The nonlinear and nonstationary properties in EEG signals: Probing the complex fluctuations by Hilbert-huang transform

Advances in Adaptive Data Analysis

Volumn 1, Issue 3, 2009, Pages 461-482

  Lo, Men Tzung ^a   Tsai, Ping Huang ^b,c   Lin, Pei Feng ^d,e   Lin, Chen ^a   Hsin, Yue Loong ^f  

^a NATIONAL CENTRAL UNIVERSITY   (Taiwan)

^b NATIONAL YANG MING UNIVERSITY   (Taiwan)

^c NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^d NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^e Tainan Hospital   (Taiwan)

^f BUDDHIST TZU CHI GENERAL HOSPITAL   (Taiwan)

Author keywords

brain topography; coherence; dementia; EEG; Hilbert Huang transform; interwave frequency; intrawave frequency modulation; nonlinear; Nonstationary; time frequency analysis

Indexed keywords

DEMENTIA; HILBERT HUANG TRANSFORMS; INTERWAVE FREQUENCY; INTRAWAVE FREQUENCY MODULATION; NONLINEAR; NONSTATIONARY; TIME FREQUENCY ANALYSIS;

DISEASES; ELECTROENCEPHALOGRAPHY; ELECTROPHYSIOLOGY; NONLINEAR ANALYSIS; RELIABILITY ANALYSIS; TIME SERIES; TIME SERIES ANALYSIS;

MATHEMATICAL TRANSFORMATIONS;

EID: 79551555690     PISSN: 17935369     EISSN: 17937175     Source Type: Journal    
DOI: 10.1142/S1793536909000199     Document Type: Article

References (52)

