Dataset Information

Dynamic Functional Connectivity Patterns in Schizophrenia and the Relationship With Hallucinations.

ABSTRACT: There is a wealth of evidence showing aberrant functional connectivity (FC) in schizophrenia but with considerable variability in findings across studies. Dynamic FC is an extension of traditional static FC, in that such analyses allow for explorations of temporal changes in connectivity. Thereby they also provide more detailed information on connectivity abnormalities in psychiatric disorders such as schizophrenia. The current study investigated dynamic FC in a sample of 80 schizophrenia patients and 80 matched healthy control subjects, replicating previous findings of aberrant dwell times in specific FC states, and further supporting a role for default mode network (DMN) dysfunction. Furthermore, relationships with hallucinations, a core symptom of schizophrenia, were explored. Two measures of hallucinations were used, one measure of current hallucination severity assessed on the day of scanning, and one trait-measure where hallucinations were assessed repeatedly over the course of 1 year. Current hallucination severity did not show a significant relationship with dynamic FC. However, the trait-measure of hallucination proneness over 1 year showed a significant relationship with dynamic FC. Patients with high hallucination proneness spent less time in connectivity states characterized by strong anti-correlation between the DMN and task-positive networks. The findings support theoretical models of hallucinations which have proposed an instability of the DMN and impaired cognitive control in patients with hallucinations. Furthermore, the results point to hallucination proneness as a potential marker for identifying distinct subgroups of schizophrenia patients.

SUBMITTER: Weber S

PROVIDER: S-EPMC7145395 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Dynamic Functional Connectivity Patterns in Schizophrenia and the Relationship With Hallucinations.

Weber Sarah S Johnsen Erik E Kroken Rune A RA Løberg Else-Marie EM Kandilarova Sevdalina S Stoyanov Drozdstoy D Kompus Kristiina K Hugdahl Kenneth K

Frontiers in psychiatry 20200331

There is a wealth of evidence showing aberrant functional connectivity (FC) in schizophrenia but with considerable variability in findings across studies. Dynamic FC is an extension of traditional static FC, in that such analyses allow for explorations of temporal changes in connectivity. Thereby they also provide more detailed information on connectivity abnormalities in psychiatric disorders such as schizophrenia. The current study investigated dynamic FC in a sample of 80 schizophrenia patien ...[more]

PMID: 32300313

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Project description:The human brain is a highly dynamic system with non-stationary neural activity and rapidly-changing neural interaction. Resting-state dynamic functional connectivity (dFC) has been widely studied during recent years, and the emerging aberrant dFC patterns have been identified as important features of many mental disorders such as schizophrenia (SZ). However, only focusing on the time-varying patterns in FC is not enough, since the local neural activity itself (in contrast to the inter-connectivity) is also found to be highly fluctuating from research using high-temporal-resolution imaging techniques. Exploring the time-varying patterns in brain activity and their relationships with time-varying brain connectivity is important for advancing our understanding of the co-evolutionary property of brain network and the underlying mechanism of brain dynamics. In this study, we introduced a framework for characterizing time-varying brain activity and exploring its associations with time-varying brain connectivity, and applied this framework to a resting-state fMRI dataset including 151 SZ patients and 163 age- and gender matched healthy controls (HCs). In this framework, 48 brain regions were first identified as intrinsic connectivity networks (ICNs) using group independent component analysis (GICA). A sliding window approach was then adopted for the estimation of dynamic amplitude of low-frequency fluctuation (dALFF) and dFC, which were used to measure time-varying brain activity and time-varying brain connectivity respectively. The dALFF was further clustered into six reoccurring states by the k-means clustering method and the group difference in occurrences of dALFF states was explored. Lastly, correlation coefficients between dALFF and dFC were calculated and the group difference in these dALFF-dFC correlations was explored. Our results suggested that 1) ALFF of brain regions was highly fluctuating during the resting-state and such dynamic patterns are altered in SZ, 2) dALFF and dFC were correlated in time and their correlations are altered in SZ. The overall results support and expand prior work on abnormalities of brain activity, static FC (sFC) and dFC in SZ, and provide new evidence on aberrant time-varying brain activity and its associations with brain connectivity in SZ, which might underscore the disrupted brain cognitive functions in this mental disorder.

Project description: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. Impact statement This work introduces the use of joint blind source separation for the study of brain dynamics to enable efficient quantification of the spatial property of dynamic blood-oxygen-level-dependent (BOLD) activity to provide insight into the relationship of dynamic BOLD activity and dynamic functional network connectivity. The identification of subgroups of schizophrenia using dynamic features allows the study of heterogeneity of schizophrenia, emphasizing the importance of functional magnetic resonance imaging analysis in the study of brain activity and functional connectivity to gain a better understanding of the human brain, especially the brain with a mental disorder.

Project description:Background and objectiveAs a key feature of schizophrenia, auditory verbal hallucination (AVH) is causing concern. Altered dynamic functional connectivity (dFC) patterns involving in auditory related regions were rarely reported in schizophrenia patients with AVH. The goal of this research was to find out the dFC abnormalities of auditory related regions in first-episode, drug-naïve schizophrenia patients with and without AVH using resting state functional magnetic resonance imaging (rs-fMRI).MethodsA total of 107 schizophrenia patients with AVH, 85 schizophrenia patients without AVH (NAVH) underwent rs-fMRI examinations, and 104 healthy controls (HC) were matched. Seed-based dFC of the primary auditory cortex (Heschl's gyrus, HES), auditory association cortex (AAC, including Brodmann's areas 22 and 42), and medial geniculate nucleus (MGN) was conducted to build a whole-brain dFC diagram, then inter group comparison and correlation analysis were performed.ResultsIn comparison to the NAVH and HC groups, the AVH group showed increased dFC from left ACC to the right middle temporal gyrus and right middle occipital gyrus, decreased dFC from left HES to the left superior occipital gyrus, left cuneus gyrus, left precuneus gyrus, decreased dFC from right HES to the posterior cingulate gyrus, and decreased dFC from left MGN to the bilateral calcarine gyrus, bilateral cuneus gyrus, bilateral lingual gyrus. The Auditory Hallucination Rating Scale (AHRS) was significantly positively correlated with the dFC values of cluster 1 (bilateral calcarine gyrus, cuneus gyrus, lingual gyrus, superior occipital gyrus, precuneus gyrus, and posterior cingulate gyrus) using left AAC seed, cluster 2 (right middle temporal gyrus and right middle occipital gyrus) using left AAC seed, cluster 1 (bilateral calcarine gyrus, cuneus gyrus, lingual gyrus, superior occipital gyrus, precuneus gyrus and posterior cingulate gyrus) using right AAC seed and cluster 2 (posterior cingulate gyrus) using right HES seed in the AVH group. In both AVH and NAVH groups, a significantly negative correlation is also found between the dFC values of cluster 2 (posterior cingulate gyrus) using the right HES seed and the PANSS negative sub-scores.ConclusionsThe present findings demonstrate that schizophrenia patients with AVH showed multiple abnormal dFC regions using auditory related cortex and nucleus as seeds, particularly involving the occipital lobe, default mode network (DMN), and middle temporal lobe, implying that the different dFC patterns of auditory related areas could provide a neurological mechanism of AVH in schizophrenia.

Dataset Information

Dynamic Functional Connectivity Patterns in Schizophrenia and the Relationship With Hallucinations.

Publications

Dynamic Functional Connectivity Patterns in Schizophrenia and the Relationship With Hallucinations.

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