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Electrophysiology in Neuropsychiatric Research: A Network Perspective

Published online by Cambridge University Press:  07 November 2014

Georg Winterer ,
Werner M. Herrmann  and
Richard Coppola
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Abstract

A growing number of anatomic and physiologic studies have shown that parallel sensory and motor information processing occurs in multiple cortical areas. These findings challenge the traditional model of brain processing, which states that the brain is a collection of physically discrete processing modules that pass information to each other by neuronal impulses in a stepwise manner. New concepts based on neural network models suggest that the brain is a dynamically shifting collection of interpenetrating, distributed, and transient neural networks. Neither of these models is necessarily mutually exclusive, but each gives different perspectives on the brain that might be complementary. Each model has its own research methodology, with functional magnetic resonance imaging supporting notions of modular processing, and electrophysiology (eg, electroencephalography) emphasizing the network model. These two technologies might be combined fruitfully in the near future to provide us with a better understanding of the brain. However, this common enterprise can succeed only when the inherent limitations and advantages of both models and technologies are known. After a general introduction about electrophysiology as a research tool and its relation to the network model, several practical examples are given on the generation of pathophysiologic models and disease classification, intermediate phenotyping for genetic investigations, and pharmacodynamic modeling. Finally, proposals are made about how to integrate electrophysiology and neuroimaging methods.

Type
Feature Articles
Information
CNS Spectrums , Volume 4 , Issue 8: Neurologic Electrophysiology: Closing in on a Moving Picture of the Brain , August 1999 , pp. 17 - 29
Copyright
Copyright © Cambridge University Press 1999

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References

REFERENCES

1. Fodor, JA. The Modularity of Mind. Cambridge, Mass: MIT Press; 1983.CrossRefGoogle Scholar
2. Norman, DA, Shallice, T. Attention to action. In: Davidson, RJ, Schwartz, GE, Shapiro, D, eds. Consciousness and Self-Regulation. New York, NY: Plenum Press; 1986:1–18.Google Scholar
3. Goldman-Rakic, PS. The prefrontal landscape: implications of functional architecture for understanding human mentation and the central executive. Philos Trans R Soc Lond Biol Sci. 1996;351:1445–1453.Google Scholar
4. Kuhn, TS. The Structure of Scientific Revolutions. Chicago, Ill: University of Chicago Press; 1962.Google Scholar
5. Lehmann, D, Skrandies, W. Segmentation of evoked potentials based on spatial field configuration in multichannel recordings. Electroencephalogr Clin Neurophysiol. 1986;38(suppl):27–29.Google Scholar
6. Strik, WK, Lehmann, D. Data-determined window size and space-oriented segmentation of spontaneous EEG map series. Electroencephalogr Clin Neurophysiol 1993;87:169–174.CrossRefGoogle ScholarPubMed
7. Pascual-Marqui, RD, Michel, CM, Lehmann, D. Segmentation of brain electrical activity into microstates: model estimation and validation. IEEE Trans Biomed Eng. 1995;42:658–665.CrossRefGoogle ScholarPubMed
