Advertisement

Complex Systems and the Evolution of Mind-Brain

  • Klaus Mainzer
Chapter
  • 149 Downloads

Abstract

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).

Keywords

Auditory Cortex Spin Glass Human Mind Learning Rule Energy Landscape 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 4.
    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) 349Google Scholar
  3. Popper, K.R., Eccles, J.C.: The Self and its Brain. Springer: Berlin (1977) 161CrossRefGoogle Scholar
  4. 4.
    Aristotle: De anima 403 b 31Google Scholar
  5. 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.
    Spinoza, B.: EthicsGoogle Scholar
  11. 4.
    Leibniz, G.W.: Monadology.Google Scholar
  12. Rescher, N.: Leibniz: An Introduction to his Philosophy. Basil Blackwell: Oxford (1979)Google Scholar
  13. 4.11
    Hume, D.: A Treatise of Human Nature (1739). Penguin: Harmondsworth (1969) 82Google Scholar
  14. 4.12
    Mainzer, K.: Kants Begründung der Mathematik und die Entwicklung von GauBbis Hilbert. In: Akten des V. Intern. Kant-Kongresses in Mainz 1981 (ed. Funke, G. ). Bouvier: Bonn (1981) 120–129Google Scholar
  15. 4.13
    Brazier, M.A.B.: A History of Neurophysiology in the 17th and 18th Centuries. Raven: New York (1984)Google Scholar
  16. 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
  17. 4.14
    Helmholtz, H.v.: Schriften zur Erkenntnistheorie (eds. Hertz, P., Schlick, M. ). Berlin (1921)Google Scholar
  18. Mainzer, K.: Geschichte der Geometrie (see Note 13 Chapter 2) 172Google Scholar
  19. 4.15
    Müller, J.: Handbuch der Physiologie des Menschen. Koblenz (1835)Google Scholar
  20. 4.
    Helmholtz, H.v.: Vorläufiger Bericht über die Fortpflanzungsgeschwindigkeit der Nervenreizung. Archiv für Anatomie, Physiologie und wissenschaftliche Medizin (1850)71–73Google Scholar
  21. 4.17
    James, W: Psychology (Briefer Course). Holt: New York (1890) 3Google Scholar
  22. 4.
    James, W: Psychology (see Note 17) 254Google Scholar
  23. 4.
    James, W: Psychology (see Note 17) Fig. 57Google Scholar
  24. 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
  25. Braitenberg, V.: Gehirngespinste. Neuroanatomie für kybernetisch Interessierte. Springer: Berlin (1973)Google Scholar
  26. 4.
    Churchland, P.S., Sejnowski, T.J.: Perspectives in cognitive neuroscience. ScienceGoogle Scholar
  27. 242.
    ) 741–745. 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. 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. An example of chemical synapses is shown in Kand, E.R., Schwartz J.: Principles of Neural Science. Elsevier: New York (1985)Google Scholar
  28. 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
  29. 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
  30. Churchland, P.M.: A Neurocomputational Perspective (see Note 22) 83, 89Google Scholar
  31. 4.24
    Cf. Schwartz, E.L. (ed.): Computational Neuroscience. MIT Press: Cambridge, Mass. (1990)Google Scholar
  32. 4.25
    Cf. Churchland, P.S., Sejnowski, T.J.: The Computational Brain. MIT Press: Cambridge, Mass. (1992) 169Google Scholar
  33. 4.26
    Hebb, D.O.: The Organization of Behavior. Wiley: New York (1949) 50Google Scholar
  34. 4.27
    Kohonen, T.: Self-Organization and Associative Memory. Springer: Berlin (1989) 105CrossRefGoogle Scholar
