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Record W2470718307 · doi:10.16910/jemr.3.2.4

The behavioural and neurophysiological modulation of microsaccades in monkeys

2009· article· en· W2470718307 on OpenAlexafffund
Donald C. Brien, Brian D. Corneil, Jillian H. Fecteau, Andrew H. Bell, Douglas P. Munoz

Bibliographic record

VenueJournal of Eye Movement Research · 2009
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsWestern UniversityQueen's University
FundersCanadian Institutes of Health Research
KeywordsMicrosaccadePsychologyNeurophysiologySaccadeNeuroscienceEye movementCue-dependent forgettingCovertSensory cueCognitive psychologySaccadic masking

Abstract

fetched live from OpenAlex

Systematic modulations of microsaccades have been observed in humans during covert orienting. We show here that monkeys are a suitable model for studying the neurophysiology governing these modulations of microsaccades. Using various cue-target saccade tasks, we observed the effects of visual and auditory cues on microsaccades in monkeys. As in human studies, following visual cues there was an early bias in cue-congruent microsaccades followed by a later bias in cue-incongruent microsaccades. Following auditory cues there was a cue-incongruent bias in left cues only. In a separate experiment, we observed that brainstem omnipause neurons, which gate all saccades, also paused during microsaccade generation. Thus, we provide evidence that at least part of the same neurocircuitry governs both large saccades and microsaccades.

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)0.0000.000

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 head0.270
GPT teacher head0.439
Teacher spread0.170 · 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

Citations36
Published2009
Admission routes2
Has abstractyes

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