Skip to main content

An LGN Inspired Detect/Transmit Framework for High Fidelity Relay of Visual Information with Limited Bandwidth

  • Conference paper
Brain, Vision, and Artificial Intelligence (BVAI 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3704))

Included in the following conference series:

  • 945 Accesses

Abstract

The mammalian visual system has developed complex strategies to optimize the allocation of its limited attentional resources for the relay of behaviorally relevant visual information. Here, we describe a framework for the relay of visual information that is based on the tonic and burst properties of the LGN. The framework consists of a multi-sensor transmitter and receiver that are connected by a channel with limited total bandwidth. Each sensor in the transmitter has two states, tonic and burst, and the current state depends on the salience of the recent visual input. In burst mode, a sensor transmits only one bit of information corresponding to the absence or presence of a salient stimulus, while in tonic mode, a sensor attempts to faithfully relay the input with as many bits as are available. By comparing video reconstructed from the signals of detect/transmit sensors with that reconstructed from the signals of transmit only sensors, we demonstrate that the detect/transmit framework can significantly improve relay by dynamically allocating bandwidth to the most salient areas of the visual field.

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

Access this chapter

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

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Sherman, S.M.: Tonic and burst firing: dual modes of thalamocortical relay. TINS 24, 122–126 (2001)

    Google Scholar 

  2. Krahe, R., Gabbiani, F.: Burst firing in sensory systems. Nature Reviews: Neuroscience 5, 13–23 (2004)

    Article  Google Scholar 

  3. Steriade, M., Llinas, R.R.: The functional states of the thalamus and the associated neuronal interplay. Physiol. Rev. 68, 649–742 (1988)

    Google Scholar 

  4. Sillito, A.M., Jones, H.E.: Corticothalamic interaction in the transfer of visual information. Phil. Trans. R. Soc. Lond. B 357, 1739–1752 (2002)

    Article  Google Scholar 

  5. Guido, W., Weyand, T.: Burst responses in thalamic relay cells of the awake behaving cat. J. Neurophysiol. 74, 1782–1786 (1995)

    Google Scholar 

  6. Weyand, T.G., Boudreaux, M., Guido, W.: Burst and tonic response modes in thalamic neurons during sleep and wakefulness. J. Neurophysiol. 85, 1107–1118 (2001)

    Google Scholar 

  7. Lesica, N.A., Stanley, G.B.: Encoding of natural scene movies by tonic and burst spikes in the lateral geniculate nucleus. J. Neurosci. 24, 10731–10740 (2004)

    Article  Google Scholar 

  8. Simoncelli, E.P., Olshausen, B.A.: Natural image statistics and neural representation. Annu. Rev. Neurosci. 24, 1193–1216 (2001)

    Article  Google Scholar 

  9. Itti, L., Koch, C.: A saliency-based search mechanism for overt and covert shifts of visual attention. Vision Res. 40, 1489–1506 (2000)

    Article  Google Scholar 

  10. Itti, L., Koch, C.: Computational modelling of visual attention. Nature Rev. Neurosci. 2, 194–203 (2001)

    Article  Google Scholar 

  11. Shipp, S.: The brain circuitry of attention. TICS 8, 223–230 (2004)

    Google Scholar 

  12. Barlow, H.B.: Possible principles underlying the transformations of sensory messages. In: Rosenblith, W.A. (ed.) Sensory Communication, pp. 217–234. MIT Press, Cambridge (1961)

    Google Scholar 

  13. Srinivasan, M.V., Laughlin, S.B., Dubs, A.: Predictive coding: A fresh view of inhibition in the retina. Proc. R. Soc. Lond. B 216, 427–459 (1982)

    Article  Google Scholar 

  14. Atick, J.J., Redlich, A.N.: What does the retina know about natural scenes? Neural Computation 4, 196–210 (1992)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Lesica, N.A., Stanley, G.B. (2005). An LGN Inspired Detect/Transmit Framework for High Fidelity Relay of Visual Information with Limited Bandwidth. In: De Gregorio, M., Di Maio, V., Frucci, M., Musio, C. (eds) Brain, Vision, and Artificial Intelligence. BVAI 2005. Lecture Notes in Computer Science, vol 3704. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11565123_18

Download citation

  • DOI: https://doi.org/10.1007/11565123_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29282-1

  • Online ISBN: 978-3-540-32029-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics