Fixational saccades reflect volitional action preparation
Bibliographic record
Abstract
Human volitional actions are preceded by preparatory processes, a critical mental process of cognitive control for future behavior. Volitional action preparation is regulated by large-scale neural circuits including the cerebral cortex and the basal ganglia. Because volitional action preparation is a covert process, the network dynamics of such neural circuits have been examined by neuroimaging and recording event-related potentials. Here, we examined whether such covert processes can be measured by the overt responses of fixational saccades (including microsaccades), the largest miniature eye movements that occur during eye fixation. We analyzed fixational saccades while adult humans maintained fixation on a central visual stimulus as they prepared to generate a volitional saccade in response to peripheral stimulus appearance. We used the antisaccade paradigm, in which subjects generate a saccade toward the opposite direction of a peripheral stimulus. Appropriate antisaccade performance requires the following two aspects of volitional control: 1) facilitation of saccades away from the stimulus and 2) suppression of inappropriate saccades toward the stimulus. We found that fixational saccades that occurred before stimulus appearance reflected the dual preparatory states of saccade facilitation and suppression and correlated with behavioral outcome (i.e., whether subjects succeeded or failed to cancel inappropriate saccades toward the stimulus). Moreover, fixational saccades explained a large proportion of individual differences in behavioral performance (poor/excellent) across subjects. These results suggest that fixational saccades predict the outcome of future volitional actions and may be used as a potential biomarker to detect people with difficulties in volitional action preparation.
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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 | 0.001 |
| 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".