S. M. Adriaanse, E. J. Sanz-arigita, M. A. Binnewijzend, R. Ossenkoppele, N. Tolboom et al., Amyloid and its association with default network integrity in Alzheimer's disease, Human Brain Mapping, vol.42, issue.Part 6, pp.779-791, 2014.
DOI : 10.1016/j.neuroimage.2008.04.251

A. Altmann, B. Ng, S. M. Landau, W. J. Jagust, and M. D. Greicius, Regional brain hypometabolism is unrelated to regional amyloid plaque burden, Brain, vol.19, issue.12, pp.3734-3746
DOI : 10.1016/j.semcdb.2011.03.011

K. Arbuthnott and J. Frank, Trail Making Test, Part B as a Measure of Executive Control: Validation Using a Set-Switching Paradigm, Journal of Clinical and Experimental Neuropsychology (Neuropsychology, Development and Cognition: Section A), vol.22, issue.4, pp.518-528, 2000.
DOI : 10.1076/1380-3395(200008)22:4;1-0;FT518

C. Babiloni, P. J. Visser, G. Frisoni, P. P. De-deyn, L. Bresciani et al., Cortical sources of resting EEG rhythms in mild cognitive impairment and subjective memory complaint, Neurobiology of Aging, vol.31, issue.10, pp.1787-1798, 2010.
DOI : 10.1016/j.neurobiolaging.2008.09.020

R. M. Baron and D. A. Kenny, The moderator???mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations., Journal of Personality and Social Psychology, vol.51, issue.6, pp.1173-1182, 1986.
DOI : 10.1037/0022-3514.51.6.1173

Y. Benjamini and Y. Hochberg, Controlling the false discovery rate -a practical and powerful approach to multiple testing, J. R. Stat. Soc. Ser. B Methodol, vol.57, pp.289-300, 1995.

A. L. Benton, Differential behavioral effects in frontal lobe disease, Neuropsychologia, vol.6, issue.1, pp.53-60, 1968.
DOI : 10.1016/0028-3932(68)90038-9

F. L. Besson, L. Joie, R. Doeuvre, L. Gaubert, M. Mezenge et al., Cognitive and Brain Profiles Associated with Current Neuroimaging Biomarkers of Preclinical Alzheimer's Disease, Journal of Neuroscience, vol.35, issue.29, pp.10402-10411, 2015.
DOI : 10.1523/JNEUROSCI.0150-15.2015

H. Buschke, Cued recall in Amnesia, Journal of Clinical Neuropsychology, vol.82, issue.4, pp.433-440, 1984.
DOI : 10.1037/h0076782

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, The Lancet Neurology, vol.11, issue.8, pp.669-678, 2012.
DOI : 10.1016/S1474-4422(12)70142-4

M. X. Cohen, Analyzing neural time series data. In: Theory and Practice, 2014.

P. Cuesta, P. Garces, N. P. Castellanos, M. E. Lopez, S. Aurtenetxe et al., Influence of the APOE epsilon4 allele and mild cognitive impairment diagnosis in the disruption of the MEG resting state functional connectivity in sources space, J. Alzheimers Dis, vol.44, pp.493-505, 2015.

D. J. Drane, R. L. Yuspeh, J. S. Huthwaite, and L. K. Klingler, Demographic characteristics and normative observations for derived-Trail Making Test indices, Neuropsychiatry Neuropsychol. Behav. Neurol, vol.15, pp.39-43, 2002.

A. Drzezga, J. A. Becker, K. R. Van-dijk, A. Sreenivasan, T. Talukdar et al., Neuronal dysfunction and disconnection of cortical hubs in non-demented subjects with elevated amyloid burden, Brain, vol.11, issue.6, pp.1635-1646, 2011.
DOI : 10.1016/S1076-6332(03)00671-8

G. Rabinovici, P. Robert, C. Rowe, S. Salloway, M. Sarazin et al., Advancing research diagnostic criteria for Alzheimer's disease: the IWG-2 criteria, Lancet Neurol, vol.13, pp.614-629

J. A. Elman, C. M. Madison, S. L. Baker, J. W. Vogel, S. M. Marks et al., Effects of Beta-Amyloid on Resting State Functional Connectivity Within and Between Networks Reflect Known Patterns of Regional Vulnerability, Cerebral Cortex, vol.25, pp.695-707, 2016.
DOI : 10.1093/brain/awq075

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, The Clinical Neuropsychologist (Neuropsychology, Development and Cognition: Section D), vol.13, issue.1, pp.30-47, 1999.
DOI : 10.1076/clin.13.1.30.1976

T. C. Ferree, P. Luu, G. S. Russell, and D. M. Tucker, Scalp electrode impedance, infection risk, and EEG data quality, Clinical Neurophysiology, vol.112, issue.3, pp.536-544, 2001.
DOI : 10.1016/S1388-2457(00)00533-2

