Neural network models of timing have struggled to account for animal timing capabilities using the accepted connectionist assumptions, in most cases without postulating the existence of explicit neuronal time-keeping mechanisms. Current ethological and physiological data, however, suggest that cellular oscillators form the foundation for animals' temporal capacities. Wepropose that these oscillators could be used as temporal filters that capture the temporal structure of the animal's experience. A model is presented that accounts for a number of the salient features of the feeding anticipatory response with only a single circadian filter. This model goes beyond current entrainment models in that it correctly predicts the relationship between the feeding period and the anticipatory interval. An alternative approach using multiple filters is examined that can account for animals' ability to correctly anticipate two daily feeding times.Although neural networks have been successfully applied to problems of a spatial nature (in the sense of spatial pattern recognition), they have been deficient in their temporal-processing capabilities. Many attempts at solving the temporal deficiencies have been profoundly nonbiological and have not taken seriously either the primary role that time plays in animal cognition (Gallistel, 1990) or physiological evidence suggesting that timing mechanisms are a cellular phenomenon (Jacklet, 1989;Takahashi & Hoffman, 1995).The research presented here takes at face value the ethological and physiological evidence that points to animals having built-in, self-sustaining oscillators that form the foundation for their temporal-processing capabilities. In this paper, we examine how by placing biologically defensible clocks into the simulated neuron, we give individual neurons a multiphasic transfer function that makes them act like temporal filters. The outputs ofbanks ofsuch filters could capture the temporal structure ofthe animal's experience. In this paper we explore how such a model can account for animals' ability to anticipate daily feeding times. We hope that this approach may ultimately unify the analysis of a variety of temporal-processing problems that animals routinely face, including the learning oftemporal intervals in classical conditioning.Correspondence should be addressed to A. P. King, University of California, Los Angeles, Computer Science Department, 3732 Boelter Hall, Los Angeles, CA 90024-1600 (e-mail: king@cs.ucla.edu).
An Animal's Anticipation of Daily Feeding TimesRosenwasser, Pelchat, and Adler (1984) examined the ability of rats to anticipate a daily feeding time. Initially a rat was given constant access to food. Under these conditions, the rat showed its regular onset ofactivity (wheel running) when the lights went out. After about 2 weeks, the rat was given access to food only for a 2-h period during its subjective day, a time it would not normally be active. After a few days of training, the rat reliably showed anticipatory activity (wheel running) before the sch...