Abstract
A novelty detector is a functional unit, that indicates whether an incoming stimulus is familiar or novel. Novelty detection is prevalent in the central nervous system (CNS), and is involved in various activities. Its basic characteristics are discussed first. Then, models of neural novelty detectors are described, and tested and evaluated in simulations. The simulations have shown that one novelty detector, the bi-compartmental, simulates very closely the behavior of neural novelty detectors. This model is constructed in a way that resembles the observed architecture and function of area 17, and similar regions in the cortex. The first step in novelty detection is data retrieval. The proposed novelty detectors can utilize various compatible modes of data storage and retrieval, and one of those has been utilized in the simulations.
Published Version
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