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Phenomenology and the Cognitive Sciences

, Volume 16, Issue 3, pp 355–385 | Cite as

Analogical reminding and the storage of experience: the paradox of Hofstadter-Sander

  • Stephen E. Robbins
Article
  • 203 Downloads

Abstract

In their exhaustive study of the cognitive operation of analogy (Surfaces and Essences, 2013), Hofstadter and Sander arrive at a paradox: the creative and inexhaustible production of analogies in our thought must derive from a “reminding” operation based upon the availability of the detailed totality of our experience. Yet the authors see no way that our experience can be stored in the brain in such detail nor do they see how such detail could be accessed or retrieved such that the innumerable analogical remindings we experience can occur. Analogy creation, then, should not be possible. The intent here is to sharpen and deepen our understanding of the paradox, emphasizing its criticality. It will be shown that the retrieval problem has its origins in the failure of memory theory to recognize the actual dynamic structure of events (experience). This structure is comprised of invariance laws as per J. J. Gibson, and this event “invariance structure” is exactly what supports Hofstadter and Sander’s missing mechanism for analogical reminding. Yet these structures of invariants, existing only over optical flows, auditory flows, haptic flows, etc., are equally difficult to imagine being stored in a static memory, and thus only exacerbate the problem of the storage of experience in the brain. A possible route to the solution of this dilemma, based in the radical model of Bergson, is also sketched.

