Advertisement

Biological Cybernetics

, Volume 62, Issue 1, pp 17–28 | Cite as

Adaptively timed conditioned responses and the cerebellum: A neural network approach

  • J. W. Moore
  • J. E. Desmond
  • N. E. Berthier
Article

Abstract

Conditioned responses often reflect knowledge about the timing of a US. This knowledge is manifested in the dependance of response topography on the CS-US interval employed in training. A neural network model and set of learning rules capable of simulating temporally adaptive features of conditioned responses is reviewed, and simulations are presented. In addition, we present a neural network implementation of the model which is designed to reconcile empirical studies of long-term synaptic depression in the cerebellum with neurobiological evidence from studies of the classically conditioned nictitating membrane response of the rabbit.

Keywords

Neural Network Depression Empirical Study Network Model Neural Network Model 
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. Albus JS (1971) A theory of cerebellar function. Math Biosci 10:25–61Google Scholar
  2. Alkon DL (1984) Calcium-mediated reduction of ionic currents: a biophysical memory trace. Science 226:1037–1045Google Scholar
  3. Berthier NE, Moore JW (1986) Cerebellar Purkinje cell activity related to the classically conditioned nictitating membrane response. Exp Brain Res 63:341–350Google Scholar
  4. Berthier NE, Desmond JE, Moore JW (1987) Brain stem control of the nictitating membrane response. In: Gormezano I, Prokasy WF, Thompson RF (eds) Classical conditioning. III. Lawrence Erlbaum, Hillsdale, NJ, pp 275–286Google Scholar
  5. Berthier NE, Barto AG, Moore JW (1988) Linear systems analysis of cerebellar deep nuclei cells during performance of classical conditioned eyeblink. Soc Neurosci (abstr) 14:1239Google Scholar
  6. Boncau CA (1958) The interstimulus interval and the latency of the conditioned eyelid response. J Exp Psychol 56:464–472Google Scholar
  7. Braitcnberg V (1967) Is the cerebellar cortex a biological clock in the millisecond range? In: Fox CA, Snider RS (eds) Progress in brain research, vol 25. The cerebellum. Elsevier, New York, pp 334–346Google Scholar
  8. Brand S, Dahl AL, Mugnaini E (1976) The length of parallel fibers in the cat cerebellar cortex. An experimental light and electron microscope study. Exp Brain Res 26:39–58Google Scholar
  9. Clark GA, McCormick DA, Lavond DG, Thompson RF (1984)Effects of lesions of cerebellar nuclei on conditioned behavioral and hippocampal responses. Brain Res 291:125–136Google Scholar
  10. Coss RG, Perkel DH (1985) The function of dendritic spines: a review of theoretical issues. Behav Neur Biol 44:151–185Google Scholar
  11. Crepel F, Krupa M (1988) Activation of protein kinase C induces a long-term depression of glutamate sensitivity of cerebellar Purkinje cells. An in vitro study. Brain Res 458:397–401Google Scholar
  12. Desmond JE (1988) Temporally adaptive conditioned responses: representation of the stimulus trace in neural-network models. Computer and Information Science Technical Report 88–80, University of Massachusetts, AmherstGoogle Scholar
  13. Desmond JE, Moore JW (1982) A brain stem region essential for the classically conditioned but not unconditioned nictitating membrane response. Physiol Behav 28:1029–1033Google Scholar
  14. Desmond JE, Moore JW (1986) Dorsolateral pontine tegmentum and the classically conditioned nictitating membrane response: analysis of CR-related activity. Exp Brain Res 65:59–74Google Scholar
  15. Desmond JE, Moore JW (1987) Red nucleus single-unit activity during the classically conditioned rabbit nictitating membrane response. Soc Neurosci (abstr) 13:841Google Scholar
