C. Berr, J. Wancata, and K. Ritchie, Prevalence of dementia in the elderly in Europe, European Neuropsychopharmacology, vol.15, issue.4, pp.463-471, 2005.
DOI : 10.1016/j.euroneuro.2005.04.003

D. Blazer, Depression in Late Life: Review and Commentary, The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, vol.58, issue.3, pp.249-265, 2003.
DOI : 10.1093/gerona/58.3.M249

C. Huang, Z. Wang, Y. Li, Y. Xie, and Q. Liu, Cognitive function and risk for depression in old age: a meta-analysis of published literature, International Psychogeriatrics, vol.101, issue.04, pp.516-525, 2011.
DOI : 10.1002/gps.1135

D. Steffens, G. Fisher, K. Langa, G. Potter, and B. Plassman, Prevalence of depression among older Americans: the Aging, Demographics and Memory Study, International Psychogeriatrics, vol.49, issue.05, pp.879-888, 2009.
DOI : 10.1097/01.JGP.0000218218.47279.db

R. Brookmeyer, E. Johnson, K. Ziegler-graham, and H. Arrighi, Forecasting the global burden of Alzheimer???s disease, Alzheimer's & Dementia, vol.3, issue.3, pp.186-191, 2007.
DOI : 10.1016/j.jalz.2007.04.381

J. Spijker and J. Macinnes, Population ageing: the timebomb that isn't?, BMJ, vol.347, issue.nov12 1, p.6598
DOI : 10.1136/bmj.f6598

M. Marmot and E. Brunner, Cohort Profile: The Whitehall II study, International Journal of Epidemiology, vol.34, issue.2, pp.251-256, 2005.
DOI : 10.1093/ije/dyh372

D. Goldberg and P. Williams, A user' s guide to the general health questionnaire. London: GL Assessment Limited, 2006.

R. Hirschfeld, The Mood Disorder Questionnaire, The Primary Care Companion to The Journal of Clinical Psychiatry, vol.04, issue.01, pp.9-11, 2002.
DOI : 10.4088/PCC.v04n0104

L. Radloff, C. The, and . Scale, The CES-D Scale: A Self-Report Depression Scale for Research in the General Population, Applied Psychological Measurement, vol.1, issue.3, pp.385-401, 1977.
DOI : 10.1177/014662167700100306

C. Spielberger, State-Trait Anxiety Inventory, 1983.
DOI : 10.1002/9780470479216.corpsy0943

C. Spielberger, Theory and Research on Anxiety, Anxiety and behavior. Edited by Spielberger CD, 1966.
DOI : 10.1016/B978-1-4832-3131-0.50006-8

A. Stewart, K. Mills, A. King, W. Haskell, D. Gillis et al., CHAMPS Physical Activity Questionnaire for Older Adults: outcomes for interventions, Medicine and Science in Sports and Exercise, vol.33, issue.7, pp.1126-1141, 2001.
DOI : 10.1097/00005768-200107000-00010

E. Deci and R. Ryan, Intrinsic Motivation and Self-Determination in Human Behavior, 1985.
DOI : 10.1007/978-1-4899-2271-7

D. Markland, Self-Determination Moderates the Effects of Perceived Competence on Intrinsic Motivation in an Exercise Setting, Journal of Sport and Exercise Psychology, vol.21, issue.4, pp.351-361, 1999.
DOI : 10.1123/jsep.21.4.351

D. Buysse, C. Reynolds, T. Monk, S. Berman, and D. Kupfer, The Pittsburgh sleep quality index: A new instrument for psychiatric practice and research, Psychiatry Research, vol.28, issue.2, pp.193-213, 1989.
DOI : 10.1016/0165-1781(89)90047-4

C. Jenkins, B. Stanton, S. Niemcryk, and R. Rose, A scale for the estimation of sleep problems in clinical research, Journal of Clinical Epidemiology, vol.41, issue.4, pp.313-321, 1988.
DOI : 10.1016/0895-4356(88)90138-2

M. Scheier, C. Carver, and M. Bridges, Distinguishing optimism from neuroticism (and trait anxiety, self-mastery, and self-esteem): A reevaluation of the Life Orientation Test., Journal of Personality and Social Psychology, vol.67, issue.6, pp.1063-1078, 1994.
DOI : 10.1037/0022-3514.67.6.1063

