Institute for Response-Genetics (e.V.), University of Zurich

EEG Spectral Patterns

Brain waves are attributed to electrical activities of the brain which are manifest as alternating potential differences at the scalp surface. When acquired through scalp electrodes, such potential differences result in time-continuous signals termed electroencephalogram (EEG). From a physical point of view, it is opportune to model the wave-like qualities of EEG as a finite sum of harmonic oscillations at discrete vibration rates triggered by a central pace-maker. Hence, brain-waves can analoguously be interpreted like sound waves in acoustics which consist of a fundamental oscillation superimposed by higher harmonics. Each of these partial tones is uniquely characterized by 2 quantities, its frequency ("pitch") and its amplitude ("loudness"). In terms of this model, brain-waves are composed of a series of "partial tones" ranging in frequency between 0.25Hz and 64Hz (7 octaves), whereby the "tonal composition" essentially depends on the state of consciousness, such as wakefulness or sleep stages.

Characteristic Fluctuations

The fluctuations of EEG partial tones display marked between-subject differences together with a high within-subject stability over time. To quantify these characteristic fluctuations we have developed the concept of "spectral patterns" which generalizes the notion "spectrum" in such a way that spectral intensities are regarded as fluctuating rather than being fixed-valued, thus incorporating the non-stationary nature of EEG time series into our model.

References

Stassen HH, Bachmann S, Bridler R, Cattapan K, Herzig D, Schneeberger A, Seifritz E. Inflammatory Processes linked to Major Depression and Schizophrenic Disorders and the Effects of Polypharmacy in Psychiatry: Evidence from a longitudinal Study of 279 Patients under Therapy. Eur Arch Psychiatry Clin Neurosci. 2021; 271(3): 507-520 [get the article]

Braun S, Bridler R, Müller N, Schwarz MJ, Seifritz E, Weisbrod M, Zgraggen A, Stassen HH: Inflammatory Processes and Schizophrenia: Two Independent Lines of Evidence from a Study of Twins Discordant and Concordant for Schizophrenic Disorders. Eur Arch Psychiatry Clin Neurosci 2017; 267: 377-389 [get the article]

Braun S, Bridler R, Müller N, Schwarz MJ, Seifritz E, Weisbrod M, Zgraggen A, Stassen HH: Inflammatory Processes and Schizophrenia: Two Independent Lines of Evidence From a Study of Twins Discordant and Concordant for Schizophrenic Disorders. Neuropsychopharmacology 2016; 41: S414–S415

Stassen HH, Delfino JP, Kluckner VJ, Lott P, Mohr C: Vulnerabilität und psychische Erkrankung. Swiss Archives of Neurology and Psychiatry 2014; 165(5): 152-157

Stassen HH, Angst J, Hell D, Scharfetter C, Szegedi A: Is there a common resilience mechanism underlying antidepressant drug response? Evidence from 2'848 patients. J Clin Psychiatry 2007; 68(8): 1195-1205

Buckelmüller J, Landolt HP, Stassen HH, Achermann P: Trait-like individual differences in the human sleep EEG. Neuroscience 2006; 138: 351-356

Weisbrod M, Hill H, Sauer H, Niethammer R, Guggenbühl S, Stassen HH: Nongenetic pathologic developments of brain-wave patterns in monozygotic twins discordant and concordant for schizophrenia. Am J Med Genetics B 2004; 125: 1-9

Stassen HH: EEG and evoked potentials. In: D. Cooper (ed) Nature Encyclopedia of the Human Genome. Nature Publishing Group, London 2003; 3: 266-269

Umbricht D, Koller R, Schmid L, Skrabo A, Grübel C, Huber T, Stassen HH: How specific are deficits in mismatch negativity generation to schizophrenia? Biol Psychiatry 2003; 53: 1120-1131

Dünki RM, Schmid GB, Stassen HH: Intraindividual specificity and stability of the human EEG: Linear vs. nonlinear approaches. Meth Inform Med 2000; 39: 78-82

Stassen HH, Coppola R. Torrey EF, Gottesman II, Kuny S, Rickler KC, Hell D: EEG differences in monozygotic twins discordant and concordant for schizophrenia. Psychophysiology 1999; 36,1: 109-117

Stassen HH, Bomben G, Hell D: Familial brain wave patterns: study of a 12 sib family. Psychiat Genetics 1998; 8: 141-153

Dünki RM, Schmid GB, Scheidegger P, Stassen HH, Bomben G, Propping P: Reliable computer-assisted classification of the EEG: EEG variants in index cases and their first-degree relatives. Am J Med Genetics B 1996; 67,1: 1-8

Kaprio J, Buchsbaum M, Gottesman II, Heath A, Körner J, Kringlen E, McGuffin P, Propping P, Rietschel M, Stassen HH: What can twin studies contribute to the understanding of adult psychopathology? In: T.J. Bouchard jr. and P. Propping: Twins as a tool for behavioral genetics. Chichester: John Wiley & Sons, Dahlem Workshop Reports, Life Sciences Research Report 1993; 53: 287-299

Stassen HH, Lykken DT, Propping P: Zwillingsuntersuchungen zur Genetik des normalen Elektroenzephalogramms. In: P. Baumann (ed): Biologische Psychiatrie der Gegenwart, Wien: Springer 1993, 139-144

Stassen HH, Lykken DT, Propping P, Bomben G: Genetic determination of the human EEG (survey of recent results from twins reared together and apart). Human Genetics 1988; 80: 165-176

Stassen HH, Lykken DT, Bomben G: The within-pair similarity of twins reared apart. Eur Arch Psychiatr Neurol Sci 1988; 237: 244-252

Stassen HH, Bomben G, Propping P: Genetic aspects of the EEG: an investigation into the within-pair similarity of monozygotic and dizygotic twins with a new method of analysis. Electroenceph clin Neurophysiol 1987; 66: 489-501

Stassen HH: The similarity approach to EEG analysis. Meth Inform Med 1985; 24: 200-212

Stassen HH: Computerized recognition of persons by EEG spectral patterns. Electroenceph clin Neurophysiol 1980; 49: 190-194

Institute for Response-Genetics (e.V.)

Chairman: Prof. Dr. Hans H. Stassen

Psychiatric Hospital (KPPP), University of Zurich

EEG Spectral Patterns

Characteristic Fluctuations

References

EEG sleep pattern of a male proband: the variability of spectral intensities is plotted on log proportional sclaes along the vertical axis at a frequency resolution of 1/6-tone over 5 octaves. The pattern encompasses theta- and flat alpha-waves superimposed to delta-activity.