A general statistical framework for frequency-domain analysis of EEG topographic structure

Computers and Biomedical Research

Volumn 30, Issue 2, 1997, Pages 129-164

  Kelly, Edward F ^a   Lenz, James E ^b   Franaszczuk, Piotr J ^c,d   Truong, Young K ^e  

^a UNIVERSITY OF NORTH CAROLINA   (United States)

^b VA MEDICAL CENTER   (United States)

^c UNIVERSITY OF WARSAW   (Poland)

^d UNIVERSITY OF MARYLAND SCHOOL OF MEDICINE   (United States)

^e University of North Carolina at Chapel Hill   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; BIOMECHANICS; BRAIN MAPPING; ELECTROENCEPHALOGRAM; FOURIER TRANSFORMATION; MATHEMATICAL ANALYSIS; PRIORITY JOURNAL;

EID: 0031127290     PISSN: 00104809     EISSN: None     Source Type: Journal    
DOI: 10.1006/cbmr.1997.1444     Document Type: Article

References (184)

1. Gevins A. High-resolution EEG. Brain Topogr. 5:1993;321.
2. Nunez P. L., Silberstein R. B., Cadusch P. J., Wijesinghe R., Westdorp A. F., Srinivasan R. A. A theoretical and experimental study of high resolution EEG based on surface Laplacians and cortical imaging. Electroenceph. Clin. Neurophysiol. 90:1994;40.
3. Perrin F., Bertrand O., Perner J. Scalp current density mapping: Value and estimation from potential data. IEEE. Trans. Biomed. Eng. BME-34:1987;283.
4. Perrin F., Pernier J., Bertrand O., Echallier J. F. Spherical splines for scalp potential and current density mapping. Electroenceph. Clin. Neurophysiol. 72:1989;184.
5. Perrin F., Pernier J., Bertrand O., Echallier J. F. Erratum. Electroenceph. Clin. Neurophysiol. 76:1989;565.
6. Thatcher R. W., Hallett M., Zeffiro T., John E. R., Huerta M. Functional Neuroimaging: Technical Foundations. 1994;Academic Press, Orlando.
7. McLaughlin D. F., Kelly E. F. Evoked potentials as indices of adaptation in the somatosensory system in humans: A review and prospectus. Brain Res. Rev. 18:1993;151.
8. McLaughlin D. F., Kelly E. F. Peripheral vs. cortical driving responses evoked by brief vibrotactile stimuli in humans. Proc. Soc. Neurosci. 1993.
9. Gray C. M., Singer W. Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex. Proc. Natl. Acad. Sci. USA. 86:1989;1698.
10. Gray C. M., Konig P., Engel A. K., Singer W. Oscillatory responses in cat visual cortex exhibit intercolumnar synchronization which reflects global stimulus properties. Nature. 338:1989;334.
11. Eckhorn R., Bauer R., Jordan W., Brosch M., Kruse W., Munk M., Reitbock H. J. Coherent oscillations: A mechanism of feature linking in the visual cortex? Biol. Cybern. 60:1988;121.
12. Freeman W. J. Analytic techniques used in the search for the physiological basis of the EEG. Methods of Analysis of Brain Electrical and Magnetic Signals. Handbook of EEG, Revised Series. I:1987;Elsevier, Amsterdam. p. 583-664.
13. Singer W. Search for coherence: A basic principle of cortical self-organization. Concepts Neurosci. 1:1990;1.
14. Tononi G., Sporns O., Edelman G. M. Reentry and the problem of integrating multiple cortical areas: Simulation of dynamic integration in the visual system. Cerebral Cortex. 2:1992;310.
15. Favorov O. V., Kelly D. G. Minicolumnar organization within somatosensory cortical segregates. I. Development of afferent connections. Cerebral Cortex. 4:1994;408.
16. Favorov O. V., Kelly D. G. Minicolumnar organization within somatosensory cortical segregate. II. Emergent functional properties. Cerebral Cortex. 4:1994;428.
