Lesion locations associated with persistent proprioceptive impairment in the upper limbs after stroke
Bibliographic record
Abstract
Proprioceptive deficits are common after stroke and have been associated with poorer recovery. Relatively little is known about the brain regions beyond primary somatosensory cortex that contribute to the percept of proprioception in humans. We examined a large sample (n = 153) of stroke survivors longitudinally to determine which brain regions were associated with persistent post-stroke proprioceptive deficits. A robotic exoskeleton quantified two components of proprioception, position sense and kinesthesia (movement sense), at 2 weeks and again at 6 months post-stroke. A statistical region of interest (sROI) analysis compared the lesion-behaviour relationships of those subjects with cortical and subcortical stroke (n = 136). The impact of damage to brainstem and cerebellum (n = 17) was examined separately. Results indicate that damage to the supramarginal gyrus, the arcuate fasciculus, and Heschl's gyrus are associated with deficits in position sense and kinesthesia at 6 months post-stroke. These results suggest that regions beyond the primary somatosensory cortex contribute to our sense of limb position and movement. This information extends our understanding of proprioceptive processing and may inform personalized interventions such as non-invasive brain stimulation where specific brain regions can be targeted to potentially improve stroke recovery.
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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".