O. Healthcare, . Genomics, J. Consultancy-fees-from, C. Diagnostics, . Ltd et al., Oryzon Genomics, and Functional Neuromodulation, and participated in scientific advisory boards of Functional Neuromodulation

, HH is a co-inventor in the following patents as a scientific expert and has received no royalties: ? In Vitro Multi-parameter Determination Method for The Diagnosis and Early Diagnosis of Neurodegenerative Disorders Patent Number, p.8916388

, ? In Vitro Procedure for Diagnosis and Early Diagnosis of Neurodegenerative Diseases Patent Number, p.8298784

, ? Neurodegenerative Markers for Psychiatric Conditions Publication Number

, ? In Vitro Multi-parameter Determination Method for The Diagnosis and Early Diagnosis of Neurodegenerative Disorders Publication Number

, ? In Vitro Method for The Diagnosis and Early Diagnosis of Neurodegenerative Disorders Publication Number

, ? In Vitro Procedure for Diagnosis and Early Diagnosis of Neurodegenerative Diseases Publication Number

, ? In Vitro Method for The Diagnosis of Neurodegenerative Diseases Patent Number, p.7547553

, ? CSF Diagnostic in Vitro Method for Diagnosis of Dementias and Neuroinflammatory Diseases Publication Number

, ? In Vitro Method for The Diagnosis of Neurodegenerative Diseases Publication Number

, ? Neurodegenerative Markers for Psychiatric Conditions Publication Number

O. Sabri, M. N. Sabbagh, J. Seibyl, H. Barthel, H. Akatsu et al., Florbetaben PET imaging to detect amyloid beta plaques in Alzheimer's disease: phase 3 study, Alzheimers Dement, vol.11, issue.8, pp.964-74, 2015.

M. E. Murray, V. J. Lowe, N. R. Graff-radford, A. M. Liesinger, A. Cannon et al., Clinicopathologic and 11C-Pittsburgh compound B implications of Thal amyloid phase across the Alzheimer's disease spectrum, Brain, vol.138, pp.1370-81, 2015.

M. D. Ikonomovic, C. J. Buckley, K. Heurling, P. Sherwin, P. A. Jones et al., Post-mortem histopathology underlying beta-amyloid PET imaging following flutemetamol F 18 injection, Acta neuropathol commun, vol.4, issue.1, p.130, 2016.

C. Marcus, E. Mena, and R. M. Subramaniam, Brain PET in the diagnosis of Alzheimer's disease, Clin Nuclear Med, vol.39, issue.10, pp.413-435, 2014.

D. R. Thal, U. Rub, M. Orantes, and H. Braak, Phases of A beta-deposition in the human brain and its relevance for the development of AD, Neurology, vol.58, issue.12, pp.1791-800, 2002.

H. Cho, J. Y. Choi, M. S. Hwang, Y. J. Kim, H. M. Lee et al., In vivo cortical spreading pattern of tau and amyloid in the Alzheimer disease spectrum, Ann Neurol, vol.80, issue.2, pp.247-58, 2016.

M. J. Grothe, H. Barthel, J. Sepulcre, M. Dyrba, O. Sabri et al., In vivo staging of regional amyloid deposition, Neurology, vol.89, issue.20, pp.2031-2039, 2017.

A. J. Mitchell, H. Beaumont, D. Ferguson, M. Yadegarfar, and B. Stubbs, Risk of dementia and mild cognitive impairment in older people with subjective memory complaints: meta-analysis, Acta Psychiatr Scand, vol.130, issue.6, pp.439-51, 2014.

B. Dubois, H. Hampel, H. H. Feldman, P. Scheltens, P. Aisen et al., Alzheimer's disease: definition, natural history, and diagnostic criteria, Alzheimers Dement, vol.12, issue.3, pp.292-323, 2016.

A. R. Kaup, J. Nettiksimmons, E. S. Leblanc, and K. Yaffe, Memory complaints and risk of cognitive impairment after nearly 2 decades among older women, Neurology, vol.85, issue.21, pp.1852-1860, 2015.

