Brain Topography

, Volume 30, Issue 3, pp 291–302 | Cite as

Whole-Brain High-Resolution Structural Connectome: Inter-Subject Validation and Application to the Anatomical Segmentation of the Striatum

  • Pierre Besson
  • Nicolas Carrière
  • S. Kathleen Bandt
  • Marc Tommasi
  • Xavier Leclerc
  • Philippe Derambure
  • Renaud Lopes
  • Louise Tyvaert
Original Paper


The present study describes extraction of high-resolution structural connectome (HRSC) in 99 healthy subjects, acquired and made available by the Human Connectome Project. Single subject connectomes were then registered to the common surface space to allow assessment of inter-individual reproducibility of this novel technique using a leave-one-out approach. The anatomic relevance of the surface-based connectome was examined via a clustering algorithm, which identified anatomic subdivisions within the striatum. The connectivity of these striatal subdivisions were then mapped on the cortical and other subcortical surfaces. Findings demonstrate that HRSC analysis is robust across individuals and accurately models the actual underlying brain networks related to the striatum. This suggests that this method has the potential to model and characterize the healthy whole-brain structural network at high anatomic resolution.


Connectome Diffusion magnetic resonance imaging High-resolution Surface-based connectivity Striatum clustering 



Data were provided by the Human Connectome Project, WU-Minn Consortium (Principal Ivestigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. This work was partially supported by a grant from CPER Nord-Pas de Calais/FEDER DATA Advanced data science and technologies 2015–2020.

Supplementary material

10548_2017_548_MOESM1_ESM.docx (6.9 mb)
Supplementary material 1 (DOCX 7040 KB)


  1. Alexander GE, DeLong MR, Strick PL (1986) Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annu Rev Neurosci 9:357–381CrossRefPubMedGoogle Scholar
  2. Alexander GE, Crutcher MD, DeLong MR (1990) Basal ganglia-thalamocortical circuits: parallel substrates for motor, oculomotor, “prefrontal” and “limbic” functions. Prog Brain Res 85:119–146CrossRefPubMedGoogle Scholar
  3. Andersson JL, Skare S, Ashburner J (2003) How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging. Neuroimage 20:870–888CrossRefPubMedGoogle Scholar
  4. Andreotti J, Jann K, Melie-Garcia L, Giezendanner S, Dierks T, Federspiel A (2014) Repeatability analysis of global and local metrics of brain structural networks. Brain Connect 4:203–220CrossRefPubMedGoogle Scholar
  5. Anwander A, Tittgemeyer M, von Cramon D, Friederici A, Knösche T (2007) Connectivity-based parcellation of Broca’s area. Cereb Cortex 17:816–825CrossRefPubMedGoogle Scholar
  6. Barnes KA, Cohen AL, Power JD, Nelson SM, Dosenbach YB, Miezin FM, Petersen SE, Schlaggar BL (2010) Identifying basal ganglia divisions in individuals using resting-state functional connectivity MRI. Front Syst Neurosci, 4:18PubMedPubMedCentralGoogle Scholar
  7. Bassett DS, Brown JA, Deshpande V, Carlson JM, Grafton ST (2011) Conserved and variable architecture of human white matter connectivity. Neuroimage 54:1262–1279CrossRefPubMedGoogle Scholar
  8. Beckmann M, Johansen-Berg H, Rushworth MFS (2009) Connectivity-based parcellation of human cingulate cortex and its relation to functional specialization. J Neurosci 29:1175–1190CrossRefGoogle Scholar