T. Brugha, P. Bebbington, C. Tennant, and J. Hurry, The List of Threatening Experiences: a subset of 12 life event categories with considerable longterm contextual threat, Psychol Med, vol.15, issue.1, pp.189-194, 1985.
DOI : 10.1037/t30128-000

T. Brugha and D. Cragg, The List of Threatening Experiences: the reliability and validity of a brief life events questionnaire, Acta Psychiatrica Scandinavica, vol.20, issue.1, pp.77-81, 1990.
DOI : 10.1037/h0026256

S. Taylor and T. Seeman, Psychosocial Resources and the SES-Health Relationship, Annals of the New York Academy of Sciences, vol.896, issue.1, pp.210-225, 1999.
DOI : 10.1111/j.1749-6632.1999.tb08117.x

D. Berle, V. Starcevic, K. Moses, A. Hannan, D. Milicevic et al., Preliminary validation of an ultra-brief version of the Penn State Worry Questionnaire, Clinical Psychology & Psychotherapy, vol.28, issue.Suppl. 20, pp.339-346, 2011.
DOI : 10.1002/cpp.724

G. Briggs and R. Nebes, Patterns of Hand Preference in a Student Population, Cortex, vol.11, issue.3, pp.230-238, 1975.
DOI : 10.1016/S0010-9452(75)80005-0

M. First, M. Gibbon, R. Spitzer, and J. Williams, User's Guide for the Structured Clinical Interview for DSM-IV-TR Axis I Disorders -Research Version -(SCID-I for DSM-IV-TR Revision, 2002.

M. Hamilton, A RATING SCALE FOR DEPRESSION, Journal of Neurology, Neurosurgery & Psychiatry, vol.23, issue.1, pp.56-62, 1960.
DOI : 10.1136/jnnp.23.1.56

R. Young, J. Biggs, V. Ziegler, and D. Meyer, A rating scale for mania: reliability, validity and sensitivity, The British Journal of Psychiatry, vol.133, issue.5, pp.429-435, 1978.
DOI : 10.1192/bjp.133.5.429

W. Goodman, L. Price, S. Rasmussen, C. Mazure, R. Fleischmann et al., The Yale-Brown Obsessive Compulsive Scale, Archives of General Psychiatry, vol.46, issue.11, pp.461006-1011, 1989.
DOI : 10.1001/archpsyc.1989.01810110048007

W. Goodman, L. Price, S. Rasmussen, C. Mazure, P. Delgado et al., The Yale-Brown Obsessive Compulsive Scale, Archives of General Psychiatry, vol.46, issue.11, pp.461012-1016, 1989.
DOI : 10.1001/archpsyc.1989.01810110054008

J. Ewing, Detecting Alcoholism, JAMA, vol.252, issue.14, pp.1905-1907, 1984.
DOI : 10.1001/jama.1984.03350140051025

J. Overall and D. Gorham, THE BRIEF PSYCHIATRIC RATING SCALE, Psychological Reports, vol.15, issue.3, pp.799-812, 1962.
DOI : 10.2466/pr0.1962.10.3.799

Z. Nasreddine, N. Phillips, V. Bedirian, S. Charbonneau, V. Whitehead et al., The Montreal Cognitive Assessment, MoCA: A Brief Screening Tool For Mild Cognitive Impairment, Journal of the American Geriatrics Society, vol.48, issue.4, pp.695-699, 2005.
DOI : 10.1111/j.1532-5415.2005.53221.x

T. Smith, N. Gildeh, and C. Holmes, The Montreal Cognitive Assessment: Validity and Utility in a Memory Clinic Setting, The Canadian Journal of Psychiatry, vol.149, issue.1, pp.329-332, 2007.
DOI : 10.1111/j.1532-5415.2005.53221.x

M. Lezak, D. Howieson, and D. Loring, Neuropsychological Assessment, 2004.

E. Gaudino, M. Geisler, and N. Squires, Construct validity in the trail making test: What makes part B harder?, Journal of Clinical and Experimental Neuropsychology, vol.17, issue.4, pp.529-535, 1995.
DOI : 10.2466/pms.1963.16.3.681

T. Tombaugh, Trail Making Test A and B: Normative data stratified by age and education, Archives of Clinical Neuropsychology, vol.19, issue.2, pp.203-214, 2004.
DOI : 10.1016/S0887-6177(03)00039-8

J. Meyers and K. Meyers, Rey complex figure test and recognition trial: Professional manual, Psychological Assessment Resources, 1995.

