motor latency in the injured nerve. Clinically there were abnormalities predominately in the sensory domain. However, there was an overall improved mean result compared with a five year follow-up in the same subjects. The cortical changes could be the result of cortical reorganisation after a changed afferent signal pattern from the injured nerve. Even though the clinical function improved over time it did not return to normal, and neither did the cortical response.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".