{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T06:34:48Z","timestamp":1781073288206,"version":"3.54.1"},"reference-count":162,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2020,4,30]],"date-time":"2020-04-30T00:00:00Z","timestamp":1588204800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JPM"],"abstract":"<jats:p>Neurodegenerative processes of various types of dementia start years before symptoms, but the presence of a \u201cneural reserve\u201d, which continuously feeds and supports neuroplastic mechanisms, helps the aging brain to preserve most of its functions within the \u201cnormality\u201d frame. Mild cognitive impairment (MCI) is an intermediate stage between dementia and normal brain aging. About 50% of MCI subjects are already in a stage that is prodromal-to-dementia and during the following 3 to 5 years will develop clinically evident symptoms, while the other 50% remains at MCI or returns to normal. If the risk factors favoring degenerative mechanisms are modified during early stages (i.e., in the prodromal), the degenerative process and the loss of abilities in daily living activities will be delayed. It is therefore extremely important to have biomarkers able to identify\u2014in association with neuropsychological tests\u2014prodromal-to-dementia MCI subjects as early as possible. MCI is a large (i.e., several million in EU) and substantially healthy population; therefore, biomarkers should be financially affordable, largely available and non-invasive, but still accurate in their diagnostic prediction. Neurodegeneration initially affects synaptic transmission and brain connectivity; methods exploring them would represent a 1st line screening. Neurophysiological techniques able to evaluate mechanisms of synaptic function and brain connectivity are attracting general interest and are described here. Results are quite encouraging and suggest that by the application of artificial intelligence (i.e., learning-machine), neurophysiological techniques represent valid biomarkers for screening campaigns of the MCI population.<\/jats:p>","DOI":"10.3390\/jpm10020034","type":"journal-article","created":{"date-parts":[[2020,5,4]],"date-time":"2020-05-04T03:29:39Z","timestamp":1588562979000},"page":"34","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":48,"title":["Neurophysiological Hallmarks of Neurodegenerative Cognitive Decline: The Study of Brain Connectivity as A Biomarker of Early Dementia"],"prefix":"10.3390","volume":"10","author":[{"given":"Paolo Maria","family":"Rossini","sequence":"first","affiliation":[{"name":"Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilitation, IRCCS San Raffaele Pisana, 00167 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesca","family":"Miraglia","sequence":"additional","affiliation":[{"name":"Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilitation, IRCCS San Raffaele Pisana, 00167 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesca","family":"Al\u00f9","sequence":"additional","affiliation":[{"name":"Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilitation, IRCCS San Raffaele Pisana, 00167 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maria","family":"Cotelli","sequence":"additional","affiliation":[{"name":"Neuropsychology Unit, IRCCS Istituto Centro San Giovanni di DioFatebenefratelli, 25125 Brescia, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Florinda","family":"Ferreri","sequence":"additional","affiliation":[{"name":"Department of Neuroscience, Unit of Neurology and Neurophysiology, University of Padua, 35100 Padua, Italy"},{"name":"Department of Clinical Neurophysiology, Kuopio University Hospital, University of Eastern Finland, 70100 Kuopio, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Riccardo Di","family":"Iorio","sequence":"additional","affiliation":[{"name":"Neurology Unit, IRCCS Polyclinic A. Gemelli Foundation, 00168 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesco","family":"Iodice","sequence":"additional","affiliation":[{"name":"Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilitation, IRCCS San Raffaele Pisana, 00167 Rome, Italy"},{"name":"Neurology Unit, IRCCS Polyclinic A. 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Ther."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.neurobiolaging.2016.03.034","article-title":"Geneva Task Force for the Roadmap of Alzheimer\u2019s Biomarkers. Clinical validity of delayed recall tests as a gateway biomarker for Alzheimer\u2019s disease in the context of a structured 5-phase development framework","volume":"52","author":"Cerami","year":"2017","journal-title":"Neurobiol. Aging"},{"key":"ref_4","first-page":"549","article-title":"Cost-effectiveness of drug therapies for Alzheimer\u2019s disease: A brief review","volume":"4","author":"Geldmacher","year":"2008","journal-title":"Neuropsychiatr. Dis. Treat."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.pneurobio.2012.07.001","article-title":"Brain excitability and connectivity of neuronal assemblies in Alzheimer\u2019s disease: From animal models to human findings","volume":"99","author":"Rossini","year":"2012","journal-title":"Prog. Neurobiol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.jalz.2010.07.001","article-title":"An economic evaluation of early assessment for Alzheimer\u2019s disease in the United Kingdom","volume":"8","author":"Getsios","year":"2012","journal-title":"Alzheimers Dement."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Barnett, J.H., Lewis, L., Blackwell, A.D., and Taylor, M. (2014). Early intervention in Alzheimer\u2019s disease: A health economic study of the effects of diagnostic timing. BMC Neurol., 14.","DOI":"10.1186\/1471-2377-14-101"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1016\/j.nicl.2015.05.006","article-title":"The relative importance of imaging markers for the prediction of Alzheimer\u2019s disease dementia in mild cognitive impairment\u2014Beyond classical regression","volume":"8","author":"Teipel","year":"2015","journal-title":"Neuroimage Clin."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1212\/WNL.0000000000006088","article-title":"How early can we diagnose Alzheimer disease (and is it sufficient)? The 2017 Wartenberg lecture","volume":"91","author":"Petersen","year":"2018","journal-title":"Neurology"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1212\/WNL.0000000000004826","article-title":"Practice guideline update summary: Mild cognitive impairment: Report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology","volume":"90","author":"Petersen","year":"2018","journal-title":"Neurology"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2424","DOI":"10.1016\/j.clinph.2006.06.754","article-title":"A theoretical basis for standing and traveling brain waves measured with human EEG with implications for an integrated consciousness","volume":"117","author":"Nunez","year":"2006","journal-title":"Clin. Neurophysiol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.jneumeth.2007.06.026","article-title":"EEG and MEG coherence: Measures of functional connectivity at distinct spatial scales of neocortical dynamics","volume":"166","author":"Srinivasan","year":"2007","journal-title":"J. Neurosci. Methods"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1471","DOI":"10.1109\/72.963782","article-title":"Blind source separation by nonstationarity of variance: A cumulant-based approach","volume":"12","author":"Hyvarinen","year":"2001","journal-title":"IEEE Trans. Neural Netw."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"703","DOI":"10.1113\/jphysiol.2007.129163","article-title":"Functional source separation and hand cortical representation for a brain-computer interface feature extraction","volume":"580","author":"Tecchio","year":"2007","journal-title":"J. Physiol."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Porcaro, C., Medaglia, M.T., Thai, N.J., Seri, S., Rotshtein, P., and Tecchio, F. (2014). Contradictory reasoning network: An EEG and FMRI study. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0092835"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1007\/BF01132771","article-title":"Use of prior knowledge in brain electromagnetic source analysis","volume":"4","author":"Scherg","year":"1991","journal-title":"Brain Topogr."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1109\/10.141192","article-title":"Multiple dipole modeling and localization from spatio-temporal MEG data","volume":"39","author":"Mosher","year":"1992","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1097\/00004691-199905000-00004","article-title":"EEG source localization and imaging using multiple signal classification approaches","volume":"16","author":"Mosher","year":"1999","journal-title":"J. Clin. Neurophysiol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1007\/BF02512476","article-title":"Interpreting magnetic fields of the brain: Minimum norm estimates","volume":"32","author":"Ilmoniemi","year":"1994","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/0167-8760(84)90014-X","article-title":"Low resolution electromagnetic tomography: A new method for localizing electrical activity in the brain","volume":"18","author":"Michel","year":"1994","journal-title":"Int. J. Psychophysiol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1006\/meth.2001.1238","article-title":"Signal processing in magnetoencephalography","volume":"25","author":"Vrba","year":"2001","journal-title":"Methods"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.neurobiolaging.2016.08.021","article-title":"Cortical sources of resting state EEG rhythms are related to brain hypometabolism in subjects with Alzheimer\u2019s disease: An EEG-PET study","volume":"48","author":"Babiloni","year":"2016","journal-title":"Neurobiol. Aging"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"035204","DOI":"10.1103\/PhysRevE.65.035204","article-title":"Reconstructing embedding spaces of coupled dynamical systems from multivariate data","volume":"65","author":"Boccaletti","year":"2002","journal-title":"Phys. Rev. E Stat. Nonlin. Soft Matter Phys."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2701","DOI":"10.1002\/hbm.20704","article-title":"Model driven EEG\/fMRI fusion of brain oscillations","volume":"30","author":"Sotero","year":"2009","journal-title":"Hum. Brain Mapp."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1016\/j.neuroimage.2012.12.051","article-title":"Time-frequency mixed-norm estimates: Sparse M\/EEG imaging with non-stationary source activations","volume":"70","author":"Gramfort","year":"2013","journal-title":"Neuroimage"},{"key":"ref_26","unstructured":"Thieme, G. (1988). Co-Planar Stereotaxic Atlas of the Human Brain, George Thieme."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1019","DOI":"10.1114\/1.1415526","article-title":"A self-coherence enhancement algorithm and its application to enhancing three-dimensional source estimation from EEGs","volume":"29","author":"Yao","year":"2001","journal-title":"Ann. Biomed. Eng."},{"key":"ref_28","first-page":"91","article-title":"Functional imaging with low-resolution brain electromagnetic tomography (LORETA): A review","volume":"24","author":"Esslen","year":"2002","journal-title":"Methods Find Exp. Clin. Pharmacol."},{"key":"ref_29","unstructured":"Pascual-Marqui, R.D. (2007). Discrete, 3D distributed, linear imaging methods of electric neuronal activity. Part 1: Exact, zero error localization. arXiv."},{"key":"ref_30","unstructured":"Pascual-Marqui, R.D. (2007). Instantaneous and lagged measurements of linear and nonlinear dependence between groups of multivariate time series: Frequency decomposition. arXiv."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"793","DOI":"10.1016\/j.neuroscience.2006.08.049","article-title":"Conversion from mild cognitive impairment to Alzheimer\u2019s disease is predicted by sources and coherence of brain electroencephalography rhythms","volume":"143","author":"Rossini","year":"2006","journal-title":"Neuroscience"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1204","DOI":"10.1016\/j.cell.2012.02.040","article-title":"Alzheimer mechanisms and therapeutic strategies","volume":"148","author":"Huang","year":"2012","journal-title":"Cell"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.neurobiolaging.2004.03.008","article-title":"Decreased EEG synchronization in Alzheimer\u2019s disease and mild cognitive impairment","volume":"26","author":"Koenig","year":"2005","journal-title":"Neurobiol. Aging"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1016\/S0197-4580(00)00153-6","article-title":"Quantitative electroencephalography in mild cognitive impairment: Longitudinal changes and possible prediction of Alzheimer\u2019s disease","volume":"21","author":"Jelic","year":"2000","journal-title":"Neurobiol. Aging"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.1007\/s00702-003-0024-8","article-title":"EEG coherence in Alzheimer\u2019s dementia","volume":"110","author":"Adler","year":"2003","journal-title":"J. Neural Transm."