J. Meyers and K. Meyers, The Rey Complex Figure and the Recognition Trial under four different administration procedures, Clin Neuropsychol, vol.9, pp.65-67, 1995.

J. Liberman, W. Stewart, O. Seines, and B. Gordon, Rater agreement for the Rey-Osterrieth Complex Figure Test, Journal of Clinical Psychology, vol.7, issue.4, pp.615-624, 1994.
DOI : 10.1002/1097-4679(199407)50:4<615::AID-JCLP2270500419>3.0.CO;2-R

M. Cherrier, M. Mendez, D. M. Perryman, and K. , Performance on the Rey- Osterrieth Complex Figure Test in Alzheimer disease and vascular dementia, Neuropsychiatry Neuropsychol Behav Neurol, vol.12, issue.2, pp.95-101, 1999.

S. Hsieh, S. Schubert, C. Hoon, E. Mioshi, and J. Hodges, Validation of the Addenbrooke's Cognitive Examination III in Frontotemporal Dementia and Alzheimer's Disease, Dementia and Geriatric Cognitive Disorders, vol.36, issue.3-4, pp.3-4242
DOI : 10.1159/000351671

E. Mioshi, K. Dawson, J. Mitchell, R. Arnold, and J. Hodges, The Addenbrooke's Cognitive Examination Revised (ACE-R): a brief cognitive test battery for dementia screening, International Journal of Geriatric Psychiatry, vol.6, issue.11, pp.1078-1085, 2006.
DOI : 10.1002/gps.1610

J. Brandt, The hopkins verbal learning test: Development of a new memory test with six equivalent forms, Clinical Neuropsychologist, vol.5, issue.2, pp.125-142, 1991.
DOI : 10.1080/00223980.1945.9917223

A. Shapiro, R. Benedict, D. Schretlen, and J. Brandt, Construct and Concurrent Validity of the Hopkins Verbal Learning Test ??? Revised, The Clinical Neuropsychologist, vol.13, issue.3, pp.348-358, 1999.
DOI : 10.1076/clin.13.3.348.1749

S. Woods, J. Scott, E. Conover, T. Marcotte, R. Heaton et al., Test-Retest Reliability of Component Process Variables Within the Hopkins Verbal Learning Test-Revised, Assessment, vol.12, issue.1, pp.96-100, 2005.
DOI : 10.1177/1073191104270342

L. Lacritz, C. Cullum, M. Weiner, and R. Rosenberg, Comparison of the Hopkins Verbal Learning Test-Revised to the California Verbal Learning Test in Alzheimer's Disease, Applied Neuropsychology, vol.14, issue.3, pp.180-184, 2001.
DOI : 10.1016/S0887-6177(98)00004-3

O. Neil-pirozzi, T. Goldstein, R. Strangman, G. Glenn, and M. , Test-re-test reliability of the Hopkins Verbal Learning Test-Revised in individuals with traumatic brain injury, Brain Inj, vol.2012, issue.12, pp.261425-1430

E. Labarge, D. Edwards, and J. Knesevich, Performance of normal elderly on the Boston Naming Test, Brain and Language, vol.27, issue.2, pp.380-384, 1986.
DOI : 10.1016/0093-934X(86)90026-X

J. Knesevich, E. Labarge, and D. Edwards, Predictive value of the Boston naming test in mild senile dementia of the alzheimer type, Psychiatry Research, vol.19, issue.2, pp.155-161, 1986.
DOI : 10.1016/0165-1781(86)90008-9

D. Wechsler, Wechsler Adult Intelligence Scale -Fourth Edition (WAIS-IV), 2008.

T. Keiser, Schizotype and the Wechsler digit span test, Journal of Clinical Psychology, vol.2, issue.2, pp.303-306, 1975.
DOI : 10.1002/1097-4679(197504)31:2<303::AID-JCLP2270310230>3.0.CO;2-C

J. Leung, G. Lee, Y. Lam, R. Chan, and J. Wu, The use of the Digit Span Test in screening for cognitive impairment in acute medical inpatients, International Psychogeriatrics, vol.4, issue.10, pp.1569-1574, 2011.
DOI : 10.1192/bjp.bp.108.055335

