Skip to main content
SpringerLink
Log in

Neurology and Neurolinguistics

  • Chapter
Machine Learning of Natural Language

  • 303 Accesses

Abstract

We come now to an overview of the anatomical and physiological evidence, and the neurological models which underlie and motivate the research we described earlier. We start with the brain, its organization and connection. The most accessible parts of the brain for physiological investigation are those which are directly sensory-motor related. These therefore form the focus of our brief neuroanatomical tour.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Nauta, W. J. H., and M. Feirtag, “The Organization of the Brain”, Sci. Amer., Vol.241 (September, 1979), pp.78–105

    Article  Google Scholar 

  2. Geschwind, N., “Specializations of the Human Brain”, Set Amer., Vol.241 (September, 1979), pp.158–171.

    Google Scholar 

  3. Op. cit., p.160.

    Google Scholar 

  4. Eccles, J.C., M. Ito, and J. Szentagothai, The Cerebellum as a Neuronal Machine (Springer-Verlag, 1967), p.314.

    Google Scholar 

  5. Stevens, C.F., “The Neuron”, Sci. Amer. Vol. 241 (September, 1979), p.49.

    Article  Google Scholar 

  6. Op. cit., p.49ff.

    Google Scholar 

  7. Iversen, L.L., “The Chemistry of the Brain”, Sci. Amer. Vol.241 (September, 1979), pp.112–3.

    Article  Google Scholar 

  8. Hubel, D.H., “The Brain (Introduction)”, Sci. Amer. Vol.241 (September, 1979), p.136.

    Article  Google Scholar 

  9. Op. cit., p.36ff.

    Google Scholar 

  10. Op. cit., p.144

    Google Scholar 

  11. also Jacobson, M., Developmental Neurobiology (Plenum Press, New York, NY, 1978), p.359.

    Google Scholar 

  12. Minsky, M., and S. Papert, Perceptrons (MIT Press, 1969).

    MATH  Google Scholar 

  13. Gigley, H.M., “Artificial Intelligence meets Brain Theory: An Integrated Approach to Simulation Modelling of Natural Language Processing”, in R. Trappl, ed., Proceedings of the Sixth European Meeting on Cybernetics and Systems Research (North Holland, 1982), p.127.

    Google Scholar 

  14. Kandel, E. R., “Small Systems of Neurons”, Sci. Amer. Vol. 241 (September, 1979), pp.60–77.

    Article  Google Scholar 

  15. Eccles, J.C., M. Ito, and J. Szentagothai, The Cerebellum as a Neuronal Machine (Springer-Verlag, 1967).

    Google Scholar 

  16. Powers, David M. W., “Lateral Interaction Behaviour Derived from Neural Packing Considerations”, DCS Report No 8317, Department of Computer Science (University of New South Wales, Australia, April, 1983).

    Google Scholar 

  17. Pollen, D. A., and S. F. Ronner, IEEE Trans Sys. Man. Cyb., Vol. SMC-13 (September, 1983), p.909

    Google Scholar 

  18. Sakitt, B., and H. B. Barlow, “A Model for the Economical Encoding of the Visual Image in the Cerebral Cortex”, Biol. Cyb., Vol. 43 (1982), pp.97–108.

    Article  Google Scholar 

  19. Kupfermann, I., and H. Pinsker, “Cellular Models of Learning and Cellular Mechanisms of Plasticity in Aplysia”, in K. H. Pribram and D. E. Broadbent, eds, Biology of Memory (Academic Press, 1970), pp.163–174

    Google Scholar 

  20. Lashley, K.S., “Studies of Cerebral Function in Learning, VI, The Theory that Synaptic Resistance is Reduced by the Passage of the Nerve Impulse” (Reprinted from Psychol Rev., 1924, 31, 369–375), in F. A. Beach, D. O. Hebb, C. T. Morgan and H. W. Nissen, eds, The Neurophysiology of Lashley (McGraw-Hill, 1960), pp.136–141.

    Google Scholar 

  21. Hebb, D.O., Organization and Behaviour (Wiley, New York, 1949).

    Google Scholar 

  22. Sinz, Rainer, and Mark R. Rosenzweig, Psychophysiology: Memory, Motivation and Event-related Potentials in Mental Operations (VEB Gustav Fischer Verlag, Jena and Berlin, GDR, 1983)

    Google Scholar 

  23. Grechenko, T.N., Rainer Sinz, and E. N. Sokolov, “Neuronal Memory: Localization and Stimulus Discrimination”, in Psychophysiology: Memory, Motivation and Event-related Potentials in Mental Operations, ed. Rainer Sinz and Mark R. Rosenzweig (VEB Gustav Fischer, 1983), pp.131–135.

