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

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Abstract

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.

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References

  • Billings SA, Fakhouri SY (1978) Theory of separable processes with applications to the identification of nonlinear systems. Proc IEE 125:1051–1058

    Google Scholar 

  • Billings SA, Fakhouri SY (1982) Identification of systems containing linear dynamic and static nonlinear elements. Automatica 18:15–26

    Google Scholar 

  • Citron MC, Emerson RC (1983) White-noise analysis of cortical directional selectivity in cat. Brain Res 279:271–277

    Google Scholar 

  • Citron MC, Emerson RC, Ide LS (1981) Spatial and temporal receptive-field analysis of the cat's geniculocortical pathway. Vision Res 21:385–396

    Google Scholar 

  • Cleland BG, Dubin MW, Levick WR (1971) Sustained and transient neurons in the cat's retina and lateral geniculate nucleus. J Physiol 217:473–496

    Google Scholar 

  • Cleland BG, Levick WR, Sanderson KJ (1973) Properties of sustained and transient ganglion cells in the cat retina. J Physiol 228:649–680

    Google Scholar 

  • Daw NW, Pearlman AL (1969) Cat color vision: one cone process or several? J Physiol 201:745–764

    Google Scholar 

  • Dean AF, Tolhurst DJ, Walker NS (1982) Non-linear temporal summation by simple cells in cat striate cortex demonstrated by failure of superposition. Exp Brain Res 45:456–458

    Google Scholar 

  • DeValois KK, Tootell RBH (1983) Spatial-frequency-specific inhibition in cat striate cortex cells. J Physiol 336:359–376

    Google Scholar 

  • Emerson RC, Gerstein GL (1977) Simple striate neurons in the cat. I. Comparison of responses to moving and stationary stimuli. J Neurophysiol 40:119–135

    Google Scholar 

  • Emerson RC, Citron MC, Felleman DJ, Kaas JH (1985) A proposed mechanism and site for cortical directional selectivity. In: Models of the visual cortex. Wiley, Sussex, pp 420–431

    Google Scholar 

  • Emerson RC, Citron MC, Vaughn WJ, Klein SA (1987) Nonlinear directionally selective subunits in complex cells of cat striate cortex. J Neurophysiol 58:33–65

    Google Scholar 

  • Emerson RC, Korenberg MJ, Citron MC (1989) Identification of intensive nonlinearities in cascade models of visual cortex and its relation to cell classification. In: Marmarelis VZ (ed) Advanced methods of physiological system modeling, vol 2. Plenum Press, New York, pp 97–111

    Google Scholar 

  • Gielen CCAM, van Gisbergen JAM, Vendrik AJH (1981) Characterization of spatial and temporal properties of monkey LGN Y-cells. Biol Cybern 40:157–170

    Google Scholar 

  • Hammond P, James CR (1971) The Purkinje shift in cat: extent of the mesopic range. J Physiol 216:99–109

    Google Scholar 

  • Henry GH, Goodwin AW, Bishop PO (1978) Spatial summation of responses in receptive fields of single cells in cat striate cortex. Exp Brain Res 32:245–266

    Google Scholar 

  • Hoffmann KP, Stone J (1971) Conduction velocity of afferents to cat visual cortex: a correlation with cortical receptive field properties. Brain Res 32:640–646

    Google Scholar 

  • Hubel DH, Wiesel TN (1959) Receptive fields of simple neurons in the cat's striate cortex. J Physiol 148:574–591

    Google Scholar 

  • Hubel DH, Wiesel TN (1962) Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. J Physiol 160:106–154

    Google Scholar 

  • Hunter IW, Korenberg MJ (1986) The identification of nonlinear biological systems: Wiener and Hammerstein cascade models. Biol Cybern 55:135–144

    Google Scholar 

  • Ikeda H, Wright MJ (1975) Spatial and temporal properties of ‘sustained’ and ‘transient’ neurons in area 17 of the cat's visual cortex. Exp Brain Res 22:363–383

    Google Scholar 

  • Klein S (1980) Probing nonlinear systems with dynamic noise. J Opt Soc Am 70:(abstr)1584

    Google Scholar 

  • Korenberg MJ (1973a) Identification of biological cascades of linear and static nonlinear systems. Proc 16-th Midwest Symp. Circuit Theory, XVIII.2, 1–91

    Google Scholar 

  • Korenberg MJ (1973b) Cross-correlation analysis of neural cascades. Proc Ann Rocky Mountain Bioeng Symp 1:47–52

    Google Scholar 

  • Korenberg MJ, Hunter IW (1986) The identification of nonlinear biological systems: LNL cascade models. Biol Cybern 55:125–134

