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Record W1982197374 · doi:10.1002/hbm.20887

Neuroanatomical differences in brain areas implicated in perceptual and other core features of autism revealed by cortical thickness analysis and voxel‐based morphometry

2009· article· en· W1982197374 on OpenAlexafffund
Krista L. Hyde, Fabienne Samson, Alan C. Evans, Laurent Mottron

Bibliographic record

VenueHuman Brain Mapping · 2009
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversité de MontréalMcGill UniversityHôpital Rivière-des-PrairiesMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health Research
KeywordsAutismPsychologyVoxel-based morphometryBrain morphometryPerceptionWhite matterVoxelAutism spectrum disorderNeuroscienceBrain sizeDevelopmental psychologyAudiologyMagnetic resonance imagingMedicine

Abstract

fetched live from OpenAlex

Autism spectrum disorder is a complex neurodevelopmental variant thought to affect 1 in 166 [Fombonne (2003): J Autism Dev Disord 33:365-382]. Individuals with autism demonstrate atypical social interaction, communication, and repetitive behaviors, but can also present enhanced abilities, particularly in auditory and visual perception and nonverbal reasoning. Structural brain differences have been reported in autism, in terms of increased total brain volume (particularly in young children with autism), and regional gray/white matter differences in both adults and children with autism, but the reports are inconsistent [Amaral et al. (2008): Trends Neurosci 31:137-145]. These inconsistencies may be due to differences in diagnostic/inclusion criteria, and age and Intelligence Quotient of participants. Here, for the first time, we used two complementary magnetic resonance imaging techniques, cortical thickness analyses, and voxel-based morphometry (VBM), to investigate the neuroanatomical differences between a homogenous group of young adults with autism of average intelligence but delayed or atypical language development (often referred to as "high-functioning autism"), relative to a closely matched group of typically developing controls. The cortical thickness and VBM techniques both revealed regional structural brain differences (mostly in terms of gray matter increases) in brain areas implicated in social cognition, communication, and repetitive behaviors, and thus in each of the core atypical features of autism. Gray matter increases were also found in auditory and visual primary and associative perceptual areas. We interpret these results as the first structural brain correlates of atypical auditory and visual perception in autism, in support of the enhanced perceptual functioning model [Mottron et al. (2006): J Autism Dev Disord 36:27-43].

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.047
GPT teacher head0.317
Teacher spread0.269 · 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

Citations303
Published2009
Admission routes2
Has abstractyes

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