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The fidelity of the cortical retinotopic map in human amblyopia

2007· article· en· W1931135842 on OpenAlexafffund
Xingfeng Li, Serge O. Dumoulin, Behzad Mansouri, Robert F. Hess

Bibliographic record

VenueEuropean Journal of Neuroscience · 2007
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsRetinotopyReceptive fieldVisual cortexVisual fieldNeuroscienceCortex (anatomy)Visual systemSurround suppressionComputer visionPsychologyComputer scienceArtificial intelligenceVisual perceptionPerception

Abstract

fetched live from OpenAlex

To delineate the fidelity of the functional cortical organization in humans with amblyopia, we undertook an investigation into how spatial information is mapped across the visual cortex in amblyopic observers. We assessed whether the boundaries of the visual areas controlled by the amblyopic and fellow fixing eye are in the same position, the fidelity of the retinotopic map within different cortical areas and the average receptive field size in different visual areas. The functional organization of the visual cortex was reconstructed using a fMRI phase-encoded retinotopic mapping analysis. This method sequentially stimulates each point in the visual field along the axes of a polar-coordinate system, thereby reconstructing the representation of the visual field on the cortex. We found that the cortical areas were very similar in normals and amblyopes, with only small differences in boundary positions of different visual areas between fixing and fellow amblyopic eye activation. Within these corresponding visual areas, we did find anomalies in retinotopy in some but not all amblyopes that were not simply a consequence of the poorer functional responses and affected central and peripheral field regions. Only a small increase in the average (or collective) receptive field size was found for full-field representation in amblyopes and none at all for central field representation. The former may simply be a consequence of the poorer functional responses.

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)0.004
metaresearch head score (Gemma)0.002
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 score0.736
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.079
GPT teacher head0.345
Teacher spread0.266 · 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

Citations57
Published2007
Admission routes2
Has abstractyes

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