We describe a principle of reinforcement that draws upon experimental analyses of both behavior and the neurosciences. Some of the implications of this principle for the interpretation of behavior are explored using computer simulations of adaptive neural networks. The simulations indicate that a single reinforcement principle, implemented in a biologically plausible neural network, is competent to produce as its cumulative product networks that can mediate a substantial number of the phenomena generated by respondent and operant contingencies. These include acquisition, extinction, reacquisition, conditioned reinforcement, and stimulus-control phenomena such as blocking and stimulus discrimination. The characteristics of the environment-behavior relations selected by the action of reinforcement on the connectivity of the network are consistent with behavior-analytic formulations: Operants are not elicited but, instead, the network permits them to be guided by the environment. Moreover, the guidance of behavior is context dependent, with the pathways activated by a stimulus determined in part by what other stimuli are acting on the network at that moment. In keeping with a selectionist approach to complexity, the cumulative effects of relatively simple reinforcement processes give promise of simulating the complex behavior of living organisms when acting upon adaptive neural networks.

The central focus of this essay is whether the effect of reinforcement is best viewed as the strengthenng of responding or the strengthening of the environmental control of responding. We make the argument that adherence to Skinner's goal of achieving a moment-to-moment analysis of behavior compels acceptance of the latter view. Moreover, a thoroughgoing commitment to a moment-to-moment analysis undermines the fundamental distinction between the conditioning process instantiated by operant and respondent contingencies while buttressing the crucially important differences in their cumulative outcomes. Computer simulations informed by experimental analyses of behavior and neuroscience are used to illustrate these points.

Transitive inference (TI) has been studied in humans and several animals such as rats, pigeons and fishes. Using different methods for training premises it has been shown that a non-trained relation between stimuli can be stablished, so that if A > B > C > D > E, then B > D. Despite the widely reported cases of TI, the specific mechanisms underlying this phenomenon remain under discussion. In the present experiment pigeons were trained in a TI procedure with four premises. After being exposed to all premises, the pigeons showed a consistent preference for B over D during the test. After overtraining C+D- alone, B was still preferred over D. However, the expected pattern of training performance (referred to as serial position effect) was distorted, whereas TI remained unaltered. The results are discussed regarding value transfer and reinforcement contingencies as possible mechanisms. We conclude that reinforcement contingencies can affect training performance without altering TI.

Revaluation refers to phenomena in which the strength of an operant is altered by reinforcer-related manipulations that take place outside the conditioning situation in which the operant was selected. As an example, if lever pressing is acquired using food as a reinforcer and food is later paired with an aversive stimulus, the frequency of lever pressing decreases when subsequently tested. Associationist psychology infers from such findings that conditioning produces a response-outcome (i.e., reinforcer) association and that the operant decreased in strength because pairing the reinforcer with the aversive stimulus changed the value of the outcome. Here, we present an approach to the interpretation of these and related findings that employs neural network simulations grounded in the experimental analysis of behavior and neuroscience. In so doing, we address some general issues regarding the relations among behavior analysis, neuroscience, and associationism.

No abstract