Responses of MST neurons to plaid stimuli
Bibliographic record
Abstract
The estimation of motion information from retinal input is a fundamental function of the primate dorsal visual pathway. Previous work has shown that this function involves multiple cortical areas, with each area integrating information from its predecessors. Compared with neurons in the primary visual cortex (V1), neurons in the middle temporal (MT) area more faithfully represent the velocity of plaid stimuli, and the observation of this pattern selectivity has led to two-stage models in which MT neurons integrate the outputs of component-selective V1 neurons. Motion integration in these models is generally complemented by motion opponency, which refines velocity selectivity. Area MT projects to a third stage of motion processing, the medial superior temporal (MST) area, but surprisingly little is known about MST responses to plaid stimuli. Here we show that increased pattern selectivity in MST is associated with greater prevalence of the mechanisms implemented by two-stage MT models: Compared with MT neurons, MST neurons integrate motion components to a greater degree and exhibit evidence of stronger motion opponency. Moreover, when tested with more challenging unikinetic plaid stimuli, an appreciable percentage of MST neurons are pattern selective, while such selectivity is rare in MT. Surprisingly, increased motion integration is found in MST even for transparent plaid stimuli, which are not typically integrated perceptually. Thus the relationship between MST and MT is qualitatively similar to that between MT and V1, as repeated application of basic motion mechanisms leads to novel selectivities at each stage along the pathway.
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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 | 0.001 |
| 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".