The connectivity can be measured using fMRI, SPECT, EEG or magnetoencephalography (MEG) ( 9).
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In contrast, functional connectivity is based on statistical dependencies between time series of cerebral activity in different brain regions. Structural connectivity describes the architecture of interregional connections, but it provides less information related to how neurophysiological functions are supported by this architecture. In this context, anatomical relations through bundles of axons are designated as structural connectivity, which can be measured using structural brain imaging such as MRI and diffusion tensor imaging (DTI). They interact with other elements in a coordinated manner through their afferent and efferent connections ( 8). In the human brain, neurons and neural populations do not function individually. Brain connectivity is a multi-faceted concept. Assessing relations between brain regions (i.e., brain connectivity) and functions in each region can be an effective approach to extracting differences between individuals with ASD and typically developing (TD) individuals. However, results of more recent studies have suggested that ASD is a dysfunction of coordination over widely distributed brain regions ( 5– 7). In the field of brain imaging, researchers have characterized the functions of individual brain regions affected by ASD.
Consequently, clinicians must rely on symptoms. Its early diagnosis is nevertheless difficult in many cases because no biological marker has been established ( 4, 5). However, impaired social cognition and communication can be improved by early and appropriate interventions ( 2, 3).
The etiology of autism spectrum disorder (ASD), a neurodevelopmental disorder characterized by stereotypic or repetitive behaviors with impaired social cognition and communication disorders ( 1), remains largely unknown. Combining graph theory and MEG might be a promising approach to establish a biological marker for ASD. Results obtained using graph theory demonstrate a difference between children with and without ASD in MEG-derived resting-state functional brain networks, and the relation of that difference with social impairment. Significant relations were also inferred for the Social Awareness ( p = 0.008) and Social Cognition ( p = 0.015) sub-scales. Lower small-worldness in the beta band of children with ASD was associated with higher Social Responsiveness Scale total t-scores ( p = 0.047). Children with ASD were found to have significantly lower small-worldness in the beta band ( p = 0.007) than TD children had. We measured autism symptoms severity using the Social Responsiveness Scale and investigated its relation with altered small-worldness using linear regression models. After brain networks were constructed and after matching with intelligence using a coarsened exact matching algorithm, ASD and TD graph theoretical measures were compared. After signal sources were localized onto the Desikan–Killiany brain atlas, statistical relations between localized activities were found and evaluated in terms of the phase lag index. Magnetoencephalographic (MEG) data were recorded for 21 children with ASD (7 girls, 60–89 months old) and for 25 typically developing (TD) control children (10 girls, 60–91 months old) in a resting state while gazing at a fixation cross. Objectives of this study were to evaluate properties of resting-state functional brain networks in children with and without ASD and to evaluate their relation with social impairment severity. Measuring whole brain networks is a promising approach to extract features of autism spectrum disorder (ASD), a brain disorder of widespread regions. 5Department of Computer Science, Chiba Institute of Technology, Narashino, Japan.4Faculty of Education, Institute of Human and Social Sciences, Kanazawa University, Kanazawa, Japan.3Department of Neuropsychiatry, Ishikawa Prefectural Takamatsu Hospital, Kahoku, Japan.2Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan.1Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan.Daiki Soma 1, Tetsu Hirosawa 1,2 *, Chiaki Hasegawa 2, Kyung-min An 2, Masafumi Kameya 1, Shoryoku Hino 3, Yuko Yoshimura 2,4, Sou Nobukawa 5, Sumie Iwasaki 2, Sanae Tanaka 2, Ken Yaoi 2, Masuhiko Sano 1, Yuka Shiota 2, Nobushige Naito 1 and Mitsuru Kikuchi 1,2
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