Alpha desynchronization during Stroop test unmasks cognitively healthy individuals with abnormal CSF Amyloid/Tau.
Authors:
Journal: Neurobiology of aging
Publication Type: Journal Article
Date: 2022
DOI: NIHMS1773555
ID: 35066324
Abstract
Synaptic dysfunctions precede cognitive decline in Alzheimer's disease by decades, affect executive functions, and can be detected by quantitative electroencephalography (qEEG). We used quantitative electroencephalography combined with Stroop testing to identify changes of inhibitory controls in cognitively healthy individuals with an abnormal versus normal ratio of cerebrospinal fluid (CSF) amyloid/total-tau. We studied two groups of participants (60-94 years) with either normal (CH-NAT or controls, n = 20) or abnormal (CH-PAT, n = 21) CSF amyloid/tau ratio. We compared: alpha event-related desynchronization (ERD), alpha spectral entropy (SE), and their relationships with estimated cognitive reserve. CH-PATs had more negative occipital alpha ERD, and higher frontal and occipital alpha SE during low load congruent trials, indicating hyperactivity. CH-PATs demonstrated fewer frontal SE changes with higher load, incongruent Stroop testing. Correlations of alpha ERD with estimated cognitive reserve were significant in CH-PATs but not in CH-NATs. These results suggested compensatory hyperactivity in CH-PATs compared to CH-NATs. We did not find differences in alpha ERD comparisons with individual CSF amyloid(A), p-tau(T), total-tau(N) biomarkers.
Chemical List
- Amyloid beta-Peptides|||Biomarkers|||Peptide Fragments|||tau Proteins
Reference List
- Arakaki X, Lee R, King KS, Fonteh AN, Harrington MG, 2019. Alpha desynchronization during simple working memory unmasks pathological aging in cognitively healthy individuals. PLoS One 14(1), e0208517.|||Arakaki X, Shoga M, Li L, Zouridakis G, Tran T, Fonteh AN, Dawlaty J, Goldweber R, Pogoda JM, Harrington MG, 2018. Alpha desynchronization/synchronization during working memory testing is compromised in acute mild traumatic brain injury (mTBI). PLoS One 13(2), e0188101.|||Atchley R, Klee D, Oken B, 2017. EEG Frequency Changes Prior to Making Errors in an Easy Stroop Task. Front Hum Neurosci 11, 521.|||Babiloni C, Blinowska K, Bonanni L, Cichocki A, De Haan W, Del Percio C, Dubois B, Escudero J, Fernandez A, Frisoni G, Guntekin B, Hajos M, Hampel H, Ifeachor E, Kilborn K, Kumar S, Johnsen K, Johannsson M, Jeong J, LeBeau F, Lizio R, Lopes da Silva F, Maestu F, McGeown WJ, McKeith I, Moretti DV, Nobili F, Olichney J, Onofrj M, Palop JJ, Rowan M, Stocchi F, Struzik ZM, Tanila H, Teipel S, Taylor JP, Weiergraber M, Yener G, Young-Pearse T, Drinkenburg WH, Randall F, 2020a. What electrophysiology tells us about Alzheimer’s disease: a window into the synchronization and connectivity of brain neurons. Neurobiol Aging 85, 58–73.|||Babiloni C, Del Percio C, Boccardi M, Lizio R, Lopez S, Carducci F, Marzano N, Soricelli A, Ferri R, Triggiani AI, Prestia A, Salinari S, Rasser PE, Basar E, Fama F, Nobili F, Yener G, Emek-Savas DD, Gesualdo L, Mundi C, Thompson PM, Rossini PM, Frisoni GB, 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(2), 556–570.|||Babiloni C, Lopez S, Del Percio C, Noce G, Pascarelli MT, Lizio R, Teipel SJ, Gonzalez-Escamilla G, Bakardjian H, George N, Cavedo E, Lista S, Chiesa PA, Vergallo A, Lemercier P, Spinelli G, Grothe MJ, Potier MC, Stocchi F, Ferri R, Habert MO, Fraga FJ, Dubois B, Hampel H, Group I.N.