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      A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study

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          Abstract

          Background

          The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact.

          Methods

          Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls.

          Results

          Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences ( P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences for the ASD-groups, when compared to the controls. Average spectral loading per factor was wide (10.1 Hz).

          Conclusions

          Classification success suggests a stable coherence loading pattern that differentiates ASD- from C-group subjects. This might constitute an EEG coherence-based phenotype of childhood autism. The predominantly reduced short-distance coherences may indicate poor local network function. The increased long-distance coherences may represent compensatory processes or reduced neural pruning. The wide average spectral range of factor loadings may suggest over-damped neural networks.

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          Most cited references49

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          Cortical activation and synchronization during sentence comprehension in high-functioning autism: evidence of underconnectivity.

          The brain activation of a group of high-functioning autistic participants was measured using functional MRI during sentence comprehension and the results compared with those of a Verbal IQ-matched control group. The groups differed in the distribution of activation in two of the key language areas. The autism group produced reliably more activation than the control group in Wernicke's (left laterosuperior temporal) area and reliably less activation than the control group in Broca's (left inferior frontal gyrus) area. Furthermore, the functional connectivity, i.e. the degree of synchronization or correlation of the time series of the activation, between the various participating cortical areas was consistently lower for the autistic than the control participants. These findings suggest that the neural basis of disordered language in autism entails a lower degree of information integration and synchronization across the large-scale cortical network for language processing. The article presents a theoretical account of the findings, related to neurobiological foundations of underconnectivity in autism.
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            Autism and abnormal development of brain connectivity.

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              Why the frontal cortex in autism might be talking only to itself: local over-connectivity but long-distance disconnection.

              Although it has long been thought that frontal lobe abnormality must play an important part in generating the severe impairment in higher-order social, emotional and cognitive functions in autism, only recently have studies identified developmentally early frontal lobe defects. At the microscopic level, neuroinflammatory reactions involving glial activation, migration defects and excess cerebral neurogenesis and/or defective apoptosis might generate frontal neural pathology early in development. It is hypothesized that these abnormal processes cause malformation and thus malfunction of frontal minicolumn microcircuitry. It is suggested that connectivity within frontal lobe is excessive, disorganized and inadequately selective, whereas connectivity between frontal cortex and other systems is poorly synchronized, weakly responsive and information impoverished. Increased local but reduced long-distance cortical-cortical reciprocal activity and coupling would impair the fundamental frontal function of integrating information from widespread and diverse systems and providing complex context-rich feedback, guidance and control to lower-level systems.
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                Author and article information

                Journal
                BMC Med
                BMC Med
                BMC Medicine
                BioMed Central
                1741-7015
                2012
                26 June 2012
                : 10
                : 64
                Affiliations
                [1 ]Department of Neurology, Children's Hospital Boston and Harvard Medical School, 300 Longwood Ave., Boston, MA 02115, USA
                [2 ]Department of Psychiatry(Psychology), Children's Hospital Boston and Harvard Medical School, 320 Longwood Ave., Boston, MA 02115, USA
                Article
                1741-7015-10-64
                10.1186/1741-7015-10-64
                3391175
                22730909
                29005e4f-a79a-4e42-96a8-9238d5e56e18
                Copyright ©2012 Duffy and Als; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 1 December 2011
                : 26 June 2012
                Categories
                Research Article

                Medicine
                autism spectrum disorder,coherence factors,eeg coherence,principal components analysis,pervasive developmental disorder,discriminant analysis,pca,pdd

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