nach oben

Journal of Neurology

Erschienen in:

03.05.2023 | Original Communication

Decreased aperiodic neural activity in Parkinson’s disease and dementia with Lewy bodies

verfasst von: Yevgenia Rosenblum, Tamara Shiner, Noa Bregman, Nir Giladi, Inbal Maidan, Firas Fahoum, Anat Mirelman

Erschienen in: Journal of Neurology | Ausgabe 8/2023

Einloggen, um Zugang zu erhalten

Abstract

Neural oscillations and signal complexity have been widely studied in neurodegenerative diseases, whereas aperiodic activity has not been explored yet in those disorders. Here, we assessed whether the study of aperiodic activity brings new insights relating to disease as compared to the conventional spectral and complexity analyses. Eyes-closed resting-state electroencephalography (EEG) was recorded in 21 patients with dementia with Lewy bodies (DLB), 28 patients with Parkinson’s disease (PD), 27 patients with mild cognitive impairment (MCI) and 22 age-matched healthy controls. Spectral power was differentiated into its oscillatory and aperiodic components using the Irregularly Resampled Auto-Spectral Analysis. Signal complexity was explored using the Lempel–Ziv algorithm (LZC). We found that DLB patients showed steeper slopes of the aperiodic power component with large effect sizes compared to the controls and MCI and with a moderate effect size compared to PD. PD patients showed steeper slopes with a moderate effect size compared to controls and MCI. Oscillatory power and LZC differentiated only between DLB and other study groups and were not sensitive enough to detect differences between PD, MCI, and controls. In conclusion, both DLB and PD are characterized by alterations in aperiodic dynamics, which are more sensitive in detecting disease-related neural changes than the traditional spectral and complexity analyses. Our findings suggest that steeper aperiodic slopes may serve as a marker of network dysfunction in DLB and PD features.

Nur mit Berechtigung zugänglich

Abásolo D, Hornero R, Gómez C, García M, López M (2006) Analysis of EEG background activity in Alzheimer’s disease patients with Lempel-Ziv complexity and central tendency measure. Med Eng Phys 28(4):315–322. https://doi.org/10.1016/j.medengphy.2005.07.004CrossRefPubMed

Abásolo D, Simons S, Morgado da Silva R, Tononi G, Vyazovskiy VV (2015) Lempel-Ziv complexity of cortical activity during sleep and waking in rats. J Neurophysiol 113(7):2742–2752. https://doi.org/10.1152/jn.00575.2014CrossRefPubMedPubMedCentral

Adelhöfer N, Paulus T, Mückschel M, Bäumer T, Bluschke A, Takacs A, Tóth-Fáber E, Tárnok Z, Roessner V, Weissbach A, Münchau A (2021) Increased scale-free and aperiodic neural activity during sensorimotor integration—a novel facet in Tourette syndrome. Brain Commun 3(4):fcab250. https://doi.org/10.1093/braincomms/fcab250CrossRefPubMedPubMedCentral

Babiloni C, Barry RJ, Başar E, Blinowska KJ, Cichocki A, Drinkenburg WH, Klimesch W, Knight RT, da Silva FL, Nunez P, Oostenveld R (2020) International Federation of Clinical Neurophysiology (IFCN)–EEG research workgroup: recommendations on frequency and topographic analysis of resting state EEG rhythms. Part 1: applications in clinical research studies. Clin Neurophysiol 131(1):285–307. https://doi.org/10.1016/j.clinph.2019.06.234CrossRefPubMed

Bédard C, Destexhe A (2009) Macroscopic models of local field potentials and the apparent 1/f noise in brain activity. Biophys J 96(7):2589–2603. https://doi.org/10.1016/j.bpj.2008.12.3951CrossRefPubMedPubMedCentral

Bódizs R, Szalárdy O, Horváth C, Ujma PP, Gombos F, Simor P, Pótári A, Zeising M, Steiger A, Dresler M (2021) A set of composite, non-redundant EEG measures of NREM sleep based on the power law scaling of the Fourier spectrum. Sci Reports 11(1):1–8. https://doi.org/10.1038/s41598-021-81230-7CrossRef

Cassani R, Estarellas M, San-Martin R, Fraga FJ, Falk TH (2018) Systematic review on resting-state EEG for Alzheimer’s disease diagnosis and progression assessment. Dis Markers 4:2018. https://doi.org/10.1155/2018/5174815CrossRef

