A white noise "go" stimulus increases the probability of startle and response triggering by startle
Bibliographic record
Abstract
It is well known that increasing the intensity of an acoustic "go" stimulus in reaction time (RT) tasks leads to faster RTs. However, if the stimulus is sufficiently intense for a startle reaction to be elicited in the sternocleidomastoid (SCM), premotor RT is further decreased to such an extent that normal cortical stimulus-response processing is bypassed (Carlsen et al. 2007). It has been shown that there is a higher probability of producing a "startle blink" response with white noise compared to a single tone at 95 and 100 dB (Blumenthal & Berg 1986). It is unclear whether SCM is similarly affected, and thus the probability of eliciting a prepared response may differ depending on the stimulus frequency content at a given intensity. In the current experiment participants performed a button release simple RT task requiring wrist extension in response to a varied "go" stimulus. The imperative "go" signal consisted of either a 40ms, 1000 Hz tone or a 40ms, white noise pulse with an intensity of 82, 100, 108, 116 or 124 dB(A). Surface EMG was measured from the wrist extensors and the SCM, and time of button release was recorded. Results showed that for all intensities below 124 dB, probability of eliciting a SCM startle response was higher for white noise. In addition, this also resulted in a higher probability of early movement release when startled indicating that white noise may be a more effective stimulus when employing startle to investigate action preparation.Acknowledgments: Supported by the Faculty of Health Sciences, University of Ottawa
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".