  35. Churchland, P.S., Sejnowski, T.J.: The Computational Brain (see Note 25 ) 54Google Scholar
  36. Ritter, H., Martinetz, T., Schulten, K.: Neuronale Netze. Eine Einführung in die Neuroinformatik selbstorganisierender Netzwerke. Addison-Wesley: Reading, Mass. (1991) 35Google Scholar
  37. 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
  38. 4.29
    Hertz, J., Krogh, A., Palmer, R.G.: Introduction to the Theory of Neural Computation. Addison-Wesley: Redwood City (1991)Google Scholar
  39. 4.30
    Serra, R., Zanarini, G.: Complex Systems and Cognitive Processes. Springer: Berlin (1990) 78CrossRefGoogle Scholar
  40. 4.
    Hertz, J., Krogh, A., Palmer, R.G.: Introduction to the Theory of Neural Computation (see Note 29)Google Scholar
  41. Hopfield, J.J., Tank, D.W.: Computing with neural circuits: A model. Science 233 (1986) 625–633ADSCrossRefGoogle Scholar
  42. 4.32
    Ackley, D.H., Hinton, G.E., Sejnowski, T.J.: A learning algorithm for Boltzmann machines. Cognitive Science 9 (1985) 147–169CrossRefGoogle Scholar
  43. 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. An illustration is shown in Churchland, P.S., Sejnowski, T.J.: The Computational Brain (see Note 25 ) 101Google Scholar
  44. 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
  45. 4.
    Kohonen, T.: Self-Organization and Associative Memory (see Note 27) 123Google Scholar
  46. 4.
    Kohonen, T.: Self-Organization and Associative Memory (see Note 27) 125Google Scholar
  47. 4.37
    Ritter, H., Martinetz, T., Schulten, K.: Neuronale Netze (see Note 27 ) 75Google Scholar
  48. 4.38
    Suga, N., O’Neill, W.E.: Neural axis representing target range in the auditory cortex of the mustache Bat. Science 206 (1979) 351–353ADSCrossRefGoogle Scholar
  49. Ritter, H., Martinetz, T., Schulten, K.: Neuronale Netze (see Note 27 ) 88Google Scholar
  50. 4.39
    Widrow, B., Hoff, M.E.: Adaptive switching circuits. 1960 IRE WESCON Convention Record. IRE: New York (1960) 36–104Google Scholar
  51. 4.40
    Cf. Churchland, P.S., Sejnowski, T.J.: The Computational Brain (see Note 25 ) 106Google Scholar
  52. 4.41
    Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Learning representations by backpropagating errors. Nature 323 (1986) 533–536ADSCrossRefGoogle Scholar
  53. Arbib, M.A.: Brains, Machines, and Mathematics. Springer: New York (1987) 117zbMATHCrossRefGoogle Scholar
  54. 4.42
    Köhler, W: Die physischen Gestalten in Ruhe und im stationären Zustand. Vieweg: Braunschweig (1920).CrossRefGoogle Scholar
  55. Jahresberichte für die ges. Physiol. und exp. Pharmakol. 3 (1925) 512–539Google Scholar
  56. 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
  57. 4.43
    Cf. Churchland, P.M.: A Neurocomputational Perspective (see Note 22 ) 209Google Scholar
  58. 4.44
    Cf. Churchland, P.M.: A Neurocomputational Perspective (see Note 22 ) 211Google Scholar
  59. 4.45
    Cf. Feigl, H., Scriven, M., Maxwell, G. (eds.): Concepts, Theories and the Mind-Body Problem. University of Minnesota Press: Minneapolis (1958).Google Scholar
  60. Marcel, A.J., Bisiach, E. (eds.): Consciousness in Contemporary Science. Clarendon Press: Oxford (1988).Google Scholar
  61. Bieri, P.: Pain: A case study for the mind-body problem. Acta Neurochirurgica 38 (1987) 157–164.CrossRefGoogle Scholar