Colombo MA, Napolitani M, Boly M, Gosseries O, Casarotto S, Rosanova M, Brichant JF, Boveroux P, Rex S, Laureys S, Massimini M (2019) The spectral exponent of the resting EEG indexes the presence of consciousness during unresponsiveness induced by propofol, xenon, and ketamine. Neuroimage 189:631–644. https://doi.org/10.1016/j.neuroimage.2019.01.024CrossRefPubMed

Darmani G, Drummond NM, Ramezanpour H, Saha U, Hoque T, Udupa K, Sarica C, Zeng K, Cortez Grippe T, Nankoo JF, Bergmann TO (2023) Long-term recording of subthalamic aperiodic activities and beta bursts in Parkinson’s disease. Mov Disord 38(2):232–243. https://doi.org/10.1002/mds.29276CrossRefPubMed

10.

Dauwels J, Srinivasan K, Ramasubba Reddy M, Musha T, Vialatte FB, Latchoumane C, Jeong J, Cichocki A (2011) Slowing and loss of complexity in Alzheimer’s EEG: two sides of the same coin? Int J Alz Dis 13:2011. https://doi.org/10.4061/2011/539621CrossRef

11.

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. https://doi.org/10.1016/j.jneumeth.2003.10.009CrossRefPubMed

12.

Donoghue T, Haller M, Peterson EJ, Varma P, Sebastian P, Gao R, Noto T, Lara AH, Wallis JD, Knight RT, Shestyuk A (2020) Parameterizing neural power spectra into periodic and aperiodic components. Nat Neurosci 23(12):1655–1665. https://doi.org/10.1038/s41593-020-00744-xCrossRefPubMedPubMedCentral

13.

Faul S (2020) Kolmogorov Complexity. https://www.mathworks.com/matlabcentral/fileexchange/6886-kolmogorov-complexity, MATLAB Central File Exchange.

14.

Gao R, Peterson EJ, Voytek B (2017) Inferring synaptic excitation/inhibition balance from field potentials. Neuroimage 158:70–78. https://doi.org/10.1016/j.neuroimage.2017.06.078CrossRefPubMed

15.

Gerster M, Waterstraat G, Litvak V, Lehnertz K, Schnitzler A, Florin E, Curio G, Nikulin V (2022) Separating neural oscillations from aperiodic 1/f activity: challenges and recommendations. Neuroinformatics 20(4):991–1012. https://doi.org/10.1007/s12021-022-09581-8CrossRefPubMedPubMedCentral

16.

Gómez C, Hornero R, Abásolo D, Fernández A, López M (2006) Complexity analysis of the magnetoencephalogram background activity in Alzheimer’s disease patients. Med Eng Phys 28(9):851–859. https://doi.org/10.1016/j.medengphy.2006.01.003CrossRefPubMed

17.

Gómez C, Dubbelink KT, Stam CJ, Abásolo D, Berendse HW, Hornero R (2011) Complexity analysis of resting-state MEG activity in early-stage Parkinson’s disease patients. Ann Biomed Eng 39(12):2935. https://doi.org/10.1007/s10439-011-0416-0CrossRefPubMed

18.

He BJ, Zempel JM, Snyder AZ, Raichle ME (2010) The temporal structures and functional significance of scale-free brain activity. Neuron 66(3):353–369. https://doi.org/10.1016/j.neuron.2010.04.020CrossRefPubMedPubMedCentral

19.

He BJ (2014) Scale-free brain activity: past, present, and future. Trends Cogn Sci 18(9):480–487. https://doi.org/10.1016/j.tics.2014.04.003CrossRefPubMedPubMedCentral

20.

Helson P, Lundqvist D, Svenningsson P, Vinding MC, Kumar A (2023) Cortex-wide topography of 1/f-exponent in Parkinson's disease. bioRxiv. https://doi.org/10.1101/2023.01.19.524792CrossRef

21.

Höhn C, Hahn MA, Lendner JD, Hoedlmoser K (2022) Spectral slope and neural complexity as robust markers of task demand and brain state during sleep and wakefulness. bioRxiv. https://doi.org/10.1101/2022.09.10.507390CrossRef

22.

Hong SL, Rebec GV (2012) A new perspective on behavioral inconsistency and neural noise in aging: compensatory speeding of neural communication. Front Aging Neurosci 25(4):27. https://doi.org/10.3389/fnagi.2012.00027CrossRef

23.

Hornero R, Abásolo D, Escudero J, Gómez C (1887) Nonlinear analysis of electroencephalogram and magnetoencephalogram recordings in patients with Alzheimer’s disease. Philos Trans A Math Phys Eng Sci 367(1887):317–336. https://doi.org/10.1098/rsta.2008.0197CrossRef

24.

Iber C (2007) The AASM manual for the scoring of sleep and associated events: rules. Terminology and technical specification. Published online

25.

Lempel A, Ziv J (1976) On the complexity of finite sequences. IEEE Trans Inf Theory 22:75–81CrossRef

26.

Lindén H, Pettersen KH, Einevoll GT (2010) Intrinsic dendritic filtering gives low-pass power spectra of local field potentials. J Comp Neurosci 29(3):423–444. https://doi.org/10.1007/s10827-010-0245-4CrossRef

27.

Litvan I, Goldman JG, Tröster AI et al (2012) Diagnostic criteria for mild cognitive impairment in Parkinson’s disease: movement disorder society task force guidelines. Mov Disord 27(3):349–356. https://doi.org/10.1002/mds.24893CrossRefPubMedPubMedCentral

28.

Mazaheri A, Slagter HA, Thut G, Foxe JJ (2018) Orchestration of brain oscillations: principles *and functions. Eur J Neurosci 48(7):2385–2388. https://doi.org/10.1111/ejn.14189CrossRefPubMed

29.

McKeith IG, Boeve BF, Dickson DW, Halliday G, Taylor JP, Weintraub D, Aarsland D, Galvin J, Attems J, Ballard CG, Bayston A (2017) Diagnosis and management of dementia with Lewy bodies: fourth consensus report of the DLB Consortium. Neurology 89:88–100. https://doi.org/10.1212/WNL.0000000000004058CrossRefPubMedPubMedCentral

30.

Medel V, Irani M, Crossley N, Ossandón T, Boncompte G (2020) Complexity and 1/f slope jointly reflect brain states. https://doi.org/10.1101/2020.09.15.298497

31.

Miskovic V, MacDonald KJ, Rhodes LJ, Cote KA (2019) Changes in EEG multiscale entropy and power-law frequency scaling during the human sleep cycle. Human Brain Mapp 40(2):538–551. https://doi.org/10.1002/hbm.24393CrossRef

32.

Neumann WJ, Staub-Bartelt F, Horn A, Schanda J, Schneider GH, Brown P, Kühn AA (2017) Long term correlation of subthalamic beta band activity with motor impairment in patients with Parkinson’s disease. Clin Neurophysiol 128(11):2286–2291. https://doi.org/10.1016/j.clinph.2017.08.028CrossRefPubMedPubMedCentral

33.

Oostenveld R, Fries P, Maris E, Schoffelen JM (2011) FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput Intell Neurosci. https://doi.org/10.1155/2011/156869CrossRefPubMedPubMedCentral

34.

Ouyang G, Hildebrandt A, Schmitz F, Herrmann CS (2020) Decomposing alpha and 1/f brain activities reveals their differential associations with cognitive processing speed. Neuroimage 205:116304. https://doi.org/10.1016/j.neuroimage.2019.116304CrossRefPubMed

35.

Petersen RC, Lopez O, Armstrong MJ, Getchius TS, Ganguli M, Gloss D, Gronseth GS, Marson D, Pringsheim T, Day GS, Sager M (2018) Practice guideline update summary: mild cognitive impairment: report of the guideline development, dissemination, and implementation subcommittee of the American Academy of Neurology. Neurology 90(3):126–135. https://doi.org/10.1212/WNL.0000000000004826CrossRefPubMedPubMedCentral

36.

Podvalny E, Noy N, Harel M, Bickel S, Chechik G, Schroeder CE, Mehta AD, Tsodyks M, Malach R (2015) A unifying principle underlying the extracellular field potential spectral responses in the human cortex. J Nerophysiol 114(1):505–519. https://doi.org/10.1152/jn.00943.2014CrossRef

37.

Rosenblum Y, Maidan I, Fahoum F, Giladi N, Bregman N, Shiner T, Mirelman A (2020) Differential changes in visual and auditory event-related oscillations in dementia with Lewy bodies. Clin Neurophysiol 131(10):2357–2366. https://doi.org/10.1016/j.clinph.2020.06.029CrossRefPubMed

38.

Rosenblum Y, Maidan I, Goldstein O, Gana-Weisz M, Orr-Urtreger A, Bregman N, Giladi N, Mirelman A, Shiner T (2022) Decreased delta-band event-related power in dementia with Lewy bodies with a mutation in the glucocerebrosidase gene. Clin Neurophysiol 143:14–20. https://doi.org/10.1016/j.clinph.2022.08.011CrossRefPubMed

39.

