Short- and Long-Intracortical Inhibition in Incomplete Spinal Cord Injury
Bibliographic record
Abstract
BACKGROUND: Short- (SICI) and long-interval intracortical inhibition (LICI) are involved in the control of movement and movement initiation. Alterations to the two circuits can result in direct alterations to the physiology of the muscles and can be used to explain the physiological changes to individuals with spinal cord injury (SCI). OBJECTIVE: To probe changes in GABAergic function by characterizing the recruitment curves of SICI and LICI interval intracortical inhibition in an upper limb muscle in chronic SCI participants with injury between C3 and C7. METHODS: Recruitment curves were elicited with conditioning stimulus intensities determined as a percentage of active motor threshold (AMT) (SICI, 60% to 110% AMT; LICI, 90% to 130% AMT) and recorded from the flexor carpi radialis muscle during an isometric contraction equal to 15% to 20% of maximum voluntary contraction. RESULTS: AMT was greater and motor-evoked potential sizes were lower in SCI compared with uninjured controls. SICI magnitude was not different between groups, although the range of conditioning stimulus intensities to evoke SICI was unique to each group. LICI was reduced in the control group during active contraction and remained present in SCI. DISCUSSION: LICI was increased in the actively contracted flexor carpi radialis muscle in individuals with SCI compared with age-matched controls. These findings indicate that GABAB function mediating LICI is different in SCI versus controls. CONCLUSIONS: Increased LICI in SCI may be attributed to the medication baclofen or to changes in the neural mechanisms controlling contraction-related modulation of the LICI circuit.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".