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.

  • News & Views
  • Published:

Predicting the visual world: silence is golden

Nature Neuroscience volume 2, pages 9–10 (1999)Cite this article

Abstract

In predictive coding, only unexpected input features are signaled to the next stage of processing. Rao and Ballard use this approach to model extra–classical receptive field effects.

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

Relevant articles

Open Access articles citing this article.

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Figure 1: A purely feedforward model10 can account for the available quantitative data on view–tuned inferotemporal cells.

References

  1. Atick, J. J. Network 3, 213–251 ( 1992).

    Article  Google Scholar 

  2. Rao, R. P. N. & Ballard, D. H. Nature Neurosci. 2, 79–87 (1999 ).

    Article  CAS  Google Scholar 

  3. Poggio, T., Reichardt, W. & Hausen, K. Naturwissenschaften 68, 443– 446 (1981).

    Article  Google Scholar 

  4. Rao, R. P. N. & Ballard, D. H. Neural Comput. 9, 721–763 (1997).

    Article  CAS  Google Scholar 

  5. Logothetis, N. K, Pauls, J. & Poggio, T. Curr. Biol. 5, 552– 563 (1995).

    Article  CAS  Google Scholar 

  6. Kobatake, E., Wang, G. & Tanaka, K. J. Neurophysiol. 80, 324– 330 (1998).

    Article  CAS  Google Scholar 

  7. Epstein, R. & Kanwisher, N. Nature 392, 598–601 (1998).

    Article  CAS  Google Scholar 

  8. Fukushima, K. Biol. Cybern. 36, 193–202 (1980).

    Article  CAS  Google Scholar 

  9. Perret, D. & Oram, M. Image Vision Comput. 11 , 317–333 (1993).

    Article  Google Scholar 

  10. Riesenhuber, M. & Poggio, T. AI Memo 1629, CBCL Paper 160 (1998).

    Google Scholar 

  11. Thorpe, S., Fize, D. & Marlot C. Nature 381, 520–522 ( 1996).

    Article  CAS  Google Scholar 

  12. Crick, F. & Koch, C. Nature 391, 245–249 (1998).

    Article  CAS  Google Scholar 

  13. Koch, C. Biophysics of Computation (Oxford Univ. Press, New York, 1998).

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Christof Koch is at the Computation and Neural Systems Program, California Institute of Technology,, Pasadena, 91125, California, USA

    Christof Koch

  2. Tomaso Poggio is at CBCL in the Brain Sciences Department and in the AI Lab at MIT, Cambridge, 02142, Massachusetts, USA

    Tomaso Poggio

Authors
  1. Christof Koch
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tomaso Poggio
    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

Koch, C., Poggio, T. Predicting the visual world: silence is golden. Nat Neurosci 2, 9–10 (1999). https://doi.org/10.1038/4511

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1038/4511

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