8. Koenig, T, Kochi, K, Lehmann, D. Event-related electric microstates of the brain differ between words with visual and abstract meaning. Electroencephalogr Clin Neurophysiol. 1998;106:535–546.CrossRefGoogle ScholarPubMed
9. Gevins, AS, Smith, ME, Le, J et al. , High resolution evoked potential imaging of the cortical dynamics of human working memory. Electroencephalogr Clin Neurophysiol. 1996;98:327–348.CrossRefGoogle ScholarPubMed
10. Snyder, AZ, Abdullaev, YG, Posner, MI, Raichle, ME. Scalp electrical potentials reflect regional cerebral blood flow responses during processing of written words. Proc Natl Acad Sci U S A. 1995;92:1689–1693.CrossRefGoogle ScholarPubMed
11. Courtney, SM, Ungerleider, LG, Keil, K, Haxby, JV. Transient and sustained activity in a distributed neural system for human working memory. Nature. 1997:386:608–611.Google Scholar
12. Josephs, O, Turner, R, Friston, K. Event-related fMRI. Hum Brain Mapp. 1997;5:243–248.3.0.CO;2-3>CrossRefGoogle Scholar
13. McKeown, MJ, Jung, T-P, Makeig, S et al. , Spatially independent activity patterns in functional MRI data during the Stroop color-naming task. Proc Natl Acad Sci USA. 1998;95:803–810.CrossRefGoogle ScholarPubMed
14. Pascual-Marqui, RD, Michel, CM, Lehmann, D. Low resolution tomography: a new method for localizing electrical activity in the brain. Int J Psychophysiol. 1994;18:49–65.CrossRefGoogle ScholarPubMed
15. Pascual-Marqui, RD. Optimum imaging with low resolution brain electric tomography (LORETA): a fair and critical comparison of instantaneous, 3D, discrete, linear inverse solutions for EEG/MEG. Presented at: 4th International Conference on Functional Mapping of the Human Brain; June 1998; Montreal, Quebec, Canada.Google Scholar
16. Gevins, AS, Le, J, Martin, NK, Reutter, B, Desmond, J, Brickett, P. High resolution EEG: 124-channel recording, spatial deblurring and MRI integration methods. Electroencephalogr Clin Neurophysiol. 1994;90:337–358.CrossRefGoogle ScholarPubMed
17. Hashimoto, I, Okada, YC, Ogawa, S. Visualization of Information Processing in the Human Brain: Recent Advances in MEG and Functional MRI. Amsterdam, Netherlands: Elsevier; 1996.Google Scholar
18. Liu, AK, Belliveau, JW, Dale, AM. Spatiotemporal imaging of human brain activity using functional fMRI constrained magnetoencephalography data: Monte Carlo stimulations. Proc Natl Acad Sci USA. 1998;95:8945–8950.CrossRefGoogle Scholar
19. Gevins, AS. The future of electroencephalography in assessing neurocognitive functioning. Electroencephalogr Clin Neurophysiol. 1998;106:165–172.CrossRefGoogle ScholarPubMed
20. McKean, MJ, Jung, TP, Makeig, S et al. , Spatially independent activity patterns in functional MRI data during the Stroop Color-Naming Task. Proc Natl Acad Sci USA. 1998;95:803–816.CrossRefGoogle Scholar
21. Heisenberg, W. Physik und Philosophie. Berlin, Germany: Ullstein; 1984.Google Scholar
22. Fuster, JM. The Prefrontal Cortex. Philadelphia, Pa: Lippincott-Raven; 1997.Google Scholar
23. Fuster, JM. Network memory. Trends Neurosci. 1997;20;451–459.CrossRefGoogle ScholarPubMed
24. Fink, GR, Halligan, PW, Marshall, JC, Frith, CD, Frackowiak, RSJ, Dolan, RJ. Where in the brain does visual attention select the forest and the trees. Nature. 1996;382:626–628.Google Scholar
25. Edelman, GM. Neural Darwinism: The Theory of Neuronal Group Selection. New York, NY: Basic Books; 1987.Google Scholar
