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Record W3159892708 · doi:10.1101/2021.04.27.441700

Exogenous attention generalizes location transfer of perceptual learning in adults with amblyopia

2021· preprint· en· W3159892708 on OpenAlexfundno aff

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2021
Typepreprint
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsnot available
FundersDivision of Graduate EducationYork UniversityNational Science Foundation
KeywordsPerceptual learningNeurotypicalCovertPerceptionPopulationVisual perceptionTask (project management)Facilitation

Abstract

fetched live from OpenAlex

SUMMARY Visual perceptual learning (VPL) is a behavioral manifestation of brain neuroplasticity. However, its practical effectiveness is limited because improvements are often specific to the trained conditions and require significant time and effort. It is critical to understand the conditions that promote learning and transfer. Covert endogenous (voluntary) and exogenous (involuntary) spatial attention help overcome VPL location specificity in neurotypical adults, but whether they also do so for people with atypical visual development is unknown. This is the first study to investigate the role of exogenous attention during VPL in adults with amblyopia, an ideal population given their asymmetrically developed, but highly plastic, visual cortex. Here we show that training on a discrimination task leads to improvements in foveal contrast sensitivity, acuity, and stereoacuity. Remarkably, exogenous attention helps generalize learning beyond trained spatial locations. Our findings reveal that attention can enhance the effectiveness of perceptual learning during rehabilitation of visual 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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.027
GPT teacher head0.244
Teacher spread0.217 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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