17. Whitsel B. L., Favorov O., Kelly D. G. Mechanisms of dynamic peri- and inter-columnar interactions in somatosensory cortex: Stimulus-specific contrast enhancement by NMDA receptor activation. Franzen O., Westman J. Information Processing in the Somatosensory System. 1991;353-370 Stockton, New York.
18. P. L. Nunez, 1988, Spatial filtering and experimental strategies in EEG, Statistics and Topography in Quantitative EEG, D. Samson-Dollfus, 196, 209, Elsevier, Amsterdam.
19. Goldman-Rakic P. S. Changing concepts of cortical connectivity: Parallel distributed cortical networks. Rakic P., Singer W. Neurobiology of Neocortex. 1988;177-202 Wiley-Interscience, Chichester.
20. Shaw J. C., O'Connor K., Ongley C. EEG coherence as a measure of cerebral functional organization. Brazier M. A. B., Petsche H. Architectonics of the Cerebral Cortex. IBRO Monograph No. 3. 1978;245-255 Raven Press, New York.
21. Rappelsberger P., Petsche H. Probability mapping: Power and coherence analyses of cognitive processes. Brain Topogr. 1:1988;46.
22. Hannan E. J. Multiple Time Series. 1970;Wiley, New York.
23. Anderson T. W. An Introduction to Multivariate Statistical Analysis. 1958;Wiley, New York.
24. Bendat J. S., Piersol A. G. Random Data. Analysis and Measurement Procedures. 1986;Wiley, New York.
25. Cooper R., Osselton J. W., Shaw J. C. EEG Technology. 1980;Butterworths, London.
26. Dumermuth G., Molinari L. Spectral analysis of EEG background activity. Gevins A. S., Remond A. Methods of Analysis of Brain Electrical and Magnetic Signals. Handbook of EEG, rev. ser. I:1987;85-130 Elsevier, Amsterdam.
27. Hinich M. J., Clay C. S. The application of the discrete Fourier transform in the estimation of power spectra, coherence, and bispectra of geophysical data. Rev. Geophys. 6:1968;347.
28. Jenkins G. M., Watts D. G. Spectral Analysis and Its Applications. 1968;Holden-Day, San Francisco.
29. Otnes R. K., Enochson L. Applied Time Series Analysis. 1978;Wiley-Interscience, New York.
30. Regan D. Human Brain Electrophysiology. Evoked Potentials and Evoked Magnetic Fields in Science and Medicine. 1989;Elsevier, New York.
31. Harris F. J. On the use of windows for harmonic analysis with the discrete Fourier transform. Proc. IEEE. 66:1978;51.
32. Fuller W. A. Introduction to Statistical Time Series. 1976;Wiley, New York.
33. Koopmans L. H. The Spectral Analysis of Time Series. 1974;Academic Press, New York.
34. Gasser T., Bacher P., Möcks J. Transformations towards the normal distribution of broad band spectral parameters of the EEG. Electroenceph. Clin. Neurophysiol. 53:1982;41-119.
35. Brillinger D. R. Time Series: Data Analysis and Theory. 1975;Holt, Rinehart, & Winston, New York.
36. Nuttall A. H., Carter G. C. A generalized framework for power spectral estimation. IEEE Trans. Acoust. Speech Signal Process. ASSP-28:1980;334.
37. Gersch W. Spectral analysis of EEGs by autoregressive decomposition of time series. Math. Biosci. 7:1970;205.
38. Zetterberg L. H. Estimation of parameters for a linear difference equation with application to EEG analysis. Math. Biosci. 5:1969;227.
39. Kay S. M., Marple S. L. Jr. Spectrum analysis: A modern perspective. Proc. IEEE. 69:1981;1380.
40. Marple S. L. Jr. Digital Spectral Analysis with Applications. 1987;Prentice-Hall, Englewood Cliffs.
41. Broersen P. M. T., Wensink H. E. On finite sample theory for autoregressive model order selection. IEEE Trans. Signal Process. 41:1993;194.
