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Temporal Memory Traces as Anticipatory Mechanisms

  • Peter CarianiEmail author
Chapter
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Abstract

Brains can be considered as goal-seeking correlation systems that use past experience to predict future events so as to guide appropriate behavior. Brains can also be considered as neural signal processing systems that utilize temporal codes, neural timing architectures operating on them, and time-domain, tape-recorder-like memory mechanisms that store and recall temporal spike patterns. If temporal memory traces can also be read out in faster-than-real-time, then these can serve as an advisory mechanism to guide prospective behavior by simulating the neural signals generated from time courses of past events, actions, and the respective hedonic consequences that previously occurred under similar circumstances. Short-term memory stores based on active regeneration of neuronal signals in networks of delay paths could subserve short-term temporal expectancies based on recent history. Polymer-based molecular mechanisms that map time-to-polymer chain position and vice versa could provide vehicles for storing and reading out permanent, long-term memory traces.

Keywords

Neural timing nets Neural codes Pitch Rhythm Auditory scene analysis Temporal codes Expectancy Music perception Engram 

References

  1. 1.
    Rosen, R.: Anticipatory Systems: Philosophical, Mathematical, and Methodological Foundations. Pergamon Press, Oxford, New York (1985)zbMATHGoogle Scholar
  2. 2.
    Rosen, R.: Anticipatory Systems: Philosophical, Mathematical, and Methodological Foundations, 2nd edn. Springer, New York (2012)CrossRefzbMATHGoogle Scholar
  3. 3.
    Nadin, M.: What speaks in favor of an inquiry into anticipatory processes? In: Klir, G. (ed.) Anticipatory Systems: Philosophical, Mathematical, and Methodological Foundations, pp. xv–lvii. Springer, New York (2012)Google Scholar
  4. 4.
    Louie, A.H.: Robert Rosen’s anticipatory systems. Foresight 12, 18–29 (2010)CrossRefGoogle Scholar
  5. 5.
    Nadin, M. (ed.): Anticipation—Learning from the Past: The Russian/Soviet Contributions to the Science of Anticipation, vol. 25. Springer, Cham, CH (2015)Google Scholar
  6. 6.
    Nadin, M. (ed.): Anticipation Across Disciplines, vol. 29. Springer, Cham CH (2016)Google Scholar
  7. 7.
    Tsagareli, M.G.: I.S. Beritashvili and psychoneural integration of behavior. In: Nadin, M. (ed.) Anticipation: Learning from the Past: The Russian/Soviet Contributions to the Science of Anticipation, vol. 25, pp. 395–414. Springer, New York (2015)Google Scholar
  8. 8.
    Vityaev, E.E.: Purposefulness as a principle of brain activity. In: Nadin, M. (ed.) Anticipation: Learning from the Past: Russian/Soviet Contributions to the Science of Anticipation, vol. 25, pp. 231–254. Springer, New York (2015)CrossRefGoogle Scholar
  9. 9.
    Zueva, E.Y., Zuev, K.B.: The concept of dominance by A.A. Ukhtomsky and Anticipation. In: Nadin, M. (ed.) Anticipation: Learning from the Past: The Russian/Soviet Contributions to the Science of Anticipation, vol. 25, pp. 13–35. Springer, New York (2015)Google Scholar
  10. 10.
    Rosenblueth, A., Wiener, N., Bigelow, J.: Behavior, purpose and teleology. Philos. Sci. 10, 18–24 (1943)CrossRefGoogle Scholar
  11. 11.
    Rosenblueth, A., Wiener, N.: Purposeful and non-purposeful behavior. Philos. Sci. 17, 318–326 (1950)CrossRefGoogle Scholar
  12. 12.
    de Latil, P.: Thinking by Machine. Houghton Mifflin, Boston (1956)Google Scholar
  13. 13.
    Ackoff, R.L., Emery, F.E.: On Purposeful Systems. Aldine-Atherton, Chicago (1972)Google Scholar
  14. 14.
    George, F.H., Johnson, L.: Purposive Behaviour and Teleological Explanations. Gordon and Breach Science Publishers, New York (1984)Google Scholar
  15. 15.
    Rashevsky, N.: Mathematical Biophysics: Physico-Mathematical Foundations of Biology, vols. I & II. Dover, New York (1960)Google Scholar
  16. 16.
    Rosen, R.: Biological systems as organizational paradigms. Int. J. Gen. Syst. 1, 165–174 (1974)CrossRefGoogle Scholar
  17. 17.
    Rosen, R.: Life Itself. Columbia University Press, New York (1991)Google Scholar
  18. 18.
    Kazansky, A.B.: Agental anticipation in the central nervous system. In: Nadin, M. (ed.) Anticipation: Learning from the Past: The Russian/Soviet Contributions to the Science of Anticipation, vol. 25, pp. 108–117. Springer, New York (2015)Google Scholar
  19. 19.
    Kilmer, W., McCulloch, W.S.: The reticular formation command and control system. In: Leibovic, K.N. (ed.) Information Processing in the Nervous System, pp. 297–307. Springer, New York (1969)Google Scholar
  20. 20.
    Mingers, J.: Self-Producing Systems. Plenum Press, New York (1995)CrossRefGoogle Scholar
  21. 21.
    Maturana, H., Varela, F.: Autopoiesis: the organization of the living. In: Maturana, H., Varela, F. (eds.) Autopoiesis and Cognition (1980), vol. 42. D. Reidel, Dordrecht, Holland (1973)Google Scholar
  22. 22.
    Maturana, H.R.: Autopoiesis. In: Zeleny, M. (ed.) Autopoiesis: A Theory of the Living. North Holland, New York (1981)Google Scholar
  23. 23.
    Rosen, R.: Some realizations of (M, R) systems and their interpretation. J. Math. Biophys. 33, 303–319 (1971)CrossRefzbMATHGoogle Scholar
  24. 24.
    Rosen, R.: What does it take to make an organism? In: Rosen, R. (ed.) Essays on Life Itself, pp. 254–269. Columbia University Press, New York (2000)Google Scholar
  25. 25.
    von Neumann, J.: The general and logical theory of automata. In: Jeffress, L.A. (ed.) Cerebral Mechanisms of Behavior (the Hixon Symposium), pp. 1–41. Wiley, New York (1951)Google Scholar
  26. 26.
    Kauffman, S.: The Origins of Order. Oxford University Press, New York (1993)Google Scholar
  27. 27.
    Kampis, G.: Self-Modifying Systems in Biology and Cognitive Science. Pergamon Press, Oxford (1991)Google Scholar
  28. 28.
    Pattee, H.H., Raczaszek-Leonardi, J.: Laws, language and life Howard Pattee’s classic papers on the physics of symbols with contemporary commentary by Howard Pattee and Joanna Raczaszek-Leonardi. Biosemiotics vol. 7. Springer, Dordrecht, New York (2012)Google Scholar
  29. 29.
    Cariani, P.: The semiotics of cybernetic percept-action systems. Int. J. Signs Semiotic Syst. 1, 1–17 (2011)CrossRefGoogle Scholar
  30. 30.
    Cariani, P.: Sign functions in natural and artificial systems. In: Trifonas, P.P. (ed.) International Handbook of Semiotics, pp. 917–950. Springer, Dordrecht (2015)CrossRefGoogle Scholar
  31. 31.
    Graham, D.W.: Aristotle’s Two Systems. Oxford University Press, New York (1987)Google Scholar
  32. 32.
    Modrak, D.K.: Aristotle: The Power of Perception. University of Chicago, Chicago (1987)Google Scholar
  33. 33.
    Favareau, D.: The evolutionary history of biosemiotics. In: Barbieri, M. (ed.) Introduction to Biosemiotics, pp. 1–67. Springer, Dordrecht (2008)Google Scholar
  34. 34.
    John, E.R.: Mechanisms of Memory. Wiley, New York (1967)Google Scholar
  35. 35.
    Milner, B., Squire, L.R., Kandel, E.R.: Cognitive neuroscience and the study of memory. Neuron 20, 445–468 (1998)CrossRefGoogle Scholar
  36. 36.
    Eichenbaum, H.: The Cognitive Neuroscience of Memory: An Introduction. Oxford University Press, New York (2012)Google Scholar
  37. 37.
    Eichenbaum, H.: Memory on time. Trends in Cognitive Sciences 17, 81–88 (2013)CrossRefGoogle Scholar
  38. 38.
    Atherton, L.A., Dupret, D., Mellor, J.R.: Memory trace replay: the shaping of memory consolidation by neuromodulation. Trends Neurosci. 38, 560–570 (2015)CrossRefGoogle Scholar
  39. 39.
    Snyder, B.: Music and Memory. MIT Press, Cambridge (2000)Google Scholar
  40. 40.
    Snyder, B.: Memory for music. In: Hallam, S., Cross, I., Thaut, M. (eds.) The Oxford Handbook of Music Psychology, pp. 107–117. Oxford University Press, Oxford, New York (2009)Google Scholar
  41. 41.
    Handel, S.: Listening: An Introduction to the Perception of Auditory Events. MIT Press, Cambridge, MA (1989)Google Scholar
  42. 42.
    Bregman, A.S.: Auditory Scene Analysis, The Perceptual Organization of Sound. MIT Press, Cambridge, MA (1990)Google Scholar
  43. 43.
    Fraisse, P.: The Psychology of Time. Harper & Row, New York (1978)Google Scholar
  44. 44.
    Longuet-Higgins, H.C.: Mental Processes: Studies in Cognitive Science. The MIT Press, Cambridge, MA (1987)Google Scholar
  45. 45.
    Longuet-Higgins, H.C.: A mechanism for the storage of temporal correlations. In: Durbin, R., Miall, C., Mitchison, G. (eds.) The Computing Neuron, pp. 99–104. Addison-Wesley, Wokingham, England (1989)Google Scholar
  46. 46.
    Thatcher, R.W., John, E.R.: Functional Neuroscience, Vol. I. Foundations of Cognitive Processes. Lawrence Erlbaum, Hillsdale, NJ (1977)Google Scholar
  47. 47.
    John, E.R., Bartlett, F., Shimokochi, M., Kleinman, D.: Neural readout from memory. J. Neurophysiol. 36, 893–924 (1973)Google Scholar
  48. 48.
    Cariani, P.A., Delgutte, B.: Neural correlates of the pitch of complex tones. II. Pitch shift, pitch ambiguity, phase invariance, pitch circularity, rate pitch, and the dominance region for pitch. J. Neurophysiol. 76, 1717–1734 (1996)Google Scholar
  49. 49.
    Cariani, P.: Temporal coding of periodicity pitch in the auditory system: an overview. Neural Plasticity 6, 147–172 (1999)CrossRefGoogle Scholar
  50. 50.
    Poeppel, D., Hickok, G.: Electromagnetic recording of the auditory system. Handb. Clin. Neurol. 129, 245–255 (2015)CrossRefGoogle Scholar
  51. 51.
    Will, U., Makeig, S.: EEG research methodology and brain entrainment. In: Berger, J., Turow, G. (eds.) Music, Science, and the Rhythmic Brain: Cultural and Clinical Implications, pp. xiv, 215 p. Routledge, New York (2011)Google Scholar
  52. 52.
    Arnal, L.H., Poeppel, D., Giraud, A.L.: Temporal coding in the auditory cortex. Handb. Clin. Neurol. 129, 85–98 (2015)CrossRefGoogle Scholar
  53. 53.
