Skip to main content
Log in

Dynamical Systems and Depression: A Framework for Theoretical Perspectives

  • Published:
Acta Biotheoretica Aims and scope Submit manuscript

Abstract

The theory of dynamical systems allows one to describe the change in a system's macroscopic behavior as a bifurcation in the underlying dynamics. We show here, from the example of depressive syndrome, the existence of a correspondence between clinical and electro-physiological dimensions and the association between clinical remission and brain dynamics reorganization (i.e. bifurcation). On the basis of this experimental study, we discuss the interest of such results concerning the question of normality versus pathology in psychiatry and the relationship between mind and brain.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

REFERENCES

  • Abarbanel, H.I.D., R. Brown, J.J. Sidorowich and L.S. Tsimring (1993). The analysis of observed chaotic data in physical systems. Review of Modern Physics 65: 1331-1392.

    Google Scholar 

  • Amit, D. (1989). Modelling brain functions. The world of attractor neural networks. Cambridge MA, Cambrige University Press.

    Google Scholar 

  • Babloyantz, A. and A. Destexhe (1986). Low dimensional chaos in an instance of epilepsy. Proceedings of National Academy of Sciences. USA 83: 3513-3517.

    Google Scholar 

  • Braitenberg, V. and A. Schüz (1991). Anatomy of the cortex. Statistics and geometry. Berlin, Springer-Verlag.

    Google Scholar 

  • Canguilhem (1966). Le normal et le pathologique. Paris, Presses Universitaires de France.

    Google Scholar 

  • Carlson-Sabelli, L, H.C. Sabelli, J. Zbilut, M. Patel, J. Messer, K. Walthall, C. Tom, P. Fink, A. Sugerman and A. Zdanovics (1994). How the heart informs about the brain: A process analysis of the electrocardiogram. In R. Trappl (Ed.) Cybernetics and systems-Proceedings European Meeting on Cybernetics and Systems research, Vienna, (Vol. 2: 1031-1038). Singapore: World Scientific.

    Google Scholar 

  • Clark, A (1989). Microcognition, Philosophy, cognitive science, and parallel distributed processing. Cambridge MA, The MIT Press.

    Google Scholar 

  • Claustrat, B., J. Brun, M. David, G. Sassolas, and G. Chazot (1992). Melatonin and Jet lag: confirmatory result using a simplified protocol. Biological Psychiatry 38(2): 705-711.

    Google Scholar 

  • Devereux, G. (1977). Normal et Anormal. In Essai d'Ethnopsychiatrie Générale, Paris, Gallimard.

    Google Scholar 

  • Foucault, M. (1954). Maladie mentale et psychologie, Paris, PUF, 1997.

    Google Scholar 

  • Foucault, M. (1972). Histoire de la folie à l'âge classique, Paris, Gallimard.

    Google Scholar 

  • Glass, L. and M.C. Mackey (1979). Pathological conditions resulting from instabilities in physiological control systems. Annals of NY Academy of Sciences 316: 214-235.

    Google Scholar 

  • Globus, G.G. and J.P. Arpaïa (1994). Psychiatry and the new dynamics. Biological Psychiatry 35: 352-364.

    Google Scholar 

  • Goldstein, K. (1933). L'analyse de l'aphasie et l'étude de l'essence du langage, Journal de Psychologie, p. 430.

  • Grassberger, P., T. Schreiber and C. Schaffracth (1991). Nonlinear time series analysis. International Journal of Bifurcation and Chaos 1: 521-547.

    Google Scholar 

  • Guckenheimer, J. and Holmes (1986). Nonlinear oscillations, dynamical systems and bifurcations of vector fields. Springer New York.

  • Hoffmann, R.E. (1987). Computer simulations of neural information processing and the schizophrenia-mania dichotomy. Archives of General Psychiatry 44: 178-188.

    Google Scholar 

  • Hollister, L.E., K.L. Davis and B.M. Davis (1980). Hormones in the treatment of psychiatric disorders. In: Kreiger and Huges, Eds. Neuro-endocrinology, Sunderland MA: Sinauer, pp. 167-175

    Google Scholar 

  • Hopfield, J.J. (1982). Neural networks and physical systems with emergent collective computational abilities. Proceedings of National Academy of Sciences 79: 2554-2558.

    Google Scholar 

  • Horowitz, M.J. (1987). States of mind: configurational analysis of individual psychology. New York: Plenum.

    Google Scholar 

  • Kantz, H. and T. Schreiber (1997). Nonlinear time series analysis. Cambridge: Cambridge University Press.

    Google Scholar 

  • Köhler, W. (1940). The dynamics in psychology. New York, Liveright.

    Google Scholar 

  • Mackey, M.C. and L. Glass (1977). Oscillation and chaos in physiological control systems. Science 197: 287-289.

    Google Scholar 

  • Mackey, M.C. and J.G. Milton (1987). Dynamical Disease. Annals of NY Academy of Sciences 504: 16-32.

    Google Scholar 

  • Milton, J.G. and D. Black (1995). Dynamic diseases in neurology and psychiatry. Chaos 5: 8-13.

