title: Two-level hierarchy with sparsely and temporally coded patterns and its possible functional role in information processing.
abstract: We study the stability of two types of mixed states in an oscillator neural network model. Patterns to be stored are represented by complex variables whose amplitudes are either 0 (silent state) or 1 (firing state) and whose phases represent the timing of firing. The mixed states are defined in terms of a certain type of average over some specified number s of memory patterns. We define two types of such mixed states, each of which corresponds to a different type of restriction placed on this set of s memory patterns. The stability of each type is investigated both theoretically and numerically. We find that only one type of a mixed state, which consists of temporally correlated patterns, is stable. Finally, we discuss a possible functional role of such mixed states in information processing.
authors.forename: Masaki
authors.initials: M
authors.lastname: Nomura
authors.forename: Toshio
authors.initials: T
authors.lastname: Aoyagi
authors.forename: Masato
authors.initials: M
authors.lastname: Okada
mesh_terms: D008606:Mental Processes / Q000502:physiology; D016571:Neural Networks, Computer