  9. Behrens TE, Johansen-Berg H, Woolrich MW, Smith SM, Wheeler-Kingshott CA, Boulby PA, Barker GJ, Sillery EL, Sheehan K, Ciccarelli O, Thompson AJ, Brady JM, Matthews PM (2003) Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging. Nat Neurosci 6:750–757CrossRefPubMedGoogle Scholar
  10. Besson P, Dinkelacker V, Valabregue R, Thivard L, Leclerc X, Baulac M, Sammler D, Colliot O, Lehéricy S, Samson S, Dupont S (2014a) Structural connectivity differences in left and right temporal lobe epilepsy. Neuroimage 100:135–144CrossRefPubMedGoogle Scholar
  11. Besson P, Lopes R, Leclerc X, Derambure P, Tyvaert L (2014b) Intra-subject reliability of the high-resolution whole-brain structural connectome. NeuroImage 102(Part 2):283–293CrossRefPubMedGoogle Scholar
  12. Bonilha L, Gleichgerrcht E, Fridriksson J, Rorden C, Breedlove JL, Nesland T, Paulus W, Helms G, Focke NK (2015) Reproducibility of the structural brain connectome derived from diffusion tensor imaging. PloS One 10:e0135247CrossRefPubMedPubMedCentralGoogle Scholar
  13. Buchanan CR, Pernet CR, Gorgolewski KJ, Storkey AJ, Bastin ME (2014) Test–retest reliability of structural brain networks from diffusion MRI. Neuroimage 86:231–243CrossRefPubMedGoogle Scholar
  14. Calamante F, Tournier J-D, Jackson GD, Connelly A (2010) Track-density imaging (TDI): super-resolution white matter imaging using whole-brain track-density mapping. Neuroimage 53:1233–1243CrossRefPubMedGoogle Scholar
  15. Calamante F, Tournier J-D, Heidemann RM, Anwander A, Jackson GD, Connelly A (2011) Track density imaging (TDI): validation of super resolution property. Neuroimage 56:1259–1266CrossRefPubMedGoogle Scholar
  16. Calamante F, Tournier J-D, Kurniawan ND, Yang Z, Gyengesi E, Galloway GJ, Reutens DC, Connelly A (2012) Super-resolution track-density imaging studies of mouse brain: comparison to histology. Neuroimage 59:286–296CrossRefPubMedGoogle Scholar
  17. Calamante F, Oh S-H, Tournier J-D, Park S-Y, Son Y-D, Chung J-Y, Chi J-G, Jackson GD, Park C-W, Kim Y-B, Connelly A, Cho Z-H (2013) Super-resolution track-density imaging of thalamic substructures: comparison with high-resolution anatomical magnetic resonance imaging at 7.0T. Hum Brain Mapp 34:2538–2548CrossRefPubMedGoogle Scholar
  18. Chao YP, Cho KH, Yeh CH, Chou KH, Chen JH, Lin CP (2009) Probabilistic topography of human corpus callosum using cytoarchitectural parcellation and high angular resolution diffusion imaging tractography. Hum Brain Mapp 30:3172–3187CrossRefPubMedGoogle Scholar
  19. Cheng H, Wang Y, Sheng J, Kronenberger WG, Mathews VP, Hummer TA, Saykin AJ (2012) Characteristics and variability of structural networks derived from diffusion tensor imaging. Neuroimage 61:1153–1164CrossRefPubMedPubMedCentralGoogle Scholar
  20. Choi EY, Yeo BT, Buckner RL (2012) The organization of the human striatum estimated by intrinsic functional connectivity. J Neurophysiol 108:2242–2263CrossRefPubMedPubMedCentralGoogle Scholar
  21. Cohen MX, Lombardo MV, Blumenfeld RS (2008) Covariance-based subdivision of the human striatum using T1-weighted MRI. Eur J Neurosci 27:1534–1546CrossRefPubMedGoogle Scholar
  22. Dale AM, Fischl B, Sereno MI (1999) Cortical surface-based analysis: I. segmentation and surface reconstruction. Neuroimage 9:179–194CrossRefPubMedGoogle Scholar
