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Record W2099086668 · doi:10.1002/hbm.20931

The contrast dependence of the cortical fMRI deficit in amblyopia; a selective loss at higher contrasts

2010· article· en· W2099086668 on OpenAlexafffund
Robert F. Hess, Xingfeng Li, Guangming Lu, Benjamin Thompson, Bruce C. Hansen

Bibliographic record

VenueHuman Brain Mapping · 2010
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsContrast (vision)Stimulus (psychology)NeuroscienceVisual cortexPsychologyPsychophysicsAudiologyCognitive psychologyPerceptionMedicinePhysicsOptics

Abstract

fetched live from OpenAlex

Although there is general agreement that the fMRI cortical response is reduced in humans with amblyopia, the deficit is subtle and has little correlation with threshold-based psychophysics. From a purely contrast sensitivity perspective, one would expect fMRI responses to be selectively reduced for stimuli of low contrasts. However, to date, all fMRI stimuli used in studies of amblyopia have been of high contrast. Furthermore, if the deficit is selective for low contrasts, one would expect it to reflect a selective M-cell loss, because M-cells have much higher contrast gain than P-cells and make a larger contribution to the threshold detection of stimuli of low spatial and medium temporal frequencies. To test these two predictions, we compared % BOLD response between the eyes of normals and amblyopes for low- and high-contrast stimuli using a phase-encoded design. The results suggest that the fMRI deficit in amblyopia depends upon stimulus contrast and that it is greater at high contrasts. This is consistent with a selective P-cell contrast deficit at a precortical or early cortical site.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.790
Threshold uncertainty score0.714

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.045
GPT teacher head0.308
Teacher spread0.263 · 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

Citations46
Published2010
Admission routes2
Has abstractyes

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