8
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Synchronization in networks of excitatory and inhibitory neurons with sparse, random connectivity.

      1 ,
      Neural computation
      MIT Press - Journals

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          In model networks of E-cells and I-cells (excitatory and inhibitory neurons, respectively), synchronous rhythmic spiking often comes about from the interplay between the two cell groups: the E-cells synchronize the I-cells and vice versa. Under ideal conditions-homogeneity in relevant network parameters and all-to-all connectivity, for instance-this mechanism can yield perfect synchronization. We find that approximate, imperfect synchronization is possible even with very sparse, random connectivity. The crucial quantity is the expected number of inputs per cell. As long as it is large enough (more precisely, as long as the variance of the total number of synaptic inputs per cell is small enough), tight synchronization is possible. The desynchronizing effect of random connectivity can be reduced by strengthening the E --> I synapses. More surprising, it cannot be reduced by strengthening the I --> E synapses. However, the decay time constant of inhibition plays an important role. Faster decay yields tighter synchrony. In particular, in models in which the inhibitory synapses are assumed to be instantaneous, the effects of sparse, random connectivity cannot be seen.

          Related collections

          Author and article information

          Journal
          Neural Comput
          Neural computation
          MIT Press - Journals
          0899-7667
          0899-7667
          Mar 2003
          : 15
          : 3
          Affiliations
          [1 ] Department of Mathematics, Tufts University, Medford, MA 02155, U.S.A. chritopher.borgers@tufts.edu
          Article
          10.1162/089976603321192059
          12620157
          ff2f8f88-6690-46b1-bf44-46e7f287670b
          History

          Comments

          Comment on this article