A secondary motor area contributing to interlimb coordination during visually guided locomotion in the cat
Bibliographic record
Abstract
We investigated the contribution of cytoarchitectonic cortical area 4δc, in the caudal bank of the cruciate sulcus of the cat, to the control of visually guided locomotion. To do so, we recorded the activity of 114 neurons in 4δc while cats walked on a treadmill and stepped over an obstacle that advanced toward them. A total of 84/114 (74%) cells were task-related and 68/84 (81%) of these cells showed significant modulation of their discharge frequency when the contralateral limbs were the first to step over the obstacle. These latter cells included a substantial proportion (27/68 40%) that discharged between the passage of the contralateral forelimb and the contralateral hindlimb over the obstacle, suggesting a contribution of this area to interlimb coordination. We further compared the discharge in area 4δc with the activity patterns of cells in the rostral division of the same cytoarchitectonic area (4δr), which has been suggested to be a separate functional region. Despite some differences in the patterns of activity in the 2 subdivisions, we suggest that activity in each is compatible with a contribution to interlimb coordination and that they should be considered as a single functional area that contributes to both forelimb-forelimb and forelimb-hindlimb coordination.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".