A. M. Winkler, P. Kochunov, J. Blangero, L. Almasy, K. Zilles et al., Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies, NeuroImage, vol.53, pp.1135-1146, 2010.

J. L. Stein, S. E. Medland, A. A. Vasquez, D. P. Hibar, R. E. Senstad et al., Identification of common variants associated with human hippocampal and intracranial volumes, Nat Genet, vol.44, pp.552-561, 2012.
URL : https://hal.archives-ouvertes.fr/pasteur-01967151

G. Blokland, G. I. De-zubicaray, K. L. Mcmahon, and M. J. Wright, Genetic and Environmental Influences on Neuroimaging Phenotypes: A Meta-Analytical Perspective on Twin Imaging Studies, Twin Res Hum Genet, vol.15, pp.351-371, 2012.

N. Jahanshad, A. D. Lee, M. Barysheva, K. L. Mcmahon, G. I. De-zubicaray et al., Genetic influences on brain asymmetry: a DTI study of 374 twins and siblings, NeuroImage, vol.52, pp.455-469, 2010.

D. G. Amaral, C. M. Schumann, and C. W. Nordahl, Neuroanatomy of autism, Trends Neurosci, vol.31, pp.137-145, 2008.
DOI : 10.1016/j.tins.2007.12.005

R. G. Steen, C. Mull, R. Mcclure, R. M. Hamer, A. Jeffrey et al., Brain volume in first-episode schizophrenia: Systematic review and meta-analysis of magnetic resonance imaging studies, Br J Psychiatry, vol.188, pp.510-518, 2012.

J. C. Bis, C. Decarli, A. V. Smith, F. Van-der-lijn, F. Crivello et al., Common variants at 12q14 and 12q24 are associated with hippocampal volume, Nat Genet, vol.44, pp.545-551, 2012.
URL : https://hal.archives-ouvertes.fr/hal-01157821

M. A. Ikram, M. Fornage, A. V. Smith, S. Seshadri, R. Schmidt et al., Common variants at 6q22 and 17q21 are associated with intracranial volume, Nat Genet, vol.44, pp.539-544, 2012.
DOI : 10.1038/ng0612-732c

URL : https://www.nature.com/articles/ng0612-732c.pdf

J. Yang, B. Benyamin, B. P. Mcevoy, S. Gordon, A. K. Henders et al., Common SNPs explain a large proportion of the heritability for human height, Nat Genet, vol.42, pp.565-569, 2010.

J. Yang, L. R. Pasquale, E. Boerwinkle, N. Caporaso, and J. M. Cunningham, Genome partitioning of genetic variation for complex traits using common SNPs, Nat Genet, vol.43, pp.519-525, 2011.

G. Schumann, E. Loth, T. Banaschewski, A. Barbot, G. Barker et al., The IMAGEN study: reinforcement-related behaviour in normal brain function and psychopathology, Mol Psychiatry, vol.15, pp.1128-1139, 2010.

M. Jenkinson, P. Bannister, M. Brady, and S. Smith, Improved optimization for the robust and accurate linear registration and motion correction of brain images, NeuroImage, vol.17, pp.825-841, 2002.

S. M. Smith, M. Jenkinson, M. W. Woolrich, C. F. Beckmann, T. Behrens et al., Advances in functional and structural MR image analysis and implementation as FSL, NeuroImage, vol.23, issue.1, pp.208-219, 2004.
DOI : 10.1016/j.neuroimage.2004.07.051

URL : http://www.fmrib.ox.ac.uk/analysis/techrep/tr04ss2/tr04ss2.pdf

R. L. Buckner, D. Head, J. Parker, A. F. Fotenos, D. Marcus et al., A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume, NeuroImage, vol.23, pp.724-738, 2004.

R. W. Cox, AFNI: software for analysis and visualization of functional magnetic resonance neuroimages, Comput Biomed Res, vol.29, pp.162-173, 1996.

Y. Zhang, M. Brady, and S. Smith, Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm, IEEE Trans Med Imaging, vol.20, pp.45-57, 2001.

B. Patenaude, S. M. Smith, D. N. Kennedy, and M. Jenkinson, A Bayesian model of shape and appearance for subcortical brain segmentation, NeuroImage, vol.56, pp.907-922, 2011.

S. Purcell, N. B. Todd-brown, K. Thomas, L. Ferreira, M. Bender et al., PLINK: a tool set for whole-genome association and population-based linkage analyses, Am J Hum Genet, vol.81, pp.559-575, 2007.
DOI : 10.1086/519795

URL : https://doi.org/10.1086/519795

S. H. Lee, J. Yang, M. E. Goddard, P. M. Visscher, and N. R. Wray, Estimation of pleiotropy between complex diseases using single-nucleotide polymorphism-derived genomic relationships and restricted maximum likelihood, Bioinforma Oxf Engl, vol.28, pp.2540-2542, 2012.

