MétaCan
Menu
Back to cohort
Record W1806292349 · doi:10.1167/15.12.434

The reorganization of extrastriate cortex in patients with lobectomy

2015· article· en· W1806292349 on OpenAlexaff
Tina Liu, Adrian Nestor, Christina Patterson, Marlene Behrmann

Bibliographic record

VenueJournal of Vision · 2015
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsHemispherectomyExtrastriate cortexVisual cortexOcular dominanceNeurosciencePsychologyCortex (anatomy)NeuroplasticityEpilepsy

Abstract

fetched live from OpenAlex

The recovery of perceptual functions that occur following cortical damage can offer key insights into the nature and plasticity of brain organization. In this respect, studies of individuals post-lobectomy/hemispherectomy offer a unique window into the nature and extent of cortical plasticity. First, in contrast with more common lesions, the extent of the damage in such patients can be extreme (i.e. an entire hemisphere in some cases) yet, at the same time, very well controlled - both cortical and subcortical structures of the remaining hemisphere are typically intact. Second, the extent of the recovery is often disproportionate relative to the extent of the damage - many compromised functions are regained partly or even completely. Using fMRI, our present work characterizes the changes in topography in extrastriate cortex in children who have undergone surgical lobectomy or hemispherectomy of ventral cortex in either hemisphere (compared with control participants who have undergone resections to other areas such as dorsal cortex). We also map language areas in each individual as an anchor for hemispheric dominance. We uncover atypicalities in the selectivity maps to common visual categories (face, object, and word) in the ventral patients and show changes in their development/reorganization over time. Overall, the current results suggest that extensive removal of visual cortex lead to atypical/diminished selectivity for common visual categories despite the absence of major recognition difficulties and that, in some cases, reorganization may result in somewhat more typical selectivity maps. Meeting abstract presented at VSS 2015

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
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 head0.028
GPT teacher head0.336
Teacher spread0.308 · 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 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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJournal of VisionSame topicAdvanced Neuroimaging Techniques and ApplicationsFrench-language works237,207