42. Hurvich C. M., Tsai C. L. Regression and time series model selection in small samples. Biometrika. 76:1989;297.
43. Berk K. N. Consistent autoregressive spectral estimates. Ann. Statist. 2:1974;489.
44. Jennrich R. I. Asymptotic properties of non-linear least squares estimators. Ann. Math. Stat. 40:1969;633.
45. S. M. Kay, 1988, Modern Spectral Estimation: Theory and Application, Prentice-Hall, Englewood Cliffs.
46. Jansen B. H. Analysis of biomedical signals by means of linear modeling. CRC Crit. Rev. Biomed. Engrg. 12:1985;343.
47. Lopes DA Silva F. H., Mars N. J. I. Parametric methods in EEG analysis. Gevins A. S., Remond A. Methods of Analysis of Brain Electrical and Magnetic Signals. Handbook of EEG, rev. ser. 1:1987;243-260 Elsevier, Amsterdam.
48. Blinowska K. J., Franaszczuk P. J. A model of the generation of electrocortical rhythms. Basar E., Bullock T. H. Brain Dynamics 2. 1989;1992-1201 Springer-Verlag, Berlin.
49. Franaszczuk P. J., Blinowska K. J. Linear model of brain electrical activity-EEG as a superposition of damped oscillatory modes. Biol. Cybern. 53:1985;19.
50. Franaszczuk P. J., Mitraszewski P., Blinowska K. J. FAD-parametric description of EEG time series. Acta Physiol. Pol. 40:1989;418.
51. Blinowska K. J., Franaszczuk P. J., Mitraszewski P. A new method of presentation of the average spectral properties of the EEG time series. Int. J. Biomed. Comput. 22:1988;97.
52. Wennberg A., Zetterberg L. H. Application of a computer-based model for EEG analysis. Electroenceph. Clin. Neurophysiol. 31:1971;457.
53. Wahba G. Automatic smoothing of the log periodogram. J. Am. Statist. Assoc. 75:1980;122.
54. Pawitan Y., O'Sullivan F. Nonparametric spectral density estimation using penalized Whittle likelihood. J. Am. Statist. Assoc. 89:1994;600.
55. Kooperberg C., Stone C. J., Truong Y. Logspline estimation of a possibly mixed spectral distribution. J. Time Ser. Anal. 16:1995;359.
56. Cooley W. W., Lohnes P. R. Multivariate Procedures for the Behavioral Sciences. 1962;Wiley, New York.
57. Morrison D. F. Multivariate Statistical Methods. 1990;McGraw-Hill, New York.
58. Johnson R. A., Wichern D. W. Applied Multivariate Statistical Analysis. 1992;Prentice-Hall, Englewood Cliffs.
59. Shumway R. H. Applied Statistical Time Series Analysis. 1988;Prentice-Hall, Englewood Cliffs.
60. Chang T. C., Krishnaiah P. R., Lee C. J. Approximations to the distribution of the likelihood ratio statistics for testing the hypotheses on covariance matrices and mean vectors simultaneously. Krishnaiah P. R. Applications of Statistics. 1977;97-108 North-Holland, Amsterdam.
61. Krishnaiah P. R., Lee J. C. Likelihood ratio tests for mean vectors and covariance matrices. Krishnaiah P. R. Handbook of Statistics. 1980;513-570 North-Holland, Amsterdam.
62. Bartels P. H., Bartels H. G. Classification strategies for topographic mapping data. Duffy F. H. Topographic Mapping of Brain Electrical Activity. 1986;225-253 Butterworths, Boston.
63. Flury B. Common Principal Components and Related Multivariate Models. 1988;Wiley, New York.
64. Reyment R., Jöreskog K. G. Applied Factor Analysis in the Natural Sciences. 1993;Cambridge Univ. Press, Cambridge.
65. Velicer W. F., Jackson D. N. Component analysis vs. common factor analysis: Some issues in selecting an appropriate procedure. Multivariate Behav. Res. 25:1990;1.
66. Zwick W. R., Velicer W. F. A comparison of five rules for determining the number of components to retain. Psychol. Bull. 99:1986;432.
