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Power spectral density and coherence analysis of Alzheimer’s EEG

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Abstract

In this paper, we investigate the abnormalities of electroencephalograph (EEG) signals in the Alzheimer’s disease (AD) by analyzing 16-scalp electrodes EEG signals and make a comparison with the normal controls. The power spectral density (PSD) which represents the power distribution of EEG series in the frequency domain is used to evaluate the abnormalities of AD brain. Spectrum analysis based on autoregressive Burg method shows that the relative PSD of AD group is increased in the theta frequency band while significantly reduced in the alpha2 frequency bands, particularly in parietal, temporal, and occipital areas. Furthermore, the coherence of two EEG series among different electrodes is analyzed in the alpha2 frequency band. It is demonstrated that the pair-wise coherence between different brain areas in AD group are remarkably decreased. Interestingly, this decrease of pair-wise electrodes is much more significant in inter-hemispheric areas than that in intra-hemispheric areas. Moreover, the linear cortico-cortical functional connectivity can be extracted based on coherence matrix, from which it is shown that the functional connections are obviously decreased, the same variation trend as relative PSD. In addition, we combine both features of the relative PSD and the normalized degree of functional network to discriminate AD patients from the normal controls by applying a support vector machine model in the alpha2 frequency band. It is indicated that the two groups can be clearly classified by the combined feature. Importantly, the accuracy of the classification is higher than that of any one feature. The obtained results show that analysis of PSD and coherence-based functional network can be taken as a potential comprehensive measure to distinguish AD patients from the normal, which may benefit our understanding of the disease.

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References

  • Abásolo D, Hornero R, Espino P (2005) Analysis of regularity in the EEG background activity of Alzheimer’s disease patients with approximate entropy. Clin Neurophysiol 116(8):1826–1834

    Article  PubMed  Google Scholar 

  • Adler G, Brassen S, Jajcevic A (2003) EEG coherence in Alzheimer’s dementia. J Neural Transm 110:1051–1058

    Article  CAS  PubMed  Google Scholar 

  • Akin M, Kiymik MK (2000) Application of periodogram and AR spectral analysis to EEG signals. J Med Syst 24:247–256

    Article  CAS  PubMed  Google Scholar 

  • Baker M, Akrofi K, Schiffer R, Michael W, Boyle O’ (2008) EEG patterns in mild cognitive impairment (MCI) patients. Open Neuroimag J 2:52–55

    Article  PubMed Central  PubMed  Google Scholar 

  • Bennys K, Rondouin G, Vergnes C, Touchon J (2001) Diagnostic value of quantitative EEG in Alzheimer’s disease. Clin Neurophysiol 31:153–160

    Article  CAS  Google Scholar 

  • Cabin RJ, Mitchell RJ (2000) To Bonferroni or not to Bonferroni: when and how are the questions. Bull Ecol Soc Am 81(3):246–248

    Google Scholar 

  • Chang C, Glover GH (2010) Time-frequency dynamics of resting-state brain connectivity measured with fMRI. Neuroimage 50:81–98

    Article  PubMed Central  PubMed  Google Scholar 

  • Chen Z, Cao J, Cao Y, Zhang Y, Gu F, Zhu G, Hong Z, Wang B, Cichocki A (2008) An empirical EEG analysis in brain death diagnosis for adults. Cogn Neurodyn 2(3):257–271

    Article  PubMed Central  PubMed  Google Scholar 

  • Claus JJ, Strijers RL, Jonkman EJ, Ongerboer de Visser BW, Jonker C, Walstra GJ, Scheltens P, van Gool WA (1999) The diagnostic value of electroencephalography in mild senile Alzheimer’ disease. Clin Neurophysiol 110:825–832

    Article  CAS  PubMed  Google Scholar 

  • Cook IA, Leuchter AF (1996) Synaptic dysfunction in Alzheimer’s disease: clinical assessment using quantitative EEG. Behav Brain Res 78:15–23

    Article  CAS  PubMed  Google Scholar 

  • Cooper JE (1995) On the publication of the diagnostic and statistical manual of mental disorders: fourth edition (DSM-IV). Br J Psychiatry 166:4–8

