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

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.

doi:10.1016/j.biopsych.2005.11.011

Cited by 226 publications

(168 citation statements)

References 37 publications

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“…Image processing, callosal thickness, and callosal area measurements were performed as detailed previously (Luders et al, 2006a, b;Narr et al, 2000Narr et al, , 2002Vidal et al, 2006). Each brain volume was corrected for radiofrequency field inhomogeneities (Sled and Pike, 1998) and placed into the standard coordinate system of the ICBM-305 average brain volume using a three-translation and three-rotation rigid-body transformation (Woods et al, 1998).…”

Section: Image Preprocessingmentioning

confidence: 99%

“…Areas measures were computed in mm 2 for each callosal segment, as described previously (Narr et al, 2002;Vidal et al, 2006).…”

Section: Callosal Thickness and Area Measurementsmentioning

confidence: 99%

“…Indeed, this method arbitrarily divides the midsagittal corpus callosum into several regions according to maximal length and thus could be biased by local variability in callosal shape. To circumvent the risk of defining the callosal sections with implicit assumptions regarding sectors with consistent fiber distribution and to increase spatial resolution of callosal measurements, we characterized callosal abnormalities by applying anatomical mesh-based geometrical modeling methods, which compute 100 pointwise indicators of callosal thickness across the whole corpus callosum at midline (Luders et al, 2006a, b;Narr et al, 2000Narr et al, , 2002Vidal et al, 2006). Importantly, these mapping methods detect and visualize the spatial patterns of callosal abnormalities using color-coded statistical maps, revealing any highly localized group differences in callosal thickness.…”

Section: Introductionmentioning

confidence: 99%

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Mapping Callosal Morphology in Early- and Late-Onset Elderly Depression: An Index of Distinct Changes in Cortical Connectivity

Ballmaier

Kumar

Elderkin‐Thompson

et al. 2007

Neuropsychopharmacol

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There is some evidence of corpus callosum abnormalities in elderly depression, but it is not known whether these deficits are regionspecific or differ based on age at onset of depression. Twenty-four patients with early-onset depression (mean age ¼ 68.00, SD75.83), 22 patients with late-onset depression (mean age ¼ 74.50, SD78.09) and 34 elderly control subjects (mean age ¼ 72.38; SD76.93) were studied. Using 3D MRI data, novel mesh-based geometrical modeling methods were applied to compare the midsagittal thickness of the corpus callosum at high spatial resolution between groups. Neuropsychological correlates of midsagittal callosal area differences were additionally investigated in a subsample of subjects. Depressed patients exhibited significant callosal thinning in the genu and splenium compared to controls. Significant callosal thinning was restricted to the genu in early-onset patients, but patients with late-onset depression exhibited significant callosal thinning in both the genu and splenium relative to controls. The splenium of the corpus callosum was also significantly thinner in subjects with late-vs early-onset depression. Genu and splenium midsagittal areas significantly correlated with memory and attention functioning among late-onset depressed patients, but not early-onset depressed patients or controls. Circumscribed structural alterations in callosal morphology may distinguish late-from early-onset depression in the elderly. These findings suggest distinct abnormalities of cortical connectivity in late-and early-onset elderly depression with possible influence on the course of illness. Patients with a late onset of depression may be at higher risk of illness progression and eventually dementia conversion than earlyonset depression, with potentially important implications for research and therapy.

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Section: Image Preprocessingmentioning

confidence: 99%

“…Areas measures were computed in mm 2 for each callosal segment, as described previously (Narr et al, 2002;Vidal et al, 2006).…”

Section: Callosal Thickness and Area Measurementsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mapping Callosal Morphology in Early- and Late-Onset Elderly Depression: An Index of Distinct Changes in Cortical Connectivity

Ballmaier

Kumar

Elderkin‐Thompson

et al. 2007

Neuropsychopharmacol

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“…[4][5][6] Neuroimaging studies of ASD shed some light on the neural substrate of ASD. Abnormalities are described in the following neural systems: [10][11][12] (1) the cerebellum -loss of Purkinje cells and anomalies in the shape of the cerebellum and vermix; 13,14 (2) the cerebral cortex -hyperplasia of grey and white matter of the frontal, temporal, and parietal lobes, 15 and abnormalities in the corpus callosum and ventricular systems; 16,17 (3) the basal ganglia -increased volume of caudate nucleus and putamen; 18 (4) the hippocampus -reduction in size and atrophy; 19 and (5) the thalamus -increased volume. 20 These findings are inconsistent, which may in part be attributable to the heterogeneity of the disturbance itself and in part to incompatible reference groups and technical limitations.…”