D. Wechsler, Test of Premorbid Functioning UK Version (TOPF UK), 2011.

D. Royall, J. Cordes, and M. Polk, CLOX: an executive clock drawing task, Journal of Neurology, Neurosurgery & Psychiatry, vol.64, issue.5, pp.588-594, 1998.
DOI : 10.1136/jnnp.64.5.588

E. Stip, A. Sepehry, A. Prouteau, C. Briand, N. L. Lalonde et al., Cognitive discernible factors between schizophrenia and schizoaffective disorder, Brain and Cognition, vol.59, issue.3, pp.292-295, 2005.
DOI : 10.1016/j.bandc.2005.07.003

M. Majer, L. Welberg, L. Capuron, A. Miller, G. Pagnoni et al., Neuropsychological Performance in Persons With Chronic Fatigue Syndrome: Results From a Population-Based Study, Psychosomatic Medicine, vol.70, issue.7, pp.829-836, 2008.
DOI : 10.1097/PSY.0b013e31817b9793

S. Gau and W. Huang, Rapid visual information processing as a cognitive endophenotype of attention deficit hyperactivity disorder, Psychological Medicine, vol.5, issue.02, pp.435-446
DOI : 10.1192/bjp.180.4.313

J. Tiffin and E. Asher, The Purdue Pegboard: norms and studies of reliability and validity., Journal of Applied Psychology, vol.32, issue.3, pp.234-247, 1948.
DOI : 10.1037/h0061266

R. Brown, M. Jahanshahi, and C. Marsden, The execution of bimanual movements in patients with Parkinson's, Huntington's and cerebellar disease., Journal of Neurology, Neurosurgery & Psychiatry, vol.56, issue.3, pp.295-297, 1993.
DOI : 10.1136/jnnp.56.3.295

K. Pernat, A. Kritikos, J. Phillips, J. Bradshaw, R. Iansek et al., The association between clinical and quantitative indexes of Parkinsonian symptomatology, Neuropsychiatry Neuropsychol Behav Neurol, vol.9, issue.4, pp.234-241, 1996.

L. Flyckt, O. Sydow, L. Bjerkenstedt, G. Edman, E. Rydin et al., Neurological signs and psychomotor performance in patients with schizophrenia, their relatives and healthy controls, Psychiatry Research, vol.86, issue.2, pp.113-129, 1999.
DOI : 10.1016/S0165-1781(99)00027-X

I. Rapin, L. Tourk, and L. Costa, Evaluation of the Purdue Pegboard as a Screening Test for Brain Damage, Developmental Medicine & Child Neurology, vol.18, issue.1, pp.45-54, 1966.
DOI : 10.1111/j.1469-8749.1966.tb08272.x

R. Schmidt, F. Fazekas, H. Offenbacher, T. Dusek, E. Zach et al., Neuropsychologic correlates of MRI white matter hyperintensities: A study of 150 normal volunteers, Neurology, vol.43, issue.12, pp.432490-2494, 1993.
DOI : 10.1212/WNL.43.12.2490

N. Raz, F. Gunning-dixon, D. Head, J. Dupuis, and J. Acker, Neuroanatomical correlates of cognitive aging: Evidence from structural magnetic resonance imaging., Neuropsychology, vol.12, issue.1, pp.95-114, 1998.
DOI : 10.1037/0894-4105.12.1.95

N. Raz, U. Lindenberger, K. Rodrigue, K. Kennedy, D. Head et al., Regional Brain Changes in Aging Healthy Adults: General Trends, Individual Differences and Modifiers, Cerebral Cortex, vol.15, issue.11, pp.151676-1689, 2005.
DOI : 10.1093/cercor/bhi044

N. Raz, K. Rodrigue, D. Head, K. Kennedy, and J. Acker, Differential aging of the medial temporal lobe: A study of a five-year change, Neurology, vol.62, issue.3, pp.433-438, 2004.
DOI : 10.1212/01.WNL.0000106466.09835.46

M. Tisdall, A. Hess, M. Reuter, E. Meintjes, B. Fischl et al., Volumetric navigators for prospective motion correction and selective reacquisition in neuroanatomical MRI, Magnetic Resonance in Medicine, vol.25, issue.Suppl 1, pp.389-399
DOI : 10.1002/mrm.23228

