Nothing Special   »   [go: up one dir, main page]
Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Complex cells as cortically amplified simple cells

Nature Neuroscience volume 2, pages 277–282 (1999)Cite this article

Abstract

The majority of synapses in primary visual cortex mediate excitation between nearby neurons, yet the role of local recurrent connections in visual processing remains unclear. We propose that these connections are responsible for the spatial-phase invariance of complex-cell responses. In a network model with selective cortical amplification, neurons exhibit simple-cell responses when recurrent connections are weak and complex-cell responses when they are strong, suggesting that simple and complex cells are the low- and high-gain limits of the same basic cortical circuit. Given the ubiquity of invariant responses in cognitive processing, the recurrent mechanism we propose for complex cells may be widely applicable.

Access through your institution
Buy or subscribe

This is a preview of subscription content, access via your institution

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 2: The effects of recurrent input on model responses.
Figure 1: The architecture of the recurrent model.
Figure 4: At high gain, the model cells are not selective for spatial phase but retain different selectivities for spatial frequency.
Figure 3: The relative modulation of the response of the model cells to a drifting 2-Hz grating as a function of g/gmax, the strength of the recurrent connections relative to the maximum stable strength.
Figure 5: Four representative neurons from a model network with a mixture of simple and complex cells.
Figure 6: Temporal-frequency tuning curves of F2 (the amplitude of the response at twice the stimulus frequency) and F0 (the amplitude of the unmodulated response) components in response to counterphase and drifting gratings.
Figure 7: Measures of complexity vary as a function of temporal frequency.

Similar content being viewed by others

References

  1. McGuire, B. A., Hornung, J. P., Gilbert, C. D. & Wiesel, T. N. Patterns of synaptic input to layer 4 of cat striate cortex. J. Neurosci. 4, 3021–3033 (1984).

    Article  CAS  Google Scholar 

  2. Kisvarday, Z. F. et al. Synaptic targets of HRP-filled layer III pyramidal cells in the cat striate cortex. Exp. Brain Res. 64, 541–542 (1986).

    Article  CAS  Google Scholar 

  3. LeVay, S. Synaptic organization of claustral and geniculate afferents to the visual cortex of the cat. J. Neurosci. 6, 3564–3575 (1986).

    Article  CAS  Google Scholar 

  4. White, E. L. Cortical Circuits: Synaptic Organization of the Cerebral Cortex (Birkauser, Boston, 1989).

  5. Braitenberg, V. & Schüz, A. Anatomy of the Cortex (Springer, Berlin, 1991).

  6. Peters, A. & Payne, B. R. Numerical relationships between geniculocortical afferents and pyramidal cell modules in cat primary visual cortex. Cereb. Cortex 3, 69–78 (1993).

    Article  CAS  Google Scholar 

  7. Peters, A. & Payne, B. R. A numerical analysis of the geniculocortical input to striate cortex in the monkey. Cereb. Cortex 4, 215–229 (1994).

    Article  CAS  Google Scholar 

  8. Douglas, R. J., Koch, C., Mahowald, M., Martin, K. A. C. & Suarez, H. H. Recurrent excitation in neocortical circuits. Science 269, 981–985 (1995).

    Article  CAS  Google Scholar 

  9. Ben-Yishai, R., Bar-Or, L. & Sompolinsky, H. Theory of orientation tuning in visual cortex. Proc. Natl. Acad. Sci. USA 92, 3844–3848 (1995).

    Article  CAS  Google Scholar 

  10. Somers, D. C., Nelson, S. B. & Sur, M. An emergent model of orientation selectivity in cat visual cortical simple cells. J. Neurosci. 15, 5448–5465 (1995).

    Article  CAS  Google Scholar 

  11. Sompolinsky, H. & Shapley, R. New perspectives on the mechanisms for orientation selectivity. Curr. Opin. Neurobiol. 7, 514–522 (1997).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  13. Chung, S. & Ferster, D. Strength and orientation tuning of the thalamic input to simple cells revealed by electrically evoked cortical suppression. Neuron 20, 1177–1189 (1998).

    Article  CAS  Google Scholar 

  14. Hubel, D. H. & Wiesel, T. N. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. J. Physiol. (Lond.) 160, 106–154 (1962).

    Article  CAS  Google Scholar 

  15. Movshon, J., Thompson, I. & Tolhurst, D. Spatial summation in the receptive fields of simple cells in the cat's striate cortex. J. Physiol. (Lond.) 283, 53–77 (1978).

    Article  CAS  Google Scholar 

  16. Movshon, J., Thompson, I. & Tolhurst, D. Receptive field organization of complex cells in cat's striate cortex. J. Physiol. (Lond.) 283, 79–99 (1978).

    Article  CAS  Google Scholar 

  17. Mel, B. W., Ruderman, D. L. & Archie, K. A. Translation–invariant orientation tuning in visual complex cells could derive from intradendritic computations. J. Neurosci. 18, 4325–4334 (1998).

    Article  CAS  Google Scholar 

  18. Adelson, E. H. & Bergen, J. R. Spatiotemporal energy models for the perception of motion. J. Opt. Soc. Am. A 2, 284–299 (1985).

    Article  CAS  Google Scholar 

  19. Pollen, D. A. & Ronner, S. F. Phase relationships between adjacent simple cells in the visual cortex. Science 212, 1409–1411 (1981).

