S. Achard and E. Bullmore, Efficiency and Cost of Economical Brain Functional Networks, PLoS Computational Biology, vol.15, issue.2, 2007.
DOI : 10.1371/journal.pcbi.0030017.sg002

S. Achard, C. Delon-martin, P. E. Vértes, F. Renard, M. Schenck et al., Hubs of brain functional networks are radically reorganized in comatose patients, Proceedings of the National Academy of Sciences, vol.109, issue.50, 2012.
DOI : 10.1073/pnas.1208933109
URL : https://hal.archives-ouvertes.fr/inserm-00769024

S. Achard, R. Salvador, B. Whitcher, J. Suckling, and E. Bullmore, A Resilient, Low-Frequency, Small-World Human Brain Functional Network with Highly Connected Association Cortical Hubs, Journal of Neuroscience, vol.26, issue.1, pp.63-72, 2006.
DOI : 10.1523/JNEUROSCI.3874-05.2006

O. Agcaoglu, R. Miller, A. Mayer, K. Hugdahl, and V. Calhoun, Lateralization of resting state networks and relationship to age and gender, NeuroImage, vol.104, pp.310-325, 2015.
DOI : 10.1016/j.neuroimage.2014.09.001

A. Alexander-bloch, R. Lambiotte, B. Roberts, J. Giedd, N. Gogtay et al., The discovery of population differences in network community structure: New methods and applications to brain functional networks in schizophrenia, NeuroImage, vol.59, issue.4, pp.3889-3900, 2012.
DOI : 10.1016/j.neuroimage.2011.11.035

M. Andellini, V. Cannatà, S. Gazzellini, B. Bernardi, and A. Napolitano, Test-retest reliability of graph metrics of resting state MRI functional brain networks: A review, Journal of Neuroscience Methods, vol.253, pp.183-192, 2015.
DOI : 10.1016/j.jneumeth.2015.05.020

R. F. Betzel, L. Byrge, Y. He, J. Goñi, X. N. Zuo et al., Changes in structural and functional connectivity among resting-state networks across the human lifespan, Changes in structural and functional connectivity among resting-state networks across the human lifespan, pp.345-357, 2014.
DOI : 10.1016/j.neuroimage.2014.07.067

R. M. Birn, E. K. Molloy, R. Patriat, T. Parker, T. B. Meier et al., The effect of scan length on the reliability of resting-state fMRI connectivity estimates, NeuroImage, vol.83, pp.550-558, 2013.
DOI : 10.1016/j.neuroimage.2013.05.099

B. Biswal, F. Zerrin-yetkin, V. M. Haughton, and J. S. Hyde, Functional connectivity in the motor cortex of resting human brain using echo-planar mri, Magnetic Resonance in Medicine, vol.13, issue.4, pp.537-541, 1995.
DOI : 10.1002/mrm.1910340409

J. M. Bland and D. G. Altman, Statistical methods for assessing agreement between two methods of clinical measurement, International Journal of Nursing Studies, vol.47, issue.8, pp.307-310, 1986.
DOI : 10.1016/j.ijnurstu.2009.10.001

T. J. Boardman, Confidence Intervals for Variance Components -- A Comparative Monte Carlo Study, Biometrics, vol.30, issue.2, pp.251-262, 1974.
DOI : 10.2307/2529647

S. Boccaletti, V. Latora, Y. Moreno, M. Chavez, and D. Hwang, Complex networks: Structure and dynamics, Physics Reports, vol.424, issue.4-5, pp.175-308, 2006.
DOI : 10.1016/j.physrep.2005.10.009

U. Braun, M. M. Plichta, C. Esslinger, C. Sauer, L. Haddad et al., Test???retest reliability of resting-state connectivity network characteristics using fMRI and graph theoretical measures, NeuroImage, vol.59, issue.2, pp.1404-1412, 2012.
DOI : 10.1016/j.neuroimage.2011.08.044

E. Bullmore and O. Sporns, Complex brain networks: graph theoretical analysis of structural and functional systems, Nature Reviews Neuroscience, vol.8, issue.3, pp.186-198, 2009.
DOI : 10.1371/journal.pone.0002051