B. Dubois, S. Epelbaum, F. Nyasse, H. Bakardjian, G. Gagliardi et al., Cognitive and neuroimaging features and brain beta-amyloidosis in individuals at risk of Alzheimer's disease (INSIGHT-preAD): a longitudinal observational study, Lancet Neurol, vol.17, issue.4, pp.335-381, 2018.

C. M. Clark, M. J. Pontecorvo, T. G. Beach, B. J. Bedell, R. E. Coleman et al., Cerebral PET with florbetapir compared with neuropathology at autopsy for detection of neuritic amyloid-? plaques: a prospective cohort study, Lancet Neurol, vol.11, issue.8, pp.669-78, 2012.

A. D. Joshi, M. J. Pontecorvo, C. M. Clark, A. P. Carpenter, D. L. Jennings et al., Performance characteristics of amyloid PET with florbetapir F 18 in patients with alzheimer's disease and cognitively normal subjects, J Nucl Med, vol.53, issue.3, pp.378-84, 2012.

M. F. Folstein, S. E. Folstein, and P. R. Mchugh, Mini-mental state". A practical method for grading the cognitive state of patients for the clinician, J Psychiatr Res, vol.12, issue.3, pp.189-98, 1975.

H. Amieva, L. Carcaillon, L. Rouze, P. 'alzit-schuermans, X. Millet et al., Cued and uncued memory tests: norms in elderly adults from the 3 cities epidemiological study, Rev Neurol, vol.163, issue.2, pp.205-226, 2007.

H. Buschke, Cued recall in amnesia, J Clin Neuropsychol, vol.6, issue.4, pp.433-473, 1984.

H. Buschke, W. B. Mowrey, W. S. Ramratan, M. E. Zimmerman, D. A. Loewenstein et al., Memory binding test distinguishes amnestic mild cognitive impairment and dementia from cognitively normal elderly, Arch Clin Neuropsychol, vol.32, issue.1, pp.29-39, 2017.

A. L. Benton, Differential behavioral effects in frontal lobe disease, Neuropsychologia, vol.6, issue.1, pp.53-60, 1968.

D. Cardebat, B. Doyon, M. Puel, P. Goulet, and Y. Joanette, Formal and semantic lexical evocation in normal subjects. Performance and dynamics of production as a function of sex, age and educational level, Acta Neurol Belg, vol.90, issue.4, pp.207-224, 1990.

Z. Shao, E. Janse, K. Visser, and A. S. Meyer, What do verbal fluency tasks measure? Predictors of verbal fluency performance in older adults, Front Psychol, vol.5, p.772, 2014.

P. S. Fastenau, N. L. Denburg, and B. J. Hufford, Adult norms for the Rey-Osterrieth Complex Figure Test and for supplemental recognition and matching trials from the Extended Complex Figure Test, Clin Neuropsychol, vol.13, issue.1, pp.30-47, 1999.

D. Wechsler, WMS-III Wechsler memory scale-third edition, 1997.

R. P. Kessels, E. Van-den-berg, C. Ruis, and A. M. Brands, The backward span of the Corsi Block-Tapping Task and its association with the WAIS-III Digit Span, Assessment, vol.15, issue.4, pp.426-460, 2008.

T. N. Tombaugh, Trail Making Test A and B: normative data stratified by age and education, Arch Clin Neuropsychol, vol.19, issue.2, pp.203-217, 2004.

B. Dubois, A. Slachevsky, I. Litvan, and B. Pillon, The FAB: a Frontal Assessment Battery at bedside, Neurology, vol.55, issue.11, pp.1621-1627, 2000.

M. Habert, H. Bertin, M. Labit, M. Diallo, M. S. Martineau et al., Evaluation of amyloid status in a cohort of elderly individuals with memory complaints: validation of the method of quantification and determination of positivity thresholds, Ann Nucl Med, vol.32, issue.2, pp.75-86, 2018.

