scholarly journals Effect of Multishell Diffusion MRI Acquisition Strategy and Parcellation Scale on Rich-Club Organization of Human Brain Structural Networks

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 970
Author(s):  
Maedeh Khalilian ◽  
Kamran Kazemi ◽  
Mahshid Fouladivanda ◽  
Malek Makki ◽  
Mohammad Sadegh Helfroush ◽  
...  
Keyword(s):  
Human Brain ◽  
Clustering Coefficient ◽  
Quality Data ◽  
B Values ◽  
Rich Club ◽  
Global Efficiency ◽  
Acquisition Strategy ◽  
The Rich ◽  
Structural Networks ◽  
Single Shell

The majority of network studies of human brain structural connectivity are based on single-shell diffusion-weighted imaging (DWI) data. Recent advances in imaging hardware and software capabilities have made it possible to acquire multishell (b-values) high-quality data required for better characterization of white-matter crossing-fiber microstructures. The purpose of this study was to investigate the extent to which brain structural organization and network topology are affected by the choice of diffusion magnetic resonance imaging (MRI) acquisition strategy and parcellation scale. We performed graph-theoretical network analysis using DWI data from 35 Human Connectome Project subjects. Our study compared four single-shell (b = 1000, 3000, 5000, 10,000 s/mm2) and multishell sampling schemes and six parcellation scales (68, 200, 400, 600, 800, 1000 nodes) using five graph metrics, including small-worldness, clustering coefficient, characteristic path length, modularity and global efficiency. Rich-club analysis was also performed to explore the rich-club organization of brain structural networks. Our results showed that the parcellation scale and imaging protocol have significant effects on the network attributes, with the parcellation scale having a substantially larger effect. Regardless of the parcellation scale, the brain structural networks exhibited a rich-club organization with similar cortical distributions across the parcellation scales involving at least 400 nodes. Compared to single b-value diffusion acquisitions, the deterministic tractography using multishell diffusion imaging data consisting of shells with b-values higher than 5000 s/mm2 resulted in significantly improved fiber-tracking results at the locations where fiber bundles cross each other. Brain structural networks constructed using the multishell acquisition scheme including high b-values also exhibited significantly shorter characteristic path lengths, higher global efficiency and lower modularity. Our results showed that both parcellation scale and sampling protocol can significantly impact the rich-club organization of brain structural networks. Therefore, caution should be taken concerning the reproducibility of connectivity results with regard to the parcellation scale and sampling scheme.

Abnormal Rich Club Organization in Hemispheric White Matter Networks of ADHD

2019 ◽  
pp. 108705471989288
Author(s):  
Dandan Li ◽  
Xiaohong Cui ◽  
Ting Yan ◽  
Bo Liu ◽  
Hui Zhang ◽  
...  
Keyword(s):  
White Matter ◽  
Diffusion Tensor ◽  
Brain Network ◽  
Rich Club ◽  
The Rich ◽  
Structural Networks ◽  
Network Studies ◽  
Insight Into ◽  
Normal Controls ◽  
Diffusion Tensor Imaging Dti

Objective: Brain network studies have revealed abnormal topology asymmetry of white matter (WM) in ADHD. Recently, rich club organization was proposed to be a key feature of brain network topology. However, abnormalities in the rich club organization of hemispheric WM networks in ADHD remain unclear. Method: Forty ADHD patients and 51 normal controls participated in this study. Structural networks were reconstructed based on diffusion tensor imaging (DTI) and analyzed with graph theory. Results: The two groups exhibited different patterns of asymmetry in connectivity measures of rich club connections. ADHD patients showed more feeder connections than normal controls. Reduced rightward asymmetry was observed in connectivity measures of local connections involving several peripheral regions of the ADHD patients. In addition, abnormal regional asymmetry scores were associated with ADHD symptoms. Conclusion: The topological changes in rich club organization provide a novel insight into the alteration of WM connections in ADHD.

Hemisphere and Gender Differences in the Rich-Club Organization of Structural Networks

2019 ◽  
Vol 29 (11) ◽  
pp. 4889-4901 ◽  
Author(s):  
Bin Wang ◽  
Qionghui Zhan ◽  
Ting Yan ◽  
Sumaira Imtiaz ◽  
Jie Xiang ◽  
...  
Keyword(s):  
Gender Differences ◽  
Cognitive Control ◽  
Spatial Attention ◽  
Visual Processing ◽  
Gender Effects ◽  
Rich Club ◽  
The Rich ◽  
And Gender ◽  
Structural Networks ◽  
Peripheral Regions

AbstractStructural and functional differences in brain hemispheric asymmetry have been well documented between female and male adults. However, potential differences in the connectivity patterns of the rich-club organization of hemispheric structural networks in females and males remain to be determined. In this study, diffusion tensor imaging was used to construct hemispheric structural networks in healthy subjects, and graph theoretical analysis approaches were applied to quantify hemisphere and gender differences in rich-club organization. The results showed that rich-club organization was consistently observed in both hemispheres of female and male adults. Moreover, a reduced level of connectivity was found in the left hemisphere. Notably, rightward asymmetries were mainly observed in feeder and local connections among one hub region and peripheral regions, many of which are implicated in visual processing and spatial attention functions. Additionally, significant gender differences were revealed in the rich-club, feeder, and local connections in rich-club organization. These gender-related hub and peripheral regions are involved in emotional, sensory, and cognitive control functions. The topological changes in rich-club organization provide novel insight into the hemisphere and gender effects on white matter connections and underlie a potential network mechanism of hemisphere- and gender-based differences in visual processing, spatial attention and cognitive control.

scholarly journals Structural network maturation of the preterm human brain

2017 ◽  
Author(s):  
Tengda Zhao ◽  
Virendra Mishra ◽  
Tina Jeon ◽  
Minhui Ouyang ◽  
Qinmu Peng ◽  
...  
Keyword(s):  
Human Brain ◽  
Large Scale ◽  
Structural Connectivity ◽  
Rich Club ◽  
Brain Connectome ◽  
Brain Circuits ◽  
Edge Strength ◽  
The Rich ◽  
Preterm Born ◽  
The Brain

AbstractDuring the 3rd trimester, large-scale of neural circuits are formed in the human brain, resulting in the adult-like brain networks at birth. However, how the brain circuits develop into a highly efficient and segregated connectome during this period is unknown. We hypothesized that faster increases of connectivity efficiency and strength at the brain hubs and rich-club are critical for emergence of an efficient and segregated brain connectome. Here, using high resolution diffusion MRI of 77 preterm-born and term-born neonates scanned at 31-42 postmenstrual weeks (PMW), we constructed the structural connectivity matrices and performed graph-theory-based analyses. We found faster increases of nodal efficiency mainly at the brain hubs, distributed in primary sensorimotor regions, superior-middle frontal and posterior cingulate gyrus during 31-42PMW. The rich-club and within-module connections were characterized by higher rates of edge strength increases. Edge strength of short-range connections increased faster than that of long-range connections. The nodal efficiencies of the hubs predicted individual postmenstrual ages more accurately than those of non-hubs. Collectively, these findings revealed regionally differentiated maturation in the baby brain structural connectome and more rapid increases of the hub and rich-club connections, which underlie network segregation and differentiated brain function emergence.

Disrupted rich-club organization of brain structural networks in Parkinson’s disease

2021 ◽  
Author(s):  
Tiantian Liu ◽  
Yan Yan ◽  
Jing Ai ◽  
Duanduan Chen ◽  
Jinglong Wu ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Rich Club ◽  
Structural Networks

scholarly journals Identification of key regulators in prostate cancer from gene expression datasets of patients

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Irengbam Rocky Mangangcha ◽  
Md. Zubbair Malik ◽  
Ömer Küçük ◽  
Shakir Ali ◽  
R. K. Brojen Singh
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Regulatory Pathways ◽  
Scale Free ◽  
Topological Parameters ◽  
Rich Club ◽  
Self Organized ◽  
Mutational Status ◽  
Interactome Network ◽  
The Rich

Abstract Identification of key regulators and regulatory pathways is an important step in the discovery of genes involved in cancer. Here, we propose a method to identify key regulators in prostate cancer (PCa) from a network constructed from gene expression datasets of PCa patients. Overexpressed genes were identified using BioXpress, having a mutational status according to COSMIC, followed by the construction of PCa Interactome network using the curated genes. The topological parameters of the network exhibited power law nature indicating hierarchical scale-free properties and five levels of organization. Highest degree hubs (k ≥ 65) were selected from the PCa network, traced, and 19 of them was identified as novel key regulators, as they participated at all network levels serving as backbone. Of the 19 hubs, some have been reported in literature to be associated with PCa and other cancers. Based on participation coefficient values most of these are connector or kinless hubs suggesting significant roles in modular linkage. The observation of non-monotonicity in the rich club formation suggested the importance of intermediate hubs in network integration, and they may play crucial roles in network stabilization. The network was self-organized as evident from fractal nature in topological parameters of it and lacked a central control mechanism.

scholarly journals Rich-club organization of the newborn human brain

2014 ◽  
Vol 111 (20) ◽  
pp. 7456-7461 ◽  
Author(s):  
G. Ball ◽  
P. Aljabar ◽  
S. Zebari ◽  
N. Tusor ◽  
T. Arichi ◽  
...  
Keyword(s):  
Human Brain ◽  
Rich Club

scholarly journals Scale-Free Networks with the Same Degree Distribution: Different Structural Properties

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
José H. H. Grisi-Filho ◽  
Raul Ossada ◽  
Fernando Ferreira ◽  
Marcos Amaku
Keyword(s):  
Structural Properties ◽  
Degree Distribution ◽  
Pearson Correlation ◽  
Clustering Coefficient ◽  
The Other ◽  
Scale Free ◽  
Component Size ◽  
Global Efficiency ◽  
Nearest Neighbours ◽  
Scale Free Networks

We have analysed some structural properties of scale-free networks with the same degree distribution. Departing from a degree distribution obtained from the Barabási-Albert (BA) algorithm, networks were generated using four additional different algorithms (Molloy-Reed, Kalisky, and two new models named A and B) besides the BA algorithm itself. For each network, we have calculated the following structural measures: average degree of the nearest neighbours, central point dominance, clustering coefficient, the Pearson correlation coefficient, and global efficiency. We found that different networks with the same degree distribution may have distinct structural properties. In particular, model B generates decentralized networks with a larger number of components, a smaller giant component size, and a low global efficiency when compared to the other algorithms, especially compared to the centralized BA networks that have all vertices in a single component, with a medium to high global efficiency. The other three models generate networks with intermediate characteristics between B and BA models. A consequence of this finding is that the dynamics of different phenomena on these networks may differ considerably.

scholarly journals Individual variability in the anatomical distribution of nodes participating in rich club structural networks

2015 ◽  
Vol 9 ◽  
Author(s):  
Madison Kocher ◽  
Ezequiel Gleichgerrcht ◽  
Travis Nesland ◽  
Chris Rorden ◽  
Julius Fridriksson ◽  
...  
Keyword(s):  
Individual Variability ◽  
Anatomical Distribution ◽  
Rich Club ◽  
Structural Networks

scholarly journals The Complexity of Urban CO2 Emission Network: An Exploration of the Yangtze River Middle Reaches Megalopolis, China

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Zuo Zhang ◽  
Zhe Wang ◽  
Wei Zhang ◽  
Yanzhong Liu ◽  
Zhi Li ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Co2 Emission ◽  
Yangtze River ◽  
Urban Agglomeration ◽  
The Yangtze River ◽  
Low Carbon ◽  
Rich Club ◽  
Production And Consumption ◽  
Structural Equivalence ◽  
The Rich

With their focus on human production and consumption activities, cities incur massive energy consumption and CO2 emissions. An intercity connection is a typical complex system in which the interaction between cities is crucial for developing low-carbon outputs within the urban agglomeration. This paper presents the construction of the CO2 emission network of an urban agglomeration in the Yangtze River middle reaches megalopolis, based on the gravity model. Combined with social network analysis (SNA), a multilevel analysis framework is proposed to deal with the complexity, spatiality, and visualization of the CO2 emission network with reference to the network features, structural equivalence, and the rich-club phenomenon. The following results emerged: firstly, the spatial structure of the CO2 emissions was characterized by low robustness and compactness, indicating disunity among the studied cities. Secondly, there was found to be a strong correlation between regionalism and intercity connections, with geographically close cities playing a similar role in the network. Thirdly, the “rich-club” cities, including Wuhan, Changsha, Xiaogan, and Zhuzhou, dominated the connections, covering more than 87.1% of the network in the Yangtze River Middle Reaches Megalopolis.

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