Literature DB >> 26129743

The influence of construction methodology on structural brain network measures: A review.

Shouliang Qi1, Stephan Meesters2, Klaas Nicolay3, Bart M Ter Haar Romeny4, Pauly Ossenblok5.   

Abstract

Structural brain networks based on diffusion MRI and tractography show robust attributes such as small-worldness, hierarchical modularity, and rich-club organization. However, there are large discrepancies in the reports about specific network measures. It is hypothesized that these discrepancies result from the influence of construction methodology. We surveyed the methodological options and their influences on network measures. It is found that most network measures are sensitive to the scale of brain parcellation, MRI gradient schemes and orientation model, and the tractography algorithm, which is in accordance with the theoretical analysis of the small-world network model. Different network weighting schemes represent different attributes of brain networks, which makes these schemes incomparable between studies. Methodology choice depends on the specific study objectives and a clear understanding of the pros and cons of a particular methodology. Because there is no way to eliminate these influences, it seems more practical to quantify them, optimize the methodologies, and construct structural brain networks with multiple spatial resolutions, multiple edge densities, and multiple weighting schemes.
Copyright © 2015 Elsevier B.V. All rights reserved.

Keywords:  Connectivity; Diffusion MRI; Methodology; Networks; Tractography

Mesh:

Year:  2015        PMID: 26129743     DOI: 10.1016/j.jneumeth.2015.06.016

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  24 in total

1.  A network-based response feature matrix as a brain injury metric.

Authors:  Shaoju Wu; Wei Zhao; Bethany Rowson; Steven Rowson; Songbai Ji
Journal:  Biomech Model Mechanobiol       Date:  2019-11-23

2.  The structural connectome of children with traumatic brain injury.

Authors:  Marsh Königs; L W Ernest van Heurn; Roel Bakx; R Jeroen Vermeulen; J Carel Goslings; Bwee Tien Poll-The; Marleen van der Wees; Coriene E Catsman-Berrevoets; Jaap Oosterlaan; Petra J W Pouwels
Journal:  Hum Brain Mapp       Date:  2017-04-21       Impact factor: 5.038

3.  The effect of network thresholding and weighting on structural brain networks in the UK Biobank.

Authors:  Colin R Buchanan; Mark E Bastin; Stuart J Ritchie; David C Liewald; James W Madole; Elliot M Tucker-Drob; Ian J Deary; Simon R Cox
Journal:  Neuroimage       Date:  2020-01-10       Impact factor: 6.556

Review 4.  Challenges and Opportunities in Connectome Construction and Quantification in the Developing Human Fetal Brain.

Authors:  David Hunt; Manjiri Dighe; Christopher Gatenby; Colin Studholme
Journal:  Top Magn Reson Imaging       Date:  2019-10

5.  Functional Brain Connections Identify Sensorineural Hearing Loss and Predict the Outcome of Cochlear Implantation.

Authors:  Qiyuan Song; Shouliang Qi; Chaoyang Jin; Lei Yang; Wei Qian; Yi Yin; Houyu Zhao; Hui Yu
Journal:  Front Comput Neurosci       Date:  2022-03-30       Impact factor: 2.380

Review 6.  Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review.

Authors:  Fan Zhang; Alessandro Daducci; Yong He; Simona Schiavi; Caio Seguin; Robert E Smith; Chun-Hung Yeh; Tengda Zhao; Lauren J O'Donnell
Journal:  Neuroimage       Date:  2022-01-01       Impact factor: 7.400

7.  Diagnosis of early Alzheimer's disease based on dynamic high order networks.

Authors:  Baiying Lei; Shuangzhi Yu; Xin Zhao; Alejandro F Frangi; Ee-Leng Tan; Ahmed Elazab; Tianfu Wang; Shuqiang Wang
Journal:  Brain Imaging Behav       Date:  2021-02       Impact factor: 3.978

8.  Structural Brain Network: What is the Effect of LiFE Optimization of Whole Brain Tractography?

Authors:  Shouliang Qi; Stephan Meesters; Klaas Nicolay; Bart M Ter Haar Romeny; Pauly Ossenblok
Journal:  Front Comput Neurosci       Date:  2016-02-16       Impact factor: 2.380

9.  Large-scale DCMs for resting-state fMRI.

Authors:  Adeel Razi; Mohamed L Seghier; Yuan Zhou; Peter McColgan; Peter Zeidman; Hae-Jeong Park; Olaf Sporns; Geraint Rees; Karl J Friston
Journal:  Netw Neurosci       Date:  2017-10-27

10.  Growing Homophilic Networks Are Natural Navigable Small Worlds.

Authors:  Yury A Malkov; Alexander Ponomarenko
Journal:  PLoS One       Date:  2016-06-27       Impact factor: 3.240

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