Skip to main content Accessibility help
×
×
Home

The use of m-sequences in the analysis of visual neurons: Linear receptive field properties

  • R. C. Reid (a1) (a2) (a3), J. D. Victor (a1) (a2) and R. M. Shapley (a1) (a3)

Abstract

We have used Sutter's (1987) spatiotemporal m-sequence method to map the receptive fields of neurons in the visual system of the cat. The stimulus consisted of a grid of 16 X 16 square regions, each of which was modulated in time by a pseudorandom binary signal, known as an m-sequence. Several strategies for displaying the m-sequence stimulus are presented. The results of the method are illustrated with two examples. For both geniculate neurons and cortical simple cells, the measurement of first-order response properties with the m-sequence method provided a detailed characterization of classical receptive-field structures. First, we measured a spatiotemporal map of both the center and surround of a Y-cell in the lateral geniculate nucleus (LGN). The time courses of the center responses was biphasic: OFF at short latencies, ON at longer latencies. The surround was also biphasic—ON then OFF—but somewhat slower. Second, we mapped the response properties of an area 17 directional simple cell. The response dynamics of the ON and OFF subregions varied considerably; the time to peak ranged over more than a factor of two. This spatiotemporal inseparability is related to the cell's directional selectivity (Reid et al., 1987, 1991; McLean & Palmer, 1989; McLean et al., 1994). The detail with which the time course of response can be measured at many different positions is one of the strengths of the m-sequence method.

