The relation between structural and functional connectivity patterns in complex brain networks

International Journal of Psychophysiology

Volumn 103, Issue , 2016, Pages 149-160

  Stam, C J ^a   van Straaten, E C W ^a   Van Dellen, E ^a,b   Tewarie, P ^a   Gong, G ^c   Hillebrand, A ^a   Meier, J ^d   Van Mieghem, P ^d  

^a VU UNIVERSITY MEDICAL CENTER   (Netherlands)

^b UNIVERSITY MEDICAL CENTER UTRECHT   (Netherlands)

^c BEIJING NORMAL UNIVERSITY   (China)

^d Delft University of Technology ^*  (Netherlands)

Author keywords

Brain dynamics; Effective connectivity; Functional connectivity; Graph theory; Phase transition; SIS model

Indexed keywords

ARTICLE; BRAIN FUNCTION; BRAIN REGION; EPIDEMIC; FIRST CERVICAL VERTEBRA; HUMAN; NERVE CELL NETWORK; NEUROANATOMY; PHASE TRANSITION; SIMULATION; TIME SERIES ANALYSIS; BIOLOGICAL MODEL; BRAIN CORTEX; BRAIN MAPPING; COMPUTER SIMULATION; FEMALE; MALE; NERVE TRACT; NONLINEAR SYSTEM; PHYSIOLOGY;

BRAIN MAPPING; CEREBRAL CORTEX; COMPUTER SIMULATION; FEMALE; HUMANS; MALE; MODELS, NEUROLOGICAL; NERVE NET; NEURAL PATHWAYS; NONLINEAR DYNAMICS;

EID: 84923100455     PISSN: 01678760     EISSN: 18727697     Source Type: Journal    
DOI: 10.1016/j.ijpsycho.2015.02.011     Document Type: Article

References (55)

