Complex Systems and the Evolution of Mind-Brain

  • Klaus Mainzer


How can one explain the emergence of brain and mind? The chapter starts with a short history of the mind-body problem. Besides religious traditions, the concepts of mind and body held by our ancestors were often influenced by the most advanced standards in science and technology (Sect. 4.1). In the framework of complex systems the brain is modeled as a complex cellular system with nonlinear dynamics. The emergence of mental states (for instance pattern recognition, feeling, thoughts) is explained by the evolution of (macroscopic) order parameters of cerebral assemblies which are caused by nonlinear (microscopic) interactions of neural cells in learning strategies far from thermal equilibrium. Pattern recognition, for instance, is interpreted as a kind of phase transition by analogy with the evolution equations which determine pattern emergence in physics, chemistry, and biology (Sect. 4.2). In recent studies in neurobiology and cognitive psychology, scientists even speculate that the emergence of consciousness and self-consciousness depends on the production rate of “meta-cell-assemblies” as neural realizations of self-reflection. The Freudian unconscious is interpreted as a (partial) switching off of order parameters referring to certain states of attention. Even our dreams and emotions seem to be governed by nonlinear dynamics (Sect. 4.3).


Auditory Cortex Spin Glass Human Mind Learning Rule Energy Landscape 
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  1. 4.1
    Diels-Kranz: B 36Google Scholar
  2. 4.2
    Cf. Guthrie, W.K.C.: A History of Greek Philosophy vol. I: The Earlier Presocratics and the Pythagoreans. Cambridge University Press: Cambridge (1962) 349;Google Scholar
  3. Popper, K.R./Eccles, J.C.: The Self and its Brain. Springer: Berlin (1977) 161CrossRefGoogle Scholar
  4. 4.3
    Aristotle: De anima 403 b 31Google Scholar
  5. 4.4
    Plato: MenonGoogle Scholar
  6. 4.5
    Cf. Galen: Galen on Anatomical Procedures. Translation of the Surviving Books with Introduction and Notes. Oxford University Press: London (1956)Google Scholar
  7. 4.6
    Wickens, G.M: Avicenna. Scientist and Philosopher. A Millenary Symposium: London (1952)Google Scholar
  8. 4.7
    Descartes, R.: Meditations (1641). Eds. E. Haldane, G. Ross. Cambridge University Press: Cambridge (1968) 153Google Scholar
  9. 4.8
    Descartes, R.: Treatise on Man ( 1664 ). Harvard University Press: Cambridge, Mass. (1972)Google Scholar
  10. 4.9
    Spinoza, B.: EthicsGoogle Scholar
  11. 4.10
    Leibniz, G.W.: Monadology; Rescher, N.: Leibniz: An Introduction to his Philosophy. Basil Blackwell: Oxford (1979)Google Scholar
  12. 4.11
    Hume, D.: A Treatise of Human Nature (1739). Penguin: Harmondsworth (1969) 82Google Scholar
  13. 4.12
    Mainzer, K.: Kants Begründung der Mathematik und die Entwicklung von Gauß bis Hilbert. In: Akten des V. Intern. Kant-Kongresses in Mainz 1981 (ed. Funke, G. ). Bouvier: Bonn (1981) 120–129Google Scholar
  14. 4.13
    Brazier, M.A.B.: A History of Neurophysiology in the 17th and 18th Centuries. Raven: New York (1984);Google Scholar
  15. Cf. Clarke, E., O’Malley, C.D.: The Human Brain and Spinal Cord: A Historical Study illustrated by Writings from Antiquity to the Twentieth Century. University of California Press: Berkeley (1968)Google Scholar
  16. 4.14
    Helmholtz, H.v.: Schriften zur Erkenntnistheorie (eds. Hertz, P., Schlick, M. ). Berlin (1921);Google Scholar
  17. Mainzer, K.: Geschichte der Geometrie (see Note 13 Chapter 2) 172Google Scholar
