A weighted communicability measure applied to complex brain networks

Journal of the Royal Society Interface

Volumn 6, Issue 33, 2009, Pages 411-414

  Crofts, Jonathan J ^a   Higham, Desmond J ^a  

^a UNIVERSITY OF STRATHCLYDE   (United Kingdom)

Author keywords

Matrix functions; Network science; Neuroscience; Unsupervised classification

Indexed keywords

FEATURE EXTRACTION; FUNCTION EVALUATION; MAGNETIC RESONANCE IMAGING;

ADJACENCY MATRICES; BRAIN NETWORKS; CONNECTIVITY STRUCTURES; CORTICAL NETWORK; GLOBAL CONNECTIVITY; HUMAN BRAIN; HUMAN CENTRAL NERVOUS SYSTEMS; IN-NETWORK; MATRIX FUNCTIONS; NETWORK SCIENCE; NEUROSCIENCE; NEW APPROACHES; NON-INVASIVE; NONINVASIVE TECHNIQUE; UNSUPERVISED CLASSIFICATION; WEIGHTED NETWORKS; WHITE MATTER TRACTS;

MATRIX ALGEBRA;

ARTICLE; BRAIN DISEASE; BRAIN FUNCTION; NERVE CELL NETWORK; NEUROSCIENCE; NUCLEAR MAGNETIC RESONANCE IMAGING; BIOLOGICAL MODEL; BRAIN; DIFFUSION WEIGHTED IMAGING; HISTOLOGY; HUMAN; PATHOPHYSIOLOGY; PHYSIOLOGY; STROKE;

BRAIN; DIFFUSION MAGNETIC RESONANCE IMAGING; HUMANS; MODELS, NEUROLOGICAL; NERVE NET; STROKE;

EID: 65249163272     PISSN: 17425689     EISSN: 17425662     Source Type: Journal    
DOI: 10.1098/rsif.2008.0484     Document Type: Article

References (16)

1. Albert, R. & Barabasi, A. L. 2002 Statistical mechanics of complex networks. Rev. Mod. Phys. 74, 47-97. (doi:10.1103/RevModPhys.74.47)
2. Borgatti, S. P. 2005 Centrality and network flow. Soc. Networks 27, 55-71. (doi:10.1016/j.socnet.2004.11.008)
3. Cox, T. F. & Cox, M. A. A. 1994 Multidimensional scaling. London, UK: Chapman and Hall.
4. Estrada, E. & Hatano, N. 2007 Statistical-mechanical approach to subgraph centrality in complex networks. Chem. Phys. Lett. 439, 247-251. (doi:10.1016/j.cplett.2007.03.098)
5. Estrada, E. & Hatano, N. 2008 Communicability in complex networks. Phys. Rev. E 77, 036 111. (doi:10.1103/PhysRevE.77.036111)
6. Higham, D. J., Kalna, G. & Kibble, M. 2007 Spectral clustering and its use in bioinformatics. J. Comput. Appl. Math. 204, 25-37. (doi:10.1016/j.cam.2006.04.026)
7. Klein, J. C., Behrens, T. E. J., Robson, M. D., Mackay, C. E., Higham, D. J. & Johansen-Berg, H. 2007Connectivity-based parcellation of human cortex using diffusion MRI: establishing reproducability, validity and observer-independence in BA 44/45 and SMA/pre-SMA. NeuroImage 34, 204-211. (doi:10.1016/j.neuroimage.2006.08.022) (Pubitemid 44765247)
8. MacKay, D. J. C. 2003 Information theory, inference and learning algorithms. Cambridge, UK: Cambridge University Press.
9. McIntosh, A. R. & Lobaugh, N. J. 2004 Partial least squares analysis of neuroimaging data: applications and advances. NeuroImage 23(Suppl. 1), 250-263. See http://rotman-baycrest.on.ca/index.php?section=84. (doi:10.1016/j.neuroimage. 2004.07.020)
10. Newman, M. E. J. 2003 The structure and function of complex networks. SIAM Rev. 45, 167-256. (doi:10.1137/S003614450342480)
11. Newman, M. E. J. 2005 A measure of betweenness centrality based on random walks. Soc. Networks 27, 39-54. (doi:10.1016/j.socnet.2004.11.009)
12. Skillicorn, D. 2007 Understanding complex datasets. Boca Rotan, FL: Chapman and Hall/CRC.
13. Smith, S. M. et al. 2004 Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage 23(Suppl. 1), 208-219. (doi:10.1016/j.neuroimage.2004.07.051)
14. Sporns, O. & Zwi, J. 2004 The small world of the cerebral cortex. Neuroinformatics 2, 145-162. (doi:10.1385/NI:2:2:145) (Pubitemid 41214095)
15. Sporns, O., Tononi, G. & Kötter, R. 2005 The human connectome: a structural description of the human brain. PLoS Comput. Biol. 1, 245-251. (doi:10.1371/journal.pcbi.0010042)
16. Strogatz, S. H. 2001 Exploring complex networks. Nature 410, 268-276. (doi:10.1038/35065725)