C. Barnes, Secrets of aging: What does a normally aging brain look like?, F1000 Biology Reports, vol.3, issue.22, 2011.
DOI : 10.3410/B3-22

S. N. Burke and C. A. Barnes, Neural plasticity in the ageing brain, Nature Reviews Neuroscience, vol.16, issue.1, pp.30-40, 2006.
DOI : 10.1016/0165-0270(86)90050-6

A. Chincarini, P. Bosco, and P. Calvini, Local MRI analysis approach in the diagnosis of early and prodromal Alzheimer's disease, NeuroImage, vol.58, issue.2, pp.469-480, 2011.
DOI : 10.1016/j.neuroimage.2011.05.083

. Bryan, Sex differences in brain aging: a quantitative magnetic resonance imaging study, Arch Neurol, vol.2, issue.55, pp.169-179, 1998.

C. E. Coffey, J. A. Saxton, G. Ratcliff, R. N. Bryan, and J. F. Lucke, Relation of education to brain size in normal aging: Implications for the reserve hypothesis, Neurology, vol.53, issue.1, pp.189-196, 1999.
DOI : 10.1212/WNL.53.1.189

R. Cuingnet, E. Gerardin, J. Tessieras, G. Auzias, S. Lehricy et al., Automatic classification of patients with Alzheimers disease from structural MRI: a comparison of ten methods using the ADNI database, NeuroImage, issue.2, pp.56766-781, 2011.

C. Davatzikos, F. Xu, Y. An, Y. Fan, and S. M. Resnik, Longitudinal progression of Alzheimer's-like patterns of atrophy in normal older adults: the SPARE-AD index, Brain, vol.132, issue.8, pp.1322026-2035, 2009.
DOI : 10.1093/brain/awp091

G. M. Fitzmaurice, N. M. Laird, and J. H. Ware, Applied Longitudinal Analysis, 2011.

A. M. Fjell, K. B. Walhovd, C. F. Notestine, L. K. Mcevoy, D. J. Hagler et al., One-Year Brain Atrophy Evident in Healthy Aging, Journal of Neuroscience, vol.29, issue.48, pp.2915223-15231, 2009.
DOI : 10.1523/JNEUROSCI.3252-09.2009

A. M. Fjell, K. B. Walhovd, and C. F. Notestine, Brain atrophy in healthy aging is related to csf levels of A?1-42, Cereb. Cortex, pp.20-29, 2010.

N. Fox and J. M. Schott, Imaging cerebral atrophy: normal ageing to Alzheimer's disease, The Lancet, vol.363, issue.9406, pp.392-394, 2004.
DOI : 10.1016/S0140-6736(04)15441-X

K. Franke, G. Ziegler, S. Klöppel, and C. Gaser, Estimating the age of healthy subjects from T1-weighted MRI scans using kernel methods: Exploring the influence of various parameters, NeuroImage, vol.50, issue.3, pp.883-892, 2010.
DOI : 10.1016/j.neuroimage.2010.01.005

G. B. Frisoni, N. C. Fox, C. R. Jack-jr, P. Scheltens, and P. M. Thompson, The clinical use of structural MRI in Alzheimer disease, Nature Reviews Neurology, vol.15, issue.2, pp.67-77, 2010.
DOI : 10.1038/nrneurol.2009.215

C. Good, R. Scahill, N. C. Fox, J. Ashburner, K. J. Friston et al., Automatic Differentiation of Anatomical Patterns in the Human Brain: Validation with Studies of Degenerative Dementias, NeuroImage, vol.17, issue.1, pp.29-46, 2002.
DOI : 10.1006/nimg.2002.1202

A. Guimond, J. Meunier, and J. P. Thirion, Average Brain Models: A Convergence Study, Computer Vision and Image Understanding, vol.77, issue.2, pp.77-79, 2000.
DOI : 10.1006/cviu.1999.0815

URL : https://hal.archives-ouvertes.fr/inria-00615030

P. R. Hof and C. V. Mobbs, Handbook of the neuroscience of aging, 1984.

X. Hua, A. D. Leow, and S. Lee, 3D characterization of brain atrophy in Alzheimer's disease and mild cognitive impairment using tensor-based morphometry, NeuroImage, vol.41, issue.1, pp.19-34, 2008.
DOI : 10.1016/j.neuroimage.2008.02.010