    Google Scholar 

  • Kulikowski JJ, Bishop PO (1981) Linear analysis of the responses of simple cells in the cat visual cortex. Exp Brain Res 44:386–400

    Google Scholar 

  • Lee YW, Schetzen M (1965) Measurement of the Wiener kernels of a nonlinear system by cross-correlation. Int J Control 2:237–254

    Google Scholar 

  • Lennie P (1980) Parallel visual pathways. Vision Res 20:561–594

    Google Scholar 

  • Levick WR (1972) Another tungsten microelectrode. Med Biol Eng 10:510–515

    Google Scholar 

  • Levine MW, Abramov I (1975) An analysis of spatial summation in the receptive fields of goldfish retinal ganglion cells. Vision Res 15:777–789

    Google Scholar 

  • Madden BC, Mancini M (1980) Separation of temporal and spatial linearity in cat visual cortex. OSA Topical Meeting on Recent Advances in Vision

  • Mancini M (1983) Temporal properties of single cells in cat visual cortex. Ph. D. thesis, University of Rochester

  • Mancini M, Madden BC, Emerson RC (1980) Linear and nonlinear characteristics of temporal responses in cat visual cortex. Invest Ophthalmol Vis Sci [Suppl] 224

  • Mancini M, Madden BC, Emerson RC (1982) Temporal nonlinearities in simple cell responses. Invest Opthalmol Vis Sci [Suppl] 22:118

    Google Scholar 

  • Marmarelis PZ, Marmarelis VS (1978) Analysis of physiological systems, Plenum Press, New York

    Google Scholar 

  • Marmarelis PZ, Naka KI (1972) White-noise analysis of a neuron chain: an application of the Wiener theory. Science 175:1276–1278

    Google Scholar 

  • Marmarelis PZ, Citron MC, Vivo CP (1986) Minimum-order Wiener modelling of spike-output systems. Biol Cybern 54:115–123

    Google Scholar 

  • Movshon JA, Thompson ID, Tolhurst DJ (1978) Spatial summation in the receptive fields of simple cells in the cat's striate cortex. J Physiol 283:53–77

    Google Scholar 

  • Pettigrew J (1974) The effect of visual experience on the development of stimulus specificity by kitten cortical neurons. J Physiol 237:49–74

    Google Scholar 

  • Pollen DA, Ronner SF (1982) Spatial computation performed by simple and complex cells in the visual cortex of the cat. Vision Res 22:101–118

    Google Scholar 

  • Schetzen M (1980) The Volterra and Wiener theories of nonlinear systems. Wiley, New York

    Google Scholar 

  • Schiller PH, Finlay BL, Volman SF (1976) Quantitative studies of single-cell properties in monkey striate cortex. I. Spatiotemporal organization of receptive fields. J Neurophysiol 39:1288–1319

    Google Scholar 

  • Shapley RM, Victor JD (1981) How the contrast gain control modifies the frequency responses of cat retinal ganglion cells. J Physiol 318:161–179

    Google Scholar 

  • Sherman SM, Watkins DW, Wilson JR (1976) Further differences in receptive field properties of simple and complex cells in cat striate cortex. Vision Res 16:919–927

    Google Scholar 

  • Simpson HR (1966) Statistical properties of a class of pseudorandom sequences. Proc IEE 113:2075–2080

    Google Scholar 

  • Spekreijse H (1969) Rectification in the goldfish retina: analysis by sinusoidal and auxiliary stimulation. Vision Res 9:1461–1472

    Google Scholar 

  • Stevens JK, Gerstein GL (1976) Spatiotemporal organization of cat lateral geniculate receptive fields. J Neurophysiol 39:213–238

    Google Scholar 

  • Stone J, Dreher B (1973) Projection of X- and Y-cells of the cat's lateral geniculate nucleus to areas 17 and 18 of visual cortex. J Neurophysiol 36:551–567

    Google Scholar 

  • Swerup C (1978) On the choice of noise for the analysis of the peripheral auditory system. Biol Cybern 29:97–104

    Google Scholar 

  • Victor JD, Shapley RM (1980) A method of nonlinear analysis in the frequency domain. Biophys J 29:459–484

    Google Scholar 

Download references

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This work comprises a portion of a PhD thesis submitted by the first author. This study was supported in part by NIH Grant EY04630 and EY06679 to R.C.E., and EY01319 (Core Grant) to the Center for Visual Science

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Mancini, M., Madden, B.C. & Emerson, R.C. White noise analysis of temporal properties in simple receptive fields of cat cortex. Biol. Cybern. 63, 209–219 (1990). https://doi.org/10.1007/BF00195860

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  • DOI: https://doi.org/10.1007/BF00195860

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