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1931","DOI":"10.1016\/j.clinph.2007.05.070","article-title":"EEG correlates in the spectrum of cognitive decline","volume":"118","author":"Vein","year":"2007","journal-title":"Clin. Neurophysiol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1718","DOI":"10.1016\/j.clinph.2011.02.011","article-title":"Differences in quantitative EEG between frontotemporal dementia and Alzheimer\u2019s disease as revealed by LORETA","volume":"122","author":"Nishida","year":"2011","journal-title":"Clin. Neurophysiol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1089\/brain.2012.0088","article-title":"EEG Alpha Power Modulation of fMRI Resting-State Connectivity","volume":"2","author":"Scheeringa","year":"2012","journal-title":"Brain Connect"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1111\/j.1469-8986.1995.tb02100.x","article-title":"Dimensional analysis of resting human EEG II: Surrogate-data testing indicates nonlinearity but not low-dimensional chaos","volume":"32","author":"Pritchard","year":"1995","journal-title":"Psychophysiology"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1016\/0006-3223(94)90004-3","article-title":"Quantification of occipital EEG changes in Alzheimer\u2019s disease utilizing a new metric: The fractal dimension","volume":"35","author":"Woyshville","year":"1994","journal-title":"Biol. Psychiatry"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1093\/cercor\/bhj127","article-title":"Small-world networks and functional connectivity in Alzheimer\u2019s disease","volume":"17","author":"Stam","year":"2007","journal-title":"Cereb. Cortex"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1038\/nrn3801","article-title":"Modern network science of neurological disorders","volume":"15","author":"Stam","year":"2014","journal-title":"Nat. Rev. Neurosci."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1159","DOI":"10.1016\/S1388-2457(99)00013-9","article-title":"Decrease of non-linear structure in the EEG of Alzheimer patients compared to healthy controls","volume":"110","author":"Jelles","year":"1999","journal-title":"Clin. Neurophysiol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"668","DOI":"10.1016\/j.neuroimage.2009.06.056","article-title":"A comparative study of synchrony measures for the early diagnosis of Alzheimer\u2019s disease based on EEG","volume":"49","author":"Dauwels","year":"2010","journal-title":"Neuroimage"},{"key":"ref_45","first-page":"3182","article-title":"Multiscale dispersion entropy for the regional analysis of resting-state magnetoencephalogram complexity in Alzheimer\u2019s disease","volume":"2017","author":"Azami","year":"2017","journal-title":"Conf. Proc. IEEE Eng. Med. Biol. Soc."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/0925-4927(93)90027-F","article-title":"Dementia of the alzheimer type: Effects on the spontaneous EEG described by dipole sources","volume":"50","author":"Dierks","year":"1993","journal-title":"Psychiatry Res. Neuroimaging"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/j.neuroimage.2008.08.005","article-title":"Hippocampal volume and cortical sources of EEG alpha rhythms in mild cognitive impairment and Alzheimer disease","volume":"44","author":"Babiloni","year":"2009","journal-title":"NeuroImage"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"201","DOI":"10.3233\/JAD-2011-0051","article-title":"Resting state cortical rhythms in mild cognitive impairment and Alzheimer\u2019s disease: Electroencephalographic evidence","volume":"26","author":"Babiloni","year":"2011","journal-title":"J. Alzheimers Dis."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Canuet, L., Tellado, I., Couceiro, V., Fraile, C., Fernandez-Novoa, L., Ishii, R., Takeda, M., and Cacabelos, R. (2012). Resting-state network disruption and APOE genotype in Alzheimer\u2019s disease: A lagged functional connectivity study. PLoS ONE, 7.","DOI":"10.1371\/journal.pone.0046289"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Hsiao, F.-J., Wang, Y.-J., Yan, S.-H., Chen, W.-T., and Lin, Y.-Y. (2013). Altered Oscillation and Synchronization of Default-Mode Network Activity in Mild Alzheimer\u2019s Disease Compared to Mild Cognitive Impairment: An Electrophysiological Study. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0068792"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1016\/j.neurobiolaging.2013.06.019","article-title":"Cortical sources of resting state electroencephalographic alpha rhythms deteriorate across time in subjects with amnesic mild cognitive impairment","volume":"35","author":"Babiloni","year":"2014","journal-title":"Neurobiol. Aging"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.ijpsycho.2015.02.008","article-title":"Brain neural synchronization and functional coupling in Alzheimer\u2019s disease as revealed by resting state EEG rhythms","volume":"103","author":"Babiloni","year":"2016","journal-title":"Int. J. Psychophysiol."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1111\/j.1479-8301.2012.00431.x","article-title":"The relationship between the diagnosis method of neuronal dysfunction (DIMENSION) and brain pathology in the early stages of Alzheimer\u2019s disease","volume":"13","author":"Kouzuki","year":"2013","journal-title":"Psychogeriatrics"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1490","DOI":"10.1016\/j.clinph.2004.01.001","article-title":"EEG dynamics in patients with Alzheimer\u2019s disease","volume":"115","author":"Jeong","year":"2004","journal-title":"Clin. Neurophysiol."