Rosenblum Y, Shiner T, Bregman N, Fahoum F, Giladi N, Maidan I, Mirelman A (2022) Event-related oscillations differentiate between cognitive, motor and visual impairments. J Neurol. https://doi.org/10.1007/s00415-021-10953-4CrossRefPubMed

40.

Rosenblum Y, Bovy L, Weber FD, Steiger A, Zeising M, Dresler M (2022) Increased aperiodic neural activity during sleep in major depressive disorder. Biol Psychiatry. https://doi.org/10.1016/j.bpsgos.2022.10.001CrossRef

41.

Sami S, Williams N, Hughes LE, Cope TE, Rittman T, Coyle-Gilchrist IT, Henson RN, Rowe JB (2018) Neurophysiological signatures of Alzheimer’s disease and frontotemporal lobar degeneration: pathology versus phenotype. Brain 141(8):2500–2510. https://doi.org/10.1093/brain/awy180CrossRefPubMedPubMedCentral

42.

Schartner M, Seth A, Noirhomme Q, Boly M, Bruno MA, Laureys S, Barrett A (2015) Complexity of multi-dimensional spontaneous EEG decreases during propofol induced general anaesthesia. PLoS ONE 10(8):e0133532. https://doi.org/10.1371/journal.pone.0133532CrossRefPubMedPubMedCentral

43.

Schartner MM, Carhart-Harris RL, Barrett AB, Seth AK, Muthukumaraswamy SD (2017) Increased spontaneous MEG signal diversity for psychoactive doses of ketamine, LSD and psilocybin. Sci Rep 7(1):1–2. https://doi.org/10.1038/srep46421CrossRef

44.

Schneider B, Szalárdy O, Ujma PP, Simor P, Gombos F, Kovács I, Dresler M, Bódizs R (2022) Scale-free and oscillatory spectral measures of sleep stages in humans. bioRxiv. https://doi.org/10.3389/fninf.2022.989262CrossRef

45.

Schnitzler A, Gross J (2005) Normal and pathological oscillatory communication in the brain. Nat Rev Neurosci 6(4):285–296. https://doi.org/10.1038/nrn1650CrossRefPubMed

46.

Shumbayawonda E, López-Sanz D, Bruña R, Serrano N, Fernández A, Maestú F, Abasolo D (2020) Complexity changes in preclinical Alzheimer’s disease: an MEG study of subjective cognitive decline and mild cognitive impairment. Clin Neurophysiol 131(2):437–445. https://doi.org/10.1016/j.clinph.2019.11.023CrossRefPubMed

47.

Stam CJ (2005) Nonlinear dynamical analysis of EEG and MEG: review of an emerging field. Clin Neurophysiol 116(10):2266–2301. https://doi.org/10.1016/j.clinph.2005.06.011CrossRefPubMed

48.

Su L, Blamire A, Watson R, He J, Hayes L, O’Brien JT (2016) Whole-brain patterns of ¹H-magnetic resonance spectroscopy imaging in Alzheimer’s disease and dementia with Lewy bodies. Transl Psychiatry 6(8):e877. https://doi.org/10.1038/tp.2016.140CrossRefPubMedPubMedCentral

49.

Timmermann C, Roseman L, Schartner M, Milliere R, Williams LT, Erritzoe D, Muthukumaraswamy S, Ashton M, Bendrioua A, Kaur O, Turton S (2019) Neural correlates of the DMT experience assessed with multivariate EEG. Sci Rep 9(1):1–3. https://doi.org/10.1002/glia.20201CrossRef

50.

Vinding M, Eriksson A, Manting C, Waldthaler J, Ferreira D, Ingvar M, Svenningsson P, Lundqvist D (2022) Changes in non-oscillatory features of the cortical sensorimotor rhythm in Parkinson's disease across age. https://doi.org/10.21203/rs.3.rs-1699006/v1

51.

Voytek B, Kramer MA, Case J, Lepage KQ, Tempesta ZR, Knight RT, Gazzaley A (2015) Age-related changes in 1/f neural electrophysiological noise. J Neurosci 35(38):13257–13265. https://doi.org/10.1523/JNEUROSCI.2332-14.2015CrossRefPubMedPubMedCentral

52.