mentioning

confidence: 99%

Minor neurological dysfunction in children with autism spectrum disorder

Jong¹,

Punt²,

Groot

et al. 2011

Developmental Medicine &Amp; Child Neurology

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AIM The aim of this study was to improve the understanding of brain function in children with autism spectrum disorder (ASD) in relation to minor neurological dysfunctions (MNDs).METHOD We studied MNDs in 122 children (93 males, 29 females; mean age 8y 1mo, SD 2y 6mo) who, among a total cohort of 705 children (513 males, 192 females; mean age 9y, SD 2y 0.5mo) referred to a regional outpatient non-academic psychiatric centre in the Netherlands, were diagnosed with ASD after an extensive multidisciplinary psychiatric assessment. Children with clear neurological abnormalities (e.g. cerebral palsy or spina bifida) were excluded from the study. MNDs were assessed in all 705 children using the Touwen examination method. Special attention was paid to the severity and type of MND. Data of the children with ASD were compared with neurological morbidity data of children with other psychiatric disorders and with children in the general population, who were born at Groningen University Hospital between 1975 and 1978. RESULTS Seventy-four percent of the children with ASD showed complex MNDs compared with 52% of the children with other psychiatric disorders and 6% of the reference group (v 2 =18.0, p<0.001; v 2 =937.5, p<0.001 respectively). Specific dysfunctions frequently encountered in ASD were dysfunctional posture and muscle tone, fine manipulative disability, dyscoordination, and excessive associated movements.CONCLUSION These findings suggest a contribution of dysfunctional supraspinal networks involving multiple parts of the brain in the pathogenesis of ASD. This is consistent with findings from neuroimaging studies, and highlights the importance of neurological examinations in paediatric psychiatric assessments.Autism spectrum disorder (ASD) is an early childhood-onset neurodevelopmental disorder characterized by delay and deviations in the development of social, communicative, and cognitive skills, and is associated with a very wide range of syndrome expression. The term 'ASD' encompasses children with the full autism syndrome as well as variants, such as Asperger syndrome, and pervasive developmental disorders not otherwise specified.Children with ASD are often described as 'clumsy' 1-3 or as having motor deficits. [4][5][6] In addition, psychiatric classification systems cite stereotypes in motor behaviour (e.g. hand-flicking or -twisting) as criteria for classifying ASD. 7,8 However, little is known about the neurological background of the clumsiness. Some studies report that children with ASD frequently exhibit soft neurological signs, 9 but only rarely are details of these signs reported. Others report motor deficits but do not refer to the neurological background of these deficits. [4][5][6] Neuroimaging studies of ASD shed some light on the neural substrate of ASD. Abnormalities are described in the following neural systems: [10][11][12] (1) the cerebellum -loss of Purkinje cells and anomalies in the shape of the cerebellum and vermix; 13,14 (2) the cerebral cortex -hyperplasia of grey and white matter of ...

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“…Studies investigating CC anomalies in autism have employed structural MRI to find reductions in area on the midsagittal plane as well as in volumetric measures. Results include overall decreases in midsagittal area (Boger-Megiddo et al, 2006;Manes et al, 1999;Vidal et al, 2006), and subregional decreases in in the anterior (Hardan, Minshew, & Keshavan, 2000;Just, Cherkassky, Keller, Kana, & Minshew, 2006;Vidal et al, 2006), middle Piven, Bailey, Ranson, & Arndt, 1997), and posterior (Just et al, 2006;Saitoh, Courchesne, Egaas, Lincoln, & Schreibman, 1995;Waiter et al, 2005) portions of the CC. The majority of nonstatistically significant results from these studies also showed a trend towards a decrease in area in all subregions.…”

Section: Corpus Callosummentioning

confidence: 99%

A Review on the Cognitive Neuroscience of Autism

Koyama

2009

Act Nerv Super

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With increased recognition in the media, heightened prevalence, and advances in research technologies, investigation into the causes of autism has broadened in recent years. Studies at the molecular, structural, and behavioral levels have resulted in significant findings, linking autism to qualitative differences in neurological function and an alteration of early development. Familial aggregation of autism demonstrates a strong genetic factor, although genetics can not completely account for its pathogenesis. Studies show autism having one of the most complex pathologies among neurodevelopmental disorders. Future studies applying sophisticated methodologies in new areas may shed light on current mysteries surrounding the disorder.

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

Cited by 226 publications

References 37 publications

Mapping Callosal Morphology in Early- and Late-Onset Elderly Depression: An Index of Distinct Changes in Cortical Connectivity

Mapping Callosal Morphology in Early- and Late-Onset Elderly Depression: An Index of Distinct Changes in Cortical Connectivity

Minor neurological dysfunction in children with autism spectrum disorder

A Review on the Cognitive Neuroscience of Autism

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