    Snyder, J.S., Large, E.W.: Gamma-band activity reflects the metric structure of rhythmic tone sequences. Brain Res. Cogn. Brain Res. 24, 117–126 (2005)CrossRefGoogle Scholar
  54. 54.
    Trainor, L.J., Zatorre, R.: The neurobiological basis of musical expectations. In: Hallam, S., Cross, I., Thaut, M. (eds.) The Oxford Handbook of Music Psychology, pp. 171–183. Oxford University Press, Oxford, New York (2009)Google Scholar
  55. 55.
    Koelsch, S.: Brain and Music. Wiley-Blackwell, Chichester (2012)Google Scholar
  56. 56.
    Malmierca, M.S., Sanchez-Vives, M.V., Escera, C., Bendixen, A.: Neuronal adaptation, novelty detection and regularity encoding in audition. Front Syst. Neurosci. 8, 111 (2014)Google Scholar
  57. 57.
    John, E.R.: Electrophysiological studies of conditioning. In: Quarton, G.C., Melnechuk, T., Schmitt, F.O. (eds.) The Neurosciences: A Study Program, pp. 690–704. Rockefeller University Press, New York (1967)Google Scholar
  58. 58.
    Morrell, F.: Electrical signs of sensory coding. In: Quarton, G.C., Melnechuck, T., Schmitt, F.O. (eds.) The Neurosciences: A Study Program, pp. 452–469. Rockefeller University Press, New York (1967)Google Scholar
  59. 59.
    Schultz, W., Dickinson, A.: Neuronal coding of prediction errors. Annu. Rev. Neurosci. 23, 473–500 (2000)CrossRefGoogle Scholar
  60. 60.
    Schultz, S.R., Panzeri, S.: Temporal correlations and neural spike train entropy. Phys. Rev. Lett. 86, 5823–5826 (2001)CrossRefGoogle Scholar
  61. 61.
    Miller, R.R., Barnet, R.C.: The role of time in elementary associations. Curr. Dir. Psychol. Sci. 2, 106–111 (1993)CrossRefGoogle Scholar
  62. 62.
    Savastano, H.I., Miller, R.R.: Time as content in Pavlovian conditioning. Behav Processes. 44, 147–192 (1998)CrossRefGoogle Scholar
  63. 63.
    Arcediano, F., Miller, R.R.: Some constraints for models of timing: a temporal coding hypothesis perspective. Learn. Motiv. 33, 105–123 (2002)Google Scholar
  64. 64.
    Tucci, V., Buhusi, C.V., Gallistel, R., Meck, W.H.: Towards an integrated understanding of the biology of timing. Philos. Trans. R. Soc. Lond. B Biol. Sci. 369, 20120470 (2014)CrossRefGoogle Scholar
  65. 65.
    Boring, E.G.: Sensation and Perception in the History of Experimental Psychology. Appleton-Century-Crofts, New York (1942)Google Scholar
  66. 66.
    Uttal, W.R. (ed.): Sensory Coding: Selected Readings. Little-Brown, Boston (1972)Google Scholar
  67. 67.
    Uttal, W.R.: The Psychobiology of Sensory Coding. Harper and Row, New York (1973)Google Scholar
  68. 68.
    Rieke, F., Warland, D., de Ruyter, R., Steveninck, V., Bialek, W.: Spikes: Exploring the Neural Code. MIT Press, Cambridge, MA (1997)Google Scholar
  69. 69.
    Cariani, P.: As if time really mattered: temporal strategies for neural coding of sensory information. Reprinted in: K Pribram, ed. Origins: Brain and Self-Organization, Hillsdale, NJ: Lawrence Erlbaum, 1994; 208–252. 12, 161–229 (Reprinted in: K Pribram, ed. Origins: Brain and Self-Organization, Hillsdale, NJ: Lawrence Erlbaum, 1994; 1208–1252) (1995)Google Scholar
  70. 70.