26. Von der Malsburg, C. Nervous structures with dynamic links. Ber Bunsen-Ges Phys Cem. 1985;89:703–710.CrossRefGoogle Scholar
27. Eckhorn, R, Reitbock, HJ. Assessment of cooperative firing in groups of neurons: special concepts of multiunit recordings from the visual system. In: Basar, E, ed. Brain Dynamics. Berlin, Germany: Springer; 1988.Google Scholar
28. Gray, CM, Singer, W. Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex. Proc Natl Acad Sci USA. 1989:86:1698–1702.CrossRefGoogle ScholarPubMed
29. Damasio, AR. The brain binds entities and events by multiregional activation from convergence zones. Neural Computation. 1989;1:123–132.CrossRefGoogle Scholar
30. Bressler, SL, Coppola, R, Nakamura, R. Episodic multiregional cortical coherence at multiple frequencies during visual task performance. Nature. 1993;366:153–156.Google Scholar
31. Hardcastle, VG. Consciousness and the neurobiology of perceptual binding. Sem Neurobiol. 1997;17:163–170.CrossRefGoogle ScholarPubMed
32. Whittington, MA, Traub, RD, Jefferys, JGR. Synchronized oscillations in interneuron networks driven by metabotropic glutamate receptor activation. Nature. 1995;373:612–615.Google Scholar
33. Penttonen, M, Kamondi, A, Acsady, L, Buzsaki, G. Gamma frequency oscillations in the hippocampus of the rat: intracellular analysis in vivo. Eur J Neurosci. 1998;10:718–728.CrossRefGoogle ScholarPubMed
34. Lopes da Silva, F. Event-related potentials: methodology and quantification. In: Niedermeyer, E, Lopes da Silva, F, eds. Electroencephalography. Baltimore, Md: Urban & Schwarzenberg; 1987.Google Scholar
35. Sayers, B, Beagley, HA, Hanshall, WR. The mechanisms of auditory evoked EEG responses. Nature. 1972;247:481–483.Google Scholar
36. Winterer, G, Ziller, M, Dorn, H et al. , Cortical activation, signal-to-noise ratio, stochastic resonance during information processing in man. Clin Neuro. 1998;110:1193–1203. (revised).Google Scholar
37. Bullock, TH, McClune, MC, Achimowicz, JZ, Iraqui-Madoz, VJ, Duckrow, RB, Spencer, SS. EEG coherence has structure in the millimeter domain: subdural and hippocampal recordings from epileptic patients. Electroencephalogr Clin Neurophysiol. 1995;95:161–177.CrossRefGoogle ScholarPubMed
38. Lehmann, D, Michel, CM. Intracerebral source localization for FFT power maps. Electroencephalogr Clin Neurophysiol. 1990;76:271–276.CrossRefGoogle ScholarPubMed
39. Lutkenhoner, B. Frequency domain localization of intracerebral dipolar sources. Electroencephalogr Clin Neurophysiol. 1992;82:112–118.CrossRefGoogle ScholarPubMed
40. Gevins, A, Smith, ME, McEvoy, L, Yu, D. High resolution EEG mapping of cortical activation related to working memory: effects of task difficulty, type of processing, and practice. Cereb Cortex. 1997;7:374–385.CrossRefGoogle ScholarPubMed
41. Ishihari, T, Yoshii, N. Multivariate analytical study of EEG and mental activity in juvenile deliquents. Electroencephalogr Clin Neurophyswl. 1972;33:71–80.CrossRefGoogle Scholar
42. Miller, R. Corticohippocampal Interplay and the Representation of Contexts in the Brain. Berlin, Germany: Springer; 1991.CrossRefGoogle Scholar
43. Westphal, KP, Grözinger, B, Diekmann, V et al. , Slower theta activity over midfrontal cortex in schizophrenic patients. Acta Psychiatr Scand. 1990;81:132–138.CrossRefGoogle ScholarPubMed