  16. Desmond JE, Moore JW (1988) Adaptive timing in neural networks: the conditioned response. Biol Cybern 58:405–415Google Scholar
  17. Dietrichs E, Walberg F (1983) Cerebellar cortical afferents from the red nucleus in the cat. Exp Brain Res 50:353–358Google Scholar
  18. Donegan NH, Lowery RW, Thompson RF (1983) Effects of lesioning cerebellar nuclei on conditioned leg-flexion responses. Soc Neurosci (abstr) 9:331Google Scholar
  19. Fujita M (1982) Adaptive filter model of the cerebellum. Biol Cybern 45:195–206Google Scholar
  20. Gingrich KJ, Byrne JH (1987) Single-cell neuronal model for associative learning. J Neurophys 57:1705–1715Google Scholar
  21. Gormezano I, Moore JW (1969) Classical conditioning. In: Marx MH (ed) Learning: processes. Collier-Macmillan, LondonGoogle Scholar
  22. Gormezano I, Kehoe EJ, Marshall BS (1983) Twenty years of classical conditioning with the rabbit. Prog Psychobiol Physiol Psychol 10:197–275Google Scholar
  23. Grossberg S, Schmajuk NA (1989) Neural dynamics of adaptive timing and temporal discrimination during associative learning. Neural Networks 2:79–102Google Scholar
  24. Haines DE (1988) Evidence of intracerebellar collateralization of nucleocortical cell processes in a prosimian primate (Galago): a fluorescence retrograde study. J Comp Neurol 275:441–451Google Scholar
  25. Hardiman MJ, Glickstein M, Yeo CH (1988) Kainic acid lesions of the cerebellar cortex abolish the classically conditioned nictitating membrane response of the rabbit. Soc Neurosci (abstr) 14:784Google Scholar
  26. Harvey JA, Winsky L, Schindler CW, McMaster SE, Welsh JP (1988) Asymmetric uptake of 2-deoxy-D-[14G] glucose in the dorsal cochlear nucleus during Pavlovian conditioning in the rabbit. Brain Res 449:213–224Google Scholar
  27. Huang CM, Liu G, Huang R (1982) Projections from the cochlear nucleus to the cerebellum. Brain Res 244:1–8Google Scholar
  28. Hull CL (1932) The goal gradient hypothesis and maze learning. Psychol Rev 39:25–43Google Scholar
  29. Ito M (1984) The cerebellum and neural control. Raven Press, New YorkGoogle Scholar
  30. Ito M (1989) Long-term depression. Ann Rev Neurosci 12:85–102Google Scholar
  31. Ito M, Sakurai M, Tongroach P (1982) Climbing fibre-induced depression of both mossy fibre responsiveness and glutamate sensitivity of cerebellar Purkinje cells. J Physiol (London) 324:113–134Google Scholar
  32. Kamin LJ (1968) Attention-like processes in classical conditioning. In: Prokasy WF (ed) Classical conditioning: a symposium. Appleton, New York, pp 118–147Google Scholar
  33. Kano M, Kato M (1987) Quisqualate receptors are specifically involved in cerebellar synaptic plasticity. Nature 325:276–279Google Scholar
  34. Kano M, Kato M (1988) Modes of induction of long-term depression at parallel fibre-Purkinje cells synapses in rabbit erebellar cortex. Neurosci Res 5:544–556Google Scholar
  35. Kelly TM, McAlduff JD, Bloedel JR (1988) Presence of eyeblink conditioning in decerebrate and decerebellate rabbit. Soc Neurosci (abstr) 14:169Google Scholar
  36. Kimmel HD (1965) Instrumental inhibitory factors in classical conditioning. In: Prokasy WF (ed) Classical conditioning. Appleton-Century-Crofts, New York, pp 148–171Google Scholar
  37. Klopf AH (1988) A neuronal model of classical conditioning. Psychobiology 16:85–125Google Scholar
  38. Lavond DG, Steinmetz JE, Yokaitis MH, Thompson RF (1987)Reacquisition of classical conditioning after removal of cerebellar cortex. Exp Brain Res 67:569–593Google Scholar
  39. Leonard DW, Theios J (1967) Effect of CS-US interval shift on classical conditioning of the nictitating membrane in the rabbit. J Comp Physiol Psychol 63:355–358Google Scholar
