scholarly journals Effects of an Online Mind–Body Training Program on the Default Mode Network: An EEG Functional Connectivity Study

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Dasom Lee ◽  
Do-Hyung Kang ◽  
Na-hyun Ha ◽  
Chang-young Oh ◽  
Ulsoon Lee ◽  
...  
2019 ◽  
Vol 372 ◽  
pp. 112059 ◽  
Author(s):  
Mauro Adenzato ◽  
Claudio Imperatori ◽  
Rita B. Ardito ◽  
Enrico Maria Valenti ◽  
Giacomo Della Marca ◽  
...  

2019 ◽  
Vol 246 ◽  
pp. 611-618 ◽  
Author(s):  
Claudio Imperatori ◽  
Benedetto Farina ◽  
Mauro Adenzato ◽  
Enrico Maria Valenti ◽  
Cristina Murgia ◽  
...  

2021 ◽  
Author(s):  
Hannah S. Heinrichs ◽  
Frauke Beyer ◽  
Evelyn Medawar ◽  
Kristin Prehn ◽  
Jürgen Ordemann ◽  
...  

2018 ◽  
Vol 7 (6) ◽  
pp. 15
Author(s):  
Ting Su ◽  
Yong-Qiang Shu ◽  
Kang-Cheng Liu ◽  
Lei Ye ◽  
Ling-Long Chen ◽  
...  

2021 ◽  
Vol 15 ◽  
Author(s):  
Mohammad S. E. Sendi ◽  
Elaheh Zendehrouh ◽  
Charles A. Ellis ◽  
Zhijia Liang ◽  
Zening Fu ◽  
...  

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.


2021 ◽  
Author(s):  
Lili Wei ◽  
Jintao Wang ◽  
Yingchun Zhang ◽  
Luoyi Xu ◽  
Kehua Yang ◽  
...  

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.


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