44. John, ER, Prichep, LS, Alper, KR et al. , Quantitative electrophysiological characteristics and subtyping of schizophrenia. Biol Psychiatry. 1994;36:801–826.CrossRefGoogle ScholarPubMed
45. Herrmann, WM, Ziller, M, Dorn, H et al. , Cortical activation in schizophrenia and its modulation by typical and atypical neuroleptic drug treatment. Presented at: 8th Central European Neuropsychopharmacological Symposium (8th CENP); August, 1998; Vienna, Austria.Google Scholar
46. Mulert, C, Winterer, G, Wuebben, Y et al. , Cortical activation in schizophrenic patients and subjects with schizotypal personality. Proceedings of the 9th European Congress of Clinical Neurophysiology (ECCN '98), Ljubjana, Slovenia. June 1998. Moduzzieditore, International Proceedings Division. Bologna, Italy.Google Scholar
47. Stabenau, JB, Pollin, W. Heridity and environment in schizophrenia, revisited. J Nerv Ment Dis. 1993;181:290–297.CrossRefGoogle Scholar
48. Berman, KF, Torrey, F, Daniel, DG, Weinberger, DR. Regional cerebral blood flow in monozygotic twins discordant and concordant for schizophrenia. Arch Gen Psychiatry. 1992;49:927–934.CrossRefGoogle ScholarPubMed
49. Jones, EG. The development of primate neocortex – an overview. In: Mednick, SA, Cannon, TD, Barr, CE, Lyon, M, eds. Fetal Neural Development and Adult Schizophrenia. Cambridge, Mass: Cambridge University Press; 1991.Google Scholar
50. Lipska, BK, Jaskiw, GE, Weinberger, DR. Postpubertal emergence of augmented exploration and amphetamine supersensitivity after neonatal deafferentation of the rat ventral hippocampus: a potential animal model of schizophrenia. Neuropsychopharmacology. 1993;9:67–75.CrossRefGoogle Scholar
51. Gershon, ES, Badner, JA, Goldin, LR, Sanders, A, Cravchik, A, Detera-Wadleigh, SD. Closing in on genes for manicdepressive illness and schizophrenia. Neuropsychopharmacology. 1998;18:233–242.CrossRefGoogle Scholar
52. Thatcher, RW, Cantor, DS, McAlaster, R, Geisler, R, Krause, P. Comprehensive predictions of outcome in closed headinjured patients. Ann N Y Acad Sci. 1991;620:82–101.Google Scholar
53. Van Beijsterveldt, CEM, Boomsma, DI. Genetics of the human electroencephalogram (EEG) and event-related potentials (ERPs): a review. Hum Genet. 1994;94:319–330.CrossRefGoogle ScholarPubMed
54. John, ER, Prichep, LS, Almas, M. Toward a quantitative electrophysiological classification system for psychiatry. In: Racagni, G, Brunello, N, Fukuda, T, eds. Biological Psychiatry. Vol 2. Amsterdam, Netherlands: Elsevier; 1991.Google Scholar
55. Hughes, JR, John, ER. Conventional and quantitative electroencephalography in psychiatry. J Neuropsychiatry. In press.Google Scholar
56. John, ER, Prichep, LS, Fridman, J, Easton, P. Neurometrics: computer-assisted differential diagnosis of brain dysfunction. Science. 1988;239:162–169.CrossRefGoogle Scholar
57. Freedman, R, Coon, H, Myles-Worsley, M et al. , Linkage of a neurophysiological deficit in schizophrenia to a chromosome 15 locus. Proc Natl Acad Sci USA. 1997;94:587–592.CrossRefGoogle ScholarPubMed
58. Saletu, B. The evoked potential in pharmacopsychiatry. Neuropsychobiology. 1977;3:74–104.CrossRefGoogle ScholarPubMed
59. Itil, TM, Shapiro, D, Schneider, SJ, Francis, IB. Computerized EEG as predictor of drug response in treatment resistant schizophrenics. J Nerv Ment Dis. 1981;169:629–637.CrossRefGoogle ScholarPubMed
60. Gaebel, W, Ulrich, G. Topographical distribution of absolute alpha-power in schizophrenic outpatients: ondrug responders versus nonresponders. Pharmacopsychiatry. 1986;19:222–223.CrossRefGoogle Scholar
61. Czobor, P, Volavka, J. Pretreatment EEG predicts shortterm response to haloperidol treatment. Biol Psychiatry. 1991;30:927–942.CrossRefGoogle ScholarPubMed
62. Czobor, P, Volavka, J. Quantitative EEG electroencephalogram effect of risperidone in schizophrenic patients. J Clin Psychopharmacol. 1993;13:332–342.CrossRefGoogle ScholarPubMed
63. Merlo, MCG, Kleinlogel, H, Koukkou, M. Differences in the EEG profiles of early and late responders to antipsychotic treatment in first-episode, drug-naive psychotic patients. Schizophr Res. 1998;30:221–228.CrossRefGoogle ScholarPubMed
64. Kang, J, Fitzpatrick, DF, Kline, JP, Hendricks, SE, Graber, B. Average evoked potential response augmentation/reduction: correlates and alteration with antidepressant therapy. Biol Psychiatry. 1991;29:205S.Google Scholar
65. Paige, SR, Fitzpatrick, DF, Kline, JP, Balogh, SE, Hendricks, SE. Event-related potential amplitude/intensity slopes predict response to antidepressants. Neuropsychobiology. 1994;30:197–201.CrossRefGoogle ScholarPubMed
66. Ulrich, G, Haug, JH, Faehndrich, E. Acute versus chronic EEG effects in maprotiline- and in clomipramine-treated depressive inpatients and the prediction of therapeutic outcome. J Affect Disord. 1994;32:213–217.CrossRefGoogle Scholar
67. Knott, VJ, Telner, JI, Lapierre, YD, Browne, M, Horn, ER. Quantitative EEG in the prediction of antidepressant response to imipramine. J Affect Disord. 1996;39:175–184.CrossRefGoogle ScholarPubMed
68. Staedt, J, Hunerjaeger, H, Ruether, E, Stoppe, G. Sleep cluster arousal analysis and treatment response to heterocyclic antidepressants in patients with major depression. J Affect Disord. 1998;49:221–227.CrossRefGoogle ScholarPubMed
69. Buchsbaum, MS, Lavine, R, Davis, G, Goodwin, F, Murphy, D, Post, R. Effects of lithium on somatosensory EPs and prediction of clinical response in patients with affective illness. In: Cooper, T, Gershon, S, Kline, N, Schou, M, eds. Lithium—Controversies and Unresolved Issues. Amsterdam, Netherlands: Excerpta Medica; 1979.Google Scholar
70. Hegerl, U, Wulif, H, Mueller-Oerlinghausen, B. Intensity dependence of auditory evoked potentials and clinical response to prophylactic lithium medication: a replication study. Psychiatry Res. 1992;44:181–191.CrossRefGoogle ScholarPubMed
71. Bartlett, EJ, Brodie, JD, Simkowitz, P et al. , Effect of haloperidol challenge on regional brain metabolism in neuroleptic-responsive and nonresponsive schizophrenic patients. Am J Psychiatry. 1998;155:337–343.CrossRefGoogle ScholarPubMed
72. Herrmann, WM. Electroencephalography in Drug Research. Berlin, Germany: Springer; 1982.Google Scholar
73. Stanski, DR. Pharmacodynamic modeling of anesthetic EEG drug effects. Annu Rev Pharmacol Toxicol. 1992;32:423–447.CrossRefGoogle ScholarPubMed
74. Herrmann, WM, Winterer, G. Das Pharmako-EEG und seine Bedeutung fuer die Klinische Pharmakologie. In: Kuemmerle, H-P, Hitzenberg, G, Spitzy, KH, eds. Klinische Pharmakologie. Landsberg, Germany. Ecomed; 1996.Google Scholar
75. Billard, V, Gambus, PL, Chamoun, N, Stanski, DR, Shafer, SL. A comparison of spectral edge, delta power, and bispectral index as EEG measures of alfentanil, propofol, and midazolam drug effects. Clin Pharmacol Ther. 1997;61:45–58.CrossRefGoogle Scholar
