On the Relevance of the Shape of Postsynaptic Potentials for the
Computational Power of Networks of Spiking Neurons
The firing of a neuron in a biological neural system causes in certain other
neurons excitatory postsynaptic potential changes (EPSP's) that are not
"rectangular", but have the form of a smooth hill. We prove in this article
for a formal model of a network of spiking neurons, that the rising
respectively declining segments of these EPSP's are in fact essential for the
computational power of the model.
Reference: W. Maass and B. Ruf.
On the relevance of the shape of postsynaptic potentials for the computational
power of networks of spiking neurons.
In Proc. of the International Conference on Artificial Neural Networks
ICANN, pages 515-520, Paris, 1995. EC2&Cie.