Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-06T09:44:06.720Z Has data issue: false hasContentIssue false
  • English
  • Français

Psychiatric Diagnostic Discriminations with Combinations of Quantitative EEG Variables

Published online by Cambridge University Press:  29 January 2018

Charles Shagass ,
Richard A. Roemer ,
John J. Straumanis  and
Richard C. Josiassen
Charles Shagass*
Affiliation:
Temple University Medical School and Philadelphia Psychiatric Center, Philadelphia, Pennsylvania 19131, USA
Richard A. Roemer
Affiliation:
Temple University Medical School and Philadelphia Psychiatric Center, Philadelphia, Pennsylvania 19131, USA
John J. Straumanis
Affiliation:
Temple University Medical School and Philadelphia Psychiatric Center, Philadelphia, Pennsylvania 19131, USA
Richard C. Josiassen
Affiliation:
Temple University Medical School and Philadelphia Psychiatric Center, Philadelphia, Pennsylvania 19131, USA
*
∗Correspondence.
Get access Rights & Permissions [Opens in a new window]

Summary

The possible psychiatric diagnostic utility of certain quantitative EEG measures was evaluated by further analysis of previously reported data from 242 unmedicated patients and 94 non-patients. Time series of amplitude, frequency and wave symmetry measures for 12-lead EEGs (eyes closed and open) were factor analyzed across leads. Factor scores meeting specified criteria in multivariate analyses were entered into discriminant analyses comparing pairs of the following groups: non-patients, neurotics, personality disorders, overt schizophrenics, latent schizophrenics, major depressives and manics. The following discriminations were obtained with at least 50 per cent sensitivity, and diagnostic confidence rates from 69 to 92 per cent: (a) non-psychotic patients (neuroses, personality disorders) from overt schizophrenics, latent schizophrenics or manics; (b) major depressives from latent schizophrenics or manics; (c) non-patients from schizophrenics (overt and latent), depressives or manics. Most discriminations were replicable in split-half analyses. Possible utility of EEG measures in differential diagnosis is supported.

