Spike independency in feed-forward networks.
A cortical neuron puts thousands of synaptic contacts on other neurons. The effect of the spike event spreads over a large number of neurons. So it is possible for spike timings to be correlated to each other. But there have not been so many reports of spike timing correlations, while there have been many reports of somewhat longer time range correlations through mean spike rates. Can independent firings be preserved in spite of a number of connections? The present study attempts to determine whether independent firings can be propagated through a simple feed-forward neural network. It is assumed that each unit obeys a threshold mechanism at each discrete time and that connections are statistically uniform with the excitation balanced to the inhibition and delay distributed. It is found that the independent firings can be stably propagated through the feed-forward network at a network parameter region, which contains the physiologically reasonable range. Another interesting result is that the independency-stable spike probability has a lower limit 0.0323.
Sakai
Yutaka
Y
Department of Information and Computer Science, Faculty of Engineering, Saitama University, Saitama 338-8570, Japan. sakai@bios.ics.saitama-u.ac.jp
D000200:Action Potentials / Q000502:physiology*; D016571:Neural Networks, Computer