CLASSIFICATION OF TEMPORAL PATTERNS IN DYNAMIC BIOLOGICAL NETWORKS

A general method is presented to classify temporal patterns generated by rhythmic biological networks when synaptic connections and cellular properties are known. The method is discrete in nature and relies on algebraic properties of state transitions and graph theory. Elements o f the set of rhythms generated by a network are compared using a metri c that quantifies the functional differences among them. The rhythms a re then classified according to their location in a metric space. Exam ples are given, and biological implications are discussed.