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      Shifting brain inhibitory balance and connectivity of the prefrontal cortex of adults with autism spectrum disorder

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          Abstract

          Currently, there are no effective pharmacologic treatments for the core symptoms of autism spectrum disorder (ASD). There is, nevertheless, potential for progress. For example, recent evidence suggests that the excitatory (E) glutamate and inhibitory (I) GABA systems may be altered in ASD. However, no prior studies of ASD have examined the ‘responsivity’ of the E–I system to pharmacologic challenge; or whether E–I modulation alters abnormalities in functional connectivity of brain regions implicated in the disorder. Therefore, we used magnetic resonance spectroscopy ([1H]MRS) to measure prefrontal E–I flux in response to the glutamate and GABA acting drug riluzole in adult men with and without ASD. We compared the change in prefrontal ‘Inhibitory Index’—the GABA fraction within the pool of glutamate plus GABA metabolites—post riluzole challenge; and the impact of riluzole on differences in resting-state functional connectivity. Despite no baseline differences in E–I balance, there was a significant group difference in response to pharmacologic challenge. Riluzole increased the prefrontal cortex inhibitory index in ASD but decreased it in controls. There was also a significant group difference in prefrontal functional connectivity at baseline, which was abolished by riluzole within the ASD group. Our results also show, for we believe the first time in ASD, that E–I flux can be ‘shifted’ with a pharmacologic challenge, but that responsivity is significantly different from controls. Further, our initial evidence suggests that abnormalities in functional connectivity can be ‘normalised’ by targeting E–I, even in adults.

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          Mutations of the X-linked genes encoding neuroligins NLGN3 and NLGN4 are associated with autism.

          Many studies have supported a genetic etiology for autism. Here we report mutations in two X-linked genes encoding neuroligins NLGN3 and NLGN4 in siblings with autism-spectrum disorders. These mutations affect cell-adhesion molecules localized at the synapse and suggest that a defect of synaptogenesis may predispose to autism.
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            Autism spectrum disorders: developmental disconnection syndromes.

            Autism is a common and heterogeneous childhood neurodevelopmental disorder. Analogous to broad syndromes such as mental retardation, autism has many etiologies and should be considered not as a single disorder but, rather, as 'the autisms'. However, recent genetic findings, coupled with emerging anatomical and functional imaging studies, suggest a potential unifying model in which higher-order association areas of the brain that normally connect to the frontal lobe are partially disconnected during development. This concept of developmental disconnection can accommodate the specific neurobehavioral features that are observed in autism, their emergence during development, and the heterogeneity of autism etiology, behaviors and cognition.
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              Estimating sample size in functional MRI (fMRI) neuroimaging studies: statistical power analyses.

              Estimation of statistical power in functional MRI (fMRI) requires knowledge of the expected percent signal change between two conditions as well as estimates of the variability in percent signal change. Variability can be divided into intra-subject variability, reflecting noise within the time series, and inter-subject variability, reflecting subject-to-subject differences in activation. The purpose of this study was to obtain estimates of percent signal change and the two sources of variability from fMRI data, and then use these parameter estimates in simulation experiments in order to generate power curves. Of interest from these simulations were conclusions concerning how many subjects are needed and how many time points within a scan are optimal in an fMRI study of cognitive function. Intra-subject variability was estimated from resting conditions, and inter-subject variability and percent signal change were estimated from verbal working memory data. Simulations derived from these parameters illustrate how percent signal change, intra- and inter-subject variability, and number of time points affect power. An empirical test experiment, using fMRI data acquired during somatosensory stimulation, showed good correspondence between the simulation-based power predictions and the power observed within somatosensory regions of interest. Our analyses suggested that for a liberal threshold of 0.05, about 12 subjects were required to achieve 80% power at the single voxel level for typical activations. At more realistic thresholds, that approach those used after correcting for multiple comparisons, the number of subjects doubled to maintain this level of power. Copyright 2002 Elsevier Science B.V.
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                Author and article information

                Journal
                Transl Psychiatry
                Transl Psychiatry
                Translational Psychiatry
                Nature Publishing Group
                2158-3188
                May 2017
                23 May 2017
                1 May 2017
                : 7
                : 5
                : e1137
                Affiliations
                [1 ]Department of Forensic and Neurodevelopmental Sciences, The Sackler Centre for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King’s College London , London, UK
                [2 ]Behavioural and Developmental Psychiatry Clinical Academic Group, South London and Maudsley NHS Trust , London, UK
                [3 ]Pharmacy Department, South London and Maudsley NHS Foundation Trust , London, UK
                [4 ]Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London , London, UK
                [5 ]Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore , MD, USA
                Author notes
                [* ]Department of Forensic and Neurodevelopmental Sciences, The Sackler Centre for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King’s College London , 16 De Crespigny Park, London SE5 8AF, UK. E-mail: grainne.mcalonan@ 123456kcl.ac.uk
                [6]

                These authors contributed equally to this work.

                [7]

                These authors contributed equally to this work.

                Article
                tp2017104
                10.1038/tp.2017.104
                5534939
                28534874
                1c9c9283-de2d-42fc-90fc-b7b47eeff7dc
                Copyright © 2017 The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 05 April 2017
                : 10 April 2017
                Categories
                Original Article

                Clinical Psychology & Psychiatry
                Clinical Psychology & Psychiatry

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