    Google Scholar 

  24. Matthies, H., “Memory Formation: A Model of Corresponding Neuronal Processes”, in Psychophysiology: Memory, Motivation and Event-related Potentials in Mental Operations, Rainer Sinz and Mark R. Rosenzweig, eds. (VEB Gustav Fischer, 1983), pp.31–38

    Google Scholar 

  25. Kandel, E. R., “Small Systems of Neurons”, Sci Amer. Vol. 241 (September, 1979), pp.60–77.

    Article  Google Scholar 

  26. Hyden, H., “The Question of a Molecular Basis for the Memory Trace”, in K. H. Pribram and D. E. Broadbent, eds, Biology of Memory (Academic Press, 1970), pp. 101–119.

    Google Scholar 

  27. McConnell, James V., T. Shigehisa, and H. Salive, “Attempts to Transfer Approach and Avoidance Responses by RNA Injections in Rats”, in K. H. Pribram and D. E. Broadbent, eds, Biology of Memory (Academic Press, 1970), pp.129–159.

    Google Scholar 

  28. Jakobson, A. L., and J. M. Schlecter, “Chemical Transfer of Training: Three Years Later”, in K. H. Pribram and D. E. Broadbent, eds, Biology of Memory (Academic Press, 1970), pp.123–128.

    Google Scholar 

  29. Sinz, Rainer, and Mark R. Rosenzweig, Psychophysiology: Memory, Motivation and Event-related Potentials in Mental Operations (VEB Gustav Fischer Verlag, Jena and Berlin, GDR, 1983), p.119.

    Google Scholar 

  30. Fukushima, K., “Cognitron: A Self-organizing Multilayered Neural Network”, Biol Cyb., Vol. 20 (1975), p.122.

    Article  Google Scholar 

  31. Sutton, R.S., and A. G. Barto, “Towards a Modern Theory of Adaptive Networks: Expectation and Prediction”, Psych. Rev., Vol. 88 (1981), p.138f.

    Article  Google Scholar 

  32. Matthies, H., “Memory Formation: A Model of Corresponding Neuronal Processes”, in Psychophysiology: Memory, Motivation and Event-related Potentials in Mental Operations, Rainer Sinz and Mark R. Rosenzweig, eds. (VEB Gustav Fischer, 1983), pp.31–38

    Google Scholar 

  33. Kandel, E. R., “Small Systems of Neurons”, Sci. Amer. Vol. 241 (September, 1979), pp.60–77

    Article  Google Scholar 

  34. Tsukahara, N., “Synaptic Plasticity in the Mammalian Central Nervous System”, Ann. Rev. Neurosci., Vol. 4 (1981), pp.351–379.

    Article  Google Scholar 

  35. Melkonian, D.S., H. H. Mkrtchian, and V. V. Fanardjian, “Simulation of Learning Processes in Neuronal Networks of the Cerebellum”, Biol Cyb., Vol.45, (1982), p.80.

    Article  Google Scholar 

  36. Marr, D., “A Theory of Cerebellar Cortex”, J. Physiol, Vol.202 (1969), pp.437–470.

    Google Scholar 

  37. Kupfermann, I., and H. Pinsker, “Cellular Models of Learning and Cellular Mechanisms of Plasticity in Aplysia”, in K. H. Pribram and D. E. Broadbent, eds, Biology of Memory (Academic Press, 1970), pp.163–174.

    Google Scholar 

  38. Malsburg, C. von der, “Self-Organization of Orientation Selective Cells in the Striate Cortex”, Kybemetik, Vol. 14 (1973), p.88.

    Google Scholar 

  39. Barto, A. G., and R. S. Sutton, “Landmark Learning: An Illustration of Associative Learning”, Technical Report #81–12 (Dept of Comp. and Inf. Sci., U. of Massachusetts, 1981)

    Google Scholar 

  40. Barto, A. G., R. S. Sutton, and P. S. Brower, “Associative Search Network: A Reinforcement Learning Associative Memory”, Biol. Cyb., Vol. 40 (1981), pp.201–211

    Article  MATH  Google Scholar 

  41. Sutton, R.S., and A. G. Barto, “Towards a Modern Theory of Adaptive Networks: Expectation and Prediction”, Psych. Rev., Vol. 88 (1981), pp.135–170

    Article  Google Scholar 

  42. Klopf, Harry, The Hedonistic Neuron: A Theory of Memory, Learning and Intelligence (Hemisphere, Washington DC, 1982).

    Google Scholar 

  43. Matthies, H., “Memory Formation: A Model of Corresponding Neuronal Processes”, in Psychophysiology: Memory, Motivation and Event-related Potentials in Mental Operations, Rainer Sinz and Mark R. Rosenzweig, eds. (VEB Gustav Fischer, 1983), pp.31–38.