  23. Deco G, Jirsa VK, McIntosh AR (2011) Emerging concepts for the dynamical organization of resting-state activity in the brain. Nat Rev Neurosci 12:43–56CrossRefPubMedGoogle Scholar
  24. DeLong M, Georgopoulos A (1981) Handbook of Physiology. The Nervous System. Motor Control. Section 1Google Scholar
  25. Derakhshan M, Caramanos Z, Giacomini PS, Narayanan S, Maranzano J, Francis SJ, Arnold DL, Collins DL (2010) Evaluation of automated techniques for the quantification of grey matter atrophy in patients with multiple sclerosis. Neuroimage 52:1261–1267CrossRefPubMedGoogle Scholar
  26. Devlin JT, Sillery EL, Hall DA, Hobden P, Behrens TE, Nunes RG, Clare S, Matthews PM, Moore DR, Johansen-Berg H (2006) Reliable identification of the auditory thalamus using multi-modal structural analyses. Neuroimage 30:1112–1120CrossRefPubMedPubMedCentralGoogle Scholar
  27. Di Martino A, Scheres A, Margulies DS, Kelly A, Uddin LQ, Shehzad Z, Biswal B, Walters JR, Castellanos FX, Milham MP (2008) Functional connectivity of human striatum: a resting state FMRI study. Cerebral Cortex 18:2735–2747CrossRefPubMedGoogle Scholar
  28. Draganski B, Kherif F, Klöppel S, Cook PA, Alexander DC, Parker GJM, Deichmann R, Ashburner J, Frackowiak RSJ (2008) Evidence for segregated and integrative connectivity patterns in the human basal ganglia. J Neurosci 28:7143–7152CrossRefPubMedGoogle Scholar
  29. Duda JT, Cook PA, Gee JC (2014) Reproducibility of graph metrics of human brain structural networks. Front Neuroinform 8:46CrossRefPubMedPubMedCentralGoogle Scholar
  30. Fernández-Seara MA, Aznárez-Sanado M, Mengual E, Loayza FR, Pastor MA (2009) Continuous performance of a novel motor sequence leads to highly correlated striatal and hippocampal perfusion increases. Neuroimage 47:1797–1808CrossRefPubMedGoogle Scholar
  31. Fischl B, Sereno MI, Dale AM (1999a) cortical surface-based analysis: II: inflation, flattening, and a surface-based coordinate system. Neuroimage 9:195–207CrossRefPubMedGoogle Scholar
  32. Fischl B, Sereno MI, Tootell RB, Dale AM (1999b) High-resolution intersubject averaging and a coordinate system for the cortical surface. Hum Brain Mapp 8:272–284CrossRefPubMedGoogle Scholar
  33. Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C, van der Kouwe A, Killiany R, Kennedy D, Klaveness S, Montillo A, Makris N, Rosen B, Dale AM (2002) Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33:341–355CrossRefPubMedGoogle Scholar
  34. Ford A, McGregor KM, Case K, Crosson B, White KD (2010) Structural connectivity of Broca’s area and medial frontal cortex. Neuroimage 52:1230–1237CrossRefPubMedPubMedCentralGoogle Scholar
  35. Friedman DP, Aggleton JP, Saunders RC (2002) Comparison of hippocampal, amygdala, and perirhinal projections to the nucleus accumbens: combined anterograde and retrograde tracing study in the Macaque brain. J Comp Neurol 450:345–365CrossRefPubMedGoogle Scholar
  36. Glasser MF, Sotiropoulos SN, Wilson JA, Coalson TS, Fischl B, Andersson JL, Xu J, Jbabdi S, Webster M, Polimeni JR, Van Essen DC, Jenkinson M (2013a) The minimal preprocessing pipelines for the human connectome project. Neuroimage 80:105–124CrossRefPubMedPubMedCentralGoogle Scholar
  37. Glasser MF, Sotiropoulos SN, Wilson JA, Coalson TS, Fischl B, Andersson JL, Xu JQ, Jbabdi S, Webster M, Polimeni JR, Van Essen DC, Jenkinson M, Consortium W-MH (2013b) The minimal preprocessing pipelines for the human connectome project. Neuroimage 80:105–124CrossRefPubMedPubMedCentralGoogle Scholar
