publication . Preprint . Other literature type . Article . 2019

Network Curvature as a Hallmark of Brain Structural Connectivity

Allen Tannenbaum; Yongxin Chen; Christophe Lenglet; Hamza Farooq; Tryphon T. Georgiou;
Open Access
  • Published: 01 Oct 2019
  • Publisher: Cold Spring Harbor Laboratory
Abstract
Although brain functionality is often remarkably robust to lesions and other insults, it may be fragile when these take place in specific locations. Previous attempts to quantify robustness and fragility sought to understand how the functional connectivity of brain networks is affected by structural changes, using either model-based predictions or empirical studies of the effects of lesions. We advance a geometric viewpoint relying on a notion of network curvature, the so-called Ollivier-Ricci curvature. This approach has been proposed to assess financial market robustness and to differentiate biological networks of cancer cells from healthy ones. Here, we apply...
Subjects
free text keywords: General Biochemistry, Genetics and Molecular Biology, General Physics and Astronomy, General Chemistry, Science, Q, Article, Magnetic resonance imaging, Computational neuroscience, Network models, Applied mathematics, Curvature, Biological network, Disease, Neuroscience, Deep brain stimulation, medicine.medical_treatment, medicine, Network topology, Computer science, Robustness (computer science), Artificial intelligence, business.industry, business, Autism, medicine.disease, Cluster analysis, Empirical research, Functional connectivity, Autism spectrum disorder, Healthy subjects, Mri studies
Funded by
NIH| SILICON GRAPHICS PRISM EXTREME 128P/1TB
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1S10RR023043-01
  • Funding stream: NATIONAL CENTER FOR RESEARCH RESOURCES
,
NSF| Theory and Techniques for Controlling the Collective Behavior of Dynamical Systems under Stochastic Uncertainty, NIH| Neuroimaging Analysis Center (NAC)
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5P41EB015902-20
  • Funding stream: NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING
,
NIH| Center for Functional Imaging Technologies
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5P41EB015896-18
  • Funding stream: NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING
,
NIH| A Storage Area Network for Structural and Functional Image Analysis
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1S10RR023401-01A2
  • Funding stream: NATIONAL CENTER FOR RESEARCH RESOURCES
61 references, page 1 of 5

[1] O. Sporns, G. Tononi, and R. Kötter, “The human connectome: A structural description of the human brain,” PLOS Computational Biology, vol. 1, 09 2005. [OpenAIRE]

[2] O. Sporns, “The human connectome: a complex network,” Annals of the New York Academy of Sciences, vol. 1224, no. 1, pp. 109-125, 2011.

[3] M. F. Glasser, S. M. Smith, D. S. Marcus, J. L. R. Andersson, E. J. Auerbach, T. E. J. Behrens, T. S. Coalson, M. P. Harms, M. Jenkinson, S. Moeller, E. C. Robinson, S. N. Sotiropoulos, J. Xu, E. Yacoub, K. Ugurbil, and D. C. Van Essen, “The human connectome project's neuroimaging approach,” Nature Neuroscience, vol. 19, no. 9, pp. 1175-1187, 2016.

[4] D. V. Essen, K. Ugurbil, E. Auerbach, D. Barch, T. Behrens, R. Bucholz, A. Chang, L. Chen, M. Corbetta, S. Curtiss, S. D. Penna, D. Feinberg, M. Glasser, N. Harel, A. Heath, L. LarsonPrior, D. Marcus, G. Michalareas, S. Moeller, R. Oostenveld, S. Petersen, F. Prior, B. Schlaggar, S. Smith, A. Snyder, J. Xu, and E. Yacoub, “The human connectome project: A data acquisition perspective,” NeuroImage, vol. 62, no. 4, pp. 2222 - 2231, 2012. [OpenAIRE]