M. F. Folstein, S. E. Folstein, and P. R. Mchugh, ???Mini-mental state???, Journal of Psychiatric Research, vol.12, issue.3, pp.189-198, 1975.
DOI : 10.1016/0022-3956(75)90026-6

S. Forster, T. Grimmer, I. Miederer, G. Henriksen, B. H. Yousefi et al., Regional Expansion of Hypometabolism in Alzheimer's Disease Follows Amyloid Deposition with Temporal Delay, Biological Psychiatry, vol.71, issue.9, pp.792-797, 2012.
DOI : 10.1016/j.biopsych.2011.04.023

P. Fries, Rhythms for Cognition: Communication through Coherence, Neuron, vol.88, issue.1, pp.220-235, 2015.
DOI : 10.1016/j.neuron.2015.09.034

A. A. Gouw, A. M. Alsema, B. M. Tijms, A. Borta, P. Scheltens et al., EEG spectral analysis as a putative early prognostic biomarker in nondemented, amyloid positive subjects, Neurobiology of Aging, vol.57, pp.133-142, 2017.
DOI : 10.1016/j.neurobiolaging.2017.05.017

W. De-haan, K. Mott, E. C. Van-straaten, P. Scheltens, and C. J. Stam, Activity Dependent Degeneration Explains Hub Vulnerability in Alzheimer's Disease, PLoS Computational Biology, vol.8, issue.8, p.1002582, 2012.
DOI : 10.1371/journal.pcbi.1002582.s008

T. Hedden, K. R. Van-dijk, J. A. Becker, A. Mehta, R. A. Sperling et al., Disruption of Functional Connectivity in Clinically Normal Older Adults Harboring Amyloid Burden, Journal of Neuroscience, vol.29, issue.40, pp.12686-12694, 2009.
DOI : 10.1523/JNEUROSCI.3189-09.2009

F. Jessen, R. E. Amariglio, M. Van-boxtel, M. Breteler, M. Ceccaldi et al., A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer's disease, Subjective Cognitive Decline Initiative Working, G., 2014. A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer's disease, pp.844-852
DOI : 10.1016/j.jalz.2014.01.001

A. D. Joshi, M. J. Pontecorvo, M. Lu, D. M. Skovronsky, M. A. Mintun et al., A Semiautomated Method for Quantification of F 18 Florbetapir PET Images, Journal of Nuclear Medicine, vol.56, issue.11, pp.1736-1741, 2015.
DOI : 10.2967/jnumed.114.153494

M. Kalafat, L. Hugonot-diener, and J. Poitrenaud, The Mini Mental State (MMS): French standardization and normative data, Rev. Neuropsychol, vol.13, pp.209-236, 2003.

V. Kljajevic, M. J. Grothe, M. Ewers, and S. Teipel, Alzheimer's Disease Neuroimaging, I, 2014. Distinct pattern of hypometabolism and atrophy in preclinical and predementia Alzheimer's disease, Neurobiol. Aging, vol.35, 1973.

C. A. Kothe and S. Makeig, BCILAB: a platform for brain???computer interface development, Journal of Neural Engineering, vol.10, issue.5, 2013.
DOI : 10.1088/1741-2560/10/5/056014

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, Journal of Nuclear Medicine, vol.54, issue.1, pp.70-77
DOI : 10.2967/jnumed.112.109009

S. H. Lee, Y. M. Park, D. W. Kim, and C. H. Im, Global synchronization index as a biological correlate of cognitive decline in Alzheimer's disease, Neuroscience Research, vol.66, issue.4, pp.333-339, 2010.
DOI : 10.1016/j.neures.2009.12.004

V. M. Leirer, C. Wienbruch, S. Kolassa, W. Schlee, T. Elbert et al., Changes in cortical slow wave activity in healthy aging, Brain Imaging and Behavior, vol.56, issue.10, pp.222-228, 2011.
DOI : 10.1001/archneur.56.10.1274

H. K. Lim, R. Nebes, B. Snitz, A. Cohen, C. Mathis et al., Regional amyloid burden and intrinsic connectivity networks in cognitively normal elderly subjects, Regional amyloid burden and intrinsic connectivity networks in cognitively normal elderly subjects, pp.3327-3338, 2014.
DOI : 10.1016/j.neuroimage.2010.11.048

M. Moosmann, P. Ritter, I. Krastel, A. Brink, S. Thees et al., Correlates of alpha rhythm in functional magnetic resonance imaging and near infrared spectroscopy, NeuroImage, vol.20, issue.1, pp.145-158, 2003.
DOI : 10.1016/S1053-8119(03)00344-6

