Diagnosis of Autism Spectrum Disorder Using Central-Moment Features From Low- and High-Order Dynamic Resting-State Functional Connectivity Networks

Diagnosis of Autism Spectrum Disorder Using Central-Moment Features From Low- and High-Order Dynamic Resting-State Functional Connectivity Networks

The sliding-window-based dynamic functional connectivity networks (D-FCNs) derived from resting-state functional magnetic resonance imaging (rs-fMRI) are effective methods for diagnosing various neurological diseases, including autism spectrum disorder (ASD). However, traditional D-FCNs are low-orde...

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Bibliographic Details
Main Authors: Feng Zhao, Zhiyuan Chen, Islem Rekik, Seong-Whan Lee, Dinggang Shen
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-04-01
Series:Frontiers in Neuroscience
Subjects:
autism spectrum disorder
dynamic functional connectivity networks
resting-state functional MRI
central-moment features
conventional FC network
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2020.00258/full

Internet

https://www.frontiersin.org/article/10.3389/fnins.2020.00258/full

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