A Hierarchical Model for Autism Spectrum Disorder (HMASD)

سال انتشار: 1395
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 259

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تاریخ نمایه سازی: 6 اسفند 1398

چکیده مقاله:

Background: Autism spectrum disorder (ASD) is a severe behavioral disorder characterized by pervasive impairments in social interactions,deficits in verbal and nonverbal communication, and stereotyped, repetitive patterns of behaviors and interests. Despiterecent advances in identifying some genes that may cause autism, its underlying neurological mechanisms are uncertain. ASD isbest conceptualized by considering the neural systems that may be defective in autistic individuals.Objectives: Here, weaim to describe a potential Hierarchical model for ASD. This interesting presented model is based on excitatoryand inhibitory characteristics of cortico-cortical networks.Methods: Jason model is one of the models applied to produce EEG in cortical areas. In this model, a cortical area is modeled withthree subpopulations including: excitatory pyramidal cells (output), excitatory interneurons groups, input inhibitory interneurongroups by means of output connections (output connections are limited to cortical planes). The presented hierarchical model forautism spectrum disorder (HMASD) is based on Jason model. HMASD is a hierarchical model of cortico-cortical networks as wellas an excitation/inhibition model in sensory, mnemonic, social and emotional systems. In HMASD there are three kinds of outerconnections including forward, backward and lateral connections, that their power is controlled by coupling parameters.Results: HMASD raises the possibility that ASD is related to excitation/inhibition imbalance in cortico-cortical networks. HMASDparameters are possible way for quantization imbalance quality.Conclusions: The most effected parts in ASD are lateral connections of HMASD. Two-sided connections which are completely symmetricbecome more active, and cause extra synchronization. On the other hand, due to special characteristic of two-sided connectionsand their ability to simulate the same phased dynamics, they cause unnatural asymmetry in children’s EEG signal. Theseresults are consistent with previous findings suggesting the association of EEG abnormalities in ASD with functional impairmentof information interacted in cortical connections.


Ghasem Sadeghi Bajestani

Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, IR Iran

Ali Sheikhani

Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, IR Iran

Mohammad Reza Hashemi Golpayegani

Department of Biomedical Engineering, Amir Kabir University of Technology, Tehran, IR Iran

Farah Ashrafzadeh

Paediatric Neurology Division, Qaem Hospital, Mashhad University of Medical Sciences, Mashhad, IR Iran

Paria Hebrani

Department of Paediatrics, Dr Sheikh Paediatric Hospital, Mashhad University of Medical Sciences, IR Iran