1. B. J. Roach and D. H. Mathalon, Event-related EEG time-frequency analysis: An overview of measures and an analysis of early gamma band phase locking in schizophrenia, Schizophr. Bull. 34 (5) (2008) 907-926.
2. D. V. Iosifescu, Prediction of response to antidepressants: Is quantitative EEG (QEEG) an alternative? CNS Neurosci. Ther. 14 (4) (2008) 263-265.
3. F. Letemendia and G. Pampiglione, Clinical and electroencephalographic observations in Alzheimer's disease, J. Neurol. N eurosurg. Psychiatry 21 (3) (1958) 167-172.
4. W. Klimesch, EEG alpha and theta oscillations reflect cognitive and memory performance: A review and analysis, Brain Res. Brain Res. Rev. 29 (2-3) (1999) 169-195. (Pubitemid 29191338)
5. E. B. Gordon, Sim et al., The EEG in presenile dementia, J. Neurol. Neurosurg. Psychiatry 30 (3) (1967) 285-291.
6. M. W. Difrancesco, S. K. Holland and J. P. Szaflarski, Simultaneous EEG/functional magnetic resonance imaging at 4 Tesla: Correlates of brain activity to spontaneous alpha rhythm during relaxation, J. Clin. Neurophysiol. 25 (5) (2008) 255-264.
7. B. J. Fish, Fisch and Spehlmann's EEG Primer: Basic Principles of Digital and Analog EEG (Elsevier, 1999).
8. A. Babloyantz, J. Salazar and C. Nicolis, Evidence of chaotic dynamics of brain activity during the sleep cycle, Phys. Lett. A 111 (3) (1985) 152-156.
9. A. Babloyantz and C. Lourenco, Computation with chaos: A paradigm for cortical activity, Proc. Natl. Acad. Sci. USA 91 (19) (1994) 9027-9031.
10. A. Babloyantz and A. Destexhe, Low-dimensional chaos in an instance of epilepsy, Proc. Natl. Acad. Sci. USA 83 (10) (1986) 3513-3517. (Pubitemid 16043065)
11. P. E. Rapp, I. D. Zimmerman, A. M. Albano et al., Dynamics of spontaneous neural activity in the Simian motor cortex: The dimension of chaotic neurons, Phys. Lett. A 110 (6) (1985) 334-338.
12. G. E. P. Box, G. M. Jenlins and G. C. Reinsel, Time Series Analysis, Forecasting and Control (Englewood Cliffs, NJ Prentice Hall, 1994).
13. M. F. Schlesinger, Fractal time and 1/f noise in complex systems, Ann. New York Acad. Sci. 504 (Persp. Biol. Dynam. Theoret. Med.) (1987) 214-228.
14. L. S. Liebovitch, Testing fractal and Markov models of ion channel kinetics, Biophys. J. 55 (2) (1989) 373-377.
15. M. T. Lo, V. Novak, C. K. Peng et al., Assessment of nonlinear phase interaction between nonstationary signals: A comparison study of methods based on Hilbert-Huang and Fourier transforms, Phys. Rev. E (2009).
16. N. E. Huang, Z. Shen, S. R. Long et al., The empirical mode decomposition method and the Hilbert spectrum for non-stationary time series analysis, Proc. Roy. Soc. London A 454 (1998) 903-995. (Pubitemid 128733183)
17. W. Huang, Z. Shen, N. E. Huang et al., Engineering analysis of biological variables: An example of blood pressure over 1 day, Proc. Natl. Acad. Sci. USA 95 (1998) 4816-4821. (Pubitemid 28208508)
18. K. Hu, C. K. Peng, M. Czosnyka et al., Nonlinear assessment of cerebral autoregulation from spontaneous blood pressure and cerebral blood flow fluctuations, Cardiovasc. Eng. 8 (1) (2008) 60-71.
19. M. T. Lo, K. Hu, Y. Liu et al., Multimodal pressure-flow analysis: Application of Hilbert Huang transform in cerebral blood flow regulation, Eurasip J. Adv. Signal Process. (2008).
20. K. Hu, M. T. Lo, C. K. Peng et al., Nonlinear pressure-flow relationship is able to detect asymmetry of brain blood circulation associated with midline shift, J. Neurotrauma 26 (2) (2009) 227-233.
21. V. Novak, A. C. Yang, L. Lepicovsky et al., Multimodal pressure-flow method to assess dynamics of cerebral autoregulation in stroke and hypertension, Biomed. Eng. Online 3 (1) (2004) 39.
22. K. Hu, C. K. Peng, N. E. Huang et al., Altered phase interactions between spontaneous blood pressure and flow fluctuations in type 2 diabetes mellitus: Nonlinear assessment of cerebral autoregulation, Phys. A-Stat. Mech. Appl. 387 (10) (2008) 2279-2292.
23. R. Maestri, G. D. Pinna, A. Accardo et al., Nonlinear indices of heart rate variability in chronic heart failure patients: Redundancy and comparative clinical value, J. Cardiovasc. Electrophysiol. 18 (4) (2007) 425-433. (Pubitemid 46435049)
24. R. Balocchi, D. Menicucci, E. Santarcangelo et al., Deriving the respiratory sinus arrhythmia from the heartbeat time series using empirical mode decomposition, Chaos, Solitons Fractals 20 (1) (2004) 171-177.
25. C. M. Sweeney-Reed and S. J. Nasuto, A novel approach to the detection of synchronisation in EEG based on empirical mode decomposition, J. Comput. Neurosci. 23 (1) (2007) 79-111. (Pubitemid 47422588)
26. M. R. Nuwer, G. Comi, R. Emerson et al., IFCN standards for digital recording of clinical EEG. International Federation of Clinical Neurophysiology, Electroencephalogr. Clin. Neurophysiol. 106 (3) (1998) 259-261.
