Quick Links

Alpha desynchronization during simple working memory unmasks pathological aging in cognitively healthy individuals.

Authors: Xianghong Arakaki|||Ryan Lee|||Kevin S King|||Alfred N Fonteh|||Michael G Harrington

Journal: PloS one

Publication Type: Journal Article

Date: 2019

DOI: PMC6314588

ID: 30601822

Affiliations:

Affiliations

    Neurosciences, Huntington Medical Research Institutes, Pasadena, California, United States of America.|||Neurosciences, Huntington Medical Research Institutes, Pasadena, California, United States of America.|||Imaging Research, Huntington Medical Research Institutes, Pasadena, California, United States of America.|||Neurosciences, Huntington Medical Research Institutes, Pasadena, California, United States of America.|||Neurosciences, Huntington Medical Research Institutes, Pasadena, California, United States of America.

Abstract

Our aim is to explore if cognitive challenge combined with objective physiology can reveal abnormal frontal alpha event-related desynchronization (ERD), in early Alzheimer's disease (AD). We used quantitative electroencephalography (qEEG) to investigate brain activities during N-back working memory (WM) processing at two different load conditions (N = 0 or 2) in an aging cohort. We studied 60-100 year old participants, with normal cognition, and who fits one of two subgroups from cerebrospinal fluid (CSF) proteins: cognitively healthy (CH) with normal amyloid/tau ratio (CH-NAT, n = 10) or pathological amyloid/tau ratio (CH-PAT, n = 14). We recorded behavioral performances, and analyzed alpha power and alpha spectral entropy (SE) at three occasions: during the resting state, and at event-related desynchronization (ERD) [250 ~ 750 ms] during 0-back and 2-back. During 0-back WM testing, the behavioral performance was similar between the two groups, however, qEEG notably differentiated CH-PATs from CH-NATs on the simple, 0-back testing: Alpha ERD decreased from baseline only in the parietal region in CH-NATs, while it decreased in all brain regions in CH-PATs. Alpha SE did not change in CH-NATs, but was increased from baseline in the CH-PATs in frontal and left lateral regions (p<0.01), and was higher in the frontal region (p<0.01) of CH-PATs compared to CH-NATs. The alpha ERD and SE analyses suggest there is frontal lobe dysfunction during WM processing in the CH-PAT stage. Additional power and correlations with behavioral performance were also explored. This study provide pilot information to further evaluate whether this biomarker has clinical significance.


