Tool and hand adaptation and localization in immersive virtual reality
Bibliographic record
Abstract
Abstract The human brain readily adapts movements to achieve motor goals. Most visuomotor adaptation studies use planar reaching with a cursor, where misaligned feedback leads to compensatory adjustments, reach aftereffects, and shifts in perceived hand location. Whether these effects extend to more natural settings and tool use remains unclear. In the Hand Experiment, we showed that in immersive virtual reality (VR), adaptation to 30° and 60° visuomotor rotations produced robust reach aftereffects and the expected shifts in hand localization. In the Pen Experiment, we extended this paradigm to a familiar hand-held tool, assessing localization of both the tool tip and the hand. Adaptation with the pen induced comparable or greater recalibration effects than with the hand-cursor, including shifts in both perceived tool and hand position. These findings demonstrate that visuomotor adaptation in immersive VR generalizes beyond cursor-based tasks, revealing how the sensorimotor system recalibrates internal representations of both the body and tools in realistic 3D environments. Author summary for PLOS ONE This study shows that when people adapt their movements in virtual reality, the brain recalibrates not only the sensed position of the hand but also of familiar tools, highlighting how we update body and tool representations in everyday-like environments.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".