    Google Scholar 

  • Nandrino, J.L., L. Pezard, J. Martinerie, F. El Massioui, B. Renault, R. Jouvent, J.-F. Allilaire and D. Widlöcher (1994). Decrease of complexity in EEG as a symptom of depression. NeuroReport 5: 528-530.

    Google Scholar 

  • Nunez, P. L. (1990). Localization of brain activity with electroencephalography. In S. Sato (Ed.) Magnetoencephalography. Advances in Neurology Vol. 54 (pp. 39-65). New York: Raven Press.

    Google Scholar 

  • Ott, E., T. Sauer and J.A. Yorke eds (1994). Coping with chaos-Analysis of chaotic data and the exploitation of chaotic systems. New-York, Wiley and Son.

    Google Scholar 

  • Osborne, A.R. and A. Provenzale (1989). A finite correlation dimension for stochastic system with power-law spectra. Physica D 35: 357-381.

    Google Scholar 

  • Petitot-Cocorda, J. (1992). Physique du sens. De la théorie des singularités aux structures sémio-narratives. Paris, Editions du CNRS.

    Google Scholar 

  • Pezard, L., J.-L. Nandrino, B. Renault, F. El Massioui, J.-F. Allilaire, J. Müller, F.J. Varela and J. Martinerie (1996a). Depression as a dynamical disease. Biological Psychiatry 39: 991-999.

    Google Scholar 

  • Pezard, L., J. Martinerie, J. Müller, F.J. Varela and B. Renault (1996b). Entropy quantification of human brain spatio-temporal dynamics. Physica D 96: 344-354.

    Google Scholar 

  • Pezard, L., J. Martinerie, F. Breton, J.-C. Bourzeix and B. Renault (1994). Nonlinear forecasting measurements of multichannel EEG dynamics. Electroencephalography and Clinical Neurophysiology 91: 383-391.

    Google Scholar 

  • Pijn, J.P., J. Van Neerven, A. Noest and F.H. Lopez Da Silva (1991). Chaos or noise in EEG signals: dependence on state and brain state. Electroencephalography and Clinical Neurophysiology 79: 371-381.

    Google Scholar 

  • Prichard, D. and J. Theiler (1994). Generating surrogate data for time series with several simultaneous measured variables. Physical Review Letter 73: 951-954.

    Google Scholar 

  • Rapp, P.E., A.M. Albano, T.I. Schmah and L.A. Farwell (1993): Filtered noise can mimic low dimensional chaotic attractors. Physical Review E 47: 2289-2297.

    Google Scholar 

  • Rapp, P.E., T.R. Bashore, J.M. Martinerie, A.M. Albano, I.D. Zimmerman and A.I. Mees (1989). Dynamics of brain electrical activity. Brain Topography 2: 99-118.

    Google Scholar 

  • Rechtman, R. and F. Raveau (1993). Fondements anthropologiques de l'ethnopsychiatrie, Encyclopédie Médico-Chirurgicale. Psychiatrie 37(715), A-10.

    Google Scholar 

  • Sabelli, H.C. and L. Carlson-Sabelli (1993). Chaos theory in psychology and medecine: mathematical priority and psychological supremacy as theory, method and mission. The social Dynamicist 4(3): 1-4.

    Google Scholar 

  • Searle, J. (1992). The rediscovery of mind. Cambridge Mass., The MIT Press Trad. fr. Tiercelin C, 1995, Paris, Gallimard.

    Google Scholar 

  • Theiler, J., B. Galdrikian, A. Longtin, S. Eubank and J.D. Farmer (1992). Using surrogate data to detect nonlinearity in time series. In: Casdagli and Eubank editors. Nonlinear Modeling and Forecasting. Reading, M.A.: Addison-Wesley, pp. 163-188.

    Google Scholar 

  • Thom, R. (1977). Stabilité Structurelle et Morphogenèse. Essai d'une théorie générale des modèles. Paris, InterEditions.

    Google Scholar 

  • Thom, R. (1988). Esquisse d'une sémiophysique, Paris, InterEditions.

    Google Scholar 

  • Von Zerssen D., D.M. Koeller and E.R. Rey (1970). Die Befindlichkeits Skala (BfS), ein einfaches Instrument zur Objectivierung von Befindlichkeitsstörungen, insbesondere im Rahmen von Längssmittuntersuchungen. Arzneim-Forsch 20: 915-918.

    Google Scholar 

  • Varela, F.J., E. Thompson and E. Rosch (1991). The Embodied mind. MIT Press, Cambridge, London.

    Google Scholar 

  • Wehr, T.A. and F.K. Goodwin (1979). Rapid cycling in manic-depressive induced by tricyclic antidepressant. Archives of General Psychiatry 36: 555-559.

    Google Scholar 

  • Widlöcher, D. (1986). La Thérapeutique comme une contrainte. Etudes psychothérapeutiques 66: 247-251.

    Google Scholar 

  • Zeeman, E.C. (1976). Brain Modelling. Springer Lecture Notes in Mathematics 525: 367-372.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Thomasson, N., Pezard, L. Dynamical Systems and Depression: A Framework for Theoretical Perspectives. Acta Biotheor 47, 209–218 (1999). https://doi.org/10.1023/A:1002686604968

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1002686604968

Navigation