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.