Keywords

Memory Analogy Invariance Gibson Bergson 

References

  1. Adelson, E., & Bergen, J. (1985). Spatiotemporal energy model of the perception of motion. Journal of the Optical Society of America, 2, 284–299.CrossRefGoogle Scholar
  2. Bar, M. (2007). The proactive brain: using analogies and associations to generate predictions. Trends in Cognitive Sciences, 11, 280–289.CrossRefGoogle Scholar
  3. Bar, M. (2011). The proactive brain. In M. Bar (Ed.), Predictions in the brain: using the past to generate a future. Oxford: Oxford University Press.CrossRefGoogle Scholar
  4. Barsalou, L. W. (1983). Ad hoc categories. Memory and Cognition, 11, 211–227.CrossRefGoogle Scholar
  5. Barsalou, L. W. (1987). The instability of graded structure: Implications for the nature of concepts. In U. Neisser (Ed.), Concepts and conceptual development (pp. 101–140). Cambridge: Cambridge University Press.Google Scholar
  6. Barsalou, L. W. (1993). Flexibility, structure and linguistic vagary in concepts: Manifestations of a compositional system of perceptual symbols. In A. Collins, S. Gathercole, M. Conway, & P. Morris (Eds.), Theories of memory. New Jersey: Erlbaum.Google Scholar
  7. Barsalou, L. W., Wilson, C. D., & Hasenkamp, W. (2010). On the vices of nominalization and the virtues of contextualizing. In B. Mesquita, L. Feldman-Barret, & E. Smith (Eds.), The mind in context (pp. 334–360). New York: Guilford Press.Google Scholar
  8. Bergson, H. (1896/1912). Matter and .emory. New York: Macmillan.Google Scholar
  9. Bohm, D. (1980). Wholeness and the implicate order. London: Routledge and Kegan-Paul.Google Scholar
  10. Casasanto, D., & Lupyan, G. (2015). All concepts are ad hoc concepts. In E. Margoulis & S. Lawrence (Eds.), The conceptual mind: new directions in the study of concepts (pp. 543–566). Cambridge: MIT Press.Google Scholar
  11. Clark, A. (2013). Whatever next? Predictive brains, situated agents and the future of cognitive science. Behavioral and Brain Sciences, 36, 1–73.CrossRefGoogle Scholar
  12. Crowder, R. G. (1993). Systems and principles in memory theory: Another critique of pure memory. In A. Collins, S. Gathercole, M. Conway, & P. Morris (Eds.), Theories of memory. New Jersey: Erlbaum.Google Scholar
  13. Dessoir, M. (1912). Outlines of the history of psychology. New York: MacMillan Co.CrossRefGoogle Scholar
  14. Dietrich, E. (2000). Analogy and conceptual change, or you can’t step into the same mind twice. In E. Dietrich & A. B. Markman (Eds.), Cognitive dynamics: conceptual and representational change in humans and machines. New Jersey: Erlbaum.Google Scholar
  15. Doumas, L., Hummel, J., & Sandhofer, C. (2008). A theory of the discovery and predication of relational concepts. Psychological Review, 115, 1–43.CrossRefGoogle Scholar
  16. Eich, J. (1985). Levels of processing, encoding specificity, elaboration, and CHARM. Psychological Review, 92, 1–38.CrossRefGoogle Scholar
  17. Elssaser, W. (1987). Reflections on a theory of organisms. Baltimore: John Hopkins University Press.Google Scholar
  18. French, R. M. (1990). Sub-cognition and the limits of the turing test. Mind, 99, 53–65.CrossRefGoogle Scholar
  19. French, R. M. (1999). When coffee cups are like old elephants, or why representation modules don’t make sense. In A. Riegler, M. Peshl, & A. von Stein (Eds.), Understanding representation in the cognitive sciences. New York: Plenum.Google Scholar
  20. Freyd, J. J. (1987). Dynamic mental representations. Psychological Review, 94, 427–438.CrossRefGoogle Scholar
  21. Galton, F. (1883). Inquiries into human faculty and its development. London: Macmillan.CrossRefGoogle Scholar
  22. Gayler, R. W. (2003). Vector symbolic architectures answer Jackendoff’s challenges for cognitive neuroscience. In P. Slezak (Ed.), ICCS/ASCS International Conference on Cognitive Science (pp. 133–138). Sydney: University of New South Wales.Google Scholar
  23. Gelernter, D. (1994). The muse in the machine: computerizing the poetry of human thought. New York: Free Press.Google Scholar
  24. Gentner, D. (1983). Structure-mapping: a theoretical framework for analogy. Cognitive Science, 7, 155–70.CrossRefGoogle Scholar
  25. Gibson, J. J. (1950). The perception of the visual world. Boston: Houghton-Mifflin.Google Scholar
  26. Gibson, J. J. (1966). The senses considered as visual systems. Boston: Houghton-Mifflin.Google Scholar
  27. Gibson, J. J. (1979). The ecological approach to visual perception. Boston: Houghton-Mifflin.Google Scholar
  28. Gick, M., & Holyhoak, K. (1983). Schema induction and analogical transfer. Cognitive Psychology, 15, 1–38.CrossRefGoogle Scholar
  29. Goldinger, S. (1998). Echoes of echoes? An episodic theory of lexical access. Psychological Review, 105, 251–279.CrossRefGoogle Scholar
  30. Goldinger, S. (2007). A complementary-systems approach to abstract and episodic speech perception. In Proceedings of the 16th International Congress of Phonetic Sciences (pp. 49–54). Saarbruecken.Google Scholar
  31. Hardcastle, V. G. (1995). Locating consciousness. Philadelphia: John Benjamins.CrossRefGoogle Scholar
  32. Hofstadter, D., & Sander, E. (2013). Surfaces and essences: analogy as the fuel and fire of thinking. New York: Basic Books.Google Scholar
  33. Hohwy, J. (2013). The predictive mind. Oxford: Oxford University Press.CrossRefGoogle Scholar
  34. Hubel, D., & Wiesel, T. N. (1959). Receptive fields of single neurons in the cat’s striate cortex. Journal of Physiology, 148, 574–591.CrossRefGoogle Scholar
  35. Hubel, D., & Wiesel, T. N. (1978). Brain mechanisms in vision. Scientific American, 241, 150–162.CrossRefGoogle Scholar
  36. Hummel, J. E., & Biederman, I. (1992). Dynamic binding in a neural network for shape recognition. Psychological Reviews, 12, 487–519.Google Scholar
  37. Indurkyha, B. (1999). Creativity of metaphor in perceptual symbol systems. Behavioral and Brain Sciences, 22, 621–622.CrossRefGoogle Scholar
  38. James, W. (1890). Principles of psychology. New York: Holt and Co.CrossRefGoogle Scholar
  39. Jenkins, J. J., Wald, J., & Pittenger, J. B. (1978). Apprehending pictorial events: an instance of psychological cohesion. Minnesota Studies of the Philosophy of Science, 9, 1978.Google Scholar
  40. Johnson, M. (1987). The body in the mind: the bodily basis of reason and imagination. Chicago: University of Chicago Press.Google Scholar
  41. Kim, N., Turvey, M., & Carrelo, C. (1993). Optimal information about the severity of upcoming contacts. Journal of Experimental Psychology: Human Perception and Performance, 19(1), 179–193.Google Scholar
  42. Kingma, I., van de Langenberg, R., & Beek, P. (2004). Which mechanical invariants are associated with the perception of length and heaviness on a nonvisible handheld rod? Testing the inertia tensor hypothesis. Journal of Experimental Psychology: Human Perception and Performance, 30, 346–354.Google Scholar
  43. Klein, D. B. (1970). A history of scientific psychology. New York: Basic Books.Google Scholar
  44. Kugler, P., & Turvey, M. (1987). Information, natural law, and the self-assembly of rhythmic movement. Hillsdale: Erlbaum.Google Scholar
  45. Lakoff, G. (1987). Women, fire, and dangerous things. Chicago: University of Chicago Press.CrossRefGoogle Scholar
  46. Murdock, B. B. (1982). A theory for the storage and retrieval of item and associative information. Psychological Review, 89(6), 609–626.CrossRefGoogle Scholar
  47. Mussati, C. L. (1924). Sui fenomeni stereocinetici. Archivo Italiano di Psycologia, 3, 105–120.Google Scholar
  48. Nakayama, K. (1998). Vision fin de si∏cle: A reductionistic explanation of perception for the 21st century? In J. Hochberg (Ed.), Perception and cognition at century’s end. New York: Academic.Google Scholar
  49. Pittenger, J. B., & Shaw, R. E. (1975). Aging faces as viscal elastic events: implications for a theory of non rigid shape perception. Journal of Experimental Psychology: Human Perception and Performance, 1, 374–382.Google Scholar
  50. Pribram, K. (1971). Languages of the brain. New Jersey: Prentice-Hall.Google Scholar
  51. Reichardt, W. (1959). Autocorrelation and the central nervous system. In W. A. Rosenblith (Ed.), Sensory communication (pp. 303–318). Cambridge: MIT Press.Google Scholar
  52. Robbins, S. E. (2002). Semantics, experience and time. Cognitive Systems Research, 3, 301–337.Google Scholar
  53. Robbins, S. E. (2004). On time, memory and dynamic form. Consciousness and Cognition, 13, 762–788.Google Scholar
  54. Robbins, S. E. (2006). Bergson and the holographic theory. Phenomenology and the Cognitive Sciences, 5, 365–394.Google Scholar
