1 Supplemental Data: Brief motion stimuli preferentially activate surround-suppressed neurons in macaque visual area MT
Bibliographic record
Abstract
Electrophysiological recordings. Two rhesus macaque monkeys took part in the experiments. Both underwent a sterile surgical procedure to implant a headpost and recording cylinder, and following recovery were seated comfortably in a primate chair (Crist Instruments) and trained to fixate a small red spot on a computer monitor in return for a liquid reward. Eye position was monitored at 200 Hz with an infrared camera (SR Research), and required to be within 2º of the fixation point in order for the reward to be dispensed. All aspects of the experiments were approved by the Animal Care Committee of the Montreal Neurological Institute, and were in compliance with regulations established by the Canadian Council on Animal Care We recorded from well-isolated single neurons in area MT. Single waveforms were sorted online and then re-sorted offline, using spike-sorting software (Plexon, Inc). Area MT was identified based on anatomical MRI scans, the prevalence of direction-selective neurons, and on the correlation between receptive field size and eccentricity. We recorded from neurons with receptive fields centered at a mean eccentricity of 12.1o (s.d. 4.1º). The eccentricities for the surround-suppressed neurons were 11.7o (s.d. 4.5º), while those for the non-suppressed neurons were 12.4o (s.d. 3.8º). This difference was not significant (t-test, p = 0.6).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.262 | 0.032 |
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".