  18. 4.15
    Müller, J.: Handbuch der Physiologie des Menschen. Koblenz (1835)Google Scholar
  19. 4.16
    Helmholtz, H.v.: Vorläufiger Bericht über die Fortpflanzungsgeschwindigkeit der Nervenreizung. Archiv für Anatomie, Physiologie und wissenschaftliche Medizin (1850) 71–73Google Scholar
  20. 4.17
    James, W: Psychology (Briefer Course). Holt: New York (1890) 3Google Scholar
  21. 4.18
    James, W: Psychology (see Note 17) 254Google Scholar
  22. 4.19
    James, W.: Psychology (see Note 17) Fig. 57Google Scholar
  23. 4.20
    Cf. Baron, R.J.: The Cerebral Computer. An Introduction to the Computational Structure of the Human Brain. Lawrence Erlbaum: Hillsdale N.J. (1987);Google Scholar
  24. Braitenberg, V.: Gehirngespinste. Neuroanatomie für kybernetisch Interessierte. Springer: Berlin (1973)Google Scholar
  25. 4.21
    Churchland, P.S./Sejnowski, T.J.: Perspectives in cognitive neuroscience. Science 242 (1988) 741–745.ADSCrossRefGoogle Scholar
  26. The subset of visual cortex is adapted from van Essen, D., Maunsell, J.H.R.: Two-dimensional maps of the cerebral cortex. Journal of Comparative Neurology 191 (1980) 255–281.Google Scholar
  27. The network model of ganglion cells is given in Hubel, D.H./Wiesel, T.N.: Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. Journal of Physiology 160 (1962) 106–154.Google Scholar
  28. An example of chemical synapses is shown in Kand, E.R./Schwartz J.: Principles of Neural Science. Elsevier: New York (1985)Google Scholar
  29. 4.22
    Cf. Churchland, P.M.: A Neurocomputational Perspective: The Nature of Mind and the Structure of Science. MIT Press: Cambridge, Mass., London (1989) 99Google Scholar
  30. 4.23
    Pellionisz, A.J.: Vistas from tensor network theory: A horizon from reductionalist neurophilosophy to the geometry of multi-unit recordings. In: Cotterill, R.M.J. (ed.): Computer Simulation in Brain Science. Cambridge University Press: Cambridge/New York/Sydney (1988) 44–73;CrossRefGoogle Scholar
  31. Churchland, PM.: A Neurocomputational Perspective (see Note 22) 83, 89Google Scholar
  32. 4.24
    Cf. Schwartz, E.L. (ed.): Computational Neuroscience. MIT Press: Cambridge, Mass. (1990)Google Scholar
  33. 4.25
    Cf. Churchland, P.S./Sejnowski, T.J.: The Computational Brain. MIT Press: Cambridge, Mass. (1992) 169Google Scholar
  34. 4.26
    Hebb, D.O.: The Organization of Behavior. Wiley: New York (1949) 50Google Scholar
  35. 4.27
    Kohonen, T.: Self-Organization and Associative Memory. Springer: Berlin (1989) 105;CrossRefGoogle Scholar
  36. Churchland, P.S./Sejnowski, T.J.: The Computational Brain (see Note 25 ) 54;Google Scholar
  37. Ritter, H./Martinetz, T./Schulten, K.: Neuronale Netze. Eine Einführung in die Neuroinformatik selbstorganisierender Netzwerke. Addison-Wesley: Reading, Mass. (1991) 35Google Scholar
  38. 4.28
    Hopfield, J.J.: Neural Network and physical systems with emergent collective computational abilities. Proceedings of the National Academy of Sciences 79 (1982) 2554–2558MathSciNetADSCrossRefGoogle Scholar
  39. 4.29
    Hertz, J./Krogh, A./Palmer, R.G.: Introduction to the Theory of Neural Computation. Addison-Wesley: Redwood City (1991)Google Scholar
  40. 4.30
    Serra, R./Zanarini, G.: Complex Systems and Cognitive Processes. Springer: Berlin (1990) 78CrossRefGoogle Scholar
  41. 4.31
    Hertz, J./Krogh, A./Palmer, R.G.: Introduction to the Theory of Neural Computation (see Note 29);Google Scholar
  42. Hopfield, J.J./Tank, D.W.: Computing with neural circuits: A model. Science 233 (1986) 625–633ADSCrossRefGoogle Scholar
