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Perceptual Function and Category-Selective Neural Organization in Children with Resections of Visual Cortex

2019· article· en· W2954790583 on OpenAlexaff
Tina T. Liu, Erez Freud, Christina Patterson, Marlene Behrmann

Bibliographic record

VenueJournal of Neuroscience · 2019
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsYork University
FundersNational Institutes of HealthNational Eye InstituteCarnegie Mellon University
KeywordsPsychologyVisual cortexPerceptionNeuroscienceCognitive psychologyPopulationCortex (anatomy)Medicine

Abstract

fetched live from OpenAlex

The consequences of cortical resection, a treatment for humans with pharmaco-resistant epilepsy, provide a unique opportunity to advance our understanding of the nature and extent of cortical (re)organization. Despite the importance of visual processing in daily life, the neural and perceptual sequellae of occipitotemporal resections remain largely unexplored. Using psychophysical and fMRI investigations, we compared the neural and visuoperceptual profiles of 10 children or adolescents following unilateral cortical resections and their age-and gender-matched controls. Dramatically, with the exception of two individuals, both of whom had relatively greater cortical alterations, all patients showed normal perceptual performance on tasks of intermediate-and high-level vision, including face and object recognition. Consistently, again with the exception of the same two individuals, both univariate and multivariate fMRI analyses revealed normal selectivity and representational structure of category-selective regions. Furthermore, the spatial organization of categoryselective regions obeyed the typical medial-to-lateral topographic organization albeit unilaterally in the structurally preserved hemisphere rather than bilaterally. These findings offer novel insights into the malleability of cortex in the pediatric population and suggest that, although experience may be necessary for the emergence of neural category-selectivity, this emergence is not necessarily contingent on the integrity of particular cortical structures.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.280

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 communication0.0000.001
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 head0.020
GPT teacher head0.266
Teacher spread0.246 · 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 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

Citations27
Published2019
Admission routes1
Has abstractyes

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