scholarly journals Aberrant Dynamic Functional Connectivity of Default Mode Network in Schizophrenia and Links to Symptom Severity

2021 ◽  
Vol 15 ◽  
Author(s):  
Mohammad S. E. Sendi ◽  
Elaheh Zendehrouh ◽  
Charles A. Ellis ◽  
Zhijia Liang ◽  
Zening Fu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Resting State ◽  
Symptom Severity ◽  
Transition Probability ◽  
Feature Selection Method ◽  
Cingulate Cortex ◽  
Anterior Cingulate ◽  
Dynamic Functional Connectivity ◽  
Default Mode

Background: Schizophrenia affects around 1% of the global population. Functional connectivity extracted from resting-state functional magnetic resonance imaging (rs-fMRI) has previously been used to study schizophrenia and has great potential to provide novel insights into the disorder. Some studies have shown abnormal functional connectivity in the default mode network (DMN) of individuals with schizophrenia, and more recent studies have shown abnormal dynamic functional connectivity (dFC) in individuals with schizophrenia. However, DMN dFC and the link between abnormal DMN dFC and symptom severity have not been well-characterized.Method: Resting-state fMRI data from subjects with schizophrenia (SZ) and healthy controls (HC) across two datasets were analyzed independently. We captured seven maximally independent subnodes in the DMN by applying group independent component analysis and estimated dFC between subnode time courses using a sliding window approach. A clustering method separated the dFCs into five reoccurring brain states. A feature selection method modeled the difference between SZs and HCs using the state-specific FC features. Finally, we used the transition probability of a hidden Markov model to characterize the link between symptom severity and dFC in SZ subjects.Results: We found decreases in the connectivity of the anterior cingulate cortex (ACC) and increases in the connectivity between the precuneus (PCu) and the posterior cingulate cortex (PCC) (i.e., PCu/PCC) of SZ subjects. In SZ, the transition probability from a state with weaker PCu/PCC and stronger ACC connectivity to a state with stronger PCu/PCC and weaker ACC connectivity increased with symptom severity.Conclusions: To our knowledge, this was the first study to investigate DMN dFC and its link to schizophrenia symptom severity. We identified reproducible neural states in a data-driven manner and demonstrated that the strength of connectivity within those states differed between SZs and HCs. Additionally, we identified a relationship between SZ symptom severity and the dynamics of DMN functional connectivity. We validated our results across two datasets. These results support the potential of dFC for use as a biomarker of schizophrenia and shed new light upon the relationship between schizophrenia and DMN dynamics.

scholarly journals Aberrant Dynamic Functional Connectivity of Default Mode Network in Schizophrenia and Links to Symptom Severity

2021 ◽  
Author(s):  
Mohammad S.E. Sendi ◽  
Elaheh Zendehrouh ◽  
Charles A. Ellis ◽  
Zhijia Liang ◽  
Zening Fu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Resting State ◽  
Symptom Severity ◽  
Transition Probability ◽  
Feature Selection Method ◽  
Cingulate Cortex ◽  
Anterior Cingulate ◽  
Dynamic Functional Connectivity ◽  
Default Mode

AbstractBackgroundSchizophrenia affects around 1% of the global population. Functional connectivity extracted from resting-state functional magnetic resonance imaging (rs-fMRI) has previously been used to study schizophrenia and has great potential to provide novel insights into the disorder. Some studies have shown abnormal functional connectivity in the default mode network of individuals with schizophrenia, and more recent studies have shown abnormal dynamic functional connectivity (dFC) in individuals with schizophrenia. However, DMN dFC and the link between abnormal DMN dFC and symptom severity have not been well characterized.MethodResting-state fMRI data from subjects with schizophrenia (SZ) and healthy controls (HC) across two datasets were analyzed independently. We captured seven maximally independent subnodes in the DMN by applying group independent component analysis and estimated dFC between subnode time courses using a sliding window approach. A clustering method separated the dFCs into five reoccurring brain states. A feature selection method modeled the difference between SZs and HCs using the state-specific FC features. Finally, we used the transition probability of a hidden Markov model to characterize the link between symptom severity and dFC in SZ subjects.ResultsWe found decreases in the connectivity of the anterior cingulate cortex (ACC) and increases in the connectivity between the precuneus (PCu) and the posterior cingulate cortex (PCC) (i.e., PCu/PCC) of SZ subjects. In SZ, the transition probability from a state with weaker PCu/PCC and stronger ACC connectivity to a state with stronger PCu/PCC and weaker ACC connectivity increased with symptom severity.ConclusionsTo our knowledge, this was the first study to investigate DMN dFC and its link to schizophrenia symptom severity. We identified reproducible neural states in a data-driven manner and demonstrated that the strength of connectivity within those states differed between SZs and HCs. Additionally, we identified a relationship between SZ symptom severity and the dynamics of DMN functional connectivity. We validated our results across two datasets. These results support the potential of dFC for use as a biomarker of schizophrenia and shed new light upon the relationship between schizophrenia and DMN dynamics.

Dynamic Functional Connectivity of Default Mode Network in Schizophrenia and Links to Symptom Severity

2021 ◽  
Vol 89 (9) ◽  
pp. S262-S263
Author(s):  
Mohammad S.E. Sendi ◽  
Elaheh Zendehrouh ◽  
Charles Ellis ◽  
Jessica Turner ◽  
Vince Calhoun
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Symptom Severity ◽  
Dynamic Functional Connectivity ◽  
Default Mode

scholarly journals Dynamic connectivity modulates local activity in the core regions of the default-mode network

2017 ◽  
Vol 114 (36) ◽  
pp. 9713-9718 ◽  
Author(s):  
Wei Tang ◽  
Hesheng Liu ◽  
Linda Douw ◽  
Mark A. Kramer ◽  
Uri T. Eden ◽  
...  
Keyword(s):  
Default Mode Network ◽  
Resting State ◽  
Large Scale ◽  
Cingulate Cortex ◽  
Posterior Cingulate Cortex ◽  
Anterior Cingulate ◽  
Default Mode ◽  
Local Activity ◽  
The Core ◽  
Dynamic Connectivity

Segregation and integration are distinctive features of large-scale brain activity. Although neuroimaging studies have been unraveling their neural correlates, how integration takes place over segregated modules remains elusive. Central to this problem is the mechanism by which a brain region adjusts its activity according to the influence it receives from other regions. In this study, we explore how dynamic connectivity between two regions affects the neural activity within a participating region. Combining functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) in the same group of subjects, we analyzed resting-state data from the core of the default-mode network. We observed directed influence from the posterior cingulate cortex (PCC) to the anterior cingulate cortex (ACC) in the 10-Hz range. This time-varying influence was associated with the power alteration in the ACC: strong influence corresponded with a decrease of power around 13–16 Hz and an increase of power in the lower (1–7 Hz) and higher (30–55 Hz) ends of the spectrum. We also found that the amplitude of the 30- to 55-Hz activity was coupled to the phase of the 3- to 4-Hz activity in the ACC. These results characterized the local spectral changes associated with network interactions. The specific spectral information both highlights the functional roles of PCC–ACC connectivity in the resting state and provides insights into the dynamic relationship between local activity and coupling dynamics of a network.

Amygdala and anterior cingulate resting-state functional connectivity in borderline personality disorder patients with a history of interpersonal trauma

2014 ◽  
Vol 44 (13) ◽  
pp. 2889-2901 ◽  
Author(s):  
A. Krause-Utz ◽  
I. M. Veer ◽  
S. A. R. B. Rombouts ◽  
M. Bohus ◽  
C. Schmahl ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Borderline Personality Disorder ◽  
Functional Connectivity ◽  
Personality Disorder ◽  
Default Mode Network ◽  
Resting State ◽  
Borderline Personality ◽  
Anterior Cingulate ◽  
Resting State Functional Connectivity ◽  
Default Mode

BackgroundStudies in borderline personality disorder (BPD) have consistently revealed abnormalities in fronto-limbic brain regions during emotional, somatosensory and cognitive challenges. Here we investigated changes in resting-state functional connectivity (RSFC) of three fronto-limbic core regions of specific importance to BPD.MethodFunctional magnetic resonance imaging data were acquired in 20 unmedicated female BPD patients and 17 healthy controls (HC, matched for age, sex and education) during rest. The amygdala, and the dorsal and ventral anterior cingulate cortex (ACC) were defined as seeds to investigate RSFC patterns of a medial temporal lobe network, the salience network and default mode network. The Dissociation Experience Scale (DES), a measure of trait dissociation, was additionally used as a predictor of RSFC with these seed regions.ResultsCompared with HC, BPD patients showed a trend towards increased RSFC between the amygdala and the insula, orbitofrontal cortex and putamen. Compared with controls, patients furthermore exhibited diminished negative RSFC between the dorsal ACC and posterior cingulate cortex, a core region of the default mode network, and regions of the dorsomedial prefrontal cortex. Last, increased negative RSFC between the ventral ACC and medial occipital regions was observed in BPD patients. DES scores were correlated with amygdala connectivity with the dorsolateral prefrontal cortex and fusiform gyrus.ConclusionsOur findings suggest alterations in resting-state networks associated with processing of negative emotions, encoding of salient events, and self-referential processing in individuals with BPD compared with HC. These results shed more light on the role of abnormal brain connectivity in BPD.

scholarly journals Cognitive Improvement is Correlated with Increased Dynamic Functional Connectivity of Default Mode Network by Personalized rTMS in Alzheimer's Disease

2021 ◽  
Author(s):  
Lili Wei ◽  
Jintao Wang ◽  
Yingchun Zhang ◽  
Luoyi Xu ◽  
Kehua Yang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Functional Connectivity ◽  
Default Mode Network ◽  
Present Report ◽  
Verbal Learning ◽  
Dynamic Functional Connectivity ◽  
Default Mode ◽  
Cognitive Improvement ◽  
Promising Therapeutic Approach

Abstract Background Repetitive transcranial magnetic stimulation (rTMS) is thought to be a promising therapeutic approach for Alzheimer's disease patients. Methods In the present report, a double-blind, randomized, sham-controlled rTMS trial was conducted in mild-to-moderate Alzheimer's disease patients. High-frequency rTMS was delivered to a subject-specific left lateral parietal region that demonstrated highest functional connectivity with the hippocampus using resting-state fMRI. The Mini Mental State Examination (MMSE) and Philadelphia Verbal Learning Test (PVLT) were used to evaluate patients’ cognitive functions. Results Patients receiving active rTMS treatment (n = 31) showed a significant increase in the MMSE, PVLT-Immediate recall, and PVLT-Short Delay recall scores after two weeks of rTMS treatment, whereas patients who received sham rTMS (n = 27) did not show significant changes in these measures. Dynamic functional connectivity (dFC) magnitude of the default mode network (DMN) in the active-rTMS group showed a significant increase after two weeks of rTMS treatment, and no significant changes were found in the sham-rTMS group. There was a significantly positive correlation between changes of the MMSE and changes of the dFC magnitude of DMN in the active-rTMS group, but not the sham-rTMS group. Conclusions Our findings are novel in demonstrating the feasibility and effectiveness of the fMRI-guided rTMS treatment in Alzheimer's disease patients, and DMN might play a vital role in therapeutic effectiveness of rTMS in Alzheimer’s disease. Trial registration: China National Medical Research Platform (http://114.255.48.20/login, No:MR-33-20-004217), retrospectively registered 2020-12-23.

Mediating Role of The Default Mode Network On Parental Acceptance/Warmth and Psychopathology in Youth

2021 ◽  
Author(s):  
Kaley Davis ◽  
Emily Hirsch ◽  
Dylan Gee ◽  
Margaret Andover ◽  
Amy Krain Roy
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Resting State ◽  
Parental Attitudes ◽  
Community Sample ◽  
Positive Parenting ◽  
Parental Acceptance ◽  
Resting State Functional Connectivity ◽  
Cross Sectional ◽  
Default Mode

Abstract Humans are reliant on their caregivers for an extended period of time, offering numerous opportunities for environmental factors, such as parental attitudes and behaviors, to impact brain development. The default mode network is a neural system encompassing the medial prefrontal cortex, posterior cingulate cortex, precuneus, and temporo-parietal junction, which is implicated in aspects of cognition and psychopathology. Delayed default mode network maturation in children and adolescents has been associated with greater general dimensional psychopathology, and positive parenting behaviors have been suggested to serve as protective mechanisms against atypical default mode network development. The current study aimed to extend the existing research by examining whether within- default mode network resting-state functional connectivity would mediate the relation between parental acceptance/warmth and youth psychopathology. Data from the Adolescent Brain and Cognitive Development study, which included a community sample of 9,058 children ages 9-10.9 years, were analyzed to test this prediction. Results from the analysis demonstrated a significant mediation, where greater parental acceptance/warmth predicted greater within- default mode network resting-state functional connectivity, which in turn predicted lower psychopathology. Our study provides preliminary support for the notion that positive parenting traits may reduce the risk for psychopathology in youth through their influence on the default mode network. Due to the cross-sectional nature of this study, we can only draw correlational inference; therefore, these relationships should be tested longitudinally in future investigations.

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