67. Van Rotterdam A. Limitations and difficulties in signal processing by means of the principal components analysis. IEEE Trans. Biomed. Eng. BME-17:1970;268.
68. Wastell D. On the correlated nature of evoked brain activity: Biophysical and statistical considerations. Biol. Psychol. 13:1981;51.
69. Silberstein R. B., Cadusch P. J. Measurement processes and spatial principal components. Brain Topogr. 4:1992;267.
70. Rawlings R. R., Rohrbaugh J. W., Begleiter H., Eckardt M. J. Spectral methods for principal components analysis of event-related brain potentials. Comput. Biomed. Res. 19:1986;497.
71. Valdez P., Bosch J., Grave R., Hernandez J., Riera J., Pascual R., Biscay R. Frequency domain models of the EEG. Brain Topog. 4:1992;309.
72. Nunez P. L. Electric Fields of the Brain: The Neurophysics of EEG. 1981;Oxford Univ. Press, New York.
73. Skrandies W., Lehmann D. Spatial principal components of multichannel maps evoked by lateral visual half-field stimuli. Electroenceph. Clin. Neurophysiol. 54:1982;662.
74. Harner R. N. Singular value decomposition - A general linear model for analysis of multivariate structure in the electroencephalogram. Brain Topogr. 3:1990;43.
75. Shepard R. A., Romney A. K., Nerlove S. Multidimensional Scaling: Theory and Applications in the Behavioral Sciences. Theory. 1972;Seminar Press, New York.
76. Kruskal J. B., Wish M. Multidimensional Scaling. 1978;Sage, Beverly Hills.
77. Schiffman S. S., Reynolds M. L., Young F. W. Introduction to Multidimensional Scaling. 1981;Academic Press, New York.
78. Wish M., Carroll J. D. Multidimensional scaling and its applications. Krishnaiah P. R., Kanal L. N. Handbook of Statistics. 1982;317-345 North-Holland, Amsterdam.
79. McCarthy G., Wood C. C. Scalp distributions of event-related potentials: An ambiguity associated with analysis of variance models. Electroenceph. Clin. Neurophysiol. 62:1985;203.
80. 2. Brain Topogr. 2:1990;237.
81. Pascual-Marqui R. D., Valdez-Sosa P. A., Alvarez-Amador A. A parametric model for multichannel EEG spectra. Int. J. Neurosci. 40:1988;89.
82. Goodman N. R. Statistical analysis based on a certain multivariate complex Gaussian distribution (an introduction). Ann. Math. Stat. 34:1963;152.
83. Goodman N. R. The distribution of the determinant of a complex Wishart distributed matrix. Ann. Math. Stat. 34:1963;178.
84. M. R. Dubman, N. R. Goodman, 1969, Spectral Analysis of Multiple Time Series, North American Rockwell.
85. Brillinger D. R. The analysis of time series collected in an experimental design. Krishnaiah P. R. Multivariate Analysis, III. 1973;241-256 Academic Press, New York.
86. Brillinger D. R. Analysis of variance and problems under time series models. Krishnaiah P. R. Handbook of Statistics. 1980;237-278 Elsevier, Amsterdam.
87. Brillinger D. R. The finite Fourier transform of a stationary process. Brillinger D. R., Krishnaiah P. R. Handbook of Statistics. 1983;21-37 Elsevier, Amsterdam.
88. Brillinger D. R., Krishnaiah P. R. Time Series in the Frequency Domain. Handbook of Statistics. 3:1983.
89. 2. Ann. Math. Stat. 36:1965;664.
90. Khatri C. G. Classical statistical analysis based on a certain multivariate complex Gaussian distribution. Ann. Math. Stat. 36:1965;98.
91. Krishnaiah P. R. Some recent developments on complex multivariate distributions. J. Multivariate Anal. 6:1976;1.
92. Krishnaiah P. R., Lee J. C., Chang T. C. The distributions of the likelihood ratio statistics for tests of certain covariance structures of complex multivariate normal populations. Biometrika. 63:1976;543.