M. A. Carskadon and C. Acebo, A self-administered rating scale for pubertal development, J Adolesc Health Off Publ Soc Adolesc Med, vol.14, pp.190-195, 1993.
DOI : 10.1016/1054-139x(93)90004-9

D. H. Alexander, J. Novembre, and K. Lange, Fast model-based estimation of ancestry in unrelated individuals, Genome Res, vol.19, pp.1655-1664, 2009.

, International HapMap Consortium. The International HapMap Project, Nature, vol.426, pp.789-796, 2003.

A. L. Price, N. J. Patterson, R. M. Plenge, M. E. Weinblatt, N. A. Shadick et al., Principal components analysis corrects for stratification in genome-wide association studies, Nat Genet, vol.38, pp.904-909, 2006.

C. Tian, R. M. Plenge, M. Ransom, A. Lee, P. Villoslada et al., Analysis and application of European genetic substructure using 300K SNP information, PLoS Genet, vol.4, pp.4-4, 2008.

P. M. Visscher, G. Hemani, A. Vinkhuyzen, G. Chen, S. H. Lee et al., Statistical Power to Detect Genetic (Co)Variance of Complex Traits Using SNP Data in Unrelated Samples, PLoS Genet, vol.10, p.1004269, 2014.

G. Davies, A. Tenesa, A. Payton, J. Yang, S. E. Harris et al., Genome-wide association studies establish that human intelligence is highly heritable and polygenic, Mol Psychiatry, vol.16, pp.996-1005, 2011.

S. Raychaudhuri, J. Korn, S. Mccarroll, . International-schizophrenia-consortium, D. Altshuler et al., Accurately assessing the risk of schizophrenia conferred by rare copy-number variation affecting genes with brain function, PLoS Genet, vol.6, p.1001097, 2010.

S. H. Lee, T. R. Decandia, S. Ripke, J. Yang, P. F. Sullivan et al., Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs, Nat Genet, vol.44, pp.247-250, 2012.

W. S. Kremen, E. Prom-wormley, M. S. Panizzon, L. T. Eyler, B. Fischl et al., Genetic and environmental influences on the size of specific brain regions in midlife: the VETSA MRI study, NeuroImage, vol.49, pp.1213-1223, 2010.

U. Yoon, D. Perusse, J. Lee, and A. C. Evans, Genetic and environmental influences on structural variability of the brain in pediatric twin: deformation based morphometry, Neurosci Lett, vol.493, pp.8-13, 2011.

D. Braber, A. Bohlken, M. M. Brouwer, R. M. Van-'t-ent, D. Kanai et al., Heritability of subcortical brain measures: a perspective for future genome-wide association studies, NeuroImage, vol.83, pp.98-102, 2013.

S. M. Purcell, J. L. Moran, M. Fromer, D. Ruderfer, N. Solovieff et al., A polygenic burden of rare disruptive mutations in schizophrenia, Nature, vol.506, pp.185-190, 2014.

M. R. Robinson, N. R. Wray, and P. M. Visscher, Explaining additional genetic variation in complex traits, Trends Genet, vol.30, pp.124-132, 2014.

M. Trzaskowski, P. S. Dale, and R. Plomin, No genetic influence for childhood behavior problems from DNA analysis, J Am Acad Child Adolesc Psychiatry, vol.52, pp.1048-1056, 2013.

E. H. Cook and S. W. Scherer, Copy-number variations associated with neuropsychiatric conditions, Nature, vol.455, pp.919-923, 2008.

. Cross-disorder, Group of the Psychiatric Genomics Consortium. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs, Nat Genet, vol.45, pp.984-994, 2013.

S. H. Lee, D. Harold, D. R. Nyholt, M. E. Goddard, K. T. Zondervan et al., Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis, Hum Mol Genet, vol.22, pp.832-841, 2013.

L. Klei, S. J. Sanders, M. T. Murtha, V. Hus, J. K. Lowe et al., Common genetic variants, acting additively, are a major source of risk for autism, Mol Autism, vol.3, p.9, 2012.

J. Park, S. Wacholder, M. H. Gail, U. Peters, K. B. Jacobs et al., Estimation of effect size distribution from genome-wide association studies and implications for future discoveries, Nat Genet, vol.42, pp.570-575, 2010.

A. Meyer-lindenberg and D. R. Weinberger, Intermediate phenotypes and genetic mechanisms of psychiatric disorders, Nat Rev Neurosci, vol.7, pp.818-827, 2006.