Effects of caudate microstimulation on spontaneous and purposive saccades
Bibliographic record
Abstract
Electrical stimulation has been delivered to the basal ganglia (BG) to treat intractable symptoms of a variety of clinical disorders. However, it is still unknown how such treatments improve behavioral symptoms. A difficulty of this problem is that artificial signals created by electrical stimulation interact with intrinsic signals before influencing behavior, thereby making it important to understand how such interactions between artificial and intrinsic signals occur. We addressed this issue by analyzing the effects of electrical stimulation under the following two behavioral conditions that induce different states of intrinsic signals: 1) subjects behave spontaneously without task demands; and 2) subjects perform a behavioral paradigm purposefully. We analyzed saccadic eye movements in monkeys while delivering microstimulation to the head and body of the caudate nucleus, a major input stage of the oculomotor BG. When monkeys generated spontaneous saccades, caudate microstimulation biased saccade vector endpoints toward the contralateral direction of stimulation sites. However, when caudate microstimulation was delivered during a purposive prosaccade (look toward a visual stimulus) or an antisaccade (look away from a stimulus) paradigm, it created overall ipsilateral biases by suppressing contralateral saccades more strongly than ipsilateral saccades. These results suggest that the impact of BG electrical stimulation changes dynamically depending on the state of intrinsic signals that vary under a variety of behavioral demands in everyday life.
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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".