White noise analysis of temporal properties in simple receptive fields of cat cortex

We studied the linear and nonlinear temporal response properties of simple cells in cat visual cortex by presenting at single positions in the receptive field an optimally oriented bar stimulus whose luminance was modulated in a random, binary fashion. By crosscorrelating a cell's response with the input it was possible to obtain the zeroth-, first-, and second-order Wiener kernels at each RF location. Simple cells showed pronounced nonlinear temporal properties as revealed by the presence of prominent second-order kernels. A more conventional type of response histogram was also calculated by time-locking a histogram on the occurrence of the desired stimulus in the random sequence. A comparison of the time course of this time-locked response with that of the kernel prediction indicated that nonlinear temporal effects of order higher than two are unimportant. The temporal properties of simple cells were well represented by a cascade model composed of a linear filter followed by a static nonlinearity. These modelling results suggested that for simple cells, the nonlinearity occurs late and probably is a soft threshold associated with the spike generating mechanism of the cortical cell itself. This result is surprising in view of the known threshold nonlinearities in preceding lateral geniculate and retinal neurons. It suggests that geniculocortical connectivity cancels the earlier nonlinearities to create a highly linear representation inside cortical simple cells.

[1]  W. Levick,et al.  Sustained and transient neurones in the cat's retina and lateral geniculate nucleus , 1971, The Journal of physiology.

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

[3]  Emerson Rc,et al.  Simple striate neurons in the cat. I. Comparison of responses to moving and stationary stimuli. , 1977 .

[4]  Klein,et al.  Nonlinear directionally selective subunits in complex cells of cat striate cortex. , 1987, Journal of neurophysiology.

[5]  M. Wright,et al.  Spatial and temporal properties of ‘sustained’ and ‘transient’ neurones in area 17 of the cat's visual cortex , 1975, Experimental Brain Research.

[6]  M. C. Citron,et al.  White noise analysis of cortical directional selectivity in cat , 1983, Brain Research.

[7]  M. Schetzen.  The Volterra and Wiener Theories of Nonlinear Systems , 1980 .

[8]  K. Naka,et al.  White-Noise Analysis of a Neuron Chain: An Application of the Wiener Theory , 1972, Science.

[9]  P. O. Bishop,et al.  Spatial summation of responses in receptive fields of single cells in cat striate cortex , 1978, Experimental Brain Research.

[10]  D. Pollen,et al.  Spatial computation performed by simple and complex cells in the visual cortex of the cat , 1982, Vision Research.

[11]  M. J. Korenberg,et al.  The identification of nonlinear biological systems: LNL cascade models , 1986, Biological Cybernetics.

[12]  J. Stone,et al.  Projection of X- and Y-cells of the cat's lateral geniculate nucleus to areas 17 and 18 of visual cortex. , 1973, Journal of neurophysiology.

[13]  P. Hammond,et al.  The Purkinje shift in cat: extent of the mesopic range , 1971, The Journal of physiology.

[14]  W. Levick,et al.  Properties of sustained and transient ganglion cells in the cat retina , 1973, The Journal of physiology.

[15]  J. Pettigrew,et al.  The effect of visual experience on the development of stimulus specificity by kitten cortical neurones , 1974, The Journal of physiology.

[16]  S. Billings,et al.  Theory of separable processes with applications to the identification of nonlinear systems , 1978 .

[17]  I. Abramov,et al.  An analysis of spatial summation in the receptive fields of goldfish retinal ganglion cells , 1975, Vision Research.

[18]  P. Lennie.  Parallel visual pathways: A review , 1980, Vision Research.

[19]  D. Hubel,et al.  Receptive fields, binocular interaction and functional architecture in the cat's visual cortex , 1962, The Journal of physiology.

[20]  QUANTITATIVE STUDIES , 1967 .

[21]  Stephen A. Billings,et al.  Identification of systems containing linear dynamic and static nonlinear elements , 1982, Autom..

[22]  J. Movshon,et al.  Spatial summation in the receptive fields of simple cells in the cat's striate cortex. , 1978, The Journal of physiology.

[23]  M. J. Korenberg,et al.  The identification of nonlinear biological systems: Wiener and Hammerstein cascade models , 1986, Biological Cybernetics.

[24]  R C Emerson,et al.  Spatial and temporal receptive-field analysis of the cat's geniculocortical pathway. , 1981, Vision research.

[25]  Michael J. Korenberg,et al.  Identification of Intensive Nonlinearities in Cascade Models of Visual Cortex and its Relation to Cell Classification , 1989 .

[26]  J. Stone,et al.  Conduction velocity of afferents to cat visual cortex: a correlation with cortical receptive field properties. , 1971, Brain research.

[27]  Vasilis Z. Marmarelis,et al.  Analysis of Physiological Systems , 1978, Computers in Biology and Medicine.

[28]  D. Hubel,et al.  Receptive fields of single neurones in the cat's striate cortex , 1959, The Journal of physiology.

[29]  C. Swerup.  On the choice of noise for the analysis of the peripheral auditory system , 2004, Biological Cybernetics.

[30]  P. O. Bishop,et al.  Linear analysis of the responses of simple cells in the cat visual cortex , 2004, Experimental Brain Research.

[31]  G L Gerstein,et al.  Spatiotemporal organization of cat lateral geniculate receptive fields. , 1976, Journal of neurophysiology.

[32]  H Spekreijse,et al.  Rectification in the goldfish retina: analysis by sinusoidal and auxiliary stimulation. , 1969, Vision research.

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

[34]  W. R. Levick,et al.  Another tungsten microelectrode , 1972, Medical and biological engineering.

[35]  H. R. Simpson.  Statistical properties of a class of pseudorandom sequences , 1966 .

[36]  M. C. Citron,et al.  Spatial and temporal receptive-field analysis of the cats geniculocortical pathway , 1981, Vision Research.

[37]  M. C. Citron,et al.  Minimum-order Wiener modelling of spike-output systems , 2004, Biological Cybernetics.

[38]  P. Schiller,et al.  Quantitative studies of single-cell properties in monkey striate cortex. I. Spatiotemporal organization of receptive fields. , 1976, Journal of neurophysiology.

[39]  C. C. A. M. Gielen,et al.  Characterization of spatial and temporal properties of monkey LGN Y-cells , 1981, Biological Cybernetics.

[40]  D. Tolhurst,et al.  Non-linear temporal summation by simple cells in cat striate cortex demonstrated by failure of superposition , 2005, Experimental Brain Research.

[41]  N. Daw,et al.  Cat colour vision: one cone process or several? , 1969, The Journal of physiology.

[42]  J D Victor,et al.  How the contrast gain control modifies the frequency responses of cat retinal ganglion cells. , 1981, The Journal of physiology.

[43]  D. W. Watkins,et al.  Further differences in receptive field properties of simple and complex cells in cat striate cortex , 1976, Vision Research.

[44]  K. D. De Valois,et al.  Spatial‐frequency‐specific inhibition in cat striate cortex cells. , 1983, The Journal of physiology.