    Article  CAS  PubMed  Google Scholar 

  • 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

    Article  PubMed  Google Scholar 

  • 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

    Article  CAS  PubMed  Google Scholar 

  • 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

    Article  CAS  PubMed  Google Scholar 

  • 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 2011:539621

    PubMed Central  PubMed  Google Scholar 

  • Dauwels J, Srinivasan K, Reddy MR, Cichocki A (2013) Near-lossless multichannel EEG compression based on matrix and tensor decompositions. IEEE J Biomed Health Inform 17(3):708–714

    Article  PubMed  Google Scholar 

  • Delbeuck X, Van der Linden M, Collette F (2003) Alzheimer’s disease as a disconnection syndrome? Neuropsychol Rev 13:79–92

    Article  CAS  PubMed  Google Scholar 

  • Dringenberg HC (2000) Alzheimer’s disease: more than a ‘cholinergic disorder’—evidence that cholinergic–monoaminergic interactions contribute to EEG slowing and dementia. Behav Brain Res 115:235–249

    Article  CAS  PubMed  Google Scholar 

  • Elgendi M, Vialatte F, Cichocki A, Latchoumane C, Jeong J, Dauwels J (2011) Optimization of EEG frequency bands for improved diagnosis of Alzheimer disease. Conf Proc IEEE Eng Med Biol Soc 2011:6087–6091

    PubMed  Google Scholar 

  • Fernández A, Hornero R, Mayo A, Poza J, Gil-Gregorio P, Ortiz T (2006) MEG spectral profile in Alzheimer’s disease and mild cognitive impairment. Clin Neurophysiol 117:306–314

    Article  PubMed  Google Scholar 

  • Fraga FJ, Falk TH, Kanda PA, Anghinah R (2013) Characterizing Alzheimer’s disease severity via resting-awake EEG amplitude modulation analysis. PLoS ONE 8(8):e72240

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Freund RJ, Littell RC (1981) SAS for linear models: a guide to the ANOVA and GLM procedures. SAS Institute, Cary

    Google Scholar 

  • Gallego-Jutglà E, Elgendi M, Vialatte F, Solé-Casals J, Cichocki A, Latchoumane C, Jeong J, Dauwels J (2012) Diagnosis of Alzheimer’s disease from EEG by means of synchrony measures in optimized frequency bands. Conf Proc IEEE Eng Med Biol Soc 2012:4266–4270

    PubMed  Google Scholar 

  • Gerhard F, Pipa G, Lima B, Neuenschwander S, Gerstner W (2011) Extraction of network topology from multi-electrode recordings: Is there a small-world effect? Front Comput Neurosci 7:4–5

    Google Scholar 

  • Gianotti LR, Künig G, Lehmann D, Faber PL, Pascual-Marqui RD, Kochi K, Schreiter-Gasser U (2007) Correlation between disease severity and brain electric LORETA tomography in Alzheimer’s disease. Clin Neurophysiol 118:186–196

    Article  PubMed  Google Scholar 

  • Han CX, Wang J, Yi GS, Che YQ (2013) Investigation of EEG abnormalities in the early stage of Parkinson’s disease. Cogn Neurodyn 7(4):351–359

    Article  PubMed Central  PubMed  Google Scholar 

  • He Y, Chen Z, Evans A (2008) Structural insights into aberrant topological patterns of large-scale cortical networks in Alzheimer’s disease. J Neurosci 28:4756–4766

    Article  CAS  PubMed  Google Scholar 

  • He Y, Chen Z, Gong G, Evans A (2009) Neuronal networks in Alzheimer’s disease. Neurosci 15:333–350

  • Hidasi Z, Czigler B, Salacz P, Csibri E, Molnár M (2007) Changes of EEG spectra and coherence following performance in a cognitive task in Alzheimer’s disease. Int J Psychophysiol 65:252–260

