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. 2008 May;119(5):1002-9.
doi: 10.1016/j.clinph.2008.01.013. Epub 2008 Mar 10.

EEG power and coherence in autistic spectrum disorder

Affiliations

EEG power and coherence in autistic spectrum disorder

Robert Coben et al. Clin Neurophysiol. 2008 May.

Abstract

Objective: Autistic spectrum disorder (ASD) has been defined as a neurodevelopmental disorder with associated deficits in executive function, language, emotional, and social function. ASD has been associated with pathophysiology in cerebral organization. The current study investigated quantitative EEG findings in twenty children diagnosed with autistic disorders as compared to 20 controls matched for gender, age and IQ.

Methods: The EEG was recorded during an eyes-closed resting condition and topographical differences in cerebral functioning were examined using estimates of absolute, relative, and total power, as well as intrahemispheric and interhemispheric coherences.

Results: There were group differences in power, intrahemispheric and interhemispheric coherences. Findings included excessive theta, primarily in right posterior regions, in autistics. There was also a pattern of deficient delta over the frontal cortex and excessive midline beta. More significantly, there was a pattern of underconnectivity in autistics compared to controls. This included decreased intrahemispheric delta and theta coherences across short to medium and long inter-electrode distances. Interhemispherically, delta and theta coherences were low across the frontal region. Delta, theta and alpha hypocoherence was also evident over the temporal regions. Lastly, there were low delta, theta and beta coherence measurements across posterior regions.

Conclusions: These results suggest dysfunctional integration of frontal and posterior brain regions in autistics along with a pattern of neural underconnectivity. This is consistent with other EEG, MRI and fMRI research suggesting that neural connectivity anomalies are a major deficit leading to autistic symptomatology.

Significance: This paper reports the largest integrated study of EEG power and coherence during a resting state in children suffering autism spectrum disorder.

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