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Coherence Analysis in the Brain Network of ASD Children using Connectivity Model and Graph Theory


Affiliations
1 Centre for Cyber Physical Systems, School of Electronics Engineering, Vellore Institute of Technology, Chennai 600 127, India
 

Autism Spectrum Disorder (ASD) belongs with the category of neuro-developmental disorders, which can be majorly categorized under decreased social relationships, communication and thought processes. Various studies in the field of biological networks prove that one of the defining features of ASD is altered brain connectivity. Hence, the understanding of the brain networks can pave the way to delve deeper into the underlying behaviour of the Autistic brains. Moreover, many studies also reveal that human brains exhibit small-world characteristics which are usually seen in simple model neural networks that emerge spontaneously upon adaptive rewiring according to the dynamical functional connectivity. Graph theory-based approaches are finding their way into the understanding of the altered connectivity in various neurological disorders. For that matter, the study focuses on implementing a graph theory-based approach to investigate on the small-world network of Autistic as well as typically developing brains and understand the behavioural changes for an Audio and Video Stimuli. The graphically generated data is then measured for functional connectivity using a symmetrical parameter known as the coherence measure.

Keywords

Autism spectrum disorder, Biological network, Coherence measure, Functional connectivity
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  • Coherence Analysis in the Brain Network of ASD Children using Connectivity Model and Graph Theory

Abstract Views: 146  |  PDF Views: 82

Authors

Menaka R
Centre for Cyber Physical Systems, School of Electronics Engineering, Vellore Institute of Technology, Chennai 600 127, India
Karthik R
Centre for Cyber Physical Systems, School of Electronics Engineering, Vellore Institute of Technology, Chennai 600 127, India
Aaditya Parthasarathy
Centre for Cyber Physical Systems, School of Electronics Engineering, Vellore Institute of Technology, Chennai 600 127, India
Manideep P
Centre for Cyber Physical Systems, School of Electronics Engineering, Vellore Institute of Technology, Chennai 600 127, India
Varsha V
Centre for Cyber Physical Systems, School of Electronics Engineering, Vellore Institute of Technology, Chennai 600 127, India

Abstract


Autism Spectrum Disorder (ASD) belongs with the category of neuro-developmental disorders, which can be majorly categorized under decreased social relationships, communication and thought processes. Various studies in the field of biological networks prove that one of the defining features of ASD is altered brain connectivity. Hence, the understanding of the brain networks can pave the way to delve deeper into the underlying behaviour of the Autistic brains. Moreover, many studies also reveal that human brains exhibit small-world characteristics which are usually seen in simple model neural networks that emerge spontaneously upon adaptive rewiring according to the dynamical functional connectivity. Graph theory-based approaches are finding their way into the understanding of the altered connectivity in various neurological disorders. For that matter, the study focuses on implementing a graph theory-based approach to investigate on the small-world network of Autistic as well as typically developing brains and understand the behavioural changes for an Audio and Video Stimuli. The graphically generated data is then measured for functional connectivity using a symmetrical parameter known as the coherence measure.

Keywords


Autism spectrum disorder, Biological network, Coherence measure, Functional connectivity

References