K. S. Button, J. P. Ioannidis, C. Mokrysz, B. A. Nosek, J. Flint et al., Power failure: why small sample size undermines the reliability of neuroscience, Nature Reviews Neuroscience, vol.80, issue.5, pp.365-376, 2013.
DOI : 10.1038/nrn3475

H. Cao, M. M. Plichta, A. Schäfer, L. Haddad, O. Grimm et al., Test???retest reliability of fMRI-based graph theoretical properties during working memory, emotion processing, and resting state, NeuroImage, vol.84, pp.888-900, 2014.
DOI : 10.1016/j.neuroimage.2013.09.013

D. V. Cicchetti, Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology., Psychological Assessment, vol.6, issue.4, 1994.
DOI : 10.1037/1040-3590.6.4.284

R. C. Craddock, G. A. James, P. E. Holtzheimer, X. P. Hu, and H. S. Mayberg, A whole brain fMRI atlas generated via spatially constrained spectral clustering, Human Brain Mapping, vol.22, issue.Pt 1, 1914.
DOI : 10.1002/hbm.21333

F. De-vico-fallani, J. Richiardi, M. Chavez, and S. Achard, Graph analysis of functional brain networks: practical issues in translational neuroscience, Philosophical Transactions of the Royal Society B: Biological Sciences, vol.513, issue.5, 2014.
DOI : 10.1002/cne.21974
URL : https://hal.archives-ouvertes.fr/hal-01062386

R. S. Desikan, F. Ségonne, B. Fischl, B. T. Quinn, B. C. Dickerson et al., An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest, NeuroImage, vol.31, issue.3, pp.968-980, 2006.
DOI : 10.1016/j.neuroimage.2006.01.021

J. Diedrichsen, J. H. Balsters, J. Flavell, E. Cussans, and N. Ramnani, A probabilistic MR atlas of the human cerebellum, NeuroImage, vol.46, issue.1, pp.39-46, 2009.
DOI : 10.1016/j.neuroimage.2009.01.045

A. Donner, A Review of Inference Procedures for the Intraclass Correlation Coefficient in the One-Way Random Effects Model, International Statistical Review / Revue Internationale de Statistique, vol.54, issue.1, pp.67-82, 1986.
DOI : 10.2307/1403259

A. Donner and G. Wells, A Comparison of Confidence Interval Methods for the Intraclass Correlation Coefficient, Biometrics, vol.42, issue.2, pp.401-412, 1986.
DOI : 10.2307/2531060

H. X. Du, X. H. Liao, Q. X. Lin, G. S. Li, Y. Z. Chi et al., Test-retest reliability of graph metrics in highresolution functional connectomics: A resting-state functional mri study, CNS Neurosci Ther URL, 2015.

H. Duvernoy, The Human Brain Stem and Cerebellum: Surface, Structure , Vascularization, and Three-dimensional Sectional Anatomy with MRI. Spring-Verlag. URL: https, 1995.
DOI : 10.1007/978-3-7091-3078-0

D. A. Feinberg, S. Moeller, S. M. Smith, E. Auerbach, S. Ramanna et al., Multiplexed echo planar imaging for sub-second whole brain fmri and fast diffusion imaging, PLoS ONE, vol.5, 2010.

M. Fiecas, H. Ombao, D. Van-lunen, R. Baumgartner, A. Coimbra et al., Quantifying temporal correlations: A test???retest evaluation of functional connectivity in resting-state fMRI, NeuroImage, vol.65, pp.231-241, 2013.
DOI : 10.1016/j.neuroimage.2012.09.052

N. Filippini, B. J. Macintosh, M. G. Hough, G. M. Goodwin, G. B. Frisoni et al., Distinct patterns of brain activity in young carriers of the APOE-??4 allele, Proceedings of the National Academy of Sciences, vol.106, issue.17, pp.7209-7214, 2009.
DOI : 10.1073/pnas.0811879106

R. A. Fisher, Theory of Statistical Estimation, Mathematical Proceedings of the Cambridge Philosophical Society, vol.80, issue.05, pp.700-725, 1925.
DOI : 10.1017/S0305004100009580

