Approximate entropy analysis of event-related potentials in patients with early vascular dementia

Journal of Clinical Neurophysiology

Volumn 29, Issue 3, 2012, Pages 230-236

  Xu, Jin ^a   Sheng, Hengsong ^a   Lou, Wutao ^a   Zhao, Songzhen ^b  

^a XI'AN JIAOTONG UNIVERSITY   (China)

^b THE FIRST AFFILIATED HOSPITAL OF XI AN JIAOTONG UNIVERSITY   (China)

Author keywords

approximate entropy (ApEn); event related potential (ERP); P300; vascular dementia (VD)

Indexed keywords

ADULT; AGED; APPROXIMATE ENTROPY; ARTICLE; CLINICAL ARTICLE; CONTROLLED STUDY; ELECTROENCEPHALOGRAM; ENTROPY; EVENT RELATED POTENTIAL; FEMALE; HUMAN; LATENT PERIOD; MALE; MULTIINFARCT DEMENTIA; TASK PERFORMANCE; WAVEFORM;

AGED; BRAIN; DEMENTIA, VASCULAR; EARLY DIAGNOSIS; ELECTROENCEPHALOGRAPHY; ENTROPY; EVOKED POTENTIALS; FEMALE; HUMANS; MALE; PHOTIC STIMULATION; REACTION TIME; SIGNAL PROCESSING, COMPUTER-ASSISTED; YOUNG ADULT;

EID: 84862232622     PISSN: 07360258     EISSN: 15371603     Source Type: Journal    
DOI: 10.1097/WNP.0b013e318257ca9d     Document Type: Article

References (38)

