Characterization of the dynamic behavior of neural activity in Alzheimer's disease: exploring the non-stationarity and recurrence structure of EEG resting-state activity.
[en] [en] OBJECTIVE: Mild cognitive impairment (MCI) and dementia due to Alzheimer's disease (AD) have been shown to induce perturbations to normal neuronal behavior and disrupt neuronal networks. Recent work suggests that the dynamic properties of resting-state neuronal activity could be affected by MCI and AD-induced neurodegeneration. The aim of the study was to characterize these properties from different perspectives: (i) using the Kullback-Leibler divergence (KLD), a measure of non-stationarity derived from the continuous wavelet transform; and (ii) using the entropy of the recurrence point density ([Formula: see text]) and the median of the recurrence point density ([Formula: see text]), two novel metrics based on recurrence quantification analysis.
APPROACH: KLD, [Formula: see text] and [Formula: see text] were computed for 49 patients with dementia due to AD, 66 patients with MCI due to AD and 43 cognitively healthy controls from 60 s electroencephalographic (EEG) recordings with a 10 s sliding window with no overlap. Afterwards, we tested whether the measures reflected alterations to normal neuronal activity induced by MCI and AD.
MAIN RESULTS: Our results showed that frequency-dependent alterations to normal dynamic behavior can be found in patients with MCI and AD, both in non-stationarity and recurrence structure. Patients with MCI showed signs of patterns of abnormal state recurrence in the theta (4-8 Hz) and beta (13-30 Hz) frequency bands that became more marked in AD. Moreover, abnormal non-stationarity patterns were found in MCI patients, but not in patients with AD in delta (1-4 Hz), alpha (8-13 Hz), and gamma (30-70 Hz).
SIGNIFICANCE: The alterations in normal levels of non-stationarity in patients with MCI suggest an initial increase in cortical activity during the development of AD. This increase could possibly be due to an impairment in neuronal inhibition that is not present during later stages. MCI and AD induce alterations to the recurrence structure of cortical activity, suggesting that normal state switching during rest may be affected by these pathologies.
Disciplines :
Neurology
Author, co-author :
Nunez Novo, Pablo ; Biomedical Engineering Group, University of Valladolid, Valladolid, Spain. Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina CIBER-BBN, Valladolid, Spain. Author to whom any correspondence should be addressed
Poza, Jesús ; Biomedical Engineering Group, University of Valladolid, Valladolid, Spain ; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina CIBER-BBN, Valladolid, Spain ; IMUVA, Instituto de Investigación en Matemáticas, University of Valladolid, Valladolid, Spain
Gómez, Carlos ; Biomedical Engineering Group, University of Valladolid, Valladolid, Spain ; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina CIBER-BBN, Valladolid, Spain
Barroso-García, Verónica ; Biomedical Engineering Group, University of Valladolid, Valladolid, Spain ; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina CIBER-BBN, Valladolid, Spain
Maturana-Candelas, Aarón ; Biomedical Engineering Group, University of Valladolid, Valladolid, Spain ; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina CIBER-BBN, Valladolid, Spain
Tola-Arribas, Miguel A ; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina CIBER-BBN, Valladolid, Spain ; Department of Neurology, Río Hortega University Hospital, Valladolid, Spain
Cano, Mónica; Department of Clinical Neurophysiology, Río Hortega University Hospital, Valladolid, Spain
Hornero, Roberto ; Biomedical Engineering Group, University of Valladolid, Valladolid, Spain ; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina CIBER-BBN, Valladolid, Spain ; IMUVA, Instituto de Investigación en Matemáticas, University of Valladolid, Valladolid, Spain
Language :
English
Title :
Characterization of the dynamic behavior of neural activity in Alzheimer's disease: exploring the non-stationarity and recurrence structure of EEG resting-state activity.
