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Record W3127319599 · doi:10.1162/jocn_a_01688

Coordination of Pupil and Saccade Responses by the Superior Colliculus

2021· article· en· W3127319599 on OpenAlexafffund
Chin‐An Wang, Douglas P. Munoz

Bibliographic record

VenueJournal of Cognitive Neuroscience · 2021
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsQueen's University
FundersCanadian Institutes of Health ResearchMinistry of Science and Technology, Taiwan
KeywordsSuperior colliculusSaccadePsychologyPupilNeuroscienceCognitive psychologyEye movement

Abstract

fetched live from OpenAlex

The appearance of a salient stimulus evokes saccadic eye movements and pupil dilation as part of the orienting response. Although the role of the superior colliculus (SC) in saccade and pupil dilation has been established separately, whether and how these responses are coordinated remains unknown. The SC also receives global luminance signals from the retina, but whether global luminance modulates saccade and pupil responses coordinated by the SC remains unknown. Here, we used microstimulation to causally determine how the SC coordinates saccade and pupil responses and whether global luminance modulates these responses by varying stimulation frequency and global luminance in male monkeys. Stimulation frequency modulated saccade and pupil responses, with trial-by-trial correlations between the two responses. Global luminance only modulated pupil, but not saccade, responses. Our results demonstrate an integrated role of the SC on coordinating saccade and pupil responses, characterizing luminance independent modulation in the SC, together elucidating the differentiated pathways underlying this behavior.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.056
GPT teacher head0.373
Teacher spread0.318 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations64
Published2021
Admission routes2
Has abstractyes

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