[5] J. A. McNab, B. L. Edlow, T. Witzel, S. Y. Huang, H. Bhat, K. Heberlein, T. Feiweier, K. Liu, B. Keil, J. Cohen-Adad, M. D. Tisdall, R. D. Folkerth, H. C. Kinney, and L. L. Wald, “The human connectome project and beyond: Initial applications of 300mt/m gradients,” NeuroImage, vol. 80, pp. 234 - 245, 2013. Mapping the Connectome. [OpenAIRE]

[6] Q. Fan, T. Witzel, A. Nummenmaa, K. R. V. Dijk, J. D. V. Horn, M. K. Drews, L. H. Somerville, M. A. Sheridan, R. M. Santillana, J. Snyder, T. Hedden, E. E. Shaw, M. O. Hollinshead, V. Renvall, R. Zanzonico, B. Keil, S. Cauley, J. R. Polimeni, D. Tisdall, R. L. Buckner, V. J. Wedeen, L. L. Wald, A. W. Toga, and B. R. Rosen, “Mgh-usc human connectome project datasets with ultra-high b-value diffusion mri,” NeuroImage, vol. 124, pp. 1108 - 1114, 2016. Sharing the wealth: Brain Imaging Repositories in 2015. [OpenAIRE]

[7] S. N. Sotiropoulos, S. Jbabdi, J. Xu, J. L. Andersson, S. Moeller, E. J. Auerbach, M. F. Glasser, M. Hernandez, G. Sapiro, M. Jenkinson, D. A. Feinberg, E. Yacoub, C. Lenglet, D. C. V. Essen, K. Ugurbil, and T. E. Behrens, “Advances in diffusion {MRI} acquisition and processing in the human connectome project,” NeuroImage, vol. 80, pp. 125 - 143, 2013. Mapping the Connectome.

[8] A. Vu, E. Auerbach, C. Lenglet, S. Moeller, S. Sotiropoulos, S. Jbabdi, J. Andersson, E. Yacoub, and K. Ugurbil, “High resolution whole brain diffusion imaging at 7t for the human connectome project,” NeuroImage, vol. 122, pp. 318 - 331, 2015.

[9] K. Setsompop, R. Kimmlingen, E. Eberlein, T. Witzel, J. Cohen-Adad, J. McNab, B. Keil, M. Tisdall, P. Hoecht, P. Dietz, S. Cauley, V. Tountcheva, V. Matschl, V. Lenz, K. Heberlein, A. Potthast, H. Thein, J. V. Horn, A. Toga, F. Schmitt, D. Lehne, B. Rosen, V. Wedeen, and L. Wald, “Pushing the limits of in vivo diffusion mri for the human connectome project,” NeuroImage, vol. 80, pp. 220 - 233, 2013. Mapping the Connectome.

[10] O. Sporns, Networks of the Brain. The MIT Press, 1st ed., 2010.

[11] K. J. Friston, “Functional and effective connectivity in neuroimaging: A synthesis,” Human Brain Mapping, vol. 2, no. 1-2, pp. 56-78, 1994. [OpenAIRE]

[12] A. Zalesky, A. Fornito, I. H. Harding, L. Cocchi, M. Yücel, C. Pantelis, and E. T. Bullmore, “Whole-brain anatomical networks: Does the choice of nodes matter?,” NeuroImage, vol. 50, no. 3, pp. 970 - 983, 2010.

[13] Z. Yao, B. Hu, Y. Xie, P. Moore, and J. Zheng, “A review of structural and functional brain networks: small world and atlas,” Brain Informatics, vol. 2, no. 1, pp. 45-52, 2015. [OpenAIRE]

[14] J. Meier, P. Tewarie, A. Hillebrand, L. Douw, B. W. van Dijk, S. M. Stufflebeam, and P. Van Mieghem, “A mapping between structural and functional brain networks,” Brain Connectivity, vol. 6, no. 4, pp. 298-311, 2016.

