Linear Models of Impulse Inputs and Linear Basis Functions for Measuring Impulse Responses

  • Walter J. Freeman
Part of the Perspectives in Neural Computing book series (PERSPECT.NEURAL)


Next I undertook systematic exploration of the behavioral correlates of this well defined generator of background and odor-induced EEG and electrically evoked potentials in waking cats by using arrays of permanently placed bipolar electrodes (Freeman 1960a,b), first by presenting different odorants to search for changes in amplitude and frequency distributions of the EEG, then by using different unconditioned stimuli to elicit reactions relating to hunger, thirst, rage and attack, fear and flight, sexual arousal, and stages of drowsiness and sleep. The only significant variations were in the amplitude of the EEG, which increased in the low-frequency range with sleep, and in the higher frequency gamma range (Bressler and Freeman 1980) with the degree of arousal and motivation. There were no patterns that were specific to either the odorant stimuli, or the responses to them, or the type of motivation. An exception was the suppression of bursts in the EEG with sneezing, yawning, sniffing, or other changes peculiar to respiratory patterns. Even in sleep there was only a modest increase in slow wave delta activity. These negative results were not very exciting.


Basis Function Stimulus Intensity Matched Filter Polar Plot Lateral Olfactory Tract 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bishop, G. H. 1958. The dendrite: receptive pole of the neuron. Electroencephalog. Clin. Neurophysiol. Suppl.10: 12–21.Google Scholar
  2. 2.
    Bode, H. W., and C. E. Shannon. 1950. A simplified derivation of linear least square smoothing and prediction theory. Proc. IRE 38: 417–425.Google Scholar
  3. 3.
    Box, G. E. P., and K. B. Wilson. 1951. On the experimental attainment of optimum conditions. J. Roy. Statist. Soc. B13: 1–45Google Scholar
  4. 4.
    Brown, R. G., and J. W. Nilsson. 1962. Introduction to Linear Analysis. Wiley, New York.Google Scholar
  5. 5.
    Freeman, W. J. 1959. An ergometer for measuring work from cats as an index for drive. J. Appl. Physiol. 14: 1071–1072.Google Scholar
  6. 6.
    Freeman, W. J. 1962. Alterations in prepyriform evoked potential in relation to stimulus intensity. Exptl. Neurol. 6: 70–84.Google Scholar
  7. 7.
    Freeman, W. J. 1963. The electrical activity of a primary sensory cortex: the analysis of EEG waves. Intern. Rev. Neurobiol. 5: 53–119.Google Scholar
  8. 8.
    Gauss, C. F. 1855.Méthode des moindres carrés; mémoires sur la combinaison des observations. Bertrand, Paris.Google Scholar
  9. 9.
    Hartley, H. O. 1961. The modified Gauss-Newton method for fitting of nonlinear regression functions by least squares. Technometrics 3: 269–280.Google Scholar
  10. 10.
    Huggins, W. H. 1960. Representation and analysis of signals. Part VII. Signal detection in a noisy world. Johns Hopkins University Report No. AFCRC-TN-60-360.Google Scholar
  11. 11.
    Lerner, R. M. 1959. The representation of signals. IRE, Trans. Circuit Theory 6: 197–216.Google Scholar
  12. 12.
    Smith, O. J. M. 1958. Feedback Control Systems. McGraw-Hill, New York.Google Scholar
  13. 13.
    Wiener, N. 1949. Extrapolation, Interpolation, and Smoothing of Stationary Time Series. Wiley, New York.Google Scholar
  14. 14.
    Wolfenden, H. H. 1942. The Fundamental Principles of Mathematical Statistics. Macmillan, Toronto.Google Scholar
  15. 15.
    Young, T. Y., and W. H. Huggins. 1961. Representation and analysis of signals. Part VIII. Representation of electrocardiogram by orthogonalized exponentials. Johns Hopkins Univ. Report No. AFCRL-187.Google Scholar

Copyright information

© Springer-Verlag London 2000

Authors and Affiliations

  • Walter J. Freeman
    • 1
  1. 1.Department of Molecular and Cell BiologyUniversity of CaliforniaBerkeleyUSA

Personalised recommendations