Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-22T17:26:48.990Z Has data issue: false hasContentIssue false
  • English
  • Français

Quantitative assessment of dynamic electroencephalogram (EEG) organization as a tool for subtyping depressive syndromes

Published online by Cambridge University Press:  16 April 2020

G. Ulrich  and
U. Fürstenberg
Get access

Summary

Up until now, no subclassification of affective psychoses has been validated biologically. This follows unavoidably from a research practice of defining diagnostic subtypes in consensus conferences and only thereafter allowing their validation. There is evidence that electroencephalograms (EEG) may be a useful tool in psychiatry, provided that the relevant information is extracted.

Our EEG quantification procedure aims at an assessment of both the amount and range of variation of spontaneous changes of topographical alpha-power distribution, developing within a certain period of recording under resting conditions. Our measures were designed to characterize the dynamic organization of the EEG. This is quite obviously an eyeball evaluation but it has nevertheless been neglected in research. The study design was done retrospectively. Included were inpatients with a primary depressive disorder. Main exclusion criteria were an age older than 62 years and psychotropic drugs other than antidepressants. The psychopathology and other clinical data were routinely assessed within three days after admission by the AMDP documentation. An EEG was also routinely performed at admission. We made use of robust, generally known non-parametric statistics.

Those patients who exhibited a dynamically rigid EEG are especially prone to recurrences, have a relative late onset of their illness, and show an acute symptomatology characterized by organic-like features.

The findings lend support to our contention that the quantitative assessment of the dynamics of the EEG-Gestalt allows the delimitation of a clinically important subtype that is characterized both cross-sectionally and in long-term respects.

Keywords

quantification of dynamic rigidity in EEGsubtyping of depressive syndrome
Type
Original article
Information
European Psychiatry , Volume 14 , Issue 4 , July 1999 , pp. 217 - 229
Copyright
Copyright © Elsevier, Paris 1999

