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This article is part of the supplement: Sixteenth Annual Computational Neuroscience Meeting: CNS*2007

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Spontaneous pattern generation by a network with dynamic synapses

Dmitri Bibitchkov123*, Barak Blumenfeld1 and Misha Tsodyks1

Author Affiliations

1 Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel

2 Department of Membrane Biophysics, Max-Planck Institute for Biophysical Chemistry, Göttingen, Germany

3 Bernstein Center for Computational Neuroscience, Göttingen, Germany

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BMC Neuroscience 2007, 8(Suppl 2):P182  doi:10.1186/1471-2202-8-S2-P182

The electronic version of this article is the complete one and can be found online at:

Published:6 July 2007

© 2007 Bibitchkov et al; licensee BioMed Central Ltd.

Poster presentation

Experimental evidence demonstrates that the ongoing spontaneous activity in the visual cortex in the absence of visual stimulation can exhibit complex spatiotemporal patterns. Voltage-sensitive dye imaging studies reveal that activity patterns similar to orientation maps can emerge and dynamically switch in V1 of anesthetized cats [1]. It has been shown that these patterns can be generated by an intracortical network which has intrinsic preferred states correlated with functional maps [2]. The suggested connectivity in such a network depends on the preferred orientation and on the degree of orientation selectivity of the interconnected neurons. In this network, single condition orientation maps are steady states of the neural dynamics and form a ring attractor. To account for dynamical switching between these intrinsic states, we introduced short-term depression into the synaptic connections in the network. We study the effects of synaptic dynamics on the stability of attractor states. We found that synaptic depression, first, stabilizes the overall network activity excluding the possibility of amplitude instability. On the other hand, synaptic depression provides a mechanism of smooth transition between states corresponding to neighboring orientations, observed experimentally. Together with a fluctuating afferent input synaptic dynamics induce dynamic switches between the ring attractor and linear phases. As a result, a complex behaviour emerges with statistical properties similar to the experimentally observed phenomena.


  1. Kenet T, Bibitchkov D, Tsodyks M, Grinvald A, Arieli A: Spontaneously emerging cortical representations of visual attributes.

    Nature 2003, 425(6961):954-956. PubMed Abstract | Publisher Full Text OpenURL

  2. Blumenfeld B, Bibitchkov D, Tsodyks M: Neural network model of the primary visual cortex: from functional architecture to lateral connectivity and back.

    J Comput Neurosci 2006, 20(2):219-241. PubMed Abstract | Publisher Full Text OpenURL