Neuroscience pp 1-23

A Short History of Neuroscience

Abstract

Although attempts to understand the physical bases for mental processes go back to the early Greek and Egyptian civilizations, modern electrophysiology began with the late eighteenth-century investigations by Luigi Galvani on the sciatic nerve-muscle preparation of the frog [8]. In 1791, this Italian physician reported that the muscle would twitch when the nerve was stimulated by a bimetallic contact and also by atmospheric electricity. Thus, Galvani proposed three types of electricity—chemical, atmospheric, and animal-with the latter being different from the two others, but his compatriot Alessandro Volta disagreed. In the attempt to show that Galvani's animal electricity was identical to that produced by bimetallic currents, Volta invented the battery, thereby launching the science of electricity in the historically convenient year of 1800. All of these early experiments were carefully repeated by the German physicist Frederick von Humboldt, confirming both Volta's view that the various forms of electricity are closely related and Galvani's observation that animal electricity has qualitatively distinctive features. Let us consider these differences.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    ED Adrian, The all-or-none principle in nerve, J. Physiol. (London) 47 (1914) 460–474.Google Scholar
  2. [2]
    S Amari, Characteristics of randomly interconnected threshold-element networks and network systems, Proc. IEEE 59 (1971) 35–47.Google Scholar
  3. [3]
    M Arbib (ed), The Handbook of Brain Theory and Neural Networks, MIT Press, Cambridge, MA, 1995.Google Scholar
  4. [4]
    J Bernstein, Untersuchungen zur Thermodynamik der bioelektrischen Ströme, Arch. ges. Physiol. 92 (1902) 521–562.CrossRefGoogle Scholar
  5. [5]
    RL Beurle, Properties of a mass of cells capable of regenerating pulses, Philos. Trans. R. Soc. (London) 240A (1956) 55–94.CrossRefGoogle Scholar
  6. [6]
    HD Block, A model for brain functioning, Rev. Mod. Phys. 34 (1962) 123–135.CrossRefGoogle Scholar
  7. [7]
    V Braitenberg, Cell assemblies in the visual cortex. In Theoretical Approaches to Complex Systems, Springer-Verlag, Berlin, 1978.Google Scholar
  8. [8]
    MAB Brasier, A History of the Electrical Activity of the Brain, Pitman, London, 1961.Google Scholar
  9. [9]
    ER Caianiello, Outline of a theory of thought-processes and thinking machines, J. theoret. Biol. 1 (1961) 204–235.CrossRefGoogle Scholar
  10. [10]
    SH Chung, SA Raymond and JY Lettvin, Multiple meaning in single visual units, Brain Behav. Evol. 3 (1970) 72–101.PubMedGoogle Scholar
  11. [11]
    KS Cole and HJ Curtis, Electrical impedance of nerve during activity, Nature 142 (1938) 209.Google Scholar
  12. [12]
    KS Cole, Membranes, Ions and Impulses, University of California Press, Berkeley, 1968.Google Scholar
  13. [13]
    JD Cowan, A statistical mechanics of nervous activity. In Some Mathematical Questions in Biology, American Mathematical Society, Providence, 1970.Google Scholar
  14. [14]
    SA Deadwyler, T Burn, and RE Hampson, Hippocampal ensemble activity during spatial delayed-nonmatch-to-sample performance in rats, J. Neurosci. 16 (1996) 354–372.PubMedGoogle Scholar
  15. [15]
    GM Edelman, Bright Air, Brilliant Fire: On the Matter of the Mind, Basic Books, New York, 1992.Google Scholar
  16. [16]
    M Faraday, Faraday’s Chemical History of a Candle, Chicago Review Press, Chicago, 1988. (Republication of A Course of Six Lectures on the Chemical History of a Candle, which first appeared in 1861.)Google Scholar
  17. [17]
    R FitzHugh, Impulses and physiological states in theoretical models of nerve membrane, Biophys. J. 1 (1961) 445–466.PubMedGoogle Scholar
  18. [18]
    E Fransén, Biophysical Simulation of Cortical Associative Memory, Doctoral thesis, Royal Institute of Technology, Stockholm, 1996.Google Scholar
  19. [19]
    WJ Freeman, Premises in neurophysiological studies of learning. In Neurobiology of Learning and Memory, G Lynch, JL McGaugh, and NM Weinberger (eds), Guilford Press, New York, 1984.Google Scholar
  20. [20]
    PH Greene, On looking for neural networks and “cell assemblies” that underlie behavior, Bull. Math. Biophys. 24 (1962) 247–275 and 395–411.PubMedCrossRefGoogle Scholar
  21. [21]
    E Harth, The Creative Loop: How the Brain Makes a Mind, Addison-Wesley, Reading, MA, 1993.Google Scholar
  22. [22]
    DO Hebb, Organization of Behavior: A Neuropsychological Theory, John Wiley &; Sons, New York, 1949.Google Scholar
  23. [23]
    H Helmholtz, Messungen über den seitlichen Verlauf der Zuckung animalischer Muskeln und die Fortpflanzungsgeschwindigkeit der Reisung in den Nerven, Arch. Anat. Physiol. (1850) 276–364.Google Scholar
  24. [24]
    W Heron, The pathology of boredom, Sci. Am. January 1957.Google Scholar
  25. [25]
    AL Hodgkin and AF Huxley, A quantitative description of membrane current and its application to conduction and excitation in nerve, J. Physiol. (London) 117 (1952) 500–544.Google Scholar
  26. [26]
    AL Hodgkin, The Conduction of the Nervous Impulse, Liverpool University Press, Liverpool, 1964.Google Scholar
  27. [27]
    JJ Hopfield, Neural networks and physical systems with emergent collective computational abilities, Proc. Natl. Acad. Sci. USA 79 (1982) 2554–2558.PubMedCrossRefGoogle Scholar
  28. [28]
    W James, What is an emotion? In Psychology Classics: A Series of Reprints and Translations, K. Dunlap (ed), Wilkins & Wilkins, Baltimore, 1922 (reprinted from Mind, 1884, 188–205).Google Scholar
  29. [29]
    BI Khodorov, The Problem of Excitability, Plenum Press, New York, 1974.Google Scholar
  30. [30]
    C Koch, Biophysics of Computation: Information Processing in Single Neurons, Oxford University Press, New York, 1999.Google Scholar
  31. [31]
    CR Legéndy, On the scheme by which the human brain stores information, Math. Biosci. 1 (1967) 555–597.CrossRefGoogle Scholar
  32. [32]
    RS Lillie, Factors affecting transmission and recovery in the passive iron wire nerve model, J. Gen. Physiol. 7 (1925) 473–507.CrossRefPubMedGoogle Scholar
  33. [33]
    R Lorente de Nó, Studies on the structure of the cerebral cortex: I. The area entrorhinalis, J. Psychol. Neurol. 45 (1934) 381–438.Google Scholar
  34. [34]
    R Lorente de Nó, Analysis of the activity of the chains of internuncial neurons, J. Neurophysiol. 1 (1938) 207–244.Google Scholar
  35. [35]
    R Luther, Räumliche Fortpflanzung chemischer Reaktionen. Z. Elektrochem. 12(32) (1906) 596–600. (English translation in J. Chem. Ed. 64 (1987) 740–742.)CrossRefGoogle Scholar
  36. [36]
    EM Maynard, CT Nordhausen, and RA Normann, The Utah intracortical electrode array: A recording structure for potential brain-computer interfaces, Electroencephalogr. Clin. Neurophysiol. 102 (1997) 228–239.PubMedCrossRefGoogle Scholar
  37. [37]
    WS McCulloch and WH Pitts, A logical calculus of the ideas immanent in nervous activity, Bull. Math. Biophys. 5 (1943) 115–133.CrossRefGoogle Scholar
  38. [38]
    TJ McHugh, KI Blum, JZ Tsien, S Tonegawa, and MA Wilson, Impaired hippocampal representation of space in CA1-specific NMDAR1 knockout mice, Cell 87 (1996) 1339–1349.PubMedCrossRefGoogle Scholar
  39. [39]
    PM Milner, The cell assembly: Mark II, Psychol. Rev. 64 (1957) 242–252.PubMedCrossRefGoogle Scholar
  40. [40]
    M Minsky and S Papert, Perceptrons, MIT Press, Cambridge, MA, 1969.Google Scholar
  41. [41]
    J Nagumo, S Arimoto, and S Yoshizawa, An active impulse transmission line simulating nerve axon, Proc. IRE 50 (1962) 2061–2070.CrossRefGoogle Scholar
  42. [42]
    MAL Nicolelis, EE Fanselow, and AA Ghazanfar, Hebb’s dream: The resurgence of cell assemblies, Neuron 19 (1997) 219–221.PubMedCrossRefGoogle Scholar
  43. [43]
    MAL Nicolelis, AA Ghazanfar, BM Faggin, S Votaw, and LMO Oliveira, Reconstructing the engram: Simultaneous, multisite, many single neuron recordings, Neuron 18 (1997) 529–537.PubMedCrossRefGoogle Scholar
  44. [44]
