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Record W2885325071 · doi:10.1016/j.celrep.2018.06.099

Successful Reorganization of Category-Selective Visual Cortex following Occipito-temporal Lobectomy in Childhood

2018· article· en· W2885325071 on OpenAlexaff
Tina T. Liu, Adrian Nestor, Mark D. Vida, John A. Pyles, Christina Patterson, Ying Yang, Fan Yang, Erez Freud, Marlene Behrmann

Bibliographic record

VenueCell Reports · 2018
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersNational Institutes of HealthNational Eye InstituteCarnegie Mellon University
KeywordsNeuroscienceExtrastriate cortexVisual cortexPsychologyCortex (anatomy)Temporal cortexLateralization of brain functionFusiform face areaVisual fieldFace perceptionPerception

Abstract

fetched live from OpenAlex

Investigations of functional (re)organization in children who have undergone large cortical resections offer a unique opportunity to elucidate the nature and extent of cortical plasticity. We report findings from a 3-year investigation of a child, U.D., who underwent surgical removal of the right occipital and posterior temporal lobes at age 6 years 9 months. Relative to controls, post-surgically, U.D. showed age-appropriate intellectual performance and visuoperceptual face and object recognition skills. Using fMRI at five different time points, we observed a persistent hemianopia and no visual field remapping. In category-selective visual cortices, however, object- and scene-selective regions in the intact left hemisphere were stable early on, but regions subserving face and word recognition emerged later and evinced competition for cortical representation. These findings reveal alterations in the selectivity and topography of category-selective regions when confined to a single hemisphere and provide insights into dynamic functional changes in extrastriate cortical architecture.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.012
GPT teacher head0.269
Teacher spread0.257 · 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

Citations42
Published2018
Admission routes1
Has abstractyes

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