93. Krishnaiah P. R., Lee J. C., Chang T. C. Likelihood ratio tests on covariance matrices and mean vectors of complex multivariate normal populations and their applications in time series. Brillinger D. R., Krishnaiah P. R. Handbook of Statistics. 1983;439-476 Elsevier, Amsterdam.
94. Shumway R. H. Discriminant analysis for time series. Krishnaiah P. R., Kanal L. N. Handbook of Statistics. 1982;1-46 North Holland, Amsterdam.
95. Rawlings R., Eckardt M., Begleiter H. Multivariate time series discrimination in the spectral domain. Comput. Biomed. Res. 17:1984;352.
96. Walter D. O., Adey W. R. Analysis of brain-wave generators as multiple statistical time-series. IEEE Trans. Biomed. Eng. BME-12:1965;8.
97. Bloomfield P. Fourier Analysis of Time Series: An Introduction. 1976;Wiley-Interscience, New York.
98. Childers D. G. Evoked responses: Electrogenesis, models, methodology, and wavefront reconstruction and tracking analysis. Proc. IEEE. 65:1977;611.
99. Carter G. C., Knapp C. H., Nuttall A. H. Estimation of the magnitude-squared coherence function via overlapped fast Fourier transform processing. IEEE Trans. Audio Electroacoust. AU-21:1973;337.
100. Carter G. C., Knapp C. H. Coherence and its estimation via the partitioned modified Chirp-Z transform. IEEE Trans. Acoust. Speech Signal Process. ASSP-23:1975;257.
101. Levine P. H., Herbert J. R., Haynes C. A., Strobel C. EEG coherence during the Transcendental Meditation technique. Scientific Research on the Transcendental Meditation Program: Collected Papers. 1976.
102. Tick L. J. Estimation of coherency. Harris B. Spectral Analysis of Time Series. 1967;133-152 Wiley, New York.
103. Carter G. C. Bias in magnitude-squared coherence estimation due to misalignment. IEEE Trans. Acoust. Speech Signal Process. ASSP-28:1980;97.
104. Tucker D. M., Roth D. L., Bair T. B. Functional connections among cortical regions: Topography of EEG coherence. Electroenceph. Clin. Neurophysiol. 63:1986;242.
105. Franaszczuk P. J., Blinowska K. H., Kowalczyk M. The application of parametric multichannel spectral estimates in the study of electrical brain activity. Biol. Cybern. 51:1985;239.
106. Lopes da Silva F. H., Vos J. E., Mooibroek J., Van Rotterdam A. Relative contribution of intracortical and thalamo-cortical processes in the generation of alpha rhythms, revealed by partial coherence analyses. Electroenceph. Clin. Neurophysiol. 50:1980;449.
107. Gersch W. Causality or driving in electrophysiological signal analysis. Math. Biosci. 14:1972;177.
108. Gersch W., Tharp B. R. Spectral regression - Amount of information analysis of seizures in humans. Kellaway P., Petersen I. Quantitative Analytic Studies in Epilepsy. 1976;509-532 Raven Press, New York.
109. Fisher R. A. Proc. R. Soc. Ser. A. 121:1928;654.
110. D. E. Amos, L. H. Koopmans, 1963, Tables of the Distribution of the Coefficient of Coherence for Stationary Bivariate Gaussian Processes, Office of Technical Services, Dept. of Commerce, Washington, D.C.
111. M. J. Alexander, C. A. Vok, 1963, Tables of the Cumulative Distribution of Sample Multiple Coherence.
112. Benignus V. A. Estimation of the coherence spectrum and its confidence interval using the fast Fourier transform. IEEE Trans. Audio Electroacoust. AU-17:1969;145.
113. Benignus V. A. Estimation of coherence spectrum of non-Gaussian time series populations. IEEE Trans. Audio Electroacoust. AU-17:1969;198.
114. Nuttall H., Carter G. C. Bias of the estimate of magnitude-squared coherence. IEEE Trans. Acoust. Speech Signal Process. ASSP-24:1976;582.
