scholarly journals Integrative Structural Brain Network Analysis in Diffusion Tensor Imaging

2017 ◽  
Vol 7 (6) ◽  
pp. 331-346 ◽  
Author(s):  
Moo K. Chung ◽  
Jamie L. Hanson ◽  
Nagesh Adluru ◽  
Andrew L. Alexander ◽  
Richard J. Davidson ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Network Analysis ◽  
Diffusion Tensor ◽  
Brain Network ◽  
Structural Brain Network ◽  
Structural Brain

scholarly journals Integrative Structural Brain Network Analysis In Diffusion Tensor Imaging

2017 ◽  
Author(s):  
Moo K. Chung ◽  
Jamie L. Hanson ◽  
Nagesh Adluru ◽  
Andrew L. Alexander ◽  
Richard J. Davidson ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Node Degree ◽  
Fiber Tracts ◽  
White Matter Fiber Tracts ◽  
Structural Brain Network ◽  
Structural Networks

AbstractIn diffusion tensor imaging, structural connectivity between brain regions is often measured by the number of white matter fiber tracts connecting them. Other features such as the length of tracts or fractional anisotropy (FA) are also used in measuring the strength of connectivity. In this study, we investigated the effects of incorporating the number of tracts, the tract length and FA-values into the connectivity model. Using various node-degree based graph theory features, the three connectivity models are compared. The methods are applied in characterizing structural networks between normal controls and maltreated children, who experienced maltreatment while living in post-institutional settings before being adopted by families in the US.

A structural brain network analysis for rapid eye movement sleep behavior disorder (RBD) patients

2017 ◽  
Vol 40 ◽  
pp. e183
Author(s):  
E.J. Lee ◽  
J.E. Yoon ◽  
M.-H. Lee ◽  
A. Min ◽  
Y.H. Hwang ◽  
...  
Keyword(s):  
Network Analysis ◽  
Eye Movement ◽  
Behavior Disorder ◽  
Brain Network ◽  
Rapid Eye Movement ◽  
Rapid Eye Movement Sleep ◽  
Sleep Behavior ◽  
Structural Brain Network ◽  
Structural Brain

STRUCTURAL BRAIN NETWORK ABNORMALITIES IN SUBJECTS WITH INTERNET ADDICTION

2017 ◽  
Vol 17 (07) ◽  
pp. 1740031 ◽  
Author(s):  
MIN-HEE LEE ◽  
AREUM MIN ◽  
YOON HO HWANG ◽  
DONG YOUN KIM ◽  
BONG SOO HAN ◽  
...  
Keyword(s):  
Internet Addiction ◽  
Diffusion Tensor ◽  
Brain Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Imaging Data ◽  
Structural Brain Network ◽  
Global And Local ◽  
The Impact ◽  
Structural Brain

Although problematic overuse of internet has increased, psychopathological characteristics and neurobiological mechanisms for internet addiction (IA) remain poorly understood. Therefore, it is necessary to investigate the impact of IA on the brain. The present study included 17 subjects with IA and 20 healthy subjects. We constructed the structural brain network from diffusion tensor imaging data and investigated alteration of structural connections in subjects with IA using the network analysis on the global and local levels. The subjects with IA showed increase of regional efficiency (RE) in bilateral orbitofrontal cortex (OFC) and decrease in right middle cingulate and middle temporal gyri ([Formula: see text]), whereas the global properties did not show significant changes. Young’s internet addiction test (IAT) scores and RE in left OFC showed positive correlation, and average time spent on internet per day was positively correlated with the RE in right OFC. This is the first study examining alterations of the structural brain connectivity in IA. We found that subjects with IA showed alterations of RE in some brain regions and RE was positively associated with the severity of IA and average time spent on internet per day. Therefore, RE may be a good property for IA assessment.

Structural brain network analysis of children with localization-related epilepsy

2017 ◽  
Vol 39 (8) ◽  
pp. 678-686 ◽  
Author(s):  
Kanako Takeda ◽  
Hiroshi Matsuda ◽  
Yusaku Miyamoto ◽  
Hitoshi Yamamoto
Keyword(s):  
Network Analysis ◽  
Brain Network ◽  
Structural Brain Network ◽  
Structural Brain

scholarly journals Changes of Structural Brain Network Following Repetitive Transcranial Magnetic Stimulation in Children With Bilateral Spastic Cerebral Palsy: A Diffusion Tensor Imaging Study

2021 ◽  
Vol 8 ◽  
Author(s):  
Wenxin Zhang ◽  
Shang Zhang ◽  
Min Zhu ◽  
Jian Tang ◽  
Xiaoke Zhao ◽  
...  
Keyword(s):  
Cerebral Palsy ◽  
Diffusion Tensor ◽  
Repetitive Transcranial Magnetic Stimulation ◽  
Inferior Frontal Gyrus ◽  
Brain Network ◽  
Spastic Cerebral Palsy ◽  
Cingulate Gyrus ◽  
Structural Brain Network ◽  
The Right ◽  
Structural Brain

Introduction: Bilateral spastic cerebral palsy (BSCP) is the most common subtype of cerebral palsy (CP), which is characterized by various motor and cognitive impairments, as well as emotional instability. However, the neural basis of these problems and how repetitive transcranial magnetic stimulation (rTMS) can make potential impacts on the disrupted structural brain network in BSCP remain unclear. This study was aimed to explore the topological characteristics of the structural brain network in BSCP following the treatment of rTMS.Methods: Fourteen children with BSCP underwent 4 weeks of TMS and 15 matched healthy children (HC) were enrolled. Diffusion tensor imaging (DTI) data were acquired from children with bilateral spastic cerebral palsy before treatment (CP1), children with bilateral spastic cerebral palsy following treatment (CP2) and HC. The graph theory analysis was applied to construct the structural brain network. Then nodal clustering coefficient (Ci) and shortest path length (Li) were measured and compared among groups.Results: Brain regions with significant group differences in Ci were located in the left precental gyrus, middle frontal gyrus, calcarine fissure, cuneus, lingual gyrus, postcentral gyrus, inferior parietal gyri, angular gyrus, precuneus, paracentral lobule and the right inferior frontal gyrus (triangular part), insula, posterior cingulate gyrus, precuneus, paracentral lobule, pallidum. In addition, significant differences were detected in the Li of the left precental gyrus, lingual gyrus, superior occipital gyrus, middle occipital gyrus, superior parietal gyrus, precuneus and the right median cingulate gyrus, posterior cingulate gyrus, hippocampus, putamen, thalamus. Post hoc t-test revealed that the CP2 group exhibited increased Ci in the right inferior frontal gyrus, pallidum and decreased Li in the right putamen, thalamus when compared with the CP1 group.Conclusion: Significant differences of node-level metrics were found in various brain regions of BSCP, which indicated a disruption in structural brain connectivity in BSCP. The alterations of the structural brain network provided a basis for understanding of the pathophysiological mechanisms of motor and cognitive impairments in BSCP. Moreover, the right inferior frontal gyrus, putamen, thalamus could potentially be biomarkers for predicting the efficacy of TMS.

scholarly journals Structural brain network analysis in families multiply affected with bipolar I disorder

2015 ◽  
Vol 234 (1) ◽  
pp. 44-51 ◽  
Author(s):  
Natalie J. Forde ◽  
Stefani O'Donoghue ◽  
Cathy Scanlon ◽  
Louise Emsell ◽  
Chris Chaddock ◽  
...  
Keyword(s):  
Network Analysis ◽  
Brain Network ◽  
Bipolar I Disorder ◽  
Structural Brain Network ◽  
Structural Brain
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