Chemical List

    Amyloid beta-Peptides|||tau Proteins

Reference List

    Lynn PA, Kang SS, Sponheim SR. Impaired retrieval processes evident during visual working memory in schizophrenia. Schizophr Res Cogn. 2016;5:47–55. 10.1016/j.scog.2016.07.002|||Lianyang L, Arakaki X, Thao T, Harrington M, Padhye N, Zouridakis G. Brain activation profiles in mTBI: evidence from ERP activity of working memory response. Conf Proc IEEE Eng Med Biol Soc. 2016;2016:1862–5. 10.1109/EMBC.2016.7591083 .|||Koppen H, Palm-Meinders I, Kruit M, Lim V, Nugroho A, Westhof I, et al. The impact of a migraine attack and its after-effects on perceptual organization, attention, and working memory. Cephalalgia. 2011;31(14):1419–27. 10.1177/0333102411417900 .|||Harrington MG, Chiang J, Pogoda JM, Gomez M, Thomas K, Marion SD, et al. Executive function changes before memory in preclinical Alzheimer's pathology: a prospective, cross-sectional, case control study. PLoS One. 2013;8(11):e79378 10.1371/journal.pone.0079378|||McGuinness B, Barrett SL, Craig D, Lawson J, Passmore AP. Executive functioning in Alzheimer's disease and vascular dementia. Int J Geriatr Psychiatry. 2010;25(6):562–8. 10.1002/gps.2375 .|||Kalpouzos G, Eustache F, de la Sayette V, Viader F, Chetelat G, Desgranges B. Working memory and FDG-PET dissociate early and late onset Alzheimer disease patients. J Neurol. 2005;252(5):548–58. 10.1007/s00415-005-0685-3 .|||Sperling RA, Aisen PS, Beckett LA, Bennett DA, Craft S, Fagan AM, et al. Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011;7(3):280–92. 10.1016/j.jalz.2011.03.003|||Jack CR Jr., Knopman DS, Jagust WJ, Shaw LM, Aisen PS, Weiner MW, et al. Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade. Lancet Neurol. 2010;9(1):119–28. 10.1016/S1474-4422(09)70299-6|||Wilder C, Moncrieffe K, Nolty A, Arakaki X, Fonteh AN, Harrington MG. Boston Naming Test predicts deterioration of cerebrospinal fluid biomarkers in pre-symptomatic Alzheimer’s disease. FASEB Journal. 2018;accepted.|||Diamond A. Executive functions. Annu Rev Psychol. 2013;64:135–68. 10.1146/annurev-psych-113011-143750|||Callicott JH, Mattay VS, Verchinski BA, Marenco S, Egan MF, Weinberger DR. Complexity of prefrontal cortical dysfunction in schizophrenia: more than up or down. Am J Psychiatry. 2003;160(12):2209–15. 10.1176/appi.ajp.160.12.2209 .|||Takahashi M, Iwamoto K, Fukatsu H, Naganawa S, Iidaka T, Ozaki N. White matter microstructure of the cingulum and cerebellar peduncle is related to sustained attention and working memory: a diffusion tensor imaging study. Neurosci Lett. 2010;477(2):72–6. 10.1016/j.neulet.2010.04.031 .|||Yener GG, Basar E. Biomarkers in Alzheimer's disease with a special emphasis on event-related oscillatory responses. Suppl Clin Neurophysiol. 2013;62:237–73. .|||Tonnies E, Trushina E. Oxidative Stress, Synaptic Dysfunction, and Alzheimer's Disease. J Alzheimers Dis. 2017;57(4):1105–21. 10.3233/JAD-161088|||Nava-Mesa MO, Jimenez-Diaz L, Yajeya J, Navarro-Lopez JD. GABAergic neurotransmission and new strategies of neuromodulation to compensate synaptic dysfunction in early stages of Alzheimer's disease. Front Cell Neurosci. 2014;8:167 10.3389/fncel.2014.00167|||Pimplikar SW, Nixon RA, Robakis NK, Shen J, Tsai LH. Amyloid-independent mechanisms in Alzheimer's disease pathogenesis. J Neurosci. 2010;30(45):14946–54. 10.1523/JNEUROSCI.4305-10.2010|||Klimesch W. alpha-band oscillations, attention, and controlled access to stored information. Trends Cogn Sci. 2012;16(12):606–17. 10.1016/j.tics.2012.10.007|||Klimesch W, Hanslmayr S, Sauseng P, Gruber W, Brozinsky CJ, Kroll NE, et al. Oscillatory EEG correlates of episodic trace decay. Cereb Cortex. 2006;16(2):280–90. 10.1093/cercor/bhi107 .|||Schack B, Klimesch W, Sauseng P. Phase synchronization between theta and upper alpha oscillations in a working memory task. Int J Psychophysiol. 2005;57(2):105–14. 10.1016/j.ijpsycho.2005.03.016 .|||Grabner RH, Fink A, Stipacek A, Neuper C, Neubauer AC. Intelligence and working memory systems: evidence of neural efficiency in alpha band ERD. Brain Res Cogn Brain Res. 2004;20(2):212–25. 