The contribution of area MT to visual motion perception depends on training
Bibliographic record
Abstract
Summary Perceptual decisions require the transformation of raw sensory inputs into cortical representations suitable for stimulus discrimination. One of the best-known examples of this transformation involves the middle temporal area (MT) of the primate visual cortex. Area MT provides a robust representation of stimulus motion, and previous work has shown that it contributes causally to performance on motion discrimination tasks. Here we report that the strength of this contribution can be highly plastic: Depending on the recent training history, pharmacological inactivation of MT can severely impair motion discrimination, or it can have little detectable influence. Similarly, depending on training, microstimulation can bias motion perception or simply introduce noise. Further analysis of neural and behavioral data suggests that training shifts the readout of motion information between MT and lower-level cortical areas. These results show that the contribution of individual brain regions to conscious perception can shift flexibly depending on sensory experience.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".