A. Fornito, A. Zalesky, and E. T. Bullmore, Network scaling effects in graph analytic studies of human resting-state fMRI data, Frontiers in Systems Neuroscience, vol.4, 2010.
DOI : 10.3389/fnsys.2010.00022

M. D. Fox and M. E. Raichle, Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging, Nature Reviews Neuroscience, vol.17, issue.9, pp.700-711, 2007.
DOI : 10.1016/j.neuroimage.2006.02.010

A. Gandy, Sequential Implementation of Monte Carlo Tests With Uniformly Bounded Resampling Risk, Journal of the American Statistical Association, vol.104, issue.488, pp.1504-1511, 2009.
DOI : 10.1198/jasa.2009.tm08368

A. Gandy and G. Hahn, MMCTest-A Safe Algorithm for Implementing Multiple Monte Carlo Tests, Scandinavian Journal of Statistics, vol.50, issue.5, pp.1083-1101, 2014.
DOI : 10.1111/sjos.12085

M. F. Glasser, S. N. Sotiropoulos, J. A. Wilson, T. S. Coalson, B. Fischl et al., The minimal preprocessing pipelines for the Human Connectome Project, NeuroImage, vol.80, pp.105-124, 2013.
DOI : 10.1016/j.neuroimage.2013.04.127

J. A. Grahn, J. A. Parkinson, and A. M. Owen, The role of the basal ganglia in learning and memory: Neuropsychological studies, Behavioural Brain Research, vol.199, issue.1, pp.53-60, 2009.
DOI : 10.1016/j.bbr.2008.11.020

C. C. Guo, F. Kurth, J. Zhou, E. A. Mayer, S. B. Eickhoff et al., One-year test???retest reliability of intrinsic connectivity network fMRI in older adults, NeuroImage, vol.61, issue.4, pp.1471-1483, 2012.
DOI : 10.1016/j.neuroimage.2012.03.027

E. M. Haacke, N. Y. Cheng, M. J. House, Q. Liu, J. Neelavalli et al., Imaging iron stores in the brain using magnetic resonance imaging, Magnetic Resonance Imaging, vol.23, issue.1, pp.1-25, 2005.
DOI : 10.1016/j.mri.2004.10.001

G. Helms, B. Draganski, R. Frackowiak, J. Ashburner, and N. Weiskopf, Improved segmentation of deep brain grey matter structures using magnetization transfer (MT) parameter maps, NeuroImage, vol.47, issue.1, pp.194-198, 2009.
DOI : 10.1016/j.neuroimage.2009.03.053

J. P. Ioannidis, How to Make More Published Research True, PLoS Medicine, vol.51, issue.7145, 2014.
DOI : 10.1371/journal.pmed.1001747.t002

A. C. Ionan, M. Y. Polley, L. M. Mcshane, and K. K. Dobbin, Comparison of confidence interval methods for an intra-class correlation coefficient (ICC), BMC Medical Research Methodology, vol.19, issue.1, 2014.
DOI : 10.1214/088342304000000017

X. Liang, J. Wang, C. Yan, N. Shu, K. Xu et al., Effects of Different Correlation Metrics and Preprocessing Factors on Small-World Brain Functional Networks: A Resting-State Functional MRI Study, PLoS ONE, vol.103, issue.3, 2012.
DOI : 10.1371/journal.pone.0032766.s014

X. H. Liao, M. R. Xia, T. Xu, Z. J. Dai, X. Y. Cao et al., Functional brain hubs and their test???retest reliability: A multiband resting-state functional MRI study, NeuroImage, vol.83, pp.969-982, 2013.
DOI : 10.1016/j.neuroimage.2013.07.058

C. Malherbe, A. Messe, E. Bardinet, M. Pelegrini-issac, V. Perlbarg et al., Combining Spatial Independent Component Analysis with Regression to Identify the Subcortical Components of Resting-State fMRI Functional Networks, Brain Connectivity, vol.4, issue.3, pp.181-192, 2014.
DOI : 10.1089/brain.2013.0160

K. O. Mcgraw and S. P. Wong, Forming inferences about some intraclass correlation coefficients., Psychological Methods, vol.1, issue.1, pp.30-46, 1996.
DOI : 10.1037/1082-989X.1.1.30