-p.S., 2020b. Resting-state posterior alpha rhythms are abnormal in subjective memory complaint seniors with preclinical Alzheimer’s neuropathology and high education level: the INSIGHT-preAD study. Neurobiol Aging 90, 43–59.|||Babiloni C, Triggiani AI, Lizio R, Cordone S, Tattoli G, Bevilacqua V, Soricelli A, Ferri R, Nobili F, Gesualdo L, Millan-Calenti JC, Bujan A, Tortelli R, Cardinali V, Barulli MR, Giannini A, Spagnolo P, Armenise S, Buenza G, Scianatico G, Logroscino G, Frisoni GB, Del Percio C, 2016. Classification of Single Normal and Alzheimer’s Disease Individuals from Cortical Sources of Resting State EEG Rhythms. Front Neurosci 10, 47.|||Bajo R, Castellanos NP, Cuesta P, Aurtenetxe S, Garcia-Prieto J, Gil-Gregorio P, del-Pozo F, Maestu F, 2012. Differential patterns of connectivity in progressive mild cognitive impairment. Brain Connect 2(1), 21–24.|||Barulli DJ, Rakitin BC, Lemaire P, Stern Y, 2013. The influence of cognitive reserve on strategy selection in normal aging. J Int Neuropsychol Soc 19(7), 841–844.|||Bateman RJ, Wen G, Morris JC, Holtzman DM, 2007. Fluctuations of CSF amyloid-beta levels: implications for a diagnostic and therapeutic biomarker. Neurology 68(9), 666–669.|||Belanger S, Belleville S, Gauthier S, 2010. Inhibition impairments in Alzheimer’s disease, mild cognitive impairment and healthy aging: effect of congruency proportion in a Stroop task. Neuropsychologia 48(2), 581–590.|||Bortone E, Bettoni L, Buzio S, Delsoldato S, Giorgi C, Mancia D, 1996. Spindle coma and alternating pattern in the course of measles encephalitis. Clin Electroencephalogr 27(4), 210–214.|||Cohen MX, 2014. Analyzing Neural Time Series Data: Theory and Practice.|||Cohen MX, 2017. Rigor and replication in time-frequency analyses of cognitive electrophysiology data. Int J Psychophysiol 111, 80–87.|||Cohen MX, Donner TH, 2013. Midfrontal conflict-related theta-band power reflects neural oscillations that predict behavior. J Neurophysiol 110(12), 2752–2763.|||Crum RM, Anthony JC, Bassett SS, Folstein MF, 1993. Population-based norms for the Mini-Mental State Examination by age and educational level. JAMA 269(18), 2386–2391.|||Cummings J, Lee G, Ritter A, Sabbagh M, Zhong K, 2019. Alzheimer’s disease drug development pipeline: 2019. Alzheimers Dement (N Y) 5, 272–293.|||Dadmehr N, Pakalnis A, Drake ME Jr., 1987. Spindle coma in viral encephalitis. Clin Electroencephalogr 18(1), 34–37.|||Delorme A, Makeig S, 2004. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods 134(1), 9–21.|||Dubois B, Hampel H, Feldman HH, Scheltens P, Aisen P, Andrieu S, Bakardjian H, Benali H, Bertram L, Blennow K, Broich K, Cavedo E, Crutch S, Dartigues JF, Duyckaerts C, Epelbaum S, Frisoni GB, Gauthier S, Genthon R, Gouw AA, Habert MO, Holtzman DM, Kivipelto M, Lista S, Molinuevo JL, O’Bryant SE, Rabinovici GD, Rowe C, Salloway S, Schneider LS, Sperling R, Teichmann M, Carrillo MC, Cummings J, Jack CR Jr., Proceedings of the Meeting of the International Working, G., the American Alzheimer’s Association on “The Preclinical State of, A.D., July, Washington Dc, U.S.A., 2016. Preclinical Alzheimer’s disease: Definition, natural history, and diagnostic criteria. Alzheimers Dement 12(3), 292–323.