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Record W4400122652 · doi:10.31234/osf.io/3mxh7

Temporal acuity of vision decreases with eccentricity and is associated with schizotypy

2024· preprint· en· W4400122652 on OpenAlexfundno aff
François R. Foerster, Anne Giersch, Paola Agalliu, Axel Cleeremans

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsnot available
FundersFonds De La Recherche Scientifique - FNRSCanadian Institute for Advanced Research
KeywordsSchizotypyEccentricity (behavior)Visual acuityPsychologyCognitive psychologyAudiologyOptometryMedicineOphthalmologyNeuroscienceSocial psychologyCognition

Abstract

fetched live from OpenAlex

Temporal acuity reflects our ability to consciously detect a perceptual change within a short period of time, such as an asynchrony separating two visual events. Asynchrony discrimination skills shape the temporal structure of perception, by determining whether distinct information is bound or segregated in time. Given the crucial role of peripheral vision in everyday tasks, such as dynamically adapting our locomotion, we evaluated asynchrony discrimination in periphery under conditions of natural vision. Further, previous research showed perceptual disturbances in patients with schizophrenia, with defective visual asynchrony processing. Exploring whether such a deficit extends to neurotypical individuals with schizotypal traits and varies across the visual fields is essential given the significance of abnormal perceptual experiences in the schizophrenia spectrum. In this virtual reality study, fifty participants performed a simultaneity judgment task within immersive virtual reality to estimate visual temporal acuity across space and filled the schizotypal personality questionnaire. Participants assessed the presence or absence of a 22 ms asynchrony between the onset of two targets. Targets were located at different eccentricities spanning the whole binocular fields and across horizontal and vertical meridians. Topographic maps were computed to visualize asynchrony discrimination skills across the visual space in two different (natural and artificial) virtual environments. Our results are threefold. First, the temporal acuity estimated in a traditional psychophysical visual context does not generalize to an ecologically-valid landscape scenery, such that asynchrony discrimination is reduced under natural vision conditions. Second, the temporal acuity of vision decreases as the eccentricity of the targets increases, but it remains constant across meridians. Third, this deterioration of temporal coding in peripheral vision concerns non-medicated individuals self-reporting perceptual and cognitive schizotypal traits. The results suggest that distinct temporal mechanisms in central and peripheral vision drive visual temporal acuity. Furthermore, perceptual and cognitive disturbances in the neurotypical population may be linked to abnormal temporal processing in peripheral vision. Overall, these findings may pave the way toward novel investigations into the variety of time experiences across neurotypical and neurodivergent populations.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.048
GPT teacher head0.328
Teacher spread0.280 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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