76. Bol, CJJG, Danhof, M, Stanski, DR, Mandema, JW. Pharmacokinetic-pharmacodynamic characterization of the cardiovascular, hypnotic, EEG and ventilatory responses to dexmedetomidine in the rat. J Pharmacol Exp Ther. 1997;283:1051–1058.Google Scholar
77. Sanyal, S, Van Tol, HH. Review of the role of dopamine D4 receptors in schizophrenia and antipsychotic action. J Psychiatry Res. 1997;31:219–232.CrossRefGoogle ScholarPubMed
78. Carlsson, A, Hansson, LO, Waters, N, Carlsson, ML. Neurotransmitter aberrations in schizophrenia: new perspectives and therapeutic implications. Life Sci. 1997;61:75–94.CrossRefGoogle ScholarPubMed
79. Meltzer, HY. Atypical antipsychotic drug therapy for treatment-resistant schizophrenia. In: Hirsch, SR, Weinberger, DR, eds. Schizophrenia. Oxford, England: Blackwell Science; 1995.Google ScholarPubMed
80. Winterer, G, Kloeppel, B, Heinz, A et al. , Quantitative EEG (QEEG) predicts relapse in patients with chronic alcoholism and points to a frontally pronounced cerebral disturbance. Psychiatry Res. 1998;78:101–113.CrossRefGoogle ScholarPubMed
81. Winterer, G, Ziller, M, Kloeppel, B, Heinz, A, Schmidt, LG, Herrmann, WM. Analysis of quantitative EEG with artificial neural networks and discriminant analysis: a methodological comparison. Neuropsychobiology. 1998;37:41–48.CrossRefGoogle ScholarPubMed
82. Bauer, LO. Electroencephalographic and autonomic predictors of relapse in alcohol-dependent patients. Alcohol Clin Exp Res. 1994;18:755–760.CrossRefGoogle ScholarPubMed
83. Glenn, SW, Sinha, R, Parsons, OA. Electrophysiological indices predict resumption of drinking in sober alcoholics. Alcohol. 1993;10:89–95.CrossRefGoogle ScholarPubMed
84. Gillin, JC, Smith, TL, Irwin, M, Butters, N, Demodena, A, Schuckit, M. Increased pressure for rapid eye movement sleep at time of hospital admission predicts relapse in nondepressed patients with primary alcoholism at 3-month follow-up. Arch Gen Psychiatry. 1994;51:189–197.CrossRefGoogle ScholarPubMed
85. Bauer, LO. Frontal P300 decrements, childhood conduct disorder, family history, and the predicton of relapse among abstinent cocaine abusers. Drug Alcohol Depend. 1997;44:1–10.CrossRefGoogle Scholar
86. Gabrielli, WF, Mednick, SA, Volavka, J. Electroencephalograms in children of alcoholic fathers. Psychophysiology. 1982;19:404.CrossRefGoogle ScholarPubMed
87. Propping, P. Pharmacogenetics of alcohol's CNS effects: implications for the etiology of alcoholism. Pharmacol Biochem Behav. 1983;18:549–553.CrossRefGoogle ScholarPubMed
88. Begleiter, H, Porjesz, B. Potential biological markers in individuals at high risk for developing alcoholism. Alcohol Clin Exp Res. 1988;12:488–493.CrossRefGoogle ScholarPubMed
89. Enoch, M-A, Rohrbaugh, JW, Davis, EZ et al. , Relationship of genetically transmitted alpha EEG traits to anxiety disorders and alcoholism. Am J Med Genet. 1995;60:400–408.CrossRefGoogle ScholarPubMed
90. Begleiter, H, Porjesz, B, Reich, T et al. , Quantitative trait loci analysis of human event-related brain potentials: P3 voltage. Electroencephalogr Clin Neurophysiol. 1998;108:244–250.CrossRefGoogle ScholarPubMed
91. Fleming, AMM, Guthrie, A. The electroencephalogram, psychological testing and other investigations in abstinent alcoholics: a longitudinal study. In: Begleiter, H, ed. Biological Effects of Alcoholism. New York, NY: Plenum Press; 1980.Google Scholar
