Dynamic characteristics of absence EEG recordings with multiscale permutation entropy analysis

Epilepsy Research

Volumn 104, Issue 3, 2013, Pages 246-252

  Ouyang, Gaoxiang ^a   Li, Jing ^b,d   Liu, Xianzeng ^c   Li, Xiaoli ^a,e  

^a YANSHAN UNIVERSITY   (China)

^b UNIVERSITY OF SHEFFIELD   (United Kingdom)

^c PEKING UNIVERSITY PEOPLE S HOSPITAL   (China)

^d NANCHANG UNIVERSITY   (China)

^e BEIJING NORMAL UNIVERSITY   (China)

Author keywords

Absence seizure; Classification; EEG; Multiscale permutation entropy

Indexed keywords

ABSENCE; ADOLESCENT; ADULT; ARTICLE; CHILD; CLINICAL ARTICLE; CONTROLLED STUDY; DISCRIMINANT ANALYSIS; ELECTROENCEPHALOGRAM; ENTROPY; FEMALE; HUMAN; MALE; MULTISCALE PERMUTATION ENTROPY; PRESCHOOL CHILD; PRIORITY JOURNAL; SCHOOL CHILD; SEIZURE; SIGNAL PROCESSING; SPIKE WAVE; STATISTICAL ANALYSIS;

ADOLESCENT; ADULT; ALGORITHMS; BRAIN; CHILD; ELECTROENCEPHALOGRAPHY; ENTROPY; EPILEPSY; EPILEPSY, ABSENCE; FEMALE; HUMANS; MALE; YOUNG ADULT;

EID: 84877000317     PISSN: 09201211     EISSN: 18726844     Source Type: Journal    
DOI: 10.1016/j.eplepsyres.2012.11.003     Document Type: Article

References (45)