10.1016/j.cogbrainres.2004.02.010 .|||Grabner RH, Neubauer AC, Stern E. Superior performance and neural efficiency: the impact of intelligence and expertise. Brain Res Bull. 2006;69(4):422–39. 10.1016/j.brainresbull.2006.02.009 .|||Del Percio C, Babiloni C, Bertollo M, Marzano N, Iacoboni M, Infarinato F, et al. Visuo-attentional and sensorimotor alpha rhythms are related to visuo-motor performance in athletes. Hum Brain Mapp. 2009;30(11):3527–40. 10.1002/hbm.20776 .|||Dong S, Reder LM, Yao Y, Liu Y, Chen F. Individual differences in working memory capacity are reflected in different ERP and EEG patterns to task difficulty. Brain Res. 2015;1616:146–56. 10.1016/j.brainres.2015.05.003 .|||Lenartowicz A, Lu S, Rodriguez C, Lau EP, Walshaw PD, McCracken JT, et al. Alpha desynchronization and fronto-parietal connectivity during spatial working memory encoding deficits in ADHD: A simultaneous EEG-fMRI study. Neuroimage Clin. 2016;11:210–23. 10.1016/j.nicl.2016.01.023|||Wang C, Rajagovindan R, Han SM, Ding M. Top-Down Control of Visual Alpha Oscillations: Sources of Control Signals and Their Mechanisms of Action. Front Hum Neurosci. 2016;10:15 10.3389/fnhum.2016.00015|||Sadaghiani S, Scheeringa R, Lehongre K, Morillon B, Giraud AL, D'Esposito M, et al. alpha-band phase synchrony is related to activity in the fronto-parietal adaptive control network. J Neurosci. 2012;32(41):14305–10. 10.1523/JNEUROSCI.1358-12.2012|||Lenartowicz A, Delorme A, Walshaw PD, Cho AL, Bilder RM, McGough JJ, et al. Electroencephalography correlates of spatial working memory deficits in attention-deficit/hyperactivity disorder: vigilance, encoding, and maintenance. J Neurosci. 2014;34(4):1171–82. 10.1523/JNEUROSCI.1765-13.2014|||Inouye T, Shinosaki K, Sakamoto H, Toi S, Ukai S, Iyama A, et al. Quantification of EEG irregularity by use of the entropy of the power spectrum. Electroencephalogr Clin Neurophysiol. 1991;79(3):204–10. Epub 1991/09/01. .|||Nunes RR, Almeida MP, Sleigh JW. [Spectral entropy: a new method for anesthetic adequacy.]. Rev Bras Anestesiol. 2004;54(3):404–22. Epub 2004/06/01. .|||Vakkuri A, Yli-Hankala A, Talja P, Mustola S, Tolvanen-Laakso H, Sampson T, et al. Time-frequency balanced spectral entropy as a measure of anesthetic drug effect in central nervous system during sevoflurane, propofol, and thiopental anesthesia. Acta Anaesthesiol Scand. 2004;48(2):145–53. Epub 2004/03/05. .|||Uriguen JA, Garcia-Zapirain B, Artieda J, Iriarte J, Valencia M. Comparison of background EEG activity of different groups of patients with idiopathic epilepsy using Shannon spectral entropy and cluster-based permutation statistical testing. PLoS One. 2017;12(9):e0184044 10.1371/journal.pone.0184044|||Lopez ME, Bruna R, Aurtenetxe S, Pineda-Pardo JA, Marcos A, Arrazola J, et al. Alpha-band hypersynchronization in progressive mild cognitive impairment: a magnetoencephalography study. J Neurosci. 2014;34(44):14551–9. 10.1523/JNEUROSCI.0964-14.2014 .|||Qi Z, Wu X, Wang Z, Zhang N, Dong H, Yao L, et al. Impairment and compensation coexist in amnestic MCI default mode network. Neuroimage. 2010;50(1):48–55. 10.1016/j.neuroimage.2009.12.025 .|||Mormino EC, Smiljic A, Hayenga AO, Onami SH, Greicius MD, Rabinovici GD, et al. Relationships between beta-amyloid and functional connectivity in different components of the default mode network in aging. Cereb Cortex. 2011;21(10):2399–407. 10.1093/cercor/bhr025|||Lim HK, Nebes R, Snitz B, Cohen A, Mathis C, Price J, et al. Regional amyloid burden and intrinsic connectivity networks in cognitively normal elderly subjects. Brain. 2014;137(Pt 12):3327–38. 10.1093/brain/awu271|||Nakamura A, Cuesta P, Fernandez A, Arahata Y, Iwata K, Kuratsubo I, et al. Electromagnetic signatures of the preclinical and prodromal stages of Alzheimer's disease. Brain. 2018. 10.1093/brain/awy044 .|||Owen AM, McMillan KM, Laird AR, Bullmore E. N-back working memory paradigm: a meta-analysis of normative functional neuroimaging studies. Hum Brain Mapp. 2005;25(1):46–59. 10.1002/hbm.20131 .