E. C. Mormino, A. Smiljic, A. O. Hayenga, S. H. Onami, M. D. Greicius et al., Relationships between Beta-Amyloid and Functional Connectivity in Different Components of the Default Mode Network in Aging, Cerebral Cortex, vol.1, issue.10, pp.2399-2407, 2011.
DOI : 10.1093/arclin/1.3.274b

M. E. Murray, V. J. Lowe, N. R. Graff-radford, A. M. Liesinger, A. Cannon et al., C-Pittsburgh compound B implications of Thal amyloid phase across the Alzheimer???s disease spectrum, Brain, vol.138, issue.5, pp.1370-1381, 2015.
DOI : 10.1172/JCI119772

N. Myers, L. Pasquini, J. Gottler, T. Grimmer, K. Koch et al., Within-patient correspondence of amyloid-?? and intrinsic network connectivity in Alzheimer???s disease, Brain, vol.73, issue.7, pp.2052-2064, 2014.
DOI : 10.1016/j.neuron.2012.03.004

I. Neuner, J. Arrubla, C. J. Werner, K. Hitz, F. Boers et al., The Default Mode Network and EEG Regional Spectral Power: A Simultaneous fMRI-EEG Study, PLoS ONE, vol.53, issue.2, 2014.
DOI : 10.1371/journal.pone.0088214.t001

R. Ossenkoppele, C. Madison, H. Oh, M. Wirth, B. N. Van-berckel et al., Is Verbal Episodic Memory in Elderly with Amyloid Deposits Preserved Through Altered Neuronal Function?, Cerebral Cortex, vol.13, issue.8, pp.2210-2218, 2014.
DOI : 10.1097/00002093-199910000-00009

L. S. Prichep, Quantitative EEG and Electromagnetic Brain Imaging in Aging and in the Evolution of Dementia, Annals of the New York Academy of Sciences, vol.229, issue.1, pp.156-167, 2007.
DOI : 10.1073/pnas.191044198

C. Sorg and M. J. Grothe, The complex link between amyloid and neuronal dysfunction in Alzheimer???s disease, Brain, vol.138, issue.12, pp.3472-3475, 2015.
DOI : 10.1016/j.neuron.2014.10.038

C. J. Stam, G. Nolte, and A. Daffertshofer, Phase lag index: Assessment of functional connectivity from multi channel EEG and MEG with diminished bias from common sources, Human Brain Mapping, vol.116, issue.11, pp.1178-1193, 2007.
DOI : 10.1016/j.clinph.2004.04.029

E. Stomrud, O. Hansson, L. Minthon, K. Blennow, I. Rosen et al., Slowing of EEG correlates with CSF biomarkers and reduced cognitive speed in elderly with normal cognition over 4 years, Neurobiology of Aging, vol.31, issue.2, pp.215-223, 2010.
DOI : 10.1016/j.neurobiolaging.2008.03.025

D. R. Thal, T. G. Beach, M. Zanette, K. Heurling, A. Chakrabarty et al., [ 18 F]flutemetamol amyloid positron emission tomography in preclinical and symptomatic Alzheimer's disease: Specific detection of advanced phases of amyloid-?? pathology, Alzheimer's & Dementia, vol.11, issue.8, pp.975-985, 2015.
DOI : 10.1016/j.jalz.2015.05.018

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, European Journal of Nuclear Medicine and Molecular Imaging, vol.43, issue.6, pp.1104-1119, 2011.
DOI : 10.1016/j.neuroimage.2010.04.013

T. N. 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

V. L. Villemagne, R. S. Mulligan, S. Pejoska, K. Ong, G. Jones et al., Comparison of 11C-PiB and 18F-florbetaben for A?? imaging in ageing and Alzheimer???s disease, European Journal of Nuclear Medicine and Molecular Imaging, vol.68, issue.5, pp.983-989, 2012.
DOI : 10.1001/archneurol.2011.77

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, Existing Pittsburgh Compound-B positron emission tomography thresholds are too high: statistical and pathological evaluation, pp.2020-2033, 2015.
DOI : 10.1212/WNL.0000000000000170
URL : https://academic.oup.com/brain/article-pdf/138/7/2020/13799993/awv112.pdf

D. Wechsler, Weschsler Memory Scale-III. The Psychological Corporation, 1997.

I. Winkler, S. Brandl, F. Horn, E. Waldburger, C. Allefeld et al., Robust artifactual independent component classification for BCI practitioners, Journal of Neural Engineering, vol.11, issue.3, 2014.
DOI : 10.1088/1741-2560/11/3/035013

I. Winkler, S. Debener, K. R. Muller, and M. Tangermann, On the influence of highpass filtering on ICA-based artifact reduction in EEG-ERP, Annual international conference of the IEEE engineering in medicine and biology, pp.4101-4105, 2015.