1. Amor F., Baillet S., Navarro V., Adam C., Martinerie J., Quyen Mle V. Cortical local and long-range synchronization interplay in human absence seizure initiation. Neuroimage 2009, 45:950-962.
2. Bai X., Vestal M., Berman R., Negishi M., Spann M., Vega C., Desalvo M., Novotny E., Constable R., Blumenfeld H. Dynamic timecourse of typical childhood absence seizures: EEG, behavior and fMRI. J. Neurosci. 2010, 30:5884-5893.
3. Bandt C., Pompe B. Permutation entropy: a natural complexity measure for time series. Phys. Rev. Lett. 2002, 88:174102.
4. Bandt C., Keller G., Pompe B. Entropy of interval maps via permutations. Nonlinearity 2002, 15:1595-1602.
5. Burioka N., Miyata M., Cornelissen G., Halberg F., Takeshima T., Kaplan D.T., Suyama H., Endo M., Maegaki Y., Nomura T., Tomita Y., Nakashima K., Shimizu E. Approximate entropy in the electroencephalogram during wake and sleep. Clin. EEG Neurosci. 2005, 36:21-24.
6. Buzsaki G. Rhythms of the Brain 2006, Oxford University Press, Oxford.
7. Catarino A., Churches O., Baron-Cohen S., Andrade A., Ring H. Atypical EEG complexity in autism spectrum conditions: a multiscale entropy analysis. Clin. Neurophysiol. 2011, 122:2375-2383.
8. Costa M., Goldberger A., Peng C. Multiscale entropy analysis of physiologic time series. Phys. Rev. Lett. 2002, 89:062102.
9. Costa M., Goldberger A., Peng C. Multiscale entropy analysis of biological signal. Phys. Rev. E 2005, 71:021906.
10. Crunelli V., Cope D.W., Terry J.R. Transition to absence seizures and the role of GABA(A) receptors. Epilepsy Res. 2011, 97:283-289.
11. Gorji A., Mittag C., Shahabi P., Seidenbecher T., Pape H.C. Seizure-related activity of intralaminar thalamic neurons in a genetic model of absence epilepsy. Neurobiol. Dis. 2011, 43:266-274.
12. Gupta D., Ossenblok P., van Luijtelaar G. Space-time network connectivity and cortical activations preceding spike wave discharges in human absence epilepsy: a MEG study. Med. Biol. Eng. Comput. 2011, 49:555-565.
13. Hogg R.V., Ledolter J. Engineering Statistics 1987, MacMillan Publishing Company.
14. Killory B., Bai X., Negishi M., Vega C., Spann M., Vestal M., Guo J., Berman R., Danielson N., Trejo J., Shisler D., Novotny E., Constable R., Blumenfeld H. Impaired attention and network connectivity in childhood absence epilepsy. Neuroimage 2011, 56:2209-2217.
15. Kramer M.A., Eden U.T., Kolaczyk E.D., Zepeda R., Eskandar E.N., Cash S.S. Coalescence and fragmentation of cortical networks during focal seizures. J. Neurosci. 2010, 30:10076-10085.
16. Li X., Ouyang G., Richards D. Predictability analysis of absence seizures with permutation entropy. Epilepsy Res. 2007, 77:70-74.
17. Li X., Cui S., Voss L. Using permutation entropy to measure the electroencephalographic effects of sevoflurane. Anesthesiology 2008, 109:448-456.
18. Li D., Li X., Liang Z., Voss L., Sleigh J. Multiscale permutation entropy analysis of EEG recordings during sevoflurane anesthesia. J Neural. Eng. 2010, 7:046010.
19. Meeren H., Pijn J., Van Luijtelaar E., Coenen A., Lopes da Silva F. Cortical focus drives widespread corticothalamic networks during spontaneous absence seizures in rats. J. Neurosci. 2002, 22:1480-1495.
20. Mizuno T., Takahashi T., Cho R., Kikuchi M., Murata T., Takahashi K., Wada Y. Assessment of EEG dynamical complexity in Alzheimer's disease using multiscale entropy. Clin. Neurophysiol. 2010, 121:1438-1446.
21. Mormann F., Elger E., Lehnertz K. Seizure anticipation: from algorithms to clinical practice. Curr. Opin. Neurol. 2006, 19:187-193.
22. Mormann F., Andrzejak R., Elger E., Lehnertz K. Seizure prediction: the long and winding road. Brain 2007, 130:314-333.
23. Neymotin S.A., Lee H., Fenton A.A., Lytton W.W. Interictal EEG discoordination in a rat seizure model. J. Clin. Neurophysiol. 2010, 27:438-444.
24. Nicolaou N., Georgiou J. The use of permutation entropy to characterize sleep electroencephalograms. Clin. EEG Neurosci. 2011, 42:24-28.
25. Nicolaou N., Georgiou J. Detection of epileptic electroencephalogram based on permutation entropy and support vector machines. Expert Syst. Appl. 2012, 39:202-209.
26. Olofsen E., Sleigh J.W., Dahan A. Permutation entropy of the electroencephalogram: a measure of anaesthetic drug effect. Br. J. Anaesth. 2008, 101:810-821.
27. Ouyang G., Li X., Dang C., Richards D. Using recurrence plot for determinism analysis of EEG recordings in genetic absence epilepsy rats. Clin. Neurophysiol. 2008, 119:1747-1755.
28. Ouyang G., Dang C., Li X. Multiscale entropy analysis of EEG recordings in epileptic rats. Biomed. Eng.: Appl. Basis Commun. 2009, 21:169-176.
29. Ouyang G., Dang C., Richards D.A., Li X. Ordinal pattern based similarity analysis for EEG recordings. Clin. Neurophysiol. 2010, 121:694-703.
30. Park J.H., Kim S., Kim C.H., Cichocki A., Kim K.S. Multiscale entropy analysis of EEG from patients under different pathological conditions. Fractals 2007, 15:399-404.
31. Polack P., Guillemain I., Hu E., Deransart C., Depaulis A., Charpier S. Deep layer somatosensory cortical neurons initiate spike-and-wave discharges in a genetic model of absence seizures. J. Neurosci. 2007, 27:6590-6599.
32. Richman J., Moorman J. Physiological time series analysis using approximate entropy and sample entropy. Am. J. Physiol. 2000, 278:2039-2049.
33. Rosso O., Larrondo H.A., Martin M.T., Plastino A., Fuentes M.A. Distinguishing noise from chaos. Phys. Rev. Lett. 2007, 99:154102.
34. Rosso O., Mendes A., Rostas J., Hunter M., Moscato P. Distinguishing childhood absence epilepsy patients from controls by the analysis of their background brain electrical activity. J. Neurosci. Methods 2009, 177:461-468.
35. Rosso O., Mendes A., Berretta R., Rostas J., Hunter M., Moscato P. Distinguishing childhood absence epilepsy patients from controls by the analysis of their background brain electrical activity (II): a combinatorial optimization approach for electrode selection. J. Neurosci. Methods 2009, 181:257-267.
36. Sadleir L.G., Farrell K., Smith S., Connolly M.B., Scheffer I.E. Electroclinical features of absence seizures in sleep. Epilepsy Res. 2011, 93:216-220.
37. Schindler K., Leung H., Elger C.E., Lehnertz K. Assessing seizure dynamics by analysing the correlation structure of multichannel intracranial EEG. Brain 2007, 130:65-77.
38. Sitnikova E. Thalamo-cortical mechanisms of sleep spindles and spike-wave discharges in rat model of absence epilepsy (a review). Epilepsy Res. 2010, 89:17-26.
39. Sitnikova E., van Luijtelaar G. Electroencephalographic precursors of spike-wave discharges in a genetic rat model of absence epilepsy: power spectrum and coherence EEG analyses. Epilepsy Res. 2009, 84:159-171.
40. Stacey W., Litt B. Technology insight: neuroengineering and epilepsy-designing devices for seizure control. Nat. Clin. Pract. Neurol. 2008, 4:190-201.
41. Stacey W., Le Van Quyen M., Mormann F., Schulze-Bonhage A. What is the present-day EEG evidence for a preictal state?. Epilepsy Res. 2011, 97:243-251.
42. Stam C. Nonlinear dynamical analysis of EEG and MEG: review of an emerging field. Clin. Neurophysiol. 2005, 116:2266-2301.
43. van Luijtelaar G., Hramov A., Sitnikova E., Koronovskii A. Spike-wave discharges in WAG/Rij rats are preceded by delta and theta precursor activity in cortex and thalamus. Clin. Neurophysiol. 2011, 122:687-695.
44. Webb A.R. Statistical Pattern Recognition 2006, Wiley, Chichester, United Kingdom. 2nd ed.
45. Yuan Q., Zhou W., Li S., Cai D. Epileptic EEG classification based on extreme learning machine and nonlinear features. Epilepsy Res. 2011, 96:29-38.