[15] E. T. Bullmore and O. Sporns, “The economy of brain network organization,” Nature Reviews Neuroscience, vol. 13, no. 5, pp. 336-349, 2012. [OpenAIRE]

61 references, page 1 of 5
Abstract
Although brain functionality is often remarkably robust to lesions and other insults, it may be fragile when these take place in specific locations. Previous attempts to quantify robustness and fragility sought to understand how the functional connectivity of brain networks is affected by structural changes, using either model-based predictions or empirical studies of the effects of lesions. We advance a geometric viewpoint relying on a notion of network curvature, the so-called Ollivier-Ricci curvature. This approach has been proposed to assess financial market robustness and to differentiate biological networks of cancer cells from healthy ones. Here, we apply...
Subjects
free text keywords: General Biochemistry, Genetics and Molecular Biology, General Physics and Astronomy, General Chemistry, Science, Q, Article, Magnetic resonance imaging, Computational neuroscience, Network models, Applied mathematics, Curvature, Biological network, Disease, Neuroscience, Deep brain stimulation, medicine.medical_treatment, medicine, Network topology, Computer science, Robustness (computer science), Artificial intelligence, business.industry, business, Autism, medicine.disease, Cluster analysis, Empirical research, Functional connectivity, Autism spectrum disorder, Healthy subjects, Mri studies
Funded by
NIH| SILICON GRAPHICS PRISM EXTREME 128P/1TB
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1S10RR023043-01
  • Funding stream: NATIONAL CENTER FOR RESEARCH RESOURCES
,
NSF| Theory and Techniques for Controlling the Collective Behavior of Dynamical Systems under Stochastic Uncertainty, NIH| Neuroimaging Analysis Center (NAC)
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5P41EB015902-20
  • Funding stream: NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING
,
NIH| Center for Functional Imaging Technologies
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5P41EB015896-18
  • Funding stream: NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING
,
NIH| A Storage Area Network for Structural and Functional Image Analysis
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1S10RR023401-01A2
  • Funding stream: NATIONAL CENTER FOR RESEARCH RESOURCES
61 references, page 1 of 5

[1] O. Sporns, G. Tononi, and R. Kötter, “The human connectome: A structural description of the human brain,” PLOS Computational Biology, vol. 1, 09 2005. [OpenAIRE]

[2] O. Sporns, “The human connectome: a complex network,” Annals of the New York Academy of Sciences, vol. 1224, no. 1, pp. 109-125, 2011.

[3] M. F. Glasser, S. M. Smith, D. S. Marcus, J. L. R. Andersson, E. J. Auerbach, T. E. J. Behrens, T. S. Coalson, M. P. Harms, M. Jenkinson, S. Moeller, E. C. Robinson, S. N. Sotiropoulos, J. Xu, E. Yacoub, K. Ugurbil, and D. C. Van Essen, “The human connectome project's neuroimaging approach,” Nature Neuroscience, vol. 19, no. 9, pp. 1175-1187, 2016.

[4] D. V. Essen, K. Ugurbil, E. Auerbach, D. Barch, T. Behrens, R. Bucholz, A. Chang, L. Chen, M. Corbetta, S. Curtiss, S. D. Penna, D. Feinberg, M. Glasser, N. Harel, A. Heath, L. LarsonPrior, D. Marcus, G. Michalareas, S. Moeller, R. Oostenveld, S. Petersen, F. Prior, B. Schlaggar, S. Smith, A. Snyder, J. Xu, and E. Yacoub, “The human connectome project: A data acquisition perspective,” NeuroImage, vol. 62, no. 4, pp. 2222 - 2231, 2012. [OpenAIRE]

[5] J. A. McNab, B. L. Edlow, T. Witzel, S. Y. Huang, H. Bhat, K. Heberlein, T. Feiweier, K. Liu, B. Keil, J. Cohen-Adad, M. D. Tisdall, R. D. Folkerth, H. C. Kinney, and L. L. Wald, “The human connectome project and beyond: Initial applications of 300mt/m gradients,” NeuroImage, vol. 80, pp. 234 - 245, 2013. Mapping the Connectome. [OpenAIRE]

