Misperceptions of speed are accounted for by the responses of neurons in macaque cortical area MT
Bibliographic record
Abstract
In humans, the perceived speed of random dot patterns (RDP) moving within small apertures is faster than that of RDPs moving within larger apertures at the same physical speed. To investigate the neural basis of this illusion, we recorded the responses of direction- and speed-selective neurons in the middle temporal area (MT) of macaque monkeys to stimuli varying in size and speed. Our results show that the preferred speed of MT neurons is slower for smaller stimuli. This effect was larger for neurons preferring faster speeds, matching our psychophysical observation in human subjects that the magnitude of the misperception is larger at higher stimulus speeds. Our physiological data indicate that, across a population of speed-tuned neurons in MT, decreasing the size of a stimulus would shift the activity profile to neurons tuned for higher speeds. Modeling a labeled-line readout of this shifted profile, we show an increased apparent speed, in line with the psychophysical observations. This link strengthens the evidence for a causal role of area MT in speed perception. The systematic shift in tuning curves of single neurons with stimulus size might reflect a general mechanism for feature-mismatch illusions in visual perception.
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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 | 0.003 |
| 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 | 0.001 |
| 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 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".