|||Arakaki X, Shoga M, Li L, Zouridakis G, Tran T, Fonteh AN, et al. Alpha desynchronization/synchronization during working memory testing is compromised in acute mild traumatic brain injury (mTBI). PLoS One. 2018;13(2):e0188101 10.1371/journal.pone.0188101 .|||Delorme A, Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods. 2004;134(1):9–21. 10.1016/j.jneumeth.2003.10.009 .|||Cohen MX, Donner TH. Midfrontal conflict-related theta-band power reflects neural oscillations that predict behavior. J Neurophysiol. 2013;110(12):2752–63. 10.1152/jn.00479.2013 .|||Cohen MX. Analyzing Neural Time Series Data: Theory and Practice. 2014.|||Vazquez-Marrufo M, Galvao-Carmona A, Benitez Lugo ML, Ruiz-Pena JL, Borges Guerra M, Izquierdo Ayuso G. Retest reliability of individual alpha ERD topography assessed by human electroencephalography. PLoS One. 2017;12(10):e0187244 10.1371/journal.pone.0187244|||Hu L, Peng W, Valentini E, Zhang Z, Hu Y. Functional features of nociceptive-induced suppression of alpha band electroencephalographic oscillations. J Pain. 2013;14(1):89–99. 10.1016/j.jpain.2012.10.008 .|||Pagano S, Fait E, Monti A, Brignani D, Mazza V. Electrophysiological Correlates of Subitizing in Healthy Aging. PLoS One. 2015;10(6):e0131063 10.1371/journal.pone.0131063|||Gola M, Magnuski M, Szumska I, Wrobel A. EEG beta band activity is related to attention and attentional deficits in the visual performance of elderly subjects. Int J Psychophysiol. 2013;89(3):334–41. 10.1016/j.ijpsycho.2013.05.007 .|||Quandt F, Bonstrup M, Schulz R, Timmermann JE, Zimerman M, Nolte G, et al. Spectral Variability in the Aged Brain during Fine Motor Control. Front Aging Neurosci. 2016;8:305 Epub 2017/01/10. 10.3389/fnagi.2016.00305|||Hong S, Beja-Glasser VF, Nfonoyim BM, Frouin A, Li S, Ramakrishnan S, et al. Complement and microglia mediate early synapse loss in Alzheimer mouse models. Science. 2016;352(6286):712–6. 10.1126/science.aad8373 .|||Nowrangi MA, Okonkwo O, Lyketsos C, Oishi K, Mori S, Albert M, et al. Atlas-based diffusion tensor imaging correlates of executive function. J Alzheimers Dis. 2015;44(2):585–98. 10.3233/JAD-141937|||Ranchet M, Morgan JC, Akinwuntan AE, Devos H. Cognitive workload across the spectrum of cognitive impairments: A systematic review of physiological measures. Neurosci Biobehav Rev. 2017;80:516–37. 10.1016/j.neubiorev.2017.07.001 .|||Foster JJ, Sutterer DW, Serences JT, Vogel EK, Awh E. The topography of alpha-band activity tracks the content of spatial working memory. J Neurophysiol. 2016;115(1):168–77. 10.1152/jn.00860.2015|||Miller KM, Price CC, Okun MS, Montijo H, Bowers D. Is the n-back task a valid neuropsychological measure for assessing working memory? Arch Clin Neuropsychol. 2009;24(7):711–7. 10.1093/arclin/acp063|||Saliasi E, Geerligs L, Lorist MM, Maurits NM. Neural correlates associated with successful working memory performance in older adults as revealed by spatial ICA. PLoS One. 2014;9(6):e99250 10.1371/journal.pone.0099250|||Schneider-Garces NJ, Gordon BA, Brumback-Peltz CR, Shin E, Lee Y, Sutton BP, et al. Span, CRUNCH, and beyond: working memory capacity and the aging brain. J Cogn Neurosci. 2010;22(4):655–69. 10.1162/jocn.2009.21230|||Bajo R, Castellanos NP, Cuesta P, Aurtenetxe S, Garcia-Prieto J, Gil-Gregorio P, et al. Differential patterns of connectivity in progressive mild cognitive impairment. Brain Connect. 2012;2(1):21–4. 10.1089/brain.2011.0069 .|||Benchenane K, Peyrache A, Khamassi M, Tierney PL, Gioanni Y, Battaglia FP, et al. Coherent theta oscillations and reorganization of spike timing in the hippocampal- prefrontal network upon learning. Neuron. 2010;66(6):921–36. 10.1016/j.neuron.2010.05.013 .|||Maurer U, Brem S, Liechti M, Maurizio S, Michels L, Brandeis D. Frontal midline theta reflects individual task performance in a working memory task. Brain Topogr. 2015;28(1):127–34. 10.1007/s10548-014-0361-y .|||Shannon CE. The mathematical theory of communication. 1963. MD Comput. 1997;14(4):306–17. Epub 1997/07/01. .|||Vanluchene AL, Vereecke H, Thas O, Mortier EP, Shafer SL, Struys MM. Spectral entropy as an electroencephalographic measure of anesthetic drug effect: a comparison with bispectral index and processed midlatency auditory evoked response. Anesthesiology. 