Cutting your nerve changes your brain
Bibliographic record
Abstract
Following upper limb peripheral nerve transection and surgical repair, some patients regain good sensorimotor function while others do not. Understanding peripheral and central mechanisms that contribute to recovery may facilitate the development of new therapeutic interventions. Plasticity following peripheral nerve transection has been demonstrated throughout the neuroaxis in animal models of nerve injury. However, the brain changes that occur following peripheral nerve transection and surgical repair in humans have not been examined. Furthermore, the extent to which peripheral nerve regeneration influences functional and structural brain changes has not been characterized. Therefore, we asked whether functional changes are accompanied by grey and/or white matter structural changes and whether these changes relate to sensory recovery? To address these key issues we (i) assessed peripheral nerve regeneration; (ii) measured functional magnetic resonance imaging brain activation (blood oxygen level dependent signal; BOLD) in response to a vibrotactile stimulus; (iii) examined grey and white matter structural brain plasticity; and (iv) correlated sensory recovery measures with grey matter changes in peripheral nerve transection and surgical repair patients. Compared to each patient's healthy contralesional nerve, transected nerves have impaired nerve conduction 1.5 years after transection and repair, conducting with decreased amplitude and increased latency. Compared to healthy controls, peripheral nerve transection and surgical repair patients had altered blood oxygen level dependent signal activity in the contralesional primary and secondary somatosensory cortices, and in a set of brain areas known as the 'task positive network'. In addition, grey matter reductions were identified in several brain areas, including the contralesional primary and secondary somatosensory cortices, in the same areas where blood oxygen level dependent signal reductions were identified. Furthermore, grey matter thinning in the post-central gyrus was negatively correlated with measures of sensory recovery (mechanical and vibration detection) demonstrating a clear link between function and structure. Finally, we identified reduced white matter fractional anisotropy in the right insula in a region that also demonstrated reduced grey matter. These results provide insight into brain plasticity and structure-function-behavioural relationships following nerve injury and have important therapeutic implications.
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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".