1. Andino Gonzalez SL, Menendez Grave de Peralta R, Thut G, et al. Measuring the complexity of time series: An application to neurophysiological signals. Hum Brain Mapp 2000;11:46-57.
2. Donchin E. Is the P300 component a manifestation of context updating? Behav Brain Sci 1988;11:357-374.
3. Egerházi A, Glaub T, Balla P, et al. P300 in mild cognitive impairment and in dementia. Psychiatr Hung 2008;23:349-357.
4. Folstein MF, Folstein SE, McHugh PR. Mini-mental state. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12:189-198.
5. Gironell A, Garcia-Sanchez C, Estevez-Gonzalez A, et al. Usefulness of p300 in subjective memory complaints: A prospective study. J Clin Neurophysiol 2005;22:279-284.
6. Homan R, Herman J, Purdy P. Cerebral location of international 10-20 system electrode placement. Electroencephalogr Clin Neurophysiol 1987;66: 376-382.
7. Hughes CP, Berg L, Danziger WL, et al. A new clinical rating scale for the staging of dementia. Br J Psychiatry 1982;140:1225-1230.
8. Jausovec N, Jausovec K. Correlations between ERP parameters and intelligence: A reconsideration. Biol Psychol 2000;55:137-154.
9. Jeong J. EEG dynamics in patients with Alzheimer's disease. Clin Neurophysiol 2004;115:1490-1505.
10. Jeong J, Chae JH, Kim SY, Han SH. Nonlinear dynamic analysis of the EEG in patients with Alzheimer's disease and vascular dementia. J Clin Neurophysiol 2001;18:58-67.
11. Jeong J, Kim SY, Han SH. Non-linear dynamical analysis of the EEG in Alzheimer's disease with optimal embedding dimension. Electroencephalogr Clin Neurophysiol 1998;106:220-228.
12. Jorm AF. Cross-national comparisons of the occurrence of Alzheimer's and vascular dementia. Eur Arch Psychiatry Clin Neurosci 1991;240:218-222.
13. Juckel G, Clotz F, Frodl T, et al. Diagnostic usefulness of cognitive auditory event-related P300 subcomponents in patients with Alzheimers disease? J Clin Neurophysiol 2008;25:147-152.
14. Kantz H, Schreiber T. Nonlinear time series analysis. Cambridge, MA: Cambridge University Press, 1997.
15. Kase CS. Epidemiology of multi-infarct dementia. Alzheimer Dis Assoc Disord 1991;5:71-76.
16. Khedr EM, Hamed SA, El-Shereef HK, et-Al. Cognitive impairment after cerebrovascular stroke: Relationship to vascular risk factors. Neuropsychiatr Dis Treat 2009;5:103-116.
17. Kutas M, McCarthy G, Donchin E. Augmenting mental chronometry: The P300 as a measure of stimulus evaluation time. Science 1977;197:792-795.
18. Lawton MP, Brodie EM. Assessment of older people: Self maintaining and instrumental activity of daily living. J Gerontol 1969;9:179-186.
19. Lehnertz K, Elgar CE. Spatio-Temporal dynamics of the primary epileptogenic area in temporal lobe epilepsy characterized by neuronal complexity loss. Electroencephalogr Clin Neurophysiol 1995;95:108-117.
20. Michie PT. Cognitive deficits in psychopathology: Insight from event-related potentials. In: Johnson R Jr, Baron JC, eds. Handbook of neuropsychology. Amsterdam, The Netherlands: Elsevier, 1995:299-330.
21. Paci C, Gobbato R, Carboni T, et al. P300 auditory event-related potentials and neuropsychological study during donepezil treatment in vascular dementia. Neurol Sci 2006;26:435-437.
22. Picton TW. The P300 wave of the human event-related potential. J Clin Neurophysiol 1992;9:456-479.
23. Pincus SM. Approximate entropy: A complexity measure for biological time series data, bioengineering. In: Fox M, Epstein MA, Davis RB, Alward T(eds): Proceedings of the IEEE 17th Annual Northeast Bioengineering conference, New York, IEEE Press, 1991; pp 35-36.
24. Pincus SM. Approximate entropy (ApEn) as a complexity measure. Chaos 1995a;5:110-117.
25. Pincus SM. Quantifying complexity and regularity of neurobiological systems. Meth Neurosci 1995b;28:336-363.
26. Polich J. Attention, probability and task demands as determinants of P300 latency in ERPs from auditory stimulus. Electroencephalogr Clin Neurophysiol 1986;63:251-259.
27. Polich J. Updating P300: An integrative theory of P3a and P3b. Clin Neurophysiol 2007;118:2128-2148.
28. Pritchard WS, Duke DW, Coburn KL, et al. EEG-based neural-net predictive classification of Alzheimer's disease versus control subjects is augmented by non-linear EEG measures. Electroencephalogr Clin Neurophysiol 1994;91:118-130.
29. Rosso OA, Blanco S, Yordanova J, et al. Wavelet entropy: A new tool for analysis of short duration brain electrical signals. J Neurosci Meth 2001;105:65-75.
30. van Deursen JA, Vuurman EFPM, Smits LL, et al. Response speed, contingent negative variation and P300 in Alzheimer's disease and MCI. Brain Cogn 2009;69:592-599.
31. Verleger R. Event related potentials and cognition: A critique of the context updating hypothesis and an alternative interpretation of P3. Behav Brain Sci 1988;11:343-356.
32. Villafane-Delgado M, Aceros C, Rodriacuteguez D. Entropy measures techniques to characterize the vocalizations of synthetic and natural neotropical anurans. In: Majkic Z, Tamir D, Wang G, (eds): Proceedings of the 2010 International Conference on Artificial Intelligence and Pattern Recognition. New York: Curran Associates, Inc. Press, 2010; pp 100-105.
33. Yang F, Hong B, Tang Q. Approximate entropy and its application in biosignal analysis. In: Metin A, ed. Nonlinear biomedical signal processing: Dynamic analysis and modeling v.2. New York, NY: IEEE Press, 2001:72-91.
34. Yordanova J, Kolev V, Rosso OA, et al. Wavelet entropy analysis of event-related potentials indicates modality-independent theta dominance. J Neurosci Meth 2002;17:99-109.
35. Yordanova J, Rosso OA, Kolev V. A transient dominance of theta event-related brain potential component characterizes stimulus processing in an auditory oddball task. Clin Neurophysiol 2003;114:529-540.
36. Zhang XS, Roy RJ, Jensen EW. EEG complexity as a measure of depth of anesthesia for patients. IEEE Trans Biomed Eng 2001;48:1424-1433.
37. Zhao N, Liu X, Yu W, Wang S. ERP instantaneous synchronization analysis based on cross approximate entropy. Prog Nat Sci 2007;17:161-164.
38. Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand 1983;67:361-370.