Type
Papers
Information
The British Journal of Psychiatry , Volume 144 , Issue 6 , June 1984 , pp. 581 - 592
Copyright
Copyright © 1984 The Royal College of Psychiatrists 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Baldessarini, R. J., Finklestein, S. & Arana, G. W. (1983) The predictive power of diagnostic tests and the effects of prevalence of illness. Archives of General Psychiatry, 40, 569–73.Google Scholar
Cooley, W. W. & Lohnes, P. R. (1971) Multivariate Data Analysis. New York: Wiley.Google Scholar
Étevenon, P., Peron-Magnan, P., Rioux, P., Pidoux, B., Bisserbe, C., Verdeaux, G. & Deniker, P. (1981) Schizophrenia assessed by computerised EEG. Advances in Biological Psychiatry, 6, 29–34.Google Scholar
Feighner, J. P., Robins, E., Guze, S. B., Woodruff, R. A., Winokur, G. & Munoz, R. (1972) Diagnostic criteria for use in psychiatric research. Archives of General Psychiatry, 26, 57–63.Google Scholar
Giannitrapani, D. & Kayton, L. (1974) Schizophrenia and EEG spectral analysis. Electroencephalography and Clinical Neurophysiology, 36, 377–86.CrossRefGoogle ScholarPubMed
Goldstein, L., Murphree, H. B., Sugerman, A. A., Pfeiffer, C. C. & Jenney, É. H. (1963) Quantitative electroencephalographic analysis of naturally occurring (schizophrenic) and drug-induced psychotic states in human males. Clinical and Pharmacologic Therapies, 4, 10–21.Google Scholar
Greenhouse, S. W. & Geisser, S. (1959) On methods in the analysis of profile data. Psychometrika, 24, 95–112.Google Scholar
Gunderson, J. G., Siever, L. J. & Spaulding, E. (1983) The search for a schizotype—Crossing the border again. Archives of General Psychiatry, 40, 15–22.Google Scholar
Helzer, J. E., Brockington, I. F. & Kendell, R. E. (1981) Predictive validity of DSM III and Feighner definitions of schizophrenia. Archives of General Psychiatry, 38, 791–797.Google Scholar
Hoch, P. & Polatin, P. (1949) Pseudoneurotic forms of schizophrenia. Psychiatric Quarterly, 23, 248–76.Google Scholar
Hurst, L. A., Mundy-Castle, A. C. & Beerstecher, D. M. (1954) The electroencephalogram in manic-depressive psychosis. Journal of Mental Science, 100, 220–40.Google Scholar
Itil, T. M., Saletu, B. & Davis, S. (1972) EEG findings in chronic schizophrenics based on digital computer period analysis and analog power spectra. Biological Psychiatry, 5, 1–13.Google ScholarPubMed
Kemali, D., Vacca, L., Marciano, F., Nolfe, G. & Iorio, G. (1981) CEEG findings in schizophrenics, depressives, obsessives, heroin addicts and normals. Advances in Biological Psychiatry, 6, 17–28.Google Scholar
Kirk, R. E. (1968) Experimental Design: Procedures for the Behavioral Sciences. Belmont, Massachusetts: Brooks/Cole.Google Scholar
Lifshitz, K. & Gradijan, J. (1972) Relationships between measures of the coefficient of variation of the mean absolute EEG voltage and spectral intensities in schizophrenic and control subjects. Biological Psychiatry, 5, 149–163.Google Scholar
Lifshitz, K. & Gradijan, J. (1974) Spectral evaluation of the electroencephalogram: Power and variability in chronic schizophrenics and control subjects. Psychophysiology, 11, 479–90.Google Scholar
Marjerrison, G., Krause, A. E. & Keogh, R. P. (1968) Variability of the EEG in schizophrenia: Quantitative analysis with a modulus voltage integrator. Electroencephalography and Clinical Neurophysiology, 24, 35–41.Google Scholar
Matousek, M., Capone, C. & Okawa, M. (1981) Measurement of the inter-hemispheral differences as a diagnostic tool in psychiatry. Advances in Biological Psychiatry, 6, 76–80.Google Scholar
Morrison, D. F. (1967) Multivariate Statistical Methods. New York: McGraw Hill.Google Scholar
Overall, J. E. & Klett, C. J. (1972) Applied Multivariate Analysis. New York: McGraw Hill.Google Scholar
Perris, C. (1975) EEG techiques in the measurement of the severity of depressive syndromes. Neuropsychobiology, 1, 16–25.Google Scholar
Perris, C., von Knorring, G. L., Cumberbatch, J. & Marciano, F. (1981) Further studies of depressed patients by means of computerized EEG. Advances in Biological Psychiatry, 6, 41–9.Google Scholar
Pope, H. G., Jonas, J. M., Hudson, J. I., Cohen, B. M. & Gunderson, J. G. (1983) The validity of DSM III borderline personality disorder. A phenomenologic, family history, treatment response, and long-term follow-up study. Archives of General Psychiatry, 50, 23–30.Google Scholar
Rodin, E., Grisell, J. & Gottlieb, J. (1968) Some electrographic differences between chronic schizophrenic patients and normal subjects. In Recent Advances in Biological Psychiatry, 194–204, Vol. 10 (ed Wortis J.). New York: Plenum Press.Google Scholar
Shagass, C., Strumanis, J. J. & Overton, D. A. (1979) Correlations between psychiatric diagnosis and some quantitative EEG variables. Neuropsychobiology 5, 16–26.Google Scholar
Shagass, C., Roemer, R. A. & Straumanis, J. J. (1982) Relationships between psychiatric diagnosis and some quantitative EEG variables. Archives of General Psychiatry, 39, 1423–35.Google Scholar
Spitzer, R. L., Endicott, J. & Robins, E. (1978) Research diagnostic criteria: Rationale and reliability. Archives of General Psychiatry, 36, 773–82.Google Scholar
Volavka, J., Matousek, M. & Roubicek, J. (1966) EEG frequency analysis in schizophrenia. Acta Psychiatrica Scandinavica, 42, 237–45.Google Scholar
Volavka, J., Abrams, R., Taylor, M. A. & Reker, D. (1981) Hemispheric lateralization of fast EEG activity in schizophrenia and endogenous depression. Advances in Biological Psychiatry, 6, 72–5.CrossRefGoogle Scholar
Submit a response

eLetters

No eLetters have been published for this article.