What Does the Brain Do When You Fake It? An fMRI Study of Pantomimed and Real Grasping
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Bibliographic record
Abstract
Given that studying neural bases of actions is very challenging with fMRI, numerous experiments have used pantomimed actions as a proxy to studying neural circuits of real actions. However, the underlying assumption that the same neural mechanisms mediate real and pantomimed actions has never been directly tested. Moreover, the assumption is called into question by neuropsychological evidence suggesting that real actions depend on the dorsal stream of visual processing whereas pretend actions also recruit the ventral stream. Here, we directly tested these ideas in neurologically intact subjects. Ten right-handed participants performed four tasks: 1) grasping real three-dimensional objects, 2) reaching toward the objects and touching them with the knuckle without hand preshaping, 3) pantomimed grasping in an adjacent location where no object was present, and 4) pantomimed reaching toward an adjacent location. As expected, in the anterior intraparietal area, there was significantly higher activation during real grasping than that during real reaching. However, the activation difference between pantomimed grasping and pantomimed reaching did not reach statistical significance. There was also no effect of pantomimed grasping within the ventral stream, including an object-selective area in the lateral occipital cortex. Instead, we found that pantomimed grasping was mediated by right-hemisphere activation, particularly the right parietal cortex. These results suggest that areas typically invoked by real actions may not necessarily be driven by "fake" actions. Moreover, pantomimed grasping may not tap object-related areas within the ventral stream, but rather may rely on mechanisms within the right hemisphere that are recruited by artificial and less practiced actions.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 it