Statistical and dimensional analysis of the neural representation of the acoustic biotope of the frog

The field of investigation is the neural representation of acoustic stimuli occurring in the natural environment of the frog. The point of departure is the description of a stimulus ensemble consisting of natural sounds: the acoustic biotope. A relation of statistical and dimensional structure of the acoustic biotope is indicated. The animal used in the neurophysiological experiments is the grass frog,Rana temporaria L.; microelectrode recordings are made in the auditory midbrain. A method is described to determine the existence of a relation between acoustic stimulus and neural events. The form of this relation has been investigated by first- and second-order stimulus-event correlation. While the first one does not give significant results, the second one leads to the spectrotemporal receptive field of the neuron for natural stimuli. Questions are formulated to estimate the value of this receptive field as a functional descriptor of the neuron. Finally, an outline is sketched for a synthetic construction of the bioacoustic space from neuroacoustic subspaces.

[1]  J. G. Pedersen,et al.  On the existence of stimulus-event relations for sensory neurons: A statistical method , 1980, Biological Cybernetics.

[2]  A. Vendrik,et al.  Spectral and temporal characteristics of activation and suppression of units in the cochlear nuclei of the anaesthetized cat , 1975, Experimental Brain Research.

[3]  T. Poggio,et al.  The Volterra Representation and the Wiener Expansion: Validity and Pitfalls , 1977 .

[4]  E. De Boer.  Polynomial correlation , 1979, Proceedings of the IEEE.

[5]  I. Whitfield.  Discharge Patterns of Single Fibers in the Cat's Auditory Nerve , 1966 .

[6]  Ad Aertsen,et al.  Spectro-temporal characterization of auditory neurons , 1981 .

[7]  A. Aertsen,et al.  Spectro-temporal receptive fields of auditory neurons in the grassfrog , 1980, Biological Cybernetics.

[8]  A. Aertsen,et al.  Neural representation of the acoustic biotope: On the existence of stimulus-event relations for sensory neurons , 1979, Biological Cybernetics.

[9]  P. I. M. Johannesma.  NEURAL REPRESENTATION OF SENSORY STIMULI AND SENSORY INTERPRETATION OF NEURAL ACTIVITY , 1981 .

[10]  E. de Boer,et al.  On cochlear encoding: Potentialities and limitations of the reverse‐correlation technique , 1978 .

[11]  Y. W. Lee,et al.  Measurement of the Wiener Kernels of a Non-linear System by Cross-correlation† , 1965 .

[12]  G. D. McCann,et al.  Development and application of white-noise modeling techniques for studies of insect visual nervous system , 1973, Kybernetik.

[13]  E. de Boer,et al.  On cochlear encoding: potentialities and limitations of the reverse-correlation technique. , 1978, The Journal of the Acoustical Society of America.

[14]  N. Wiener,et al.  Nonlinear Problems in Random Theory , 1964 .

[15]  F G Worden,et al.  Auditory processing of biologically significant sounds. , 1972, Neurosciences Research Program bulletin.

[16]  A. Aertsen,et al.  A comparison of the Spectro-Temporal sensitivity of auditory neurons to tonal and natural stimuli , 1981, Biological Cybernetics.

[17]  R. Shapley,et al.  A method of nonlinear analysis in the frequency domain. , 1980, Biophysical journal.

[18]  C.C.A.M. Gielen,et al.  Spatio-temporal and chromatic properties of visual neurones in the rhesus monkey geniculate nucleus , 1980 .

[19]  G L Gerstein,et al.  Interactions between neurons in auditory cortex of the cat. , 1974, Journal of neurophysiology.

[20]  A. Aertsen,et al.  The phonochrome: A coherent spectro-temporal representation of sound , 1981, Hearing Research.

[21]  J. Barrett.  The Use of Functionals in the Analysis of Non-linear Physical Systems† , 1963 .

[22]  P Kuyper,et al.  Triggered correlation. , 1968, IEEE transactions on bio-medical engineering.

[23]  A. Vendrik,et al.  Neurons in the cochlear nucleus investigated with tone and noise stimuli , 1975, Experimental Brain Research.

[24]  Michael A. Arbib,et al.  The metaphorical brain : an introduction to cybernetics as artificial intelligence and brain theory , 1972 .

[25]  M. Sanders.  Handbook of Sensory Physiology , 1975 .

[26]  P. I. M. Johannesma,et al.  Spectro-temporal characteristics of single units in the auditory midbrain of the lightly anaesthetised grass frog (Rana temporaria L.) Investigated with noise stimuli , 1981, Hearing Research.

[27]  Alexander Joseph.  Book reviewDischarge patterns of single fibers in the cat's auditory nerve: Nelson Yuan-Sheng Kiang, with the assistance of Takeshi Watanabe, Eleanor C. Thomas and Louise F. Clark: Research Monograph no. 35. Cambridge, Mass., The M.I.T. Press, 1965 , 1967 .

[28]  W. H. F. Barnes.  The Nature of Explanation , 1944, Nature.

[29]  P. I. M. Johannesma.  Functional Identification of Auditory Neurons Based on Stimulus-Event Correlation , 1980 .

[30]  J. J. Gelder,et al.  CALLING AND ASSOCIATED BEHAVIOUR OF THE COMMON FROG, RANA TEMPORARIA, DURING BREEDING ACTIVITY , 1978 .

[31]  D. J. Hermes,et al.  Spectro-temporal characterization of auditory neurons: Redundant or necessary? , 1981, Hearing Research.

[32]  G. Palm,et al.  On representation and approximation of nonlinear systems , 1979, Biological Cybernetics.

[33]  A. Aertsen,et al.  The Spectro-Temporal Receptive Field , 1981, Biological Cybernetics.

[34]  A. Møller,et al.  Statistical evaluation of the dynamic properties of cochlear nucleus units using stimuli modulated with pseudorandom noise. , 1973, Brain research.

[35]  W. McCulloch,et al.  Embodiments of Mind , 1966 .