1. Barabasi, A.L., Albert, R., Emergence of scaling in random networks. Science 286:5439 (1999), 509–512 (Oct 15).
2. Barrat, A., Barthélemy, M., Pastor-Satorras, R., Vespignani, A., The architecture of complex weighted networks. Proc. Natl. Acad. Sci. U. S. A. 101:11 (2004), 3747–3752 (Mar 16).
3. Bassett, D.S., Bullmore, E., Small-world brain networks. Neuroscientist 12:6 (2006), 512–523 (Dec).
4. Beggs, J.M., Plenz, D., Neuronal avalanches in neocortical circuits. J Neurosci. 23:35 (2003), 11167–11177.
5. Boguñá, M., Castellano, C., Pastor-Satorras, R., Nature of the epidemic threshold for the susceptible–infected–susceptible dynamics in networks. Phys. Rev. Lett., 111(6), 2013, 068701 (Aug 9).
6. Bullmore, E., Sporns, O., Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. Rev. Neurosci. 10:3 (2009), 186–198 (Mar).
7. Castellano, C., Pastor-Satorras, R., Thresholds for epidemic spreading in networks. Phys. Rev. Lett., 105(21), 2010, 218701 (Nov 19).
8. de Haan, W., Mott, K., van Straaten, E.C., Scheltens, P., Stam, C.J., Activity dependent degeneration explains hub vulnerability in Alzheimer's disease. PLoS Comput. Biol., 8(8), 2012, e1002582.
9. Deco, G., Jirsa, V.K., McIntosh, A.R., Emerging concepts for the dynamical organization of resting-state activity in the brain. Nat. Rev. Neurosci. 12:1 (2011), 43–56 (Jan).
10. Deco, G., Senden, M., Jirsa, V., How anatomy shapes dynamics: a semi-analytical study of the brain at rest by a simple spin model. Front. Comput. Neurosci., 6, 2012, 68 (Sep 20).
11. Deco, G., Ponce-Alvarez, A., Mantini, D., Romani, G.L., Hagmann, P., Corbetta, M., Resting-state functional connectivity emerges from structurally and dynamically shaped slow linear fluctuations. J. Neurosci. 33:27 (2013), 11239–11252 (Jul 3).
12. Friston, K.J., Frith, C.D., Turner, R., Frackowiak, R.S., Characterizing evoked hemodynamics with fMRI. Neuroimage 2:2 (1995), 157–165 (Jun).
13. Friston, K., Moran, R., Seth, A.K., Analysing connectivity with Granger causality and dynamic causal modelling. Curr. Opin. Neurobiol. 23:2 (2013), 172–178 (Apr).
14. Gong, G., He, Y., Concha, L., Lebel, C., Gross, D.W., Evans, A.C., Beaulieu, C., Mapping anatomical connectivity patterns of human cerebral cortex using in vivo diffusion tensor imaging tractography. Cereb. Cortex 19:3 (2009), 524–536.
15. Gerstein, G.L., Aertsen, A.M., Representation of cooperative firing activity among simultaneously recorded neurons. J. Neurophysiol. 54:6 (1985), 1513–1528 (Dec).
16. Guimerà, R., Nunes Amaral, L.A., Functional cartography of complex metabolic networks. Nature 433:7028 (2005), 895–900 (Feb 24).
17. Haimovici, A., Tagliazucchi, E., Balenzuela, P., Chialvo, D.R., Brain organization into resting state networks emerges at criticality on a model of the human connectome. Phys. Rev. Lett., 110(17), 2013, 178101 (Apr 26).
18. Hermundstad, A.M., Bassett, D.S., Brown, K.S., Aminoff, E.M., Clewett, D., Freeman, S., Frithsen, A., Johnson, A., Tipper, C.M., Miller, M.B., Grafton, S.T., Carlson, J.M., Structural foundations of resting-state and task-based functional connectivity in the human brain. Proc. Natl. Acad. Sci. U. S. A. 110:15 (2013), 6169–6174 (Apr 9).
19. Hillebrand, A., Barnes, G.R., Bosboom, J.L., Berendse, H.W., Stam, C.J., Frequency-dependent functional connectivity within resting-state networks: an atlas-based MEG beamformer solution. Neuroimage 59:4 (2012), 3909–3921 (Feb 15).
20. Honey, C.J., Sporns, O., Dynamical consequences of lesions in cortical networks. Hum. Brain Mapp. 29:7 (2008), 802–809 (Jul).
21. Honey, C.J., Kötter, R., Breakspear, M., Sporns, O., Network structure of cerebral cortex shapes functional connectivity on multiple time scales. Proc. Natl. Acad. Sci. U. S. A. 104:24 (2007), 10240–10245 (Jun 12).
22. Honey, C.J., Sporns, O., Cammoun, L., Gigandet, X., Thiran, J.P., Meuli, R., Hagmann, P., Predicting human resting-state functional connectivity from structural connectivity. Proc. Natl. Acad. Sci. U. S. A. 106:6 (2009), 2035–2040 (Feb 10).
23. Honey, C.J., Thivierge, J.P., Sporns, O., Can structure predict function in the human brain?. Neuroimage 52:3 (2010), 766–776 (Sep).
24. Kaiser, M., The potential of the human connectome as a biomarker of brain disease. Front. Hum. Neurosci., 7, 2013, 484 (Aug 15).
25. Kaiser, M., Hilgetag, C.C., Optimal hierarchical modular topologies for producing limited sustained activation of neural networks. Front. Neuroinform., 4, 2010, 8 (May 14).
26. Markov, N.T., Ercsey-Ravasz, M., Van Essen, D.C., Knoblauch, K., Toroczkai, Z., Kennedy, H., Cortical high-density counterstream architectures. Science, 342(6158), 2013, 1238406.
27. Maslov, S., Sneppen, K., Detection of topological patterns in protein networks. Genet. Eng. (N.Y.) 26 (2004), 33–47.
28. Newman, M.E.J., Girvan, M., Finding and evaluating community structure in networks. Phys. Rev. E, 69, 2004, 06113.
29. O'Dea, R., Crofts, J.J., Kaiser, M., Spreading dynamics on spatially constrained complex brain networks. J. R. Soc. Interface, 10(81), 2013, 20130016 (Feb 13).
30. Park, H.J., Friston, K., Structural and functional brain networks: from connections to cognition. Science, 342(6158), 2013, 1238411 (Nov 1).
31. Pereda, E., Quiroga, R.Q., Bhattacharya, J., Nonlinear multivariate analysis of neurophysiological signals. Prog. Neurobiol. 77:1–2 (2005), 1–37 (Sep–Oct).
32. Ponten, S.C., Daffertshofer, A., Hillebrand, A., Stam, C.J., The relationship between structural and functional connectivity: graph theoretical analysis of an EEG neural mass model. Neuroimage 52:3 (2010), 985–994 (Sep).
33. Rubinov, M., Sporns, O., van Leeuwen, C., Breakspear, M., Symbiotic relationship between brain structure and dynamics. BMC Neurosci., 10, 2009, 55 (Jun 2).
34. Rubinov, M., Sporns, O., Thivierge, J.P., Breakspear, M., Neurobiologically realistic determinants of self-organized criticality in networks of spiking neurons. PLoS Comput. Biol., 7(6), 2011, e1002038 (Jun).
35. Shew, W.L., Plenz, D., The functional benefits of criticality in the cortex. Neuroscientist 19:1 (2013), 88–100 (Feb).
36. Sporns, O., Network attributes for segregation and integration in the human brain. Curr. Opin. Neurobiol. 23:2 (2013), 162–171 (Apr).
37. Stam, C.J., van Straaten, E.C., The organization of physiological brain networks. Clin. Neurophysiol. 123:6 (2012), 1067–1087 (Jun).
38. Stam, C.J., Hillebrand, A., Wang, H., Van Mieghem, P., Emergence of modular structure in a large-scale brain network with interactions between dynamics and connectivity. Front. Comput. Neurosci., 4, 2010.
39. Tewarie, P., Hillebrand, A., Schoonheim, M.M., van Dijk, B.W., Geurts, J.J., Barkhof, F., Polman, C.H., Stam, C.J., Functional brain network analysis using minimum spanning trees in Multiple Sclerosis: an MEG source-space study. Neuroimage, 2013, 10.1016/j.neuroimage.2013.10.022 (Oct 22, pii: S1053-8119(13)01045-8, [Epub ahead of print]).
40. Tewarie, P., Hillebrand, A., van Dellen, E., Schoonheim, M.M., Barkhof, F., Polman, C.H., Beaulieu, C., Gong, G., van Dijk, B.W., Stam, C.J., Structural degree predicts functional network connectivity: a multimodal resting-state fMRI and MEG study. Neuroimage 97 (2014), 296–307.
41. Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., Mazoyer, B., Joliot, M., Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15:1 (2002), 273–289 (Jan).
42. van Dellen, E., Hillebrand, A., Douw, L., Heimans, J.J., Reijneveld, J.C., Stam, C.J., Local polymorphic delta activity in cortical lesions causes global decreases in functional connectivity. Neuroimage 83C (2013), 524–532 (Jun 12).
43. van den Heuvel, M.P., Hulshoff Pol, H.E., Exploring the brain network: a review on resting-state fMRI functional connectivity. Eur. Neuropsychopharmacol. 20:8 (2010), 519–534 (Aug).
44. van den Heuvel, M.P., Sporns, O., Network hubs in the human brain. Trends Cogn. Sci., 2013, 10.1016/j.tics.2013.09.012 (Oct 26, pii: S1364-6613(13)00216-7, [Epub ahead of print]).
45. van den Heuvel, M.P., Stam, C.J., Boersma, M., Hulshoff Pol, H.E., Small-world and scale-free organization of voxel-based resting-state functional connectivity in the human brain. Neuroimage 43:3 (2008), 528–539 (Nov 15).
46. van den Heuvel, M.P., Stam, C.J., Kahn, R.S., Hulshoff Pol, H.E., Efficiency of functional brain networks and intellectual performance. J. Neurosci. 29:23 (2009), 7619–7624 (Jun 10).
47. van den Heuvel, M.P., Kahn, R.S., Goñi, J., Sporns, O., High-cost, high-capacity backbone for global brain communication. Proc. Natl. Acad. Sci. U. S. A. 109:28 (2012), 11372–11377 (Jul 10).
48. Van Mieghem, P., Epidemic phase transition of the SIS-type in networks. Europhys. Lett. (EPL), 97, 2012, 48004 (Februari).
49. Van Mieghem, P., Double orthogonality and the nature of networks. 2013, Delft University of Technology (report20130923, http://www.nas.ewi.tudelft.nl/people/Piet/papers/TUD20130923_Double_orthogonality.pdf).
50. Van Mieghem, P., van de Bovenkamp, R., Non-Markovian infection spread dramatically alters the SIS epidemic threshold in networks. Phys. Rev. Lett., 110(10), 2013, 108701 (March).
51. Van Mieghem, P., Omic, J.S., Kooij, R.E., Virus spread in networks. IEEE/ACM Trans. Netw. 17:1 (2009), 1–14 (February).
52. van Straaten, E.C., Stam, C.J., Structure out of chaos: functional brain network analysis with EEG, MEG, and functional MRI. Eur. Neuropsychopharmacol. 23:1 (2013), 7–18 (Jan).
53. Wang, H., Li, Q., D'Agostino, G., Havlin, S., Stanley, H.E., Van Mieghem, P., Effect of the interconnected network structure on the epidemic threshold. Phys. Rev. E Stat. Nonlin. Soft Matter Phys., 88(2), 2013, 022801 (Aug).
54. Watts, D.J., Strogatz, S.H., Collective dynamics of ‘small-world’ networks. Nature 393:6684 (1998), 440–442 (Jun 4).
55. Yu, S., Yang, H., Shriki, O., Plenz, D., Universal organization of resting brain activity at the thermodynamic critical point. Front. Syst. Neurosci., 7, 2013, 42 (Aug 22).