Posterior parietal cortex estimates the relationship between object and body location during locomotion
Bibliographic record
Abstract
We test the hypothesis that the posterior parietal cortex (PPC) contributes to the control of visually guided locomotor gait modifications by constructing an estimation of object location relative to body state, and in particular the changing gap between them. To test this hypothesis, we recorded neuronal activity from areas 5b and 7 of the PPC of cats walking on a treadmill and stepping over a moving obstacle whose speed of advance was varied (slowed or accelerated with respect to the speed of the cat). We found distinct populations of neurons in the PPC, primarily in area 5b, that signaled distance- or time-to-contact with the obstacle, regardless of which limb was the first to step over the obstacle. We propose that these cells are involved in a sensorimotor transformation whereby information on the location of an obstacle with respect to the body is used to initiate the gait modification.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".