Assessing Mild Cognitive Impairment Using Portable Electroencephalography: The P300 Component
Abstract
Increased prevalence of mild cognitive impairments (MCIs) and dementias are a growing concern as the population ages, which produces a need for an objective, accessible, and cost-effective tool to facilitate early detection and intervention. This article investigates whether a portable electroencephalography (EEG) system can provide an effective measure of MCI using a visual oddball task to target the memory and attention event-related potential (ERP) component called the P300. In this study, 40 participants were separated into two groups: individuals with a diagnosed cognitive impairment and a healthy age-matched control group. Participants completed two typical pen-and-paper MCI assessments to gather behavioural data, which were followed by a perceptual EEG oddball task to gather brain data. Results show that the MCI group demonstrated decreased behavioural task performance in the pen-and-paper assessments and a modulated brain response during the oddball task when compared to healthy controls, which the portable EEG system revealed to be a decreased P300 peak amplitude. These results indicate the capability of portable EEGs to identify biomarkers for MCI and their potential use in the diagnostic process. This capability could provide major benefits to patients, their families, and physicians, and would also assist with Alzheimer’s research. Future research could expand on these findings by applying a lifespan or disease-span approach to investigate P300 changes in the course of a healthy individual’s life compared to P300 changes in individuals with MCI over the entire course of their disease. This research could also cultivate a greater understanding of how MCI progresses, which could improve diagnostic or treatment development.
Downloads
References
Babiloni, C., del Percio, C., Lizio, R., Marzano, N., Infarinato, F., Soricelli, A., Salvatore, E., Ferri, R., Bonforte, C., Tedeschi, G., Montella, P., Baglieri, A., Rodriguez, G., Famà, F., Nobili, F., Vernieri, F., Ursini, F., Mundi, C., Frisoni, G. B., & Rossini, P. M. (2014). Cortical sources of resting state electroencephalographic alpha rhythms deteriorate across time in subjects with amnesic mild cognitive impairment. Neurobiology of Aging, 35(1), 130–142. https://doi.org/10.1016/J.NEUROBIOLAGING.2013.06.019
Biasiucci, A., Franceschiello, B., & Murray, M. M. (2019). Electroencephalography. Current Biology, 29(3), R80–R85. https://doi.org/10.1016/J.CUB.2018.11.052
Burdorf, B. T. (2021). Comparing MRI and CT machine accessibility among urban and rural county hospitals. Journal of Public Health Research, 11(1), 2527. https://doi.org/10.4081/JPHR.2021.2527
Cecchi, M., Moore, D. K., Sadowsky, C. H., Solomon, P. R., Doraiswamy, P. M., Smith, C. D., Jicha, G. A., Budson, A. E., Arnold, S. E., & Fadem, K. C. (2015). A clinical trial to validate event-related potential markers of Alzheimer’s disease in outpatient settings. Alzheimer’s and Dementia: Diagnosis, Assessment and Disease Monitoring, 1(4), 387–394. https://doi.org/10.1016/J.DADM.2015.08.004
Chambers, L. W., Bancej, C., & Mcdowell, I. (2016). Prevalence and monetary costs of dementia in Canada. www.alzheimer.ca
Chapman, R. M., McCrary, J. W., Gardner, M. N., Sandoval, T. C., Guillily, M. D., Reilly, L. A., & DeGrush, E. (2011). Brain ERP components predict which individuals progress to Alzheimer’s disease and which do not. Neurobiology of Aging, 32(10), 1742–1755. https://doi.org/10.1016/J.NEUROBIOLAGING.2009.11.010
Correa-Jaraba, K. S., Lindín, M., & Díaz, F. (2018). Increased amplitude of the P3a ERP component as a neurocognitive marker for differentiating amnestic subtypes of mild cognitive impairment. Frontiers in Aging Neuroscience, 10(19), 1–13. https://doi.org/10.3389/FNAGI.2018.00019
Coles, M. G. H., & Rugg, M. D. (1996). Event-related brain potentials: An introduction. In M. D. Rugg & M. G. H. Coles (Eds.), Electrophysiology of mind: Event-related brain potentials and cognition (pp. 1–26). Oxford University Press.
