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Record W3176103694 · doi:10.1162/jocn_a_01750

Dissociable Contribution of Extrastriate Responses to Representational Enhancement of Gaze Targets

2021· article· en· W3176103694 on OpenAlexaff
Yaser Merrikhi, Mohammad Shams-Ahmar, Hamid Karimi-Rouzbahani, Kelsey Clark, Reza Ebrahimpour, Behrad Noudoost

Bibliographic record

VenueJournal of Cognitive Neuroscience · 2021
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsMcGill University
FundersNational Institute of Neurological Disorders and StrokeNational Eye InstituteNational Institute of Mental HealthNational Institutes of Health
KeywordsPsychologySaccadeSaccadic maskingNeuroscienceVisual cortexEye movementGazePerceptionPopulationSaccadic suppression of image displacementVisual perceptionCognitive psychologyExtrastriate cortexCommunication

Abstract

fetched live from OpenAlex

Before saccadic eye movements, our perception of the saccade targets is enhanced. Changes in the visual representation of saccade targets, which presumably underlie this perceptual benefit, emerge even before the eye begins to move. This perisaccadic enhancement has been shown to involve changes in the response magnitude, selectivity, and reliability of visual neurons. In this study, we quantified multiple aspects of perisaccadic changes in the neural response, including gain, feature tuning, contrast response function, reliability, and correlated activity between neurons. We then assessed the contributions of these various perisaccadic modulations to the population's enhanced perisaccadic representation of saccade targets. We found a partial dissociation between the motor information, carried entirely by gain changes, and visual information, which depended on all three types of modulation. These findings expand our understanding of the perisaccadic enhancement of visual representations and further support the existence of multiple sources of motor modulation and visual enhancement within extrastriate visual cortex.

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)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
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 score0.064
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.075
GPT teacher head0.388
Teacher spread0.313 · 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.

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

Citations12
Published2021
Admission routes1
Has abstractyes

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