27. Z. Wu and N. E. Huang, Ensemble empirical mode decomposition: A noise-assisted data analysis method, Centre for Ocean-Land-Atmosphere Studies, Tech Rep No 2005;193.
28. Z. Wu and N. E. Huang, Ensemble empirical mode decomposition: A noise-assisted data analysis method, Adv. Adapt. Data Anal. 1 (2009) 1-41.
29. M. G. Rosenblum, A. S. Pikovsky and J. Kurths, Phase synchronization of chaotic oscillators, Phys. Rev. Lett. 76 (11) (1996) 1804-1807. (Pubitemid 126638871)
30. P. Tass, M. G. Rosenblum, J. Weule et al., Detection of n: m phase locking from noisy data: Application to magnetoencephalography, Phys. Rev. Lett. 81 (15) (1998) 3291-4329.
31. C. Schafer, M. G. Rosenblum, J. Kurths et al., Heartbeat synchronized with ventilation, Nature 392 (6673) (1998) 239-240.
32. N. Delprat, B. Escudie, P. Guillemain et al., Asymptotic wavelet and Gabor analysis - extraction of instantaneous frequencies, IEEE Trans. Inform. Theory 38 (2) (1992) 644-664.
33. D. B. Lindsley, Psychological phenomenon and the electroencephalogram, Electroencephalogr. Clin. Neurophysiol. 4 (4) (1952) 443-456.
34. S. Tong, Z. Li, Y. Zhu et al., Describing the nonstationarity level of neurological signals based on quantifications of time-frequency representation, IEEE Trans. Biomed. Eng. 54 (10) (2007) 1780-1785. (Pubitemid 47450547)
35. S. N. Prabhakar, Modern Spectrum Analysis of Time Series (CRC Press, Boca Raton, 1996).
36. V. L. Newhouse, E. S. Furgason and G. F. Johnson et al., The dependence of ultrasound doppler bandwidth on beam geometry, IEEE Trans. Sonics Ultrason. 27 (2) (1980) 50-59.
37. D. W. Liddell, Investigations of EEG findings in presenile dementia, J. Neurol. Neurosu rg. P sychi atry 21 (3) (1958) 173-176.
38. H. Soininen, V. J. Partanen, E. L. Helkala et al., EEG findings in senile dementia and normal aging, Acta Neurol. Scand. 65 (1) (1982) 59-70. (Pubitemid 12178848)
39. R. P. Brenner, C. F. Reynolds III, R. F. Ulrich, Diagnostic efficacy of computerized spectral versus visual EEG analysis in elderly normal, demented and depressed subjects, Electroencephalogr. Clin. Neurophysiol. 69 (2) (1988) 110-117. (Pubitemid 18024751)
40. Y. Fischer, B. H. Gahwiler and S. M. Thompson, Activation of intrinsic hippocampal theta oscillations by acetylcholine in rat septo-hippocampal cocultures, J. Physiol. 519 (2) (1999) 405-413. (Pubitemid 29430004)
41. E. R. John, The neurophysics of consciousness, Brain Res. Brain Res. Rev. 39 (1) (2002) 1-28. (Pubitemid 34666984)
42. I. A. Sulg, S. Cronqvist, H. Schuller et al., The effect of intracardial pacemaker therapy on cerebral blood flow and electroencephalogram in patients with complete atrioventricular block, Circulation 39 (1969) 487-494.
43. M. R. Nuwer, Quantitative EEG: I. Techniques and problems of frequency analysis and topographic mapping, J. Clin. Neurophysiol. 5 (1) (1988) 1-43. (Pubitemid 18045956)
44. A. F. Leuchter, I. A. Cook, R. B. Lufkin et al., Cordance: A new method for assessment of cerebral perfusion and metabolism using quantitative electroencephalography, Neuroimage 1 (3) (1994) 208-219. (Pubitemid 24253436)
45. R. W. Thatcher, P. J. Krause and M. Hrybyk, Cortico-cortical associations and EEG coherence: A two-compartmental model, Electroencephalogr. Clin. Neurophysiol. 64 (2) (1986) 123-143. (Pubitemid 16057727)
46. G. Pfurtscheller and C. Andrew, Event-related changes of band power and coherence: Methodology and interpretation, J. Clin. Neurophysiol. 16 (6) (1999) 512-519.
47. S. J. Teipel, W. Bayer, G. E. Alexander et al., Regional pattern of hippocampus and corpus callosum atrophy in Alzheimer's disease in relation to dementia severity: Evidence for early neocortical degeneration, Neurobiol. Aging 24 (1) (2003) 85-94. (Pubitemid 35454146)
48. S. J. Teipel, W. Bayer, G. E. Alexander et al., Progression of corpus callosum atrophy in Alzheimer disease, Arch Neurol. 59 (2) (2002) 243-248. (Pubitemid 34240940)
49. S. J. Teipel, H. Hampel, G. E. Alexander et al., Dissociation between corpus callosum atrophy and white matter pathology in Alzheimer's disease, Neurology 51 (5) (1998) 1381-1385. (Pubitemid 28520562)
50. H. Hampel, S. J. Teipel, G. E. Alexander et al., Corpus callosum atrophy is a possible indicator of region-and cell type-specific neuronal degeneration in Alzheimer disease: A magnetic resonance imaging analysis, Arch Neurol. 55 (2) (1998) 193-198.
51. P. Vermersch, J. Roche, M. Hamon et al., White matter magnetic resonance imaging hyperintensity in Alzheimer's disease: Correlations with corpus callosum atrophy, J. Neurol. 243 (3) (1996) 231-234. (Pubitemid 26071984)
52. A. M. Husain, Electroencephalographic assessment of coma, J. Clin. Neurophysiol. 23 (3) (2006) 208-220. (Pubitemid 44305225)