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Bibliography
Babiloni C, Lizio R, Marzano N, Capotosto P, Soricelli A, Triggiani A I, Cordone S, Gesualdo L and Del Percio C 2015 Brain neural synchronization and functional coupling in Alzheimer's disease as revealed by resting state EEG rhythms Int. J. Psychophysiol. 103 88-102
Tognoli E and Kelso J A S 2014 The metastable brain Neuron 81 35-48
Michel C M and Koenig T 2018 EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: a review NeuroImage 180 577-93
Dauwels J, Vialatte F and Cichocki A 2010 Diagnosis of Alzheimer's disease from EEG signals: Where are we standing? Curr. Alzheimer Res. 7 487-505
Petersen R C 2004 Mild cognitive impairment as a clinical entity and treatment target Arch. Neurol. 62 1160-3
Poza J, Gómez C, García M, Tola-Arribas M A, Carreres A, Cano M and Hornero R 2017 Spatio-temporal fluctuations of neural dynamics in mild cognitive impairment and Alzheimer's disease Curr. Alzheimer Res. 14 924-36
Poza J, Gómez C, García M, Corralejo R, Fernández A and Hornero R 2014 Analysis of neural dynamics in mild cognitive impairment and Alzheimer's disease using wavelet turbulence J. Neural Eng. 11 026010
Gómez C, Juan-Cruz C, Poza J, Ruiz-Gómez S J, Gomez-Pilar J, Núñez P, García M, Fernández A and Hornero R 2018 Alterations of effective connectivity patterns in mild cognitive impairment: an MEG study J. Alzheimer's Dis. 65 843-54
O'Neill G C, Tewarie P, Vidaurre D, Liuzzi L, Woolrich M W and Brookes M J 2018 Dynamics of large-scale electrophysiological networks: a technical review NeuroImage 180 559-76
Zbilut J P and Webber C L 2006 Recurrence quantification analysis Wiley Encyclopedia of Biomedical Engineering (Hoboken, NJ: Wiley)
Blanco S, Garcia H, Quiroga R Q, Romanelli L and Rosso O A 1995 Stationarity of the EEG series IEEE Eng. Med. Biol. Mag. 14 395-9
Rosso O A, Martin M T, Figliola A, Keller K and Plastino A 2006 EEG analysis using wavelet-based information tools J. Neurosci. Methods 153 163-82
Núñez P, Poza J, Gómez C, Rodríguez-González V, Ruiz-Gómez S J, Maturana-Candelas A and Hornero R 2019 Characterizing non-stationarity in Alzheimer's disease and mild cognitive impairment by means of Kullback-Leibler divergence Biosystems and Biorobotics (Berlin: Springer) pp 574-8
Núñez P, Poza J, Gómez C, Rodríguez-González V, Ruiz-Gómez S, Maturana-Candelas A and Hornero R 2019 Characterization of EEG resting-state activity in Alzheimer's disease by means of recurrence plot analyses Proc. of the 41st Annual Int. Conf. of the IEEE Eng. Med. Biol. Soc. Conf. pp 5786-9
Marwan N, Carmen Romano M, Thiel M and Kurths J 2007 Recurrence plots for the analysis of complex systems Phys. Rep. 438 237-329
Núñez P, Poza J, Bachiller A, Gomez-Pilar J, Lubeiro A, Molina V and Hornero R 2017 Exploring non-stationarity patterns in schizophrenia: neural reorganization abnormalities in the alpha band J. Neural Eng. 14 046001
Tong S, Li Z, Zhu Y and Thakor N V 2007 Describing the nonstationarity level of neurological signals based on quantifications of time-frequency representation IEEE Trans. Biomed. Eng. 54 1780-5
McKhann G et al 2011 The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease Alzheimers Dementia 7 263-9
Albert M S et al 2011 The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease Alzheimer's Dementia 7 270-9
Núñez P, Poza J, Gomez C, Rodríguez-González V, Hillebrand A, Tola-Arribas M Á, Cano M and Hornero R 2019 Characterizing the fluctuations of dynamic resting-state electrophysiological functional connectivity: reduced neuronal coupling variability in mild cognitive impairment and dementia due to Alzheimer's disease J. Neural Eng. 16 056030
Roach B J and Mathalon D H 2008 Event-related EEG time-frequency analysis: an overview of measures and an analysis of early gamma band phase locking in schizophrenia Schizophrenia Bull. 34 907-26
Rioul O and Vetterli M 1991 Wavelets and signal processing IEEE Signal Process. Mag. 8 14-38
Tallon-Baudry C, Bertrand O, Delpuech C and Pernier J 1996 Stimulus specificity of phase-locked and non-phase-locked 40 Hz visual responses in human J. Neurosci. 16 4240-9
Samar V J, Bopardikar A, Rao R and Swartz K 1999 Wavelet analysis of neuroelectric waveforms: a conceptual tutorial Brain Lang. 66 7-60
Bachiller A, Poza J, Gómez C, Molina V, Suazo V and Hornero R 2015 A comparative study of event-related coupling patterns during an auditory oddball task in schizophrenia J. Neural Eng. 12 016007
Torrence C and Compo G P 1998 A practical guide to wavelet analysis Bull. Am. Meteorol. Soc. 79 61-78
Webber C and Zbilut J 2005 Recurrence quantification analysis of nonlinear dynamical systems Tutorials in Contemporary Nonlinear Methods for the Behavioral Sciences Web Book (Alexandria, VA: National Science Foundation) pp 26-94
Martín-González S, Navarro-Mesa J L, Juliá-Serdá G, Ramírez-Ávila G M and Ravelo-García A G 2018 Improving the understanding of sleep apnea characterization using recurrence quantification analysis by defining overall acceptable values for the dimensionality of the system, the delay, and the distance threshold PLoS One 13 e0194462