Costa, A. S., Reich, A., Fimm, B., Ketteler, S. T., Schulz, J. B., & Reetz, K. (2014). Evidence of the sensitivity of the MoCA alternate forms in monitoring cognitive change in early Alzheimer's disease. Dementia and geriatric cognitive disorders, 37(1-2), 95–103. https://doi.org/10.1159/000351864
Deiber, M. P., Ibañez, V., Missonnier, P., Herrmann, F., Fazio-Costa, L., Gold, G., & Giannakopoulos, P. (2009). Abnormal-induced theta activity supports early directed-attention network deficits in progressive MCI. Neurobiology of Aging, 30(9), 1444–1452. https://doi.org/10.1016/J.NEUROBIOLAGING.2007.11.021
Delorme, A., & Makeig, S. (2004). EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 134(1), 9–21. https://doi.org/10.1016/J.JNEUMETH.2003.10.009
Donchin, E., & Coles, M. G. H. (1988). Is the P300 component a manifestation of context updating? Behavioral and Brain Sciences, 11(3), 357–374. https://doi.org/10.1017/S0140525X00058027
Duits, F. H., Martinez-Lage, P., Paquet, C., Engelborghs, S., Lleó, A., Hausner, L., Molinuevo, J. L., Stomrud, E., Farotti, L., Ramakers, I. H. G. B., Tsolaki, M., Skarsgård, C., Åstrand, R., Wallin, A., Vyhnalek, M., Holmber-Clausen, M., Forlenza, O. v., Ghezzi, L., Ingelsson, M., … Blennow, K. (2016). Performance and complications of lumbar puncture in memory clinics: Results of the multicenter lumbar puncture feasibility study. Alzheimer’s & Dementia, 12(2), 154–163. https://doi.org/10.1016/J.JALZ.2015.08.003
Gale, S. A., Acar, D., & Daffner, K. R. (2018). Dementia. The American Journal of Medicine, 131(10), 1161–1169. https://doi.org/10.1016/J.AMJMED.2018.01.022
Galvin, J. E. (2018). Using informant and performance screening methods to detect mild cognitive impairment and dementia. Neurology of Aging, 7, 19-25. https://doi.org/10.1007/s13670-018-0236-2
Gauthier, S., Reisberg, B., Zaudig, M., Petersen, R. C., Ritchie, K., Broich, K., Belleville, S., Brodaty, H., Bennett, D., Chertkow, H., Cummings, J. L., de Leon, M., Feldman, H., Ganguli, M., Hampel, H., Scheltens, P., Tierney, M. C., Whitehouse, P., & Winblad, B. (2006). Mild cognitive impairment. The Lancet, 367(9518), 1262–1270. https://doi.org/10.1016/S0140-6736(06)68542-5
Gillis, C., Mirzaei, F., Potashman, M., Ikram, M. A., & Maserejian, N. (2019). The incidence of mild cognitive impairment: A systematic review and data synthesis. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, 11(1), 248. https://doi.org/10.1016/J.DADM.2019.01.004
Gottlibe, M., Rosen, O., Weller, B., Mahagney, A., Omar, N., Khuri, A., Srugo, I., & Genizi, J. (2020). Stroke identification using a portable EEG device—A pilot study. Neurophysiologie Clinique, 50(1), 21–25. https://doi.org/10.1016/J.NEUCLI.2019.12.004
