Spatiotemporal Structure of Nonlinear Subunits in Macaque Visual Cortex
Bibliographic record
Abstract
The primate visual system is arranged hierarchically, starting from the retina and continuing through a series of extrastriate visual areas. Selectivity for motion is first found in individual neurons in the primate visual cortex (V1), in which many simple cells respond selectively to the direction and speed of moving stimuli. Beyond simple cells, most studies of direction selectivity have focused on either V1 complex cells or neurons in the middle temporal area (MT/V5). To understand how visual information is transferred along this pathway, we have studied all three types of neurons, using a reverse correlation procedure to obtain high spatial and temporal resolution maps of activity for different motion stimuli. Most complex and MT cells showed strong second-order interactions, indicating that they were tuned for particular displacements of an apparent motion stimulus. The spatiotemporal structure of these interactions showed a high degree of similarity between the populations of V1 complex cells and MT cells, in terms of the spatiotemporal limits and preferences for motion and their two-dimensional spatial structure. Much of the structure in the V1 and MT second-order kernels could be accounted for on the basis of the first-order responses of V1 simple cells, under the assumption of a Reichardt or motion-energy type of computation.
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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 | 0.001 |
| 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".