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      Thalamocortical Hyperconnectivity and Amygdala-Cortical Hypoconnectivity in Male Patients With Autism Spectrum Disorder

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          Abstract

          Background: Analyses of resting-state functional magnetic resonance imaging (rs-fMRI) have been performed to investigate pathophysiological changes in the brains of patients with autism spectrum disorder (ASD) relative to typically developing controls (CTLs). However, the results of these previous studies, which have reported mixed patterns of hypo- and hyperconnectivity, are controversial, likely due to the small sample sizes and limited age range of included participants.

          Methods: To overcome this issue, we analyzed multisite neuroimaging data from a large sample (n = 626) of male participants aged between 5 and 29 years (mean age = 13 years). The rs-fMRI data were preprocessed using SPM12 and DPARSF software, and signal changes in 90 brain regions were extracted. Multiple linear regression was used to exclude the effect of site differences in connectivity data. Subcortical–cortical connectivity was computed using connectivities in the hippocampus, amygdala, caudate nucleus, putamen, pallidum, and thalamus. Eighty-eight connectivities in each structure were compared between patients with ASD and CTLs using multiple linear regression with group, age, and age × group interactions, head movement parameters, and overall connectivity as variables.

          Results: After correcting for multiple comparisons, patients in the ASD group exhibited significant increases in connectivity between the thalamus and 19 cortical regions distributed throughout the fronto-parietal lobes, including the temporo-parietal junction and posterior cingulate cortices. In addition, there were significant decreases in connectivity between the amygdala and six cortical regions. The mean effect size of hyperconnectivity (0.25) was greater than that for hypoconnectivity (0.08). No other subcortical structures showed significant group differences. A group-by-age interaction was observed for connectivity between the thalamus and motor-somatosensory areas.

          Conclusions: These results demonstrate that pathophysiological changes associated with ASD are more likely related to thalamocortical hyperconnectivity than to amygdala-cortical hypoconnectivity. Future studies should examine full sets of clinical and behavioral symptoms in combination with functional connectivity to explore possible biomarkers for ASD.

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          Most cited references32

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          Sensory processing in autism: a review of neurophysiologic findings.

          Atypical sensory-based behaviors are a ubiquitous feature of autism spectrum disorders (ASDs). In this article, we review the neural underpinnings of sensory processing in autism by reviewing the literature on neurophysiological responses to auditory, tactile, and visual stimuli in autistic individuals. We review studies of unimodal sensory processing and multisensory integration that use a variety of neuroimaging techniques, including electroencephalography (EEG), magnetoencephalography (MEG), and functional MRI. We then explore the impact of covert and overt attention on sensory processing. With additional characterization, neurophysiologic profiles of sensory processing in ASD may serve as valuable biomarkers for diagnosis and monitoring of therapeutic interventions for autism and reveal potential strategies and target brain regions for therapeutic interventions.
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            The dual systems model: Review, reappraisal, and reaffirmation

            Highlights • Evidence related to the dual systems model of adolescent risk taking is reviewed. • The review encompasses both the psychological and neuroimaging literatures. • Recent findings (since 2008) generally support the dual systems model. • Recommendations are made for future research directions.
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              Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example

              Resting-state functional Magnetic Resonance Imaging (R-fMRI) holds the promise to reveal functional biomarkers of neuropsychiatric disorders. However, extracting such biomarkers is challenging for complex multi-faceted neuropathologies, such as autism spectrum disorders. Large multi-site datasets increase sample sizes to compensate for this complexity, at the cost of uncontrolled heterogeneity. This heterogeneity raises new challenges, akin to those face in realistic diagnostic applications. Here, we demonstrate the feasibility of inter-site classification of neuropsychiatric status, with an application to the Autism Brain Imaging Data Exchange (ABIDE) database, a large (N=871) multi-site autism dataset. For this purpose, we investigate pipelines that extract the most predictive biomarkers from the data. These R-fMRI pipelines build participant-specific connectomes from functionally-defined brain areas. Connectomes are then compared across participants to learn patterns of connectivity that differentiate typical controls from individuals with autism. We predict this neuropsychiatric status for participants from the same acquisition sites or different, unseen, ones. Good choices of methods for the various steps of the pipeline lead to 67% prediction accuracy on the full ABIDE data, which is significantly better than previously reported results. We perform extensive validation on multiple subsets of the data defined by different inclusion criteria. These enables detailed analysis of the factors contributing to successful connectome-based prediction. First, prediction accuracy improves as we include more subjects, up to the maximum amount of subjects available. Second, the definition of functional brain areas is of paramount importance for biomarker discovery: brain areas extracted from large R-fMRI datasets outperform reference atlases in the classification tasks.
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                Author and article information

                Contributors
                Journal
                Front Psychiatry
                Front Psychiatry
                Front. Psychiatry
                Frontiers in Psychiatry
                Frontiers Media S.A.
                1664-0640
                16 April 2019
                2019
                : 10
                : 252
                Affiliations
                [1] 1Brain & Mind Research Center, Nagoya University , Nagoya, Japan
                [2] 2Department of Physical and Occupational Therapy, Graduate School of Medicine, Nagoya University , Nagoya, Japan
                [3] 3Department of Education, Psychology, and Human Studies, Aoyama Gakuin University , Tokyo, Japan
                Author notes

                Edited by: Lin Shi, The Chinese University of Hong Kong, China

                Reviewed by: Baxter P. Rogers, Vanderbilt University, United States; Meiling Li, Harvard Medical School, United States

                *Correspondence: Tetsuya Iidaka, iidaka@ 123456met.nagoya-u.ac.jp

                This article was submitted to Neuroimaging and Stimulation, a section of the journal Frontiers in Psychiatry

                Article
                10.3389/fpsyt.2019.00252
                6482335
                31057443
                71ad0b4d-c6e8-4b22-b147-28135c6e1214
                Copyright © 2019 Iidaka, Kogata, Mano and Komeda

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 06 December 2018
                : 02 April 2019
                Page count
                Figures: 3, Tables: 3, Equations: 0, References: 53, Pages: 11, Words: 6157
                Funding
                Funded by: Japan Society for the Promotion of Science 10.13039/501100001691
                Categories
                Psychiatry
                Original Research

                Clinical Psychology & Psychiatry
                resting,functional magnetic resonance imaging,age,development,network,amygdala

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