A. Van-der-kouwe, T. Benner, D. Salat, and B. Fischl, Brain morphometry with multiecho MPRAGE, NeuroImage, vol.40, issue.2, pp.559-569, 2008.
DOI : 10.1016/j.neuroimage.2007.12.025

B. Patenaude, S. Smith, D. Kennedy, and M. Jenkinson, A Bayesian model of shape and appearance for subcortical brain segmentation, NeuroImage, vol.56, issue.3, pp.907-922, 2011.
DOI : 10.1016/j.neuroimage.2011.02.046

S. Mori and J. Zhang, Principles of Diffusion Tensor Imaging and Its Applications to Basic Neuroscience Research, Neuron, vol.51, issue.5, pp.527-539, 2006.
DOI : 10.1016/j.neuron.2006.08.012

S. Sotiropoulos, S. Jbabdi, J. Xu, J. Andersson, S. Moeller et al., Advances in diffusion MRI acquisition and processing in the Human Connectome Project, NeuroImage, vol.80, pp.125-168, 2013.
DOI : 10.1016/j.neuroimage.2013.05.057

J. Andersson, S. Skare, and J. Ashburner, How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging, NeuroImage, vol.20, issue.2, pp.870-888, 2003.
DOI : 10.1016/S1053-8119(03)00336-7

P. Basser, J. Mattiello, and D. Lebihan, Estimation of the Effective Self-Diffusion Tensor from the NMR Spin Echo, Journal of Magnetic Resonance, Series B, vol.103, issue.3, pp.247-254, 1994.
DOI : 10.1006/jmrb.1994.1037

URL : https://hal.archives-ouvertes.fr/hal-00349722

C. Pierpaoli, P. Jezzard, P. Basser, A. Barnett, D. Chiro et al., Diffusion tensor MR imaging of the human brain., Radiology, vol.201, issue.3, pp.637-648, 1996.
DOI : 10.1148/radiology.201.3.8939209

T. Behrens, H. Berg, S. Jbabdi, M. Rushworth, and M. Woolrich, Probabilistic diffusion tractography with multiple fibre orientations: What can we gain?, NeuroImage, vol.34, issue.1, pp.144-155, 2007.
DOI : 10.1016/j.neuroimage.2006.09.018

M. Raichle, A. Macleod, A. Snyder, W. Powers, D. Gusnard et al., A default mode of brain function, Proceedings of the National Academy of Sciences, vol.98, issue.2, pp.676-682, 2001.
DOI : 10.1073/pnas.98.2.676

S. Chen, T. Ross, W. Zhan, C. Myers, K. Chuang et al., Group independent component analysis reveals consistent resting-state networks across multiple sessions, Brain Research, vol.1239, pp.141-151, 2008.
DOI : 10.1016/j.brainres.2008.08.028

J. Damoiseaux, S. Rombouts, F. Barkhof, P. Scheltens, C. Stam et al., Consistent resting-state networks across healthy subjects, Proceedings of the National Academy of Sciences, vol.103, issue.37, pp.13848-13853, 2006.
DOI : 10.1073/pnas.0601417103

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1564249

M. Fukunaga, S. Horovitz, J. De-zwart, P. Van-gelderen, T. Balkin et al., Metabolic Origin of Bold Signal Fluctuations in the Absence of Stimuli, Journal of Cerebral Blood Flow & Metabolism, vol.8, issue.7, pp.281377-1387, 2008.
DOI : 10.1016/j.neuroimage.2003.11.025

R. Goldman, J. Stern, J. Engel, . Jr, and M. Cohen, Simultaneous EEG and fMRI of the alpha rhythm, NeuroReport, vol.13, issue.18, pp.2487-2492, 2002.
DOI : 10.1097/00001756-200212200-00022

S. Kannurpatti, B. Biswal, Y. Kim, and B. Rosen, Spatio-temporal characteristics of low-frequency BOLD signal fluctuations in isoflurane-anesthetized rat brain, NeuroImage, vol.40, issue.4, pp.1738-1747, 2008.
DOI : 10.1016/j.neuroimage.2007.05.061

J. Vincent, G. Patel, M. Fox, A. Snyder, J. Baker et al., Intrinsic functional architecture in the anaesthetized monkey brain, Nature, vol.8, issue.7140, pp.44783-86, 2007.
DOI : 10.1038/nature05758