115. Lopes Silva F. H., Hoeks A., van Lierop T. H. M. T., Schrijer C. F., Storm van Leeuwen W. Confidence intervals of spectra and coherence functions - Their relevance for quantifying thalamo-cortical relationships. Matejcek M., Schenk G. K. Quantitative Analysis of the EEG. 1975;437-449 AEG Telefunken, Constanz.
116. Cooper R. Measurement of time and phase relationships of the EEG. Dolce G., Künkel H. CEAN: Computerized EEG Analysis. 1975;85-97 Fischer, Stuttgart.
117. Vos J. E., Scholten C. A., van Woerden H. H. Phase spectra: Estimation and interpretation. Matejcek M., Schenk G. K. Quantitative Analysis of the EEG. 1975;409-419 AEG Telefunken, Konstanz.
118. Oppenheim A. V., Shafer R. W. Discrete-Time Signal Processing. 1989;Prentice-Hall, Englewood Cliffs.
119. Gotman J. Measurement of small time differences between EEG channels: Method and application to epileptic seizure propagation. Electroenceph. Clin. Neurophysiol. 56:1983;501.
120. Ktonas P. Y., Mallart P. Y. Estimation of time delay between EEG signals for epileptic focus localization: Statistical error considerations. Electroenceph. Clin. Neurophysiol. 78:1991;105.
121. Harris B., Gath I., Rondouin G., Feuerstein C. On time delay estimation of epiletic EEG. IEEE Trans. Biomed. Eng. 41:1994;820.
122. Adey W. R., Walter D. O. Application of phase detection and averaging techniques in computer analysis of EEG records in the cat. Exp. Neurology. 7:1963;186.
123. Goodman N. R. Measuring amplitude and phase. J. Franklin Inst. 270:1960;437.
124. Zar J. H. Biostatistical Analysis. 1984;Prentice-Hall, Englewood Cliffs.
125. Mardia K. V. Statistics of Directional Data. 1972;Academic Press, New York.
126. Strasburger H. The analysis of steady state evoked potentials revisited. Clin. Vis. Sci. 1:1987;245.
127. Gasser T. A quantitative topographic component analysis for the EEG at rest. Sampson-Dollfus D. Statistics and Topography in Quantitative EEG. 1988;139-149 Elsevier, Paris.
128. Galbraith G. C. The effect of prior EEG "coupling" upon the visual evoked response. IEEE Trans. Biomed. Eng. BME-14:1967;223.
129. Gersch W. Non-stationary multichannel time series analysis. Gevins A. S., Remond A. Methods of Analysis of Brain Electrical and Magnetic Signals. Handbook of EEG. I:1987;261-296 Elsevier, Amsterdam.
130. Gersch W., Yonemoto J. Parametric times series models for multivariate EEG analysis. Comput. Biomed. Res. 10:1977;113.
131. Gersch W., Yonemoto J., Naitoh P. Automatic classification of multivariate EEG's using an amount of information measure and the eigenvalues of parametric time series model features. Comput. Biomed. Res. 10:1977;297.
132. Akaike H. Recent development of statistical methods for spectrum estimation. Yamaguchi N., Fujisawa K. Recent Advances in EEG and EMG Data Processing. 1981;68-78 Elsevier/North-Holland, Amsterdam.
133. Jones R. H. Identification and autoregressive spectrum estimation. IEEE Trans. Automat. Control. AC-19:1974;894.
134. Kaminski M. J., Blinowska K. J. A new method of the description of the information flow in the brain structures. Biol. Cybern. 65:1991;203.
135. Gath I., Feuerstein C., Pham D. T., Rondouin G. On the tracking of rapid dynamic changes in seizure EEG. IEEE Trans. Biomed. Eng. 39:1992;952.
136. Franaszczuk P. J., Bergey G. K., Kaminiski M. J. Analysis of mesial temporal seizure onset and propagation using the directed transfer function method. Electroenceph. Clin. Neurophysiol. 91:1994;413.