},{"key":"ref_55","first-page":"317","article-title":"Nonlinear analysis of electroencephalogram and magnetoencephalogram recordings in patients with Alzheimer\u2019s disease","volume":"367","author":"Hornero","year":"2009","journal-title":"Philos. Trans. A Math. Phys. Eng. Sci."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/0167-2789(83)90298-1","article-title":"Measuring the strangeness of strange attractors","volume":"9","author":"Grassberger","year":"1983","journal-title":"Phys. D Nonlinear Phenom."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/0167-2789(85)90011-9","article-title":"Determining Lyapunov exponents from a time series","volume":"16","author":"Wolf","year":"1985","journal-title":"Phys. D Nonlinear Phenom."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"340","DOI":"10.1038\/nn.4497","article-title":"Dynamic models of large-scale brain activity","volume":"20","author":"Breakspear","year":"2017","journal-title":"Nat. Neurosci."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1016\/j.clinph.2014.07.005","article-title":"Quantitative EEG markers relate to Alzheimer\u2019s disease severity in the Prospective Dementia Registry Austria (PRODEM)","volume":"126","author":"Garn","year":"2015","journal-title":"Clin. Neurophysiol."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.bspc.2015.08.004","article-title":"Improved multiscale permutation entropy for biomedical signal analysis: Interpretation and application to electroencephalogram recordings","volume":"23","author":"Azami","year":"2016","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Smits, F.M., Porcaro, C., Cottone, C., Cancelli, A., Rossini, P.M., and Tecchio, F. (2016). Electroencephalographic Fractal Dimension in Healthy Ageing and Alzheimer\u2019s Disease. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0149587"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/0167-2789(88)90081-4","article-title":"Approach to an irregular time series on the basis of the fractal theory","volume":"31","author":"Higuchi","year":"1988","journal-title":"Phys. D Nonlinear Phenom."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/0010-4825(88)90041-8","article-title":"Fractals and the analysis of waveforms","volume":"18","author":"Katz","year":"1988","journal-title":"Comput. Biol. Med."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"H2039","DOI":"10.1152\/ajpheart.2000.278.6.H2039","article-title":"Physiological time-series analysis using approximate entropy and sample entropy","volume":"278","author":"Richman","year":"2000","journal-title":"Am. J. Physiol. Heart Circ. Physiol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"174102","DOI":"10.1103\/PhysRevLett.88.174102","article-title":"Permutation entropy: A natural complexity measure for time series","volume":"88","author":"Bandt","year":"2002","journal-title":"Phys. Rev. Lett."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"3110","DOI":"10.3390\/e17053110","article-title":"The Multiscale Entropy Algorithm and Its Variants: A Review","volume":"17","year":"2015","journal-title":"Entropy"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"021906","DOI":"10.1103\/PhysRevE.71.021906","article-title":"Multiscale entropy analysis of biological signals","volume":"71","author":"Costa","year":"2005","journal-title":"Phys. Rev. E Stat. Nonlin. Soft Matter Phys."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/j.pnpbp.2012.09.015","article-title":"Is mental illness complex? From behavior to brain","volume":"45","author":"Yang","year":"2013","journal-title":"Prog. Neuropsychopharmacol. Biol. Psychiatry"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"1091","DOI":"10.1088\/0967-3334\/27\/11\/004","article-title":"Analysis of electroencephalograms in Alzheimer\u2019s disease patients with multiscale entropy","volume":"27","author":"Escudero","year":"2006","journal-title":"Physiol. Meas."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/j.jneumeth.2016.09.004","article-title":"The multiscale entropy: Guidelines for use and interpretation in brain signal analysis","volume":"273","author":"Courtiol","year":"2016","journal-title":"J. Neurosci. Methods"},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Azami, H., Ab\u00e1solo, D., Simons, S., and Escudero, J. (2017). Univariate and Multivariate Generalized Multiscale Entropy to Characterise EEG Signals in Alzheimer\u2019s Disease. Entropy, 19.","DOI":"10.3390\/e19010031"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"061918","DOI":"10.1103\/PhysRevE.84.061918","article-title":"Multivariate multiscale entropy: A tool for complexity analysis of multichannel data","volume":"84","author":"Ahmed","year":"2011","journal-title":"Phys. Rev. E Stat. Nonlin. Soft Matter Phys."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"3284","DOI":"10.1109\/JSEN.2013.2271735","article-title":"Entropic Measures of EEG Complexity in Alzheimer\u2019s Disease Through a Multivariate Multiscale Approach","volume":"13","author":"Labate","year":"2013","journal-title":"IEEE Sens. J."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Azami, H., Escudero, J., and Fern\u00e1ndez, A. (2016, January 29\u201330). Refined composite multivariate multiscale entropy based on variance for analysis of resting-state magnetoencephalograms in Alzheimer\u2019s disease. Proceedings of the 2016 International Conference for Students on Applied Engineering (ICSAE), Qingdao, China.","DOI":"10.1109\/ICSAE.2016.7810227"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"2414","DOI":"10.1166\/asl.2013.4966","article-title":"Analysis of Electroencephalography Activity in Early Stage Alzheimer\u2019s Disease Using a Multiscale Statistical Complexity Measure","volume":"19","author":"Morison","year":"2013","journal-title":"Adv. Sci. Lett."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.ijpsycho.2017.07.006","article-title":"Classification of mild cognitive impairment EEG using combined recurrence and cross recurrence quantification analysis","volume":"120","author":"Timothy","year":"2017","journal-title":"Int. J. Psychophysiol."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1242\/jeb.153.1.177","article-title":"The formation of cooperative cell assemblies in the visual cortex","volume":"153","author":"Singer","year":"1990","journal-title":"J. Exp. Biol."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1002\/hbm.1050","article-title":"Analysis and visualization of single-trial event-related potentials","volume":"14","author":"Jung","year":"2001","journal-title":"Hum. Brain Mapp."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"690","DOI":"10.1126\/science.1066168","article-title":"Dynamic brain sources of visual evoked responses","volume":"295","author":"Makeig","year":"2002","journal-title":"Science"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"909","DOI":"10.1016\/j.neuroimage.2005.10.036","article-title":"Modulation of spectral power and of phase resetting of EEG contributes differentially to the generation of auditory event-related potentials","volume":"30","author":"Fuentemilla","year":"2006","journal-title":"Neuroimage"},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1113\/jphysiol.1939.sp003798","article-title":"Impulses in the pyramidal tract","volume":"97","author":"Adrian","year":"1939","journal-title":"J. Physiol."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"781","DOI":"10.1038\/436781a","article-title":"Neuroscience: Neurons and navigation","volume":"436","year":"2005","journal-title":"Nature"},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"1833","DOI":"10.1016\/j.clinph.2019.06.006","article-title":"Methods for analysis of brain connectivity: An IFCN-sponsored review","volume":"130","author":"Rossini","year":"2019","journal-title":"Clin. Neurophysiol."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.neuron.2006.09.020","article-title":"Neural synchrony in brain disorders: Relevance for cognitive dysfunctions and pathophysiology","volume":"52","author":"Uhlhaas","year":"2006","journal-title":"Neuron"},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"484","DOI":"10.1038\/nn.3952","article-title":"What does gamma coherence tell us about inter-regional neural communication?","volume":"18","author":"Schomburg","year":"2015","journal-title":"Nat. Neurosci."},{"key":"ref_86","first-page":"2624","article-title":"Time-frequency analysis of electroencephalogram series","volume":"51","author":"Blanco","year":"1995","journal-title":"Phys. Rev. E Stat. Phys. Plasmas Fluids Relat. Interdiscip. Topics"},{"key":"ref_87","unstructured":"Nunez, P.L. (2020, March 26). Spatial-Temporal Structures of Human Alpha Rhythms: Theory, Microcurrent Sources, Multiscale Measurements, and Global Binding of Local Networks. Available online: https:\/\/onlinelibrary.wiley.com\/doi\/full\/10.1002\/hbm.1030."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"2190","DOI":"10.1016\/j.sigpro.2005.07.010","article-title":"Nonstationary nature of the brain activity as revealed by EEG\/MEG: Methodological, practical and conceptual challenges","volume":"85","author":"Kaplan","year":"2005","journal-title":"Signal Process."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1016\/j.bbr.2016.09.057","article-title":"Searching for signs of aging and dementia in EEG through network analysis","volume":"317","author":"Miraglia","year":"2017","journal-title":"Behav. Brain Res."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"913","DOI":"10.1098\/rstb.2005.1637","article-title":"Comparing functional connectivity via thresholding correlations and singular value decomposition","volume":"360","author":"Worsley","year":"2005","journal-title":"Philos. Trans. R Soc. Lond. B Biol. Sci."},{"key":"ref_91","doi-asserted-by":"crossref","unstructured":"Canuet, L., Ishii, R., Pascual-Marqui, R.D., Iwase, M., Kurimoto, R., Aoki, Y., Ikeda, S., Takahashi, H., Nakahachi, T., and Takeda, M. (2011). Resting-state EEG source localization and functional connectivity in schizophrenia-like psychosis of epilepsy. PLoS ONE, 6.","DOI":"10.1371\/journal.pone.0027863"},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"1995","DOI":"10.1016\/j.clinph.2014.02.018","article-title":"Sequential processing in the equiprobable auditory Go\/NoGo task: Children vs. adults","volume":"125","author":"Barry","year":"2014","journal-title":"Clin. Neurophysiol."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"31","DOI":"10.3389\/fnhum.2015.00031","article-title":"Detection of EEG-resting state independent networks by eLORETA-ICA method","volume":"9","author":"Aoki","year":"2015","journal-title":"Front. Hum. Neurosci."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1159\/000368119","article-title":"Emotion Regulation of Neuroticism: Emotional Information Processing Related to Psychosomatic State Evaluated by Electroencephalography and Exact Low-Resolution Brain Electromagnetic Tomography","volume":"71","author":"Ikeda","year":"2015","journal-title":"Neuropsychobiology"},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"919","DOI":"10.1093\/schbul\/sbu134","article-title":"Aberrant Current Source-Density and Lagged Phase Synchronization of Neural Oscillations as Markers for Emerging Psychosis","volume":"41","author":"Ramyead","year":"2015","journal-title":"Schizophr. Bull."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"1239","DOI":"10.3233\/JAD-140090","article-title":"Human brain networks in physiological aging: A graph theoretical analysis of cortical connectivity from EEG data","volume":"41","author":"Vecchio","year":"2014","journal-title":"J. Alzheimers Dis."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"745","DOI":"10.3233\/JAD-142484","article-title":"Cortical brain connectivity evaluated by graph theory in dementia: A correlation study between functional and structural data","volume":"45","author":"Vecchio","year":"2015","journal-title":"J. Alzheimers Dis."},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"113","DOI":"10.3233\/JAD-132087","article-title":"Human brain networks in cognitive decline: A graph theoretical analysis of cortical connectivity from EEG data","volume":"41","author":"Vecchio","year":"2014","journal-title":"J. Alzheimers Dis."},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.neuroimage.2016.01.051","article-title":"Effects of transcranial direct current stimulation on the functional coupling of the sensorimotor cortical network","volume":"140","author":"Vecchio","year":"2016","journal-title":"Neuroimage"},{"key":"ref_100","doi-asserted-by":"crossref","unstructured":"Murray, M.M., and Wallace, M.T. (2012). Multisensory Integration through Neural Coherence. The Neural Bases of Multisensory Processes, CRC Press\/Taylor & Francis. Frontiers in Neuroscience.","DOI":"10.1201\/b11092"},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1146\/annurev.ne.18.030195.003011","article-title":"Visual feature integration and the temporal correlation hypothesis","volume":"18","author":"Singer","year":"1995","journal-title":"Annu. Rev. Neurosci."},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"1513","DOI":"10.1093\/brain\/121.8.1513","article-title":"Functional coupling and regional activation of human cortical motor areas during simple, internally paced and externally paced finger movements","volume":"121","author":"Gerloff","year":"1998","journal-title":"Brain"},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/S0896-6273(00)80821-1","article-title":"Neuronal synchrony: A versatile code for the definition of relations?","volume":"24","author":"Singer","year":"1999","journal-title":"Neuron"},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"2888","DOI":"10.1111\/ejn.12657","article-title":"The control of complex finger movements by directional information flow between mesial frontocentral areas and the primary motor cortex","volume":"40","author":"Boenstrup","year":"2014","journal-title":"Eur. J. Neurosci."},{"key":"ref_105","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1002\/(SICI)1097-0193(1999)8:4<194::AID-HBM4>3.0.CO;2-C","article-title":"Measuring phase synchrony in brain signals","volume":"8","author":"Lachaux","year":"1999","journal-title":"Hum. Brain Mapp."},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"066138","DOI":"10.1103\/PhysRevE.69.066138","article-title":"Estimating mutual information","volume":"69","author":"Kraskov","year":"2004","journal-title":"Phys. Rev. E Stat. Nonlin. Soft Matter Phys."},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"213","DOI":"10.55782\/ane-1995-1078","article-title":"Investigation of coherence structure and EEG activity propagation during sleep","volume":"55","author":"Blinowska","year":"1995","journal-title":"Acta Neurobiol. Exp."},{"key":"ref_108","doi-asserted-by":"crossref","first-page":"1273","DOI":"10.1016\/S1053-8119(03)00202-7","article-title":"Dynamic causal modelling","volume":"19","author":"Friston","year":"2003","journal-title":"Neuroimage"},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"1866","DOI":"10.1002\/hbm.20775","article-title":"Dynamic causal modeling for EEG and MEG","volume":"30","author":"Kiebel","year":"2009","journal-title":"Hum. Brain Mapp."},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"897","DOI":"10.1017\/S0033291715002895","article-title":"Meta-connectomics: Human brain network and connectivity meta-analyses","volume":"46","author":"Crossley","year":"2016","journal-title":"Psychol. Med."},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.neuroscience.2015.09.028","article-title":"Small-worldness characteristics and its gender relation in specific hemispheric networks","volume":"310","author":"Miraglia","year":"2015","journal-title":"Neuroscience"},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"1261","DOI":"10.1016\/j.clinph.2015.07.040","article-title":"EEG characteristics in \u201ceyes-open\u201d versus \u201ceyes-closed\u201d conditions: Small-world network architecture in healthy aging and age-related brain degeneration","volume":"127","author":"Miraglia","year":"2016","journal-title":"Clin. Neurophysiol."},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"1059","DOI":"10.1016\/j.neuroimage.2009.10.003","article-title":"Complex network measures of brain connectivity: Uses and interpretations","volume":"52","author":"Rubinov","year":"2010","journal-title":"Neuroimage"},{"key":"ref_114","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.neuroimage.2013.03.023","article-title":"The human connectome: Origins and challenges","volume":"80","author":"Sporns","year":"2013","journal-title":"Neuroimage"},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1089\/brain.2011.0043","article-title":"Disruption of functional brain networks in Alzheimer\u2019s disease: What can we learn from graph spectral analysis of resting-state magnetoencephalography?","volume":"2","author":"Wang","year":"2012","journal-title":"Brain Connect"},{"key":"ref_116","doi-asserted-by":"crossref","first-page":"065103","DOI":"10.1103\/PhysRevE.71.065103","article-title":"Intensity and coherence of motifs in weighted complex networks","volume":"71","author":"Onnela","year":"2005","journal-title":"Phys. Rev. E Stat. Nonlin. Soft Matter Phys."},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1016\/j.jneumeth.2018.08.026","article-title":"Comparison of statistical tests in effective connectivity analysis of ECoG data","volume":"308","author":"Moharramipour","year":"2018","journal-title":"J. Neurosci. Methods"},{"key":"ref_118","unstructured":"Vecchio, F., Miraglia, F., Al\u00f9, F., Judica, E., Cotelli, M., Pellicciari, M., and Rossini, P. Human brain networks in physiological and pathological aging: Reproducibility of EEG graph theoretical analysis in cortical connectivity, (Unpublished)."},{"key":"ref_119","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.neubiorev.2014.05.009","article-title":"Test-retest reliabilities of resting-state FMRI measurements in human brain functional connectomics: A systems neuroscience perspective","volume":"45","author":"Zuo","year":"2014","journal-title":"Neurosci. Biobehav. Rev."},{"key":"ref_120","doi-asserted-by":"crossref","unstructured":"120Colclough, G.L., Woolrich, M.W., Tewarie, P.K., Brookes, M.J., Quinn, A.J., and Smith, S.M. (2016). How reliable are MEG resting-state connectivity metrics?. Neuroimage, 138, 284\u2013293.","DOI":"10.1016\/j.neuroimage.2016.05.070"},{"key":"ref_121","doi-asserted-by":"crossref","first-page":"694","DOI":"10.3389\/fnins.2017.00694","article-title":"Improving the Reliability of Network Metrics in Structural Brain Networks by Integrating Different Network Weighting Strategies into a Single Graph","volume":"11","author":"Dimitriadis","year":"2017","journal-title":"Front. Neurosci."},{"key":"ref_122","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1038\/30918","article-title":"Collective dynamics of \u201csmall-world\u201d networks","volume":"393","author":"Watts","year":"1998","journal-title":"Nature"},{"key":"ref_123","doi-asserted-by":"crossref","first-page":"026121","DOI":"10.1103\/PhysRevE.68.026121","article-title":"Properties of highly clustered networks","volume":"68","author":"Newman","year":"2003","journal-title":"Phys. Rev. E Stat. Nonlin. Soft Matter Phys."},{"key":"ref_124","doi-asserted-by":"crossref","first-page":"198701","DOI":"10.1103\/PhysRevLett.87.198701","article-title":"Efficient behavior of small-world networks","volume":"87","author":"Latora","year":"2001","journal-title":"Phys. Rev. Lett."},{"key":"ref_125","doi-asserted-by":"crossref","first-page":"1969","DOI":"10.1002\/hbm.22306","article-title":"Time-varying coupling of EEG oscillations predicts excitability fluctuations in the primary motor cortex as reflected by motor evoked potentials amplitude: An EEG-TMS study","volume":"35","author":"Ferreri","year":"2014","journal-title":"Hum. Brain Mapp."},{"key":"ref_126","doi-asserted-by":"crossref","unstructured":"Vecchio, F., Miraglia, F., Judica, E., Cotelli, M., Al\u00f9, F., and Rossini, P.M. (2020). Human brain networks: A graph theoretical analysis of cortical connectivity normative database from EEG data in healthy elderly subjects. Geroscience.","DOI":"10.1007\/s11357-020-00176-2"},{"key":"ref_127","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1007\/s11682-016-9528-3","article-title":"\u201cSmall World\u201d architecture in brain connectivity and hippocampal volume in Alzheimer\u2019s disease: A study via graph theory from EEG data","volume":"11","author":"Vecchio","year":"2017","journal-title":"Brain Imaging Behav."},{"key":"ref_128","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1002\/ana.25289","article-title":"Sustainable method for Alzheimer dementia prediction in mild cognitive impairment: Electroencephalographic connectivity and graph theory combined with apolipoprotein E","volume":"84","author":"Vecchio","year":"2018","journal-title":"Ann. Neurol."},{"key":"ref_129","unstructured":"Schomer, D.L., and Silva, F.H.L.D. (2017). Niedermeyer\u2019s ElectroencephalographyBasic Principles, Clinical Applications, and Related Fields, Oxford University Press."},{"key":"ref_130","doi-asserted-by":"crossref","unstructured":"130Giri, M., Zhang, M., and L\u00fc, Y. (2016). Genes associated with Alzheimer\u2019s disease: An overview and current status. Clin. Interv. Aging, 11, 665\u2013681.","DOI":"10.2147\/CIA.S105769"},{"key":"ref_131","doi-asserted-by":"crossref","first-page":"2050004","DOI":"10.1142\/S0129065720500045","article-title":"Small World Index in Default Mode Network Predicts Progression from Mild Cognitive Impairment to Dementia","volume":"30","author":"Miraglia","year":"2020","journal-title":"Int. J. Neural Syst."},{"key":"ref_132","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1007\/s11571-011-9172-y","article-title":"Brain\u2019s alpha activity is highly reduced in euthymic bipolar disorder patients","volume":"6","author":"Ozerdem","year":"2012","journal-title":"Cogn. Neurodyn."},{"key":"ref_133","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/S1364-6613(99)01299-1","article-title":"Oscillatory gamma activity in humans and its role in object representation","volume":"3","author":"Bertrand","year":"1999","journal-title":"Trends Cogn. Sci."},{"key":"ref_134","doi-asserted-by":"crossref","first-page":"3322","DOI":"10.1111\/j.1460-9568.2008.06290.x","article-title":"Behavioral relevance of gamma-band activity for short-term memory-based auditory decision-making","volume":"27","author":"Kaiser","year":"2008","journal-title":"Eur. J. Neurosci."},{"key":"ref_135","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.tics.2012.12.003","article-title":"Gamma oscillations: Precise temporal coordination without a metronome","volume":"17","author":"Fries","year":"2013","journal-title":"Trends Cogn. Sci."},{"key":"ref_136","doi-asserted-by":"crossref","first-page":"1077","DOI":"10.1016\/j.neuron.2013.08.019","article-title":"Attentional modulation of cell-class-specific gamma-band synchronization in awake monkey area v4","volume":"80","author":"Vinck","year":"2013","journal-title":"Neuron"},{"key":"ref_137","unstructured":"Abeles, M. (2020, March 26). Corticonics: Neural Circuits of the Cerebral Cortex. Available online: \/core\/books\/corticonics\/7BF149062695412A32FFC1255C98B410."},{"key":"ref_138","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1016\/j.tics.2005.08.011","article-title":"A mechanism for cognitive dynamics: Neuronal communication through neuronal coherence","volume":"9","author":"Fries","year":"2005","journal-title":"Trends Cogn. Sci."},{"key":"ref_139","doi-asserted-by":"crossref","first-page":"55","DOI":"10.3389\/fnagi.2014.00055","article-title":"The effects of automated artifact removal algorithms on electroencephalography-based Alzheimer\u2019s disease diagnosis","volume":"6","author":"Cassani","year":"2014","journal-title":"Front. Aging Neurosci."},{"key":"ref_140","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.cmpb.2018.06.011","article-title":"Early diagnosis of mild cognitive impairment and Alzheimer\u2019s with event-related potentials and event-related desynchronization in N-back working memory tasks","volume":"164","author":"Fraga","year":"2018","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_141","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1177\/155005941104200304","article-title":"Improving Alzheimer\u2019s disease diagnosis with machine learning techniques","volume":"42","author":"Trambaiolli","year":"2011","journal-title":"Clin. EEG Neurosci."},{"key":"ref_142","doi-asserted-by":"crossref","unstructured":"Cassani, R., Estarellas, M., San-Martin, R., Fraga, F.J., and Falk, T.H. (2018). Systematic Review on Resting-State EEG for Alzheimer\u2019s Disease Diagnosis and Progression Assessment. Dis. Markers, 2018.","DOI":"10.1155\/2018\/5174815"},{"key":"ref_143","doi-asserted-by":"crossref","unstructured":"Vecchio, F., Miraglia, F., Al\u00f9, F., Menna, M., Judica, E., Cotelli, M., and Rossini, P. (2020). Classification of Alzheimer\u2019s Disease respect to physiological aging with innovative EEG Biomarkers in a machine learning implementation. J. Alzheimer Dis., in press.","DOI":"10.3233\/JAD-200171"},{"key":"ref_144","doi-asserted-by":"crossref","first-page":"1106","DOI":"10.1016\/S0140-6736(85)92413-4","article-title":"Non-invasive magnetic stimulation of human motor cortex","volume":"1","author":"Barker","year":"1985","journal-title":"Lancet"},{"key":"ref_145","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1007\/s10548-009-0123-4","article-title":"Methodology for combined TMS and EEG","volume":"22","author":"Ilmoniemi","year":"2010","journal-title":"Brain Topogr."},{"key":"ref_146","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1016\/0168-5597(89)90030-0","article-title":"Comparison of human transcallosal responses evoked by magnetic coil and electrical stimulation","volume":"74","author":"Cracco","year":"1989","journal-title":"Electroencephalogr. Clin. Neurophysiol."},{"key":"ref_147","doi-asserted-by":"crossref","first-page":"3537","DOI":"10.1097\/00001756-199711100-00024","article-title":"Neuronal responses to magnetic stimulation reveal cortical reactivity and connectivity","volume":"8","author":"Ilmoniemi","year":"1997","journal-title":"Neuroreport"},{"key":"ref_148","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1515\/revneuro-2013-0019","article-title":"TMS and TMS-EEG techniques in the study of the excitability, connectivity, and plasticity of the human motor cortex","volume":"24","author":"Ferreri","year":"2013","journal-title":"Rev. Neurosci."},{"key":"ref_149","doi-asserted-by":"crossref","first-page":"1699","DOI":"10.1016\/j.clinph.2006.05.006","article-title":"Transcranial magnetic stimulation and cortical evoked potentials: A TMS\/EEG co-registration study","volume":"117","author":"Bonato","year":"2006","journal-title":"Clin. Neurophysiol."},{"key":"ref_150","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.neuroimage.2010.07.056","article-title":"Human brain connectivity during single and paired pulse transcranial magnetic stimulation","volume":"54","author":"Ferreri","year":"2011","journal-title":"Neuroimage"},{"key":"ref_151","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1152\/jn.00796.2011","article-title":"Human brain cortical correlates of short-latency afferent inhibition: A combined EEG-TMS study","volume":"108","author":"Ferreri","year":"2012","journal-title":"J. Neurophysiol."},{"key":"ref_152","doi-asserted-by":"crossref","first-page":"2228","DOI":"10.1126\/science.1117256","article-title":"Breakdown of cortical effective connectivity during sleep","volume":"309","author":"Massimini","year":"2005","journal-title":"Science"},{"key":"ref_153","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/j.neuroscience.2017.06.014","article-title":"Age-related changes of cortical excitability and connectivity in healthy humans: Non-invasive evaluation of sensorimotor network by means of TMS-EEG","volume":"357","author":"Ferreri","year":"2017","journal-title":"Neuroscience"},{"key":"ref_154","doi-asserted-by":"crossref","first-page":"7679","DOI":"10.1523\/JNEUROSCI.0445-09.2009","article-title":"Natural frequencies of human corticothalamic circuits","volume":"29","author":"Rosanova","year":"2009","journal-title":"J. Neurosci."},{"key":"ref_155","doi-asserted-by":"crossref","first-page":"252","DOI":"10.3389\/fnagi.2017.00252","article-title":"Corrigendum: Oscillatory Activities in Neurological Disorders of Elderly: Biomarkers to Target for Neuromodulation","volume":"9","author":"Assenza","year":"2017","journal-title":"Front. Aging Neurosci."},{"key":"ref_156","doi-asserted-by":"crossref","first-page":"654794","DOI":"10.4061\/2011\/654794","article-title":"Combining transcranial magnetic stimulation and electroencephalography may contribute to assess the severity of Alzheimer\u2019s disease","volume":"2011","author":"Julkunen","year":"2011","journal-title":"Int. J. Alzheimers Dis."},{"key":"ref_157","doi-asserted-by":"crossref","first-page":"592","DOI":"10.1097\/WNR.0b013e328349433a","article-title":"Transcranial magnetic stimulation-evoked EEG\/cortical potentials in physiological and pathological aging","volume":"22","author":"Casarotto","year":"2011","journal-title":"Neuroreport"},{"key":"ref_158","doi-asserted-by":"crossref","first-page":"2083","DOI":"10.1002\/hbm.23158","article-title":"Sensorimotor cortex excitability and connectivity in Alzheimer\u2019s disease: A TMS-EEG Co-registration study","volume":"37","author":"Ferreri","year":"2016","journal-title":"Hum. Brain Mapp."},{"key":"ref_159","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.neurobiolaging.2019.04.008","article-title":"Predicting Alzheimer\u2019s disease severity by means of TMS-EEG coregistration","volume":"80","author":"Bagattini","year":"2019","journal-title":"Neurobiol. Aging"},{"key":"ref_160","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1016\/j.neuroimage.2017.12.048","article-title":"Transcranial magnetic stimulation of the precuneus enhances memory and neural activity in prodromal Alzheimer\u2019s disease","volume":"169","author":"Koch","year":"2018","journal-title":"Neuroimage"},{"key":"ref_161","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1002\/ana.10416","article-title":"Motor cortex excitability in Alzheimer\u2019s disease: A transcranial magnetic stimulation study","volume":"53","author":"Ferreri","year":"2003","journal-title":"Ann. Neurol."},{"key":"ref_162","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.neulet.2011.01.064","article-title":"Motor cortex excitability in Alzheimer\u2019s disease: A transcranial magnetic stimulation follow-up study","volume":"492","author":"Ferreri","year":"2011","journal-title":"Neurosci. 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