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      Greater Social Competence Is Associated With Higher Interpersonal Neural Synchrony in Adolescents With Autism

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          Abstract

          Difficulty engaging in reciprocal social interactions is a core characteristic of autism spectrum disorder. The mechanisms supporting effective dynamic real-time social exchanges are not yet well understood. This proof-of-concept hyperscanning electroencephalography study examined neural synchrony as the mechanism supporting interpersonal social interaction in 34 adolescents with autism spectrum disorder (50% female), age 10–16 years, paired with neurotypical confederates of similar age. The degree of brain-to-brain neural synchrony was quantified at temporo-parietal scalp locations as the circular correlation of oscillatory amplitudes in theta, alpha, and beta frequency bands while the participants engaged in a friendly conversation. In line with the hypotheses, interpersonal neural synchrony was significantly greater during the social interaction compared to the baseline. Lower levels of synchrony were associated with increased behavioral symptoms of social difficulties. With regard to sex differences, we found evidence for stronger interpersonal neural synchrony during conversation than baseline in females with autism, but not in male participants, for whom such condition differences did not reach statistical significance. This study established the feasibility of hyperscanning during real-time social interactions as an informative approach to examine social competence in autism, demonstrated that neural coordination of activity between the interacting brains may contribute to social behavior, and offered new insights into sex-related variability in social functioning in individuals with autism spectrum disorders.

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          Most cited references63

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          Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years — Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2016

          Problem/Condition Autism spectrum disorder (ASD). Period Covered 2016. Description of System The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance program that provides estimates of the prevalence of ASD among children aged 8 years whose parents or guardians live in 11 ADDM Network sites in the United States (Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin). Surveillance is conducted in two phases. The first phase involves review and abstraction of comprehensive evaluations that were completed by medical and educational service providers in the community. In the second phase, experienced clinicians who systematically review all abstracted information determine ASD case status. The case definition is based on ASD criteria described in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Results For 2016, across all 11 sites, ASD prevalence was 18.5 per 1,000 (one in 54) children aged 8 years, and ASD was 4.3 times as prevalent among boys as among girls. ASD prevalence varied by site, ranging from 13.1 (Colorado) to 31.4 (New Jersey). Prevalence estimates were approximately identical for non-Hispanic white (white), non-Hispanic black (black), and Asian/Pacific Islander children (18.5, 18.3, and 17.9, respectively) but lower for Hispanic children (15.4). Among children with ASD for whom data on intellectual or cognitive functioning were available, 33% were classified as having intellectual disability (intelligence quotient [IQ] ≤70); this percentage was higher among girls than boys (40% versus 32%) and among black and Hispanic than white children (47%, 36%, and 27%, respectively). Black children with ASD were less likely to have a first evaluation by age 36 months than were white children with ASD (40% versus 45%). The overall median age at earliest known ASD diagnosis (51 months) was similar by sex and racial and ethnic groups; however, black children with IQ ≤70 had a later median age at ASD diagnosis than white children with IQ ≤70 (48 months versus 42 months). Interpretation The prevalence of ASD varied considerably across sites and was higher than previous estimates since 2014. Although no overall difference in ASD prevalence between black and white children aged 8 years was observed, the disparities for black children persisted in early evaluation and diagnosis of ASD. Hispanic children also continue to be identified as having ASD less frequently than white or black children. Public Health Action These findings highlight the variability in the evaluation and detection of ASD across communities and between sociodemographic groups. Continued efforts are needed for early and equitable identification of ASD and timely enrollment in services.
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            What Is the Male-to-Female Ratio in Autism Spectrum Disorder? A Systematic Review and Meta-Analysis

            To derive the first systematically calculated estimate of the relative proportion of boys and girls with autism spectrum disorder (ASD) through a meta-analysis of prevalence studies conducted since the introduction of the DSM-IV and the International Classification of Diseases, Tenth Revision.
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              Nonparametric estimation of Shannon’s index of diversity when there are unseen species in sample

              Journal of Autism and Developmental Disorders, 30(3), 205-223
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                Author and article information

                Contributors
                Journal
                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                1662-5161
                06 January 2022
                2021
                : 15
                : 790085
                Affiliations
                [1] 1Vanderbilt Kennedy Center, Vanderbilt University Medical Center , Nashville, TN, United States
                [2] 2Department of Hearing and Speech Sciences, Vanderbilt University Medical Center , Nashville, TN, United States
                [3] 3Vanderbilt University , Nashville, TN, United States
                [4] 4Institute for Software Integrated Systems, Vanderbilt University , Nashville, TN, United States
                [5] 5Department of Electrical and Computer Engineering, Vanderbilt University , Nashville, TN, United States
                [6] 6Department of Biostatistics, Vanderbilt University Medical Center , Nashville, TN, United States
                [7] 7Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center , Nashville, TN, United States
                Author notes

                Edited by: Cosimo Urgesi, University of Udine, Italy

                Reviewed by: Marc Woodbury-Smith, Newcastle University, United Kingdom; Lucia Maria Sacheli, University of Milano-Bicocca, Italy

                *Correspondence: Alexandra P. Key sasha.key@ 123456vumc.org

                Specialty section: This article was submitted to Cognitive Neuroscience, a section of the journal Frontiers in Human Neuroscience

                Article
                10.3389/fnhum.2021.790085
                8770262
                35069156
                3ca95bb3-9ea1-4bd2-92d5-209257aea476
                Copyright © 2022 Key, Yan, Metelko, Chang, Kang, Pilkington and Corbett.

                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(s) 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 October 2021
                : 16 December 2021
                Page count
                Figures: 2, Tables: 4, Equations: 0, References: 63, Pages: 9, Words: 7126
                Funding
                Funded by: Eunice Kennedy Shriver National Institute of Child Health and Human Development, doi 10.13039/100009633;
                Award ID: U54HD083211
                Funded by: National Institute of Mental Health, doi 10.13039/100000025;
                Award ID: R01MH114906
                Categories
                Human Neuroscience
                Original Research

                Neurosciences
                autism,hyperscanning,eeg,social,synchrony,sex differences
                Neurosciences
                autism, hyperscanning, eeg, social, synchrony, sex differences

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