Dwell time mediates the preparation of single vs. multiple component movements
Bibliographic record
Abstract
Targeted reciprocal aiming movements are pervasive in everyday life (e.g. video games), but it is unclear how timing parameters between elements affects the preparation of these movements. In order to probe the preparatory state of the motor system a loud (>124 dB) startling acoustic stimulus (SAS) can be used since it has been shown that the prepared and intended movement is "triggered" involuntarily by the SAS (Carlsen et al. 2012). In the present experiment, participants performed ballistic 20 deg. extension-flexion movements using the right wrist to a fixed target region in which duration of a pause (dwell time) at the target was manipulated (50ms, 200ms, or 500ms). A SAS was presented randomly during 20% of trials before either moving toward or moving away from the target region to determine how motor preparatory mode was affected by task requirements. Results indicate that for the shorter dwell times (50ms, 200ms), the SAS presented prior to the initial outward movement led to significantly earlier onsets of both the outward and return components (p's < .05). In contrast, for the long dwell time (500ms), only the outward component of the movement was elicited early. Similar results were seen for SAS delivered prior to exiting the target region. These findings suggest that for long dwell times the movement was planned as two separate components while for shorter dwell times (
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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 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".