Gu, L., Chen, J., Gao, L., Shu, H., Wang, Z., Liu, D., Yan, Y., Li, S., & Zhang, Z. (2019). Deficits of visuospatial working memory and executive function in single- versus multiple-domain amnestic mild cognitive impairment: A combined ERP and sLORETA study. Clinical Neurophysiology, 130(5), 739–751. https://doi.org/10.1016/J.CLINPH.2019.01.025
Hünerli, D., Emek-Savaş, D. D., Çavuşoğlu, B., Dönmez Çolakoğlu, B., Ada, E., & Yener, G. G. (2019). Mild cognitive impairment in Parkinson’s disease is associated with decreased P300 amplitude and reduced putamen volume. Clinical Neurophysiology, 130(8), 1208–1217. https://doi.org/10.1016/J.CLINPH.2019.04.314
Jiang, S., Qu, C., Wang, F., Liu, Y., Qiao, Z., Qiu, X., Yang, X., & Yang, Y. (2015). Using event-related potential P300 as an electrophysiological marker for differential diagnosis and to predict the progression of mild cognitive impairment: a meta-analysis. Neurological Sciences, 36(7), 1105–1112. https://doi.org/10.1007/S10072-015-2099-Z
Jiménez, E. C., Sierra-Marcos, A., Romeo, A., Hashemi, A., Leonovych, O., Valenzuela, P. B., Puig, M. S., Supèr, H. (2021). Altered vergence eye movements and pupil response of patients with Alzheimer’s disease and mild cognitive impairment during an oddball task. Journal of Alzheimer’s Disease, 82(1), 421-433. https://doi.org/10.3233/JAD-201301
Kavcic, V., Daugherty, A. M., & Giordani, B. (2021). Post-task modulation of resting state EEG differentiates MCI patients from controls. Alzheimer’s and Dementia: Diagnosis, Assessment and Disease Monitoring, 13(1), 1-6. https://doi.org/10.1002/DAD2.12153
Klekociuk, S. Z., & Summers, M. J. (2014). Lowered performance in working memory and attentional sub-processes are most prominent in multi-domain amnestic mild cognitive impairment subtypes. Psychogeriatrics, 14(1), 63–71. https://doi.org/10.1111/PSYG.12042
Krigolson, O. E., Hammerstrom, M. R., Abimbola, W., Trska, R., Wright, B. W., Hecker, K. G., & Binsted, G. (2021). Using Muse: Rapid mobile assessment of brain performance. Frontiers in Neuroscience, 15(634147), 1-11. https://doi.org/10.3389/FNINS.2021.634147
Krigolson, O. E., & Holroyd, C. B. (2007). Hierarchical error processing: different errors, different systems. Brain research, 1155, 70-80. https://doi.org/10.1016/j.brainres.2007.04.024
Krigolson, O. E., Williams, C. C., Norton, A., Hassall, C. D., & Colino, F. L. (2017). Choosing MUSE: Validation of a low-cost, portable EEG system for ERP research. Frontiers in Neuroscience, 11(109), 1-10. https://doi.org/10.3389/fnins.2017.00109
Langa, K. M., & Levine, D. A. (2014). The diagnosis and management of mild cognitive impairment: A clinical review. Journal of the American Medical Association, 312(23), 2551-2561. https://doi.org/10.1001/jama.2014.13806
Luck, S. J. (2014). An introduction to the event-related potential technique. MIT Press.