  62. Lycan, W.G.: Consciousness. MIT Press: Cambridge, Mass. (1987)Google Scholar
  63. 4.46
    Flohr, H.: Brain processes and phenomenal consciousness. A new and specific hypothesis. Theory and Psychology 1 (2) (1991) 248CrossRefGoogle Scholar
  64. 4.47
    von der Malsburg, C.: Self-organization of orientation sensitive cells in the striate cortex. Kybernetik 14 (1973) 85–100.CrossRefGoogle Scholar
  65. 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
  66. 4.48
    Cf. Pöppel, E. (ed.): Gehirn und Bewußtsein. VCH Verlagsgesellschaft: Weinheim (1989).Google Scholar
  67. Singer, W. (ed.): Gehirn und Kognition. Spektrum der Wissenschaft: Heidelberg (1990)Google Scholar
  68. 4.49
    Haken, H., Stadler, M. (eds.): Synergetics of Cognition (see Note 42 ) 206Google Scholar
  69. 4.50
    Haken, H., Stadler, M. (eds.): Synergetics of Cognition (see Note 42 ) 204Google Scholar
  70. 4.51
    Pöppel, E.: Die neurophysiologische Definition des Zustands “bewußt”. In: Pöppel, E. (ed.): Gehirn und Bewußtsein (see Note 48 ) 18Google Scholar
  71. 4.52
    Searle, J.R.: Intentionality. An Essay in the Philosophy of Mind. Cambridge University Press: Cambridge (1983).CrossRefGoogle Scholar
  72. Dennett, D.: The Intentional Stance, MIT Press: Cambridge, Mass. (1987)Google Scholar
  73. 4.53
    Shaw, R.E., Kinsella-Shaw, J.M.: Ecological mechanics: A physical geometry for intentional constraints. Hum. Mov. Sci. 7 (1988) 155CrossRefGoogle Scholar
  74. 4.54
    For Figs. 4.22a-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
  75. 4.55
    Kelso, J.A.S., Mandell, A.J., Shlesinger, M.F. (eds.): Dynamic Patterns in Complex Systems. World Scientific: Singapore (1988).zbMATHGoogle Scholar
  76. For Figs. 4.24a-b, 4.25 compare Haken, H., Haken-Krell, M.: Erfolgsgeheimnisse der Wahrnehmung. Deutsche Verlags-Anstalt: Stuttgart (1992) 36, 38Google Scholar
  77. 4.56
    Kelso, J.A.S.: Phase transitions: Foundations of behavior. In: Haken, H., Stadler, M. (eds.): Synergetics of Cognition (see Note 42 ) 260Google Scholar
  78. 4.57
    Searle, J.R.: Mind, brains and programs. Behavioral and Brain Science 3 (1980) 417–424.CrossRefGoogle Scholar
  79. Intrinsic intentionality. Behavioral and Brain Science 3 (1980) 450–456.CrossRefGoogle Scholar
  80. Analytic philosophy and mental phenomena. Midwest Studies in Philosophy 5 (1980) 405–423.Google Scholar
  81. For a critique of Searle’s position compare Putnam, H.: Representation and Reality. MIT Press: Cambridge, Mass. (1988) 26Google Scholar
  82. 4.58
    Eccles, J.C.: The Neurophysiological Basis of Mind. Clarendon Press: Oxford (1953).Google Scholar
  83. Facing Reality. Springer: New York (1970).Google Scholar
  84. Eccles, J.C. (ed.): Mind and Brain, Paragon: Washington, D.C. (1982)Google Scholar
  85. 4.59
    Palm, G. Assoziatives Gedächtnis und Gehirn. In: Singer, W. (ed.): Gehirn und Kognition (see Note 48 ) 172.Google Scholar
  86. Palm, G. (ed.): Neural Assemblies: An Alternative Approach to Artificial Intelligence. Springer: Berlin (1984)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Klaus Mainzer
    • 1
  1. 1.Lehrstuhl für Philosophie und WissenschaftstheorieUniversität AugsburgAugsburgGermany

Personalised recommendations