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      Resting state EEG abnormalities in autism spectrum disorders

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          Abstract

          Autism spectrum disorders (ASD) are a group of complex and heterogeneous developmental disorders involving multiple neural system dysfunctions. In an effort to understand neurophysiological substrates, identify etiopathophysiologically distinct subgroups of patients, and track outcomes of novel treatments with translational biomarkers, EEG (electroencephalography) studies offer a promising research strategy in ASD. Resting-state EEG studies of ASD suggest a U-shaped profile of electrophysiological power alterations, with excessive power in low-frequency and high-frequency bands, abnormal functional connectivity, and enhanced power in the left hemisphere of the brain. In this review, we provide a summary of recent findings, discuss limitations in available research that may contribute to inconsistencies in the literature, and offer suggestions for future research in this area for advancing the understanding of ASD.

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          Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging.

          Michael Fox, Marcus E. Raichle (2007)
          The majority of functional neuroscience studies have focused on the brain's response to a task or stimulus. However, the brain is very active even in the absence of explicit input or output. In this Article we review recent studies examining spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal of functional magnetic resonance imaging as a potentially important and revealing manifestation of spontaneous neuronal activity. Although several challenges remain, these studies have provided insight into the intrinsic functional architecture of the brain, variability in behaviour and potential physiological correlates of neurological and psychiatric disease.
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            Advances in autism genetics: on the threshold of a new neurobiology.

            Brett Abrahams, Daniel Geschwind (2008)
            Autism is a heterogeneous syndrome defined by impairments in three core domains: social interaction, language and range of interests. Recent work has led to the identification of several autism susceptibility genes and an increased appreciation of the contribution of de novo and inherited copy number variation. Promising strategies are also being applied to identify common genetic risk variants. Systems biology approaches, including array-based expression profiling, are poised to provide additional insights into this group of disorders, in which heterogeneity, both genetic and phenotypic, is emerging as a dominant theme.
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              Measuring phase synchrony in brain signals

              Francisco J. Varela, Eugenio Rodriguez, Jean-Philippe Lachaux … (1999)
              This article presents, for the first time, a practical method for the direct quantification of frequency‐specific synchronization (i.e., transient phase‐locking) between two neuroelectric signals. The motivation for its development is to be able to examine the role of neural synchronies as a putative mechanism for long‐range neural integration during cognitive tasks. The method, called phase‐locking statistics (PLS), measures the significance of the phase covariance between two signals with a reasonable time‐resolution (<100 ms). Unlike the more traditional method of spectral coherence, PLS separates the phase and amplitude components and can be directly interpreted in the framework of neural integration. To validate synchrony values against background fluctuations, PLS uses surrogate data and thus makes no a priori assumptions on the nature of the experimental data. We also apply PLS to investigate intracortical recordings from an epileptic patient performing a visual discrimination task. We find large‐scale synchronies in the gamma band (45 Hz), e.g., between hippocampus and frontal gyrus, and local synchronies, within a limbic region, a few cm apart. We argue that whereas long‐scale effects do reflect cognitive processing, short‐scale synchronies are likely to be due to volume conduction. We discuss ways to separate such conduction effects from true signal synchrony. Hum Brain Mapping 8:194–208, 1999. © 1999 Wiley‐Liss, Inc.
              Article 0 comments Cited 469 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): J Neurodev Disord
                Journal ID (iso-abbrev): J Neurodev Disord
                Title: Journal of Neurodevelopmental Disorders
                Publisher: BioMed Central
                ISSN (Print): 1866-1947
                ISSN (Electronic): 1866-1955
                Publication date (Print): 2013
                Publication date (Electronic): 16 September 2013
                Volume: 5
                Issue: 1
                Page: 24
                Affiliations
                [1 ]Department of Psychiatry, University of Texas Southwestern, Dallas, TX, USA
                [2 ]Department of Pediatrics, University of Texas Southwestern, Dallas, TX, USA
                [3 ]Center for Autism Spectrum Disorders, Bond University, Gold Coast, Australia
                Article
                Publisher ID: 1866-1955-5-24
                DOI: 10.1186/1866-1955-5-24
                PMC ID: 3847481
                PubMed ID: 24040879
                SO-VID: 2150eb21-48c2-4cbe-96e4-53b8a6495637
                Copyright © Copyright © 2013 Wang et al.; licensee BioMed Central Ltd.
                License:

                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
                Date received : 13 May 2013
                Date accepted : 4 September 2013
                Categories
                Subject: Review

                ScienceOpen disciplines: Neurosciences
                Keywords: resting-state,eeg,autism,electroencephalography
                Data availability:
                ScienceOpen disciplines: Neurosciences
                Keywords: resting-state, eeg, autism, electroencephalography

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