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Coding of Microsaccades in Three-Dimensional Space by Premotor Saccadic Neurons

2012· article· en· W2033707743 on OpenAlexaff
Marion R. Van Horn, Kathleen E. Cullen

Bibliographic record

VenueJournal of Neuroscience · 2012
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsMcGill University
Fundersnot available
KeywordsMicrosaccadeSaccadic maskingFixation (population genetics)Eye movementNeuroscienceSaccadic suppression of image displacementPsychologyVisual spaceVisual perceptionComputer visionPerceptionArtificial intelligenceComputer scienceBiology

Abstract

fetched live from OpenAlex

Microsaccades are small, involuntary eye movements that are produced during fixation. While accurate visual perception requires precise binocular coordination during fixation, previous studies of the neural control of microsaccades measured the movement of one eye only. Here we show how premotor saccadic neurons control these small fixational eye movements in three-dimensional space. Microsaccadic eye movements, produced by monkeys trained to fixate targets presented at different depths, were similarly distributed in three-dimensional space during both near and far viewing. Single unit recordings of the neural activity of premotor neurons further revealed that the brainstem saccadic circuitry controls these minute disconjugate shifts of gaze by preferentially encoding the dynamic movement of an individual eye (i.e., integrated control of conjugate and vergence motion). These findings challenge the traditional notion that microsaccades are strictly conjugate and have important implications for studies that use microsaccades to evaluate visual and attentional processing, as well as certain neurological disorders.

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)0.001
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 score0.034
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.072
GPT teacher head0.331
Teacher spread0.259 · 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

Citations42
Published2012
Admission routes1
Has abstractyes

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