Multivariate multi-scale weighted permutation entropy analysis of EEG complexity for Alzheimer’s disease

Abásolo D, Hornero R, Espino P, Poza J, Sánchez CI, de la Rosa R (2005) Analysis of regularity in the EEG background activity of Alzheimer’s disease patients with approximate entropy. Clin Neurophysiol 116:1826–1834 Abásolo D, Hornero R, Espino P, Alvarez D, Poza J (2006) Entropy analysis of the EEG background activity in Alzheimer’s disease patients. Physiol Meas 27:241–253 Abásolo D, Escudero J, Hornero R, Gómez C, Espino P (2008) Approximate entropy and auto mutual information analysis of the electroencephalogram in Alzheimer’s disease patients. Med Biol Eng Comput 46:1019–1028 Ahmed MU, Mandic DP (2012) Multivariate multiscale entropy analysis. IEEE Signal Process Lett 19:91–94 Baker M, Akrofi K, Schiffer R, O’Boyle MW (2008) EEG Patterns in Mild cognitive impairment (MCI) patients. Open Neuroimag J 2:52–55 Bandt C, Pompe B (2002) Permutation entropy: a natural complexity measure for time series. Phys Rev Lett 88:174102 Başar E, Güntekin B, Atagün I, Gölbaşı BT, Tülay E, Özerdem A (2012) Brain’s alpha activity is highly reduced in euthymic bipolar disorder patients. Cogn Neurodyn 6:11–20 Bjørk MH, Stovner LJ, Engstrøm M, Stjern M, Hagen K, Sand T (2009) Interictal quantitative EEG in migraine: a blinded controlled study. J Headache Pain 10:331–339 Blennow K, de Leon MJ, Zetterberg H (2006) Alzheimer's disease. Lancet 368:387–403 Bruzzo AA, Gesierich B, Santi M, Tassinari C, Birbaumer N, Rubboli G (2008) Permutation entropy to detect vigilance changes and preictal states from scalp EEG in epileptic patients: a preliminary study. Neurol Sci 29:3–9 Cao Y, Tung W, Gao JB, Protopopescu VA, Hively LM (2004) Detecting dynamical changes in time series using the permutation entropy. Phys Rev E 70:046217 Cao YZ, Cai LH, Wang J, Wang RF, Yu HT, Cao YB, Liu J (2015) Characterization of complexity in the electroencephalograph activity of Alzheimer’s disease based on fuzzy entropy. Chaos 25:083116 Costa M, Goldberger AL, Peng CK (2002) Multiscale entropy analysis of complex physiologic time series. Phys Rev Lett 89:068102 Czigler B, Csikós D, Hidasi Z, Anna Gaál Z, Csibri E, Kiss E, Salacz P, Molnár M (2008) Quantitative EEG in early Alzheimer’s disease patients—power spectrum and complexity features. Int J Psychophysiol 68:75–80 Dauwels J, Vialatte F, Cichocki A (2010a) Diagnosis of Alzheimer’s disease from EEG Signals: where are we standing? Curr Alzheimer Res 7:487–505 Dauwels J, Vialatte F, Musha T, Cichocki A (2010b) A comparative study of synchrony measures for the early diagnosis of Alzheimer’s disease based on EEG. Neuroimage 49:668–693 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 Alzheimers Dis 2011:53962. doi:10.4061/2011/539621 Deng B, Liang L, Li SN, Wang RF, Yu HT, Wang J, Wei XL (2015) Complexity extraction of electroencephalograms in Alzheimer’s disease with weighted-permutation entropy. Chaos 25:043105 Escudero J, Abásolo D, Hornero R, Espino P, López M (2006) Analysis of electroencephalograms in Alzheimer’s disease patients with multiscale entropy. Physiol Meas 27:1091–1106 Fadlallah B, Chen B, Keil A, Príncipe J (2013) Weighted-permutation entropy: a complexity measure for time series incorporating amplitude information. Phys Rev E 87:022911 Hemmati S, Ahmadlou M, Gharib M, Vameghi R, Sajedi F (2013) Down syndrome’s brain dynamics: analysis of fractality in resting state. Cogn Neurodyn 7:333–340 Hutcheon B, Yarom Y (2000) Resonance, oscillation and the intrinsic frequency preferences of neurons. Trends Neurosci 23:216–222 Jelles B, Scheltens P, van der Flier WM, Jonkman EJ, da Silva FH, Stam CJ (2008) Global dynamical analysis of the EEG in Alzheimer’s disease: frequency-specific changes of functional interactions. Clin Neurophysiol 119:837–841 Keller K, Wittfeld K (2004) Distances of time series components