Brain functional network alterations caused by a strong desire to void in healthy adults: a graph theory analysis study

2020 ◽  
Vol 39 (7) ◽  
pp. 1966-1976
Author(s):  
Dongqing Pang ◽  
Yi Gao ◽  
Limin Liao ◽  
Xiaoqian Ying
Keyword(s):  
Graph Theory ◽  
Healthy Adults ◽  
Functional Network ◽  
Theory Analysis ◽  
Analysis Study ◽  
Brain Functional Network ◽  
Graph Theory Analysis

Abnormal brain white matter network in young smokers: a graph theory analysis study

2017 ◽  
Vol 12 (2) ◽  
pp. 345-356 ◽  
Author(s):  
Yajuan Zhang ◽  
Min Li ◽  
Ruonan Wang ◽  
Yanzhi Bi ◽  
Yangding Li ◽  
...  
Keyword(s):  
Graph Theory ◽  
White Matter ◽  
Theory Analysis ◽  
Analysis Study ◽  
Brain White Matter ◽  
Young Smokers ◽  
Graph Theory Analysis ◽  
Abnormal Brain

scholarly journals Altered Functional Network in Infants With Profound Bilateral Congenital Sensorineural Hearing Loss: A Graph Theory Analysis

2022 ◽  
Vol 15 ◽  
Author(s):  
Wenzhuo Cui ◽  
Shanshan Wang ◽  
Boyu Chen ◽  
Guoguang Fan
Keyword(s):  
Hearing Loss ◽  
Graph Theory ◽  
Functional Connectivity ◽  
Sensorineural Hearing Loss ◽  
Small World ◽  
Normal Hearing ◽  
Functional Network ◽  
Theory Analysis ◽  
Functional Reorganization ◽  
Graph Theory Analysis

Functional magnetic resonance imaging (fMRI) studies have suggested that there is a functional reorganization of brain areas in patients with sensorineural hearing loss (SNHL). Recently, graph theory analysis has brought a new understanding of the functional connectome and topological features in central neural system diseases. However, little is known about the functional network topology changes in SNHL patients, especially in infants. In this study, 34 infants with profound bilateral congenital SNHL and 28 infants with normal hearing aged 11–36 months were recruited. No difference was found in small-world parameters and network efficiency parameters. Differences in global and nodal topologic organization, hub distribution, and whole-brain functional connectivity were explored using graph theory analysis. Both normal-hearing infants and SNHL infants exhibited small-world topology. Furthermore, the SNHL group showed a decreased nodal degree in the bilateral thalamus. Six hubs in the SNHL group and seven hubs in the normal-hearing group were identified. The left middle temporal gyrus was a hub only in the SNHL group, while the right parahippocampal gyrus and bilateral temporal pole were hubs only in the normal-hearing group. Functional connectivity between auditory regions and motor regions, between auditory regions and default-mode-network (DMN) regions, and within DMN regions was found to be decreased in the SNHL group. These results indicate a functional reorganization of brain functional networks as a result of hearing loss. This study provides evidence that functional reorganization occurs in the early stage of life in infants with profound bilateral congenital SNHL from the perspective of complex networks.

scholarly journals Dynamic Network Connectivity Reveals Markers of Response to Deep Brain Stimulation in Parkinson’s Disease

2021 ◽  
Vol 15 ◽  
Author(s):  
Chengyuan Wu ◽  
Caio Matias ◽  
Thomas Foltynie ◽  
Patricia Limousin ◽  
Ludvic Zrinzo ◽  
...  
Keyword(s):  
Graph Theory ◽  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Theory Analysis ◽  
Whole Brain ◽  
Network Properties ◽  
Brain States ◽  
Graph Theory Analysis ◽  
Stn Dbs ◽  
Deep Brain

Background: Neuronal loss in Parkinson’s Disease (PD) leads to widespread neural network dysfunction. While graph theory allows for analysis of whole brain networks, patterns of functional connectivity (FC) associated with motor response to deep brain stimulation of the subthalamic nucleus (STN-DBS) have yet to be explored.Objective/Hypothesis: To investigate the distributed network properties associated with STN-DBS in patients with advanced PD.Methods: Eighteen patients underwent 3-Tesla resting state functional MRI (rs-fMRI) prior to STN-DBS. Improvement in UPDRS-III scores following STN-DBS were assessed 1 year after implantation. Independent component analysis (ICA) was applied to extract spatially independent components (ICs) from the rs-fMRI. FC between ICs was calculated across the entire time series and for dynamic brain states. Graph theory analysis was performed to investigate whole brain network topography in static and dynamic states.Results: Dynamic analysis identified two unique brain states: a relative hypoconnected state and a relative hyperconnected state. Time spent in a state, dwell time, and number of transitions were not correlated with DBS response. There were no significant FC findings, but graph theory analysis demonstrated significant relationships with STN-DBS response only during the hypoconnected state – STN-DBS was negatively correlated with network assortativity.Conclusion: Given the widespread effects of dopamine depletion in PD, analysis of whole brain networks is critical to our understanding of the pathophysiology of this disease. Only by leveraging graph theoretical analysis of dynamic FC were we able to isolate a hypoconnected brain state that contained distinct network properties associated with the clinical effects of STN-DBS.

scholarly journals Functional neural networks of honesty and dishonesty in children: Evidence from graph theory analysis

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Xiao Pan Ding ◽  
Si Jia Wu ◽  
Jiangang Liu ◽  
Genyue Fu ◽  
Kang Lee
Keyword(s):  
Neural Networks ◽  
Graph Theory ◽  
Theory Analysis ◽  
Graph Theory Analysis
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