Forward Versus Backward Walking: Transfer of Podokinetic Adaptation
Bibliographic record
Abstract
We asked whether podokinetic adaptation to walking on a circular treadmill transfers to different forms of locomotion. Subjects were blindfolded and asked to walk straight across the floor, in the forward and backward directions, following podokinetic (PK) stimulation that consisted of 30 min of forward walking-in-place on the perimeter of a disk rotating in the clockwise direction. During both forward and backward walking following forward-walking PK stimulation, subjects involuntarily walked along curved trajectories at angular velocities well above vestibular threshold, although they perceived that they were walking along straight paths. The curved paths of forward and backward walking were indistinguishable from one another. Transfer of PK adaptations acquired during forward walking on the turntable to backward walking trials suggests that the PK system controls general locomotor trajectory. Adaptation of the system thus influences forms of locomotion other than that used during acquisition of the adaptation. This transfer also supports the concept that forward and backward walking are controlled by neural networks that share common elements. An interesting feature of the transfer of PK adaptation is that for both forward and backward walking, subjects turned in a counterclockwise direction. As such, the direction of relative rotation between the trunk and feet was maintained for both forward and backward walking. However, the relationship of the lower extremities to the center of rotation was not preserved. The left limb was the inner leg during PK stimulation and forward walking after adaptation, but the left leg was the outer leg during backward walking. These results suggest that PK adaptation affects general locomotor trajectory via a remodeling of the rotational relationship between the trunk and the feet.
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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 | 0.000 | 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 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".