Functional Sub-regions for Optic Flow Processing in the Posteromedial Lateral Suprasylvian Cortex of the Cat
Bibliographic record
Abstract
During locomotion, an observer sees a large and complex pattern of visual motion called optic flow. This phenomenon is characterized by elements in the environment accelerating and expanding as they move peripherally. In cats, previous studies have indicated that the posteromedial part of the lateral suprasylvian (PMLS) cortex may be involved in the processing of optic flow fields. We further addressed this issue by studying the importance of specific parameters of the optic flow patterns and investigating whether cell responses to these stimuli depend on receptive field (RF) location in the visual field. Results can be summarized as follows: approximately two-thirds of PMLS cells responded to optic flow fields and a subset of these (84/153) showed a clear direction selectivity for motion along the frontal axis. Of these units, the majority responded preferentially to expansion rather than contraction of the pattern. Cells' responses depend on RF location in the visual field. For centrally located RFs, tested both when the origin of motion was within the RF or at the area centralis, responses were generally comparable whether or not size or speed gradients were removed from the optic flow pattern. A different tendency was observed for peripherally located RFs. In general, these cells exhibited a preferred direction almost exclusively when the origin of motion was placed at the area centralis, and neuronal discharges and direction selectivity for many of them were reduced when the optic flow cues were removed from the pattern. The results of this study suggest that there may be functional differences in response properties between PMLS cells located in the central and peripheral parts of the visual field that may reflect a specialization of the PMLS cortex in optic flow processing.
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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) | 0.002 | 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".