H. W. Muller-gartner, J. M. Links, J. L. Prince, R. N. Bryan, E. Mcveigh et al., Measurement of radiotracer concentration in brain gray matter using positron emission tomography: MRI-based correction for partial volume effects, J Cereb Blood Flow Metab, vol.12, issue.4, pp.571-83, 1992.

R. S. Desikan, F. Segonne, 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.968-80, 2006.

G. Gonzalez-escamilla, C. Lange, and S. Teipel, PETPVE12: an SPM toolbox for partial volume effects correction in brain PET-application to amyloid imaging with AV45-PET, NeuroImage, vol.147, p.8, 2017.

W. E. Klunk, R. A. Koeppe, J. C. Price, T. L. Benzinger, M. D. Devous et al., The Centiloid Project: standardizing quantitative amyloid plaque estimation by PET, Alzheimers Dement, vol.11, issue.1, pp.1-15, 2015.

A. M. Catafau, S. Bullich, J. P. Seibyl, H. Barthel, B. Ghetti et al., Cerebellar amyloid-beta plaques: how frequent are they, and do they influence 18F-Florbetaben SUV ratios?, J Nucl Med, vol.57, issue.11, pp.1740-1745, 2016.

S. M. Landau, C. Breault, A. D. Joshi, M. Pontecorvo, C. A. Mathis et al., Amyloid-? imaging with Pittsburgh compound B and florbetapir: comparing radiotracers and quantification methods, J Nuclear Med, vol.54, issue.1, pp.70-77, 2013.

C. M. Clark, J. A. Schneider, B. J. Bedell, T. G. Beach, W. B. Bilker et al., Use of florbetapir-PET for imaging beta-amyloid pathology, JAMA, vol.305, issue.3, pp.275-83, 2011.

A. S. Fleisher, K. Chen, X. Liu, A. Roontiva, P. Thiyyagura et al., Using positron emission tomography and florbetapir F18 to image cortical amyloid in patients with mild cognitive impairment or dementia due to Alzheimer disease, Arch Neurol, vol.68, issue.11, pp.1404-1415, 2011.

D. R. Thal, T. G. Beach, M. Zanette, K. Heurling, A. Chakrabarty et al., 18F]flutemetamol amyloid positron emission tomography in preclinical and symptomatic Alzheimer's disease: specific detection of advanced phases of amyloid-? pathology, Alzheimers Dement, vol.11, issue.8, pp.975-85, 2015.

S. Salloway, J. E. Gamez, U. Singh, C. H. Sadowsky, T. Villena et al., Performance of [(18)F]flutemetamol amyloid imaging against the neuritic plaque component of CERAD and the current (2012) NIA-AA recommendations for the neuropathologic diagnosis of Alzheimer's disease. Alzheimer's Dementia, vol.9, pp.25-34, 2017.

S. Villeneuve, G. D. Rabinovici, B. I. Cohn-sheehy, C. Madison, N. Ayakta et al., Existing Pittsburgh compound-B positron emission tomography thresholds are too high: statistical and pathological evaluation, Brain, vol.138, pp.2020-2053, 2015.
DOI : 10.1093/brain/awv112

URL : https://academic.oup.com/brain/article-pdf/138/7/2020/13799993/awv112.pdf

R. Lemos, C. Cunha, J. Maroco, A. Afonso, M. R. Simoes et al., Free and Cued Selective Reminding Test is superior to the Wechsler Memory Scale in discriminating mild cognitive impairment from Alzheimer's disease, Geriatr Gerontol Int, vol.15, issue.8, pp.961-969, 2015.

W. B. Mowrey, R. B. Lipton, M. J. Katz, W. S. Ramratan, D. A. Loewenstein et al., Memory binding test predicts incident amnestic mild cognitive impairment, J Alzheimers Dis, vol.53, issue.4, pp.1585-95, 2016.
DOI : 10.3233/jad-160291

K. V. Papp, D. M. Rentz, I. Orlovsky, R. A. Sperling, and E. C. Mormino, Optimizing the preclinical Alzheimer's cognitive composite with semantic processing: the PACC5, Alzheimers Dementia, vol.3, issue.4, pp.668-77, 2017.