    MacKay, D.M.: Self-organization in the time domain. In: Yovitts, M.C., Jacobi, G.T., Goldstein, G.D. (eds.) Self-Organizing Systems 1962, pp. 37–48. Spartan Books, Washington, D.C. (1962)Google Scholar
  71. 71.
    Pratt, G.: Pulse computation. Department of Electrical Engineering and Computer Science, vol. Ph.D., pp. 214 leaves. Massachusetts Institute of Technology, Cambridge, MA (1989)Google Scholar
  72. 72.
    Braitenberg, V.: The neuroanatomy of time. In: Miller, R. (ed.) Time and the Brain, pp. 391–396. Harwood Academic Ppublishers, Australia (2000)Google Scholar
  73. 73.
    Abeles, M.: Synfire chains. In: Arbib, M.A. (ed.) The Handbook of Brain Theory and Neural Networks (2nd Ed.), pp. 1143–1146. MIT Press, Cambridge, MA (2003)Google Scholar
  74. 74.
    Izhikevich, E.M.: Polychronization: computation with spikes. Neural Comput. 18, 245–282 (2006)MathSciNetCrossRefzbMATHGoogle Scholar
  75. 75.
    Cariani, P.: Temporal coding of periodicity pitch in the auditory system: an overview. Neural Plast. 6, 147–172 (1999)CrossRefGoogle Scholar
  76. 76.
    Cariani, P.: Temporal coding of sensory information in the brain. Acoust. Sci. Tech. 22, 77–84 (2001)CrossRefGoogle Scholar
  77. 77.
    Perkell, D.H., Bullock, T. H.: Neural coding. Neurosciences Research Program Bulletin. 6,3 221–348 (1968)Google Scholar
  78. 78.
    Emmers, R.: Pain: A Spike-Interval Coded Message in the Brain. Raven Press, New York (1981)Google Scholar
  79. 79.
    Cariani, P.A., Delgutte, B.: Neural correlates of the pitch of complex tones. I. Pitch and pitch salience. II. Pitch shift, pitch ambiguity, phase-invariance, pitch circularity, and the dominance region for pitch. J. Neurophysiol. 76, 1698–1734 (1996)Google Scholar
  80. 80.
    Orbach, J.: The Neuropsychological Theories of Lashley and Hebb. University Press of America, Lanham (1998)Google Scholar
  81. 81.
    Cariani, P., Micheyl, C.: Towards a theory of infomation processing in the auditory cortex. In: Poeppel, D., Overath, T., Popper, A. (eds.) Human Auditory Cortex: Springer Handbook of Auditory Research. Springer, New York (2012)Google Scholar
  82. 82.
    Zanto, T.P., Snyder, J.S., Large, E.W.: Neural correlates of rhythmic expectancy. Adv. Cogn. Psychol. 2, 221–231 (2006)CrossRefGoogle Scholar
  83. 83.
    Fujioka, T., Trainor, L.J., Large, E.W., Ross, B.: Internalized timing of isochronous sounds is represented in neuromagnetic beta oscillations. J. Neurosci. 32, 1791–1802 (2012)CrossRefGoogle Scholar
  84. 84.
    Nozaradan, S.: Exploring how musical rhythm entrains brain activity with electroencephalogram frequency-tagging. Philos. Trans. R. Soc. Lond. B Biol. Sci. 369 (2014)Google Scholar
  85. 85.
    Hickok, G., Poeppel, D.: Neural basis of speech perception. Handb. Clin. Neurol. 129, 149–160 (2015)CrossRefGoogle Scholar
  86. 86.
    Ding, N., Melloni, L., Zhang, H., Tian, X., Poeppel, D.: Cortical tracking of hierarchical linguistic structures in connected speech. Nat. Neurosci. (2015)Google Scholar
  87. 87.
    Thaut, M.: Rhythm, music, and the brain: scientific foundations and clinical applications. Routledge, New York (2005)Google Scholar
  88. 88.