N. Metropolis and S. Ulam, The Monte Carlo Method, Journal of the American Statistical Association, vol.44, issue.247, pp.335-341, 1949.
DOI : 10.1080/01621459.1949.10483310

F. A. Middleton and P. L. Strick, Basal Ganglia Output and Cognition: Evidence from Anatomical, Behavioral, and Clinical Studies, Brain and Cognition, vol.42, issue.2, pp.183-200, 2000.
DOI : 10.1006/brcg.1999.1099

R. Müller and P. Büttner, A critical discussion of intraclass correlation coefficients, Statistics in Medicine, vol.19, issue.23-24, pp.2465-2476, 1994.
DOI : 10.1002/sim.4780132310

K. Murphy, R. M. Birn, D. A. Handwerker, T. B. Jones, and P. A. Bandettini, The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced?, NeuroImage, vol.44, issue.3, pp.893-905, 2009.
DOI : 10.1016/j.neuroimage.2008.09.036

S. Nakagawa and H. Schielzeth, Repeatability for gaussian and nongaussian data: a practical guide for biologists, Biol Rev Camb Philos Soc, vol.85, pp.935-956, 2010.

O. Reilly, J. X. Beckmann, C. F. Tomassini, V. Ramnani, N. Johansen-berg et al., Distinct and Overlapping Functional Zones in the Cerebellum Defined by Resting State Functional Connectivity, Cerebral Cortex, vol.20, issue.4, pp.953-965, 1991.
DOI : 10.1093/cercor/bhp157

M. Rubinov and O. Sporns, Complex network measures of brain connectivity: Uses and interpretations, NeuroImage, vol.52, issue.3, pp.1059-1069, 2010.
DOI : 10.1016/j.neuroimage.2009.10.003

Z. S. Saad, S. J. Gotts, K. Murphy, G. Chen, H. J. Jo et al., Trouble at Rest: How Correlation Patterns and Group Differences Become Distorted After Global Signal Regression, Brain Connectivity, vol.2, issue.1, pp.25-32, 2012.
DOI : 10.1089/brain.2012.0080

M. P. Sampat, G. J. Whitman, T. W. Stephens, L. D. Broemeling, N. A. Heger et al., The reliability of measuring physical characteristics of spiculated masses on mammography, The British Journal of Radiology, vol.79, issue.special_issue_2, pp.134-140, 2006.
DOI : 10.1259/bjr/96723280

T. D. Satterthwaite, D. H. Wolf, D. R. Roalf, K. Ruparel, G. Erus et al., Linked Sex Differences in Cognition and Functional Connectivity in Youth, Cerebral Cortex, vol.25, issue.9, pp.2383-2394, 2015.
DOI : 10.1093/cercor/bhu036

J. D. Schmahmann, J. Doyon, D. Mcdonald, C. Holmes, K. Lavoie et al., Three-Dimensional MRI Atlas of the Human Cerebellum in Proportional Stereotaxic Space, NeuroImage, vol.10, issue.3, pp.233-260, 1999.
DOI : 10.1006/nimg.1999.0459

A. J. Schwarz and J. Mcgonigle, Negative edges and soft thresholding in complex network analysis of resting state functional connectivity data, NeuroImage, vol.55, issue.3, pp.1132-1146, 2011.
DOI : 10.1016/j.neuroimage.2010.12.047

W. R. Shirer, H. Jiang, C. M. Price, B. Ng, and M. D. Greicius, Optimization of rs-fMRI Pre-processing for Enhanced Signal-Noise Separation, Test-Retest Reliability, and Group Discrimination, NeuroImage, vol.117, pp.67-79, 2015.
DOI : 10.1016/j.neuroimage.2015.05.015

P. E. Shrout and J. L. Fleiss, Intraclass correlations: Uses in assessing rater reliability., Psychological Bulletin, vol.86, issue.2, pp.420-428, 1979.
DOI : 10.1037/0033-2909.86.2.420

S. M. Smith, C. F. Beckmann, J. Andersson, E. J. Auerbach, J. Bijsterbosch et al., Resting-state fMRI in the Human Connectome Project, NeuroImage, vol.80, pp.144-168, 2013.
DOI : 10.1016/j.neuroimage.2013.05.039

