Disrupting somatosensory processing impairs motor execution but not motor imagery
Bibliographic record
Abstract
While motor imagery (MI) is thought to be 'functionally equivalent' with motor execution (ME), the equivalence of feedforward/back mechanisms between the two modalities is unexplored. Here, we tested the equivalence of these mechanisms between MI and ME via two experiments designed to probe the role of somatosensory processing (Exp 1), and cognitive processing (Exp 2). All participants engaged in a force-matching task adapted for MI. A reference force was applied (1-10) to one index finger while participants matched the force with their opposite index finger via ME or MI (control conditions). Participants then rated the force (1-10). Exp 1: Participants (N = 27) additionally performed the task with tactile stimulation (ME+TAC, MI+TAC). Exp 2: Participants (N = 15) performed the task in dual-task conditions (ME+COG, MI+COG). Pearson's correlations were computed to test the association between reference forces and force ratings in each condition. Within each practice modality, effect sizes were calculated on resultant correlation coefficients between control and experimental conditions (e.g., MI minus MI+TAC). Results indicate that (Exp 1) tactile stimulation impaired performance in ME (d = 0.46) but not MI (d = -0.02). Dual-task conditions (Exp 2) impaired performance to a greater extent in MI (d = 0.70) than ME (d = -0.49). The dissociable pattern of results suggests while somatosensory processing is critical for ME, it is not for MI. In contrast, MI may rely on cognitive resources not required by ME. Overall, findings indicate a functional equivalence between feedforward mechanisms in MI and ME may not exist.Acknowledgments: This work was supported by internal UBC funding (ASPIRE) awarded to SK.
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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 | 0.001 |
| 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".