Moretti, D. v., Frisoni, G. B., Fracassi, C., Pievani, M., Geroldi, C., Binetti, G., Rossini, P. M., & Zanetti, O. (2011). MCI patients’ EEGs show group differences between those who progress and those who do not progress to AD. Neurobiology of Aging, 32(4), 563–571. https://doi.org/10.1016/J.NEUROBIOLAGING.2009.04.003
Musall, S., von Pföstl, V., Rauch, A., Logothetis, N. K., & Whittingstall, K. (2014). Effects of neural synchrony on surface EEG. Cerebral Cortex, 24(4), 1045–1053. https://doi.org/10.1093/CERCOR/BHS389
Nasreddine, Z. S., Phillips, N. A., Bédirian, V., Charbonneau, S., Whitehead, V., Collin, I., Cummings, J. L., & Chertkow, H. (2005). The Montreal Cognitive Assessment, MoCA: A brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society, 53(4), 695–699. https://doi.org/10.1111/J.1532-5415.2005.53221.X
Nieuwenhuis, S., Aston-Jones, G., & Cohen, J. D. (2005). Decision making, the P3, and the locus coeruleus-norepinephrine system. Psychological Bulletin, 131(4), 510–532. https://doi.org/10.1037/0033-2909.131.4.510
Oken, B. S., & Chiappa, K. H. (1986). Statistical issues concerning computerized analysis of brainwave topography. Annals of Neurology, 19(5), 493-494. https://doi.org/10.1002/ana.410190511
Olejniczak, P. (2006). Neurophysiologic basis of EEG. Journal of Clinical Neurophysiology, 23(3), 186–189. https://doi.org/10.1097/01.wnp.0000220079.61973.6c
On, F. R., Jailani, R., Norhazman, H., & Zaini, N. M. (2013). Binaural beat effect on brainwaves based on EEG. IEEE 9th International Colloquium on Signal Processing and Its Applications, 339–343. https://doi.org/10.1109/CSPA.2013.6530068
Owens, D. K., Davidson, K. W., Krist, A. H., Barry, M. J., Cabana, M., Caughey, A. B., Doubeni, C. A., Epling, J. W., Kubik, M., Landefeld, C. S., Mangione, C. M., Pbert, L., Silverstein, M., Simon, M. A., Tseng, C.-W., & Wong, J. B. (2020). Screening for cognitive impairment in older adults: US preventive services task force recommendation statement. Journal of the American Medical Association, 323(8), 757–763. https://doi.org/10.1001/JAMA.2020.0435
Parra, M. A., Ascencio, L. L., Urquina, H. F., Manes, F., & Ibáñez, A. M. (2012). P300 and neuropsychological assessment in mild cognitive impairment and Alzheimer dementia. Frontiers in Neurology, 3(172), 1-10. https://doi.org/10.3389/fneur.2012.00172
Patnode, C. D., Perdue, L. A., Rossom, R. C., Rushkin, M. C., Redmond, N., Thomas, R. G., & Lin, J. S. (2020). Evidence Synthesis Number 189 Screening for Cognitive Impairment in Older Adults: An Evidence Update for the U.S. Preventive Services Task Force. https://www.ncbi.nlm.nih.gov/books/NBK554654/
Perry, D. C., Datta, S., Sturm, V. E., Wood, K. A., Zakrzewski, J., Seeley, W. W., Miller, B. L., Kramer, J. H., Rosen, H. J. (2017). Reward deficits in behavioural variant frontotemporal dementia include insensitivity to negative stimuli, Brain, 140(12), 3346–3356. https://doi.org/10.1093/brain/awx259
Pfeffer, R. I., Kurosaki, T. T., Harrah, C. H., Chance, J. M., & Filos, S. (1982). Measurement of functional activities in older adults in the community. Journal of Gerontology, 37(3), 323–329. https://doi.org/10.1093/GERONJ/37.3.323
Polich, J. (2012). Neuropsychology of P300. The Oxford handbook of Event-Related Potential components. https://doi.org/10.1093/OXFORDHB/9780195374148.013.0089
Polich, J. (2007). Updating P300: An integrative theory of P3a and P3b. Clinical Neurophysiology, 118(10), 2128–2148. https://doi.org/10.1016/J.CLINPH.2007.04.019
Pu, L., Lion, K. M., Todorovic, M., & Moyle, W. (2021). Portable EEG monitoring for older adults with dementia and chronic pain—A feasibility study. Geriatric Nursing, 42(1), 124–128. https://doi.org/10.1016/J.GERINURSE.2020.12.008
