The analysis of continuous temporal sequences by a map of sequential leaky integrators

The problem to detect and recognize the occurrence of specific events in a continually evolving environment, is particularly important in many fields, starting from motor planning. In this paper, the authors propose a two-dimensional map, where the processing elements correspond to specific instances of leaky integrators whose parameters (or tops) are learned in a self-organizing manner: in this way the map becomes a topologic representation of temporal sequences whose presence in a continuous temporal data flow is detectable by means of the activation level of the corresponding neurons