D. M. Rentz, P. Rodriguez, M. A. Amariglio, R. Stern, Y. Sperling et al., Promising developments in neuropsychological approaches for the detection of preclinical Alzheimer's disease: a selective review, Alzheimers Res Ther, vol.5, issue.6, p.58, 2013.

S. E. Schindler, M. S. Jasielec, H. Weng, J. J. Hassenstab, E. Grober et al., Neuropsychological measures that detect early impairment and decline in preclinical Alzheimer disease, Neurobiol Aging, vol.56, pp.25-32, 2017.
DOI : 10.1016/j.neurobiolaging.2017.04.004

URL : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5505233

M. C. Donohue, R. A. Sperling, R. Petersen, C. K. Sun, M. W. Weiner et al., Association between elevated brain amyloid and subsequent cognitive decline among cognitively normal persons, JAMA, vol.317, issue.22, pp.2305-2321, 2017.
DOI : 10.1001/jama.2017.6669

URL : https://jamanetwork.com/journals/jama/articlepdf/2631529/jama_donohue_2017_oi_170051.pdf

D. Han, S. Nguyen, C. P. Stricker, N. H. Nation, and D. A. , Detectable neuropsychological differences in early preclinical Alzheimer's disease: a meta-analysis, Neuropsychol Rev, vol.27, issue.4, pp.305-330, 2017.

M. Bilgel, Y. An, A. Lang, J. Prince, L. Ferrucci et al., Trajectories of Alzheimer disease-related cognitive measures in a longitudinal sample, Alzheimers Dementia, vol.10, issue.6, pp.735-777, 2014.

E. Grober, C. B. Hall, R. B. Lipton, A. B. Zonderman, S. M. Resnick et al., Memory impairment, executive dysfunction, and intellectual decline in preclinical Alzheimer's disease, J Int Neuropsychol Soc, vol.14, issue.2, pp.266-78, 2008.

J. B. Langbaum, S. Hendrix, N. Ayutyanont, D. A. Bennett, R. C. Shah et al., Establishing composite cognitive endpoints for use in preclinical Alzheimer's disease trials, J Prev Alzheimer's Dis, vol.2, issue.1, pp.2-3, 2015.

R. E. Amariglio, J. A. Becker, J. Carmasin, L. P. Wadsworth, N. Lorius et al., Subjective cognitive complaints and amyloid burden in cognitively normal older individuals, Neuropsychologia, vol.50, issue.12, pp.2880-2886, 2012.
DOI : 10.1016/j.neuropsychologia.2012.08.011

URL : http://europepmc.org/articles/pmc3473106?pdf=render

H. Braak and E. Braak, Neuropathological stageing of Alzheimer-related changes, Acta Neuropathol, vol.82, issue.4, pp.239-59, 1991.

A. Charidimou, K. Farid, H. H. Tsai, L. K. Tsai, R. F. Yen et al., Amyloid-PET burden and regional distribution in cerebral amyloid angiopathy: a systematic review and meta-analysis of biomarker performance, J Neurol Neurosurg Psychiatry, vol.89, issue.4, pp.410-417, 2018.

M. Tanskanen, M. Makela, L. Myllykangas, I. L. Notkola, T. Polvikoski et al., Prevalence and severity of cerebral amyloid angiopathy: a populationbased study on very elderly Finns (Vantaa 85+), Neuropathol Appl Neurobiol, vol.38, issue.4, pp.329-365, 2012.

E. M. Arenaza-urquijo and P. Vemuri, Resistance vs resilience to Alzheimer disease, Clarifying Terminol Preclin Stud, vol.90, issue.15, pp.695-703, 2018.
DOI : 10.1212/wnl.0000000000005303

E. J. Rogalski, T. Gefen, J. Shi, M. Samimi, E. Bigio et al., Youthful memory capacity in old brains: anatomic and genetic clues from the Northwestern SuperAging Project, J Cogn Neurosci, vol.25, issue.1, pp.29-36, 2013.