    Article  PubMed  Google Scholar 

  • Hogan MJ, Swanwick GR, Kaiser J, Rowan M, Lawlor B (2003) Memory-related EEG power and coherence reductions in mild Alzheimer’s disease. Int J Psychophysiol 49:147–163

    Article  PubMed  Google Scholar 

  • Jelic V, Johansson SE, Almkvist O, Shigeta M, Julin P, Nordberg A, Winblad B, Wahlund LO (2000) Quantitative electroencephalography in mild cognitive impairment: longitudinal changes and possible prediction of Alzheimer’s disease. Neurobiol Aging 21:533–540

    Article  CAS  PubMed  Google Scholar 

  • Jelles B, van Birgelen JH, Slaets JP, Hekster RE, Jonkman EJ, Stam CJ (1999) Decrease of non-linear structure in the EEG of Alzheimer patients compared to healthy controls. Clin Neurophysiol 110(7):1159–1167

    Article  CAS  PubMed  Google Scholar 

  • 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

    Article  CAS  PubMed  Google Scholar 

  • Jeong J (2004) EEG dynamics in patients with Alzheimer’s disease. Clin Neurophysiol 115:1490–1505

    Article  PubMed  Google Scholar 

  • Jiang ZY (2005) Abnormal cortical functional connections in Alzheimer’s disease: analysis of inter- and intra-hemispheric EEG coherence. J Zhejiang Univ Sci B 6:259–264

    Article  PubMed Central  PubMed  Google Scholar 

  • Jolliffe IT (1986) Principal component analysis. Springer, New York

    Book  Google Scholar 

  • Joudaki A, Salehi Niloufar, Jalili mail Mahdi, Knyazeva MG (2012) EEG-based functional brain networks: Does the network size matter? PLoS ONE 7(4):e35673

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Kay SM (1988) Modern spectral estimation: theory and application. Prentice-Hall, New Jersey

    Google Scholar 

  • Knott V, Mohr E, Mahoney C, Ilivitsky V (2000) Electroencephalographic coherence in Alzheimer’s disease: comparisons with a control group and population norms. J Geriatr Psychiatry Neurol 13:1–8

    Article  CAS  PubMed  Google Scholar 

  • Koenig T, Prichep L, Dierks T, Hubl D, Wahlund LO, John ER, Jelic V (2005) Decreased EEG synchronization in Alzheimer’s disease and mild cognitive impairment. Neurobiol Aging 26:165–171

    Article  CAS  PubMed  Google Scholar 

  • Lizio R, Vecchio F, Frisoni GB, Ferri R, Rodriguez G, Babiloni C (2011) Electroencephalographic rhythms in Alzheimer’s disease. Int J Alzheimer’s Dis 2011:927573

    Google Scholar 

  • Locatelli T, Cursi M, Liberati D, Franceschi M, Comi G (1998) EEG coherence in Alzheimer’s disease. Electroencephalogr Clin Neurophysiol 106:229–237

    Article  CAS  PubMed  Google Scholar 

  • Mattson MP (2004) Pathways towards and away from Alzheimer’s disease. Nature 430:634–639

    Article  Google Scholar 

  • Molnár M, Csuhaj R, Horváth S, Vastagh I, Gaál ZA, Czigler B, Bálint A, Csikós D, Nagy Z (2006) Spectral and complexity features of the EEG changed by visual input in a case of subcortical stroke compared to healthy controls. Clin Neurophysiol 117(4):771–780

    Article  PubMed  Google Scholar 

  • 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

    Article  CAS  PubMed  Google Scholar 

  • Nunez PL, Wingeier BM, Silberstein RB (2001) Spatial-temporal structures of human alpha rhythms: theory, microcurrent sources, multiscale measurements, and global binding of local networks. Hum Brain Mapp 13:125–164

    Article  CAS  PubMed  Google Scholar 

  • Pei X, Wang J, Deng B, Wei X, Yu H (2014) WLPVG approach to the analysis of EEG-based functional brain network under manual acupuncture. Cogn Neurodyn 8(5):417–428

    Article  PubMed  Google Scholar 

  • Pereda E, Quiroga RQ, Bhattacharya J (2005) Nonlinear multivariate analysis of neurophysiological signals. Prog Neurobiol 77:1–37