  40. Levey AB, Martin I (1968) Shape of the conditioned eyelid response. Psychol Rev 75:398–408Google Scholar
  41. Llinas R, Hillman DE (1969) Physiological and morphological organization of the cerebellar circuits in various vertebrates. In: Llinas R (ed) Neurobiology of cerebellar evolution and development. American Medical Association, Chicago, pp 43–73Google Scholar
  42. Llinas R, Muhlethaler M (1988) Electrophysiology of guinea-pig cerebellar nuclear cells in the in vitro brain stem-cerebellar preparation. J Physiol (London) 404:251–258Google Scholar
  43. Logan FA (1956) A micromolar approach to behavior theory. Psychol Rev 65:63–73Google Scholar
  44. Marchant HG, Moore JW (1973) Blocking of the rabbit's conditioned nictitating membrane response in Kamin's twostage paradigm. J Exp Psychol 101:155–158Google Scholar
  45. Marr D (1969) A theory of cerebellar cortex. J Physiol 202:437–470Google Scholar
  46. Martin I, Levey AB (1965) Efficiency of the conditioned eyelid response. Science 150:781–783Google Scholar
  47. Menne D (1985) Theoretical limits of time resolution in narrow band neurons. In: Michelsen A (ed) Time resolution in auditory systems. Proceedings of the 11th Danavox symposium on hearing. Springer, Berlin, Heidelberg New York, pp 96–107Google Scholar
  48. Millenson JR, Kehoe EJ, Gormezano I (1977) Classical conditioning of the rabbit's nictitating membrane response under fixed and mixed CS-US intervals. Learn Motiv 8:351–366Google Scholar
  49. Moore JW (1979) Brain processes and conditioning. In: Dickinson A, Boakes RA (eds) Mechanisms of learning and motivation: a memorial volume to Jerzy Konorski. Erlbaum, Hillsdale, NJ, pp 111–142Google Scholar
  50. Moore JW, Berthier NE (1987) Purkinje cell activity and the conditioned nictitating membrane response. In: Glickstein M, Yeo C, Stein J (eds) Cerebellum and neuronal plasticity. Plenum Press, New York, pp 339–352Google Scholar
  51. Moore JW, Blazis DEJ (1989) Conditioning and the cerebellum. In: Arbib MA, Amari S (eds) Dynamic interactions in neural networks: Models and data. Springer, New York Berlin Heidelberg, pp 261–277Google Scholar
  52. Moore JW, Stickney KJ (1985) Antiassociations: conditioned inhibition in attentional-associative networks. In: Miller RR, Spear NE (eds) Information processes in animals: conditioned inhibition. Erlbaum, Hillsdale, NJ, pp 209–222Google Scholar
  53. Moore JW, Desmond JE, Berthier NE, Blazis DEJ, Sutton RS, Barto AG (1986) Simulation of the classically conditioned nictitating membrane response by a neuron-like adaptive element: response topography, neuronal firing, and interstimulus intervals. Behav Brain Res 21:143–154Google Scholar
  54. Nelson B, Barmack NH, Mugnaini E (1984) A GABAergic cerebello-olivary projection in the rat. Soc Neurosci (abstr) 10:539Google Scholar
  55. Norman RF, Buchwald JS, Villablanca JR (1977) Classical conditioning with auditory discrimination of the eye blink in decerebrate cats. Science 196:551–553Google Scholar
  56. Nowak AJ, Gormezano I (1988) Reflex modification (RM) and classical conditioning of the rabbit's nictitating membrane response (NMR) to electrical stimulation of brain stem structures as an unconditioned stimulus (UCS). Soc Neurosci (abstr) 14:3Google Scholar
  57. Polenchar BE, Patterson MM (1984) Cerebellar deep nuclei lesions abolish or impair an instrumental avoidance response in rabbit. Soc Neurosci (abstr) 10:123Google Scholar
  58. Port RL, Mikhail AA, Patterson MM (1985) Differential effects of hippocampectomy on classically conditioned rabbit nictitating membrane response related to interstimulus interval. Behav Neurosci 99:200–208Google Scholar
  59. Ross WN, Werman R (1987) Mapping calcium transients in the dendrites of Purkinje cells from the guinea-pig cerebellum in vitro. J Physiol (London) 389:319–336Google Scholar
  60. Sakurai M (1987) Synaptic modification of parallel fiberPurkinje cell transmission in in vitro guinea-pig cerebellar slices. J Physiol (London) 394:463–480Google Scholar
  61. Scheibel ME, Scheibel AB (1985) Structural substrates for integrative patterns in the brain stem reticular core. In: Jasper H, Proctor LD, Knighton RS, Noshay WS, Costello RT (eds) Reticular formation of the brain. Little, Brown, Boston, pp 31–55Google Scholar
  62. Scheibel ME, Scheibel AB (1967) Anatomical basis of attention mechanisms in vertebrate brains. In: Quarton GC, Melnechuk T, Schmitt FO (eds) The neurosciences. A study program. The Rockefeller University Press, New York, pp 577–602Google Scholar
  63. Schmajuk NA, Moore JW (1988) The hippocampus and the classically conditioned nictitating membrane response: a real-time attentional-associative model. Psychobiology 16:20–35Google Scholar
  64. Schmajuk NA, Moore JW (1989) Simulation of the classically conditioned nictitating membrane response by an attentional-associative network: response topography, neuronal firing, and the effects of hippocampal lesions and simulation. Behav Brain Res 32:173–189Google Scholar
  65. Schreurs BG (1988) Stimulation of the spinal trigeminal nucleus supports classical conditioning of the rabbit's nictitating membrane response. Behav Neurosci 102:163–172Google Scholar
  66. Sears RJ, Baker JS, Frey PW (1979) The eye blink as a timelocked response: implications for serial and second-order conditioning. J Exp Psychol: Anim Behav Proc 5:43–64Google Scholar
  67. Sutton RS, Barto AG (1981) Toward a modern theory of adaptive networks: expectation and prediction. Psychol Rev 88:135–170Google Scholar
  68. Tank DW, Sugimori M, Connor JA, Llinas RR (1988) Spatially resolved calcium dynamics of mammalian Purkinje cells in cerebellar slice. Science 242:773–777Google Scholar
  69. Tesauro G (1986) Simple neural models of classical conditioning. Biol Cybern 55:187–200Google Scholar
  70. Thompson RF (1986) The neurobiology of learning and memory. Science 233:941–947Google Scholar
  71. Thompson RF, Donegan NH, Clark GA, Lavond DG, Lincoln JS, Madden J, Mamounas LA, Mauk MD, McCormick DA (1987) Neuronal substrates of discrete conditioned reflexes, conditioned fear states, and their interactions in the rabbit. In: Gormezano I, Prokasy WF, Thompson RF (eds) Classical conditioning. III. Erlbaum, Hillsdale, NJ, pp 371–400Google Scholar
  72. Weiss C, Tocco G, Thompson JK, Thompson RF (1988) Anatomical analysis of cerebellar-olivary projections in the rabbit. Soc Neurosci (abstr) 14:493Google Scholar
  73. Wells GR, Hardiman MJ, Yeo CH (1989) Visual projections to the pontine nuclei in rabbit: Orthograde and retrograde tracing studies with WGA-HRP. J Comp Neurol 279:629–652Google Scholar
  74. Yeo CB (1987) Cerebellum and classical conditioning. In: Glickstein M, Yeo C, Stein J (eds) Cerebellum and neuronal plasticity. Plenum Press, New York, pp 321–338Google Scholar
  75. Yeo CH, Hardiman MJ (1988) Loss of conditioned responses following cerebellar cortical lesions is not a performance deficit. Soc Neurosci (abstr) 14:3Google Scholar
  76. Zipser D (1986) A model of hippocampal learning during classical conditioning. Behav Neurosci 100:764–776Google Scholar

Copyright information

© Springer-Verlag 1989

Authors and Affiliations

  • J. W. Moore
    • 1
  • J. E. Desmond
    • 1
  • N. E. Berthier
    • 1
  1. 1.Department of PsychologyUniversity of MassachusettsAmherstUSA

Personalised recommendations