  38. Glasser MF, Coalson TS, Robinson EC, Hacker CD, Harwell J, Yacoub E, Ugurbil K, Andersson J, Beckmann CF, Jenkinson M, Smith SM, Van Essen DC (2016) A multi-modal parcellation of human cerebral cortex. Nature 536:171–178CrossRefPubMedPubMedCentralGoogle Scholar
  39. Gorbach NS, Schutte C, Melzer C, Goldau M, Sujazow O, Jitsev J, Douglas T, Tittgemeyer M (2011) Hierarchical information-based clustering for connectivity-based cortex parcellation. Front Neuroinform 5:18CrossRefPubMedPubMedCentralGoogle Scholar
  40. Haber SN (2003) The primate basal ganglia: parallel and integrative networks. J Chem Neuroanat 26:317–330CrossRefPubMedGoogle Scholar
  41. Haber SN (2011) 11 neuroanatomy of reward: a view from the ventral striatum. Neurobiol Sensat Reward 235Google Scholar
  42. Haber SN, Knutson B (2010) The reward circuit: linking primate anatomy and human imaging. Neuropsychopharmacology 35:4–26CrossRefPubMedGoogle Scholar
  43. Hagmann P, Cammoun L, Gigandet X, Meuli R, Honey CJ, Wedeen VJ, Sporns O (2008) Mapping the structural core of human cerebral cortex. PLoS Biol 6:e159CrossRefPubMedPubMedCentralGoogle Scholar
  44. Helms G, Draganski B, Frackowiak R, Ashburner J, Weiskopf N (2009) Improved segmentation of deep brain grey matter structures using magnetization transfer (MT) parameter maps. Neuroimage 47:194–198CrossRefPubMedPubMedCentralGoogle Scholar
  45. Hikosaka O, Nakamura K, Sakai K, Nakahara H (2002) Central mechanisms of motor skill learning. Curr Opin Neurobiol 12:217–222CrossRefPubMedGoogle Scholar
  46. Johansen-Berg H, Behrens TEJ, Sillery E, Ciccarelli O, Thompson AJ, Smith SM, Matthews PM (2005) Functional–anatomical validation and individual variation of diffusion tractography-based segmentation of the human thalamus. Cereb Cortex 15:31–39CrossRefPubMedGoogle Scholar
  47. Jueptner M, Frith C, Brooks D, Frackowiak R, Passingham R (1997) Anatomy of motor learning. II. Subcortical structures and learning by trial and error. J Neurophysiol 77:1325–1337PubMedGoogle Scholar
  48. Kim H, Chupin M, Colliot O, Bernhardt BC, Bernasconi N, Bernasconi A (2012) Automatic hippocampal segmentation in temporal lobe epilepsy: impact of developmental abnormalities. Neuroimage 59:3178–3186CrossRefPubMedGoogle Scholar
  49. Klein JC, Behrens TE, Robson MD, Mackay CE, Higham DJ, Johansen-Berg H (2007) Connectivity-based parcellation of human cortex using diffusion MRI: establishing reproducibility, validity and observer independence in BA 44/45 and SMA/pre-SMA. Neuroimage 34:204–211CrossRefPubMedGoogle Scholar
  50. Kwon D-H, Kim J-M, Oh S-H, Jeong H-J, Park S-Y, Oh E-S, Chi J-G, Kim Y-B, Jeon BS, Cho Z-H (2012) Seven-tesla magnetic resonance images of the substantia nigra in Parkinson disease. Ann Neurol 71:267–277CrossRefPubMedGoogle Scholar
  51. Lambert C, Zrinzo L, Nagy Z, Lutti A, Hariz M, Foltynie T, Draganski B, Ashburner J, Frackowiak R (2012) Confirmation of functional zones within the human subthalamic nucleus: patterns of connectivity and sub-parcellation using diffusion weighted imaging. Neuroimage 60:83–94CrossRefPubMedPubMedCentralGoogle Scholar
  52. Leh SE, Ptito A, Chakravarty MM, Strafella AP (2007) Fronto-striatal connections in the human brain: a probabilistic diffusion tractography study. Neurosci Lett 419:113–118CrossRefPubMedPubMedCentralGoogle Scholar