D. Feinberg, S. Moeller, S. Smith, E. Auerbach, S. Ramanna et al., Multiplexed Echo Planar Imaging for Sub-Second Whole Brain FMRI and Fast Diffusion Imaging, PLoS ONE, vol.106, issue.12, p.15710, 2010.
DOI : 10.1371/journal.pone.0015710.s007

S. Moeller, E. Yacoub, C. Olman, E. Auerbach, J. Strupp et al., Multiband multislice GE-EPI at 7 tesla, with 16-fold acceleration using partial parallel imaging with application to high spatial and temporal whole-brain fMRI, Magnetic Resonance in Medicine, vol.54, issue.5, pp.1144-1153, 2010.
DOI : 10.1002/mrm.22361

C. Beckmann, M. Deluca, J. Devlin, and S. Smith, Investigations into resting-state connectivity using independent component analysis, Philosophical Transactions of the Royal Society B: Biological Sciences, vol.8, issue.2-3, pp.1001-1013, 1457.
DOI : 10.1002/(SICI)1097-0193(1999)8:2/3<151::AID-HBM13>3.0.CO;2-5

M. Jenkinson, Fast, automated,N-dimensional phase-unwrapping algorithm, Magnetic Resonance in Medicine, vol.16, issue.1, pp.193-197, 2003.
DOI : 10.1002/mrm.10354

G. Salimi-khorshidi, G. Douaud, C. Beckmann, M. Glasser, L. Griffanti et al., Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiers, NeuroImage, vol.90, pp.449-468, 2014.
DOI : 10.1016/j.neuroimage.2013.11.046

L. Griffanti, G. Salimi-khorshidi, C. Beckmann, E. Auerbach, G. Douaud et al., ICA-based artefact removal and accelerated fMRI acquisition for improved resting state network imaging, NeuroImage, vol.95, pp.232-247, 2014.
DOI : 10.1016/j.neuroimage.2014.03.034

D. Greve and B. Fischl, Accurate and robust brain image alignment using boundary-based registration, NeuroImage, vol.48, issue.1, pp.63-72, 2009.
DOI : 10.1016/j.neuroimage.2009.06.060

N. Filippini, B. Macintosh, M. Hough, G. Goodwin, G. Frisoni et al., Distinct patterns of brain activity in young carriers of the APOE-epsilon4 allele, Proc Natl Acad Sci, issue.17, pp.1067209-7214, 2009.

S. Smith, P. Fox, K. Miller, D. Glahn, P. Fox et al., Correspondence of the brain's functional architecture during activation and rest, Proceedings of the National Academy of Sciences, vol.106, issue.31, pp.10613040-13045, 2009.
DOI : 10.1073/pnas.0905267106

C. Beckmann and S. Smith, Probabilistic Independent Component Analysis for Functional Magnetic Resonance Imaging, IEEE Transactions on Medical Imaging, vol.23, issue.2, pp.137-152, 2004.
DOI : 10.1109/TMI.2003.822821

J. Hui, R. Wilson, D. Bennett, J. Bienias, D. Gilley et al., Rate of cognitive decline and mortality in Alzheimer's disease, Neurology, vol.61, issue.10, pp.611356-1361, 2003.
DOI : 10.1212/01.WNL.0000094327.68399.59

P. Sullivan, R. Pary, F. Telang, A. Rifai, and G. Zubenko, Risk factors for white matter changes detected by magnetic resonance imaging in the elderly, Stroke, vol.21, issue.10, pp.1424-1428, 1990.
DOI : 10.1161/01.STR.21.10.1424

C. Decarli, D. Murphy, M. Tranh, C. Grady, J. Haxby et al., The effect of white matter hyperintensity volume on brain structure, cognitive performance, and cerebral metabolism of glucose in 51 healthy adults, Neurology, vol.45, issue.11, pp.452077-2084, 1995.
DOI : 10.1212/WNL.45.11.2077

E. Garde, L. Mortensen, E. Rostrup, E. Paulson, and O. , Decline in intelligence is associated with progression in white matter hyperintensity volume, Journal of Neurology, Neurosurgery & Psychiatry, vol.76, issue.9, pp.1289-1291, 2005.
DOI : 10.1136/jnnp.2004.055905