Waschke L, Donoghue T, Fiedler L, Smith S, Garrett DD, Voytek B, Obleser J (2021) Modality-specific tracking of attention and sensory statistics in the human electrophysiological spectral exponent. Elife. https://doi.org/10.1101/2021.01.13.426522CrossRefPubMedPubMedCentral

53.

Wen H, Liu Z (2016) Separating fractal and oscillatory components in the power spectrum of neurophysiological signal. Brain Topogr 29(1):13–26. https://doi.org/10.1007/s10548-015-0448-0CrossRefPubMed

54.

Wiest C, Torrecillos F, Pogosyan A, Bange M, Muthuraman M, Groppa S, Hulse N, Hasegawa H, Ashkan K, Baig F, Morgante F (2023) The aperiodic exponent of subthalamic field potentials reflects excitation/inhibition balance in Parkinsonism. Elife 12:e82467. https://elifesciences.org/articles/82467?s=03

55.

Zhang J, Villringer A, Nikulin VV (2022) Dopaminergic modulation of local non-oscillatory activity and global-network properties in Parkinson’s disease: an EEG study. Front Aging Neurosci 14:846017. https://doi.org/10.3389/fnagi.2022.846017CrossRefPubMedPubMedCentral

Titel: Decreased aperiodic neural activity in Parkinson’s disease and dementia with Lewy bodies
verfasst von: Yevgenia Rosenblum
Tamara Shiner
Noa Bregman
Nir Giladi
Inbal Maidan
Firas Fahoum
Anat Mirelman
Publikationsdatum: 03.05.2023
Verlag: Springer Berlin Heidelberg
Erschienen in: Journal of Neurology / Ausgabe 8/2023
Print ISSN: 0340-5354
Elektronische ISSN: 1432-1459
DOI: https://doi.org/10.1007/s00415-023-11728-9

Leitlinien kompakt für die Neurologie

Mit medbee Pocketcards sicher entscheiden.

^{Seit 2022 gehört die medbee GmbH zum Springer Medizin Verlag}

Kostenlos registrieren

Neu im Fachgebiet Neurologie

Nicht Creutzfeldt Jakob, sondern Abführtee-Vergiftung

29.05.2024 Hyponatriämie Nachrichten

Eine ältere Frau trinkt regelmäßig Sennesblättertee gegen ihre Verstopfung. Der scheint plötzlich gut zu wirken. Auf Durchfall und Erbrechen folgt allerdings eine Hyponatriämie. Nach deren Korrektur kommt es plötzlich zu progredienten Kognitions- und Verhaltensstörungen.

Schutz der Synapsen bei Alzheimer

29.05.2024 Morbus Alzheimer Nachrichten

Mit einem Neurotrophin-Rezeptor-Modulator lässt sich möglicherweise eine bestehende Alzheimerdemenz etwas abschwächen: Erste Phase-2-Daten deuten auf einen verbesserten Synapsenschutz.

Sozialer Aufstieg verringert Demenzgefahr

24.05.2024 Demenz Nachrichten

Ein hohes soziales Niveau ist mit die beste Versicherung gegen eine Demenz. Noch geringer ist das Demenzrisiko für Menschen, die sozial aufsteigen: Sie gewinnen fast zwei demenzfreie Lebensjahre. Umgekehrt steigt die Demenzgefahr beim sozialen Abstieg.

Hirnblutung unter DOAK und VKA ähnlich bedrohlich

17.05.2024 Direkte orale Antikoagulanzien Nachrichten

Kommt es zu einer nichttraumatischen Hirnblutung, spielt es keine große Rolle, ob die Betroffenen zuvor direkt wirksame orale Antikoagulanzien oder Marcumar bekommen haben: Die Prognose ist ähnlich schlecht.

Update Neurologie

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.

Newsletter bestellen

Live-Webinar "Urologie und Sexualmedizin in der Praxis"

Springer Medizin

Abstract

Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten

Weitere Artikel der Ausgabe 8/2023

Identifying novel genes for amyotrophic lateral sclerosis by integrating human brain proteomes with genome-wide association data

Antiplatelet therapy may improve the prognosis of patients with moyamoya disease: a 12-year retrospective study

Memory-guided navigation in amyotrophic lateral sclerosis

Gadolinium contrast agents: dermal deposits and potential effects on epidermal small nerve fibers

Safety and effectiveness of ataluren in patients with nonsense mutation DMD in the STRIDE Registry compared with the CINRG Duchenne Natural History Study (2015–2022): 2022 interim analysis