Christine Vidal

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BACKGROUND Volumetric studies have reported reductions in the size of the corpus callosum (CC) in autism, but the callosal regions contributing to this deficit have differed among studies. In this study, a computational method was used to detect and map the spatial pattern of CC abnormalities in male patients with autism. METHODS Twenty-four boys with(More)
CONTEXT We previously detected a dynamic wave of gray matter loss in childhood-onset schizophrenia that started in parietal association cortices and proceeded frontally to envelop dorsolateral prefrontal and temporal cortices, including superior temporal gyri. OBJECTIVE To map gray matter loss rates across the medial hemispheric surface, including the(More)
Children with autism spectrum disorder (ASD) exhibit characteristic cognitive and behavioral differences, but no systematic pattern of neuroanatomical differences has been consistently found. Recent neurodevelopmental models posit an abnormal early surge in subcortical white matter growth in at least some autistic children, perhaps normalizing by adulthood,(More)
The rapid creation of comprehensive brain image databases mandates the development of mathematical algorithms to uncover disease specific patterns of brain structure and function in human populations. We describe our construction of probabilistic atlases that store detailed information on how the brain varies across age and gender, across time, in health(More)
Brain imaging studies of the hippocampus in autism have yielded inconsistent results. In this study, a computational mapping strategy was used to examine the three-dimensional profile of hippocampal abnormalities in autism. Twenty-one males with autism (age: 9.5+/-3.3 years) and 24 male controls (age: 10.3+/-2.4 years) underwent a volumetric magnetic(More)
MRI scans provide exceptionally detailed information on how the human brain changes throughout childhood, adolescence, and into old age. We describe several approaches for understanding developmental changes in brain structures based on MRI. Atlas-based “parcellation” methods, for example, measure volumes of brain substructures, revealing how they change(More)
In this study, a computational mapping technique was used to examine the three-dimensional profile of the lateral ventricles in autism. T1-weighted three-dimensional magnetic resonance images of the brain were acquired from 20 males with autism (age: 10.1+/-3.5 years) and 22 male control subjects (age: 10.7+/-2.5 years). The lateral ventricles were(More)
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