Paper Info
Title
Relationship Between Dynamic Blood-Oxygen-Level-Dependent Activity And Functional Network Connectivity: Characterization Of Schizophrenia Subgroups
Abstract
Aim: In this work, we propose the novel use of adaptively constrained independent vector analysis (acIVA) to effectively capture the temporal and spatial properties of dynamic blood-oxygen-level-dependent (BOLD) activity (dBA), and we efficiently quantify the spatial property of dBA (sdBA). We also propose to incorporate dBA into the study of brain dynamics to gain insight into activity-connectivity co-evolution patterns.Introduction: Studies of the dynamics of the human brain using functional magnetic resonance imaging (fMRI) have enabled the identification of unique functional network connectivity (FNC) states and provided new insights into mental disorders. There is evidence showing that both BOLD activity, which is captured by fMRI, and FNC are related to mental and cognitive processes. However, a few studies have evaluated the inter-relationships of these two domains of function. Moreover, the identification of subgroups of schizophrenia has gained significant clinical importance due to a need to study the heterogeneity of schizophrenia.Methods: We design a simulation study to verify the effectiveness of acIVA and apply acIVA to the dynamic study of resting-state fMRI data collected from individuals with schizophrenia and healthy controls (HCs) to investigate the relationship between dBA and dynamic FNC (dFNC).Results: The simulation study demonstrates that acIVA accurately captures the spatial variability and provides an efficient quantification of sdBA. The fMRI analysis yields synchronized sdBA-temporal property of dBA (tdBA) patterns and shows that the dBA and dFNC are significantly correlated in the spatial domain. Using these dynamic features, we identify schizophrenia subgroups with significant differences in terms of their clinical symptoms.Conclusion: We find that brain function is abnormally organized in schizophrenia compared with HCs since there are less synchronized sdBA-tdBA patterns in schizophrenia and schizophrenia prefers a component that merges multiple brain regions. Identification of schizophrenia subgroups using dynamic features inspires the use of neuroimaging in studying the heterogeneity of disorders.
Year
DOI
Venue
2021
10.1089/brain.2020.0815
BRAIN CONNECTIVITY
Keywords
DocType
Volume
adaptively constrained IVA, dynamic BOLD activity, dynamic functional network connectivity, dynamic study, resting-state fMRI data
Journal
11
Issue
ISSN
Citations 
6
2158-0014
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Qunfang Long103.38
Suchita Bhinge233.80
Vince D Calhoun32769268.91
Tulay Adali421116.65