  53. Lehéricy S, Ducros M, Van De Moortele P-F, Francois C, Thivard L, Poupon C, Swindale N, Ugurbil K, Kim D-S (2004) Diffusion tensor fiber tracking shows distinct corticostriatal circuits in humans. Ann Neurol 55:522–529CrossRefPubMedGoogle Scholar
  54. MacLean PD (1972) Cerebral evolution and emotional processes: new findings on the striatal complex. Ann NY Acad Sci 193:137–149CrossRefPubMedGoogle Scholar
  55. Mars RB, Jbabdi S, Sallet J, O’Reilly JX, Croxson PL, Olivier E, Noonan MP, Bergmann C, Mitchell AS, Baxter MG, Behrens TE, Johansen-Berg H, Tomassini V, Miller KL, Rushworth MF (2011) Diffusion-weighted imaging tractography-based parcellation of the human parietal cortex and comparison with human and macaque resting-state functional connectivity. J Neurosci 31:4087–4100CrossRefPubMedPubMedCentralGoogle Scholar
  56. Middleton FA, Strick PL (2000) Basal ganglia and cerebellar loops: motor and cognitive circuits. Brain Res Brain Res Rev 31:236–250CrossRefPubMedGoogle Scholar
  57. Nakagawa TT, Woolrich M, Luckhoo H, Joensson M, Mohseni H, Kringelbach ML, Jirsa V, Deco G (2014) How delays matter in an oscillatory whole-brain spiking-neuron network model for MEG alpha-rhythms at rest. Neuroimage 87:383–394CrossRefPubMedGoogle Scholar
  58. Nanetti L, Cerliani L, Gazzola V, Renken R, Keysers C (2009) Group analyses of connectivity-based cortical parcellation using repeated k-means clustering. Neuroimage 47:1666–1677CrossRefPubMedGoogle Scholar
  59. Ng AY, Jordan MI, Weiss Y (2002) On spectral clustering: analysis and an algorithm. Adv Neural Inf Process Syst 2:849–856Google Scholar
  60. O’Muircheartaigh J, Vollmar C, Traynor C, Barker GJ, Kumari V, Symms MR, Thompson P, Duncan JS, Koepp MJ, Richardson MP (2011) Clustering probabilistic tractograms using independent component analysis applied to the thalamus. Neuroimage 54:2020–2032CrossRefPubMedPubMedCentralGoogle Scholar
  61. Owen JP, Ziv E, Bukshpun P, Pojman N, Wakahiro M, Berman JI, Roberts TP, Friedman EJ, Sherr EH, Mukherjee P (2013) Test-retest reliability of computational network measurements derived from the structural connectome of the human brain. Brain Connect 3:160–176CrossRefPubMedPubMedCentralGoogle Scholar
  62. Parent A (1990) Extrinsic connections of the basal ganglia. Trends Neurosci 13:254–258CrossRefPubMedGoogle Scholar
  63. Patenaude B, Smith SM, Kennedy DN, Jenkinson M (2011) A Bayesian model of shape and appearance for subcortical brain segmentation. Neuroimage 56:907–922CrossRefPubMedPubMedCentralGoogle Scholar
  64. Perrin M, Cointepas Y, Cachia A, Poupon C, Thirion B, Riviere D, Cathier P, El Kouby V, Constantinesco A, Le Bihan D, Mangin JF (2008) Connectivity-based parcellation of the cortical mantle using q-ball diffusion imaging. Int J Biomed Imaging 2008:368406CrossRefPubMedPubMedCentralGoogle Scholar
  65. Postuma RB, Dagher A (2006) Basal ganglia functional connectivity based on a meta-analysis of 126 positron emission tomography and functional magnetic resonance imaging publications. Cerebral Cortex 16:1508–1521CrossRefPubMedGoogle Scholar
  66. Rousseeuw PJ (1987) Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J Comput Appl Math 20:53–65CrossRefGoogle Scholar
  67. Samu D, Seth AK, Nowotny T (2014) Influence of wiring cost on the large-scale architecture of human cortical connectivity. PLoS Comput Biol 10:e1003557CrossRefPubMedPubMedCentralGoogle Scholar