2004;101(1):34–42. Epub 2004/06/29. .|||Tian Y, Zhang H, Xu W, Zhang H, Yang L, Zheng S, et al. Spectral Entropy Can Predict Changes of Working Memory Performance Reduced by Short-Time Training in the Delayed-Match-to-Sample Task. Front Hum Neurosci. 2017;11:437 Epub 2017/09/16. 10.3389/fnhum.2017.00437|||Blanco S, Garay A, Coulombie D. Comparison of frequency bands using spectral entropy for epileptic seizure prediction. ISRN Neurol. 2013;2013:287327 Epub 2013/06/20. 10.1155/2013/287327|||Bachiller A, Diez A, Suazo V, Dominguez C, Ayuso M, Hornero R, et al. Decreased spectral entropy modulation in patients with schizophrenia during a P300 task. Eur Arch Psychiatry Clin Neurosci. 2014;264(6):533–43. Epub 2014/02/06. 10.1007/s00406-014-0488-6 .|||Babiloni C, Frisoni GB, Pievani M, Vecchio F, Infarinato F, Geroldi C, et al. White matter vascular lesions are related to parietal-to-frontal coupling of EEG rhythms in mild cognitive impairment. Hum Brain Mapp. 2008;29(12):1355–67. 10.1002/hbm.20467 .|||Garcia-Marin V, Blazquez-Llorca L, Rodriguez JR, Boluda S, Muntane G, Ferrer I, et al. Diminished perisomatic GABAergic terminals on cortical neurons adjacent to amyloid plaques. Front Neuroanat. 2009;3:28 10.3389/neuro.05.028.2009|||Stephan KE, Baldeweg T, Friston KJ. Synaptic plasticity and dysconnection in schizophrenia. Biol Psychiatry. 2006;59(10):929–39. 10.1016/j.biopsych.2005.10.005 .|||Golob EJ, Ringman JM, Irimajiri R, Bright S, Schaffer B, Medina LD, et al. Cortical event-related potentials in preclinical familial Alzheimer disease. Neurology. 2009;73(20):1649–55. 10.1212/WNL.0b013e3181c1de77|||Bobes MA, Garcia YF, Lopera F, Quiroz YT, Galan L, Vega M, et al. ERP generator anomalies in presymptomatic carriers of the Alzheimer's disease E280A PS-1 mutation. Hum Brain Mapp. 2010;31(2):247–65. 10.1002/hbm.20861 .|||Baskaran A, Milev R, McIntyre RS. The neurobiology of the EEG biomarker as a predictor of treatment response in depression. Neuropharmacology. 2012;63(4):507–13. 10.1016/j.neuropharm.2012.04.021 .|||Olichney JM, Pak J, Salmon DP, Yang JC, Gahagan T, Nowacki R, et al. Abnormal P600 word repetition effect in elderly persons with preclinical Alzheimer's disease. Cogn Neurosci. 2013;4(3–4):143–51. 10.1080/17588928.2013.838945|||Deiber MP, Ibanez V, Missonnier P, Herrmann F, Fazio-Costa L, Gold G, et al. Abnormal-induced theta activity supports early directed-attention network deficits in progressive MCI. Neurobiol Aging. 2009;30(9):1444–52. 10.1016/j.neurobiolaging.2007.11.021 .|||Li J, Broster LS, Jicha GA, Munro NB, Schmitt FA, Abner E, et al. A cognitive electrophysiological signature differentiates amnestic mild cognitive impairment from normal aging. Alzheimers Res Ther. 2017;9(1):3 10.1186/s13195-016-0229-3|||Nakazono T, Jun H, Blurton-Jones M, Green KN, Igarashi KM. Gamma oscillations in the entorhinal-hippocampal circuit underlying memory and dementia. Neurosci Res. 2018;129:40–6. 10.1016/j.neures.2018.02.002 .|||Iaccarino HF, Singer AC, Martorell AJ, Rudenko A, Gao F, Gillingham TZ, et al. Gamma frequency entrainment attenuates amyloid load and modifies microglia. Nature. 2016;540(7632):230–5. 10.1038/nature20587|||Vorobyov S, Cichocki A. Blind noise reduction for multisensory signals using ICA and subspace filtering, with application to EEG analysis. Biol Cybern. 2002;86(4):293–303. 10.1007/s00422-001-0298-6 .|||Junghofer M, Elbert T, Tucker DM, Braun C. The polar average reference effect: a bias in estimating the head surface integral in EEG recording. Clin Neurophysiol. 1999;110(6):1149–55. .|||Yao D. A method to standardize a reference of scalp EEG recordings to a point at infinity. Physiol Meas. 2001;22(4):693–711. .|||Yao D, Wang L, Oostenveld R, Nielsen KD, Arendt-Nielsen L, Chen AC. A comparative study of different references for EEG spectral mapping: the issue of the neutral reference and the use of the infinity reference. Physiol Meas. 2005;26(3):173–84. 10.1088/0967-3334/26/3/003 .