    Article  CAS  Google Scholar 

  20. Toyama, K., Kimura, M. & Tanaka, K. Organization of cat visual cortex as investigated by cross–correlation technique. J. Neurophysiol. 46, 202–214 (1981).

    Article  CAS  Google Scholar 

  21. Hawken, M. J., Shapley, R. M. & Grosof, D. H. Temporal-frequency selectivity in monkey visual cortex. Vis. Neurosci. 13, 477–492 (1996).

    Article  CAS  Google Scholar 

  22. Chance, F. S., Nelson, S. B. & Abbott, L. F. Synaptic depression and the temporal response characteristics of V1 cells. J. Neurosci. 18, 4785–4799 (1998).

    Article  CAS  Google Scholar 

  23. Varela, J. A. et al. A quantitative description of short-term plasticity at excitatory synapses in layer 2/3 of rat primary visual cortex. J. Neurosci. 17, 7926–7940 (1997).

    Article  CAS  Google Scholar 

  24. Abbott, L. F., Varela, J. A., Sen, K. & Nelson, S. B. Synaptic depression and cortical gain control. Science 275, 220–224 (1997).

    Article  CAS  Google Scholar 

  25. Tsodyks, M. V. & Markram, H. The neural code between neocortical pyramidal neurons depends on neurotransmitter release probability. Proc. Natl. Acad. Sci. USA 94, 719–723 (1997).

    Article  CAS  Google Scholar 

  26. Alonso, J.-M. & Martinez, L. M. Functional connectivity between simple cells and complex cells in cat striate cortex. Nat. Neurosci. 1, 395–403 (1998).

    Article  CAS  Google Scholar 

  27. Hoffman, K. P. & Stone, J. Conduction velocity of afferents of cat visual cortex: a correlation with cortical receptive field properties. Brain Res. 32, 460–466 (1971).

    Article  CAS  Google Scholar 

  28. Singer, W., Tretter, F. & Cynader, M. Organization of cat striate cortex: a correlation of receptive-field properties with afferent and efferent connections. J. Neurophysiol. 38, 1080–1098 (1975).

    Article  CAS  Google Scholar 

  29. Ferster, D. & Lindström, S. An intracellular analysis of geniculo-cortical connectivity in area 17 of the cat. J. Physiol. (Lond.) 342, 181–215 (1983).

    Article  CAS  Google Scholar 

  30. Hammond, P. & MacKay, D. M. Differential responses of cat visual cortical cells to textured stimuli. Exp. Brain Res. 22, 427–430 (1975).

    Article  Google Scholar 

  31. Movshon, J. A. The velocity tuning of single units in cat striate cortex. J. Physiol. (Lond.) 249, 445–468 (1975).

    Article  CAS  Google Scholar 

  32. Hammond, P. & MacKay, D. M. Differential responsiveness of simple and complex cells in cat striate cortex to visual texture. Exp. Brain Res. 30, 275–296 (1977).

    CAS  PubMed  Google Scholar 

  33. Malpeli, J. G. Activity of cells in area 17 of the cat in absence of input from layer A of lateral geniculate nucleus. J. Neurophysiol. 49, 595–610 (1983).

    Article  CAS  Google Scholar 

  34. Malpeli, J. G., Lee, C., Schwark, H. D. & Weyand, T. G. Cat area 17. I. Pattern of thalamic control of cortical layers. J. Neurophysiol. 56, 1062–1073 (1986).

    Article  CAS  Google Scholar 

  35. Mignard, M. & Malpeli, J. G. Paths of information flow through visual cortex. Science 251, 1249–1251 (1991).

    Article  CAS  Google Scholar 

  36. Sillito, A. M. The contribution of inhibitory mechanisms to the receptive field properties of neurones in the striate cortex of the cat. J. Physiol. (Lond.) 250, 305–329 (1975).

    Article  CAS  Google Scholar 

  37. Borg-Graham, L. J., Monier, C. & Frégnac, Y. Visual input evokes transient and strong shunting inhibition in visual cortical neurons. Nature 393, 369–373 (1998).

    Article  CAS  Google Scholar 

  38. Debanne, D., Shulz, D. E. & Frégnac, Y. Activity-dependent regulation of 'on' and 'off' responses in cat visual cortical receptive fields. J. Physiol. (Lond.) 508, 523–548 (1998).

    Article  CAS  Google Scholar 

  39. Treves, A. Mean-field analysis of neuronal spike dynamics. Network 4, 259–284 (1993).

    Article  Google Scholar 

Download references

Acknowledgements

Research supported by the Sloan Center for Theoretical Neurobiology at Brandeis University, the National Science Foundation (DMS-95-03261), the W.M. Keck Foundation, the National Eye Institute (EY-11116) and the Alfred P. Sloan Foundation.

Author information

Authors and Affiliations

  1. Volen Center and Department of Biology, Brandeis University, Waltham, 02454-9110, Massachusetts, USA

    Frances S. Chance, Sacha B. Nelson & L.F. Abbott

Authors
  1. Frances S. Chance
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sacha B. Nelson
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. L.F. Abbott
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to L.F. Abbott.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chance, F., Nelson, S. & Abbott, L. Complex cells as cortically amplified simple cells. Nat Neurosci 2, 277–282 (1999). https://doi.org/10.1038/6381

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1038/6381

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing