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Record W2258214923 · doi:10.1152/jn.00987.2015

Microsaccade direction reflects the economic value of potential saccade goals and predicts saccade choice

2015· article· en· W2258214923 on OpenAlexafffund
Gongchen Yu, Baijie Xu, Yuchen Zhao, Beizhen Zhang, Mingpo Yang, Janis Ying Ying Kan, David Milstein, Dhushan Thevarajah, Michael C. Dorris

Bibliographic record

VenueJournal of Neurophysiology · 2015
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchChinese Academy of Sciences
KeywordsMicrosaccadeSaccadeSuperior colliculusPsychologyGazeEye movementCognitive psychologySaccadic maskingNeurosciencePerception

Abstract

fetched live from OpenAlex

Microsaccades are small-amplitude (typically <1°), ballistic eye movements that occur when attempting to fixate gaze. Initially thought to be generated randomly, it has recently been established that microsaccades are influenced by sensory stimuli, attentional processes, and certain cognitive states. Whether decision processes influence microsaccades, however, is unknown. Here, we adapted two classic economic tasks to examine whether microsaccades reflect evolving saccade decisions. Volitional saccade choices of monkey and human subjects provided a measure of the subjective value of targets. Importantly, analyses occurred during a period of complete darkness to minimize the known influence of sensory and attentional processes on microsaccades. As the time of saccadic choice approached, microsaccade direction became the following: 1) biased toward targets as a function of their subjective value and 2) predictive of upcoming, voluntary choice. Our results indicate that microsaccade direction is influenced by and is a reliable tell of evolving saccade decisions. Our results are consistent with dynamic decision processes within the midbrain superior colliculus; that is, microsaccade direction is influenced by the transition of activity toward caudal saccade regions associated with high saccade value and/or future saccade choice.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.389

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.055
GPT teacher head0.331
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2015
Admission routes2
Has abstractyes

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