  43. 4.32
    Ackley, D.H./Hinton, G.E./Sejnowski, T.J.: A learning algorithm for Boltzmann machines. Cognitive Science 9 (1985) 147–169CrossRefGoogle Scholar
  44. 4.33
    A mathematical elaboration of the learning algorithm for a Boltzmann machine is given in Serra, R., Zanarini, G.: Complex Systems and Cognitive Processes (see Note 30 ) 137.Google Scholar
  45. An illustration is shown in Churchland, P.S., Sejnowski, T.J.: The Computational Brain (see Note 25 ) 101Google Scholar
  46. 4.34
    Rumelhart, D.E./Zipser, D.: Feature discovery by competitive learning. In: McClelland, J.L./Rumelhart, D.E. (eds.): Parallel Distributed Processing. MIT Press: Cambridge, Mass. (1986)Google Scholar
  47. 4.35
    Kohonen, T.: Self-Organization and Associative Memory (see Note 27) 123Google Scholar
  48. 4.36
    Kohonen, T.: Self-Organization and Associative Memory (see Note 27) 125Google Scholar
  49. 4.37
    Ritter, H./Martinetz, T., Schulten, K.: Neuronale Netze (see Note 27 ) 75Google Scholar
  50. 4.38
    Suga, N./O’Neill, W.E.: Neural axis representing target range in the auditoryGoogle Scholar
  51. cortex of the mustache Bat. Science 206 (1979) 351–353;Google Scholar
  52. Ritter, H./Martinetz, T./Schulten, K.: Neuronale Netze (see Note 27 ) 88Google Scholar
  53. 4.39
    Widrow, B./Hoff, M.E.: Adaptive switching circuits. 1960 IRE WESCON Convention Record. IRE: New York (1960) 36–104Google Scholar
  54. 4.40
    Cf. Churchland, P.S./Sejnowski, T.J.: The Computational Brain (see Note 25 ) 106Google Scholar
  55. 4.41
    Rumelhart, D.E./Hinton, G.E./Williams, R.J.: Learning representations by backpropagating errors. Nature 323 (1986) 533–536;ADSCrossRefGoogle Scholar
  56. Arbib, M.A.: Brains, Machines, and Mathematics. Springer: New York (1987) 117zbMATHCrossRefGoogle Scholar
  57. 4.42
    Köhler, W: Die physischen Gestalten in Ruhe und im stationären Zustand. Vieweg: Braunschweig (1920);CrossRefGoogle Scholar
  58. Köhler, W: Jahresberichte für die ges. Physiol. und exp. Pharmakol. 3 (1925) 512–539;Google Scholar
  59. Stadler, M./Kruse, P.: The self-organization perspective in cognitive research: Historical remarks and new experimental approaches. In: Haken, H./Stadler, M. (eds.): Synergetics of Cognition. Springer: Berlin (1990) 33Google Scholar
  60. 4.43
    Cf. Churchland, P.M.: A Neurocomputational Perspective (see Note 22 ) 209Google Scholar
  61. 4.44
    Cf. Churchland, P.M.: A Neurocomputational Perspective (see Note 22 ) 211Google Scholar
  62. 4.45
    Cf. Feigl, H./criven, M./Maxwell, G. (eds.): Concepts, Theories and the Mind-Body Problem. University of Minnesota Press: Minneapolis (1958);Google Scholar
  63. Marcel, A.J./Bisiach, E. (eds.): Consciousness in Contemporary Science. Clarendon Press: Oxford (1988);Google Scholar
  64. Bieri, P.: Pain: A case study for the mind-body problem. Acta Neurochirurgica 38 (1987) 157–164;CrossRefGoogle Scholar
  65. Lycan, W.G.: Consciousness. MIT Press: Cambridge, Mass. (1987)Google Scholar
  66. 4.46
    Flohr, H.: Brain processes and phenomenal consciousness. A new and specific hypothesis. Theory & Psychology 1 (2) (1991) 248CrossRefGoogle Scholar
  67. 4.47
    von der Malsburg, C.: Self-organization of orientation sensitive cells in the striate cortex. Kybernetik 14 (1973) 85–100;CrossRefGoogle Scholar
  68. Wilshaw, D.J./von der Malsburg, C.: How patterned neural connections can be set up by self-organization. Proceedings of the Royal Society Series B 194 (1976) 431–445ADSCrossRefGoogle Scholar
  69. 4.48