137. Oken B. S., Chiappa K. H. Statistical issues concerning computerized analysis of brain-wave topography. Ann. Neurol. 19:1986;493.
138. Abt K. Statistical aspects of neurophysiologic topography. J. Clin. Neurophysiol. 7:1990;519.
139. Kiers H. A. L., ten Berge J. M. F. Alternating least square algorithms for simultaneous components analysis with equal component weight matrices in two or more populations. Psychometrika. 54:1989;467.
140. Kiers H. A. L., ten Berge J. M. F. Hierarchical relations between methods for simultaneous component analysis and a technique for rotation to a simple simultaneous structure. Brit. J. Math. Stat. Psychol. 47:1994;109.
141. Millsap R. E., Meredith W. Component analysis in cross-sectional and longitudinal data. Psychometrika. 53:1988;123.
142. Jöreskog K. G. A general method of analysis for covariance structures. Biometrika. 57:1970;239.
143. Jöreskog K. G. Simultaneous factor analysis in several populations. Psychometrika. 36:1971;409.
144. Sörbom D. A general method for studying differences in factor means and factor structures between groups. Brit. J. Math. Stat. Psychol. 27:1974;229.
145. Jöreskog K. G., Sörbom D. LISREL 7 - A Guide to the Program and Applications. 1989;SPSS Publications, Chicago.
146. Jöreskog K. G., Sörbom D. LISREL 8: Structural Equation Modeling with the SIMPLIS Command Language. 1993;Erlbaum, Hillsdale.
147. Byrne B. M., Shavelson R. J., Muthern B. Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychol. Bull. 105:1989;456.
148. McIntosh A. R., Gonzalez-Lima F. Structural equation modeling and its application to network analysis in functional brain imaging. Human Brain Mapping. 2:1994;2.
149. Tucker D. M., Roth D. L. Factoring the coherence matrix: Patterning of the frequency-specific covariance in a multichannel EEG. Psychophysiology. 21:1984;228.
150. Harman H. H. Modern Factor Analysis. 1976;Univ. of Chicago Press, Chicago.
151. Gorsuch R. L. Factor Analysis. 1983;Erlbaum, Hillsdale.
152. Mulaik S. A. The Foundations of Factor Analysis. 1972;McGraw-Hill, New York.
153. Tucker L. R. The extension of factor analysis to three-dimensional matrices. Frederiksen N., Gulliksen H. Contributions to Mathematical Psychology. 1964;Holt Rinehart& Winston, New York.
154. Tucker L. R. Some mathematical notes on three-mode factor analysis. Psychometrika. 31:1966;279.
155. Tucker L. R. Relations between multidimensional scaling and three-mode factor analysis. Psychometrika. 37:1972;3.
156. Law H. G., Snyder C. W., Hattie J. A., McDonald R. P. Research Methods for Multimode Data Analysis. 1984;Praeger, New York.
157. Field A. S., Graupe D. Topographic components analysis of evoked potentials: estimation of model parameters and evaluation of parameter uniqueness. J. Biomed. Eng. 12:1990;287.
158. Field A. S., Graupe D. Topographic component (parallel factor) analysis of multichannel evoked potentials: Practical issues in trilinear spatiotemporal decomposition. Brain Topogr. 3:1991;407.
159. Harshman R. A., Lundy M. E. PARAFAC: Parallel factor analysis. Comput. Stat. Data Anal. 18:1994;39.
160. Möcks J. Topographic components model for event-related potentials and some biophysical considerations. IEEE Trans. Biomed. Eng. BME-35:1988;482.
161. Dunseath W. J. R., Kelly E. F. PC-based data-acquisition system for high-resolution EEG. IEEE Trans. Biomed. Eng. 42:1995;1212.
162. Lenz J. E., Kelly E. F. Computer-based calibration and measurement of an EEG data-acquisition system. IEEE Trans. Biomed. Eng. BME-28:1981;396.
163. Lehmann D. Principles of spatial analysis. Gevins A. S., Remond R. Methods of Analysis of Brain Electrical and Magnetic Signals. Handbook of EEG, rev. ser. I:1987;309-354 Elsevier, Amsterdam.
164. Walter D. O., Etevenon P., Pidoux B., Tortrat D., Guillou S. Computerized topo-EEG spectral maps: Difficulties and perspectives. Neuropsychobiology. 11:1984;264.
165. Fein G., Raz J., Brown F. F., Merrin E. L. Common reference coherence data are confounded by power and phase effects. Electroenceph. Clin. Neurophysiol. 69:1988;581.
166. Tomberg C., Desmedt J. E., Ozaki I. Right or left ear reference changes the voltage of frontal and parietal somatosensory evoked potentials. Electroenceph. Clin. Neurophysiol. 80:1991;504.
167. Stephenson W. A., Gibbs F. A. A balanced noncephalic reference electrode. Electroenceph. Clin. Neurophysiol. 3:1951;237.
168. Pernier J., Perrin F., Bertrand O. Scalp current density fields: Concept and properties. Electroenceph. Clin. Neurophysiol. 69:1988;385.
169. Biggins C. A., Fein G., Raz J., Amira A. Artifactually high coherences result from using spherical spline computation of scalp current density. Electroenceph. Clin. Neurophysiol. 79:1991;413.
170. Biggins C. A., Ezekiel F., Fein G. Spline computation of scalp current density and coherence: A reply to Perrin. Electroenceph. Clin. Neurophysiol. 83:1992;172.
171. Perrin F. Comments on article by Bigginset al. Electroenceph. Clin. Neurophysiol. 83:1992;171.
172. Pascual-Marqui R. D. The spherical spline Laplacian does not produce artifactually high coherences: Comments on two articles by Bigginset al. Electroenceph. Clin. Neurophysiol. 87:1993;62.
173. Mardia K. V. Tests of univariate and multivariate normality. Krishnaiah P. R. Handbook of Statistics. 1980;279-320 North-Holland, Amsterdam.
174. Ito P. K. Robustness of ANOVA and MANOVA test procedures. Krishnaiah P. R. Handbook of Statistics. 1980;199-236 North-Holland, Amsterdam.
175. Akaike H. On the statistical estimation of the frequency response function of a system having multiple input. Ann. Inst. Stat. Math. 17:1965;185.
176. Blair R. C., Karniski W. Distribution-free statistical analyses of surface and volumetric maps. Thatcher R. W., Hallett M., Zeffiro T., John E. R., Huerta M. Functional Neuroimaging: Technical Foundations. 1994;19-28 Academic Press, Orlando.
177. Barlow J. S. Methods of analysis of nonstationary EEGs with emphasis on segmentation techniques. A comparative review. J. Clin. Neurophysiol. 2:1985;267.
178. Elul R. The genesis of the EEG. Int. J. Neurobiol. 15:1972;227.
179. E. M. Dewan, 1969, Non-linear Cross-Spectral Analysis and Pattern Recognition, Office of Aerospace Research, USAF.
180. Kullback S. Information Theory and Statistics. 1969;Wiley, New York.
181. Mars N. J. I., Lopes da Saliva F. H. EEG analysis methods based on information theory. Gevins A. S., Remond R. Methods of Analysis of Brain Electrical and Magnetic Signals. Handbook of EEG, rev. ser. I:1987;297-307 Elsevier, Amsterdam.
182. Nikias C. L., Petropulu A. P. Higher-Order Spectra Analysis: A Nonlinear Signal Processing Framework. 1993;PTR Prentice-Hall, Englewood Cliffs.
183. Saltzberg B., Burton W. D., Burch N. R., Fletcher J., Michaels R. Electrophysiological measures of regional neural interactive coupling. Linear and non-linear dependence relationships among multiple channel electroencephalographic recordings. Int. J. Biomed. Comput. 18:1986;77.
184. Kitagawa G. A procedure for modeling of non-stationary time series. Ann. Inst. Stat. Math. B. 30:1978;351.