Abstract
Direct storage of temporal sequences is analysed in terms of a neural net composed of leaky integrator neurons with a range of time constants. These neurons store previously presented patterns and allow the transitions between the patterns of a sequence to be learnt. This is shown even to lead to disambiguation (which is defined in Section 1). Storage capacity is determined by simulation. We also present a detailed study of the efficiency of this system in its dependence on the type of neuronal activity. Finally, we note the relevance of our model to understanding activity in the hippocampus.
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