F. Fazekas, J. Chawluk, A. Alavi, H. Hurtig, and R. Zimmerman, MR signal abnormalities at 1.5 T in Alzheimer's dementia and normal aging, American Journal of Roentgenology, vol.149, issue.2, pp.351-356, 1987.
DOI : 10.2214/ajr.149.2.351

C. Cordonnier, A. Salman, R. Wardlaw, and J. , Spontaneous brain microbleeds: systematic review, subgroup analyses and standards for study design and reporting, Brain, vol.130, issue.8, pp.1988-2003, 2007.
DOI : 10.1093/brain/awl387

C. Cordonnier, G. Potter, C. Jackson, F. Doubal, S. Keir et al., Improving Interrater Agreement About Brain Microbleeds: Development of the Brain Observer MicroBleed Scale (BOMBS), Stroke, vol.40, issue.1, pp.94-99, 2009.
DOI : 10.1161/STROKEAHA.108.526996

M. Poels, M. Ikram, A. Van-der-lugt, A. Hofman, W. Niessen et al., Cerebral microbleeds are associated with worse cognitive function: The Rotterdam Scan Study, Neurology, vol.78, issue.5, pp.78326-333
DOI : 10.1212/WNL.0b013e3182452928

J. Schneider, Brain Microbleeds and Cognitive Function, Stroke, vol.38, issue.6, pp.1730-1731, 2007.
DOI : 10.1161/STROKEAHA.107.487173

J. Wardlaw, M. Bastin, V. Hernandez, M. Maniega, S. Royle et al., Brain Aging, Cognition in Youth and Old Age and Vascular Disease in the Lothian Birth Cohort 1936: Rationale, Design and Methodology of the Imaging Protocol, International Journal of Stroke, vol.62, issue.6, pp.547-559, 2011.
DOI : 10.1002/hbm.10062

S. Smith, M. Jenkinson, H. Johansen-berg, D. Rueckert, T. Nichols et al., Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data, NeuroImage, vol.31, issue.4, pp.311487-1505, 2006.
DOI : 10.1016/j.neuroimage.2006.02.024

J. Block and A. Kremen, IQ and ego-resiliency: Conceptual and empirical connections and separateness., Journal of Personality and Social Psychology, vol.70, issue.2, pp.349-361, 1996.
DOI : 10.1037/0022-3514.70.2.349

T. Frodl, A. Carballedo, A. Fagan, D. Lisiecka, Y. Ferguson et al., Effects of early-life adversity on white matter diffusivity changes in patients at risk for major depression, Journal of Psychiatry & Neuroscience, vol.37, issue.1, pp.37-45
DOI : 10.1503/jpn.110028

N. Filippini, L. Nickerson, C. Beckmann, K. Ebmeier, G. Frisoni et al., Age-related adaptations of brain function during a memory task are also present at rest, NeuroImage, vol.59, issue.4, pp.3821-3828
DOI : 10.1016/j.neuroimage.2011.11.063

S. Stringhini, S. Sabia, M. Shipley, E. Brunner, H. Nabi et al., Association of Socioeconomic Position With Health Behaviors and Mortality, JAMA, vol.303, issue.12, pp.1159-1166
DOI : 10.1001/jama.2010.297

URL : https://hal.archives-ouvertes.fr/inserm-00468691

M. Hyde, R. Wiggins, P. Higgs, and D. Blane, A measure of quality of life in early old age: The theory, development and properties of a needs satisfaction model (CASP-19), Aging & Mental Health, vol.7, issue.3, pp.186-194, 2003.
DOI : 10.1080/1360786031000101157

A. Singh-manoux, M. Richards, and M. Marmot, Leisure activities and cognitive function in middle age: evidence from the Whitehall II study, Journal of Epidemiology & Community Health, vol.57, issue.11, pp.907-913, 2003.
DOI : 10.1136/jech.57.11.907

URL : https://hal.archives-ouvertes.fr/inserm-01154130

B. Keating, S. Tischfield, S. Murray, T. Bhangale, T. Price et al., Concept, Design and Implementation of a Cardiovascular Gene-Centric 50 K SNP Array for Large-Scale Genomic Association Studies, PLoS ONE, vol.39, issue.5, p.3583, 2008.
DOI : 10.1371/journal.pone.0003583.s003