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Synchrony is stubborn in feedforward cortical networks

Nature Neuroscience volume 6, pages 543–544 (2003)Cite this article

Action potential propagation has been studied extensively in model networks. Now a new paper describes an innovative method of combining neuronal recordings with real-time neuronal modeling to create multi-layer feedforward networks. Neurons in deep layers tend to fire in synchrony, suggesting such networks may code sensory information by groups of neurons that fire together.

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Figure 1: Making a sparsely connected multi-layer feedforward network using a single cortical neuron and a computer.

Ivelisse Robles

References

  1. Izhikevich, E.M., Desai, N.S., Walcott, E.C. & Hoppensteadt, F.C. Trends Neurosci. 26, 161–167 (2003).

    Article  CAS  Google Scholar 

  2. Abeles, M. Corticonics: Neural Circuits of the Cerebral Cortex (Cambridge Univ. Press, Cambridge, UK, 1991).

    Book  Google Scholar 

  3. Singer, W. Neuron 24, 49–65 (1999).

    Article  CAS  Google Scholar 

  4. Reyes, A. Nat. Neurosci. 6, 595–601 (2003).

    Article  Google Scholar 

  5. Shadlen, M.N. & Newsome, W.T. J. Neurosci. 18, 3870–3896 (1998).

    Article  CAS  Google Scholar 

  6. van Rossum, M.C.W., Turrigiano, G.G. & Nelson, S.B. J. Neurosci. 22, 1956–1966 (2002).

    Article  CAS  Google Scholar 

  7. Litvak, V., Sompolinsky, H., Segev, I. & Abeles, M. J. Neurosci. 23, 3006–3015 (2003).

    Article  CAS  Google Scholar 

  8. Diesmann, M., Gewaltig, M.O. & Aertsen, A. Nature 402, 529–533 (1999).

    Article  CAS  Google Scholar 

  9. Golomb, D. & Hansel, D. Neural Comput. 12, 1095–1139 (2000).

    Article  CAS  Google Scholar 

  10. Agmon-Snir, H. & Segev, I. J. Neurophysiol. 70, 2066–2085 (1993).

    Article  CAS  Google Scholar 

  11. Mainen, Z.F. & Sejnowski, T.J. Nature 25, 363–366 (1996).

    Article  Google Scholar 

  12. Reyes, A. Annu. Rev. Neurosci. 24, 653–675 (2001).

    Article  CAS  Google Scholar 

  13. Larkum, M.E., Zhu, J.J., Sakmann, B. Nature 398, 338–341 (1999).

    Article  CAS  Google Scholar 

  14. Williams, S.R. & Stuart, G.J. Science 295, 1907–1910 (2002).

    Article  CAS  Google Scholar 

  15. van Vreeswijk, C. & Sompolinsky, H. Science 274, 1724–1726 (1996).

    Article  CAS  Google Scholar 

Download references

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Authors and Affiliations

  1. the Department of Neurobiology and Center for Neural Computation, The Hebrew University, Jerusalem, 91904, Israel

    Idan Segev

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  1. Idan Segev
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Segev, I. Synchrony is stubborn in feedforward cortical networks. Nat Neurosci 6, 543–544 (2003). https://doi.org/10.1038/nn0603-543

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