Models and Analogues in Biology

By Society for Experimental Biology | Go to book overview
which for strong feedback over many paths has an approximate magnitude . Since, however, both Tin and TB are proportional to the gain k, we have a transmission modulus that is practically independent of k. Fluctuations of gain in the M feedback paths tend to cancel out if they occur at random about a stable mean value and the summating unit is thus more accurate than one operating without feedback.More complex circuits giving what has been called 'detail filtering' and 'maximum amplitude filtering' have also been described (Taylor, 1959), and the main problems for the future appear to centre on the classification of types of circuit and quantitative analysis of their properties. Eventually it may be possible to draw accurate signal flow diagrams from observation of the nervous system but at present we can only make hypothetical diagrams that do not conflict with any observations of anatomy and neurophysiology for the region considered.
REFERENCES
BURNS B. DELISLE ( 1954). The production of after bursts in isolated unanaesthetized cerebral cortex. J. Physiol 125, 427-446.
COLE K. S. ( 1955). Automatic computation of nerve-excitation. National Bureau of Standards Report No. 4238, 1-39.
ECCLES J. C. ( 1953). The Neurophysiological at Basis of Mind. Oxford. p. 132.
HODGKIN A. L. ( 1948). The local electric changes associated with repetitive action in a non-modullated axon. J. Physiol. 107, 163-181.
HODGKIN A. L. & HUXLEY A. F. ( 1952). A quantitative description of membrane current and its application to conduction and excitation in nerve. J. Physiol. 177, 500-544.
MASON S. J. ( 1953). Feedback Theory--some properties of signal flow graphs. Proc. I.R.E. 41, 1144.
MCINTYRE A. K. ( 1956). Multiple firing at central synapses. Nature, Lond. 178, 302-304.
TAYLOR W. K. ( 1955). Electrical simulation of some nervous system functional activities. Information Theory, Ed. Cherry C. Butterworth. 314-328.
TAYLOR W. K. ( 1959). Pattern recognition by means of automatic analogue apparatus. Proc. Inst. Electrical Engs.106B., No. 26. 198-209.
UTTLEY A. M. ( 1954). The classification of signals in the nervous system. E.E.G. Clin. Neurophysiol. 6, 479-494.

EXPLANATION OF PLATES
Plate 1. For explanation, see text.
Plate 2. Voltage waveforms at points in the neuron and synapse analogues.
Plate 3. Responses of the circuit shown in Fig. 5.

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Models and Analogues in Biology
Table of contents

Table of contents

  • Title Page iii
  • Contents v
  • Preface vii
  • Quantum Physics and Biology† 1
  • Models in Genetics 6
  • Kinetic Models of Development And Heredity 13
  • Tissues in Culture and in the Body 28
  • References 40
  • Models of Muscle 41
  • References 66
  • Mechanical Models in Zoology 69
  • Conclusions 82
  • Physical Models in Biology 83
  • Estimation of Values Of Parameters of a Model to Conform With Observations 102
  • Summary 120
  • Applications of Theoretical Models to the Study of Flight- Behaviour in Locusts and Birds 122
  • References 138
  • Electrical Analogues in Biology 140
  • Computers and the Nervous System 152
  • References 168
  • Models in Cybernetics 169
  • References 190
  • Modelling of Large-Scale Nervous Activity 192
  • Conclusions 197
  • Energy Models of Motivation 199
  • Summary 212
  • The Use of Models in the Teaching Of Embryology 214
  • School Biology as An Educational Model 230
  • Conclusion 241
  • The Problem of Communication In Biological Teaching 243
  • Acknowledge Ments 248
  • A Review of the Symposium: Models and Analogues in Biology 250
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