Movement Strategy Moderates the Effect of Spatially Congruent Cues on the Stability of Rhythmic Bimanual Finger Movements
Bibliographic record
Abstract
Spatially congruent cues increase the speed of bimanual reach decisions compared with abstract symbolic cues, particularly for asymmetric reaches. Asymmetric rhythmic bimanual movements are less stable than symmetric rhythmic movements, but it is not well understood if spatially congruent cues similarly increase the stability of asymmetric rhythmic bimanual movements. To address this question, in Experiment 1, participants performed symmetric and asymmetric bimanual rhythmic finger tapping movements at different movement frequencies in time with flickering spatially congruent and abstract symbolic stimuli. As expected, symmetric movements were more stable. Spatially congruent cues similarly increased the stability of symmetric and asymmetric movements compared with abstract symbolic cues. The benefits of spatial congruence and movement symmetry were restricted to high movement frequencies (>2 Hz). To better understand if the emergence of these effects at high movement frequencies was driven by a change in movement strategy, in Experiment 2, video of the hands was concurrently recorded during task performance. Markerless motion tracking software revealed that participants switched from discontinuous to continuous movement strategies with increasing movement frequency. Because discontinuous and continuous movements are thought to be controlled by distinct neurocognitive systems, this might explain why the beneficial effects of spatial congruence and response symmetry emerged only at high movement frequencies. Overall, results from the current study indicate that the perceptual quality of the stimulus use to cue movement frequency can have powerful effects on the stability of rhythmic bimanual movements, but that these effects may depend on whether discontinuous or continuous movement strategies are selected.
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 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 | 0.003 |
| 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 | 0.001 |
| 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".