Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Computational Modeling of Orientation Tuning Dynamics in Monkey Primary Visual Cortex

  • Published:
Journal of Computational Neuroscience Aims and scope Submit manuscript

Abstract

In the primate visual pathway, orientation tuning of neurons is first observed in the primary visual cortex. The LGN cells that comprise the thalamic input to V1 are not orientation tuned, but some V1 neurons are quite selective. Two main classes of theoretical models have been offered to explain orientation selectivity: feedforward models, in which inputs from spatially aligned LGN cells are summed together by one cortical neuron; and feedback models, in which an initial weak orientation bias due to convergent LGN input is sharpened and amplified by intracortical feedback. Recent data on the dynamics of orientation tuning, obtained by a cross-correlation technique, may help to distinguish between these classes of models. To test this possibility, we simulated the measurement of orientation tuning dynamics on various receptive field models, including a simple Hubel-Wiesel type feedforward model: a linear spatiotemporal filter followed by an integrate-and-fire spike generator. The computational study reveals that simple feedforward models may account for some aspects of the experimental data but fail to explain many salient features of orientation tuning dynamics in V1 cells. A simple feedback model of interacting cells is also considered. This model is successful in explaining the appearance of Mexican-hat orientation profiles, but other features of the data continue to be unexplained.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Albrecht DG, Geisler WS (1991) Motion selectivity and the contrastresponse function of simple cells in the visual cortex. Vis. Neurosci. 7:531–546.

    PubMed  Google Scholar 

  • Andrews DP (1965) Perception of contours in the central fovea. Nature 205:1218–1220.

    Google Scholar 

  • Andrews DP (1967) Perception of contour orientation in the central fovea. Part I. Short lines. Vis. Res. 7:975–997.

    PubMed  Google Scholar 

  • Ben-Yishai R, Bar-Or RL, Sompolinksy H (1995) Theory of orientation tuning in the visual cortex. Proc. Natl. Acad. of Sci. USA 92:3844–3848.

    Google Scholar 

  • Carandini M, Ringach DL (1997) Predictions of a recurrent model of orientation selectivity. Vis. Res. 37:3061–3071.

    PubMed  Google Scholar 

  • Citron MC, Emerson RC (1983) White noise analysis of cortical directional selectivity in cat. Brain Res. 279:271–7.

    PubMed  Google Scholar 

  • Connors BW, Gutnick MJ, Prince DA (1982) Electrophysiological properties of neocortical neurons in vitro. J. Neurophysiol. 48:1302–1320.

    PubMed  Google Scholar 

  • Das A (1996) Orientation in visual cortex: A simple mechanism emerges. Neuron 16:477–480.

    PubMed  Google Scholar 

  • Daugman JG (1985) Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. J. Opt. Soc. Am. A 2(7):1160–9.

    PubMed  Google Scholar 

  • DeAngelis GC, Ohzawa I, Freeman RD (1993a) Spatiotemporal organization of simple-cell receptive fields in the cat's striate cortex. ii. Linearity of temporal and spatial summation. J. Neurophysiol. 69:1118–35.

    PubMed  Google Scholar 

  • DeAngelis GC, Ohzawa I, Freeman RD (1993b) Spatiotemporal organization of simple-cell receptive fields in the cat's striate cortex. i. General characteristics and postnatal development. J. Neurophysiol. 69:1091–117.

    PubMed  Google Scholar 

  • de Boer E, Kuyper P (1968) Triggered correlation. IEEE Trans. on Biomed. Eng. 15:169–179.

    Google Scholar 

  • Douglas RJ, Koch C, Mahowald M, Martin KA, Suarez HH (1995) Recurrent excitation in neocortical circuits. Science 269:981–985.

    PubMed  Google Scholar 

  • Ferster D (1986) Orientation selectivity of synaptic potentials in neurons of cat primary visual cortex. J. Neurosci. 6:1284–1301.

    PubMed  Google Scholar 

  • Ferster D, Chung S, Wheat H (1996) Orientation selectivity of thalamic input to simple cells of cat visual cortex. Nature 380:249–252.

    PubMed  Google Scholar 

  • Gielen CC, van Gisbergen JA, Vendrik AJ (1981) Characterization of spatial and temporal properties of monkey LGN Y-cells. Biol. Cyb. 40(3):157–170.

    Google Scholar 

  • Gut A (1988) Stopped random walks: Limit theorems and applications. Springer Verlag, New York.

    Google Scholar 

  • Hawken MJ, Parker AJ, Lund JS (1988) Laminar organization and contrast sensitivity of direction-selective cells in the striate cortex of the old world monkey. J. Neurosci. 8:3541–3548.

    PubMed  Google Scholar 

  • Heeger DJ (1992a) Half-squaring in responses of cat striate cells. Visual Neurosci. 9(5):427–443.

    Google Scholar 

  • Heeger DJ (1992b) Normalization of cell responses in cat striate cortex. Visual Neurosci. 9(2):181–197.

    Google Scholar 

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

    PubMed  Google Scholar 

  • Hubel DH, Wiesel TN (1968) Receptive fields and functional architecture of monkey striate cortex. J. Physiol. Lond. 195:215–245.

    PubMed  Google Scholar 

  • Jones JP, Palmer LA (1987) The two-dimensional spatial structure of simple receptive fields in the cat striate cortex. J. Neurophysiol. 58:1187–1258.

    PubMed  Google Scholar 

  • M MC, Mechler F, Leonard CS, Movshon JA (1996) Spike train encoding by regular-spiking cells of the visual cortex. J. Neurophysiol. 76(5):3425–3441.

    PubMed  Google Scholar 

  • Maex R, Orban GA (1991) Subtraction inhibition combined with a spiking threshold accounts for cortical direction selectivity. Proc. Natl. Acad. Sci. USA 88(9):3549–53.

    PubMed  Google Scholar 

  • Maex R, Orban GA (1996) Model circuit of spiking neurons generating directional selectivity in simple cells. J. Neurophysiol. 75:1515–1545.

    PubMed  Google Scholar 

  • Marcelja S (1980) Mathematical description of the responses of simple cortical cells. J. Opt. Soc. Am. 70(11):1297–1300.

    PubMed  Google Scholar 

  • Marmarelis PN, Marmarelis VZ (1978) Analysis of Physiological Systems: The White Noise Approach. New York: Plenum Press.

    Google Scholar 

  • McCormick DA, Connors BW, Lighthall JW (1985) Comparative electrophysiology of pyramidal and sparsely spiny stellate neurons of the neocortex. J. Neurophysiol. 54:782–806.

    PubMed  Google Scholar 

  • McLean J, Palmer LA (1989) Contribution of linear spatiotemporal receptive field structure to velocity selectivity of simple cells in area 17 of cat. Vis. Res. 29:675–9.

    PubMed  Google Scholar 

  • McLean J, Raab S, Palmer LA (1994) Contribution of linear mechanisms to the specification of local motion by simple cells in areas 17 and 18 of the cat. Vis. Neurosci. 11:271–94.

    PubMed  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. Lond. 283:53–77.

    PubMed  Google Scholar 

  • Palmer LA, Davis TL (1981) Receptive-field structure in cat striate cortex. J. Neurophysiol. 46(2):260–76.

    PubMed  Google Scholar 

  • Reid RC, Alonso JM (1996) The processing and encoding of information in the visual cortex. Current Opinion in Neurobiol. 6:475–480.

    Google Scholar 

  • Reid RC, Soodak RE, Shapley RM (1991) Directional selectivity and spatiotemporal structure of receptive fields of simple cells in cat striate cortex. J. Neurophysiol. 66:505–529.

    PubMed  Google Scholar 

  • Reid RC, Victor JD, Shapley RM (1997) The use of m-sequences in the analysis of visual neurons: Linear receptive field properties. Vis. Neurosci. 14:1015–1027.

    PubMed  Google Scholar 

  • Ringach DL, Hawken MJ, Shapley R (1997a) Dynamics of excitatory and inhibitory mechanisms shaping the orientation tuning of neurons in: V1. In: Society for Neuroscience Abstract. 23:1544, pt. 2.

    Google Scholar 

  • Ringach DL, Hawken MJ, Shapley R (1997b) Dynamics of orientation tuning in macaque primary visual cortex. Nature 387:281–284.

    PubMed  Google Scholar 

  • Ringach DL, Hawken MJ, Shapley R (1998) Spatial-phase dependent and independent response components of oriented neurons in macaque V1. In Invest. Ophthal. and Vis. Sci. (Suppl.), 39:S683.

    Google Scholar 

  • Ringach DL, Sapiro G, Shapley R (1997c) A subspace reverse correlation technique for the study of visual neurons. Vis. Res. 37:2455–2464.

    PubMed  Google Scholar 

  • Somers DC, Nelson SB, Sur M (1995) An emergent model of orientation selectivity in cat visual cortical simple cells. J. Neurosci. 269:5448–5465.

    Google Scholar 

  • Sompolinsky H, Shapley R (1997) New perspectives on the mechanisms for orientation selectivity. Current Opinion in Neurobiol. 7:514–522.

    Google Scholar 

  • Tolhurst DJ, Dean AF (1991) Evaluation of a linear model of directional selectivity in simple cells of the cat's striate cortex. Vis. Neurosci. 6(5):421–428.

    PubMed  Google Scholar 

  • Victor JD (1992) Nonlinear systems analysis in vision: overview of kernel methods. In: Pinter R, Nabet B, eds. Nonlinear vision: Determination of Neural Receptive Fields, Function and Networks. CRC Press, Cleveland, OH, vol. 1, pp. 1–37.

    Google Scholar 

  • Wörgötter F, Niebur E, Koch C (1991) Quantification and comparison of cell properties in cat's striate cortex determined by different types of stimuli. J. Neurophysiol. 66:1163–1176.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mathematics, University of Pennsylvania, 209 South 33rd Street, Philadelphia, PA, 19104-6395

    M.C. Pugh

  2. Departments of Neurobiology and Psychology, University of California at Los Angeles, Los Angeles, CA, 90095

    D.L. Ringach

  3. Center for Neural Science, New York University, New York, NY, 10003

    R. Shapley

  4. Courant Institute for Mathematical Sciences, New York University, New York, NY, 10012

    M.J. Shelley

Authors
  1. M.C. Pugh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. D.L. Ringach
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. R. Shapley
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. M.J. Shelley
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Pugh, M., Ringach, D., Shapley, R. et al. Computational Modeling of Orientation Tuning Dynamics in Monkey Primary Visual Cortex. J Comput Neurosci 8, 143–159 (2000). https://doi.org/10.1023/A:1008921231855

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1008921231855

Search

Navigation