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Multiple synfire chains in simultaneous action lead to poisson-like neuronal firing

Raphael Ritz

The Salk Institute

The irregularity of neuronal firing times is commonly interpreted as being due to noise. Here, an alternative approach is taken to show that even in a completely deterministic model - without any noise - neuronal firing times might appear random. This can be achieved in an attractor model with spiking neurons where the limit cycles are complex spatio-temporal spiking patterns, a generalization of the synfire chains as introduced by Abeles. Simultaneous activation of several such synfire chains can lead to arbitrarily complex-looking spike patterns at the single neuron level. In addition, a learning rule is suggested that allows to store general spatio-temporal spiking patterns. As a consequence of this work, traditional assumptions about neuronal coding have to be reexamined and more elaborated experimental techniques are required to crack the neural code.

Tony Zador
Wed Mar 12 22:07:02 PST 1997