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

Abt, K. Planing controlled trials on the basis of descriptive data analysis. Statistics Med 1991; 10: 777–795.CrossRefGoogle Scholar
Akiskal, H, Bitar, AH, Puzantian, VR, Rosenthal, TL, Walker, PW. The nosological status of neurotic depression. Arch Gen Psychiatry 1978; 35: 756–766.CrossRefGoogle ScholarPubMed
Alexopoulos, GS, Meyers, BS, Young, RC, Campbell, S, Silbersweig, D, Charlson, M. Vascular depression hypothesis. Arch Gen Psychiatry 1997; 54: 915–922.CrossRefGoogle Scholar
Angst, JHow recurrent and predictable is depressive illness?In: Montgomery, SARouillon, F eds. Long-term treatment of depression. 1992 Chichester: Wiley; 113.Google Scholar
Austin, MP, Mitchell, P. The anatomy of melancholia: does frontal-subcortical pathophysiology underpin its psychomotor and cognitive manifestations? Psychol Med 1995; 25: 665–672.CrossRefGoogle ScholarPubMed
Baron, M, Mendlewicz, J, Klotz, J. Age of onset and genetic transmission in affective disorders. Acta Psychiatr Scand 1981; 64: 373–380.CrossRefGoogle ScholarPubMed
Baumann, U, Stieglitz, RDTestmanual zum AMDP. Berlin: System Springer; 1983.CrossRefGoogle Scholar
Bente, D. Das Elektroencephalogramm bei Psychosen. Befunde Probleme Hippokrates 1965; 36: 817–823.Google Scholar
Bente, D. Psychophysiologische Hypothesen zur Genese depressiver Erkrankungen Ärztl. Praxis 1975; 27: 3641–3643.Google Scholar
Bente, D. Elektroencephalographische Gesichtspunkte zum Wach-Schlaf-Verhalten und zur Chronophysiologie endogener Depressionen Arzneimittelforsch. Drug Res 1976; 26: 1058–1061.Google Scholar
Bente, DVigilanz, dissoziative Vigilanzverschiebung und Insuffizienz des Vigilitätstonus 13-28.In: Kranz, H, Heinrich, K eds. Begleitwirkungen und Miberfolge der psychiatrischen. Stuttgart: Pharmakotherapie Thieme; 1964.Google Scholar
Blanc, C, Lairy, GC. Modifications de l'EEG au cours des syndromes dépressifs. Rev Neurol 1960; 102: 371–374.Google Scholar
Brodaty, H, Harris, L, Peters, K, Wilhelm, K, Hickie, I, Boyce, P. Prognosis of depression in the elderly: a comparison with younger patients. Br J Psychiatry 1993; 163: 589–596.CrossRefGoogle ScholarPubMed
Dalack, GW, Roose, SP. Perspectives on the relationship between cardiovascular disease and affective disorder. Clin Psychiatry 1990; 51 (7 Suppl): 4–9.Google ScholarPubMed
Farmer, A, McGuffin, P. The classification of depressions. Contemporary confusion revisited. Br J Psychiatry 1989; 155: 437–443.CrossRefGoogle ScholarPubMed
Giles, DE, Jarrett, RB, Biggs, MM, Guzick, DS, Rush, AJ. Clinical predictors of recurrence in depression. Am J Psychiatry 1989; 146: 764–767.Google ScholarPubMed
Gitlin, MJ, Swendsen, J, Heller, TL, Hammen, C. Relapse and impairment in bipolar disorder. Am J Psychiatry 1995; 152: 1635–1640.Google ScholarPubMed
Grof, PSelektionskriterien für kurative und prophylaktische Lithiumbehandlung.In: Müller-Oerlinghausen, B, Greil, W, Berghöfer, A eds. Die Lithiumtherapie. Berlin: Springer; 1997.Google Scholar
Guy, W, Ban, TA. The AMDP-system. Berlin: Springer; 1982.CrossRefGoogle Scholar
Hailperin, T. Best possible inequalities for the probability of a logical function of events. Am Math Monthly 1965; 72: 343–359.CrossRefGoogle Scholar
Keller, MB, Lavori, PW, Rice, J, Coryell, W, Hirschfeld, RMA. The persistent risk of chronicity in recurrent episodes of non-bipolar major depressive disorder: a prospective follow-up. Am J Psychiatry 1986; 143: 24–28.Google Scholar
Kiloh, L, Andrews, G, Neilson, M. The long-term outcome of depressive illness. Br J Psychiatry 1988; 153: 752–757.CrossRefGoogle ScholarPubMed
Kessel, A, Holt, NF. Depression-an analysis of a follow-up study. Br J Psychiatry 1965; 111: 1143–1153.CrossRefGoogle Scholar
Krishnan, KRR. Neuroanatomic substrates of depression in elderly. J Geriatr Psychiatry Neurol 1993; 6: 39–58.CrossRefGoogle Scholar
Krishnan, KRR, Goli, V, Ellinwood, EH, France, RD, Blazer, DZ, Nemeroff, CB. Leukoencephalopathy in patients diagnosed as major depressive. Biol Psychiatry 1988; 23: 519–522.CrossRefGoogle ScholarPubMed
Lee, AS, Murray, RM. The long-term outcome of maudsley depressives. Br J Psychiatry 1988; 153: 741–751.CrossRefGoogle ScholarPubMed
Lesser, IM, Hill-Gutierrez, E, Miller, RL, Boone, KB. Late-onset depression with white matter lesions. Psychosomatics 1993; 34: 364–367.CrossRefGoogle ScholarPubMed
Loomis, AL, Harvey, EN, Hobart, GH. Cerebral states during sleep, as studied by human brain potentials. Exp Psychol 1937; 21: 127–144.CrossRefGoogle Scholar
McKay, AP, Torbuck, AF, Shapleske, J. Neuropsychological function in manic depressive psychosis, evidence for persistent deficits in patients with chronic, severe illness. Br J Psychiatry 1995; 167: 51–57.CrossRefGoogle ScholarPubMed
O'Connell, RA, Mayo, JA, Flatow, L, Cuthbertson, B, O'Brien, B. Outcome of bipolar disorder on long-term treatment with lithium. Br J Psychiatry 1991; 159: 123–129.CrossRefGoogle ScholarPubMed
VanOs, J, Jones, P, Lewis, G, Wadsworth, M, Murray, R. Developmental precursors of affective illness in a general population birth cohort. Arch Gen Psychiatry 1997; 54: 625–631.CrossRefGoogle Scholar
Parker, G, Brotchie, H. Psychomotor change as a feature of depressive disorders: an historical overview. Aust N Z J Psychiatr 1992; 26: 146–155.CrossRefGoogle Scholar
Post, F. The management and nature of depressive illness in late life: a follow through study. Br J Psychiatry 1972; 121: 393–404.CrossRefGoogle ScholarPubMed
VanPraag, HM. Diagnosis, the rate-limiting factor of biological depression research. Neuropsychobiol 1993; 28: 107–206.Google Scholar
Prien, RF, Kupfer, DJ, Mansky, PA. Drug therapy in the prevention of recurrences in unipolar and bipolar affective disorder: report of the NIMH collaborative study group comparing lithium carbonate, imipramine, and a lithium-carbonate-imipramine combination. Arch Gen Psychiatry 1984; 41: 1096–1104.CrossRefGoogle Scholar
Rechlin, T. Decreased parameters of heart rate variation in amitriptyline treated patients: lower parameters in melancholic depression than in neurotic depression — A biological marker? Biol Psychiatry 1994; 36: 705–707.CrossRefGoogle ScholarPubMed
Roth, B. The clinical and theoretical importance of EEG rhythms corresponding to states of lowered vigilance EEG. Clin Neurophysiol 196; 13 395–399.CrossRefGoogle Scholar
Rüger, B. Das maximale Signifikanzniveau des Tests: ‘Lehne Ho ab, wenn kunter gegebenen Tests zur Ablehnung führten’. Metrika 1978; 25: 171–178.CrossRefGoogle Scholar
Sapin, LR, Berrettini, WH, Nurnberger, JI. Mediational factors underlying cognitive changes and laterality in affective illness. Biol Psychiatry 1987; 22: 979–986.CrossRefGoogle ScholarPubMed
Savard, RJ, Rey, AC, Post, RM. Halstead-Reitan category test in bipolar and unipolar affective disorders. Nerv Ment Dis 1980; 168: 297–304.CrossRefGoogle ScholarPubMed
Strian, F, Klicpera, C, Caspar, F. Autonomic activation and endogenous depression. Arch Psychiatr Nerv 1977; 223: 203–218.CrossRefGoogle ScholarPubMed
Surtees, PG, Barkley, C. Future imperfect: the long-term outcome of depression. Br J Psychiatry 1994; 164: 327–342.CrossRefGoogle ScholarPubMed
Taylor, MA. Are schizophrenia and affective disorder related? A selective literature review. Am J Psychiatry 1992; 149: 22–32.Google ScholarPubMed
Tham, A, Engelbrektson, K, Mathé, AA, Johnson, L, Olsson, E, Aberg-Wistedt, A. Impaired neurophysiological performance in euthymic patients with recurring mood disorders. Clin Psychiatry 1997; 58: 26–29.CrossRefGoogle Scholar
Ulrich, G, Brand, C. Dynamically rigid EEG and subtyping of depressive syndromes. Eur Psychiatry 1993; 8: 25–34.CrossRefGoogle Scholar
Ulrich, G, Frick, K. A new quantitative approach to the assessment of stages of vigilance as defined by spatiotemporal EEG patterning. Percept Mot Skills 1986; 62: 567–576.CrossRefGoogle ScholarPubMed
Ulrich, G, Frick, K, Stieglitz, RD. Interindividual variability of lithium-induced EEG changes in healthy volunteers. Psychiatry Res 1987; 20: 273–278.CrossRefGoogle ScholarPubMed
Ulrich, G, Herrmann, WM, Hegerl, U, Müller-Oerlinghausen, B. Effect of lithium on the dynamics of electroencephalographic vigilance in healthy subjects. J Affect Disord 1990; 20: 19–25.CrossRefGoogle ScholarPubMed
Ulrich, G, Frick, K, Lewinsky, M. Lithium and the theoretical concept of ‘dynamic restriction’: a comparison of the effects on different levels of quantitative EEG analysis. Lithium 1993; 3: 33–44.Google Scholar
Ulrich, GPsychiatrische Elektoenzephalographie. Fischer: Jena; 1994.Google Scholar
Videbech, P. MRI findings in patients with affective disorder: a meta-analysis. Acta Psychiatr Scand 1997; 96: 157–168.CrossRefGoogle ScholarPubMed
Whatmore, GB, Ellis, RM. Some neurophysiological aspects of depressed states — An electromyographic study. Arch Gen Psychiatry 1959; 1: 86–96.Google Scholar
Whatmore, GB, Ellis, RM. Further neurophysiologic aspects of depressed states – An electromyographic study. Arch Gen Psychiatry 1962; 6: 75–85.CrossRefGoogle ScholarPubMed
Winokur, G, Coryell, W, Keller, M, Endicott, J, Akiskal, HA. A prospective follow-up study of patients with bipolar and primary unipolar affective disorder. Arch Gen Psychiatry 1993; 50: 457–465.CrossRefGoogle ScholarPubMed
Winokur, G. All roads lead to depression: clinically homogenous, etiologically heterogeneous. J Affect Disord 1997; 45: 97–108.CrossRefGoogle Scholar
Young, RC, Klerman, GL. Mania in late life: focus on age of onset. Am J Psychiatry 1992; 4: 73–78.Google Scholar
Submit a response

Comments

No Comments have been published for this article.