Skip to main content

Synchronisation, Binding, and the Role of Correlated Firing in Fast Information Transmission

  • Chapter
  • First Online:
Emergent Neural Computational Architectures Based on Neuroscience

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2036))

  • 697 Accesses

Abstract

Does synchronization between action potentials from differ- ent neurons in the visual system play a substantial role in solving the binding problem? The binding problem can be studied quantitatively in the broader framework of the information contained in neural spike trains about some external correlate, which in this case is object configurations in the visual field. We approach this problem by using a mathematical formalism that quantifies the impact of correlated firing in short time scales. Using a power series expansion, the mutual information an ensem- ble of neurons conveys about external stimuli is broken down into firing rate and correlation components. This leads to a new quantification pro- cedure directly applicable to simultaneous multiple neuron recordings. It theoretically constrains the neural code, showing that correlations con- tribute less significantly than firing rates to rapid information processing. By using this approach to study the limits upon the amount of informa- tion that an ideal observer is able to extract from a synchrony code, it may be possible to determine whether the available amount of infor- mation is sufficient to support computational processes such as feature binding.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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.

References

  1. C. von der Malsburg. Binding in models of perception and brain function. Current Opinion in Neurobiology, 5:520–526, 1995.

    Article  Google Scholar 

  2. W. Singer, A.K. Engel, A.K. Kreiter, M.H.J. Munk, S. Neuenschwander, and P. Roelfsema. Neuronal assemblies: necessity, signature and detectability. Trends in Cognitive Sciences, 1:252–261, 1997.

    Article  Google Scholar 

  3. M.N. Shadlen and A.J. Movshon. Synchrony unbound: a critical evaluation of the temporal binding hypothesis. Neuron, 24:67–77, 1999.

    Article  Google Scholar 

  4. G.M. Ghose and J. Maunsell. Specialized representations in visual cortex: a role for binding? Neuron, 24:79–85, 1999.

    Article  Google Scholar 

  5. M.P. Young, K. Tanaka, and S. Yamane. On oscillating neuronal responses in the visual cortex of the monkey. J. Neurophysiol., 67:1464–1474, 1992.

    Google Scholar 

  6. H.D.R. Golledge, C.C. Hilgetag, and M.J. Tovée. Information processing: a solution to the binding problem? Current Biology, 6(9):1092–1095, 1996.

    Article  Google Scholar 

  7. A.M.H.J. Aertsen, G.L. Gerstein, M.K. Habib, and G. Palm. Dynamics of neuronal firing correlation: modulation of “effective connectivity”. J. Neurophysiol., 61:900–917, 1989.

    Google Scholar 

  8. E.D. Adrian. The impulses produced by sensory nerve endings: Part I. J. Physiol. (Lond.), 61:49–72, 1926.

    Google Scholar 

  9. K.H. Britten, M.N. Shadlen, W.T. Newsome, and J.A. Movshon. The analysis of visual-motion-a comparison of neuronal and psychophysical performance. J. Neurosci., 12:4745–4765, 1992.

    Google Scholar 

  10. M.N. Shadlen and W.T. Newsome. Motion perception: seeing and deciding. Proc. Natl. Acad. Sci. USA, 93:628–633, 1996.

    Article  Google Scholar 

  11. C.E. Shannon. A mathematical theory of communication. AT&T Bell Labs. Tech. J., 27:379–423, 1948.

    MathSciNet  MATH  Google Scholar 

  12. M.J. Tovée, E.T. Rolls, A. Treves, and R.P. Bellis. Information encoding and the response of single neurons in the primate temporal visual cortex. J. Neurophysiol., 70:640–654, 1993.

    Google Scholar 

  13. S. Thorpe, D. Fize, and C. Marlot. Speed of processing in the human visual system. Nature, 381:520–522, 1996.

    Article  Google Scholar 

  14. E.T. Rolls, M.J. Tovee, and S. Panzeri. The neurophysiology of backward visual masking: Information analysis. J. Cognitive Neurosci., 11:335–346, 1999.

    Article  Google Scholar 

  15. C.M. Gray, A.K. Engel, P. König, and W. Singer. Synchronization of oscillatory neuronal responses in cat striate cortex: Temporal properties. Visual Neuroscience, 8:337–347, 1992.

    Article  Google Scholar 

  16. A.K. Kreiter and W. Singer. Stimulus-dependent synchronization of neuronal responses in the visual cortex of the awake macaque monkey. J. Neurosci., 16:2381–2396, 1996.

    Google Scholar 

  17. P. König, A.K. Engel, and W. Singer. Relation between oscillatory activity and long-range synchronization in cat visual cortex. Proc. Natl. Acad. Sci. USA, 92:290–294, 1995.

    Article  Google Scholar 

  18. S.C. de Oliveira, A. Thiele, and A. Hoffmann. Synchronization of neuronal activity during stimulus expectation in a direction discrimination task. J. Neurosci., 17:9248–9260, 1997.

    Google Scholar 

  19. P. König, A.K. Engel, P.R. Roelfsema, and W. Singer. How precise is neuronal synchronization? Neural Computation, 7:469–485, 1995.

    Article  Google Scholar 

  20. Y. Hata, T. Tsumoto, H. Sato, and H. Tamura. Horizontal interactions between visual cortical neurones studied by cross-correlation analysis in the cat. Journal of Physiology, 441:593–614, 1991.

    Google Scholar 

  21. F. Rieke, D. Warland, R.R. de Ruyter van Steveninck, and W. Bialek. Spikes: exploring the neural code. MIT Press, Cambridge, MA, 1996.

    MATH  Google Scholar 

  22. A. Borst and F.E. Theunissen. Information theory and neural coding. Nature Neuroscience, 2:947–957, 1999.

    Article  Google Scholar 

  23. S. Panzeri, S.R. Schultz, A. Treves, and E.T. Rolls. Correlations and the encoding of information in the nervous system. Proc. R. Soc. Lond. B, 266:1001–1012, 1999.

    Article  Google Scholar 

  24. S. Panzeri and S. Schultz. A unified approach to the study of temporal, correlational and rate coding. Neural Comp., page submitted, 1999.

    Google Scholar 

  25. M.N. Shadlen and W.T. Newsome. The variable discharge of cortical neurons: implications for connectivity, computation and coding. J. Neurosci., 18(10):3870–3896, 1998.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Schultz, S.R., Golledge, H.D.R., Panzeri, S. (2001). Synchronisation, Binding, and the Role of Correlated Firing in Fast Information Transmission. In: Wermter, S., Austin, J., Willshaw, D. (eds) Emergent Neural Computational Architectures Based on Neuroscience. Lecture Notes in Computer Science(), vol 2036. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44597-8_16

Download citation

  • DOI: https://doi.org/10.1007/3-540-44597-8_16

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42363-8

  • Online ISBN: 978-3-540-44597-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics