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Whence Perceptual Meaning? A Cartography of Current Ideas

  • Francisco J. Varela
Part of the Boston Studies in the Philosophy and History of Science book series (BSPS, volume 130)

Abstract

This essay was written for the purpose of providing a minimal common ground for discussion. It is, of necessity, an ambitious attempt to give a concise account of the various current ideas on the origin of meaning in living and artificial systems in such a way that it is accessible to an interdisciplinary audience, and yet substantive enough to produce debate among the specialists. I apologize at the outset to both groups for passages that will seem irritatingly simple or too abstruse.

Keywords

Common Sense Cognitive Science Cognitive System Symbolic Description Connectionist Strategy 
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.

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Notes

  1. 1.
    This Section owes much to our recent collective work on the neglected history of early cybernetics, self-organization, and cognition, published as Cahiers du CREA N°s 7–9. The only other useful source is S. Heims, John von Neumann and Norbert Wiener, MIT Press, 1980.Google Scholar
  2. 1a.
    The recent book by H. Gardner, The Mind’s New Science: A History of the Cognitive Revolution, Basic Books, 1985, discusses this period only in a superficial way.Google Scholar
  3. 2.
    The best sources here are the oft-cited Macy Conferences, published as Cybernetics-Circular causal and feedback Mechanisms in Biological and Social Systems, Josiah Macy Jr. Foundation, New York, 5 volumes.Google Scholar
  4. 3.
    Bulletin of Mathematical Biophysics, 5, 1943. Reprinted in W. McCulloch, Embodiments of Mind, MIT Press, 1965Google Scholar
  5. 4.
    For an interesting perspective about this historical/conceptual moment see also A. Hodges, Alan Turing: The Enigma of Intelligence, Touchstone, New York, 1984.Google Scholar
  6. 5.
    See H. Gardner, Alan Turing: The Enigma of Intelligence, Touchstone, New York, 1984 @@@op. cit., Chapter 5 for this period.Google Scholar
  7. 6.
    This designation is justified in J. Haugland (Ed.), Mind Design, MIT Press, 1981. Other designations used are: computationalism (Fodor) or symbolic processing. For this section I have profited much from D. Andler’ s article in Cahier du CREA N° 9.Google Scholar
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    For more on this see J. Searle, Intentionality, Cambridge U. P., 1983.Google Scholar
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    S. Kosslyn, Psychol. Rev. 88, 46–66, 1981.CrossRefGoogle Scholar
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    This is the opening line of a popular textbook in neuroscience: “The brain is an unresting assembly of cells that continually receives information, elaborates and perceives it, and makes decision.” S. Kuffler and J. Nichols, From Neuron to Brain, Sinauer Associates, Boston, 2nd ed., 1984, p. 3.Google Scholar
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    D. Hubel and T. Wiesel, J. Physiol. 160, 106 (1962). For a recent account of this work see Kuffler and Nichols, op. cit. Ch. 2–4.Google Scholar
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    F. Rosenblatt, Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms, Spartan Book, 1962.Google Scholar
  16. 15.
    For more on the complex early origins of self-organization ideas see I. Stengers, Cahier du CREA N° 8, pp. 7–105.Google Scholar
  17. 16.
    ‘The logical geography of computational approaches’, MIT Sloan Conference, 1984.Google Scholar
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    For extensive discussion on this point of view see P. Dumouchel and J.-P. Dupuy (Eds.), L’Auto-organisation: De la physique au politique, Eds. du Seuil, Paris, 1983.Google Scholar
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    See for example H. von Foerster (Ed.), Principles of Self-Organization, Pergamon Press, 1962.Google Scholar
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    An accessible introduction to the modern theory of dynamical systems is: R. Abraham and C. Shaw, Dynamics: The Geometry of Behavior, Aerial Press, Santa Cruz, 3 vols., 1985.Google Scholar
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    M. Fishman and C. Michael, Vision Res., 13, 1415 (1973)CrossRefGoogle Scholar
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    and F. Morell, Nature 238, 44–46 (1972).CrossRefGoogle Scholar
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    J. Allman, F. Miezen and E. McGuiness, Ann. Rev. Neuroscien. 8, 407–430 (1985).CrossRefGoogle Scholar
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    F. Varela and W. Singer, Exp. Brain Res. 66, 10–20 (1987).CrossRefGoogle Scholar
  26. 24.
    An interesting collection of examples is: G. Palm and A. Aersten (Eds.), Brain Theory, Springer Verlag, 1986.Google Scholar
  27. 25.
    The name is proposed in: J. Feldman and D. Ballard, ‘Connectionist models and their properties’, Cognitive Science 6, 205–254 (1982).CrossRefGoogle Scholar
  28. 25a.
    For extensive discussion of current work in this direction see: D. Rumelhart and J. McClelland (Eds.), Parallel Distributed Processing: Studies on the Microstructure of Cognition, MIT Press, 1986, 2 vols.Google Scholar
  29. 26.
    The main idea is due to J. Hopfield, Proc. Natl. Acad. Sci. (U.S.A.), 79, 2554–2556 (1982).CrossRefGoogle Scholar
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    There are many variants associated to these ideas. See in particular: G. Hinton, T. Sejnowsky, and D. Ackley, Cognitive Science 9, 147–163 (1984),Google Scholar
  31. 27a.
    and G. Toulousse, S. Dehaene, and J. Changeaux, Proc. Natl. Acad. Sci. (U.S.A.), 83, 1695–1698 (1986).CrossRefGoogle Scholar
  32. 28.
    The idea is due to D. Rumelhart, G. Hinton, and R. Williams, in: Rumelhart and McClelland, op. cit., Ch. 8.Google Scholar
  33. 29.
    T. Sejnowski and C. Rosenbaum, ‘NetTalk: A parallel network that learns to read aloud’, TR JHU/EECS-86/01, John Hopkins Univ.Google Scholar
  34. 30.
    For the distinction between symbolic and emergent description and explanation in biological systems see F. Varela, Principles of Biological Autonomy, North Holland, New York, 1979, Ch. 7,Google Scholar
  35. 30a.
    and more recently S. Oyama, The Ontogeny of Information, Cambridge U. Press, 1985.Google Scholar
  36. 31.
    See D. Hillis, ‘Intelligence as emergent behavior’, Daedalus, Winter 1989, and P. Smolesnky, ‘On the proper treatment of connectionism’, Beh. Brain Sci. 11: 1, 1989.Google Scholar
  37. 31a.
    In a very different vein J. Feldman, ‘Neural representation of conceptual knowledge’, U. Rochester TR189 (1986) proposes a middle ground between ‘punctuate’ and distributed systems.Google Scholar
  38. 32.
    P. Smolesnky in: Rumelhart and McClelland, op. cit., Ch. 6.Google Scholar
  39. 33.
    This is extensively argued by two noted spokesmen of cognitivism: J. Fodor and S. Pylyshyn, ‘Connectionism and cognitive architecture: A critical review’, Cognition, 1989. For the opposite philosophical position in favor of connectionism see: H. Dreyfus, ‘Making a mind vs. modeling the brain: AI again at the cross-riads’. Daedalus, Winter, 1989.Google Scholar
  40. 34.
    Most influential in this respect is the work of H. G. Gadamer, Truth and Method, Seabury Press, 1975. For a clear introduction to hermeneutics see Palmer, Hermeneutics, Northwestern Univ. Press, 1979.Google Scholar
  41. 34a.
    The formulation of this section owes a great deal to the influence of F. Flores, see: T. Winnograd and F. Flores Understanding Computers and Cognition: A New Foundation for Design, Ablex, New Jersey, 1986.Google Scholar
  42. 35.
    The name is far from being an established one. I suggest it here for pedagogical reasons, until a better one is proposed.Google Scholar
  43. 36.
    H. Dreyfus and S. Dreyfus, Mind over Machine, Free Press/Macmillan, New York, 1986.Google Scholar
  44. 37.
    For this explicit way of constructing biologically inspired networks see T. Poggio, V. Torre and C. Koch, Nature 317, 314–319 (1986).CrossRefGoogle Scholar
  45. 38.
    For an interesting sample of discussion in AI about these themes see the multiple review of Winnograd and Flores’ s book, in Artif. Intell. (1987).Google Scholar
  46. 39.
    The main reference points we have in mind here are (in their English versions): M. Heidegger, Being and Time, Harper and Row, 1977;Google Scholar
  47. 39a.
    M. Merleau-Ponty, The Phenomenology of Perception, Routledge and Kegan Paul, 1962;Google Scholar
  48. 39b.
    Michel Foucault, Discipline and Punish: The birth of the prison, Vintage/Random House, 1979.Google Scholar
  49. 40.
    This is discussed in my contribution to the previous Stanford Symposium, ‘Living ways of sense making: A middle way approach to neuroscience’, in P. Livingston (Ed.), Order and Disorder, Anma Libris, Stanford, 1984.Google Scholar
  50. 41.
    See for instance P. Watzlawick (Ed.), The Invented Reality: Essays on Constructivism, Norton, New York, 1985.Google Scholar
  51. 42.
    Most clearly seen in the Vienna school of Konrad Lorenz, as expressed, for example, in Behind the Mirror, Harper and Row, 1979.Google Scholar
  52. 43.
    See for instance E. Land, Proc. Natl. Acad. Sci. (U.S.A.) 80, 5163–5169 (1983).CrossRefGoogle Scholar
  53. 44.
    P. Gouras and E. Zenner, Progr. Sensory Physiol. 1, 139–179 (1981).CrossRefGoogle Scholar
  54. 45.
    F. Varela et al., Arch. Biol. Med. Exp, 16, 291–303 (1983); E. Thompson, A. Palacios, F. Varela, Beh. Brain Sci. (in press), 1992.Google Scholar
  55. 46.
    W. Freeman, Mass Action in the Nervous System, Academic Press, 1975.Google Scholar
  56. 47.
    W. Freeman and C. Skarda, Brain Res. Reviews, 10, 145–175 (1985). Significantly, a section of this article is entitled: ‘A retraction on “representation”’ (p. 169).CrossRefGoogle Scholar
  57. 48.
    This biologically inspired re-interpretation of cognition was presented in H. Maturana and F. Varela, Autopoiesis and Cognition: The realization of the Living, D. Reidel, Boston, 1980, and F. Varela, Principles of Biological Autonomy, op. cit. CrossRefGoogle Scholar
  58. 48a.
    For an introductory exposition to this point of view and more recent developments see H. Maturana and F. Varela, The Tree of Knowledge: the Biological Roots of Human Understanding, New Science Library, Boston 1987. The links with language and AI are discussed in Winnograd and Flores, op. cit. Google Scholar
  59. 49.
    See J. H. Holland, ‘Escaping brittleness’, in: Machine Intelligence, Vol. 2 (1986).Google Scholar
  60. 50.
    An interesting recent collections of diverse papers in this direction can be found in: Evolution, Games and Learning: Models for Adaptation in Machines and Nature, Physica 22D (1986). Surely, many of the contributors would not agree with our readings of their work. For an explicit example see: F. Varela, ‘Structural coupling and the origin of meaning in a simple cellular automata’, in E. Secarz, (Ed.), The Semiotics of Cellular Communications, Springer-Verlag, New York, 1987.Google Scholar
  61. 51.
    P. Smolesnky, op. cit., p. 260.Google Scholar
  62. 52.
    It is worth noting that similar arguments can be applied to evolutionary thinking today. For the parallels between cognitive representationism and evolutionary adaptationism, see F. Varela, in: P. Livingston (Ed.), op. cit. and the Introduction in this volume.Google Scholar
  63. 53.
    See also the remarks by Roger Schank in AI Magazine, pp. 122–135 (Fall 1985).Google Scholar
  64. 54.
    This is the trend within the new field of ‘Artificial Life’; see e.g. Ch. Langton (Ed.), Artificial Life, Addison-Wesley, New Jersey, 1990.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 1992

Authors and Affiliations

  • Francisco J. Varela
    • 1
  1. 1.Ecole PolytechniqueCREAParisFrance

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