Brain Relatively Inert Network: Taking Adult Attention Deficit Hyperactivity Disorder as an Example

Resting-state functional MRI (rs-fMRI) has been increasingly applied in the research of brain cognitive science and psychiatric diseases. However, previous studies only focused on specific activation areas of the brain, and there are few studies on the inactivation areas. This may overlook much info...

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Autores principales:	Hua Zhang, Weiming Zeng, Jin Deng, Yuhu Shi, Le Zhao, Ying Li
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	activation network relatively inert network functional MRI group ICA functional connectivity adult ADHD Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Acceso en línea:	https://doaj.org/article/86d66984ba09486abf23dedee65b16ba
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spelling	oai:doaj.org-article:86d66984ba09486abf23dedee65b16ba2021-12-03T07:19:46ZBrain Relatively Inert Network: Taking Adult Attention Deficit Hyperactivity Disorder as an Example1662-453X10.3389/fnins.2021.771947https://doaj.org/article/86d66984ba09486abf23dedee65b16ba2021-12-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fnins.2021.771947/fullhttps://doaj.org/toc/1662-453XResting-state functional MRI (rs-fMRI) has been increasingly applied in the research of brain cognitive science and psychiatric diseases. However, previous studies only focused on specific activation areas of the brain, and there are few studies on the inactivation areas. This may overlook much information that explains the brain’s cognitive function. In this paper, we propose a relatively inert network (RIN) and try to explore its important role in understanding the cognitive mechanism of the brain and the study of mental diseases, using adult attention deficit hyperactivity disorder (ADHD) as an example. Here, we utilize methods based on group independent component analysis (GICA) and t-test to identify RIN and calculate its corresponding time series. Through experiments, alterations in the RIN and the corresponding activation network (AN) in adult ADHD patients are observed. And compared with those in the left brain, the activation changes in the right brain are greater. Further, when the RIN functional connectivity is introduced as a feature to classify adult ADHD patients from healthy controls (HCs), the classification accuracy rate is 12% higher than that of the original functional connectivity feature. This was also verified by testing on an independent public dataset. These findings confirm that the RIN of the brain contains much information that will probably be neglected. Moreover, this research provides an effective new means of exploring the information integration between brain regions and the diagnosis of mental illness.Hua ZhangWeiming ZengJin DengYuhu ShiLe ZhaoYing LiFrontiers Media S.A.articleactivation networkrelatively inert networkfunctional MRIgroup ICAfunctional connectivityadult ADHDNeurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENFrontiers in Neuroscience, Vol 15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	activation network relatively inert network functional MRI group ICA functional connectivity adult ADHD Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
spellingShingle	activation network relatively inert network functional MRI group ICA functional connectivity adult ADHD Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Hua Zhang Weiming Zeng Jin Deng Yuhu Shi Le Zhao Ying Li Brain Relatively Inert Network: Taking Adult Attention Deficit Hyperactivity Disorder as an Example
description	Resting-state functional MRI (rs-fMRI) has been increasingly applied in the research of brain cognitive science and psychiatric diseases. However, previous studies only focused on specific activation areas of the brain, and there are few studies on the inactivation areas. This may overlook much information that explains the brain’s cognitive function. In this paper, we propose a relatively inert network (RIN) and try to explore its important role in understanding the cognitive mechanism of the brain and the study of mental diseases, using adult attention deficit hyperactivity disorder (ADHD) as an example. Here, we utilize methods based on group independent component analysis (GICA) and t-test to identify RIN and calculate its corresponding time series. Through experiments, alterations in the RIN and the corresponding activation network (AN) in adult ADHD patients are observed. And compared with those in the left brain, the activation changes in the right brain are greater. Further, when the RIN functional connectivity is introduced as a feature to classify adult ADHD patients from healthy controls (HCs), the classification accuracy rate is 12% higher than that of the original functional connectivity feature. This was also verified by testing on an independent public dataset. These findings confirm that the RIN of the brain contains much information that will probably be neglected. Moreover, this research provides an effective new means of exploring the information integration between brain regions and the diagnosis of mental illness.
format	article
author	Hua Zhang Weiming Zeng Jin Deng Yuhu Shi Le Zhao Ying Li
author_facet	Hua Zhang Weiming Zeng Jin Deng Yuhu Shi Le Zhao Ying Li
author_sort	Hua Zhang
title	Brain Relatively Inert Network: Taking Adult Attention Deficit Hyperactivity Disorder as an Example
title_short	Brain Relatively Inert Network: Taking Adult Attention Deficit Hyperactivity Disorder as an Example
title_full	Brain Relatively Inert Network: Taking Adult Attention Deficit Hyperactivity Disorder as an Example
title_fullStr	Brain Relatively Inert Network: Taking Adult Attention Deficit Hyperactivity Disorder as an Example
title_full_unstemmed	Brain Relatively Inert Network: Taking Adult Attention Deficit Hyperactivity Disorder as an Example
title_sort	brain relatively inert network: taking adult attention deficit hyperactivity disorder as an example
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/86d66984ba09486abf23dedee65b16ba
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Brain Relatively Inert Network: Taking Adult Attention Deficit Hyperactivity Disorder as an Example

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