|||Ekman U, Ferreira D, Westman E, 2018. The A/T/N biomarker scheme and patterns of brain atrophy assessed in mild cognitive impairment. Sci Rep 8(1), 8431.|||Ergen M, Saban S, Kirmizi-Alsan E, Uslu A, Keskin-Ergen Y, Demiralp T, 2014. Time-frequency analysis of the event-related potentials associated with the Stroop test. Int J Psychophysiol 94(3), 463–472.|||Fagan AM, Shaw LM, Xiong C, Vanderstichele H, Mintun MA, Trojanowski JQ, Coart E, Morris JC, Holtzman DM, 2011. Comparison of analytical platforms for cerebrospinal fluid measures of beta-amyloid 1–42, total tau, and p-tau181 for identifying Alzheimer disease amyloid plaque pathology. Arch Neurol 68(9), 1137–1144.|||Fleck JI, Arnold M, Dykstra B, Casario K, Douglas E, Morris O, 2019. Distinct Functional Connectivity Patterns Are Associated With Social and Cognitive Lifestyle Factors: Pathways to Cognitive Reserve. Front Aging Neurosci 11, 310.|||Frankenmolen NL, Fasotti L, Kessels RPC, Oosterman JM, 2018. The influence of cognitive reserve and age on the use of memory strategies. Exp Aging Res 44(2), 117–134.|||Freitas S, Simoes MR, Alves L, Santana I, 2013. Montreal cognitive assessment: validation study for mild cognitive impairment and Alzheimer disease. Alzheimer Dis Assoc Disord 27(1), 37–43.|||Gatz M, 2005. Educating the brain to avoid dementia: can mental exercise prevent Alzheimer disease? PLoS Med 2(1), e7.|||Giogkaraki E, Michaelides MP, Constantinidou F, 2013. The role of cognitive reserve in cognitive aging: results from the neurocognitive study on aging. J Clin Exp Neuropsychol 35(10), 1024–1035.|||Harari O, Cruchaga C, Kauwe JS, Ainscough BJ, Bales K, Pickering EH, Bertelsen S, Fagan AM, Holtzman DM, Morris JC, Goate AM, Alzheimer’s Disease Neuroimaging I, 2014. Phosphorylated tau-Abeta42 ratio as a continuous trait for biomarker discovery for early-stage Alzheimer’s disease in multiplex immunoassay panels of cerebrospinal fluid. Biol Psychiatry 75(9), 723–731.|||Harrington MG, Chiang J, Pogoda JM, Gomez M, Thomas K, Marion SD, Miller KJ, Siddarth P, Yi X, Zhou F, Lee S, Arakaki X, Cowan RP, Tran T, Charleswell C, Ross BD, Fonteh AN, 2013. Executive function changes before memory in preclinical Alzheimer’s pathology: a prospective, cross-sectional, case control study. PLoS One 8(11), e79378.|||Harrington MG, Edminster SP, Buennagel DP, Chiang JP, Sweeney MD, CHui HC, V ZB, Fonteh AN, 2019. Four-Year Longitudinal Study of Cognitively Healthy Individuals: CSF Amyloid/Tau Levels and Nanoparticle Membranes Identify High Risk For Alzheimer’s Disease. Alzheimer’s & Dementia 15(7S).|||Hu L, Peng W, Valentini E, Zhang Z, Hu Y, 2013. Functional features of nociceptive-induced suppression of alpha band electroencephalographic oscillations. J Pain 14(1), 89–99.|||Inouye T, Shinosaki K, Sakamoto H, Toi S, Ukai S, Iyama A, Katsuda Y, Hirano M, 1991. Quantification of EEG irregularity by use of the entropy of the power spectrum. Electroencephalogr Clin Neurophysiol 79(3), 204–210.|||Jack CR Jr., Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, Holtzman DM, Jagust W, Jessen F, Karlawish J, Liu E, Molinuevo JL, Montine T, Phelps C, Rankin KP, Rowe CC, Scheltens P, Siemers E, Snyder HM, Sperling R, Contributors, 2018. NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease. Alzheimers Dement 14(4), 535–562.