Modulation of tactile suppression during goal-directed movement
Bibliographic record
Abstract
When we move our ability to detect tactile events on the moving limb is reduced. This process, known as movement-related tactile suppression, prevents unimportant sensory information from bombarding our central nervous system. This study explored whether movement-related suppression can be modulated according to task-relevance. In three experiments participants performed volitional self-driven (Experiment 1-3) and motor-driven (Experiment 1-2) reaching and grasping movements. Over the course of the movement, weak electrical stimulation was presented at task-relevant (i.e., index finger and thumb) and irrelevant sites (i.e., forearm) on the moving limb. In Experiment 1, participants displayed reduced detectability during movement (90% resting detection). This was true for all locations on the moving limb irrespective of task-relevance and during both self and motor-driven movements. In Experiments 2 and 3 a range of stimulus amplitudes were presented to one task relevant location during both self and motor-driven movements (Experiment 2) and to a task relevant and irrelevant site during self-driven movements (Experiment 3). This change in methodology allowed us to get a direct estimate of perceptual thresholds and asses the magnitude of movement-related tactile suppression. During both self and motor-driven movement, participants exhibited an increased perceptual threshold at the index finger (Experiment 2). The magnitude of suppression however, was greater at the irrelevant site (forearm) than at the relevant site (index finger; Experiment 3). Collectively these experiments suggest that although tactile suppression may be a general consequence of movement, this suppression can be modulated in a relevance-dependent manner.Acknowledgments: Supported by the Natural Sciences and Engineering Research Council of Canada
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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 | 0.002 |
| 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".