J. Song, A. S. Desphande, T. B. Meier, D. L. Tudorascu, S. Vergun et al., Age-Related Differences in Test-Retest Reliability in Resting-State Brain Functional Connectivity, PLoS ONE, vol.22, issue.12, 2012.
DOI : 10.1371/journal.pone.0049847.s010

C. J. Stoodley and J. D. Schmahmann, Functional topography in the human cerebellum: A meta-analysis of neuroimaging studies, NeuroImage, vol.44, issue.2, pp.489-501, 2009.
DOI : 10.1016/j.neuroimage.2008.08.039

C. J. Stoodley, E. M. Valera, and J. D. Schmahmann, Functional topography of the cerebellum for motor and cognitive tasks: An fMRI study, NeuroImage, vol.59, issue.2, pp.1560-1570, 2012.
DOI : 10.1016/j.neuroimage.2011.08.065

B. Thirion, P. Pinel, S. Mériaux, A. Roche, S. Dehaene et al., Analysis of a large fMRI cohort: Statistical and methodological issues for group analyses, NeuroImage, vol.35, issue.1, 2007.
DOI : 10.1016/j.neuroimage.2006.11.054
URL : https://hal.archives-ouvertes.fr/cea-00371089

D. Tomasi, E. Shokri-kojori, and N. D. Volkow, High-Resolution Functional Connectivity Density: Hub Locations, Sensitivity, Specificity, Reproducibility, and Reliability, Cerebral Cortex, vol.26, issue.7, 2015.
DOI : 10.1093/cercor/bhv171

D. Tomasi and N. D. Volkow, Laterality Patterns of Brain Functional Connectivity: Gender Effects, Cerebral Cortex, vol.22, issue.6, pp.1455-1462, 2012.
DOI : 10.1093/cercor/bhr230

N. Tzourio-mazoyer, B. Landeau, D. Papathanassiou, F. Crivello, O. Etard et al., Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain, NeuroImage, vol.15, issue.1, pp.273-289, 2002.
DOI : 10.1006/nimg.2001.0978

K. R. Van-dijk, T. Hedden, A. Venkataraman, K. C. Evans, S. W. Lazar et al., Intrinsic Functional Connectivity As a Tool For Human Connectomics: Theory, Properties, and Optimization, Journal of Neurophysiology, vol.103, issue.1, pp.297-321, 2009.
DOI : 10.1152/jn.00783.2009

J. H. Wang, X. N. Zuo, S. Gohel, M. P. Milham, B. B. Biswal et al., Graph Theoretical Analysis of Functional Brain Networks: Test-Retest Evaluation on Short- and Long-Term Resting-State Functional MRI Data, PLoS ONE, vol.424, issue.242, 2011.
DOI : 10.1371/journal.pone.0021976.s015

T. Welton, D. Kent, D. Auer, and R. Dineen, Reproducibility of graphtheoretic brain network metrics: A systematic review, Brain Connectivity, vol.5, 2015.

C. T. Whitlow, R. Casanova, and J. A. Maldjian, Effect of Resting-State Functional MR Imaging Duration on Stability of Graph Theory Metrics of Brain Network Connectivity, Radiology, vol.259, issue.2, 2011.
DOI : 10.1148/radiol.11101708

D. Yin, F. Song, D. Xu, L. Sun, W. Men et al., Altered topological properties of the cortical motor-related network in patients with subcortical stroke revealed by graph theoretical analysis, Human Brain Mapping, vol.34, issue.6825, pp.3343-3359, 2014.
DOI : 10.1002/hbm.22406

A. Zalesky, A. Fornito, I. H. Harding, L. Cocchi, M. Yücel et al., Whole-brain anatomical networks: Does the choice of nodes matter?, NeuroImage, vol.50, issue.3, pp.970-983, 2010.
DOI : 10.1016/j.neuroimage.2009.12.027

X. N. Zuo and X. X. Xing, Test-retest reliabilities of resting-state FMRI measurements in human brain functional connectomics: A systems neuroscience perspective, Neuroscience & Biobehavioral Reviews, vol.45, p.24875392, 2014.
DOI : 10.1016/j.neubiorev.2014.05.009