The Effects of Implicit Motor Imagery Using the Hand Laterality Judgement Task
Bibliographic record
Abstract
Cognitive states like motor imagery (MI; simulating actions without overtly executing them) share a close correspondence with action execution, and hence, activate the motor system in a similar way. Unlike external objects, the mental rotations of one’s own hand are strongly influenced by the same motor rules and anatomical constraints that shape real movements. In view of these anatomical constraints, response times are longer for hands presented at awkward orientations (i.e., 90° lateral and 180°) and from the palm view. Conversely, hands presented in more manageable orientations (i.e., 0° and 90° medial) from back views generate the fastest responses. Palm-view stimuli are processed by similar brain regions involved in motor simulation and execution, while back-view stimuli are thought to be processed by visual areas of the brain. This supposed shift in strategy offers that when viewing back-hand stimuli, participants employ visual strategies generating the fastest responses, whereas palm-hand stimuli employ motoric strategies resulting in longer recognition times. Using the hand laterality judgment task, fifty younger adults mentally simulated hands displayed from two different viewpoints (palm and back) and in four different orientations: 0°, 90°medial, 90° lateral, and 180°. Results indicated that the fastest transformations of hands occurred at 0° and 90°M without differences between these two orientations, while the slowest hand transformation occurred at 90°L and 180°. The comparison between back and palm views revealed longer response times when hands were shown from the palm view. Results suggest that when shown palm-view stimuli, participants process hands as body parts rather than external objects. In other words, participants mentally rotate their own hands into the orientation of the visually presented hand, eliciting an implicit motor strategy. Taking this into account, it is suggestive that internal motor representations have an important role in motor planning and execution that govern real-world hand movements.
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 | 0.004 |
| 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 | 0.001 |
| 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".