Mapping Corpus Callosum Deficits in Autism: An Index of Aberrant Cortical Connectivity

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...

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Published in	Biological psychiatry (1969) Vol. 60; no. 3; pp. 218 - 225
Main Authors	Vidal, Christine N., Nicolson, Rob, DeVito, Timothy J., Hayashi, Kiralee M., Geaga, Jennifer A., Drost, Dick J., Williamson, Peter C., Rajakumar, Nagalingam, Sui, Yihong, Dutton, Rebecca A., Toga, Arthur W., Thompson, Paul M.
Format	Journal Article
Language	English
Published	New York, NY Elsevier Inc 01.08.2006 Elsevier Science
Subjects	Adolescent Analysis of Variance Autism Autistic Disorder - diagnosis Autistic Disorder - physiopathology Biological and medical sciences Brain Mapping - methods Child Child clinical studies corpus callosum Corpus Callosum - anatomy & histology Corpus Callosum - pathology Corpus Callosum - physiopathology Developmental disorders Humans imaging Imaging, Three-Dimensional - methods Infantile autism Magnetic Resonance Imaging - methods Magnetic Resonance Imaging - statistics & numerical data Male Medical sciences MRI Psychology. Psychoanalysis. Psychiatry Psychopathology. Psychiatry Reference Values three-dimensional (3D) maps white matter Autism white matter corpus callosum MRI imaging three-dimensional (3D) maps Imaging Medical imagery Developmental disorder Nuclear magnetic resonance imaging White matter Corpus callosum
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Abstract	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. Twenty-four boys with autism (aged 10.0 ± 3.3 years) and 26 control boys (aged 11.0 ± 2.5 years) underwent a magnetic resonance imaging (MRI) scan at 3 Tesla. Total and regional areas of the CC were determined using traditional morphometric methods. Three-dimensional (3D) surface models of the CC were also created from the MRI scans. Statistical maps were created to visualize morphologic variability of the CC and to localize regions of callosal thinning in autism. Traditional morphometric methods detected a significant reduction in the total callosal area and in the anterior third of the CC in patients with autism; however, 3D maps revealed significant reductions in both the splenium and genu of the CC in patients. Statistical maps of the CC revealed callosal deficits in autism with greater precision than traditional morphometric methods. These abnormalities suggest aberrant connections between cortical regions, which is consistent with the hypothesis of abnormal cortical connectivity in autism.
AbstractList	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. Twenty-four boys with autism (aged 10.0 +/- 3.3 years) and 26 control boys (aged 11.0 +/- 2.5 years) underwent a magnetic resonance imaging (MRI) scan at 3 Tesla. Total and regional areas of the CC were determined using traditional morphometric methods. Three-dimensional (3D) surface models of the CC were also created from the MRI scans. Statistical maps were created to visualize morphologic variability of the CC and to localize regions of callosal thinning in autism. Traditional morphometric methods detected a significant reduction in the total callosal area and in the anterior third of the CC in patients with autism; however, 3D maps revealed significant reductions in both the splenium and genu of the CC in patients. Statistical maps of the CC revealed callosal deficits in autism with greater precision than traditional morphometric methods. These abnormalities suggest aberrant connections between cortical regions, which is consistent with the hypothesis of abnormal cortical connectivity in autism. 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 autism (aged 10.0 plus or minus 3.3 years) and 26 control boys (aged 11.0 plus or minus 2.5 years) underwent a magnetic resonance imaging (MRI) scan at 3 Tesla. Total and regional areas of the CC were determined using traditional morphometric methods. Three-dimensional (3D) surface models of the CC were also created from the MRI scans. Statistical maps were created to visualize morphologic variability of the CC and to localize regions of callosal thinning in autism. Results Traditional morphometric methods detected a significant reduction in the total callosal area and in the anterior third of the CC in patients with autism; however, 3D maps revealed significant reductions in both the splenium and genu of the CC in patients. Conclusions Statistical maps of the CC revealed callosal deficits in autism with greater precision than traditional morphometric methods. These abnormalities suggest aberrant connections between cortical regions, which is consistent with the hypothesis of abnormal cortical connectivity in autism. 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. Twenty-four boys with autism (aged 10.0 ± 3.3 years) and 26 control boys (aged 11.0 ± 2.5 years) underwent a magnetic resonance imaging (MRI) scan at 3 Tesla. Total and regional areas of the CC were determined using traditional morphometric methods. Three-dimensional (3D) surface models of the CC were also created from the MRI scans. Statistical maps were created to visualize morphologic variability of the CC and to localize regions of callosal thinning in autism. Traditional morphometric methods detected a significant reduction in the total callosal area and in the anterior third of the CC in patients with autism; however, 3D maps revealed significant reductions in both the splenium and genu of the CC in patients. Statistical maps of the CC revealed callosal deficits in autism with greater precision than traditional morphometric methods. These abnormalities suggest aberrant connections between cortical regions, which is consistent with the hypothesis of abnormal cortical connectivity in autism. 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.BACKGROUNDVolumetric 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.Twenty-four boys with autism (aged 10.0 +/- 3.3 years) and 26 control boys (aged 11.0 +/- 2.5 years) underwent a magnetic resonance imaging (MRI) scan at 3 Tesla. Total and regional areas of the CC were determined using traditional morphometric methods. Three-dimensional (3D) surface models of the CC were also created from the MRI scans. Statistical maps were created to visualize morphologic variability of the CC and to localize regions of callosal thinning in autism.METHODSTwenty-four boys with autism (aged 10.0 +/- 3.3 years) and 26 control boys (aged 11.0 +/- 2.5 years) underwent a magnetic resonance imaging (MRI) scan at 3 Tesla. Total and regional areas of the CC were determined using traditional morphometric methods. Three-dimensional (3D) surface models of the CC were also created from the MRI scans. Statistical maps were created to visualize morphologic variability of the CC and to localize regions of callosal thinning in autism.Traditional morphometric methods detected a significant reduction in the total callosal area and in the anterior third of the CC in patients with autism; however, 3D maps revealed significant reductions in both the splenium and genu of the CC in patients.RESULTSTraditional morphometric methods detected a significant reduction in the total callosal area and in the anterior third of the CC in patients with autism; however, 3D maps revealed significant reductions in both the splenium and genu of the CC in patients.Statistical maps of the CC revealed callosal deficits in autism with greater precision than traditional morphometric methods. These abnormalities suggest aberrant connections between cortical regions, which is consistent with the hypothesis of abnormal cortical connectivity in autism.CONCLUSIONSStatistical maps of the CC revealed callosal deficits in autism with greater precision than traditional morphometric methods. These abnormalities suggest aberrant connections between cortical regions, which is consistent with the hypothesis of abnormal cortical connectivity in autism.
