Response preparation and execution during intentional bimanual pattern switching
Bibliographic record
Abstract
During continuous bimanual coordination, in-phase (IP; 0° relative phase) and anti-phase (AP; 180° relative phase) patterns can be stably performed without practice. Paradigms in which participants are required to intentionally switch between these coordination patterns have been used to investigate the interaction between the performer’s intentions and intrinsic dynamics of the body’s preferred patterns. The current study examined the processes associated with switching preparation and execution through the use of a startling acoustic stimulus (SAS) as the switch stimulus. A SAS is known to involuntarily trigger preprogrammed responses at a shortened latency and, thus, can be used to probe advance preparation. Participants performed cyclical IP and AP bimanual elbow extension-flexion movements in which they were required to switch patterns in response to an auditory switch cue, which was either nonstartling (80 dB) or a SAS (120 dB). Results indicated that reaction time to the switch stimulus (i.e., switch onset) was significantly reduced on startle trials, indicative of advance preparation of the switch response. Similarly, switching time was reduced on startle trials, which was attributed to increased neural activation caused by the SAS. Switching time was also shorter for AP to IP trials, but only when the switching stimulus occurred at either the midpoint or reversal locations within the movement cycle, suggesting that the switch location may affect the intrinsic dynamics of the system. NEW & NOTEWORTHY The current study provides novel information regarding preparation and execution of intentional switching between in-phase and anti-phase bimanual coordination patterns. Using a startling acoustic stimulus, we provide strong evidence that the switching response is prepared before the switch stimulus, and switch execution is accelerated by the startling stimulus. In addition, the time required to switch between patterns and relative limb contribution is dependent upon where in the movement cycle the switch stimulus occurred.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".