M. Lorenzi, N. Ayache, G. B. Frisoni, and X. Pennec, LCC-Demons: A robust and accurate symmetric diffeomorphic registration algorithm, NeuroImage, vol.81, issue.81, pp.470-83, 2013.
DOI : 10.1016/j.neuroimage.2013.04.114

URL : https://hal.archives-ouvertes.fr/hal-00819895

A. R. Luft, M. Skalej, J. B. Schulk, D. Welte, R. Kolb et al., Patterns of Age-related Shrinkage in Cerebellum and Brainstem Observed In Vivo Using Three-dimensional MRI Volumetry, Cerebral Cortex, vol.9, issue.7, pp.712-721, 1999.
DOI : 10.1093/cercor/9.7.712

C. D. Abner, L. J. Smith, R. J. Van-eldik, S. W. Kryscio, and . Scheff, Alzheimer's disease is not " brain aging " : neuropathological, genetic, and epidemiological human studies, Acta Neuropathol, vol.121, issue.5, pp.571-587, 2011.

B. Ridha, J. Barnes, J. Bartlett, A. Godbolt, T. Pepple et al., Tracking atrophy progression in familial Alzheimer's disease: a serial MRI study, The Lancet Neurology, vol.5, issue.10, pp.828-834, 2006.
DOI : 10.1016/S1474-4422(06)70550-6

C. R. Harvey, M. W. Jack, A. J. Weiner, and . Saykin, Longitudinal MRI atrophy biomarkers: Relationship to conversion in the ADNI cohort, Neurobiol Aging, issue.9, pp.311401-1418, 2010.

M. N. Samtani, M. Farnum, V. Lobanov, E. Yang, N. Raghavan et al., An Improved Model for Disease Progression in Patients From the Alzheimer's Disease Neuroimaging Initiative, The Journal of Clinical Pharmacology, vol.74, issue.2, pp.629-644, 2012.
DOI : 10.1177/0091270011405497

R. I. Scahill, J. M. Schott, J. M. Stevens, M. N. Rossor, and N. C. Fox, Mapping the evolution of regional atrophy in Alzheimer's disease: Unbiased analysis of fluid-registered serial MRI, Proceedings of the National Academy of Sciences, vol.99, issue.7, pp.4703-4707, 2002.
DOI : 10.1073/pnas.052587399

E. R. Sowell, B. S. Peterson, P. M. Thompson, S. E. Welcome, A. L. Henkenius et al., Mapping cortical change across the human life span, Nature Neuroscience, vol.6, issue.3, pp.309-315, 2003.
DOI : 10.1038/nn1008

P. Thompson, K. M. Ayashi, G. Zubicaray, A. L. Janke, S. E. Rose et al., Dynamics of gray matter loss in Alzheimer's disease, The Journal of Neuroscience, vol.23, pp.994-1005, 2003.

A. Torvik, S. Torp, and C. F. Lindboe, Atrophy of the cerebellar vermis in ageing, Journal of the Neurological Sciences, vol.76, issue.2-3, pp.283-294, 1986.
DOI : 10.1016/0022-510X(86)90176-0

D. Tosun, N. Schuff, and D. Truran-sacrey, Relations between brain tissue loss, CSF biomarkers, and the ApoE genetic profile: a longitudinal MRI study, Neurobiology of Aging, vol.31, issue.8, pp.31-39, 2010.
DOI : 10.1016/j.neurobiolaging.2010.04.030

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, 2001.
DOI : 10.1006/nimg.2001.0978

E. Yang, M. Farnum, V. Lobanov, T. Schultz, N. Raghavan et al., Quantifying the pathophysiological timeline of Alzheimer's disease, Journal of Alzheimer's Disease, vol.26, issue.4, pp.745-753, 2011.

Y. Zhang, M. Brady, and S. M. Smith, Segmentation of brain mr images through The parallel transport is a mathematical tool used in the context of diffeomorphic registration for resampling a given velocity field in the template geometry [Lorenzi and Pennec, 2013.