  68. Sánchez-Benavides G, Gómez-Ansón B, Sainz A, Vives Y, Delfino M, Peña-Casanova J (2010) Manual validation of FreeSurfer’s automated hippocampal segmentation in normal aging, mild cognitive impairment, and Alzheimer Disease subjects. Psychiatry Res Neuroimaging 181:219–225CrossRefPubMedGoogle Scholar
  69. Schubotz RI, Anwander A, Knosche TR, von Cramon DY, Tittgemeyer M (2010) Anatomical and functional parcellation of the human lateral premotor cortex. Neuroimage 50:396–408CrossRefPubMedGoogle Scholar
  70. Selemon L, Goldman-Rakic P (1985) Longitudinal topography and interdigitation of corticostriatal projections in the rhesus monkey. J Neurosci 5:776–794PubMedGoogle Scholar
  71. Shi J, Malik J (2000) Normalized cuts and image segmentation. IEEE Trans Pattern Anal Mach Intell 22:888–905CrossRefGoogle Scholar
  72. Smith RE, Tournier J-D, Calamante F, Connelly A (2015) The effects of SIFT on the reproducibility and biological accuracy of the structural connectome. Neuroimage 104:253–265CrossRefPubMedGoogle Scholar
  73. Sotiropoulos SN, Jbabdi S, Xu J, Andersson JL, Moeller S, Auerbach EJ, Glasser MF, Hernandez M, Sapiro G, Jenkinson M, Feinberg DA, Yacoub E, Lenglet C, Van Essen DC, Ugurbil K, Behrens TEJ (2013) Advances in diffusion MRI acquisition and processing in the human connectome project. Neuroimage 80:125–143CrossRefPubMedPubMedCentralGoogle Scholar
  74. Sporns O, Tononi G, Kötter R (2005) The human connectome: a structural description of the human brain. PLoS Comput Biol 1:e42CrossRefPubMedPubMedCentralGoogle Scholar
  75. Strogatz SH (2001) Exploring complex networks. Nature 410:268–276CrossRefPubMedGoogle Scholar
  76. Styner M, Oguz I, Xu S, Brechbuhler C, Pantazis D, Levitt JJ, Shenton ME, Gerig G (2006) Framework for the Statistical Shape Analysis of Brain Structures using SPHARM-PDM. Insight J 1071:242–250Google Scholar
  77. Sugar CA, James GM (2003) Finding the number of clusters in a dataset. J Amer Statistical Assoc 98:750–763CrossRefGoogle Scholar
  78. Tomassini V, Jbabdi S, Klein JC, Behrens TE, Pozzilli C, Matthews PM, Rushworth MF, Johansen-Berg H (2007) Diffusion-weighted imaging tractography-based parcellation of the human lateral premotor cortex identifies dorsal and ventral subregions with anatomical and functional specializations. J Neurosci 27:10259–10269CrossRefPubMedGoogle Scholar
  79. Tournier JD, Calamante F, Connelly A (2007) Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution. Neuroimage 35:1459–1472CrossRefPubMedGoogle Scholar
  80. Tournier J, Calamante F, Connelly A (2012) MRtrix: diffusion tractography in crossing fiber regions. Int J Imaging Syst Technol 22:53–66CrossRefGoogle Scholar
  81. Tournier JD, Calamante F, Connelly A (2013) Determination of the appropriate b value and number of gradient directions for high-angular-resolution diffusion-weighted imaging. NMR Biomed 26:1775–1786CrossRefPubMedGoogle Scholar
  82. Ugurbil K, Xu J, Auerbach EJ, Moeller S, Vu AT, Duarte-Carvajalino JM, Lenglet C, Wu X, Schmitter S, Van de Moortele PF, Strupp J, Sapiro G, De Martino F, Wang D, Harel N, Garwood M, Chen L, Feinberg DA, Smith SM, Miller KL, Sotiropoulos SN, Jbabdi S, Andersson JL, Behrens TE, Glasser MF, Van Essen DC, Yacoub E (2013) Pushing spatial and temporal resolution for functional and diffusion MRI in the human connectome project. Neuroimage 80:80–104CrossRefPubMedPubMedCentralGoogle Scholar
