Screening of autism based on task-free fMRI using graph theoretical approach. (30th May 2017)
- Record Type:
- Journal Article
- Title:
- Screening of autism based on task-free fMRI using graph theoretical approach. (30th May 2017)
- Main Title:
- Screening of autism based on task-free fMRI using graph theoretical approach
- Authors:
- Sadeghi, Masoumeh
Khosrowabadi, Reza
Bakouie, Fatemeh
Mahdavi, Hoda
Eslahchi, Changiz
Pouretemad, Hamidreza - Abstract:
- Abstract: 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. Highlights: Global parameters of the brain functional connectome are decreased in autism (ASD). Centrality of the brain regions areAbstract: 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. Highlights: Global parameters of the brain functional connectome are decreased in autism (ASD). Centrality of the brain regions are mainly altered at the right hemisphere in ASD. Alteration of FC local parameters may warrant screening of ASD. … (more)
- Is Part Of:
- Psychiatry research. Volume 263(2017)
- Journal:
- Psychiatry research
- Issue:
- Volume 263(2017)
- Issue Display:
- Volume 263, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 263
- Issue:
- 2017
- Issue Sort Value:
- 2017-0263-2017-0000
- Page Start:
- 48
- Page End:
- 56
- Publication Date:
- 2017-05-30
- Subjects:
- Autism spectrum disorder -- Functional connectivity -- Graph theory -- Classification -- Support vector machine
Psychiatry -- Periodicals
Brain -- Imaging -- Periodicals
Psychiatry -- Periodicals
Diagnostic Imaging -- Periodicals
Psychiatrie -- Périodiques
Cerveau -- Imagerie pour le diagnostic -- Périodiques
616.890754 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09254927 ↗
http://www.clinicalkey.com/dura/browse/journalIssue/09254927 ↗
http://www.clinicalkey.com.au/dura/browse/journalIssue/09254927 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.pscychresns.2017.02.004 ↗
- Languages:
- English
- ISSNs:
- 0925-4927
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6946.263705
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 2207.xml