Screening of autism based on task-free fMRI using graph theoretical approach.
Studies on autism spectrum disorder (ASD) have indicated several dysfunctions in the structure, and functional organization of the brain. However, findings have not been established as a general diagnostic tool yet. In this regard, current study proposed an automatic screening method for recognition of ASDs from healthy controls (HCs) based on their brain functional abnormalities. In this paradigm, brain functional networks of 60 adolescent and young adult males (29 ASDs and 31 HCs) were estimated from subjects' task-free fMRI data. Then, autism screening was developed based on characteristics of the functional networks using the following steps: A) local and global parameters of the brain functional network were calculated using graph theory. B) network parameters of the ASDs were statistically compared to the HCs. C) significantly altered parameters were used as input features of the screening system. D) performance of the system was verified using various classification techniques. The support vector machine showed superiority to others with an accuracy of 92%. Subsequently, reliability of the results was examined using an independent dataset including 20 ASDs and 20 HCs. Our findings suggest that local parameters of the brain functional network, despite the individual variability, can potentially be used for autism screening.
Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran; Department of Computer Sciences, Faculty of Mathematics, Shahid Beheshti University, Tehran, Iran.
Masoumeh
M
Sadeghi
Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran. Electronic address: r_khosroabadi@sbu.ac.ir.
Reza
R
Khosrowabadi
Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran.
Fatemeh
F
Bakouie
Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran.
Hoda
H
Mahdavi
Department of Computer Sciences, Faculty of Mathematics, Shahid Beheshti University, Tehran, Iran; School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.
Changiz
C
Eslahchi
Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran; Faculty of Psychology and Educational Sciences, Shahid Beheshti University, Tehran, Iran.
Hamidreza
H
Pouretemad
D000293:Adolescent; D000328:Adult; D000067877:Autism Spectrum Disorder / Q000000981:diagnostic imaging* / Q000503:physiopathology; D001321:Autistic Disorder / Q000000981:diagnostic imaging / Q000503:physiopathology; D001921:Brain / Q000000981:diagnostic imaging* / Q000503:physiopathology; D001931:Brain Mapping / Q000379:methods*; D002648:Child; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D009415:Nerve Net / Q000000981:diagnostic imaging* / Q000503:physiopathology; D015203:Reproducibility of Results; D060388:Support Vector Machine; D055815:Young Adult
Autism spectrum disorder; Classification; Functional connectivity; Graph theory; Support vector machine