    NJ Nilsson, Learning Machines: Foundations of Trainable Pattern-Classifying Systems, Morgan Kaufmann, San Mateo, CA, 1990.Google Scholar
  45. [45]
    CT Nordhausen, EM Maynard, and RA Normann, Single unit recording capabilities of a 100 microelectrode array. Brain Res. 726 (1996) 129–140.PubMedCrossRefGoogle Scholar
  46. [46]
    PL Nuñes, The brain wave equation: A model for the EEG; Math. Biosci. 21 (1974) 279–297.CrossRefGoogle Scholar
  47. [47]
    G Palm, Toward a theory of cell assemblies, Biol. Cybern. 39 (1981) 181–194.PubMedCrossRefGoogle Scholar
  48. [48]
    G Palm, Cell assemblies, coherence, and corticohippocampal interplay, Hippocampus 3 (1993) 219–226.PubMedGoogle Scholar
  49. [49]
    RM Pritchard, W Heron, and DO Hebb, Visual perception approached by the method of stabilised images, Can. J. Psyckol. 14 (1960) 67–77.Google Scholar
  50. [50]
    S RamÓn y Cajal, Structure et connexions des neurons, Arch. Fisiol. 5 (1908) 1–25.Google Scholar
  51. [51]
    A Rapoport, “Ignition” phenomena in random nets, Bull. Math. Biophys. 14 (1952) 35–44.CrossRefGoogle Scholar
  52. [52]
    N Rochester, JH Holland, LH Haibt, and WL Duda, Tests on a cell assembly theory of the action of a brain using a large digital computer, Trans. IRE Inf. Theory IT-2 (1956) 80–93.CrossRefGoogle Scholar
  53. [53]
    F Rosenblatt, The Perceptron: A probabilistic model for information storage and organisation in the brain, Psychol. Rev. 65 (1958) 298–311.CrossRefGoogle Scholar
  54. [54]
    WAH Rushton, A theory of the effects of fibre sise in medullated nerve, J. Physiol. (London) 115 (1951) 101–122.Google Scholar
  55. [55]
    AC Scott, The electrophysics of a nerve fiber, Rev. Mod. Phys. 47 (1975) 487–533.CrossRefGoogle Scholar
  56. [56]
    AC Scott, Nonlinear Science: Emergence and Dynamics of Coherent Structures, Oxford University Press, Oxford, 1999.Google Scholar
  57. [57]
    CS Sherrington, The Integrative Action of the Nervous System, Yale University Press, New Haven, 1906.Google Scholar
  58. [58]
    DR Smith and CH Davidson, Maintained activity in neural nets, J. Assoc. Comput. Mach. 9 (1962) 268–279.Google Scholar
  59. [59]
    G Stuart, N Spruston, and M Häusser, Dendrites, Oxford University Press, Oxford, 1999.Google Scholar
  60. [60]
    I Tasaki, Physiology and Electrochemistry of Nerve Fibers, Academic Press, New York, 1982.Google Scholar
  61. [61]
    WR Thompson and W Heron, The effects of restricting experience on the problem-solving capacity of dogs, Can. J. Psychol. 8 (1954) 17–31.PubMedGoogle Scholar
  62. [62]
    AM Turing, The chemical basis of morphogenesis, Philos. Trans. R. Soc. London B237 (1952) 37–72.Google Scholar
  63. [63]
    SG Waxman, Regional differentiation of the axon: A review with special reference to the concept of the multiplex neuron, Brain Res. 47 (1972) 269–288.PubMedCrossRefGoogle Scholar
  64. [64]
    H White, The formation of cell assemblies, Bull. Math. Biophys. 23 (1961) 43–53.CrossRefGoogle Scholar
  65. [65]
    N Wiener, Cybernetics, The Technology Press, Cambridge, MA, 1961.Google Scholar
  66. [66]
    HR Wilson and JD Cowan, Excitatory and inhibitory interactions in localised populations of neurons, Biophys. J. 12 (1972) 1–24.PubMedGoogle Scholar
  67. [67]
    MA Wilson and BL McNaughton, Dynamics of the hippocampal ensemble code for space, Science 261 (1993) 1055–1058.PubMedCrossRefGoogle Scholar
  68. [68]
    JY Wu, LB Cohen, and CX Falk, Neuronal activity during different behaviors in Aplysia: A distributed organisation? Science 263 (1994) 820–823.PubMedCrossRefGoogle Scholar
  69. [69]
    JZ Young, Structure of nerve fibers and synapses in some invertebrates. Cold Spring Harbor Sytmp. Quant. Biol. 4 (1936) 1–6.Google Scholar
  70. [70]
    JZ Young, Doubt and Certainty in Science, Oxford University Press, Oxford, 1951.Google Scholar
  71. [71]
    YaB Zeldovich and DA Frank-Kamenetsky, K teorii ravnomernogo rasprostranenia plameni, Dokl. Akad. Nauk SSSR 19 (1938) 693–697.Google Scholar

Copyright information

© Springer-Verlag New York, Inc. 2002

Personalised recommendations