    Google Scholar 

  44. Klopf, Harry, The Hedonistic Neuron: A Theory of Memory, Learning and Intelligence (Hemisphere, Washington DC, 1982), pp.9–16.

    Google Scholar 

  45. Kandel, E. R., “Small Systems of Neurons”, Sci. Amer. Vol. 241 (September, 1979), pp.60–77

    Article  Google Scholar 

  46. Sinz, Rainer, and Mark R. Rosenzweig, Psychophysiology: Memory, Motivation and Event-related Potentials in Mental Operations (VEB Gustav Fischer Verlag, Jena and Berlin, GDR, 1983).

    Google Scholar 

  47. Malsburg, C. von der, “Self-Organization of Orientation Selective Cells in the Striate Cortex”, Kybernetik, Vol. 14 (1973), pp.85–100.

    Article  Google Scholar 

  48. Goldschlager, Leslie M., A Computational Theory of Higher Brain Function (Computer Science Department, Standford University, Standford, CA, April 1984).

    Google Scholar 

  49. Grossberg, S., “Associative and Competitive Principles of Learning and Development”, in Competition and Cooperation in Neural Nets, S. Amari and M. A. Arbib, eds (Springer-Verlag, 1982), pp.295–341

    Google Scholar 

  50. Ellias, S.A., and S. Grossberg, “Pattern Formation, Contrast Control and Oscillations in the Short Term Memory of Shunting On-Centre Off-Surround Networks”, Biol. Cyb., Vol. 20 (1975), pp.69–98.

    Article  MathSciNet  MATH  Google Scholar 

  51. Malsburg, C. von der, and J. D. Cowan, “Outline of a Theory for the Ontogenesis of Iso-Orientation Domains in the Visual Cortex”, Biol. Cyb., Vol. 45 (1982), pp.49–56.

    Article  Google Scholar 

  52. Cowan, W.M., “The Development of the Brain”, Sci. Amer., Vol.241 (September, 1979), p.116.

    Article  Google Scholar 

  53. Pettigrew, J. D., C. Olson, and H. V. B. Hirsch, “Cortical Effect of Selective Visual Experience: Degeneration or Reorganization?”, Brain Research, Vol. 51 (1973), pp.345–351.

    Article  Google Scholar 

  54. Tsukahara, N., “Synaptic Plasticity in the Mammalian Central Nervous System”, Ann. Rev. Neurosci., Vol. 4 (1981), p.430.

    Article  Google Scholar 

  55. Cowan, W.M., “The Development of the Brain”, Sci. Amer., Vol.241 (September, 1979), p.116.

    Article  Google Scholar 

  56. Jacobson, M., Developmental Neurobiology (Plenum Press, New York, NY, 1978), p.399ff.

    Google Scholar 

  57. Willshaw, David J., and C. von der Malsburg, “How patterned neural connections can be set up by self-organization”, Proc R. Soc. Lond. B, Vol. 194 (1976), pp.431–445

    Article  Google Scholar 

  58. Willshaw, David J., and C. von der Malsburg, “A Marker Induction Mechanism for the Establishment of Ordered Neural Mappings: Its Application to the Retinotectal Problem”, Phil. Trans. Roy. Soc. Lond. B, Vol. 287 (1979), pp.203–243.

    Article  Google Scholar 

  59. Aertsen, A. M. H. J., and P. I. M. Johannesma, “The Spectro-Temporal Receptive: A Functional Characteristic of Auditory Neurons”, Biol. Cyb., Vol. 42 (1981), pp.133–143

    Article  MATH  Google Scholar 

  60. Aertsen, A. M. H. J., and P. I. M. Johannesma, “A Comparison of the Spectro-Temporal Sensitivity of Auditory Neurons to Tonal and Natural Stimuli”, Biol Cyb., Vol. 42 (1981), pp.145–156.

    Article  Google Scholar 

  61. Grossberg, S., “Associative and Competitive Principles of Learning and Development”, in Competition and Cooperation in Neural Nets, S. Amari and M. A. Arbib, eds (Springer-Verlag, 1982), pp.295–341.

    Google Scholar 

  62. Lettvin, J.Y., H. R. Maturana, W. S. McCulloch, and W. H. Pitts, “What the Frog’s Eye Tells the Frog’s Brain”, Proceedings of the Institute of Radio Engineers, Vol.47 (November, 1959), pp.1940–1951.

    Google Scholar 

  63. Hirai, Y., “A Template Matching Model for Pattern Recognition: Self-Organization of Templates and Template Matching by a Disinhibitory Neural Network”, Biol Cyb., Vol. 38 (1980), pp.91–101.

