Home Functional changes in brain oscillations in dementia: a review
Article
Licensed
Unlicensed Requires Authentication

Functional changes in brain oscillations in dementia: a review

  • Andreina Giustiniani ORCID logo EMAIL logo , Laura Danesin , Beatrice Bozzetto , AnnaRita Macina , Silvia Benavides-Varela and Francesca Burgio
Published/Copyright: June 21, 2022
Become an author with De Gruyter Brill

Abstract

A growing body of evidence indicates that several characteristics of electroencephalography (EEG) and magnetoencephalography (MEG) play a functional role in cognition and could be linked to the progression of cognitive decline in some neurological diseases such as dementia. The present paper reviews previous studies investigating changes in brain oscillations associated to the most common types of dementia, namely Alzheimer’s disease (AD), frontotemporal degeneration (FTD), and vascular dementia (VaD), with the aim of identifying pathology-specific patterns of alterations and supporting differential diagnosis in clinical practice. The included studies analysed changes in frequency power, functional connectivity, and event-related potentials, as well as the relationship between electrophysiological changes and cognitive deficits. Current evidence suggests that an increase in slow wave activity (i.e., theta and delta) as well as a general reduction in the power of faster frequency bands (i.e., alpha and beta) characterizes AD, VaD, and FTD. Additionally, compared to healthy controls, AD exhibits alteration in latencies and amplitudes of the most common event related potentials. In the reviewed studies, these changes generally correlate with performances in many cognitive tests. In conclusion, particularly in AD, neurophysiological changes can be reliable early markers of dementia.


Corresponding author: Andreina Giustiniani, Neuropsychology Department, IRCCS San Camillo Hospital, via Alberoni 70,30126, Venice, Italy, E-mail:

Funding source: Ministero della Salute

Award Identifier / Grant number: GR-2018-12367927

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: This work was supported by “Progetto giovani ricercatori: FINAGE” (GR-2018-12367927) from the Ministry of Health to F. B.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

References

Adaikkan, C. and Tsai, L.H. (2020). Gamma entrainment: impact on neurocircuits, glia, and therapeutic opportunities. Trends Neurosci. 43: 24–41.10.1016/j.tins.2019.11.001Search in Google Scholar PubMed

Adams, N.E., Hughes, L.E., Rouse, M.A., Phillips, H.N., Shaw, A.D., Murley, A.G., Cope, T.E., Bevan-Jones, W.R., Passamonti, L., Street, D., et al.. (2021). GABAergic cortical network physiology in frontotemporal lobar degeneration. Brain 144: 2135–2145.10.1093/brain/awab097Search in Google Scholar PubMed PubMed Central

Adler, G., Brassen, S., and Jajcevic, A. (2003). EEG coherence in Alzheimer’s dementia. J. Neural. Transm. 110: 1051–1058.10.1007/s00702-003-0024-8Search in Google Scholar PubMed

Ally, B.A., Jones, G.E., Cole, J.A., and Budson, A.E. (2006). The P300 component in patients with Alzheimer’s disease and their biological children. Biol. Psychol. 72: 180–187.10.1016/j.biopsycho.2005.10.004Search in Google Scholar PubMed

Ashford, J.W., Coburn, K.L., Rose, T.L., and Bayley, P.J. (2011). P300 energy loss in aging and Alzheimers disease. J. Alzheim. Dis. 26: 229–238.10.3233/JAD-2011-0061Search in Google Scholar PubMed

Babiloni, C., Binetti, G., Cassetta, E., Cerboneschi, D., Dal Forno, G., Del Percio, C., Ferreri, F., Ferri, R., Lanuzza, B., Miniussi, C., et al.. (2004a). Mapping distributed sources of cortical rhythms in mild Alzheimer’s disease. A multicentric EEG study. NeuroImage 22: 57–67.10.1016/j.neuroimage.2003.09.028Search in Google Scholar PubMed

Babiloni, C., Ferri, R., Moretti, D.V., Strambi, A., Binetti, G., Dal Forno, G., Ferreri, F., Lanuzza, B., Bonato, C., Nobili, F., et al.. (2004b). Abnormal fronto-parietal coupling of brain rhythms in mild Alzheimer’s disease: a multicentric EEG study. Eur. J. Neurosci. 19: 2583–2590.10.1111/j.0953-816X.2004.03333.xSearch in Google Scholar PubMed

Babiloni, C., Binetti, G., Cassetta, E., Forno, G.D., Del, Percio C., Ferreri, F., Ferri, R., Frisoni, G., Hirata, K., Lanuzza, B., et al.. (2006a). Sources of cortical rhythms change as a function of cognitive impairment in pathological aging: a multicenter study. Clin. Neurophysiol. 117: 252–268.10.1016/j.clinph.2005.09.019Search in Google Scholar PubMed

Babiloni, C., Frisoni, G., Steriade, M., Bresciani, L., Binetti, G., Del Percio, C., Geroldi, C., Miniussi, C., Nobili, F., Rodriguez, G., et al.. (2006b). Frontal white matter volume and delta EEG sources negatively correlate in awake subjects with mild cognitive impairment and Alzheimer’s disease. Clin. Neurophysiol. 117: 113–1129.10.1016/j.clinph.2006.01.020Search in Google Scholar PubMed

Babiloni, C., Bosco, P., Ghidoni, R., Del Percio, C., Squitti, R., Binetti, G., Benussi, L., Ferri, R., Frisoni, G., Lanuzza, B., et al.. (2007a). Homocysteine and electroencephalographic rhythms in Alzheimer disease: a multicentric study. Neuroscience 145: 942–954.10.1016/j.neuroscience.2006.12.065Search in Google Scholar PubMed

Babiloni, C., Cassetta, E., Binetti, G., Tombini, M., Del Percio, C., Ferreri, F., Ferri, R., Frisoni, G., Lanuzza, B., Nobili, F., et al.. (2007b). Resting EEG sources correlate with attentional span in mild cognitive impairment and Alzheimer’s disease. Eur. J. Neurosci. 25: 3742–3757.10.1111/j.1460-9568.2007.05601.xSearch in Google Scholar PubMed

Babiloni, C., De Pandis, M.F., Vecchio, F., Buffo, P., Sorpresi, F., Frisoni, G.B., and Rossini, P.M. (2011a). Cortical sources of resting state electroencephalographic rhythms in Parkinson’s disease related dementia and Alzheimer’s disease. Clin. Neurophysiol. 122: 2355–2364.10.1016/j.clinph.2011.03.029Search in Google Scholar PubMed

Babiloni, C., Lizio, R., Carducci, F., Vecchio, F., Redolfi, A., Marino, S., Tedeschi, G., Montella, P., Guizzaro, A., Esposito, F., et al.. (2011b). Resting state cortical electroencephalographic rhythms and white matter vascular lesions in subjects with Alzheimer’s disease: an Italian multicenter study. J. Alzheim. Dis. 26: 331–346.10.3233/JAD-2011-101710Search in Google Scholar PubMed

Babiloni, C., Carducci, F., Lizio, R., Vecchio, F., Baglieri, A., Bernardini, S., Cavedo, E., Bozzao, A., Buttinelli, C., Esposito, F., et al.. (2013a). Resting state cortical electroencephalographic rhythms are related to gray matter volume in subjects with mild cognitive impairment and Alzheimer’s disease. Hum. Brain 36: 1427–1446.10.1002/hbm.22005Search in Google Scholar PubMed PubMed Central

Babiloni, C., Lizio, R., Del Percio, C., Marzano, N., Soricelli, A., Salvatore, E., Ferri, R., Cosentino, F.I.I., Tedeschi, G., Montella, P., et al.. (2013b). Cortical sources of resting state EEG rhythms are sensitive to the progression of early stage Alzheimer’s disease. J. Alzheim. Dis. 34: 1015–1035.10.3233/JAD-121750Search in Google Scholar PubMed

Babiloni, C., Del Percio, C., Boccardi, M., Lizio, R., Lopez, S., Carducci, F., Marzano, N., Soricelli, A., Ferri, R., Triggiani, A.I., et al.. (2015). Occipital sources of resting-state alpha rhythms are related to local gray matter density in subjects with amnesic mild cognitive impairment and Alzheimer’s disease. Neurobiol. Aging 36: 556–570.10.1016/j.neurobiolaging.2014.09.011Search in Google Scholar PubMed PubMed Central

Babiloni, C., Del Percio, C., Caroli, A., Salvatore, E., Nicolai, E., Marzano, N., Lizio, R., Cavedo, E., Landau, S., Chen, K., et al.. (2016). Cortical sources of resting state EEG rhythms are related to brain hypometabolism in subjects with Alzheimer’s disease: an EEG-PET study. Neurobiol. Aging 48: 122–134.10.1016/j.neurobiolaging.2016.08.021Search in Google Scholar PubMed

Baddeley, A.D., Baddeley, H.A., Bucks, R.S., and Wilcock, G.K. (2001). Attentional control in Alzheimer’s disease. Brain 124: 1479–1481.10.1093/brain/124.8.1492Search in Google Scholar PubMed

Başar-Eroglu, C., Başar, E., Demiralp, T., and Schürmann, M. (1992). P300-response: possible psychophysiological correlates in delta and theta frequency channels. A review. Int. J. Psychophysiol. 13: 161–179.10.1016/0167-8760(92)90055-GSearch in Google Scholar PubMed

Başar, E., Başar-Eroǧlu, C., Güntekin, B., and Yener, G.G. (2013). Brain’s alpha, beta, gamma, delta, and theta oscillations in neuropsychiatric diseases: proposal for biomarker strategies. Suppl. Clin. Neurophysiol. 62: 19–54.10.1016/B978-0-7020-5307-8.00002-8Search in Google Scholar

Başar, E. and Düzgün, A. (2016). How is the brain working? Research on brain oscillations and connectivities in a new “Take-Off” state. Int. J. Psychophysiol. 103: 3–11.10.1016/j.ijpsycho.2015.02.007Search in Google Scholar PubMed

Başar, E., Femir, B., Emek-Savaş, D.D., Güntekin, B., and Yener, G.G. (2017). Increased long distance event-related gamma band connectivity in Alzheimer’s disease. NeuroImage Clin. 14: 580–590.10.1016/j.nicl.2017.02.021Search in Google Scholar PubMed PubMed Central

Bathgate, D., Snowden, J.S., Varma, A., Blackshaw, A., and Neary, D. (2001). Behaviour in frontotemporal dementia, Alzheimer’s disease and vascular dementia. Acta Neurol. Scand. 103: 367–378.10.1034/j.1600-0404.2001.2000236.xSearch in Google Scholar PubMed

Bauer, M., Oostenveld, R., Peeters, M., and Fries, P. (2006). Tactile spatial attention enhances gamma-band activity in somatosensory cortex and reduces low-frequency activity in parieto-occipital areas. J. Neurosci. 26: 490–501.10.1523/JNEUROSCI.5228-04.2006Search in Google Scholar PubMed PubMed Central

Bennys, K., Portet, F., Touchon, J., and Rondouin, G. (2007). Diagnostic value of event-related evoked potentials N200 and P300 subcomponents in early diagnosis of Alzheimer’s disease and mild cognitive impairment. J. Clin. Neurophysiol. 24: 405–412.10.1097/WNP.0b013e31815068d5Search in Google Scholar PubMed

Boise, L., Camicioli, R., Morgan, D.L., Rose, J.H., and Congleton, L. (1999). Diagnosing dementia: perspectives of primary care physicians. Gerontol. 39: 457–464.10.1093/geront/39.4.457Search in Google Scholar PubMed

Bonnefond, M. and Jensen, O. (2012). Alpha oscillations serve to protect working memory maintenance against anticipated distracters. Curr. Biol. 22: 1969–1974.10.1016/j.cub.2012.08.029Search in Google Scholar PubMed

Buffalo, E.A., Fries, P., Landman, R., Buschman, T.J., and Desimone, R. (2011). Laminar differences in gamma and alpha coherence in the ventral stream. Proc. Natl. Acad. Sci. U. S. A. 108: 11262–11267.10.1073/pnas.1011284108Search in Google Scholar PubMed PubMed Central

Cannon, J., Mccarthy, M.M., Lee, S., Lee, J., Börgers, C., Whittington, M.A., and Kopell, N. (2014). Neurosystems: brain rhythms and cognitive processing. Eur. J. Neurosci. 39: 705–719.10.1111/ejn.12453Search in Google Scholar PubMed PubMed Central

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’s disease: a lagged functional connectivity study. PLoS One 7: e46289.10.1371/journal.pone.0046289Search in Google Scholar PubMed PubMed Central

Caravaglios, G., Castro, G., Costanzo, E., Di Maria, G., Mancuso, D., and Muscoso, E.G. (2010). Theta power responses in mild Alzheimer’s disease during an auditory oddball paradigm: lack of theta enhancement during stimulus processing. J. Neural. Transm. 117: 1195–1208.10.1007/s00702-010-0488-2Search in Google Scholar PubMed

Caravaglios, G., Costanzo, E., Palermo, F., and Muscoso, E.G. (2008). Decreased amplitude of auditory event-related delta responses in Alzheimer’s disease. Int. J. Psychophysiol. 70: 23–32.10.1016/j.ijpsycho.2008.04.004Search in Google Scholar PubMed

Caso, F., Cursi, M., Magnani, G., Fanelli, G., Falautano, M., Comi, G., Leocani, L., and Minicucci, F. (2012). Quantitative EEG and LORETA: valuable tools in discerning FTD from AD? Neurobiol. Aging 33: 2343–2356.10.1016/j.neurobiolaging.2011.12.011Search in Google Scholar PubMed

Castellani, R.J., Rolston, R.K., and Smith, M.A. (2010). Alzheimer disease. Disease-a-month: DM 56: 484.10.1016/j.disamonth.2010.06.001Search in Google Scholar PubMed PubMed Central

Chang, Y.S., Chen, H.L., Hsu, C.Y., Tang, S.H., and Liu, C.K. (2014). Parallel improvement of cognitive functions and p300 latency following donepezil treatment in patients with Alzheimer’s disease: a case-control study. J. Clin. Neurophysiol. 31: 81–85.10.1097/01.wnp.0000436899.48243.5eSearch in Google Scholar PubMed

Chen, C.C., Kiebel, S.J., Kilner, J.M., Ward, N.S., Stephan, K.E., Wang, W.J., and Friston, K.J. (2012). A dynamic causal model for evoked and induced responses. NeuroImage 59: 340–348.10.1016/j.neuroimage.2011.07.066Search in Google Scholar PubMed PubMed Central

Chen, Y. and Huang, X. (2016). Modulation of alpha and beta oscillations during an n-back task with varying temporal memory load. Front. Psychol. 6: 2031.10.3389/fpsyg.2015.02031Search in Google Scholar PubMed PubMed Central

Collette, F. and Van Der Linden, M. (2002). Brain imaging of the central executive component of working memory. Neurosci. Biobehav. Rev. 26: 105–125.10.1016/S0149-7634(01)00063-XSearch in Google Scholar

Conley, E.M., Michalewski, H.J., and Starr, A. (1999). The N100 auditory cortical evoked potential indexes scanning of auditory short-term memory. Clin. Neurophysiol. 110: 2086–2093.10.1016/S1388-2457(99)00183-2Search in Google Scholar PubMed

Cummins, T.D.R. and Finnigan, S. (2007). Theta power is reduced in healthy cognitive aging. Int. J. Psychophysiol. 66: 10–17.10.1016/j.ijpsycho.2007.05.008Search in Google Scholar PubMed

Cunha, M., Hugo Bastos, V., Veiga, H., Cagy, M., McDowell, K., Furtado, V., Piedade, R., and Ribeiro, P. (2004). Changes in cortical power distribution produced by memory consolidation as a function of a typewriting skill. Arq. Neuropsiquiatr. 62: 662–668.10.1590/S0004-282X2004000400018Search in Google Scholar PubMed

D’Amelio, M. and Rossini, P.M. (2012). Brain excitability and connectivity of neuronal assemblies in Alzheimer’s disease: from animal models to human findings. Prog. Neurobiol. 99: 42–60.10.1016/j.pneurobio.2012.07.001Search in Google Scholar PubMed

de Haan, W., Stam, C.J., Jones, B.F., Zuiderwijk, I.M., Van Dijk, B.W., and Scheltens, P. (2008). Resting-state oscillatory brain dynamics in Alzheimer disease. J. Clin. Neurophysiol. 25: 187–193.10.1097/WNP.0b013e31817da184Search in Google Scholar PubMed

Delatour, B., Blanchard, V., Pradier, L., and Duyckaerts, C. (2004). Alzheimer pathology disorganizes cortico-cortical circuitry: direct evidence from a transgenic animal model. Neurobiol. Dis. 16: 41–47.10.1016/j.nbd.2004.01.008Search in Google Scholar PubMed

Donner, T.H., Siegel, M., Fries, P., and Engel, A.K. (2009). Buildup of choice-predictive activity in human motor cortex during perceptual decision making. Curr. Biol. 19: 1581–1585.10.1016/j.cub.2009.07.066Search in Google Scholar PubMed

Engels, M.M.A., Hillebrand, A., Van Der Flier, W.M., Stam, C.J., Scheltens, P., and Van Straaten, E.C.W. (2016). Slowing of hippocampal activity correlates with cognitive decline in early onset Alzheimer’s disease. An MEG study with virtual electrodes. Front. Hum. Neurosci. 10: 238.10.3389/fnhum.2016.00238Search in Google Scholar PubMed PubMed Central

Fernández, A., Arrazola, J., Maestú, F., Arno, C., Gil-Gregorio, P., Wienbruch, C., and Ortiz, T. (2003). Correlations of hippocampal atrophy and focal low-frequency magnetic activity in Alzheimer disease: volumetric MR imaging – magnetoencephalographic study. Am. J. Neuroradiol. 24: 481–487.Search in Google Scholar

Fonseca, Lineu C., Tedrus, G.M.A.S., Prandi, L.R., Almeida, A.M., and Furlanetto, D.S. (2011a). Alzheimer’s disease: relationship between cognitive aspects and power and coherence EEG measures. Arq. Neuropsiquiatr. 69: 875–881.10.1590/S0004-282X2011000700005Search in Google Scholar

Fonseca, L.C., Tedrus, G.M.A.S., Prandi, L.R., and de Andrade, A.C.A. (2011b). Quantitative electroencephalography power and coherence measurements in the diagnosis of mild and moderate Alzheimer’s disease. Arq. Neuropsiquiatr. 69: 297–303.10.1590/S0004-282X2011000300006Search in Google Scholar PubMed

Fries, P. (2005). A mechanism for cognitive dynamics: neuronal communication through neuronal coherence. Trends Cognit. Sci. 9: 474–480.10.1016/j.tics.2005.08.011Search in Google Scholar PubMed

Frodl, T., Hampel, H., Juckel, G., Bürger, K., Padberg, F., Engel, R.R., Möller, H.J., and Hegerl, U. (2002). Value of event-related P300 subcomponents in the clinical diagnosis of mild cognitive impairment and Alzheimer’s disease. Psychophysiology 39: 175–181.10.1111/1469-8986.3920175Search in Google Scholar

Gaetz, W., Edgar, J.C., Wang, D.J., and Roberts, T.P.L. (2011). Relating MEG measured motor cortical oscillations to resting γ-aminobutyric acid (GABA) concentration. Neuroimage 55: 616–621.10.1016/j.neuroimage.2010.12.077Search in Google Scholar PubMed PubMed Central

Gentili, R.J., Rietschel, J.C., Jaquess, K.J., Lo, L.C., Prevost, C.M., Miller, M.W., Mohler, J.M., Oh, H., Tan, Y.Y., and Hatfield, B.D. (2014). Brain biomarkers based assessment of cognitive workload in pilots under various task demands. In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC, pp. 5860–5863.10.1109/EMBC.2014.6944961Search in Google Scholar PubMed

Ghani, U., Signal, N., Niazi, I.K., and Taylor, D. (2020). ERP based measures of cognitive workload: a review. Neurosci. Biobehav. Rev. 118: 18–26.10.1016/j.neubiorev.2020.07.020Search in Google Scholar PubMed

Giacobini, E. (2003). Cholinergic function and Alzheimer’s disease. Int. J. Geriatr. Psychiatr. 18: S1–S5.10.1002/gps.935Search in Google Scholar PubMed

Gianotti, L.R.R., Künig, G., Lehmann, D., Faber, P.L., Pascual-Marqui, R.D., Kochi, K., and Schreiter-Gasser, U. (2007). Correlation between disease severity and brain electric LORETA tomography in Alzheimer’s disease. Clin. Neurophysiol. 118: 186–196.10.1016/j.clinph.2006.09.007Search in Google Scholar PubMed

Giovannetti, A.E. and Fuhrmann, M. (2019). Unsupervised excitation: GABAergic dysfunctions in Alzheimer’s disease. Brain Res. 1707: 216–226.10.1016/j.brainres.2018.11.042Search in Google Scholar PubMed

Gironell, A., García-Sánchez, C., Estévez-González, A., Boltes, A., and Kulisevsky, J. (2005). Usefulness of P300 in subjective memory complaints: a prospective study. J. Clin. Neurophysiol. 22: 279–284.10.1097/01.WNP.0000173559.60113.ABSearch in Google Scholar PubMed

Giustiniani, A., Tarantino, V., Bonaventura, R.E., Smirni, D., Turriziani, P., and Oliveri, M. (2019). Effects of low-gamma tACS on primary motor cortex in implicit motor learning. Behav. Brain Res. 376: 112170.10.1016/j.bbr.2019.112170Search in Google Scholar PubMed

Giustiniani, A., Tarantino, V., Bracco, M., Bonaventura, R.E., and Oliveri, M. (2021). Functional role of cerebellar gamma frequency in motor sequences learning: a tACS study. Cerebellum 20: 913–921.10.1007/s12311-021-01255-6Search in Google Scholar PubMed PubMed Central

Gruber, T., Tsivilis, D., Montaldi, D., and Müller, M.M. (2004). Induced gamma band responses: an early marker of memory encoding and retrieval. NeuroReport 15: 1837–1841.10.1097/01.wnr.0000137077.26010.12Search in Google Scholar PubMed

Hall, S.D., Stanford, I.M., Yamawaki, N., McAllister, C.J., Rönnqvist, K.C., Woodhall, G.L., and Furlong, P.L. (2011). The role of GABAergic modulation in motor function related neuronal network activity. Neuroimage 56: 1506–1510.10.1016/j.neuroimage.2011.02.025Search in Google Scholar PubMed

Hansenne, M., Pitchot, W., Pinto, E., Reggers, J., Papart, P., and Ansseau, M. (2000). P300 event-related brain potential and personality in depression. Eur. Psychiatr. 15: 370–377.10.1016/S0924-9338(00)00505-8Search in Google Scholar PubMed

Harmony, T. (2013). The functional significance of delta oscillations in cognitive processing. Front. Integr. Neurosci. 7: 83.10.3389/fnint.2013.00083Search in Google Scholar PubMed PubMed Central

Hata, M., Kazui, H., Tanaka, T., Ishii, R., Canuet, L., Pascual-Marqui, R.D., Aoki, Y., Ikeda, S., Kanemoto, H., Yoshiyama, K., et al.. (2016). Functional connectivity assessed by resting state EEG correlates with cognitive decline of Alzheimer’s disease – an eLORETA study. Clin. Neurophysiol. 127: 1269–1278.10.1016/j.clinph.2015.10.030Search in Google Scholar PubMed

Hauk, O., Davis, M.H., Ford, M., Pulvermüller, F., and Marslen-Wilson, W.D. (2006). The time course of visual word recognition as revealed by linear regression analysis of ERP data. Neuroimage 30: 1383–1400.10.1016/j.neuroimage.2005.11.048Search in Google Scholar PubMed

Herrmann, C.S. and Demiralp, T. (2005). Human EEG gamma oscillations in neuropsychiatric disorders. Clin. Neurophysiol. 116: 2719–2733.10.1016/j.clinph.2005.07.007Search in Google Scholar PubMed

Herweg, N.A., Solomon, E.A., and Kahana, M.J. (2020). Theta oscillations in human memory. Trends Cognit. Sci. 24: 208–227.10.1016/j.tics.2019.12.006Search in Google Scholar PubMed PubMed Central

Hirata, K., Hozumi, A., Tanaka, H., Kubo, J., Zeng, X.H., Yamazaki, K., Asahi, K., and Nakano, T. (2000). Abnormal information processing in dementia of Alzheimer type. A study using the event-related potential’s field. Eur. Arch. Psychiatr. Clin. Neurosci. 250: 152–155.10.1007/s004060070033Search in Google Scholar PubMed

Hohman, T.J., Tommet, D., Marks, S., Contreras, J., Jones, R., and Mungas, D. (2017). Evaluating Alzheimer’s disease biomarkers as mediators of age-related cognitive decline. Neurobiol. Aging 58: 120–128.10.1016/j.neurobiolaging.2017.06.022Search in Google Scholar PubMed PubMed Central

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’s disease compared to mild cognitive impairment: an electrophysiological study. PLoS One 8: e68792.10.1371/journal.pone.0068792Search in Google Scholar PubMed PubMed Central

Huang, C., Wahlund, L.O., Dierks, T., Julin, P., Winblad, B., and Jelic, V. (2000). Discrimination of Alzheimer’s disease and mild cognitive impairment by equivalent EEG sources: a cross-sectional and longitudinal study. Clin. Neurophysiol. 111: 1961–1967.10.1016/S1388-2457(00)00454-5Search in Google Scholar

Hughes, L.E., Rittman, T., Robbins, T.W., and Rowe, J.B. (2018). Reorganization of cortical oscillatory dynamics underlying disinhibition in frontotemporal dementia. Brain 141: 2486–2499.10.1093/brain/awy176Search in Google Scholar PubMed PubMed Central

Iaccarino, H.F., Singer, A.C., Martorell, A.J., Rudenko, A., Gao, F., Gillingham, T.Z., Mathys, H., Seo, J., Kritskiy, O., Abdurrob, F., et al.. (2016). Gamma frequency entrainment attenuates amyloid load and modifies microglia. Nature 540: 230–235.10.1038/nature20587Search in Google Scholar PubMed PubMed Central

Jacobs, J., Kahana, M.J., Ekstrom, A.D., and Fried, I. (2007). Brain oscillations control timing of single-neuron activity in humans. J. Neurosci. 27: 3839–3844.10.1523/JNEUROSCI.4636-06.2007Search in Google Scholar PubMed PubMed Central

Jafari, Z., Kolb, B.E., and Mohajerani, M.H. (2020). Neural oscillations and brain stimulation in Alzheimer’s disease. Progress in Neurobiology 194: 101878.10.1016/j.pneurobio.2020.101878Search in Google Scholar PubMed

Jensen, O., Bonnefond, M., Marshall, T.R., and Tiesinga, P. (2015). Oscillatory mechanisms of feedforward and feedback visual processing. Trends Neurosci. 38: 192–194.10.1016/j.tins.2015.02.006Search in Google Scholar PubMed

Jensen, O., Gips, B., Bergmann, T.O., and Bonnefond, M. (2014). Temporal coding organized by coupled alpha and gamma oscillations prioritize visual processing. Trends Neurosci. 37: 357–369.10.1016/j.tins.2014.04.001Search in Google Scholar PubMed

Jensen, O. and Mazaheri, A. (2010). Shaping functional architecture by oscillatory alpha activity: gating by inhibition. Front. Hum. Neurosci. 186.10.3389/fnhum.2010.00186Search in Google Scholar PubMed PubMed Central

Jensen, O., Spaak, E., and Zumer, J.M. (2019). Human brain oscillations: from physiological mechanisms to analysis and cognition. In: Magnetoencephalography: from signals to dynamic cortical networks, 2nd ed. Springer, Cham, pp. 471–517.10.1007/978-3-030-00087-5_17Search in Google Scholar

Jeong, J., Chae, J.H., Kim, S.Y., and Han, S.H. (2001). Nonlinear dynamic analysis of the EEG in patients with Alzheimer’s disease and vascular dementia. J. Clin. Neurophysiol. 18: 58–67.10.1097/00004691-200101000-00010Search in Google Scholar PubMed

John, E.R., Prichep, L.S., Fridman, J., and Easton, P. (1988). Neurometrics: computer-assisted differential diagnosis of brain dysfunctions. Science 239: 162–169.10.1126/science.3336779Search in Google Scholar PubMed

Jokisch, D. and Jensen, O. (2007). Modulation of gamma and alpha activity during a working memory task engaging the dorsal or ventral stream. J. Neurosci. 27: 3244–3251.10.1523/JNEUROSCI.5399-06.2007Search in Google Scholar PubMed PubMed Central

Juckel, G., Clotz, F., Frodl, T., Kawohl, W., Hampel, H., Pogarell, O., and Hegerl, U. (2008). Diagnostic usefulness of cognitive auditory event-related P300 subcomponents in patients with Alzheimers disease? J. Clin. Neurophysiol. 25: 147–152.10.1097/WNP.0b013e3181727c95Search in Google Scholar PubMed

Katada, E., Sato, K., Ojika, K., and Ueda, R. (2005). Cognitive event-related potentials: useful clinical information in Alzheimer’s disease. Curr. Alzheimer Res. 1: 63–69.10.2174/1567205043480609Search in Google Scholar PubMed

Kikuchi, M., Wada, Y., and Koshino, Y. (2002). Differences in EEG harmonic driving responses to photic stimulation between normal aging and Alzheimer’s disease. Clin. EEG Neurosci. 33: 86–92.10.1177/155005940203300208Search in Google Scholar PubMed

Killiany, R.J., Moss, M.B., Albert, M.S., Sandor, T., Tieman, J., and Jolesz, F. (1993). Temporal lobe regions on magnetic resonance imaging identify patients with early Alzheimer’s disease. Arch. Neurol. 50: 949–954.10.1001/archneur.1993.00540090052010Search in Google Scholar PubMed

Kim, J.S., Lee, S.H., Park, G., Kim, S., Bae, S.M., Kim, D.W., and Im, C.H. (2012). Clinical implications of quantitative electroencephalography and current source density in patients with Alzheimer’s disease. Brain Topogr. 25: 461–474.10.1007/s10548-012-0234-1Search in Google Scholar PubMed

Klimesch, W., Doppelmayr, M., Russegger, H., Pachinger, T., and Schwaiger, J. (1998). Induced alpha band power changes in the human EEG and attention. Neurosci. Lett. 244: 73–76.10.1016/S0304-3940(98)00122-0Search in Google Scholar

Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Res. Rev. 29: 169–195.10.1016/S0165-0173(98)00056-3Search in Google Scholar PubMed

Knott, V., Mohr, E., Mahoney, C., and Ilivitsky, V. (2000). Electroencephalographic coherence in Alzheimer’s disease: comparisons with a control group and population norms. J. Geriatr. Psychiatr. Neurol. 13: 1–8.10.1177/089198870001300101Search in Google Scholar PubMed

Knott, V., Mohr, E., Mahoney, C., and Ilivitsky, V. (2001). Quantitative electroencephalography in Alzheimer’s disease: comparison with a control group, population norms and mental status. J. Psychiatry Neurosci. 26: 106.Search in Google Scholar

Koenig, T., Prichep, L., Dierks, T., Hubl, D., Wahlund, L.O., John, E.R., and Jelic, V. (2005). Decreased EEG synchronization in Alzheimer’s disease and mild cognitive impairment. Neurobiol. Aging 26: 165–171.10.1016/j.neurobiolaging.2004.03.008Search in Google Scholar PubMed

Koga, H., Takashima, Y., Murakawa, R., Uchino, A., Yuzuriha, T., and Yao, H. (2009). Cognitive consequences of multiple lacunes and leukoaraiosis as vascular cognitive impairment in community-dwelling elderly individuals. J. Stroke Cerebrovasc. Dis. 18: 32–37.10.1016/j.jstrokecerebrovasdis.2008.07.010Search in Google Scholar PubMed

Kurita, A., Murakami, M., Takagi, S., Matsushima, M., and Suzuki, M. (2010). Visual hallucinations and altered visual information processing in Parkinson disease and dementia with lewy bodies. Mov. Disord. 25: 167–171.10.1002/mds.22919Search in Google Scholar PubMed

Kutas, M., Mccarthy, G., and Donchin, E. (1977). Augmenting mental chronometry: the p300 as a measure of stimulus evaluation time. Science 197: 792–795.10.1126/science.887923Search in Google Scholar PubMed

Lai, C.L., Lin, R.T., Liou, L.M., and Liu, C.K. (2010). The role of event-related potentials in cognitive decline in Alzheimer’s disease. Clin. Neurophysiol. 121: 194–199.10.1016/j.clinph.2009.11.001Search in Google Scholar PubMed

Lakatos, P., Karmos, G., Mehta, A.D., Ulbert, I., and Schroeder, C.E. (2008). Entrainment of neuronal oscillations as a mechanism of attentional selection. Science 320: 110–113.10.1126/science.1154735Search in Google Scholar PubMed

Lanctôt, K.L., Herrmaan, N., Mazzotta, P., Khan, L.R., and Ingber, N. (2004). GABAergic function in Alzheimer’s disease: evidence for dysfunction and potential as a therapeutic target for the treatment of behavioral and psychological symptoms of dementia. Can. J. Psychiatr. 49: 439–453.10.1177/070674370404900705Search in Google Scholar PubMed

Laske, C., Sohrabi, H.R., Frost, S.M., López-De-Ipiña, K., Garrard, P., Buscema, M., Dauwels, J., Soekadar, S.R., Mueller, S., Linnemann, C., et al.. (2015). Innovative diagnostic tools for early detection of Alzheimer’s disease. Alzheimer’s Dement. 11: 561–578.10.1016/j.jalz.2014.06.004Search in Google Scholar PubMed

Lee, M.S., Lee, S.H., Moon, E.O., Moon, Y.J., Kim, S., Kim, S.H., and Jung, I.K. (2013). Neuropsychological correlates of the P300 in patients with Alzheimer’s disease. Prog. Neuro-Psychopharmacol. Biol. Psychiatry 40: 62–69.10.1016/j.pnpbp.2012.08.009Search in Google Scholar PubMed

Lindau, M., Jelic, V., Johansson, S.E., Andersen, C., Wahlund, L.O., and Almkvist, O. (2003). Quantitative EEG abnormalities and cognitive dysfunctions in frontotemporal dementia and Alzheimer’s disease. Dement. Geriatr. Cognit. Disord. 15: 106–114.10.1159/000067973Search in Google Scholar PubMed

Lizio, R., Del Percio, C., Marzano, N., Soricelli, A., Yener, G.G., Basąr, E., Mundi, C., De Rosa, S., Triggiani, A.I., Ferri, R., et al.. (2015). Neurophysiological assessment of Alzheimer’s disease individuals by a single electroencephalographic marker. J. Alzheim. Dis. 49: 159–177.10.3233/JAD-143042Search in Google Scholar PubMed

Locatelli, T., Cursi, M., Liberati, D., Franceschi, M., and Comi, G. (1998). EEG coherence in Alzheimer’s disease. Electroencephalogr. Clin. Neurophysiol. 106: 229–237.10.1016/S0013-4694(97)00129-6Search in Google Scholar

Luck, S.J. (2012). Event related potentials. In Cooper, H., Camic, P. M., Long, D. L., Panter, A. T., Rindskopf, D., and Sher, K. J. (Eds.), APA handbook of research methods in psychology: Foundations, planning, measures, and psychometrics, Vol. 1. Washinton, DC, American Psychological Association, pp. 523–546.10.1037/13619-028Search in Google Scholar

Luu, P., Tucker, D.M., and Makeig, S. (2004). Frontal midline theta and the error-related negativity: neurophysiological mechanisms of action regulation. Clin. Neurophysiol. 115: 1821–1835.10.1016/j.clinph.2004.03.031Search in Google Scholar PubMed

Mohandas, E. and Rajmohan, V. (2009). Frontotemporal dementia: an updated overview. Indian J. Psychiatr. 51(Suppl. 1): S65.10.4103/0019-5545.44908Search in Google Scholar

Moretti, D.V., Paternicò, D., Binetti, G., Zanetti, O., and Frisoni, G.B. (2012). EEG markers are associated to gray matter changes in thalamus and basal ganglia in subjects with mild cognitive impairment. NeuroImage 60: 489–496.10.1016/j.neuroimage.2011.11.086Search in Google Scholar PubMed

Muller, H.F. and Schwartz, G. (1978). Electroencephalograms and autopsy findings in geropsychiatry. J. Gerontol. 33: 504–513.10.1093/geronj/33.4.504Search in Google Scholar PubMed

Murley, A.G., Rouse, M.A., Simon Jones, P., Ye, R., Hezemans, F.H., O’Callaghan, C., Frangou, P., Kourtzi, Z., Rua, C., Adrian Carpenter, T., et al.. (2021). GABA and glutamate deficits from frontotemporal lobar degeneration are associated with disinhibition. Brain 143: 3449–3462.10.1093/brain/awaa305Search in Google Scholar PubMed PubMed Central

Murley, A.G. and Rowe, J.B. (2018). Neurotransmitter deficits from fronto temporal lobar degeneration. Brain 141: 1263–1285.10.1093/brain/awx327Search in Google Scholar PubMed PubMed Central

Musaeus, C.S., Engedal, K., Høgh, P., Jelic, V., Mørup, M., Naik, M., Oeksengaard, A.R., Snaedal, J., Wahlund, L.O., Waldemar, G., et al.. (2019). Oscillatory connectivity as a diagnostic marker of dementia due to Alzheimer’s disease. Clin. Neurophysiol. 130: 1889–1899.10.1016/j.clinph.2019.07.016Search in Google Scholar PubMed

Muscoso, E.G., Costanzo, E., Daniele, O., Maugeri, D., Natale, E., and Caravaglios, G. (2006). Auditory event-related potentials in subcortical vascular cognitive impairment and in Alzheimer’s disease. J. Neural. Transm. 113: 1779–1786.10.1007/s00702-006-0574-7Search in Google Scholar PubMed

Neary, D., Snowden, J.S., Gustafson, L., Passant, U., Stuss, D., Black, S., Freedman, M., Kertesz, A., Robert, P.H., Albert, M., et al.. (1998). Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria. Neurology 51: 1546–1554.10.1212/WNL.51.6.1546Search in Google Scholar

Neary, D., Snowden, J., and Mann, D. (2005). Frontotemporal dementia. Lancet Neurol. 4: 771–780.10.1201/b13239-91Search in Google Scholar

Nimmrich, V., Draguhn, A., and Axmacher, N. (2015). Neuronal network oscillations in neurodegenerative diseases. NeuroMolecular Med. 17: 270–284.10.1007/s12017-015-8355-9Search in Google Scholar PubMed

Nishida, K., Yoshimura, M., Isotani, T., Yoshida, T., Kitaura, Y., Saito, A., Mii, H., Kato, M., Takekita, Y., Suwa, A., et al.. (2011). Differences in quantitative EEG between frontotemporal dementia and Alzheimer’s disease as revealed by LORETA. Clin. Neurophysiol. 122: 1718–1725.10.1016/j.clinph.2011.02.011Search in Google Scholar PubMed

O’Brien, J.T. and Thomas, A. (2015). Vascular dementia. Lancet 386: 1698–1706.10.1016/S0140-6736(15)00463-8Search in Google Scholar PubMed

Palva, S. and Palva, J.M. (2011). Functional roles of alpha-band phase synchronization in local and large-scale cortical networks. Front. Psychol. 2: 204.10.3389/fpsyg.2011.00204Search in Google Scholar PubMed PubMed Central

Pfurtscheller, G. and Lopes Da Silva, F.H. (1999). Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin. Neurophysiol. 110: 1842–1857.10.1016/S1388-2457(99)00141-8Search in Google Scholar

Platt, B. and Riedel, G. (2011). The cholinergic system, EEG and sleep. Behav. Brain Res. 221: 499–504.10.1016/j.bbr.2011.01.017Search in Google Scholar PubMed

Polich, J. and Corey-Bloom, J. (2005). Alzheimers disease and P300: review and evaluation of task and modality. Curr. Alzheimer Res. 2: 515–525.10.2174/156720505774932214Search in Google Scholar PubMed

Polich, J. (2007). Updating P300: an integrative theory of P3a and P3b. Clin. Neurophysiol. 118: 2128–2148.10.1016/j.clinph.2007.04.019Search in Google Scholar PubMed PubMed Central

Ponomareva, N.V., Selesneva, N.D., and Jarikov, G.A. (2003). EEG alterations in subjects at high familial risk for Alzheimer’s disease. Neuropsychobiology 48: 152–159.10.1159/000073633Search in Google Scholar PubMed

Poza, J., Hornero, R., Abásolo, D., Fernández, A., and Escudero, J. (2007). Analysis of spontaneous MEG activity in patients with Alzheimer’s disease using spectral entropies. Conf. Proc. IEEE Eng. Med. Biol. Soc.: 6179–6182.10.1109/IEMBS.2007.4353766Search in Google Scholar PubMed

Reisberg, B., Ferris, S.H., Schneck, M.K., Corwin, J., Mir, P., Friedman, E., Sherman, K.A., McCarthy, M., and Bartus, R.T. (1982). Piracetam in the treatment of cognitive impairment in the elderly. Drug Dev. Res. 2: 475–480.10.1002/ddr.430020508Search in Google Scholar

Ribary, U., Ioannides, A.A., Singh, K.D., Hasson, R., Bolton, J.P.R., Lado, F., Mogilner, A., and Llinás, R. (1991). Magnetic field tomography of coherent thalamocortical 40-Hz oscillations in humans. Proc. Natl. Acad. Sci. U. S. A 88: 11037–11041.10.1073/pnas.88.24.11037Search in Google Scholar PubMed PubMed Central

Ricceri, L., Minghetti, L., Moles, A., Popoli, P., Confaloni, A., De Simone, R., Piscopo, P., Scattoni, M.L., Di Luca, M., and Calamandrei, G. (2004). Cognitive and neurological deficits induced by early and prolonged basal forebrain cholinergic hypofunction in rats. Exp. Neurol. 189: 162–172.10.1016/j.expneurol.2004.05.025Search in Google Scholar PubMed

Robillard, A. (2007). Clinical diagnosis of dementia. Alzheimer’s Dement. 3: 292–298.10.1016/j.jalz.2007.08.002Search in Google Scholar PubMed

Sanei, S. and Chambers, J.A. (2013). EEG Signal Processing. Wiley & sons, Chichester.Search in Google Scholar

Sankari, Z., Adeli, H., and Adeli, A. (2011). Intrahemispheric, interhemispheric, and distal EEG coherence in Alzheimer’s disease. Clin. Neurophysiol. 122: 897–906.10.1016/j.clinph.2010.09.008Search in Google Scholar PubMed

Scheeringa, R., Petersson, K.M., Oostenveld, R., Norris, D.G., Hagoort, P., and Bastiaansen, M.C.M. (2009). Trial-by-trial coupling between EEG and BOLD identifies networks related to alpha and theta EEG power increases during working memory maintenance. NeuroImage 44: 1224–1238.10.1016/j.neuroimage.2008.08.041Search in Google Scholar PubMed

Sebastian, M.V., Menor, J., and Elosua, M.R. (2006). Attentional dysfunction of the central executive in AD: Evidence from dual task and perseveration errors. Cortex 42: 1015–1020.10.1016/S0010-9452(08)70207-7Search in Google Scholar

Siegel, M., Donner, T.H., and Engel, A.K. (2012). Spectral fingerprints of large-scale neuronal interactions. Nat. Rev. Neurosci. 13: 121–134.10.1038/nrn3137Search in Google Scholar PubMed

Smith, M.E., Halgren, E., Sokolik, M., Baudena, P., Musolino, A., Liegeois-Chauvel, C., and Chauvel, P. (1990). The intracranial topography of the P3 event-related potential elicited during auditory oddball. Electroencephalogr. Clin. Neurophysiol. 76: 235–248.10.1016/0013-4694(90)90018-FSearch in Google Scholar

Sokhadze, E.M., Casanova, M.F., Casanova, E., Lamina, E., Kelly, D.P., and Khachidze, I. (2017). Event-related potentials (ERP) in cognitive neuroscience research and applications. NeuroRegulation 4: 14.10.15540/nr.4.1.14Search in Google Scholar

Stam, C.J., Jones, B.F., Manshanden, I., van Cappellen van Walsum, A.M., Montez, T., Verbunt, J.P.A., de Munck, J.C., van Dijk, B.W., Berendse, H.W., and Scheltens, P. (2006). Magnetoencephalographic evaluation of resting-state functional connectivity in Alzheimer’s disease. NeuroImage 32: 1335–1344.10.1016/j.neuroimage.2006.05.033Search in Google Scholar PubMed

Stam, C.J., Van Cappellen van Walsum, A.M., Pijnenburg, Y.A.L., Berendse, H.W., De Munck, J.C., Scheltens, P., and Van Dijk, B.W. (2002). Generalized synchronization of MEG recordings in Alzheimer’s disease: evidence for involvement of the gamma band. J. Clin. Neurophysiol. 19: 562–574.10.1097/00004691-200212000-00010Search in Google Scholar PubMed

Sumi, N., Nan’no, H., Fujimoto, O., Ohta, Y., and Takeda, M. (2000). Interpeak latency of auditory event-related potentials (P300) in senile depression and dementia of the Alzheimer type. Psychiatr. Clin. Neurosci. 54: 679–684.10.1046/j.1440-1819.2000.00769.xSearch in Google Scholar PubMed

Sur, S. and Sinha, V. (2009). Event-related potential: an overview. Ind. Psychiatr. J. 18: 70.10.4103/0972-6748.57865Search in Google Scholar PubMed PubMed Central

Turriziani, P., Smirni, D., Zappalà, G., Mangano, G.R., Oliveri, M., and Cipolotti, L. (2012). Enhancing memory performance with rTMS in healthy subjects and individuals with Mild Cognitive Impairment: the role of the right dorsolateral prefrontal cortex. Front. Hum. Neurosci. 6: 62.10.3389/fnhum.2012.00062Search in Google Scholar PubMed PubMed Central

van der Hiele, K., Vein, A.A., Reijntjes, R.H.A.M., Westendorp, R.G.J., Bollen, E.L.E.M., van Buchem, M.A., van Dijk, J.G., and Middelkoop, H.A.M. (2007). EEG correlates in the spectrum of cognitive decline. Clin. Neurophysiol. 118: 1931–1939.10.1016/j.clinph.2007.05.070Search in Google Scholar PubMed

Van Diepen, R.M., Foxe, J.J., and Mazaheri, A. (2019). The functional role of alpha-band activity in attentional processing: the current zeitgeist and future outlook. Curr. Opin. Psychol 29: 229–238.10.1016/j.copsyc.2019.03.015Search in Google Scholar PubMed

Van Ede, F., De Lange, F., Jensen, O., and Maris, E. (2011). Orienting attention to an upcoming tactile event involves a spatially and temporally specific modulation of sensorimotor alpha- and beta-band oscillations. J. Neurosci. 31: 2016–2024.10.1523/JNEUROSCI.5630-10.2011Search in Google Scholar PubMed PubMed Central

van Straaten, E.C.W., de Haan, W., de Waal, H., Scheltens, P., van der Flier, W.M., Barkhof, F., Koene, T., and Stam, C.J. (2012). Disturbed oscillatory brain dynamics in subcortical ischemic vascular dementia. BMC Neurosci. 13: 1–7.10.1186/1471-2202-13-85Search in Google Scholar PubMed PubMed Central

Vecchio, F., Miraglia, F., Marra, C., Quaranta, D., Vita, M.G., Bramanti, P., and Rossini, P.M. (2014). Human brain networks in cognitive decline: a graph theoretical analysis of cortical connectivity from EEG data. J. Alzheim. Dis. 41: 113–127.10.3233/JAD-132087Search in Google Scholar PubMed

Villa, A.E.P., Tetko, I.V., Dutoit, P., and Vantini, G. (2000). Non-linear cortico-cortical interactions modulated by cholinergic afferences from the rat basal forebrain. Biosystems 58: 219–228.10.1016/S0303-2647(00)00126-XSearch in Google Scholar

Whitham, E.M., Pope, K.J., Fitzgibbon, S.P., Lewis, T., Clark, C.R., Loveless, S., Broberg, M., Wallace, A., DeLosAngeles, D., Lillie, P., et al.. (2007). Scalp electrical recording during paralysis: quantitative evidence that EEG frequencies above 20 Hz are contaminated by EMG. Clin. Neurophysiol. 118: 1877–1888.10.1016/j.clinph.2007.04.027Search in Google Scholar PubMed

Wu, L., Chen, Y., and Zhou, J. (2014). A promising method to distinguish vascular dementia from Alzheimer’s disease with standardized low-resolution brain electromagnetic tomography and quantitative EEG. Clin. EEG Neurosci. 45: 152–157.10.1177/1550059413496779Search in Google Scholar PubMed

Yamaguchi, S., Tsuchiya, H., Yamagata, S., Toyoda, G., and Kobayashi, S. (2000). Event-related brain potentials in response to novel sounds in dementia. Clin. Neurophysiol. 111: 195–203.10.1016/S1388-2457(99)00228-XSearch in Google Scholar PubMed

Yener, G.G., Güntekin, B., Öniz, A., and Başar, E. (2007). Increased frontal phase-locking of event-related theta oscillations in Alzheimer patients treated with cholinesterase inhibitors. Int. J. Psychophysiol. 64: 46–52.10.1016/j.ijpsycho.2006.07.006Search in Google Scholar PubMed

Yu, M., Gouw, A.A., Hillebrand, A., Tijms, B.M., Stam, C.J., van Straaten, E.C.W., and Pijnenburg, Y.A.L. (2016). Different functional connectivity and network topology in behavioral variant of frontotemporal dementia and Alzheimer’s disease: an EEG study. Neurobiol. Aging 42: 150–162.10.1016/j.neurobiolaging.2016.03.018Search in Google Scholar PubMed

Yuvaraj, R., Murugappan, M., Mohamed Ibrahim, N., Iqbal Omar, M., Sundaraj, K., Mohamad, K., Palaniappan, R., Mesquita, E., and Satiyan, M. (2014). On the analysis of EEG power, frequency and asymmetry in Parkinson’s disease during emotion processing. Behav. Brain Funct. 10: 1–19.10.1186/1744-9081-10-12Search in Google Scholar PubMed PubMed Central

Zheng-Yan (2005). Abnormal cortical functional connections in Alzheimer’s disease: analysis of inter- and intra-hemispheric EEG coherence. J. Zhejiang Univ. Sci. B 6: 259–264.10.1631/jzus.2005.B0259Search in Google Scholar

Received: 2022-02-01
Accepted: 2022-05-16
Published Online: 2022-06-21
Published in Print: 2023-01-27

© 2022 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 6.11.2025 from https://www.degruyterbrill.com/document/doi/10.1515/revneuro-2022-0010/html
Scroll to top button