|||Jack CR Jr., Holtzman DM, 2013. Biomarker modeling of Alzheimer’s disease. Neuron 80(6), 1347–1358.|||Jack CR Jr., Wiste HJ, Weigand SD, Knopman DS, Lowe V, Vemuri P, Mielke MM, Jones DT, Senjem ML, Gunter JL, Gregg BE, Pankratz VS, Petersen RC, 2013. Amyloid-first and neurodegeneration-first profiles characterize incident amyloid PET positivity. Neurology 81(20), 1732–1740.|||Jaiswal S, Tsai SY, Juan CH, Muggleton NG, Liang WK, 2019. Low delta and high alpha power are associated with better conflict control and working memory in high mindfulness, low anxiety individuals. Soc Cogn Affect Neurosci 14(6), 645–655.|||Jensen O, Mazaheri A, 2010. Shaping functional architecture by oscillatory alpha activity: gating by inhibition. Front Hum Neurosci 4, 186.|||Jiang J, Zhang Q, Van Gaal S, 2015. EEG neural oscillatory dynamics reveal semantic and response conflict at difference levels of conflict awareness. Sci Rep 5, 12008.|||Kane MJ, Engle RW, 2003. Working-memory capacity and the control of attention: the contributions of goal neglect, response competition, and task set to Stroop interference. J Exp Psychol Gen 132(1), 47–70.|||Kim TK, 2015. T test as a parametric statistic. Korean J Anesthesiol 68(6), 540–546.|||Klimesch W, 2012. alpha-band oscillations, attention, and controlled access to stored information. Trends Cogn Sci 16(12), 606–617.|||Klimesch W, Sauseng P, Hanslmayr S, 2007. EEG alpha oscillations: the inhibition-timing hypothesis. Brain Res Rev 53(1), 63–88.|||Krause CM, Boman PA, Sillanmaki L, Varho T, Holopainen IE, 2008. Brain oscillatory EEG event-related desynchronization (ERD) and -sychronization (ERS) responses during an auditory memory task are altered in children with epilepsy. Seizure 17(1), 1–10.|||Larson MJ, Kaufman DA, Perlstein WM, 2009. Conflict adaptation and cognitive control adjustments following traumatic brain injury. J Int Neuropsychol Soc 15(6), 927–937.|||Lee J, Jang H, Kang SH, Kim J, Kim JS, Kim JP, Kim HJ, Seo SW, Na DL, 2020. Cerebrospinal Fluid Biomarkers for the Diagnosis and Classification of Alzheimer’s Disease Spectrum. J Korean Med Sci 35(44), e361.|||Li C, Zheng J, Wang J, Gui L, Li C, 2009. An fMRI stroop task study of prefrontal cortical function in normal aging, mild cognitive impairment, and Alzheimer’s disease. Curr Alzheimer Res 6(6), 525–530.|||Lianyang L, Arakaki X, Thao T, Harrington M, Padhye N, Zouridakis G, 2016. Brain activation profiles in mTBI: evidence from ERP activity of working memory response. Conf Proc IEEE Eng Med Biol Soc 2016, 1862–1865.|||Ma Q, Shang Q, 2013. The influence of negative emotion on the Simon effect as reflected by p300. ScientificWorldJournal 2013, 516906.|||Menardi A, Pascual-Leone A, Fried PJ, Santarnecchi E, 2018. The Role of Cognitive Reserve in Alzheimer’s Disease and Aging: A Multi-Modal Imaging Review. J Alzheimers Dis 66(4), 1341–1362.|||Montagne A, Nation DA, Sagare AP, Barisano G, Sweeney MD, Chakhoyan A, Pachicano M, Joe E, Nelson AR, D’Orazio LM, Buennagel DP, Harrington MG, Benzinger TLS, Fagan AM, Ringman JM, Schneider LS, Morris JC, Reiman EM, Caselli RJ, Chui HC, Tcw J, Chen Y, Pa J, Conti PS, Law M, Toga AW, Zlokovic BV, 2020. APOE4 leads to blood-brain barrier dysfunction predicting cognitive decline. Nature 581(7806), 71–76.