Schinkel S, Dimigen O and Marwan N 2008 Selection of recurrence threshold for signal detection Eur. Phys. J.: Spec. Top. 164 45-53
Ouyang G, Li X, Dang C and Richards D A 2008 Using recurrence plot for determinism analysis of EEG recordings in genetic absence epilepsy rats Clin. Neurophysiol. 119 1747-55
Heunis T, Aldrich C, Peters J M, Jeste S S, Sahin M, Scheffer C and de Vries P J 2018 Recurrence quantification analysis of resting state EEG signals in autism spectrum disorder - mdash;a systematic methodological exploration of technical and demographic confounders in the search for biomarkers BMC Med. 16 1-17
Marwan N, Wessel N, Meyerfeldt U, Schirdewan A and Kurths J 2002 Recurrence-plot-based measures of complexity and their application to heart-rate-variability data Phys. Rev. E 66 1-8
Eckmann J-P, Kamphorst S O and Ruelle D 1987 Recurrence plots of dynamical systems Eur. Lett. 4 973-7
Freedman D and Diaconis P 1981 On the histogram as a density estimator: L2 theory Z. Wahrscheinlichkeitstheor. Verwandte Geb. 57 453-76
Benjamini Y and Hochberg Y 1995 Controlling the false discovery rate: a practical and powerful approach to multiple testing J. R. Stat. Soc. 57 289-300
Dauwels J, Srinivasan K, Ramasubba Reddy M, Musha T, Vialatte F-B, Latchoumane C, Jeong J and Cichocki A 2011 Slowing and loss of complexity in Alzheimer's EEG: two sides of the same coin? Int. J. Alzheimer's Dis. 2011 1-10
Jeong J 2004 EEG dynamics in patients with Alzheimer's disease Clin. Neurophysiol. 115 1490-505
Maestú F, Yubero R, Moratti S, Campo P, Gil-Gregorio P, Paul N, Solesio E, del Pozo F and Nevado A 2011 Brain activity patterns in stable and progressive mild cognitive impairment during working memory as evidenced by magnetoencephalography J. Clin. Neurophysiol. 28 202-9
Gaubert S et al 2019 EEG evidence of compensatory mechanisms in preclinical Alzheimer's disease Brain 142 1497-500
de Haan W, Mott K, van Straaten E C, Scheltens P and Stam C J 2012 Activity dependent degeneration explains Hub vulnerability in Alzheimer's disease PLoS Comput. Biol. 8 e1002582
Palop J J and Mucke L 2010 Amyloid-β - mdash;induced neuronal dysfunction in Alzheimer's disease: from synapses toward neural networks Nat. Neurosci. 13 812-8
Haense C, Kalbe E, Herholz K, Hohmann C, Neumaier B, Krais R and Heiss W-D 2012 Cholinergic system function and cognition in mild cognitive impairment Neurobiol. Aging 33 867-77
Quiroz Y T, Budson A E, Celone K, Ruiz A, Newmark R, Castrillón G, Lopera F and Stern C E 2010 Hippocampal hyperactivation in presymptomatic familial Alzheimer's disease Ann. Neurol. 68 865-75
Spitzer B and Haegens S 2017 Beyond the status quo: a role for beta oscillations in endogenous content (Re)activation eneuro 4 ENEURO.0170-17.2017
Stam C J, van der Made Y, Pijnenburg Y A L and Scheltens P 2003 EEG synchronization in mild cognitive impairment and Alzheimer's disease Acta Neurol. Scand. 108 90-6
Babiloni C et al 2018 Abnormalities of resting state cortical EEG rhythms in subjects with mild cognitive impairment due to Alzheimer's and Lewy body diseases J. Alzheimer's Dis. 62 247-68
Herrmann C S and Demiralp T 2005 Human EEG gamma oscillations in neuropsychiatric disorders Clin. Neurophysiol. 116 2719-33
Stam C J, Van Cappellen van Walsum A M, Pijnenburg Y A, 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. 19 562-74
Gomez C, Stam C, Hornero R, Fernandez A and Maestu F 2009 Disturbed beta band functional connectivity in patients with mild cognitive impairment: an MEG study IEEE Trans. Biomed. Eng. 56 1683-90
Khanna A, Pascual-Leone A, Michel C M and Farzan F 2015 Microstates in resting-state EEG: current status and future directions Neurosci. Biobehav. Rev. 49 105-13
Zbilut J P, Zaldivar-Comenges J-M and Strozzi F 2002 Recurrence quantification based Liapunov exponents for monitoring divergence in experimental data Phys. Lett. A 297 173-81
Stephan B C M, Hunter S, Harris D, Llewellyn D J, Siervo M, Matthews F E and Brayne C 2012 The neuropathological profile of mild cognitive impairment (MCI): a systematic review Mol. Psychiatry 17 1056-76
Uhlhaas P J and Singer W 2006 Neural synchrony in brain disorders: relevance for cognitive dysfunctions and pathophysiology Neuron 52 155-68
Sheline Y I and Raichle M E 2013 Resting state functional connectivity in preclinical Alzheimer's disease Biol. Psychiatry 74 340-7
Zbilut J P, Thomasson N and Webber C L 2002 Recurrence quantification analysis as a tool for nonlinear exploration of nonstationary cardiac signals Med. Eng. Phys. 24 53-60
Tewarie P, Liuzzi L, O'Neill G C, Quinn A J, Griffa A, Woolrich M W, Stam C J, Hillebrand A and Brookes M J 2019 Tracking dynamic brain networks using high temporal resolution MEG measures of functional connectivity NeuroImage 200 38-50
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