Identification of Asperger's from healthy individuals: Using a graph theoretical approach on the task-free fMRI data

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Mobarezpour Jahangir; Khosrowabadi Reza; GHADERI REZA; NAVI KEIVAN

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Advances in Cognitive Sciences Year:2019 | Volume:21 | Issue:3 Page(s): 74-83

Download Full-Text

Persian Verion

View:

1,198

Download:

Cites:

Information Journal Paper

Title

Identification of Asperger's from healthy individuals: Using a graph theoretical approach on the task-free fMRI data

Author(s)

Mobarezpour Jahangir | Khosrowabadi Reza | GHADERI REZA | NAVI KEIVAN | Issue Writer Certificate

Keywords

Asperger's syndromeQ1

Functional magnetic resonance imagingQ1

((fMRI))Q1

Graph theoryQ1

Abstract

Introduction: Asperger’ s syndrome is generally known as a neurodevelopmental disorder. The main features of this syndrome are the lack of social interaction, non-verbal communication, unusual repetitive behavior, restricted interests, and may have an inherent talent such as mathematics, music, etc. Nonetheless, their brain structural and functional variations as compared to healthy individuals require to be well understood. Methods: This study intends to identify differences of the task-free (fMRI) data in Asperger’ s syndrome as compared to healthy individuals using the graph-theoretical approach. In this approach, graph local and global measures are calculated from the functional network, which estimated through taking the correlation between activities in different parts of the brain. Subsequently, the differential pattern of local and global measures in Asperger’ s syndrome as compared to healthy control group is investigated. Two groups of the subjects are matched in terms of age, gender, handedness, and IQ scores. Results: Results revealed the significant differences in local measures at temporal, amygdala, thalamus, and heschl regions. Classification of the tf-(fMRI) data based on the identified measures shows an accuracy of 84% to discriminate Asperger's individuals from the healthy group. Conclusion: Accordingly, local measures extracted from the graph of the task-free functional connectivity network have a good potential for screening of Asperger's syndrome that can be used as an automatically-diagnosed method of this disorder.

Cites

No record.

References

No record.

Cite

APA: Copy

Mobarezpour, Jahangir, Khosrowabadi, Reza, GHADERI, REZA, & NAVI, KEIVAN. (2019). Identification of Asperger's from healthy individuals: Using a graph theoretical approach on the task-free fMRI data. ADVANCES IN COGNITIVE SCIENCE, 21(3 ), 74-83. SID. https://sid.ir/paper/82875/en

Vancouver: Copy

Mobarezpour Jahangir, Khosrowabadi Reza, GHADERI REZA, NAVI KEIVAN. Identification of Asperger's from healthy individuals: Using a graph theoretical approach on the task-free fMRI data. ADVANCES IN COGNITIVE SCIENCE[Internet]. 2019;21(3 ):74-83. Available from: https://sid.ir/paper/82875/en

IEEE: Copy

Jahangir Mobarezpour, Reza Khosrowabadi, REZA GHADERI, and KEIVAN NAVI, “Identification of Asperger's from healthy individuals: Using a graph theoretical approach on the task-free fMRI data,” ADVANCES IN COGNITIVE SCIENCE, vol. 21, no. 3 , pp. 74–83, 2019, [Online]. Available: https://sid.ir/paper/82875/en

Related Journal Papers