Tactile suppression is enhanced following a startling acoustic stimulus
Bibliographic record
Abstract
The ability to perceive a tactile stimulus is reduced in a moving limb. This sensory attenuation effect, termed tactile suppression, is attributed to movement-related gating that allows the central nervous system to selectively process sensory information. However, the origin of this gating is debated, with some accounts implicating a forward-model, and others attributing the effect to backward-masking from peripheral reafference. The present study investigated the role of voluntary response initiation processes in tactile suppression by employing a startling acoustic stimulus (SAS) to trigger the early release of a planned movement independent of voluntary mechanisms. A forward-model account would predict that the timing of the suppression would be related to the expected time of voluntary initiation of the response, whereas a reafference account would predict that the suppression is linked directly to the timing of the motor act. Participants (n=10) performed a simple reaction time task requiring lifting the hand off a switch as quickly as possible following an auditory Go-signal, which was occasionally replaced with a 120dB SAS. A near-threshold electrical stimulus was applied to the moving hand at various time-points (50-170ms) after the Go-signal and participants reported whether they detected it. Preliminary results revealed detection rate was significantly lower for SAS trials at all stimulation times, suggesting that suppression does not depend on voluntary initiation but is linked to the production of the motor response. Moreover, detection rate was significantly lower on SAS trials even when time-locked to movement onset, suggesting that SAS may have further impeded sensory processing.
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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) | 0.002 | 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".