    Barlow, H.B.: Single units and sensatioperceptual psychology. Perception 1 (1972) 371CrossRefGoogle Scholar
  70. 4.49
    Singer, W: The role of synchrony in neocortical processing and synaptic plasticity. In: Domany, E./Van Hemmen, L./Schulten, K. (eds.): Model of Neural Networks I I. Springer: Berlin (1994)Google Scholar
  71. 4.50
    Deco, G./Schürmann, B.: Information Dynamics: Foundations and Applications (see Note 2.71) 229 (Fig. 10. 1 )Google Scholar
  72. 4.51
    Cf. Pöppel, E. (ed.): Gehirn und Bewußtsein. VCH Verlagsgesellschaft: Weinheim (1989);Google Scholar
  73. Singer, W. (ed.): Gehirn und Kognition. Spektrum der Wissenschaft: Heidelberg (1990)Google Scholar
  74. 4.52
    Haken, H./Stadler, M. (eds.): Synergetics of Cognition (see Note 42 ) 206Google Scholar
  75. 4.53
    Haken, H./Stadler, M. (eds.): Synergetics of Cognition (see Note 42 ) 204Google Scholar
  76. 4.54
    Pöppel, E.: Die neurophysiologische Definition des Zustands “bewußt”. In: Pöppel, E. (ed.): Gehirn und Bewußtsein (see Note 51 ) 18Google Scholar
  77. 4.55
    Searle, J.R.: Intentionality. An Essay in the Philosophy of Mind. Cambridge University Press: Cambridge (1983);CrossRefGoogle Scholar
  78. Dennett, D.: The Intentional Stance, MIT Press: Cambridge, Mass. (1987)Google Scholar
  79. 4.56
    Shaw, R.E./Kinsella-Shaw, J.M.: Ecological mechanics: A physical geometry for intentional constraints. Hum. Mov. Sci. 7 (1988) 155CrossRefGoogle Scholar
  80. 4.57
    For Figs. 4.23a-d, 4.23 Kugler, P.N., Shaw, R.E.: Symmetry and symmetry breaking in thermodynamic and epistemic engines: A coupling of first and second laws. In: Haken, H., Stadler, M. (eds.): Synergetics of Cognition (see Note 42) 317, 318, 319, 328Google Scholar
  81. 4.58
    Kelso, J.A.S./Mandell, A.J./Shlesinger, M.F. (eds.): Dynamic Patterns in Complex Systems. World Scientific: Singapore (1988);zbMATHGoogle Scholar
  82. For Figs. 4.24a-b, 4.25 compare Haken, H./Haken-Krell, M.: Erfolgsgeheimnisse der Wahrnehmung. Deutsche Verlags-Anstalt: Stuttgart (1992) 36, 38Google Scholar
  83. 4.59
    Kelso, J.A.S.: Phase transitions: Foundations of behavior. In: Haken, H./Stadler, M. (eds.): Synergetics of Cognition (see Note 42 ) 260Google Scholar
  84. 4.60
    Searle, J.R.: Mind, brains and programs. Behavioral and Brain Science 3 (1980) 417–424;CrossRefGoogle Scholar
  85. Searle, J.R.: Intrinsic intentionality. Behavioral and Brain Science 3 (1980) 450–456;CrossRefGoogle Scholar
  86. Searle, J.R.: Analytic philosophy and mental phenomena. Midwest Studies in Philosophy 5 (1980) 405–423.Google Scholar
  87. Searle, J.R.: For a critique of Searle’s position compare Putnam, H.: Representation and Reality. MIT Press: Cambridge, Mass. (1988) 26Google Scholar
  88. 4.61
    Eccles, J.C.: The Neurophysiological Basis of Mind. Clarendon Press: Oxford (1953);Google Scholar
  89. Eccles, J.C.: Facing Reality. Springer: New York (1970);Google Scholar
  90. Eccles, J.C. (ed.): Mind and Brain, Paragon: Washington, D.C. (1982)Google Scholar
  91. 4.62
    Palm, G.; Assoziatives Gedächtnis und Gehirn. In: Singer, W. (ed.): Gehirn und Kognition (see Note 51 ) 172;Google Scholar
  92. Palm, G. (ed.): Neural Assemblies: An Alternative Approach to Artificial Intelligence. Springer: Berlin (1984)Google Scholar

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© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Klaus Mainzer
    • 1
  1. 1.Lehrstuhl für Philosophie und Wissenschaftstheorie, Institut für Interdisziplinäre InformatikUniversität AugsburgAugsburgGermany

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