by means of symbolic dynamics. Int J Bifurcat Chaos 14:693–703 Labate D, La Foresta F, Morabito G, Palamara I, Morabito FC (2013) Entropic measures of EEG complexity in Alzheimer’s disease through a multivariate multiscale approach. IEEE Sens J 13:3284–3292 Laske C, Sohrabi HR, Frost SM et al (2015) Innovative diagnostic tools for early detection of Alzheimer’s disease. Alzheimers Dement 11:561–578 Li X, Ouyang G, Richards DA (2007) Predictability analysis of absence seizures with permutation entropy. Epilepsy Res 77:70–74 Li X, Cui S, Voss LJ (2008) Using permutation entropy to measure the electroencephalographic effect of sevoflurane. Anesthesiology 109:448–456 Liu X et al (2016) Multiple characteristics analysis of Alzheimer’s electroencephalogram by power spectral density and Lempel–Ziv complexity. Cogn Neurodyn 10:121–133 Lorenz EN (1963) Deterministic nonperiodic flow. J Atmos Sci 20:130–141 Mattson MP (2004) Pathways towards and away from Alzheimer’s disease. Nature 430:631–639 Morabito FC, Labate D, La Foresta F, Bramanti A, Morabito G, Palamara I (2012) Multivariate multi-scale permutation entropy for complexity analysis of Alzheimer’s disease EEG. Entropy 14:1186–1202 Moretti DV, Fracassi C, Pievani M, Geroldi C, Binetti G, Zanetti O, Sosta K, Rossini PM, Frisoni GB (2009) Increase of theta/gamma ratio is associated with memory impairment. Clin Neurophysiol 120:295–303 Olofsen E, Sleigh JW, Dahan A (2008) Permutation entropy of the electroencephalogram: a measure of an aesthetic drug effect. Br J Anaesth 101:810–821 Ouyang GX, Li XL, Dang CY, Richards DA (2009) Deterministic dynamics of neural activity during absence seizures in rats. Phys Rev E 79:041146 Ouyang GX, Dang CY, Richards DA, Li XL (2010) Ordinal pattern based similarity analysis for EEG recordings. Clin Neurophysiol 121:694–703 Park JH, Kim S, Kim CH, Cichocki A, Kim K (2007) Multiscale entropy analysis of EEG from patients under different pathological conditions. Fractals 15:399–404 Schinkel S, Marwan N, Kurths J (2007) Order patterns recurrence plots in the analysis of ERP data. Cogn Neurodyn 1:317–325 Schinkel S, Marwan N, Kurths J (2009) Brain signal analysis based on recurrences. J Physiol Paris 103:315–323 Schnitzler A, Gross J (2005) Normal and pathological oscillatory communication in the brain. Nat Rev Neurosci 6:285–296 Takahashi T (2013) Complexity of spontaneous brain activity in mental disorders. Prog Neuropsychopharmacol Biol Psychiatry 45:258–266 Talebi N, Nasrabadi AM, Curran T (2012) Investigation of changes in EEG complexity during memory retrieval: the effect of midazolam. Cogn Neurodyn 6:537–546 Timothy LT, Krishna BM, Menon MK, Nair U (2014) Permutation entropy analysis of EEG of mild cognitive impairment patients during memory activation task. Fractals, wavelets, and their applications. Springer, Berlin, pp 395–406 van der Hiele K, Vein AA, Reijntjes RH, Westendorp RG, Bollen EL, van Buchem MA, van Dijk JG, Middelkoop HA (2007) EEG correlates in the spectrum of cognitive decline. Clin Neurophysiol 118:1931–1939 Von Stein A, Sarnthein J (2000) Different frequencies for different scales of cortical integration: from local gamma to long range alpha/theta synchronization. Int J Psychophysiol 38:301–313 Wang RF, Wang J, Yu HT, Wei XL, Yang C, Deng B (2015) Power spectral density and coherence analysis of Alzheimer’s EEG. Cogn Neurodyn 9:291–304 Woon WL, Cichocki A, Vialatte F, Musha T (2007) Techniques for early detection of Alzheimer’s disease using spontaneous EEG recordings. Physiol Meas 28:335–347 Yang AC et al (2013) Cognitive and neuropsychiatric correlates of EEG dynamic complexity in patients with Alzheimer’s disease. Prog Neuropsychopharmacol Biol Psychiatry 47:52–61 Yi GS et al (2014) Ordinal pattern based complexity analysis for EEG activity evoked by manual acupuncture in healthy subjects. Int J Bifurcat Chaos 24:1450018