Motor network recovery in patients with chronic spinal cord compression: a longitudinal study following decompression surgery
Bibliographic record
Abstract
OBJECTIVE The authors used functional MRI to assess cortical reorganization of the motor network after chronic spinal cord compression and to characterize the plasticity that occurs following surgical intervention. METHODS A 3-T MRI scanner was used to acquire functional images of the brain in 22 patients with reversible cervical spinal cord compression and 10 control subjects. Controls performed a finger-tapping task on 3 different occasions (baseline, 6-week follow-up, and 6-month follow-up), whereas patients performed the identical task before surgery and again 6 weeks and 6 months after spinal decompression surgery. RESULTS After surgical intervention, an increased percentage blood oxygen level-dependent signal and volume of activation was observed within the contralateral and ipsilateral motor network. The volume of activation of the contralateral primary motor cortex was associated with functional measures both at baseline (r = 0.55, p < 0.01) and 6 months after surgery (r = 0.55, p < 0.01). The percentage blood oxygen level-dependent signal of the ipsilateral supplementary motor area 6 months after surgery was associated with increased function 6 months after surgery (r = 0.48, p < 0.01). CONCLUSIONS Plasticity of the contralateral and ipsilateral motor network plays complementary roles in maintaining neurological function in patients with spinal cord compression and may be critical in the recovery phase following surgery.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".