Reorganization of Brain Resting-state Functional Connectivity Following 14 Days of Elbow Immobilization in Young Females
Bibliographic record
Abstract
Limb immobilization is known to cause significant decreases in muscle strength and muscle mass as early as two days following the onset of immobilization. However, the decline in strength surpasses the decline in muscle mass, suggesting that factors in addition to muscle loss, such as neuroplasticity, contribute to the decrease in force production. However, little is known regarding immobilization-induced neural changes, although sensorimotor regions seem to be the most affected. The present study aimed to determine whether brain functional organization is altered following 14 days of unilateral elbow immobilization. Functional organization was quantified using resting-state functional connectivity, a measure of the synchronicity of the spontaneous discharge of different brain regions at rest. Data was obtained from twelve healthy young females before and after completing the immobilization period. A seed-to-voxel analysis was performed using seeds associated with cortical, subcortical, and cerebellar sensorimotor regions of the brain. The results showed changes predominantly involving cerebellar connectivity. For example, the immobilization period caused a decrease in connectivity between the motor cerebellar region of the immobilized arm and the left temporal lobe, and an increase between the same cerebellar region and the supplementary motor area. Overall, changes in connectivity occurred in regions typically associated with error detection and motor learning, suggesting a potential functional reorganization of the brain within 14 days of elbow immobilization.
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 | 0.000 |
| 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".