Author	Hayashi, Kiralee M. Sui, Yihong Rajakumar, Nagalingam Nicolson, Rob Williamson, Peter C. DeVito, Timothy J. Dutton, Rebecca A. Thompson, Paul M. Vidal, Christine N. Geaga, Jennifer A. Drost, Dick J. Toga, Arthur W.
Author_xml	– sequence: 1 givenname: Christine N. surname: Vidal fullname: Vidal, Christine N. organization: Laboratory of Neuro Imaging, Brain Mapping Division, Department of Neurology, UCLA School of Medicine, Los Angeles, California – sequence: 2 givenname: Rob surname: Nicolson fullname: Nicolson, Rob organization: Department of Psychiatry, University of Western Ontario, London, Ontario, Canada – sequence: 3 givenname: Timothy J. surname: DeVito fullname: DeVito, Timothy J. organization: Laboratory of Neuro Imaging, Brain Mapping Division, Department of Neurology, UCLA School of Medicine, Los Angeles, California – sequence: 4 givenname: Kiralee M. surname: Hayashi fullname: Hayashi, Kiralee M. organization: Laboratory of Neuro Imaging, Brain Mapping Division, Department of Neurology, UCLA School of Medicine, Los Angeles, California – sequence: 5 givenname: Jennifer A. surname: Geaga fullname: Geaga, Jennifer A. organization: Laboratory of Neuro Imaging, Brain Mapping Division, Department of Neurology, UCLA School of Medicine, Los Angeles, California – sequence: 6 givenname: Dick J. surname: Drost fullname: Drost, Dick J. organization: Department of Medical Biophysics, University of Western Ontario, London, Ontario, Canada – sequence: 7 givenname: Peter C. surname: Williamson fullname: Williamson, Peter C. organization: Department of Psychiatry, University of Western Ontario, London, Ontario, Canada – sequence: 8 givenname: Nagalingam surname: Rajakumar fullname: Rajakumar, Nagalingam organization: Department of Psychiatry, University of Western Ontario, London, Ontario, Canada – sequence: 9 givenname: Yihong surname: Sui fullname: Sui, Yihong organization: Laboratory of Neuro Imaging, Brain Mapping Division, Department of Neurology, UCLA School of Medicine, Los Angeles, California – sequence: 10 givenname: Rebecca A. surname: Dutton fullname: Dutton, Rebecca A. organization: Laboratory of Neuro Imaging, Brain Mapping Division, Department of Neurology, UCLA School of Medicine, Los Angeles, California – sequence: 11 givenname: Arthur W. surname: Toga fullname: Toga, Arthur W. organization: Laboratory of Neuro Imaging, Brain Mapping Division, Department of Neurology, UCLA School of Medicine, Los Angeles, California – sequence: 12 givenname: Paul M. surname: Thompson fullname: Thompson, Paul M. email: thompson@loni.ucla.edu organization: Laboratory of Neuro Imaging, Brain Mapping Division, Department of Neurology, UCLA School of Medicine, Los Angeles, California
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Publisher	Elsevier Inc Elsevier Science
Publisher_xml	– name: Elsevier Inc – name: Elsevier Science
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A postmortem morphological study publication-title: Brain doi: 10.1093/brain/112.3.799
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Snippet	Volumetric studies have reported reductions in the size of the corpus callosum (CC) in autism, but the callosal regions contributing to this deficit have... Background Volumetric studies have reported reductions in the size of the corpus callosum (CC) in autism, but the callosal regions contributing to this deficit...
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SubjectTerms	Adolescent Analysis of Variance Autism Autistic Disorder - diagnosis Autistic Disorder - physiopathology Biological and medical sciences Brain Mapping - methods Child Child clinical studies corpus callosum Corpus Callosum - anatomy & histology Corpus Callosum - pathology Corpus Callosum - physiopathology Developmental disorders Humans imaging Imaging, Three-Dimensional - methods Infantile autism Magnetic Resonance Imaging - methods Magnetic Resonance Imaging - statistics & numerical data Male Medical sciences MRI Psychology. Psychoanalysis. Psychiatry Psychopathology. Psychiatry Reference Values three-dimensional (3D) maps white matter
Title	Mapping Corpus Callosum Deficits in Autism: An Index of Aberrant Cortical Connectivity
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