Chaos and Complexity: Can It Help Us to Understand Mood and Behavior?

WHEN A disaster such as the bombing of the federal building in Oklahoma City occurs, many people wonder why psychiatrists, law officials, friends, and relatives are not more capable of accurately predicting human behavior. Not only during periods of disaster but also in day-to-day practice, psychiatrists are constantly faced with life-defining decisions based on the accurate Prediction of behavior. One of the most common and important decisions facing psychiatrists treating very ill patients is predicting if or when Patients will be dangerous to themselves or to others. While great strides have been made in the diagnosis and treatment of severe mental illness, few models have directly addressed the issue of predictability of behavior. Gottschalk et al 1 address this issue from a new theoretical approach. The article, in part, challenges us to question whether the laws governing complex physical systems may help us better Predict the fluctuations in mood states associated

[1]  Ralph Abraham,et al.  A Visual Introduction to Dynamical Systems Theory for Psychology , 1990 .

[2]  F. Goodwin,et al.  MANIC-DEPRESSIVE PATIENTS MAY BE SUPERSENSITIVE TO LIGHT , 1981, The Lancet.

[3]  A. Mandell Non-equilibrium behavior of some brain enzyme and receptor systems. , 1984, Annual review of pharmacology and toxicology.

[4]  M. Mitchell Waldrop,et al.  Complexity : the emerging science and the edge of order and chaos , 1992 .

[5]  L. Glass,et al.  Oscillation and chaos in physiological control systems. , 1977, Science.

[6]  W. Pritchard,et al.  Measuring chaos in the brain: a tutorial review of nonlinear dynamical EEG analysis. , 1992, The International journal of neuroscience.

[7]  A. Goldberger,et al.  Loss of 'complexity' and aging. Potential applications of fractals and chaos theory to senescence. , 1992, JAMA.

[8]  A Gottschalk,et al.  Evidence of chaotic mood variation in bipolar disorder. , 1995, Archives of general psychiatry.

[9]  Theiler,et al.  Generating surrogate data for time series with several simultaneously measured variables. , 1994, Physical review letters.

[10]  Theiler,et al.  Spurious dimension from correlation algorithms applied to limited time-series data. , 1986, Physical review. A, General physics.

[11]  D. Kupfer,et al.  Biological rhythms and depression: The role of zeitgebers and zeitstorers , 1993 .

[12]  N. Packard,et al.  POWER SPECTRA AND MIXING PROPERTIES OF STRANGE ATTRACTORS , 1980 .

[13]  E. Lorenz Deterministic nonperiodic flow , 1963 .

[14]  Arnold J. Mandell,et al.  Dynamical systems in psychiatry: Now what? , 1992, Biological Psychiatry.

[15]  D. Rubinow,et al.  Conditioning and Sensitisation in the Longitudinal Course of Affective Illness , 1986, British Journal of Psychiatry.

[16]  L. Glass,et al.  From Clocks to Chaos: The Rhythms of Life , 1988 .

[17]  G. Globus,et al.  Psychiatry and the new dynamics , 1994, Biological Psychiatry.

[18]  P. Jauhar,et al.  Psychiatric Morbidity and Time Zone Changes: A Study of Patients from Heathrow Airport , 1982, British Journal of Psychiatry.

[19]  P E Rapp,et al.  A guide to dynamical analysis , 1994, Integrative physiological and behavioral science : the official journal of the Pavlovian Society.

[20]  J. Yorke,et al.  Dimension of chaotic attractors , 1982 .

[21]  F. Goodwin Manic-Depressive Illness , 1990 .

[22]  B A Huberman,et al.  Chaotic behavior in dopamine neurodynamics. , 1984, Proceedings of the National Academy of Sciences of the United States of America.

[23]  A Garfinkel,et al.  Controlling cardiac chaos. , 1992, Science.

[24]  P. Grassberger,et al.  Measuring the Strangeness of Strange Attractors , 1983 .

[25]  Stewart W. Johnson,et al.  Observatories on the moon , 1990 .

[26]  M. Jiménez-Montaño,et al.  Toward a quantitative characterization of patient-therapist communication. , 1991, Mathematical biosciences.

[27]  Robert M. May,et al.  Simple mathematical models with very complicated dynamics , 1976, Nature.

[28]  Albano,et al.  Filtered noise can mimic low-dimensional chaotic attractors. , 1993, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[29]  A Garfinkel,et al.  Nonlinear analysis of EEG sleep states. , 1991, Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology.

[30]  James Theiler,et al.  Using surrogate data to detect nonlinearity in time series , 1991 .

[31]  James Gleick Chaos: Making a New Science , 1987 .

[32]  Bruce J. West,et al.  Chaos and fractals in human physiology. , 1990, Scientific American.

[33]  W. Freeman,et al.  Chaos in psychiatry , 1992, Biological Psychiatry.

[34]  D. Kupfer,et al.  Effects of lithium on sleep in mania , 1989, Biological Psychiatry.

[35]  D J Kupfer,et al.  Polysomnographic characteristics of young manic patients. Comparison with unipolar depressed patients and normal control subjects. , 1992, Archives of general psychiatry.

[36]  James Theiler,et al.  On the evidence for low-dimensional chaos in an epileptic electroencephalogram , 1995 .

[37]  W. Freeman,et al.  How brains make chaos in order to make sense of the world , 1987, Behavioral and Brain Sciences.

[38]  Alfonso M Albano,et al.  Phase-randomized surrogates can produce spurious identifications of non-random structure , 1994 .

[39]  John Horgan,et al.  From Complexity to Perplexity , 1995 .

[40]  B H Jansen,et al.  Quantitative analysis of electroencephalograms: is there chaos in the future? , 1991, International journal of bio-medical computing.

[41]  R. Abraham,et al.  Dynamics--the geometry of behavior , 1983 .

[42]  D. Kupfer,et al.  Electroencephalographic sleep in mania. , 1988, Archives of general psychiatry.

[43]  A. Garfinkel A mathematics for physiology. , 1983, The American journal of physiology.