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Features of the resting-state functional brain network of children with autism spectrum disorder: EEG source-level analysis

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Abstract

We study the specific features of the organization of the functional brain networks of children with autism spectrum disorder (ASD) by analyzing at the source level the data obtained in the EEG experiment in the resting-state paradigm. We pay special attention to age-related changes in the characteristics of functional networks during the particularly important age period from early childhood to adolescence. The analyzed experimental groups consisted of 148 ASD children and 173 neurotypical children that were considered as a control group. In the theta band, we revealed an age-independent functional connectivity pattern, consisting of the brain areas responsible for emotions and consciousness, where the strength of connections is higher in neurotypical children compared to ASD children. Moreover, we discovered lower network global clustering in the delta + theta band in ASD children. Thus, more segregated, but more highly connected subnets are formed in the delta + theta band in neurotypical individuals compared to ASD ones. We can suggest increased control over emotions and stronger interaction between the emotional and conscious domains in neurotypical children. In the extended alpha band, we revealed an age-dependent functional connectivity pattern, demonstrating hyper-activation in the ASD group for ages below 6–7 years old and hypo-activation—for older ages. Also, we discuss the development of effective approaches to autism therapy, which should be based on the normalization of aberrant functional connections.

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Data availibility statement

The datasets analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

The study was supported by the Russian Foundation for Basic Research and National Natural Science Foundation of China (Project No. 19-52-55001) and Project 36-L-22 of the Priority 2030 program of Immanuel Kant Baltic Federal University. Data set was collected in the frame of Russian Science Foundation project No. 20-68-46042.

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Authors and Affiliations

  1. Baltic Center for Artificial Intelligence and Neurotechnology, Immanuel Kant Baltic Federal University, A. Nevskogo Str., Kaliningrad, 236016, Russia

    Semen Kurkin, Elena Pitsik & Alexander Hramov

  2. Neuroscience Research Institute, Samara State Medical University, Chapaevskaya Str., Samara, 443099, Russia

    Semen Kurkin, Elena Pitsik & Alexander Hramov

  3. Division for the Promotion of New Cardiac Information Technology, Saratov State Medical University, Bolshaya Kazachia Str., Saratov, 410012, Russia

    Semen Kurkin, Elena Pitsik & Alexander Hramov

  4. Faculty of Computer Science, Innopolis University, Universitetskaya Str., Innopolis, 420500, Russia

    Nikita Smirnov & Muhammad Salman Kabir

  5. Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Butlerova St., Moscow, 117485, Russia

    Olga Martynova, Olga Sysoeva & Galina Portnova

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  1. Semen Kurkin
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by SK, NS, EP, MSK, OM, OS, GP, and AH The first draft of the manuscript was written by SK and EP and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Alexander Hramov.

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Kurkin, S., Smirnov, N., Pitsik, E. et al. Features of the resting-state functional brain network of children with autism spectrum disorder: EEG source-level analysis. Eur. Phys. J. Spec. Top. 232, 683–693 (2023). https://doi.org/10.1140/epjs/s11734-022-00717-0

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  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1140/epjs/s11734-022-00717-0

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