Changes in Functional Magnetic Resonance Imaging Cortical Activation with Cross Education to an Immobilized Limb
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to assess cortical activation associated with the cross-education effect to an immobilized limb, using functional magnetic resonance imaging. METHODS: Fourteen right-handed participants were assigned to two groups. One group (n = 7) wore a cast and strength trained the free arm (CAST-TRAIN). The second group (n = 7) wore a cast and did not strength train (CAST). Casts were applied to the nondominant (left) wrist and hand. Strength training was maximal isometric handgrip contractions (right hand) 5 d·wk(-1). Peak force (handgrip dynamometer), muscle thickness (ultrasound), EMG, and cortical activation (functional magnetic resonance imaging) were assessed before and after the intervention. RESULTS: CAST-TRAIN improved right handgrip strength by 10.7% (P < 0.01) with no change in muscle thickness. There was a significant group × time interaction for strength of the immobilized arm (P < 0.05). Handgrip strength of the immobilized arm of CAST-TRAIN was maintained, whereas the immobilized arm of CAST significantly decreased by 11% (P < 0.05). Muscle thickness of the immobilized arm decreased by an average of 3.3% (P < 0.05) for all participants and was not different between groups after adjusting for baseline differences. There was a significant group × time interaction for EMG activation (P < 0.05), where CAST-TRAIN showed an increasing trend and CAST showed a decreasing trend, pooled across arms. For the immobilized arm of CAST-TRAIN, there was a significant increase in contralateral motor cortex activation after training (P < 0.05). For the immobilized arm of CAST, there was no change in motor cortex activation. CONCLUSIONS: Handgrip strength training of the free limb attenuated strength loss during unilateral immobilization. The maintenance of strength in the immobilized limb via the cross-education effect may be associated with increased motor cortex activation.
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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 | 0.000 | 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) | 0.003 | 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".