Saccade Suppression by Electrical Microstimulation in Monkey Caudate Nucleus
Bibliographic record
Abstract
It has been suggested that the caudate nucleus, the input stage of the basal ganglia, facilitates and suppresses saccade initiation based on its anatomical characteristics. Although the involvement of the caudate nucleus in saccade facilitation has been shown previously, it is still unclear whether the caudate nucleus is also involved in saccade suppression. Here, we revealed the direct involvement of the caudate nucleus in saccade suppression by electrical microstimulation in behaving monkeys. We delivered microstimulation to the caudate nucleus while monkeys performed the prosaccade (look toward a peripheral visual stimulus) and antisaccade (look away from the stimulus) paradigm. The reaction times of contralateral saccades were prolonged on both prosaccade and antisaccade trials. The suppression effects on reaction times were stronger on prosaccade trials compared with antisaccade trials. The analysis of reaction time distributions using the linear approach to threshold with ergodic rate model (LATER model) revealed that microstimulation prolonged reaction times by reducing the rate of rise to the threshold for saccade initiation. Microstimulation also worsened correct performance rates for contralateral saccades. The same microstimulation prolonged and/or shortened the reaction times of ipsilateral saccades, although the effects were not as consistent as those on contralateral saccades. We conclude that caudate signals are sufficient to suppress contralateral saccades and influence saccadic decision by controlling contralateral and ipsilateral saccade commands at the same time.
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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) | 0.000 | 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".