The several roles of stimuli in token reinforcement

Common Practices used to Establish and Implement Token Economies in Clinical and Instructional Settings: A Survey of BACB Certificants

Token economies are among the most widely used procedures in behavior analysis and research on token economies has spanned over 80 years. Several textbooks have outlined the essential components of token economies and suggested how they can be trained and implemented in practice. However, procedures evaluated in applied research can vary from how those procedures are implemented in clinical practice. It is conceivable that the way in which token economies are implemented in clinical settings does not resemble the procedures described in research and behavior analytic textbooks. We surveyed 255 board certified behavior analysts and board certified assistant behavior analysts about their commonly used practices when training and implementing token economies with individuals with autism and other neurodevelopmental disorders. Results suggest that certain aspects of token economies in practice often bear only superficial resemblance to how they are described in textbooks.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40617-023-00800-5.

Cooperative responding in rats: II. Performance on fixed-ratio schedules of mutual reinforcement

Coordinated responses of 5 dyads of rats were investigated under fixed-ratio (FR) schedules of mutual water reinforcement. Coordinated responding was defined as 2 consecutive lever-presses, 1 from each of 2 rats, occurring <.5 s apart. In the FR schedules, each coordinated episode was defined as 1 response in the FR sequence. The size of FR schedules was parametrically manipulated assuming the values of FR 1, 6, 12, 18, 24, 30, 50, and 9, in this order. Each FR remained in effect until responding reached stability. Under all conditions, pairs of rats received access to water simultaneously (mutual reinforcement). Rates and proportions of coordinated responding showed a bitonic inverted U-shaped function of ratio size. Postreinforcement pauses increased systematically as the interreinforcement interval increased. Local rates and proportions increased as a function of response location within ratios. Results of a control condition with relaxed temporal constraints for mutual reinforcement showed decreases in rates and proportion of coordinated responses, suggesting that the coordinated responses were controlled by the mutual reinforcement contingencies. The present experiment showed that coordinated responding is quantitatively affected by 3 properties of FR schedules: response requirement, reinforcement rates, and proximity to reinforcement.

Token reinforcement: Translational research and application

The present paper provides an integrative review of research on token reinforcement systems, organized in relation to basic behavioral functions and economic variables. This type of functional taxonomy provides a useful way to organize the literature, bringing order to a wide range of findings across species and settings, and revealing gaps in the research and areas especially ripe for analysis and application. Unlike standard translational research, based on a unidirectional model in which the analysis moves from laboratory to the applied realm, work in the area of token systems is best served by a bidirectional interplay between laboratory and applied research, where applied questions inspire research on basic mechanisms. When based on and contributing to an analysis, applied research on token economies can be on the leading edge of theoretical advances, helping set the scientific research agenda.

Substitution effects in a generalized token economy with pigeons

Pigeons made repeated choices between earning and exchanging reinforcer-specific tokens (green tokens exchangeable for food, red tokens exchangeable for water) and reinforcer-general tokens (white tokens exchangeable for food or water) in a closed token economy. Food and green food tokens could be earned on one panel; water and red water tokens could be earned on a second panel; white generalized tokens could be earned on either panel. Responses on one key produced tokens according to a fixed-ratio schedule, whereas responses on a second key produced exchange periods, during which all previously earned tokens could be exchanged for the appropriate commodity. Most conditions were conducted in a closed economy, and pigeons distributed their token allocation in ways that permitted food and water consumption. When the price of all tokens was equal and low, most pigeons preferred the generalized tokens. When token-production prices were manipulated, pigeons reduced production of the tokens that increased in price while increasing production of the generalized tokens that remained at a fixed price. The latter is consistent with a substitution effect: Generalized tokens increased and were exchanged for the more expensive reinforcer. When food and water were made freely available outside the session, token production and exchange was sharply reduced but was not eliminated, even in conditions when it no longer produced tokens. The results join with other recent data in showing sustained generalized functions of token reinforcers, and demonstrate the utility of token-economic methods for assessing demand for and substitution among multiple commodities in a laboratory context.

Pigeons' demand and preference for specific and generalized conditioned reinforcers in a token economy

Pigeons' demand and preference for specific and generalized tokens was examined in a token economy. Pigeons could produce and exchange different colored tokens for food, for water, or for food or water. Token production was measured across three phases, which examined: (1) across-session price increases (typical demand curve method); (2) within-session price increases (progressive-ratio, PR, schedule); and (3) concurrent pairwise choices between the token types. Exponential demand curves were fitted to the response data and accounted for over 90% total variance. Demand curve parameter values, Pmax , Omax and α showed that demand was ordered in the following way: food tokens, generalized tokens, water tokens, both in Phase 1 and in Phase 3. This suggests that the preferences were predictable on the basis of elasticity and response output from the demand analysis. Pmax and Omax values failed to consistently predict breakpoints and peak response rates in the PR schedules in Phase 2, however, suggesting limits on a unitary conception of reinforcer efficacy. The patterns of generalized token production and exchange in Phase 3 suggest that the generalized tokens served as substitutes for the specific food and water tokens. Taken together, the present findings demonstrate the utility of behavioral economic concepts in the analysis of generalized reinforcement.