Dynamic functional connectivity analysis reveals decreased variability of the default-mode network in developing autistic brain

2018 ◽  
Vol 11 (11) ◽  
pp. 1479-1493 ◽  
Author(s):  
Changchun He ◽  
Yanchi Chen ◽  
Taorong Jian ◽  
Heng Chen ◽  
Xiaonan Guo ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Connectivity Analysis ◽  
Dynamic Functional Connectivity ◽  
Default Mode ◽  
Functional Connectivity Analysis

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 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.

scholarly journals Single-scale time-dependent window-sizes in sliding-window dynamic functional connectivity analysis: A validation study

NeuroImage ◽  
2020 ◽  
Vol 220 ◽  
pp. 117111
Author(s):  
Xiaowei Zhuang ◽  
Zhengshi Yang ◽  
Virendra Mishra ◽  
Karthik Sreenivasan ◽  
Charles Bernick ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Validation Study ◽  
Sliding Window ◽  
Time Dependent ◽  
Connectivity Analysis ◽  
Dynamic Functional Connectivity ◽  
Functional Connectivity Analysis ◽  
Single Scale

scholarly journals Altered Functional Integration in the Salience and Default Mode Networks in Euthymic Pediatric Bipolar Disorder

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Weifang Cao ◽  
Haoran Chen ◽  
Qing Jiao ◽  
Dong Cui ◽  
Yongxin Guo ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Functional Connectivity ◽  
Functional Integration ◽  
Angular Gyrus ◽  
Pediatric Bipolar Disorder ◽  
Healthy Controls ◽  
Connectivity Analysis ◽  
Functional Connectivity Density ◽  
Default Mode ◽  
Functional Connectivity Analysis

Accumulating studies demonstrate emotional and cognitive dysregulation in the euthymic period of pediatric bipolar disorder (PBD). However, the relative contribution of functional integration in human brain to disturbed emotion and cognitive function in the euthymic PBD patients remains unclear. In this study, 16 euthymic PBD patients and 16 healthy controls underwent resting-state functional magnetic resonance imaging. A data-driven functional connectivity analysis was used to investigate functional connectivity changes of the euthymic PBD. Compared with healthy controls, the euthymic PBD exhibited greater global functional connectivity density in the left anterior insula and lower global functional connectivity density in the right temporoparietal junction, the left angular gyrus, and the bilateral occipital lobule. A distant functional connectivity analysis demonstrated altered integration within the salience and default mode networks in euthymic PBD. Correlation analysis found that altered functional connectivity of the salience network was related to the reduced performance in the backward digit span test, and altered functional connectivity of the default mode network was related to the Young Mania Rating Scale in euthymic PBD patients. Our findings indicated that disturbed functional integration in salience and default mode networks might shed light on the physiopathology associated with emotional and cognitive dysregulation in PBD.

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
Sign in / Sign up

Export Citation Format

Share Document