Spontaneous Dynamics of Asymmetric Random Recurrent Spiking Neural Networks

Details Spontaneous Dynamics of Asymmetric Random Recurrent Spiking Neural Networks Spontaneous Dynamics of Asymmetric Random Recurrent Spiking Neural Networks

2004-11-17

arxiv.org/abs/cs/0411052v1

Computer Science

Neural and Evolutionary Computing

28 pages, 7 figures

Scientific paper

We study in this paper the effect of an unique initial stimulation on random recurrent networks of leaky integrate and fire neurons. Indeed given a stochastic connectivity this so-called spontaneous mode exhibits various non trivial dynamics. This study brings forward a mathematical formalism that allows us to examine the variability of the afterward dynamics according to the parameters of the weight distribution. Provided independence hypothesis (e.g. in the case of very large networks) we are able to compute the average number of neurons that fire at a given time -- the spiking activity. In accordance with numerical simulations, we prove that this spiking activity reaches a steady-state, we characterize this steady-state and explore the transients.

Affiliated with

Also associated with

No associations

Rating

Spontaneous Dynamics of Asymmetric Random Recurrent Spiking Neural Networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Spontaneous Dynamics of Asymmetric Random Recurrent Spiking Neural Networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Spontaneous Dynamics of Asymmetric Random Recurrent Spiking Neural Networks will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-654660