    Article  MATH  Google Scholar 

  64. Wilks, Y., “An Artificial Intelligence Approach to Machine Translation”, in Roger C. Schank and K. M. Colby, eds, Computer Models of Thought and Language (Freeman, 1973), p.115.

    Google Scholar 

  65. Willshaw, David J., and H. C. Longuet-Higgins, “The Holophone—Recent Developments”, in D. Michie, ed., Machine Intelligence 4 (Edinburgh UP, Edinburgh UK, 1969), p.353f.

    Google Scholar 

  66. Op. cit., p.355.

    Google Scholar 

  67. Longuet-Higgins, H. C, “Holographic Model of Temporal Recall”, Nature, Vol. 217 (6th Jan 1968), p. 104

    Article  Google Scholar 

  68. Willshaw, David J., O. P. Buneman, and H. C. Longuet-Higgins, “Non-Holographic Associative Memory”, Nature, Vol. 222 (7th June 1969), pp.960–962.

    Article  Google Scholar 

  69. Spinelli, D.N., “OCCAM: A Computer Model for a Content Addressable Memory in the Central Nervous System”, in K. H. Pribram and D. E. Broadbent, Biology of Memory (Academic Press, 1970), pp.293–306.

    Google Scholar 

  70. Hirai, Y., “A Model of Human Associative Processor (HASP)”, IEEE Trans Sys. Man. Cyb., Vol. SMC-13 (September, 1983), pp.851–856

    Google Scholar 

  71. Willwacher, G., “Storage of a Temporal Pattern Sequence in a Network”, Biol Cyb., Vol. 43 (1982), pp.115–126.

    Article  Google Scholar 

  72. Malsburg, C. von der, “Self-Organization of Orientation Selective Cells in the Striate Cortex”, Kybemetik, Vol. 14 (1973), pp.85–100.

    Google Scholar 

  73. Lashley, K.S., “Studies of Cerebral Function in Learning, VI, The Theory that Synaptic Resistance is Reduced by the Passage of the Nerve Impulse” (Reprinted from Psychol Rev., 1924, 31, 369–375), in F. A. Beach, D. O. Hebb, C. T. Morgan and H. W. Nissen, eds, The Neurophysiology of Lashley (McGraw-Hill, 1960), p.500f.

    Google Scholar 

  74. Uhr, Leonard, Pattern Recognition, Learning and Thought: Computer-Programmed Models of Higher Mental Processes (Prentice-Hall, Englewood Cliffs, NJ, 1973), p.xix.

    MATH  Google Scholar 

  75. Zipser, Birgit, and Ronald McKay, “Monoclonal antibodies distinguish identifiable neurones in the leech”, Nature, Vol. 289 (12 February 1981), p.554.

    Article  Google Scholar 

  76. Chang, C. L., and R. C. Lee, Symbolic Logic and Mechanical Theorem Proving (Academic Press, 1973), p.193.

    MATH  Google Scholar 

  77. Jacobson, M., Developmental Neurobiology (Plenum Press, New York, NY, 1978), p375.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. FB Informatik, University of Kaiserslautern, 259A Trafalgar St., 2049, Petersham, New South Wales, Australia

    David M. W. Powers ThC(Hons), PhD, MACS, MIEEE (Senior Research Fellow, Director)

  2. Honorary Associate in Computing, MPCE, Macquarie University, 259A Trafalgar St., 2049, Petersham, New South Wales, Australia

    David M. W. Powers ThC(Hons), PhD, MACS, MIEEE (Senior Research Fellow, Director)

  3. IMPACT Ltd, 259A Trafalgar St., 2049, Petersham, New South Wales, Australia

    David M. W. Powers ThC(Hons), PhD, MACS, MIEEE (Senior Research Fellow, Director)

  4. ‘Bentwys’, Llanbair Discoed, NB6 6LX, Chepstow, Gwent, UK

    Christopher C. R. Turk MA (Cantab), DPhil (Sussex)

  5. College of Cardiff, University of Wales, UK

    Christopher C. R. Turk MA (Cantab), DPhil (Sussex)

Authors
  1. David M. W. Powers ThC(Hons), PhD, MACS, MIEEE
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christopher C. R. Turk MA (Cantab), DPhil (Sussex)
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 1989 Springer-Verlag London Limited

About this chapter

Cite this chapter

Powers, D.M.W., Turk, C.C.R. (1989). Neurology and Neurolinguistics. In: Machine Learning of Natural Language. Springer, London. https://doi.org/10.1007/978-1-4471-1697-4_7

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-1697-4_7

  • Publisher Name: Springer, London

  • Print ISBN: 978-3-540-19557-3

  • Online ISBN: 978-1-4471-1697-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation