Advertisement

Journal of Computational Neuroscience

, Volume 8, Issue 2, pp 143–159 | Cite as

Computational Modeling of Orientation Tuning Dynamics in Monkey Primary Visual Cortex

  • M.C. Pugh
  • D.L. Ringach
  • R. Shapley
  • M.J. Shelley
Article

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.

cortical dynamics orientation tuning monkey primary visual cortex layers 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Albrecht DG, Geisler WS (1991) Motion selectivity and the contrastresponse function of simple cells in the visual cortex. Vis. Neurosci. 7:531–546.PubMedGoogle Scholar
  2. Andrews DP (1965) Perception of contours in the central fovea. Nature 205:1218–1220.Google Scholar
  3. Andrews DP (1967) Perception of contour orientation in the central fovea. Part I. Short lines. Vis. Res. 7:975–997.PubMedGoogle Scholar
  4. 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
  5. Carandini M, Ringach DL (1997) Predictions of a recurrent model of orientation selectivity. Vis. Res. 37:3061–3071.PubMedGoogle Scholar
  6. Citron MC, Emerson RC (1983) White noise analysis of cortical directional selectivity in cat. Brain Res. 279:271–7.PubMedGoogle Scholar
  7. Connors BW, Gutnick MJ, Prince DA (1982) Electrophysiological properties of neocortical neurons in vitro. J. Neurophysiol. 48:1302–1320.PubMedGoogle Scholar
  8. Das A (1996) Orientation in visual cortex: A simple mechanism emerges. Neuron 16:477–480.PubMedGoogle Scholar
  9. 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.PubMedGoogle Scholar
  10. 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.PubMedGoogle Scholar
  11. 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.PubMedGoogle Scholar
  12. de Boer E, Kuyper P (1968) Triggered correlation. IEEE Trans. on Biomed. Eng. 15:169–179.Google Scholar
  13. Douglas RJ, Koch C, Mahowald M, Martin KA, Suarez HH (1995) Recurrent excitation in neocortical circuits. Science 269:981–985.PubMedGoogle Scholar
  14. Ferster D (1986) Orientation selectivity of synaptic potentials in neurons of cat primary visual cortex. J. Neurosci. 6:1284–1301.PubMedGoogle Scholar
  15. Ferster D, Chung S, Wheat H (1996) Orientation selectivity of thalamic input to simple cells of cat visual cortex. Nature 380:249–252.PubMedGoogle Scholar
  16. 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
  17. Gut A (1988) Stopped random walks: Limit theorems and applications. Springer Verlag, New York.Google Scholar
  18. 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.PubMedGoogle Scholar
  19. Heeger DJ (1992a) Half-squaring in responses of cat striate cells. Visual Neurosci. 9(5):427–443.Google Scholar
  20. Heeger DJ (1992b) Normalization of cell responses in cat striate cortex. Visual Neurosci. 9(2):181–197.Google Scholar
  21. Hubel DH, Wiesel TN (1962) Receptive fields, binocular interaction and functional architecture of cat's visual cortex. J. Physiol. Lond. 160:106–154.PubMedGoogle Scholar
  22. Hubel DH, Wiesel TN (1968) Receptive fields and functional architecture of monkey striate cortex. J. Physiol. Lond. 195:215–245.PubMedGoogle Scholar
  23. Jones JP, Palmer LA (1987) The two-dimensional spatial structure of simple receptive fields in the cat striate cortex. J. Neurophysiol. 58:1187–1258.PubMedGoogle Scholar
  24. 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.PubMedGoogle Scholar
  25. 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.PubMedGoogle Scholar
  26. Maex R, Orban GA (1996) Model circuit of spiking neurons generating directional selectivity in simple cells. J. Neurophysiol. 75:1515–1545.PubMedGoogle Scholar
  27. Marcelja S (1980) Mathematical description of the responses of simple cortical cells. J. Opt. Soc. Am. 70(11):1297–1300.PubMedGoogle Scholar
  28. Marmarelis PN, Marmarelis VZ (1978) Analysis of Physiological Systems: The White Noise Approach. New York: Plenum Press.Google Scholar
  29. McCormick DA, Connors BW, Lighthall JW (1985) Comparative electrophysiology of pyramidal and sparsely spiny stellate neurons of the neocortex. J. Neurophysiol. 54:782–806.PubMedGoogle Scholar
  30. 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.PubMedGoogle Scholar
  31. 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.PubMedGoogle Scholar
  32. 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.PubMedGoogle Scholar
  33. Palmer LA, Davis TL (1981) Receptive-field structure in cat striate cortex. J. Neurophysiol. 46(2):260–76.PubMedGoogle Scholar
  34. Reid RC, Alonso JM (1996) The processing and encoding of information in the visual cortex. Current Opinion in Neurobiol. 6:475–480.Google Scholar
  35. 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.PubMedGoogle Scholar
  36. 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.PubMedGoogle Scholar
  37. 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
  38. Ringach DL, Hawken MJ, Shapley R (1997b) Dynamics of orientation tuning in macaque primary visual cortex. Nature 387:281–284.PubMedGoogle Scholar
  39. 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
  40. Ringach DL, Sapiro G, Shapley R (1997c) A subspace reverse correlation technique for the study of visual neurons. Vis. Res. 37:2455–2464.PubMedGoogle Scholar
  41. 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
  42. Sompolinsky H, Shapley R (1997) New perspectives on the mechanisms for orientation selectivity. Current Opinion in Neurobiol. 7:514–522.Google Scholar
  43. 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.PubMedGoogle Scholar
  44. 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
  45. 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

Copyright information

© Kluwer Academic Publishers 2000

Authors and Affiliations

  • M.C. Pugh
    • 1
  • D.L. Ringach
    • 2
  • R. Shapley
    • 3
  • M.J. Shelley
    • 4
  1. 1.Department of MathematicsUniversity of PennsylvaniaPhiladelphia
  2. 2.Departments of Neurobiology and PsychologyUniversity of California at Los AngelesLos Angeles
  3. 3.Center for Neural ScienceNew York UniversityNew York
  4. 4.Courant Institute for Mathematical SciencesNew York UniversityNew York

Personalised recommendations