|||Mortamais M, Portet F, Brickman AM, Provenzano FA, Muraskin J, Akbaraly TN, Berr C, Touchon J, Bonafe A, le Bars E, Menjot de Champfleur N, Maller JJ, Meslin C, Sabatier R, Ritchie K, Artero S, 2014. Education modulates the impact of white matter lesions on the risk of mild cognitive impairment and dementia. Am J Geriatr Psychiatry 22(11), 1336–1345.|||Nakamura A, Cuesta P, Fernandez A, Arahata Y, Iwata K, Kuratsubo I, Bundo M, Hattori H, Sakurai T, Fukuda K, Washimi Y, Endo H, Takeda A, Diers K, Bajo R, Maestu F, Ito K, Kato T, 2018. Electromagnetic signatures of the preclinical and prodromal stages of Alzheimer’s disease. Brain 141(5), 1470–1485.|||Narbutas J, Egroo MV, Chylinski D, Gonzalez PV, Jimenez CG, Besson G, Ghaemmaghami P, Hammad G, Muto V, Schmidt C, Luxen A, Salmon E, Maquet P, Bastin C, Vandewalle G, Collette F, 2019. Cognitive efficiency in late midlife is linked to lifestyle characteristics and allostatic load. Aging (Albany NY) 11(17), 7169–7186.|||Nathan PJ, Lim YY, Abbott R, Galluzzi S, Marizzoni M, Babiloni C, Albani D, Bartres-Faz D, Didic M, Farotti L, Parnetti L, Salvadori N, Muller BW, Forloni G, Girtler N, Hensch T, Jovicich J, Leeuwis A, Marra C, Molinuevo JL, Nobili F, Pariente J, Payoux P, Ranjeva JP, Rolandi E, Rossini PM, Schonknecht P, Soricelli A, Tsolaki M, Visser PJ, Wiltfang J, Richardson JC, Bordet R, Blin O, Frisoni GB, PharmaCog C, 2017. Association between CSF biomarkers, hippocampal volume and cognitive function in patients with amnestic mild cognitive impairment (MCI). Neurobiol Aging 53, 1–10.|||Nombela C, Nombela M, Castell P, Garcia T, Lopez-Coronado J, Herrero MT, 2014. Alpha-theta effects associated with ageing during the Stroop test. PLoS One 9(5), e95657.|||Nunes RR, Almeida MP, Sleigh JW, 2004. [Spectral entropy: a new method for anesthetic adequacy.]. Rev Bras Anestesiol 54(3), 404–422.|||Pagano S, Fait E, Monti A, Brignani D, Mazza V, 2015. Electrophysiological Correlates of Subitizing in Healthy Aging. PLoS One 10(6), e0131063.|||Pan C, Korff A, Galasko D, Ginghina C, Peskind E, Li G, Quinn J, Montine TJ, Cain K, Shi M, Zhang J, 2015. Diagnostic Values of Cerebrospinal Fluid T-Tau and Abeta(4)(2) using Meso Scale Discovery Assays for Alzheimer’s Disease. J Alzheimers Dis 45(3), 709–719.|||Patten RV, Fagan AM, Kaufman DAS, 2018. Differential Cued-Stroop Performance in Cognitively Asymptomatic Older Adults with Biomarker-Identified Risk for Alzheimer’s Disease: A Pilot Study. Curr Alzheimer Res 15(9), 820–827.|||Pettigrew C, Soldan A, Zhu Y, Cai Q, Wang MC, Moghekar A, Miller MI, Singh B, Martinez O, Fletcher E, DeCarli C, Albert M, 2020. Cognitive reserve and rate of change in Alzheimer’s and cerebrovascular disease biomarkers among cognitively normal individuals. Neurobiol Aging 88, 33–41.|||Qi Z, Wu X, Wang Z, Zhang N, Dong H, Yao L, Li K, 2010. Impairment and compensation coexist in amnestic MCI default mode network. Neuroimage 50(1), 48–55.|||Quandt F, Bonstrup M, Schulz R, Timmermann JE, Zimerman M, Nolte G, Hummel FC, 2016. Spectral Variability in the Aged Brain during Fine Motor Control. Front Aging Neurosci 8, 305.|||Ranasinghe KG, Cha J, Iaccarino L, Hinkley LB, Beagle AJ, Pham J, Jagust WJ, Miller BL, Rankin KP, Rabinovici GD, Vossel KA, Nagarajan SS, 2020. Neurophysiological signatures in Alzheimer’s disease are distinctly associated with TAU, amyloid-beta accumulation, and cognitive decline. Sci Transl Med 12(534).