[6] Q. Fan, T. Witzel, A. Nummenmaa, K. R. V. Dijk, J. D. V. Horn, M. K. Drews, L. H. Somerville, M. A. Sheridan, R. M. Santillana, J. Snyder, T. Hedden, E. E. Shaw, M. O. Hollinshead, V. Renvall, R. Zanzonico, B. Keil, S. Cauley, J. R. Polimeni, D. Tisdall, R. L. Buckner, V. J. Wedeen, L. L. Wald, A. W. Toga, and B. R. Rosen, “Mgh-usc human connectome project datasets with ultra-high b-value diffusion mri,” NeuroImage, vol. 124, pp. 1108 - 1114, 2016. Sharing the wealth: Brain Imaging Repositories in 2015. [OpenAIRE]

[7] S. N. Sotiropoulos, S. Jbabdi, J. Xu, J. L. Andersson, S. Moeller, E. J. Auerbach, M. F. Glasser, M. Hernandez, G. Sapiro, M. Jenkinson, D. A. Feinberg, E. Yacoub, C. Lenglet, D. C. V. Essen, K. Ugurbil, and T. E. Behrens, “Advances in diffusion {MRI} acquisition and processing in the human connectome project,” NeuroImage, vol. 80, pp. 125 - 143, 2013. Mapping the Connectome.

[8] A. Vu, E. Auerbach, C. Lenglet, S. Moeller, S. Sotiropoulos, S. Jbabdi, J. Andersson, E. Yacoub, and K. Ugurbil, “High resolution whole brain diffusion imaging at 7t for the human connectome project,” NeuroImage, vol. 122, pp. 318 - 331, 2015.

[9] K. Setsompop, R. Kimmlingen, E. Eberlein, T. Witzel, J. Cohen-Adad, J. McNab, B. Keil, M. Tisdall, P. Hoecht, P. Dietz, S. Cauley, V. Tountcheva, V. Matschl, V. Lenz, K. Heberlein, A. Potthast, H. Thein, J. V. Horn, A. Toga, F. Schmitt, D. Lehne, B. Rosen, V. Wedeen, and L. Wald, “Pushing the limits of in vivo diffusion mri for the human connectome project,” NeuroImage, vol. 80, pp. 220 - 233, 2013. Mapping the Connectome.

[10] O. Sporns, Networks of the Brain. The MIT Press, 1st ed., 2010.

[11] K. J. Friston, “Functional and effective connectivity in neuroimaging: A synthesis,” Human Brain Mapping, vol. 2, no. 1-2, pp. 56-78, 1994. [OpenAIRE]

[12] A. Zalesky, A. Fornito, I. H. Harding, L. Cocchi, M. Yücel, C. Pantelis, and E. T. Bullmore, “Whole-brain anatomical networks: Does the choice of nodes matter?,” NeuroImage, vol. 50, no. 3, pp. 970 - 983, 2010.

[13] Z. Yao, B. Hu, Y. Xie, P. Moore, and J. Zheng, “A review of structural and functional brain networks: small world and atlas,” Brain Informatics, vol. 2, no. 1, pp. 45-52, 2015. [OpenAIRE]

[14] J. Meier, P. Tewarie, A. Hillebrand, L. Douw, B. W. van Dijk, S. M. Stufflebeam, and P. Van Mieghem, “A mapping between structural and functional brain networks,” Brain Connectivity, vol. 6, no. 4, pp. 298-311, 2016.

[15] E. T. Bullmore and O. Sporns, “The economy of brain network organization,” Nature Reviews Neuroscience, vol. 13, no. 5, pp. 336-349, 2012. [OpenAIRE]

61 references, page 1 of 5
Any information missing or wrong?Report an Issue