    Article  PubMed  Google Scholar 

  • Ponomareva NV, Selesneva ND, Jarikov GA (2003) EEG alterations in subjects at high familial risk for Alzheimer’s disease. Neuropsychobiology 48:152–159

    Article  CAS  PubMed  Google Scholar 

  • Reid AT, Evans AC (2013) Structural networks in Alzheimer’s disease. Eur Neuropsychopharmacol 23(1):63–77

    Article  CAS  PubMed  Google Scholar 

  • Rossini PM, Del Percio C, Pasqualetti P, Cassetta E, Binetti G, Dal Forno G, Ferreri F, Frisoni G, Chiovenda P, Miniussi C, Parisi L, Tombini M, Vecchio F, Babiloni C (2006) Conversion from mild cognitive impairment to Alzheimer’s disease is predicted by sources and coherence of brain electroencephalography rhythms. Neuroscience 143:793–803

    Article  CAS  PubMed  Google Scholar 

  • Rubinov M, Sporns O (2010) Complex network measures of brain connectivity: uses and interpretations. Neuroimage 52(3):1059–1069

    Article  PubMed  Google Scholar 

  • Sankari Z, Adeli H, Adeli A (2011) Intrahemispheric, interhemispheric, and distal EEG coherence in Alzheimer’s disease. Clin Neurophysiol 122:897–906

    Article  PubMed  Google Scholar 

  • Sankari Z, Adeli H, Adeli A (2012) Wavelet coherence model for diagnosis of Alzheimer disease. Clin EEG Neurosci 43(4):268–278

    Article  PubMed  Google Scholar 

  • Sanz-Arigita EJ, Schoonheim MM, Damoiseaux JS, Rombouts SA, Maris E, Barkhof F, Scheltens P, Schreiter-Gasser U, Gasser T, Ziegler P (1994) Quantitative EEG analysis in early onset Alzheimer’s disease: correlations with severity, clinical characteristics, visual EEG and CCT. Electroencephalogr Clin Neurophysiol 90:267–272

    Article  Google Scholar 

  • Shalbaf R, Behnam H, Moghadam HJ (2014) Monitoring depth of anesthesia using combination of EEG measure and hemodynamic variables. Cogn Neurodyn. doi:10.1007/s11571-014-9295-z

  • Spiegel A, Tonner PH, Renna M (2006) Altered states of consciousness: processed EEG in mental disease. Best Pract Res Clin Anaesthesiol 20:57–67

    Article  PubMed  Google Scholar 

  • Stam CJ (2010) Loss of ‘small-world’ networks in Alzheimer’s disease: graph analysis of FMRI resting-state functional connectivity. PLoS ONE 5(11):e13788

    Article  PubMed Central  PubMed  Google Scholar 

  • Stam CJ, van der Made Y, Pijnenburg YAL, Scheltens Ph (2003) EEG synchronization in mild cognitive impairment and Alzheimer’s disease. Acta Neurol Scand 108:90–96

    Article  CAS  PubMed  Google Scholar 

  • Stam CJ, Montez T, Jones BF, Rombouts SARB, van der Made Y, Pijnenburg YAL, Scheltens P (2005) Disturbed fluctuations of resting state EEG synchronization in Alzheimer’s disease. Clin Neurophysiol 116:708–715

    Article  CAS  PubMed  Google Scholar 

  • Stam CJ, Jones BF, Manshanden I, Van Cappellen van Walsum AM, Montez T, Verbunt JP, de Munck JC, van Dijk BW, Berendse HW, Scheltens P (2006) Magnetoencephalographic evaluation of resting-state functional connectivity in Alzheimer’s disease. Neuroimage 32:1335–1344

    Article  CAS  PubMed  Google Scholar 

  • Stam CJ, Jones BF, Nolte G, Breakspear M, Scheltensc P (2007) Small-world networks and functional connectivity in Alzheimer’s disease. Cereb Cortex 17(1):92–99

    Article  CAS  PubMed  Google Scholar 

  • Supekar K, Menon V, Rubin D, Musen M, Greicius MD (2008) Network analysis of intrinsic functional brain connectivity in Alzheimer’s disease. PLoS Comput Biol 4:e1000100

    Article  PubMed Central  PubMed  Google Scholar 

  • Tijms BM, Wink AM, de Haan W, van der Flier WM, Stam CJ, Scheltens P, Barkhof F (2013) Alzheimer’s disease: connecting findings from graph theoretical studies of brain networks. Neurobiol Aging 34(8):2023–2036

    Article  PubMed  Google Scholar 

  • Uhlhaas P, Singer W (2006) Neural synchrony in brain disorders: relevance for cognitive dysfunctions and pathophysiology. Neuron 52:155–168

    Article  CAS  PubMed  Google Scholar 

  • 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

    Article  PubMed  Google Scholar 

  • van Deursen JA, Vuurman EF, Verhey FR, van Kranen-Mastenbroek VH, Riedel WJ (2008) Increased EEG gamma band activity in Alzheimer’s disease and mild cognitive impairment. J Neural Transm 115:1301–1311

    Article  PubMed Central  PubMed  Google Scholar 

  • Vecchio F, Babiloni C, Lizio R, Fallani FV, Blinowska K, Verrienti G, Frisoni G, Rossini PM (2003) Resting state cortical EEG rhythms in Alzheimer’s disease: toward EEG markers for clinical applications—a review. Suppl Clin Neurophysiol 62:223–236

    Article  Google Scholar 

  • Vemuri P, Jones DT, Jack CR Jr (2012) Resting state functional MRI in Alzheimer’s disease. Alzheimers Res Ther 4:2

    Article  PubMed Central  PubMed  Google Scholar 

  • Vialatte FB, Dauwels J, Musha T, Cichocki A (2012) Audio representations of multi-channel EEG: a new tool for diagnosis of brain disorders. Am J Neurodegener Dis 1(3):292–304

    PubMed Central  PubMed  Google Scholar 

  • Wang RF, Wang J, Yu H, Wei XL, Yang C, Deng B (2014) Decreased coherence and functional connectivity of electroencephalograph in Alzheimer’s disease. Chaos 24(3):033136

    Article  PubMed  Google Scholar 

  • Yi G, Wang J, Bian H, Han C, Deng B, Wei X, Li H (2013) Multi-scale order recurrence quantification analysis of EEG signals evoked by manual acupuncture in healthy subjects. Cogn Neurodyn 7(1):79–88

    Article  PubMed Central  PubMed  Google Scholar 

  • Zhang X, Lei X, Wu T, Jiang T (2014) A review of EEG and MEG for brainnetome research. Cogn Neurodyn 8(2):87–98

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Zhou Y, Wang K, Liu Y, Song M, Song SW, Jiang T (2010) Spontaneous brain activity observed with functional magnetic resonance imaging as a potential biomarker in neuropsychiatric disorders. Cogn Neurodyn 4(4):275–294

    Article  PubMed Central  PubMed  Google Scholar 

  • Zweig MH, Campbell G (1993) Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin Chem 39:561–577

    CAS  PubMed  Google Scholar 

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Acknowledgments

This work is supported by Tianjin Municipal Natural Science Foundation under Grants 12JCZDJC21100 and 13JCZDJC27900 and Tianjin Research Program of Application Foundation and Advanced Technology under Grants 14JCQNJC01200.

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Authors and Affiliations

  1. School of Electrical Engineering and Automation, Tianjin University, Tianjin, China

    Ruofan Wang, Jiang Wang, Haitao Yu, Xile Wei, Chen Yang & Bin Deng

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  1. Ruofan Wang
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  2. Jiang Wang
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  3. Haitao Yu
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Correspondence to Bin Deng.

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Wang, R., Wang, J., Yu, H. et al. Power spectral density and coherence analysis of Alzheimer’s EEG. Cogn Neurodyn 9, 291–304 (2015). https://doi.org/10.1007/s11571-014-9325-x

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