92. Pollock, VE, Schneider, LS, Zemansky, MF, Gleason, RP, Pawluczyk, S. Topographic quantitative EEG amplitude in recovered alcoholics. Psychiatry Res. 1992;45:25–32.CrossRefGoogle ScholarPubMed
93. Vogel, F, Schalt, E, Krueger, J, Propping, P, Lehnert, KF. The electroencephalogram (EEG) as a research tool in human behavior genetics: psychological examinations in healthy males with various inherited EEG variants: I. Rationale of the study, material methods, heritability of test parameters. Hum Genet. 1979;47:1–45.CrossRefGoogle Scholar
94. Steinlein, O, Anokhin, A, Yping, M, Schalt, E, Vogel, F. Localization of a gene for the human low-voltage EEG on 20q and genetic heterogeneity. Genomics. 1992;12:69–73.CrossRefGoogle ScholarPubMed
95. Steinlein, O, Fischer, C, Keil, R, Smigrodzki, R, Vogel, F. D2S19, linked to low voltage EEG, benign neonatal convulsions, and Fanconi anemia, maps to a region of enhanced recombination and is localized between CpG islands. Hum Mol Genet. 1993;1:325–329.CrossRefGoogle Scholar
96. Seeck, M, Lazeyras, F, Michel, CM et al. , Non-invasive epileptic focus localization using EEG-triggered functional MRI and electromagnetic tomography. Electroencephalogr Clin Neurophysiol. 1998;106:508–512.CrossRefGoogle ScholarPubMed
97. Grimm, C, Schreiber, M, Kristeva-Feige, R, Mergner, T, Hennig, J, Lucking, CH. A comparison between electrical source localisation and fMRI during somatosensory stimulation. Electroencephalogr Clin Neurophysiol. 1998;106:22–29.CrossRefGoogle ScholarPubMed
98. Thatcher, RW, Biver, C, McAlaster, R, Camacho, M, Salazar, A. Biophysical linkage between MRI and EEG amplitude in closed head injury. Neuroimage. 1998;7:352–367.CrossRefGoogle ScholarPubMed
99. Krieger, D, Sclabassi, RJ, Coppola, R, Nakamura, R. Spatiotemporal cortical patterns evoked in monkeys by a discrimination task. J of Cognition and Neuroscience. 1991;3:242–251.CrossRefGoogle ScholarPubMed
100. Shagass, C, Roemer, RA, Straumanis, JJ. Relationship between psychiatric diagnosis and some-quantitative EEG variables. Arch Gen Psychiatry. 1982;39:1433–1435.CrossRefGoogle ScholarPubMed
101. Pascual-Marqui, RD, Koukkou, M, Lehmann, D. Hyperfrontality in never-treated first-break schizophrenics demonstrated by low resolution electromagnetic tomography (LORETA). Electroencephalogr Clin Neurophysiol. 1997;103:92.CrossRefGoogle Scholar
102. Gold, S, Christian, B, Arndt, S et al. , Functional MRI statistical software packages: a comparative analysis. Human Brain Mapping. 1998;6:73–84.3.0.CO;2-H>CrossRefGoogle ScholarPubMed
103. Press, WH, Teukolsky, SA, Vetterling, WT, Flannery, BP. Numerical Recipes in C: The Art of Scientific Computing. Cambridge, Mass: Cambridge University Press; 1992.Google Scholar
104. Bandettini, PA, Jesmanowicz, A, Wong, EC, Hyde, JS. Processing strategies for time-course data sets in functional MRI of the human brain. Magn Reson Med. 1993;30:161–173.CrossRefGoogle ScholarPubMed
105. Friston, KJ, Frith, CD, Liddle, PF, Frackowiak, RS. Functional connectivity: the principle-component analysis of large (PET) data sets. J Cereb Blood Flow Metab. 1993;13:5–14.CrossRefGoogle Scholar
106. Makeig, S, Jung, T-P, Bell, AJ, Gharemani, D, Sejnowski, TJ. Blind separation of auditory event-related brain responses into independent components. Proc Natl Acad Sci U S A. 1997;94:10979–10984.CrossRefGoogle ScholarPubMed