Computational Versus Associative Models of Simple Conditioning

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Abstract
In associative models of simple conditioning, conductive connections (associations, Hebbian synapses) are strengthened by the repetitive temporal pairing of stimuli. The associations cause the animal to behave more adaptively, but they do not encode information about objectively specifiable properties of the conditioning experience. In information processing (computational) models, the temporal intervals in that experience are timed and the results recorded in memory for later use in computations that determine the decisions whether and when to respond to the conditioned stimulus. The predictions of these latter models depend on the ratios of remembered and currently experienced temporal intervals; hence, they are time-scale invariant. Two examples of empirical time-scale invariance are described: Neither the delay of reinforcement nor the ratio of reinforced to unreinforced presentations of the conditioned stimulus affects rates of acquisition and extinction. Time-scale invariance has far-reaching implications for models of the processes that underlie conditioning, for example, models of Hebbian synapses.

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