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.
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© 2007 Springer-Verlag Berlin Heidelberg
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Sirovich, R., Sacerdote, L., Villa, A.E.P. (2007). Effect of Increasing Inhibitory Inputs on Information Processing Within a Small Network of Spiking Neurons. In: Sandoval, F., Prieto, A., Cabestany, J., Graña, M. (eds) Computational and Ambient Intelligence. IWANN 2007. Lecture Notes in Computer Science, vol 4507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73007-1_4
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DOI: https://doi.org/10.1007/978-3-540-73007-1_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73006-4
Online ISBN: 978-3-540-73007-1
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