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Investigating Resting-state Functional Connectivity in Children and Adolescents at High Familial Risk for Schizophrenia.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Investigating Resting-state Functional Connectivity in Children and Adolescents at High Familial Risk for Schizophrenia./
Author:	Imamoglu, Aslihan.
Description:	1 online resource (112 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-11, Section: B.
Contained By:	Dissertations Abstracts International85-11B.
Subject:	Psychology. -
Online resource:	click for full text (PQDT)
ISBN:	9798382629711

Investigating Resting-state Functional Connectivity in Children and Adolescents at High Familial Risk for Schizophrenia.
Imamoglu, Aslihan.

Investigating Resting-state Functional Connectivity in Children and Adolescents at High Familial Risk for Schizophrenia. - 1 online resource (112 pages)

Source: Dissertations Abstracts International, Volume: 85-11, Section: B.

Thesis (Ph.D.)--The University of North Carolina at Chapel Hill, 2024.

Includes bibliographical references

Schizophrenia is characterized by disruptions in resting-state functional connectivity, which has been proposed to underlie cognitive dysfunction that is prevalent in both individuals with schizophrenia and their first-degree relatives. Specifically, individuals with schizophrenia exhibit altered network organization at whole brain network and hippocampal network levels. The current study investigated whether such abnormalities are present in 76 children and adolescents (aged 9-16 years) with and without familial risk for schizophrenia. I characterized whole brain functional connectivity by employing graph theory metrics of network segregation (i.e., local efficiency, modularity), integration (i.e., global efficiency), and small-worldness. Then, I assessed the modularity of two hippocampal networks (i.e., hippocampal-MTLC and hippocampal-cortical network) that are integral to episodic (day-to-day) memory, as well as the participation coefficient of the hippocampus. I observed that when a pre-defined network structure was assumed, participants at high familial risk for schizophrenia (i.e., high-risk) showed altered levels of modularity than controls at both whole brain and hippocampal-cortical network levels. Higher modularity in hippocampal networks was associated with better episodic memory for control participants. However, these patterns were no longer present when community structures were optimized for each participant. Together, these results imply that while familial risk for schizophrenia may affect the modularity of functional networks, the detection of such effects relies heavily on the methodological approach used to identify functional communities.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798382629711Subjects--Topical Terms:

555998
Psychology.
Subjects--Index Terms:

Episodic memoryIndex Terms--Genre/Form:

554714
Electronic books.

Investigating Resting-state Functional Connectivity in Children and Adolescents at High Familial Risk for Schizophrenia.
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520 $a Schizophrenia is characterized by disruptions in resting-state functional connectivity, which has been proposed to underlie cognitive dysfunction that is prevalent in both individuals with schizophrenia and their first-degree relatives. Specifically, individuals with schizophrenia exhibit altered network organization at whole brain network and hippocampal network levels. The current study investigated whether such abnormalities are present in 76 children and adolescents (aged 9-16 years) with and without familial risk for schizophrenia. I characterized whole brain functional connectivity by employing graph theory metrics of network segregation (i.e., local efficiency, modularity), integration (i.e., global efficiency), and small-worldness. Then, I assessed the modularity of two hippocampal networks (i.e., hippocampal-MTLC and hippocampal-cortical network) that are integral to episodic (day-to-day) memory, as well as the participation coefficient of the hippocampus. I observed that when a pre-defined network structure was assumed, participants at high familial risk for schizophrenia (i.e., high-risk) showed altered levels of modularity than controls at both whole brain and hippocampal-cortical network levels. Higher modularity in hippocampal networks was associated with better episodic memory for control participants. However, these patterns were no longer present when community structures were optimized for each participant. Together, these results imply that while familial risk for schizophrenia may affect the modularity of functional networks, the detection of such effects relies heavily on the methodological approach used to identify functional communities.
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