M. C. Donohue, R. A. Sperling, and R. Petersen, Association between elevated brain amyloid and subsequent cognitive decline among cognitively normal persons, JAMA, vol.317, issue.22, pp.2305-2321, 2017.
DOI : 10.1001/jama.2017.6669

URL : https://jamanetwork.com/journals/jama/articlepdf/2631529/jama_donohue_2017_oi_170051.pdf

W. J. Jagust, S. M. Landau, R. A. Koeppe, E. M. Reiman, K. Chen et al., The Alzheimer's Disease Neuroimaging Initiative 2 PET Core: 2015. Alzheimer's Dementia, vol.11, pp.757-71, 2015.
DOI : 10.1016/j.jalz.2015.05.001

URL : http://europepmc.org/articles/pmc4510459?pdf=render

K. M. Rodrigue, K. M. Kennedy, M. D. Devous, . Sr, J. R. Rieck et al., Amyloid burden in healthy aging: regional distribution and cognitive consequences, vol.78, pp.387-95, 2012.

M. M. Mielke, H. J. Wiste, S. D. Weigand, D. S. Knopman, V. J. Lowe et al., Indicators of amyloid burden in a population-based study of cognitively normal elderly, Neurology, vol.79, issue.15, pp.1570-1577, 2012.

R. L. Mcnamee, S. H. Yee, J. C. Price, W. E. Klunk, B. Rosario et al., Consideration of optimal time window for Pittsburgh compound B PET summed uptake measurements, J Nucl Med, vol.50, issue.3, pp.348-55, 2009.

S. S. Golla, S. C. Verfaillie, R. Boellaard, S. M. Adriaanse, M. D. Zwan et al., Quantification of [18F]florbetapir: a test-retest tracer kinetic modelling study, J Cereb Blood Flow Metab, 2018.

J. Ottoy, J. Verhaeghe, E. Niemantsverdriet, L. Wyffels, C. Somers et al., Validation of the semiquantitative static SUVR method for (18)F-AV45 PET by pharmacokinetic modeling with an arterial input function, J Nucl Med, vol.58, issue.9, pp.1483-1492, 2017.

B. A. Thomas, K. Erlandsson, M. Modat, L. Thurfjell, R. Vandenberghe et al., The importance of appropriate partial volume correction for PET quantification in Alzheimer's disease, Eur J Nucl Med Mol Imaging, vol.38, issue.6, pp.1104-1123, 2011.

Y. Su, T. M. Blazey, A. Z. Snyder, M. E. Raichle, D. S. Marcus et al., Partial volume correction in quantitative amyloid imaging, NeuroImage, vol.107, pp.55-64, 2015.

M. Brendel, M. Hogenauer, A. Delker, J. Sauerbeck, P. Bartenstein et al., Improved longitudinal [(18)F]-AV45 amyloid PET by white matter reference and VOI-based partial volume effect correction, NeuroImage, vol.108, pp.450-459, 2015.

K. Matsubara, M. Ibaraki, H. Shimada, Y. Ikoma, T. Suhara et al., Impact of spillover from white matter by partial volume effect on quantification of amyloid deposition with, PiB PET. NeuroImage, vol.143, issue.11, pp.316-340, 2016.

G. Gonzalez-escamilla, C. Lange, S. Teipel, R. Buchert, and M. J. Grothe, Alzheimer's disease neuroimaging I. PETPVE12: an SPM toolbox for partial volume effects correction in brain PET-application to amyloid imaging with AV45PET, NeuroImage, vol.147, pp.669-77, 2017.

M. Rullmann, J. Dukart, K. T. Hoffmann, J. Luthardt, S. Tiepolt et al., Partial-volume effect correction improves quantitative analysis of 18FFlorbetaben beta-amyloid PET scans, J Nucl Med, vol.57, issue.2, pp.198-203, 2016.