Unconscious arrow stimuli do not influence motor performance automatically
Bibliographic record
Abstract
Visible arrow cues have been suggested to lead to reflexive motor responses (Kingstone and colleagues, 2002, 2009). In the current study, we examined the degree of automaticity of arrow evoked responses by presenting the arrows unconsciously. Specifically, we asked if prime arrows presented in a backward masking paradigm (and hence not seen by subjects) would influence responses even when they were irrelevant to the task (i.e. subjects were not supposed to respond to them). Subjects were instructed to reach to a centre target. If a large left (or right) visible 'mask' arrow was displayed, they were to modify their movements and land at the left (or right) target. If an arrow in the right (or left) direction was presented, subjects were to continue pointing to the centre target. Small left and right arrows, as well as neutral primes, preceded all large mask arrows. Results revealed that although subjects were not aware of them, primes influenced performance such that subjects completed a greater number of responses to the left target when the left prime was presented compared to the right and neutral primes. Arrow primes indicating the non-response (i.e. right (or left)) direction did not influence movements, resulting in similar movement kinematics on trials in which the neutral and right primes were displayed. Thus, unconscious, irrelevant arrow stimuli do not appear to influence reaching movements automatically, suggesting that they can be ignored.Acknowledgments: This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC), awarded to Erin K. Cressman.
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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".