Case Studies in Neuroscience: Evidence of motor thalamus reorganization following bilateral forearm amputations
Bibliographic record
Abstract
Following injury, functional improvement can result from central nervous system plasticity. Use-dependent plasticity of motor systems is evident, for example, in recovery of function resulting from rehabilitative interventions. Here, we present a single patient who underwent bilateral microelectrode-guided stereotactic implantation of deep brain stimulating leads for the treatment of essential tremor 52 yr following bilateral arm amputations. The tremor affected his upper extremities and had rendered him unable to perform fine motor tasks with his prostheses, significantly reducing his independence. We found a large territory of neurons in the ventral intermediate nucleus of his thalamus that responded to shoulder protraction, the movement that he used to control fine motor movements of his terminal hook prostheses. We propose that reorganization of this motor nucleus may have occurred secondary to a use-dependent gain of function in neurons that were previously involved in hand movement. NEW & NOTEWORTHY We had a unique opportunity to record neurons in the ventrointermediate (Vim) motor nucleus of thalamus in a patient with essential tremor, decades following bilateral forearm amputations. We demonstrate that a large region of Vim is active during shoulder protraction-the movement used to operate the patient's mechanical prostheses. We suggest that this provides evidence of human motor thalamic plasticity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".