|||Riedner BA, Goldstein MR, Plante DT, Rumble ME, Ferrarelli F, Tononi G, Benca RM, 2016. Regional Patterns of Elevated Alpha and High-Frequency Electroencephalographic Activity during Nonrapid Eye Movement Sleep in Chronic Insomnia: A Pilot Study. Sleep 39(4), 801–812.|||Ritchie C, Smailagic N, Noel-Storr AH, Ukoumunne O, Ladds EC, Martin S, 2017. CSF tau and the CSF tau/ABeta ratio for the diagnosis of Alzheimer’s disease dementia and other dementias in people with mild cognitive impairment (MCI). Cochrane Database Syst Rev 3, CD010803.|||Rochart R, Liu Q, Fonteh AN, Harrington MG, Arakaki X, 2020. Compromised Behavior and Gamma Power During Working Memory in Cognitively Healthy Individuals With Abnormal CSF Amyloid/Tau. Front Aging Neurosci 12, 574214.|||Roe CM, Fagan AM, Grant EA, Hassenstab J, Moulder KL, Maue Dreyfus D, Sutphen CL, Benzinger TL, Mintun MA, Holtzman DM, Morris JC, 2013. Amyloid imaging and CSF biomarkers in predicting cognitive impairment up to 7.5 years later. Neurology 80(19), 1784–1791.|||Schneider JA, Arvanitakis Z, Leurgans SE, Bennett DA, 2009. The neuropathology of probable Alzheimer disease and mild cognitive impairment. Ann Neurol 66(2), 200–208.|||Stam CJ, de Haan W, Daffertshofer A, Jones BF, Manshanden I, van Cappellen van Walsum AM, Montez T, Verbunt JP, de Munck JC, van Dijk BW, Berendse HW, Scheltens P, 2009. Graph theoretical analysis of magnetoencephalographic functional connectivity in Alzheimer’s disease. Brain 132(Pt 1), 213–224.|||Stern Y, 2009. Cognitive reserve. Neuropsychologia 47(10), 2015–2028.|||Suffczynski P, Kalitzin S, Pfurtscheller G, Lopes da Silva FH, 2001. Computational model of thalamo-cortical networks: dynamical control of alpha rhythms in relation to focal attention. Int J Psychophysiol 43(1), 25–40.|||Tissier C, Linzarini A, Allaire-Duquette G, Mevel K, Poirel N, Dollfus S, Etard O, Orliac F, Peyrin C, Charron S, Raznahan A, Houde O, Borst G, Cachia A, 2018. Sulcal Polymorphisms of the IFC and ACC Contribute to Inhibitory Control Variability in Children and Adults. eNeuro 5(1).|||Tse CS, Balota DA, Yap MJ, Duchek JM, McCabe DP, 2010. Effects of healthy aging and early stage dementia of the Alzheimer’s type on components of response time distributions in three attention tasks. Neuropsychology 24(3), 300–315.|||van Veen V, Carter CS, 2005. Separating semantic conflict and response conflict in the Stroop task: a functional MRI study. Neuroimage 27(3), 497–504.|||Vazquez-Marrufo M, Galvao-Carmona A, Benitez Lugo ML, Ruiz-Pena JL, Borges Guerra M, Izquierdo Ayuso G, 2017. Retest reliability of individual alpha ERD topography assessed by human electroencephalography. PLoS One 12(10), e0187244.|||Wilder C, Moncrieffe K, Nolty A, ;, Arakaki X, Fonteh A, Harrington M, 2018. Boston Naming Test predicts deterioration of cerebrospinal fluid biomarkers in pre-symptomatic Alzheimer’s disease. The FASEB Journal 32(1_supplement).|||Wilson RS, Bennett DA, Gilley DW, Beckett LA, Barnes LL, Evans DA, 2000. Premorbid reading activity and patterns of cognitive decline in Alzheimer disease. Arch Neurol 57(12), 1718–1723.|||Xavier G, Su Ting A, Fauzan N, 2020. Exploratory study of brain waves and corresponding brain regions of fatigue on-call doctors using quantitative electroencephalogram. J Occup Health 62(1), e12121.