“Automatic” online reach corrections are associated with individual differences in executive function.
Bibliographic record
Abstract
Previous research has demonstrated that the dorsal visual stream is able to execute rapid online movement corrections to sudden changes in target position. This “automatic pilot” can operate in the absence of visual awareness, and even under circumstances where participants are instructed to not correct their movements. In the current study, we examined the extent to which these “automatic” corrections might be related to individual differences in executive function. To examine this, healthy adult participants (n=80) completed two versions of the automatic pilot task on a touch screen: 1) a “Correct” condition in which participants were instructed to correct their movement to the new target location on jump trials, and 2) an “Ignore” condition in which participants were told to ignore any target jumps, and point to the initial target location. In addition to completing these two versions of the automatic pilot task, participants also completed the Sustained Attention to Response Task (SART), in which they were asked to respond when a number was presented, except for the number 3. Finally, participants completed self-report questionnaires indexing executive attention, impulsivity, and executive function including the Adult ADHD Self Report Scale (ASRS), the Cognitive Failures Questionnaire (CFQ), and the Behavioural Rating Inventory of Executive Function for Adults (BRIEF-A).Our results indicated that, similar to previous research, participants made significantly more corrections to target jumps in the “Correct” condition, compared to the “Ignore” condition. Importantly, “automatic” unintended corrections in the “Ignore” condition were significantly correlated with poorer scores on the ASRS, the CFQ and the BRIEF-A. However, unintended corrections were not correlated with errors or reaction times on the SART. These results suggest that the automatic pilot task is sensitive to self-reported individual differences in executive function, and may be useful as a visuomotor measure of response inhibition and cognitive control in both healthy and clinical populations.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".