Copyright

References

Hide All
Adelson, E.H. & Bergen, J.R. (1985). Spatiotemporal energy models for the perception of motion. Journal of the Optical Society of America 2, 285299.
Albrecht, D.G. & Geisler, W.S. (1991). Motion selectivity and the contrast-response function of simple cells in the visual cortex. Visual Neuroscience 7, 531546.
Alonso, J.M. & Reid, R.C. (1994). Coupling between neighboring LGN cells: Possible implications for simple receptive fields. Society for Neuroscience Abstracts 20, 1476.
Alonso, J.M., Atick, J.J. & Reid, R.C. (1995). The temporal responses of LGN receptive fields studied with white noise. Investigative Ophthalmology and Visual Science (Suppl.) 36, S. 689.
Baseler, H.A., Sutter, E.E., Klein, S.A. & Carney, T. (1994). The topography of visual evoked response properties across the visual field. Electroencephalography and Clinical Neurophysiology 90, 6581.
Benardete, E.A. & Victor, J.D. (1994). An extension of the m-sequence technique for the analysis of multi-input nonlinear systems. In Nonlinear Vision: Determination of Neural Receptive Fields, Function, and Networks, ed. Pinter, R. & Nabet, B., pp. 87110. Cleveland, Ohio: CRC Press.
Britten, K.H. (1995). Spatial interactions within monkey middle temporal (MT) receptive fields. Society for Neuroscience Abstracts 21, 663.
Bussgang, J.J. (1952). Crosscorrelation functions of amplitude-distorted Gaussian signals. Technical Report 216, MIT Research Laboratory of Electronics.
Citron, M.C., Kroeker, J.P. & McCann, G.D. (1981). Nonlinear interactions in ganglion cell receptive fields. Journal of Neurophysiology 46, 11611176.
Dawis, S., Shapley, R., Kaplan, E. & Tranchina, D. (1984). The receptive field organization of X-cells in the cat: Spatiotemporal coupling and asymmetry. Vision Research 24, 549561.
DeAngelis, G.C., Ohzawa, I., Freeman, R.D. (1993 a). Spatiotemporal organization of simple-cell receptive fields in the cat's striate cortex. I. General characteristics and postnatal development. Journal of Neurophysiology 69, 10911117.
DeAngelis, G.C., Ohzawa, I., Freeman, R.D. (1993 b). Spatiotemporal organization of simple-cell receptive fields in the cat's striate cortex. II. Linearity of temporal and spatial summation. Journal of Neurophysiology 69, 11181135.
DeAngelis, G.C., Ohzawa, I., Freeman, R.D. (1995). Receptive-field dynamics in the central visual pathways. Trends in Neuroscience 618, 451458.
de Boer, E. & Kuyper, P. (1968). Triggered correlation. IEEE Transactions on Biomedical Engineering 15, 169179.
Emerson, R. C., Citron, M.C., Vaughn, W.J. & Klein, S.A. (1987). Nonlinear directionally selective subunits in complex cells of cat striate cortex. Journal of Neurophysiology 58, 3365.
Enroth-Cugell, C. & Robson, J.G. (1966). The contrast sensitivity of retinal ganglion cells of the cat. Journal of Physiology 187, 517552.
Golomb, S.W. (1982). Shift Register Sequences, Laguna Hills, California: Aegean Park Press.
Hochstein, S. & Shapley, R.M. (1976). Quantitative analysis of retinal ganglion cell classifications. Journal of Physiology 262, 237264.
Hubel, D.H. (1957). Tungsten microelectrode for recording from single units. Science 125, 549550.
Jacobson, L.D., Gaska, J.P., Chen, H.-W. & Pollen, D.A. (1993). Structural testing of multi-input linear-nonlinear cascade models for cells in the macaque striate cortex. Journal of Physiology 160, 106154.
Jagadeesh, B., Wheat, H.S. & Ferster, D. (1993). Linearity of summation of synaptic potentials underlying direction selectivity in simple cells of the cat visual cortex. Science 262, 19011904.
Jones, J.P. & Palmer, L.A. (1987). The two-dimensional spatial structure of simple receptive fields in cat striate cortex. Journal of Neurophysiology 58, 11871211.
Kitano, M., Niiyama, K., Kasamatsu, T, Sutter, E.E. & Norcia, A.M. (1994). Retinotopic and nonretinotopic field potentials in cat visual cortex. Visual Neuroscience 11, 953977.
Levick, W.R. & Thibos, L.H. (1980). Orientation bias of cat retinal ganglion cells. Nature 286, 389390.
Marmarelis, P.Z. & Marmarelis, V.Z. (1978). Analysis of Physiological Systems. New York: Plenum Press.
McLean, J. & Palmer, L. (1989). Contributions of linear spatiotemporal receptive field structure to velocity selectivity of simple cells in area 17 of cat. Vision Research 29, 675679.
McLean, J., Raab, S. & Palmer, L.A. (1994). Contribution of linear mechanisms to the specification of local motion by simple cells in areas 17 and 18 of the cat. Visual Neuroscience 11, 271294.
Milkman, N., Schick, G., Rossetto, M., Ratliff, F, Shapley, R. & Victor, J. (1980). A two-dimensional computer-controlled visual stimulator. Behavior Research Methods and Instrumentation 12, 283292.
Movshon, J. A., Thompson, I. D. & Tolhurst, D. J. (1978). Spatial summation in the receptive field of simple cells in the cat's striate cortex. Journal of Physiology 283, 5377.
