Investigating the neuroanatomy underlying proprioception using a stroke model
Bibliographic record
Abstract
Neuroanatomical investigations have associated cortical areas, beyond Primary Somatosensory Cortex (S1), with impaired proprioception. Cortical regions have included temporoparietal (TP) regions (supramarginal gyrus, superior temporal gyrus, Heschl's gyrus) and insula. Previous approaches have struggled to account for concurrent damage across multiple brain regions. Here, we used a targeted lesion analysis approach to examine the impact of specific combinations of cortical and sub-cortical lesions and quantified the prevalence of proprioceptive impairments when different regions are damaged or spared. Seventy-seven individuals with stroke (49 male; 28 female) were identified meeting prespecified lesion criteria based on MRI/CT imaging: 1) TP lesions without S1, 2) TP lesions with S1, 3) isolated S1 lesions, 4) isolated insula lesions, and 5) lesions not impacting these regions (other regions group). Initially, participants meeting these criteria (1-4) were grouped together into right or left lesion groups and compared to each other, and the other regions group (5), on a robotic Arm Position Matching (APM) task and a Kinesthesia (KIN) task. We then examined the behaviour of individuals that met each specific criteria (groups 1-5). Proprioceptive impairments were more prevalent following right hemisphere lesions than left hemisphere lesions. The extent of damage to TP regions correlated with performance on both robotic tasks. Even without concurrent S1 lesions, TP and insular lesions were associated with impairments on the APM and KIN tasks. Finally, lesions not impacting these regions were much less likely to result in impairments. This study highlights the critical importance of TP and insular regions for accurate proprioception. SIGNIFICANCE STATEMENT: This work advances our understanding of the neuroanatomy of human proprioception. We validate the importance of regions, beyond the dorsal column medial lemniscal pathway and S1, for proprioception. Further, we provide additional evidence of the importance of the right hemisphere for human proprioception. Improved knowledge on the neuroanatomy of proprioception is crucial for advancing therapeutic approaches which target individuals with proprioceptive impairments following neurological injury or with neurological disorders.
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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 | 0.000 |
| 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) | 0.002 | 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".