  83. Uğurbil K, Xu J, Auerbach EJ, Moeller S, Vu AT, Duarte-Carvajalino JM, Lenglet C, Wu X, Schmitter S, Van de Moortele PF, Strupp J, Sapiro G, De Martino F, Wang D, Harel N, Garwood M, Chen L, Feinberg DA, Smith SM, Miller KL, Sotiropoulos SN, Jbabdi S, Andersson JLR, Behrens TEJ, Glasser MF, Van Essen DC, Yacoub E (2013) Pushing spatial and temporal resolution for functional and diffusion MRI in the Human connectome project. Neuroimage 80:80–104CrossRefPubMedPubMedCentralGoogle Scholar
  84. Vaessen MJ, Hofman PA, Tijssen HN, Aldenkamp AP, Jansen JF, Backes WH (2010) The effect and reproducibility of different clinical DTI gradient sets on small world brain connectivity measures. Neuroimage 51:1106–1116CrossRefPubMedGoogle Scholar
  85. Van Essen DC, Ugurbil K (2012) The future of the human connectome. Neuroimage 62:1299–1310CrossRefPubMedPubMedCentralGoogle Scholar
  86. van den Heuvel MP, Sporns O (2011) Rich-club organization of the human connectome. J Neurosci 31:15775–15786CrossRefPubMedGoogle Scholar
  87. Verstraete E, Veldink JH, Mandl RCW, van den Berg LH, van den Heuvel MP (2011) Impaired structural motor connectome in amyotrophic lateral sclerosis. PloS One 6:e24239CrossRefPubMedPubMedCentralGoogle Scholar
  88. Vinh NX, Epps J, Bailey J (2010) Information theoretic measures for clusterings comparison: variants, properties, normalization and correction for chance. J Mach Learn Res 11:2837–2854Google Scholar
  89. Von Luxburg U (2007) A tutorial on spectral clustering. Stat Comput 17:395–416CrossRefGoogle Scholar
  90. Welton T, Kent DA, Auer DP, Dineen RA (2014) Reproducibility of graph-theoretic brain network metrics: a systematic review. Brain Connect 5:193–202CrossRefGoogle Scholar
  91. Yeo BT, Krienen FM, Sepulcre J, Sabuncu MR, Lashkari D, Hollinshead M, Roffman JL, Smoller JW, Zöllei L, Polimeni JR (2011) The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J Neurophysiol 106:1125–1165CrossRefPubMedGoogle Scholar
  92. Zalesky A, Fornito A, Harding IH, Cocchi L, Yucel M, Pantelis C, Bullmore ET (2010) Whole-brain anatomical networks: does the choice of nodes matter? Neuroimage 50:970–983CrossRefPubMedGoogle Scholar
  93. Zalesky A, Solowij N, Yücel M, Lubman DI, Takagi M, Harding IH, Lorenzetti V, Wang R, Searle K, Pantelis C, Seal M (2012) Effect of long-term cannabis use on axonal fibre connectivity. Brain 135:2245–2255CrossRefPubMedGoogle Scholar
  94. Zhang D, Snyder AZ, Fox MD, Sansbury MW, Shimony JS, Raichle ME (2008) Intrinsic functional relations between human cerebral cortex and thalamus. J Neurophysiol 100:1740–1748CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Aix Marseille Université, CNRS, CRMBMMarseilleFrance
  2. 2.AP-HM, CHU Timone, Pôle d’Imagerie, CEMEREMMarseilleFrance
  3. 3.U1171, INSERM, Université de LilleLilleFrance
  4. 4.Neurology and Movement disorders DepartmentLille University HospitalLilleFrance
  5. 5.Université de Lille, CRIStAL UMR9189, INRIA, Magnet TeamLilleFrance
  6. 6.Clinical Imaging Core FacilityINSERM U1171, Lille University HospitalLilleFrance
  7. 7.Department of Clinical NeurophysiologyLille University HospitalLilleFrance
  8. 8.Department of NeurologyNancy University HospitalNancyFrance
  9. 9.CRAN, UMR CNRS 7039, University of LorraineNancyFrance

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