The role of spatial embedding in mouse brain networks constructed from diffusion tractography and tracer injections.
Connectome
Diffusion MRI
Geometric networks
Graph theory
Neural tracer
Tractography
Journal
NeuroImage
ISSN: 1095-9572
Titre abrégé: Neuroimage
Pays: United States
ID NLM: 9215515
Informations de publication
Date de publication:
01 12 2021
01 12 2021
Historique:
received:
15
04
2021
revised:
07
09
2021
accepted:
10
09
2021
pubmed:
15
9
2021
medline:
22
1
2022
entrez:
14
9
2021
Statut:
ppublish
Résumé
Diffusion MRI tractography is the only noninvasive method to measure the structural connectome in humans. However, recent validation studies have revealed limitations of modern tractography approaches, which lead to significant mistracking caused in part by local uncertainties in fiber orientations that accumulate to produce larger errors for longer streamlines. Characterizing the role of this length bias in tractography is complicated by the true underlying contribution of spatial embedding to brain topology. In this work, we compare graphs constructed with ex vivo tractography data in mice and neural tracer data from the Allen Mouse Brain Connectivity Atlas to random geometric surrogate graphs which preserve the low-order distance effects from each modality in order to quantify the role of geometry in various network properties. We find that geometry plays a substantially larger role in determining the topology of graphs produced by tractography than graphs produced by tracers. Tractography underestimates weights at long distances compared to neural tracers, which leads tractography to place network hubs close to the geometric center of the brain, as do corresponding tractography-derived random geometric surrogates, while tracer graphs place hubs further into peripheral areas of the cortex. We also explore the role of spatial embedding in modular structure, network efficiency and other topological measures in both modalities. Throughout, we compare the use of two different tractography streamline node assignment strategies and find that the overall differences between tractography approaches are small relative to the differences between tractography- and tracer-derived graphs. These analyses help quantify geometric biases inherent to tractography and promote the use of geometric benchmarking in future tractography validation efforts.
Identifiants
pubmed: 34520833
pii: S1053-8119(21)00849-1
doi: 10.1016/j.neuroimage.2021.118576
pmc: PMC8611903
mid: NIHMS1755362
pii:
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
118576Subventions
Organisme : NIMH NIH HHS
ID : U01 MH109100
Pays : United States
Organisme : NINDS NIH HHS
ID : F31 NS113571
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA014599
Pays : United States
Organisme : NIH HHS
ID : S10 OD025081
Pays : United States
Organisme : NIBIB NIH HHS
ID : R01 EB026300
Pays : United States
Organisme : NCRR NIH HHS
ID : S10 RR021039
Pays : United States
Informations de copyright
Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.
Références
Sci Rep. 2019 Sep 16;9(1):13412
pubmed: 31527782
PLoS Biol. 2016 Jul 21;14(7):e1002512
pubmed: 27441598
Proc Natl Acad Sci U S A. 2015 Aug 11;112(32):10032-7
pubmed: 26216962
Neuroimage. 2013 Oct 15;80:515-26
pubmed: 23623973
Neuroimage. 2013 Oct 15;80:14-7
pubmed: 23321152
J Magn Reson Imaging. 2021 Jun;53(6):1666-1682
pubmed: 32557893
Proc Natl Acad Sci U S A. 2014 Nov 18;111(46):16574-9
pubmed: 25368179
PLoS Comput Biol. 2016 Sep 12;12(9):e1005104
pubmed: 27617835
Neuroimage. 2012 Sep;62(3):1924-38
pubmed: 22705374
Neuroimage. 2010 Sep;52(3):1059-69
pubmed: 19819337
Neuroimage. 2015 Oct 1;119:338-51
pubmed: 26163802
Med Image Anal. 2008 Feb;12(1):26-41
pubmed: 17659998
Neuroimage. 2012 Feb 15;59(4):3976-94
pubmed: 22036682
Nature. 2014 Apr 10;508(7495):207-14
pubmed: 24695228
Nat Neurosci. 2016 Aug 26;19(9):1175-87
pubmed: 27571196
NMR Biomed. 2017 Dec;30(12):
pubmed: 28915311
Neuroimage. 2004 Nov;23(3):1176-85
pubmed: 15528117
PLoS Biol. 2009 Jul;7(7):e1000157
pubmed: 19621066
J Stat Mech. 2005 Feb 1;2005(P02001):nihpa35573
pubmed: 18159217
Netw Neurosci. 2019 Jul 01;3(3):656-673
pubmed: 31410372
Netw Neurosci. 2018 Dec 01;3(1):217-236
pubmed: 30793081
NMR Biomed. 2019 Apr;32(4):e3785
pubmed: 28945294
Neuroimage. 2016 Nov 15;142:394-406
pubmed: 27523449
Biophys J. 1994 Jan;66(1):259-67
pubmed: 8130344
Brain Struct Funct. 2018 Jul;223(6):2841-2858
pubmed: 29663135
Nat Commun. 2017 Nov 7;8(1):1349
pubmed: 29116093
Magn Reson Med. 2021 Feb;85(2):667-677
pubmed: 32783262
Magn Reson Med. 2016 Nov;76(5):1582-1593
pubmed: 26599599
J Magn Reson B. 1996 Jun;111(3):209-19
pubmed: 8661285
Sci Adv. 2020 Dec 18;6(51):
pubmed: 33355124
Neuron. 2013 Oct 2;80(1):184-97
pubmed: 24094111
PLoS Comput Biol. 2005 Sep;1(4):e42
pubmed: 16201007
Neuroimage. 2016 Jan 1;124(Pt A):379-393
pubmed: 26364864
Annu Rev Psychol. 2016;67:613-40
pubmed: 26393868
Neuroimage. 2019 Nov 15;202:116137
pubmed: 31473352
Neuroimage. 2014 Sep;98:266-78
pubmed: 24816531
Neuroimage. 2020 Nov 1;221:117201
pubmed: 32739552
Brain Connect. 2013;3(4):423-37
pubmed: 23802922
Cereb Cortex. 2015 Nov;25(11):4628-37
pubmed: 26048951
Magn Reson Med. 2012 Mar;67(3):844-55
pubmed: 22183751
Neuron. 2018 Feb 7;97(3):698-715.e10
pubmed: 29420935
Neuroimage. 2007 May 1;35(4):1459-72
pubmed: 17379540
Nat Rev Neurosci. 2012 Apr 13;13(5):336-49
pubmed: 22498897
Neuroimage. 2011 Aug 1;57(3):892-907
pubmed: 21605688
Cereb Cortex. 2014 Jan;24(1):17-36
pubmed: 23010748
Neuroimage. 2009 Jul 1;46(3):786-802
pubmed: 19195496
Phys Rev E Stat Nonlin Soft Matter Phys. 2004 Nov;70(5 Pt 2):056131
pubmed: 15600716
Neuroimage. 2019 Jan 15;185:1-11
pubmed: 30317017
Trends Cogn Sci. 2013 Dec;17(12):683-96
pubmed: 24231140
Nat Neurosci. 2015 Nov;18(11):1546-55
pubmed: 26505566
Neuroimage. 2015 Jul 15;115:202-13
pubmed: 25953631
Proc Natl Acad Sci U S A. 2015 Apr 21;112(16):E2093-101
pubmed: 25848037
Phys Rev Lett. 2001 Nov 5;87(19):198701
pubmed: 11690461