Advance knowledge of upcoming startle stimulus does not inhibit the startle reflex during a reaction time task
Bibliographic record
Abstract
The startle reflex is a defensive physiological response to an unexpected and intense stimulus, resulting in a generalized flexion response that typically includes activation in the sternocleidomastoid (SCM) muscle. A startling acoustic stimulus (SAS) can also involuntarily trigger the release of a pre-planned movement with decreased latency, a phenomenon termed the StartReact effect (Carlsen et al., 2004). It is generally accepted that only an unexpected, intense stimulus leads to an overt startle reflex. However, because startle habituation is attenuated during reaction (RT) time tasks, it is unclear whether foreknowledge of an impending SAS would have any effect on the startle reflex or the RT speeding effect of startle. To test this, sixteen participants completed a simple RT task consisting of two sequential blocks. In one block, the SAS, which replaced the usual go-signal, was randomly presented in 20% of trials without the knowledge of the participants. In the other, participants were warned of the upcoming SAS. One group completed the random block first, while a second completed the warned block first. Results showed that advance knowledge of an upcoming SAS had no effect on the incidence of observing a startle reaction (p = .971), but led to significant RT savings in both control and startle trials (p = .019). These data suggest that when used in the context of a RT task, a SAS does not need to be unexpected in order to elicit a startle reaction and speeded RTs, and can benefit advance preparation. Acknowledgments: Supported by NSERC and the Ontario Ministry of Research and Innovation
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".