    Large, E.W., Snyder, J.S.: Pulse and meter as neural resonance. Ann. N. Y. Acad. Sci. 1169, 46–57 (2009)CrossRefGoogle Scholar
  89. 89.
    Doelling, K.B., Poeppel, D.: Cortical entrainment to music and its modulation by expertise. Proc. Natl. Acad. Sci. USA 112, E6233–E6242 (2015)CrossRefGoogle Scholar
  90. 90.
    Cariani, P., Micheyl, C.: Towards a theory of information processing in the auditory cortex. In: Poeppel, D., Overath, T., Popper, A. (eds.) Human Auditory Cortex: Springer Handbook of Auditory Research, pp. 351–390. Springer, New York (2012)CrossRefGoogle Scholar
  91. 91.
    Doelling, K.B., Arnal, L.H., Ghitza, O., Poeppel, D.: Acoustic landmarks drive delta-theta oscillations to enable speech comprehension by facilitating perceptual parsing. Neuroimage 85(Pt 2), 761–768 (2014)CrossRefGoogle Scholar
  92. 92.
    Farbood, M.M., Rowland, J., Marcus, G., Ghitza, O., Poeppel, D.: Decoding time for the identification of musical key. Atten. Percept. Psychophys. 77, 28–35 (2015)CrossRefGoogle Scholar
  93. 93.
    Swanson, L.W.: Brain Architecture: Understanding the Basic Plan. Oxford University Press, New York (2012)Google Scholar
  94. 94.
    Cariani, P.: Neural timing nets. Neural Netw. 14, 737–753 (2001)CrossRefGoogle Scholar
  95. 95.
    Cariani, P.: Temporal codes, timing nets, and music perception. J. New Music Res. 30, 107–136 (2002)CrossRefGoogle Scholar
  96. 96.
    Cariani, P.A.: Temporal codes and computations for sensory representation and scene analysis. IEEE Trans Neural Netw./Publication IEEE Neural Netw. Counc. 15, 1100–1111 (2004)CrossRefGoogle Scholar
  97. 97.
    Cariani, P.: Outline of a cybernetic theory of brain function based on neural timing nets. Kybernetes 44, 1219–1232 (2015)Google Scholar
  98. 98.
    Sporns, O.: Networks of the brain. MIT Press, Cambridge, Mass (2011)zbMATHGoogle Scholar
  99. 99.
    Abeles, M.: Local Cortical Circuits. An Electrophysiological Study. Springer, Berlin (1982)CrossRefGoogle Scholar
  100. 100.
    Abeles, M.: Corticonics. Cambridge University Press, Cambridge (1990)Google Scholar
  101. 101.
    John, E.R.: Switchboard vs. statistical theories of learning and memory. Science 177, 850–864 (1972)CrossRefGoogle Scholar
  102. 102.
    Lorente de No, R.: Circulation of impulses and memory. In: Schmitt, F.O. (ed.) Macromolecular Specificity and Biological Memory, pp. 89–90. MIT Press, Cambridge, MA (1962)Google Scholar
  103. 103.
    Schmitt, F.O.: Biologically structured microfields and stochastic memory models. In: Schmitt, F.O. (ed.) Macromolecular Specificity and Biological Memory, pp. 7–17. MIT Press, Cambridge, MA (1962)Google Scholar
  104. 104.
    John, E.R.: Studies of memory. In: Schmitt, F.O. (ed.) Macromolecular Specificity and Biological Memory, pp. 80–85. MIT Press, Cambridge, MA (1962)Google Scholar
  105. 105.
    Cariani, P.: Symbols and dynamics in the brain. Biosystems 60, 59–83 (2001)CrossRefGoogle Scholar
  106. 106.
    Landry, C.D., Kandel, E.R., Rajasethupathy, P.: New mechanisms in memory storage: piRNAs and epigenetics. Trends Neurosci. 36, 535–542 (2013)CrossRefGoogle Scholar

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Authors and Affiliations

  1. 1.Hearing Research CenterBoston UniversityBostonUSA

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