Joint hub identification for brain networks by multivariate graph inference.
Brain network
Connector hub
Graph spectrum
Hub identification
Journal
Medical image analysis
ISSN: 1361-8423
Titre abrégé: Med Image Anal
Pays: Netherlands
ID NLM: 9713490
Informations de publication
Date de publication:
10 2021
10 2021
Historique:
received:
27
04
2020
revised:
01
07
2021
accepted:
02
07
2021
pubmed:
19
7
2021
medline:
24
9
2021
entrez:
18
7
2021
Statut:
ppublish
Résumé
Recent developments in neuroimaging allow us to investigate the structural and functional connectivity between brain regions in vivo. Mounting evidence suggests that hub nodes play a central role in brain communication and neural integration. Such high centrality, however, makes hub nodes particularly susceptible to pathological network alterations and the identification of hub nodes from brain networks has attracted much attention in neuroimaging. Current popular hub identification methods often work in a univariate manner, i.e., selecting the hub nodes one after another based on either heuristic of the connectivity profile at each node or predefined settings of network modules. Since the topological information of the entire network (such as network modules) is not fully utilized, current methods have limited power to identify hubs that link multiple modules (connector hubs) and are biased toward identifying hubs having many connections within the same module (provincial hubs). To address this challenge, we propose a novel multivariate hub identification method. Our method identifies connector hubs as those that partition the network into disconnected components when they are removed from the network. Furthermore, we extend our hub identification method to find the population-based hub nodes from a group of network data. We have compared our hub identification method with existing methods on both simulated and human brain network data. Our proposed method achieves more accurate and replicable discovery of hub nodes and exhibits enhanced statistical power in identifying network alterations related to neurological disorders such as Alzheimer's disease and obsessive-compulsive disorder.
Identifiants
pubmed: 34274691
pii: S1361-8415(21)00208-5
doi: 10.1016/j.media.2021.102162
pmc: PMC8453134
mid: NIHMS1725059
pii:
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
102162Subventions
Organisme : NIA NIH HHS
ID : K01 AG049089
Pays : United States
Organisme : NIA NIH HHS
ID : R21 AG059065
Pays : United States
Organisme : NIA NIH HHS
ID : R03 AG070701
Pays : United States
Organisme : NIA NIH HHS
ID : R03 AG073927
Pays : United States
Organisme : NIA NIH HHS
ID : RF1 AG068399
Pays : United States
Informations de copyright
Copyright © 2021 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Références
PLoS One. 2007 Jul 04;2(7):e597
pubmed: 17611629
Transl Psychiatry. 2017 Aug 22;7(8):e1218
pubmed: 28892073
Neuroimage. 2002 Jan;15(1):273-89
pubmed: 11771995
J Neurosci. 2008 Sep 10;28(37):9239-48
pubmed: 18784304
Proc Natl Acad Sci U S A. 2012 Dec 11;109(50):20608-13
pubmed: 23185007
Neuroimage. 2008 Nov 15;43(3):528-39
pubmed: 18786642
J Neurosci. 2010 Nov 24;30(47):15915-26
pubmed: 21106830
Neuron. 2013 Aug 21;79(4):798-813
pubmed: 23972601
Nat Commun. 2015 Apr 23;6:6868
pubmed: 25904405
Nat Rev Neurosci. 2012 Apr 13;13(5):336-49
pubmed: 22498897
Biol Psychiatry. 2013 Jan 1;73(1):24-31
pubmed: 22831979
Neuroimage Clin. 2018 Mar 16;18:849-870
pubmed: 29876270
Sci Rep. 2020 Oct 14;10(1):17320
pubmed: 33057130
PLoS One. 2007 Oct 17;2(10):e1049
pubmed: 17940613
Neuroimage. 2010 Oct 15;53(1):1-15
pubmed: 20547229
Nature. 2005 Feb 24;433(7028):895-900
pubmed: 15729348
Neuroimage Clin. 2015 May 01;8:356-66
pubmed: 26106561
Proc Natl Acad Sci U S A. 1949 Nov;35(11):652-5
pubmed: 16578320
Science. 2013 Nov 1;342(6158):1238411
pubmed: 24179229
Psychol Med. 2020 Jul;50(9):1490-1500
pubmed: 31272523
PLoS One. 2013 Jun 10;8(6):e65511
pubmed: 23935801
Brain. 2011 Jun;134(Pt 6):1635-46
pubmed: 21490054
IEEE Trans Med Imaging. 2013 Nov;32(11):2078-98
pubmed: 23864168
IEEE J Biomed Health Inform. 2017 Jul;21(4):949-955
pubmed: 27305688
Neuroinformatics. 2004;2(2):145-62
pubmed: 15319512
J Neurosci. 2009 Feb 11;29(6):1860-73
pubmed: 19211893
Proc Natl Acad Sci U S A. 2006 Jun 6;103(23):8577-82
pubmed: 16723398
Neurobiol Aging. 2008 Jan;29(1):23-30
pubmed: 17097767
Neurobiol Aging. 2013 Aug;34(8):2023-36
pubmed: 23541878
Nat Rev Neurosci. 2015 Mar;16(3):159-72
pubmed: 25697159
Biol Cybern. 2004 May;90(5):311-7
pubmed: 15221391
Nat Rev Neurosci. 2009 Mar;10(3):186-98
pubmed: 19190637
Neurobiol Aging. 2012 May;33(5):899-913
pubmed: 20724031
Cereb Cortex. 2013 Jan;23(1):127-38
pubmed: 22275481
Biol Psychiatry. 2014 Apr 15;75(8):595-605
pubmed: 24314349
J Cogn Neurosci. 2012 Jun;24(6):1275-85
pubmed: 22401285
Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Jun;71(6 Pt 2):065103
pubmed: 16089800
Neuroimage. 2010 Sep;52(3):1059-69
pubmed: 19819337
JAMA Psychiatry. 2013 Jun;70(6):619-29
pubmed: 23740050
Dialogues Clin Neurosci. 2018 Jun;20(2):111-121
pubmed: 30250388
Neuroimage. 2010 Apr 15;50(3):970-83
pubmed: 20035887
J Neurosci. 2006 Jan 4;26(1):63-72
pubmed: 16399673
Brain. 2014 Aug;137(Pt 8):2382-95
pubmed: 25057133
Trends Cogn Sci. 2013 Dec;17(12):683-96
pubmed: 24231140
Biol Psychiatry. 2014 Apr 15;75(8):606-14
pubmed: 24099506
Proc Natl Acad Sci U S A. 2014 Sep 30;111(39):14247-52
pubmed: 25225403
Neuroimage. 2013 Nov 15;82:403-15
pubmed: 23747961
PLoS One. 2010 Apr 27;5(4):e10232
pubmed: 20436911
PLoS One. 2013 Oct 30;8(10):e78293
pubmed: 24205186
Neuroimage. 2012 Aug 15;62(2):774-81
pubmed: 22248573