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      Increased scale-free dynamics in salience network in adult high-functioning autism

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          Abstract

          Autism spectrum disorder (ASD) is clinically characterized by extremely slow and inflexible behavior. The neuronal mechanisms of these symptoms remain unclear though. Using fMRI, we investigate the resting state's temporal structure in the frequency domain (scale-free activity as measured with Power-Law Exponent, PLE, and Spectral Entropy, SE) and temporal variance (neural variability) in high-functioning, adult ASD comparing them with schizophrenic and neurotypical subjects. We show that ASD is characterized by high PLE in salience network, especially in dorsal anterior cingulate. This increase in PLE was 1) specific for salience network; 2) independent of other measures such as neuronal variability/SD and functional connectivity, which did not show any significant difference; 3) detected in two independent samples of ASD but not in the schizophrenia sample. Among salience network subregions, dorsal anterior cingulate cortex exhibited PLE differences between ASD and neurotypicals in both samples, showing high robustness in ROC curves values. Salience network abnormal temporal structure was confirmed by SE, which was strongly anticorrelated with PLE and thus decreased in ASD. Taken together, our findings show abnormal temporal structure (but normal temporal variance) in resting state salience network in adult high-functioning ASD. The abnormally high PLE indicates a relative predominance of slower over faster frequencies, which may underlie the slow adaptation to unexpected changes and the inflexible behavior observed in autistic individuals. The specificity of abnormal PLE in salience network suggests its potential utility as biomarker in ASD.

          Highlights

          • Lower frequencies dominate fMRI power spectrum in high functioning autism at rest.

          • Increased Power-Law Exponent in salience network and dorsal anterior cingulate.

          • Spectral measures in frequency domain reach fair diagnostics levels.

          • Findings are replicated in a second sample in autism but absent in schizophrenia.

          • Specificity is confirmed by negative findings of other measures in the same regions.

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          Most cited references74

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          The temporal structures and functional significance of scale-free brain activity.

          Scale-free dynamics, with a power spectrum following P proportional to f(-beta), are an intrinsic feature of many complex processes in nature. In neural systems, scale-free activity is often neglected in electrophysiological research. Here, we investigate scale-free dynamics in human brain and show that it contains extensive nested frequencies, with the phase of lower frequencies modulating the amplitude of higher frequencies in an upward progression across the frequency spectrum. The functional significance of scale-free brain activity is indicated by task performance modulation and regional variation, with beta being larger in default network and visual cortex and smaller in hippocampus and cerebellum. The precise patterns of nested frequencies in the brain differ from other scale-free dynamics in nature, such as earth seismic waves and stock market fluctuations, suggesting system-specific generative mechanisms. Our findings reveal robust temporal structures and behavioral significance of scale-free brain activity and should motivate future study on its physiological mechanisms and cognitive implications. Copyright 2010 Elsevier Inc. All rights reserved.
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            Long-range temporal correlations and scaling behavior in human brain oscillations.

            The human brain spontaneously generates neural oscillations with a large variability in frequency, amplitude, duration, and recurrence. Little, however, is known about the long-term spatiotemporal structure of the complex patterns of ongoing activity. A central unresolved issue is whether fluctuations in oscillatory activity reflect a memory of the dynamics of the system for more than a few seconds. We investigated the temporal correlations of network oscillations in the normal human brain at time scales ranging from a few seconds to several minutes. Ongoing activity during eyes-open and eyes-closed conditions was recorded with simultaneous magnetoencephalography and electroencephalography. Here we show that amplitude fluctuations of 10 and 20 Hz oscillations are correlated over thousands of oscillation cycles. Our analyses also indicated that these amplitude fluctuations obey power-law scaling behavior. The scaling exponents were highly invariant across subjects. We propose that the large variability, the long-range correlations, and the power-law scaling behavior of spontaneous oscillations find a unifying explanation within the theory of self-organized criticality, which offers a general mechanism for the emergence of correlations and complex dynamics in stochastic multiunit systems. The demonstrated scaling laws pose novel quantitative constraints on computational models of network oscillations. We argue that critical-state dynamics of spontaneous oscillations may lend neural networks capable of quick reorganization during processing demands.
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              Motor coordination in autism spectrum disorders: a synthesis and meta-analysis.

              Are motor coordination deficits an underlying cardinal feature of Autism Spectrum Disorders (ASD)? Database searches identified 83 ASD studies focused on motor coordination, arm movements, gait, or postural stability deficits. Data extraction involved between-group comparisons for ASD and typically developing controls (N = 51). Rigorous meta-analysis techniques including random effects models, forest and funnel plots, I (2), publication bias, fail-safe analysis, and moderator variable analyses determined a significant standardized mean difference effect equal to 1.20 (SE = 0.144; p <0.0001; Z = 10.49). This large effect indicated substantial motor coordination deficits in the ASD groups across a wide range of behaviors. The current overall findings portray motor coordination deficits as pervasive across diagnoses, thus, a cardinal feature of ASD.
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                Author and article information

                Contributors
                Journal
                Neuroimage Clin
                Neuroimage Clin
                NeuroImage : Clinical
                Elsevier
                2213-1582
                10 December 2018
                2019
                10 December 2018
                : 21
                : 101634
                Affiliations
                [a ]Department of Brain and Behavioral Science, University of Pavia, 27100 Pavia, Italy
                [b ]Department of Psychological, Health and Territorial Sciences (DiSPuTer), G. d'Annunzio University of Chieti-Pescara, 66013 Chieti, Italy
                [c ]Biomedical Engineering Group, E.T.S. Ingenieros de Telecomunicación, University of Valladolid, 47011 Valladolid, Spain
                [d ]Mental Health Centre, Zhejiang University School of Medicine, Hangzhou, China
                [e ]Institute of Mental Health Research, University of Ottawa, K1Z 7K4 Ottawa, ON, Canada
                [f ]Brain and Mind Research Institute, University of Ottawa, K1H 8M5 Ottawa, ON, Canada
                [g ]Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
                Author notes
                [* ]Corresponding author at: University of Pavia, Department of Brain and Behavioral Sciences, Via Bassi 21, Pavia (PV), Italy. stefano.damiani01@ 123456ateneopv.it
                Article
                S2213-1582(18)30382-6 101634
                10.1016/j.nicl.2018.101634
                6411906
                30558869
                68360af0-bddc-414f-a967-0aeedcbe76ce
                © 2018 Published by Elsevier Inc.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 1 October 2018
                : 13 November 2018
                : 8 December 2018
                Categories
                Article

                asd,schizophrenia,resting state fmri,salience network,power-law exponent,spectral entropy

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