  55. Robbins, S. E. (2008). Semantic redintegration: Ecological Invariance. Commentary on Rogers, T. & McClellan, J. (2008). Précis on Semantic Cognition: A Parallel Distributed Processing Approach. Behavioral and Brain Sciences, 726–727.Google Scholar
  56. Robbins, S. E. (2009). The COST of explicit memory. Phenomenology and the Cognitive Sciences, 8, 33Robbins, S. E. (2009). The COST of explicit memory. Phenomenology and the Cognitive Sciences, 8, 33–66.Google Scholar
  57. Robbins, S. E. (2013). Form, qualia and time: The hard problem re-formed. Mind and Matter, 2, 1–25.Google Scholar
  58. Robbins, S. E. (2014). Collapsing the Singularity: Bergson, Gibson and the Mythologies of Artificial Intelligence. Atlanta: CreateSpace.Google Scholar
  59. Rogers, T., & McClelland, J. (2004). Semantic cognition: a parallel distributed processing approach. Cambridge: MIT Press.Google Scholar
  60. Rogers, T., & McClelland, J. (2008). Precis of: semantic cognition: a parallel distributed processing approach. Behavioral and Brain Sciences, 31, 689–749.CrossRefGoogle Scholar
  61. Sartre, J. (1962). Imagination: a psychological critique. (Translated by Forrest Williams). Ann Arbor: University of Michigan Press.Google Scholar
  62. Savelsbergh, G. J. P., Whiting, H. T., & Bootsma, R. J. (1991). Grasping tau. Journal of Experimental Psychology: Human Perception and Performance, 17, 315–322.Google Scholar
  63. Shaw, R. E., & McIntyre, M. (1974). The algoristic foundations of cognitive psychology. In D. Palermo & W. Weimer (Eds.), Cognition and the symbolic processes. New Jersey: Lawrence Erlbaum Associates.Google Scholar
  64. Sherry, D., & Schacter, D. (1987). The evolution of multiple memory systems. Pscyhological Review, 94, 439–454.CrossRefGoogle Scholar
  65. Spaulding, T., & Murphy, G. (1996). Effects of background knowledge on category construction. Journal of Experimental Psychology: Learning, Memory, and Cognition, 8, 484–494.Google Scholar
  66. Tulving, E. (1972). Episodic and semantic memory. In E. Tulving, W. Donaldson (Eds.), Organization of memory. Academic Press.Google Scholar
  67. Turvey, M., & Carello, C. (1995). Dynamic touch. In W. Epstein & S. Rogers (Eds.), Perception of space and motion. San Diego: Academic.Google Scholar
  68. Ullman, S. (1979a). The interpretation of visual motion. Cambridge: MIT Press.Google Scholar
  69. Ullman, S. (1979b). The interpretation of structure from motion. Proceedings of the Royal Society of London. Series B, 203, 405–426.CrossRefGoogle Scholar
  70. Ullman, S. (1984). Maximizing rigidity: the incremental recovery of 3-D structure from rigid and non-rigid motion. Perception, 13, 255–274.CrossRefGoogle Scholar
  71. Ullman, S. (1986). Competence, performance and the rigidity assumption. Perception, 15, 644–646.Google Scholar
  72. Vicente, K. J., & Wang, J. H. (1998). An ecological theory of expertise effects in memory recall. Psychological Review, 105, 33–57.CrossRefGoogle Scholar
  73. Viviani, P., & Mounoud, P. (1990). Perceptuo-motor compatibility in pursuit tracking of two-dimensional movements. Journal of Motor Behavior, 22, 407–443.CrossRefGoogle Scholar
  74. Viviani, P., & Stucchi, N. (1992). Biological movements look uniform: evidence of motor-perceptual interactions. Journal of Experimental Psychology: Human Perception and Performance, 18, 603–623.Google Scholar
  75. Watson, A. B., & Ahumada, A. J. (1983). Model of human visual-motion sensing. Journal of the Optical Society of America A, 2, 322–341.CrossRefGoogle Scholar
  76. Weiss, Y., Simoncelli, E., & Adelson, E. (2002). Motion illusions as optimal percepts. Nature Neuroscience, 5, 598–604.CrossRefGoogle Scholar
  77. Weiss, Y., & Adelson, E. (1998). Slow and smooth: a Bayesian theory for the combination of local motion signals in human vision. MIT A. I. Memo No. 1624.Google Scholar
  78. Wheeler, M. (2008). Cognition in context: phenomenology, situated robotics and the frame problem. International Journal of Philosophical Studies, 16, 323–49.CrossRefGoogle Scholar
  79. Zimmer, H. D., Helstrup, T., & Engelkamp, J. (2000). Pop-Out into memory: a retrieval mechanism that is enhanced with the recall of subject-performed tasks. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 658–670.Google Scholar

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© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.JacksonUSA

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