Qian, X., Dai, W., Xu, R., & Ling, H. (2020). One intelligent framework for screening and intervention of Mild Cognitive Impairment (MCI). The Journal of Engineering, 2020(13), 422–425. https://doi.org/10.1049/JOE.2019.1209
Randolph, C., (2012). The Repeatable Battery for the Assessment of Neuropsychological Status update. Pearson. https://www.pearsonassessments.com/store/usassessments/en/Store/Professional-Assessments/Cognition-%26-Neuro/Repeatable-Battery-for-the-Assessment-of-Neuropsychological-Status-Update/p/100000726.html
Randolph, C., Tierney, M. C., Mohr, E., & Chase, T. N. (2010). The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS): Preliminary clinical validity. Journal of Clinical and Experimental Neuropsychology, 20(3), 310–319. https://doi.org/10.1076/JCEN.20.3.310.823
Sabbagh, M. N., Boada, M., Borson, S., Chilukuri, M., Doraiswamy, P. M., Dubois, B., Ingram, J., Iwata, A., Porsteinsson, A. P., Possin, K. L., Rabinovici, G. D., Vellas, B., Chao, S., Vergallo, A., & Hampel, H. (2020). Rationale for early diagnosis of mild cognitive impairment (MCI) supported by emerging digital technologies. The Journal of Prevention of Alzheimer’s Disease, 7(3), 158–164. https://doi.org/10.14283/JPAD.2020.19
Saunders, N. L. J., & Summers, M. J. (2011). Longitudinal deficits to attention, executive, and working memory in subtypes of mild cognitive impairment. Neuropsychology, 25(2), 237–248. https://doi.org/10.1037/A0021134
Seeck, M., Koessler, L., Bast, T., Leijten, F., Michel, C., Baumgartner, C., He, B., & Beniczky, S. (2017). The standardized EEG electrode array of the IFCN. Clinical Neurophysiology, 128(10), 2070–2077. https://doi.org/10.1016/j.clinph.2017.06.254
Sheik, J. I., & Yesavage, J. A. (1986). Geriatric Depression Scale: Recent evidence and development of a shorter version. Clinical Gerontology: A Guide to Assessment and Intervention, 5(1–2), 165–173. https://doi.org/10.1300/J018v05n01_09
Smailovic, U., & Jelic, V. (2019). Neurophysiological markers of Alzheimer’s disease: Quantitative EEG approach. Neurology and Therapy, 8(2), 37–55. https://doi.org/10.1007/S40120-019-00169-0
Tülay, E. E., Güntekin, B., Yener, G., Bayram, A., Başar-Eroğlu, C., & Demiralp, T. (2020). Evoked and induced EEG oscillations to visual targets reveal a differential pattern of change along the spectrum of cognitive decline in Alzheimer’s Disease. International Journal of Psychophysiology, 155, 41–48. https://doi.org/10.1016/J.IJPSYCHO.2020.06.001
Vemuri, P., Wiste, H. J., Weigand, S. D., Shaw, L. M., Trojanowski, J. Q., Weiner, M. W., Knopman, D. S., Petersen, R. C., & Jack, C. R. (2009). MRI and CSF biomarkers in normal, MCI, and AD subjects: Predicting future clinical change. Neurology, 73(4), 294–301. https://doi.org/10.1212/WNL.0B013E3181AF79FB
Yokomizo, J. E., Simon, S. S., & Bottino, C. M. de C. (2014). Cognitive screening for dementia in primary care: A systematic review. International Psychogeriatrics, 26(11), 1783–1804. https://doi.org/10.1017/S1041610214001082
Copyright (c) 2022 Hannah H. Smith
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors contributing to the Artbutus Review agree to release their articles under the Creative Commons Attribution-Noncommercial 4.0 Unported license. This licence allows anyone to share their work (copy, distribute, transmit) and to adapt it for non-commercial purposes provided that appropriate attribution is given, and that in the event of reuse or distribution, the terms of this license are made clear.
Authors retain copyright of their work and grant the journal right of first publication.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
