Macaque Dorsolateral Prefrontal Cortex Does not Suppress Saccade-Related Activity in the Superior Colliculus
Bibliographic record
Abstract
Of the many functions ascribed to the dorsolateral prefrontal cortex (DLPFC), the ability to override automatic stimulus-driven behavior is one of the most prominent. This ability has been investigated extensively with the antisaccade task, which requires suppression of saccades toward suddenly appearing visual stimuli. Convergent lines of evidence have supported a model in which the DLPFC suppresses unwanted saccades by inhibiting saccade-related activity in the ipsilateral superior colliculus (SC), a midbrain oculomotor structure. Here, we carried out a direct test of this inhibitory model using unilateral cryogenic deactivation of the DLPFC within the caudal principal sulcus (cPS) and simultaneous single-neuron recording of SC saccade-related neurons in monkeys performing saccades and antisaccades. Contrary to the inhibition model, which predicts that attenuation of inhibition effected by unilateral cPS deactivation should result in activity increases in ipsilateral and decreases in contralateral SC, we observed a delayed onset of saccade-related activity in the ipsilateral SC, and activity increases in the contralateral SC. These effects were mirrored by increased error rates of ipsiversive antisaccades, and reaction times of contraversive saccades. These data challenge the inhibitory model and suggest instead that the primary influence of the DLPFC on the SC is excitatory.
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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 | 0.000 |
| 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) | 0.001 | 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".