Inferring neural signalling directionality from undirected structural connectomes

被引:61
作者
Seguin, Caio [1 ,2 ]
Razi, Adeel [3 ,4 ,5 ]
Zalesky, Andrew [1 ,2 ,6 ]
机构
[1] Univ Melbourne, Melbourne Neuropsychiat Ctr, Melbourne, Vic 3010, Australia
[2] Melbourne Hlth, Melbourne, Vic 3010, Australia
[3] Monash Univ, Turner Inst Brain & Mental Hlth, Clayton, Vic 3800, Australia
[4] UCL, Wellcome Trust Ctr Neuroimaging, London WC1E 6BT, England
[5] NED Univ Engn & Technol, Dept Elect Engn, Karachi 75270, Sindh, Pakistan
[6] Univ Melbourne, Melbourne Sch Engn, Dept Biomed Engn, Melbourne, Vic 3010, Australia
基金
英国医学研究理事会; 澳大利亚研究理事会;
关键词
FUNCTIONAL CONNECTIVITY; BRAIN; NETWORK; ORGANIZATION; SPECIFICITY; NAVIGATION;
D O I
10.1038/s41467-019-12201-w
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Neural information flow is inherently directional. To date, investigation of directional communication in the human structural connectome has been precluded by the inability of non-invasive neuroimaging methods to resolve axonal directionality. Here, we demonstrate that decentralized measures of network communication, applied to the undirected topology and geometry of brain networks, can infer putative directions of large-scale neural signalling. We propose the concept of send-receive communication asymmetry to characterize cortical regions as senders, receivers or neutral, based on differences between their incoming and outgoing communication efficiencies. Our results reveal a send-receive cortical hierarchy that recapitulates established organizational gradients differentiating sensory-motor and multi-modal areas. We find that send-receive asymmetries are significantly associated with the directionality of effective connectivity derived from spectral dynamic causal modeling. Finally, using fruit fly, mouse and macaque connectomes, we provide further evidence suggesting that directionality of neural signalling is significantly encoded in the undirected architecture of nervous systems.
引用
收藏
页数:13
相关论文
共 72 条
[1]   Network diffusion accurately models the relationship between structural and functional brain connectivity networks [J].
Abdelnour, Farras ;
Voss, Henning U. ;
Raj, Ashish .
NEUROIMAGE, 2014, 90 :335-347
[2]  
Allard A., 2018, ARXIV180106079
[3]   Variability and reliability of effective connectivity within the core default mode network: A multi-site longitudinal spectral DCM study [J].
Almgren, Hannes ;
de Steen, Frederik Van ;
Kuehn, Simone ;
Razi, Adeel ;
Friston, Karl ;
Marinazzo, Daniele .
NEUROIMAGE, 2018, 183 :757-768
[4]   Mapping hybrid functional-structural connectivity traits in the human connectome [J].
Amico, Enrico ;
Goni, Joaquin .
NETWORK NEUROSCIENCE, 2018, 2 (03) :306-322
[5]   A spectrum of routing strategies for brain networks [J].
Avena-Koenigsberger, Andrea ;
Yan, Xiaoran ;
Kolchinsky, Artemy ;
van den Heuvel, Martijn P. ;
Hagmann, Patric ;
Sporns, Olaf .
PLOS COMPUTATIONAL BIOLOGY, 2019, 15 (03)
[6]   Communication dynamics in complex brain networks [J].
Avena-Koenigsberger, Andrea ;
Misic, Bratislav ;
Sporns, Olaf .
NATURE REVIEWS NEUROSCIENCE, 2018, 19 (01) :17-33
[7]   Path ensembles and a tradeoff between communication efficiency and resilience in the human connectome [J].
Avena-Koenigsberger, Andrea ;
Misic, Bratislav ;
Hawkins, Robert X. D. ;
Griffa, Alessandra ;
Hagmann, Patric ;
Goni, Joaquin ;
Sporns, Olaf .
BRAIN STRUCTURE & FUNCTION, 2017, 222 (01) :603-618
[8]   Studying Brain Circuit Function with Dynamic Causal Modeling for Optogenetic fMRI [J].
Bernal-Casas, David ;
Lee, Hyun Joo ;
Weitz, Andrew J. ;
Lee, Jin Hyung .
NEURON, 2017, 93 (03) :522-+
[9]   Changes in structural and functional connectivity among resting-state networks across the human lifespan [J].
Betzel, Richard F. ;
Byrge, Lisa ;
He, Ye ;
Goni, Joaquin ;
Zuo, Xi-Nian ;
Sporns, Olaf .
NEUROIMAGE, 2014, 102 :345-357
[10]   Navigability of complex networks [J].
Boguna, Marian ;
Krioukov, Dmitri ;
Claffy, K. C. .
NATURE PHYSICS, 2009, 5 (01) :74-80