Naka, K.I., Sakuranaga, M. & Ando, Y.I. (1985). White-noise analysis as a tool in vision physiology. In Progress in Clinical and Biological Research. Vol. 176, Contemporary Sensory Neurobiology, ed. Correia, M.J. & Perachio, A.A., pp. 307322. New York: Alan R. Liss.
Nuttal, A.H. (1957). Invariance of correlation functions under nonlinear transformations. Technical report, MIT Laboratory of Electronics.
Ohzawa, I. & Freeman, R.D. (1986). The binocular organization of simple cells in the cat's visual cortex. Journal of Neurophysiology 56, 221242.
Reid, R.C. & Alonso, J.M. (1995). Specificity of monosynaptic connections from thalamus to visual cortex. Nature 378, 281284.
Reid, R.C. & Shapley, R.M. (1992). The spatial structure of L, M, and S cone inputs to receptive fields in primate lateral geniculate nucleus. Nature 356, 716718.
Reid, R.C., Soodak, R.E. & Shapley, R.M. (1987). Linear mechanisms of directional selectivity in simple cells of cat striate cortex. Proceedings of the National Academy of Sciences of the U.S.A. 84, 87408744.
Reid, R.C., Soodak, R.E. & Shapley, R.M. (1991). Directional selectivity and spatiotemporal structure of receptive fields of simple cells in cat striate cortex. Journal of Neurophysiology 66, 505529.
Sakai, H.M, Naka, K.-I. & Korenberg, M.J. (1990). White-noise analysis in visual neuroscience. Visual Neuroscience 1, 287296.
Shapley, R.M. & Victor, J.D. (1981). How the contrast gain control modifies the frequency responses of cat retinal ganglion cells. Journal of Physiology 318, 161179.
Shapley, R.M. & Victor, J.D. (1978). The effect of contrast on the transfer properties of cat retinal ganglion cells. Journal of Physiology 285, 275298.
Soodak, R.E., Shapley, R.M. & Kaplan, E. (1991). Fine structure of receptive-field centers of X and Y cells of the cat. Visual Neuroscience 6, 621628.
Sutter, E.E. (1987). A practical non-stochastic approach to nonlinear time-domain analysis. In Advanced Methods of Physiological Systems Modeling, Vol. I, ed. Marmarelis, V.Los Angeles, California: University of Southern California.
Sutter, E.E. (1992 a). The fast m-transform: A fast computation of cross-correlations with binary m-sequences. SIAM Journal on Computing 20, 686694.
Sutter, E.E. (1992 b). A deterministic approach to nonlinear systems analysis. In Nonlinear Vision: Determination of Neural Receptive Fields, Function, and Networks, ed. Pinter, R. & Nabet, B., pp. 171220. Cleveland, Ohio: CRC Press.
Sutter, E.E. & Tran, D. (1992). The field topography of ERG components in man—I. The photopic luminance response. Vision Research 32, 433446.
Sutter, E.E. & Vaegan, . (1990). Lateral interaction component and local luminance nonlinearities in the human pattern ERG. Vision Research 30, 659671.
Szulborski, R.G. & Palmer, L.A. (1990). The two-dimensional spatial structure of nonlinear subunits in the receptive fields of complex cells. Vision Research 30, 249254.
Victor, J.D. & Shapley, R.M. (1979). Receptive field mechanisms of cat X and Y retinal ganglion cells. Journal of General Physiology 74, 275298.
Victor, J.D., Shapley, R.M. & Knight, B.W. (1977). Nonlinear analysis of cat retinal ganglion cells in the frequency domain. Proceedings of the National Academy of Sciences of the U.S.A. 74, 30683972.
Victor, J.D. (1987). The dynamics of the cat retinal X cell centre. Journal of Physiology 386, 219246.
Victor, J.D. (1991). Asymptotic approach of generalized orthogonal functional expansions to Wiener kernels. Annals of Biomedical Engineering 19, 383399.
Victor, J.D. (1992). Nonlinear systems analysis in vision: Overview of kernel methods. In Nonlinear Vision: Determination of Neural Receptive Fields, Function, and Networks, ed. Pinter, R. & Nabet, B., pp. 137. Cleveland, Ohio: CRC Press.
Victor, J.D., Purpura, K., Katz, E. & Mao, B. (1994). Population encoding of spatial frequency, orientation, and color in macaque V1. Journal of Neurophysiology 72, 21512166.
Victor, J.D. & Knight, B.W. (1979). Nonlinear analysis with an arbitrary stimulus ensemble. Quarterly of Applied Mathematics 37, 113136.
Vidyasagar, T.R. & Heide, W. (1984). Geniculate orientation biases seen with moving sine-wave gratings: Implications for a model of simple cell afferent connectivity. Experimental Brain Research 57, 196200.
Watson, A.B. & Ahumada, A.J. Jr (1985). Models of human visualmotion sensing. Journal of the Optical Society of America 2, 322342.
Weiss, T. (1966). A model of the peripheral auditory system. Kybernetik 3, 153175.
Wiener, N. (1958). Nonlinear Problems in Random Theory. New York: Wiley.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Visual Neuroscience
  • ISSN: 0952-5238
  • EISSN: 1469-8714
  • URL: /core/journals/visual-neuroscience
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Keywords

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed