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 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.

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

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 brain architectures match intrinsic functional networks and vary across domains: A study from 15000+ individuals

2019 ◽  
Author(s):  
Na Luo ◽  
Jing Sui ◽  
Anees Abrol ◽  
Jessica A. Turner ◽  
Eswar Damaraju ◽  
...  
Keyword(s):  
Individual Variability ◽  
Association Cortex ◽  
Functional Networks ◽  
Functional Domains ◽  
Network Module ◽  
Replication Cohort ◽  
Discovery Cohort ◽  
Cortical Areas ◽  
Frontoparietal Network ◽  
Structural Networks

AbstractBrain structural networks have been shown to consistently organize in functionally meaningful architectures covering the entire brain. However, to what extent brain structural architectures match the intrinsic functional networks in different functional domains remains under explored. In this study, based on independent component analysis, we revealed 45 pairs of structural-functional (S-F) component maps, distributing across 9 functional domains, in both a discovery cohort (n=6005) and a replication cohort (UK Biobank, n=9214), providing a well-match multimodal spatial map template for public use. Further network module analysis suggested that unimodal cortical areas (e.g. somatomotor and visual networks) indicate higher S-F coherence, while heteromodal association cortices, especially the frontoparietal network (FPN), exhibit more S-F divergence. Collectively, these results suggest that the expanding and maturing brain association cortex demonstrates a higher degree of changes compared to unimodal cortex, which may lead to higher inter-individual variability and lower S-F coherence.

scholarly journals Efficient Coding in the Economics of Human Brain Connectomics

2020 ◽  
Author(s):  
Dale Zhou ◽  
Christopher W. Lynn ◽  
Zaixu Cui ◽  
Rastko Ciric ◽  
Graham L. Baum ◽  
...  
Keyword(s):  
Information Transfer ◽  
Information Diffusion ◽  
Brain Regions ◽  
Compression Efficiency ◽  
Rich Club ◽  
Trade Offs ◽  
Neural Communication ◽  
Structural Path ◽  
Structural Networks ◽  
Speed Accuracy

AbstractIn systems neuroscience, most models posit that brain regions communicate information under constraints of efficiency. Yet, metabolic and information transfer efficiency across structural networks are not understood. In a large cohort of youth, we find metabolic costs associated with structural path strengths supporting information diffusion. Metabolism is balanced with the coupling of structures supporting diffusion and network modularity. To understand efficient network communication, we develop a theory specifying minimum rates of message diffusion that brain regions should transmit for an expected fidelity, and we test five predictions from the theory. We introduce compression efficiency, which quantifies differing trade-offs between lossy compression and communication fidelity in structural networks. Compression efficiency evolves with development, heightens when metabolic gradients guide diffusion, constrains network complexity, explains how rich-club hubs integrate information, and correlates with cortical areal scaling, myelination, and speed-accuracy trade-offs. Our findings elucidate how network structures and metabolic resources support efficient neural communication.

Inter-individual variation shapes the human microbiome

2019 ◽  
Vol 42 ◽  
Author(s):  
Emily F. Wissel ◽  
Leigh K. Smith
Keyword(s):  
Individual Differences ◽  
Individual Variation ◽  
Human Microbiome ◽  
Individual Variability ◽  
Microbiota Composition ◽  
Target Article ◽  
Microbiome Research

Abstract The target article suggests inter-individual variability is a weakness of microbiota-gut-brain (MGB) research, but we discuss why it is actually a strength. We comment on how accounting for individual differences can help researchers systematically understand the observed variance in microbiota composition, interpret null findings, and potentially improve the efficacy of therapeutic treatments in future clinical microbiome research.

Interpreting HVEM of muscle-cell impulse networks

1992 ◽  
Vol 50 (1) ◽  
pp. 126-127
Author(s):  
Paul DeCosta ◽  
Kyugon Cho ◽  
Stephen Shemlon ◽  
Heesung Jun ◽  
Stanley M. Dunn
Keyword(s):  
Structural Analysis ◽  
Muscle Cell ◽  
Electron Micrographs ◽  
Relative Size ◽  
Automatic Classification ◽  
Nerve Fibers ◽  
Analysis Algorithm ◽  
Structural Networks

Introduction: The analysis and interpretation of electron micrographs of cells and tissues, often requires the accurate extraction of structural networks, which either provide immediate 2D or 3D information, or from which the desired information can be inferred. The images of these structures contain lines and/or curves whose orientation, lengths, and intersections characterize the overall network.Some examples exist of studies that have been done in the analysis of networks of natural structures. In, Sebok and Roemer determine the complexity of nerve structures in an EM formed slide. Here the number of nodes that exist in the image describes how dense nerve fibers are in a particular region of the skin. Hildith proposes a network structural analysis algorithm for the automatic classification of chromosome spreads (type, relative size and orientation).

EURRECA’s Approach for Estimating Micronutrient Requirements

2011 ◽  
Vol 81 (4) ◽  
pp. 256-263 ◽  
Author(s):  
Christophe Matthys ◽  
Pieter van ‘t Veer ◽  
Lisette de Groot ◽  
Lee Hooper ◽  
Adriënne E.J.M. Cavelaars ◽  
...  
Keyword(s):  
Reference Values ◽  
Policy Decision ◽  
Individual Variability ◽  
The Body ◽  
Decision Makers ◽  
Nutrient Requirements ◽  
Factorial Approach ◽  
Dietary Reference Values ◽  
Health Policy Decision ◽  
Quantitative Integration

In Europe, micronutrient dietary reference values have been established by (inter)national committees of experts and are used by public health policy decision-makers to monitor and assess the adequacy of diets within population groups. The approaches used to derive dietary reference values (including average requirements) vary considerably across countries, and so far no evidence-based reason has been identified for this variation. Nutrient requirements are traditionally based on the minimum amount of a nutrient needed by an individual to avoid deficiency, and is defined by the body’s physiological needs. Alternatively the requirement can be defined as the intake at which health is optimal, including the prevention of chronic diet-related diseases. Both approaches are confronted with many challenges (e. g., bioavailability, inter and intra-individual variability). EURRECA has derived a transparent approach for the quantitative integration of evidence on Intake-Status-Health associations and/or Factorial approach (including bioavailability) estimates. To facilitate the derivation of dietary reference values, EURopean micronutrient RECommendations Aligned (EURRECA) is developing a process flow chart to guide nutrient requirement-setting bodies through the process of setting dietary reference values, which aims to facilitate the scientific alignment of deriving these values.

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