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Effect of Increasing Inhibitory Inputs on Information Processing Within a Small Network of Spiking Neurons

  • Roberta Sirovich
  • Laura Sacerdote
  • Alessandro E. P. Villa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4507)

Abstract

In this paper the activity of a spiking neuron A that receives a background input from the network in which it is embedded and strong inputs from an excitatory unit E and an inhibitory unit I is studied. The membrane potential of the neuron A is described by a jump diffusion model. Several types of interspike interval distributions of the excitatory strong inputs are considered as Poissonian inhibitory inputs increase intensity. It is shown that, independently of the distribution of the excitatory inpu, they are more efficiently transmitted as inhibition increases to larger intensities.

Keywords

Firing Rate Process Versus Spike Train Excitatory Input Counting Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Roberta Sirovich
    • 1
    • 2
  • Laura Sacerdote
    • 1
  • Alessandro E. P. Villa
    • 2
  1. 1.Department of Mathematics, University of Torino, Via Carlo Alberto 10, 10123 TorinoItaly
  2. 2.Neuroheuristics Research Group, University Joseph Fourier Grenoble 1, Equipe NanoNeurosciences Fondamentales et Appliques, Grenoble Institut des Neurosciences - U 836 Inserm - UJF -CEAFrance

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