Rule-dependent Activity for Prosaccades and Antisaccades in the Primate Prefrontal Cortex
Bibliographic record
Abstract
Everyday life typically requires behavior that involves far more than simple stimulus-response associations. Environmental cues are often ambiguous and require different actions depending on the situation. The prefrontal cortex (PFC) is thought to be crucial for this flexible control of behavior. An important task that probes this ability is the antisaccade task in which subjects have to suppress a glance towards a suddenly presented peripheral stimulus and instead look away from the stimulus to its mirror location. Here we recorded the activity of PFC neurons in monkeys trained to alternate between blocks of prosaccade and antisaccade trials with no external instruction cues. We found that the activity of many neurons was different between the two tasks during the fixation period before the peripheral stimulus was presented. These differences were already present on the first correct trials after a task switch. The activity of these neurons also discriminated between correct responses and errors. We hypothesize that the PFC provides bias signals to saccade-related areas that are necessary to preset the oculomotor system for different tasks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.001 | 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".