The nature of the reward representation in Pavlovian conditioning has been of perennial interest to students of associative learning theory. We consider the view that it consists of a range of different attributes, each of which may be governed by different learning rules. We investigated this issue through a series of experiments using a time-sensitive Pavlovian-to-instrumental transfer procedure, aiming to dissociate learning about temporal and specific sensory features of a reward. Our results successfully demonstrated that learning about these different features appears to be dissociable, with learning about the specific sensory features of a Pavlovian unconditioned stimulus (US) occurring very rapidly across a wide range of experimental procedures, while learning about the temporal features of the US occurred slightly less quickly and was more sensitive to parametric disruption. These results are discussed with regard to the potential independence or interdependence of the relevant learning processes, and to some recent neurophysiological recording and brain lesion work, which provide additional means to investigate these dissociations.

Three experiments sought to develop the suggestion that, under some circumstances, common associative learning mechanisms might underlie animal conditioning and human causal learning, by demonstrating, in humans, an effect analogous to the unblocking by reinforcer omission observed in animal conditioning. Experiment 1 found no such effect. Experiment 2, designed to prevent inhibitory influences that might have masked excitatory unblocking in Experiment 1, demonstrated unblocking, indicating common human-animal associative learning mechanisms in which the associability of a stimulus varies as a function of its predictive history. Experiment 3, using a similar design but with a procedure promoting application of rational inference processes, failed to detect the same unblocking effect, indicating that associative and cognitive mechanisms may influence human causal learning.

Apathy, characterized by generally reduced interest in and likelihood to perform goal-directed actions, is a recognized symptom of Huntington’s disease (HD), a devastating neurological disorder caused by a CAG repeat expansion of the Htt gene located on chromosome 4. The present experiments used a modified progressive ratio task that incorporated a fixed-ratio schedule of reinforcement component to assess consummatory behavior, and a progressive-ratio schedule component that required increasing numbers of lever-presses for successive reinforcers (0.01 ml of evaporated milk). The studies revealed an apathetic phenotype in two mouse models of HD, with decreased response rates either overall or only at higher ratio requirements in the progressive-ratio component relative to wild-type controls. Based on the procedure used (within-session fixed- and progressive-ratio components), it is proposed that an observed phenotype can be ascribed either specifically to reduced motivation to work for food reinforcement or more generally to deficits in consummatory behavior. This procedure provides a simple means to assess this type of phenotype in rodents, with issues in consummatory vs. incentive motivation reflected in general alterations in fixed- versus progressive alterations on an escalating-ratio schedules respectively, providing translational measures of the amotivation/apathy construct of the human realm to the homologous construct of incentive motivation in preclinical models of human disease.

Two experiments examined the outcome specificity of a learned predictiveness effect in human causal learning. Experiment 1 indicated that prior experience of a cue-outcome relation modulates learning about that cue with respect to a different outcome from the same affective class but not with respect to an outcome from a different affective class. Experiment 2 ruled out an interpretation of this effect in terms of context specificity. These results indicate that learned predictiveness effects in human causal learning index an associability that is specific to a particular class of outcomes. Moreover, they mirror demonstrations of the reinforcer specificity of analogous effects in animal conditioning, supporting the suggestion that, under some circumstances, human causal learning and animal conditioning reflect the operation of common associative mechanisms.In the field of animal conditioning, it is relatively well established that experience of a predictive (or nonpredictive) relation between a conditioned stimulus (CS) and an unconditioned stimulus (US) appears to affect the processing power devoted to learning about that CS on subsequent learning episodes. One model of such learned predictiveness effects in animal conditioning is that proposed by Mackintosh (1975), which states that the change in associative strength (⌬V) for CS A on each learning episode is given bywhere V A represents the associative strength of CS A, S is a constant learning-rate parameter, and is the asymptote of conditioning supportable by the US occurring on that trial. ␣ A represents the associability of Cue A. Mackintosh allowed associability to change as a result of experience of a cue's predictiveness, with animals proposed to devote more processing power to stimuli that are uniquely successful in their predictions. Specifically, Cue A maintains a high associability to the extent that it is a better predictor of the outcome of the current trial than are all other cues present. Conversely, associability decreases if the outcome is predicted by other events at least as well as by Cue A. The extent to which the outcome is predicted by Cue A is represented by the absolute value of the error term ( Ϫ V A ). These ideas can therefore be encapsulated in the following rules:andwhere V Z is the associative strength of all stimuli other than Cue A present on that trial. The size of the change in associability on each trial is proportional to the magnitude of these inequalities. It should be noted that this is not the only theory of associative learning to incorporate a variable associability mechanism. For instance, Pearce and Hall (1980) proposed an alternative approach that, although it takes a very different view of the way associability operates, is able to predict many of the same learned predictiveness effects as is the Mackintosh (1975) model. That said, the PearceHall model is less readily applied to the particular experiments dealt with in the current article (see the General Discussion), and, hence, the approach to associability take...