Identifying brain areas correlated with ADOS raw scores by studying altered dynamic functional connectivity patterns
•Using dynamic functional connectivity to study the brain functional connectivity in the autistic subjects.•Providing novel algorithm to quantify brain over connectivity and under connectivity in the brain.•Study the correlation between increased and decreased functional connectivity with ADOS score...
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Published in | Medical image analysis Vol. 68; p. 101899 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Netherlands
Elsevier B.V
01.02.2021
Elsevier BV |
Subjects | |
Online Access | Get full text |
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Summary: | •Using dynamic functional connectivity to study the brain functional connectivity in the autistic subjects.•Providing novel algorithm to quantify brain over connectivity and under connectivity in the brain.•Study the correlation between increased and decreased functional connectivity with ADOS score.
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Altered functional connectivity patterns play an important role in explaining autism spectrum disorder related impairments. In order to examine such connectivity, resting state functional MRI is the most commonly used technique. To date, the majority of works in this area examine a whole time series of brain activation as a discrete stationary process. This study proposes a more detailed analysis of how functional connectivity fluctuates over time and how it is used to quantify instances demonstrating overconnectivity or underconnectivity. Non-parametric surrogates test identifies the areas where underconnectivity or overconnectivity correlate with the Autism Diagnosis Observation Schedule. In addition, this study shows how the areas identified affect the subjects behaviors. Our ultimate goal is a personalized autism diagnosis and treatment CAD system, where each subject impairments are distinctly mapped so they can be addressed with targeted treatments. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 1361-8415 1361-8423 1361-8423 |
DOI: | 10.1016/j.media.2020.101899 |