Perspectives on Behavior Science最新文献

{"title":"Dynamic Interactions between Induction and Reinforcement in the Organization of Behavior.","authors":"Gabriela E López-Tolsa, Ricardo Pellón","doi":"10.1007/s40614-025-00453-5","DOIUrl":"10.1007/s40614-025-00453-5","url":null,"abstract":"<p><p>Behavior is dynamic because it results from the interactions between organisms and their environment. Reinforcement is the primary mechanism for explaining behavior, and it has evolved in various ways, allowing for the explanation of different aspects of behavior acquisition and maintenance. The adequacy of reinforcement in explaining behavior acquisition has mostly been tested on target behaviors. However, a broader understanding of behavior requires accounting not only for target behaviors but for all behaviors in a given situation. This article presents several experiments showcasing schedule-induced behaviors to analyze the variables that determine which behaviors are acquired and how they are organized. First, the effects of both physical and contingency-based constraints on the organization of behavior are examined. Second, the role of competition and collaboration between behaviors in determining their distribution is discussed. Third, a dual effect of reinforcers on behavioral patterns is proposed. It is concluded that behaviors interact with one another and with environmental stimuli, and behavioral patterns are continuously induced, updated, and reinforced. Data in this article highlight the need to focus on the moment-to-moment updating of behavioral patterns to fully understand behavioral dynamics.</p>","PeriodicalId":44993,"journal":{"name":"Perspectives on Behavior Science","volume":"48 2","pages":"315-339"},"PeriodicalIF":2.5,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12162401/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144303135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unpredictable Drug Access and its Relevance for Substance Use Disorders: A Critical Review.","authors":"William S Doyle, Kevin B Freeman, Sally L Huskinson","doi":"10.1007/s40614-025-00449-1","DOIUrl":"10.1007/s40614-025-00449-1","url":null,"abstract":"<p><p>Many factors contribute to drug use and the development of substance use disorders (SUDs). We and others have argued that individuals who misuse illicit drugs face circumstances in which their access to drugs is variable or unpredictable, particularly for those who are experiencing poverty. Herein, we make the case that such unpredictable drug access increases drug intake and choice, particularly when the time and effort required to obtain drugs is relatively large. If translated to real-world scenarios, unpredictable access could lead to increased severity of drug misuse, poorer treatment outcomes, persistence of drug seeking during periods of drug unavailability, drug taking despite negative consequences, and increased relapse rates, though additional research is surely needed. We describe how variable drug access can be evaluated in the laboratory, review prior research that has compared variable vs. fixed drug access, provide a summary of preclinical findings based on the literature reviewed, and end with implications for policy and treatment for individuals with SUDs.</p>","PeriodicalId":44993,"journal":{"name":"Perspectives on Behavior Science","volume":"48 2","pages":"367-387"},"PeriodicalIF":2.5,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12162454/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144303170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pigeon in a Box: <i>Columba livia</i> as Subject in Behavioral Research.","authors":"Eduardo J Fernandez, Kennon A Lattal","doi":"10.1007/s40614-025-00454-4","DOIUrl":"10.1007/s40614-025-00454-4","url":null,"abstract":"<p><p>Pigeons (<i>Columba livia</i>) have played a central role as subjects in the experimental analysis of behavior since the 1940s. This review considers the use of pigeons by humans across several domains: (1) their early use as a domesticated species and in early psychology laboratory experiments; (2) their rise, and recent decline relative to the use of other species, as a subject in behavior-analytic research published in the <i>Journal of the Experimental Analysis of Behavior</i>; and (3) their influence in research extending beyond behavior analysis. In addition, in the latter two sections, quantitative data are presented to document the frequency of use of laboratory pigeons and their impact outside of the lab, respectively. The review concludes with observations on both the past and future of the pigeon as a subject for the experimental analysis of behavior.</p>","PeriodicalId":44993,"journal":{"name":"Perspectives on Behavior Science","volume":"48 2","pages":"499-512"},"PeriodicalIF":2.5,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12162423/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144303164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Model of Consumer Demand with Anchoring and Price Effects on Purchase Behavior.","authors":"Javier Corredor, Daniel Jerez, Juan Sebastián Cely-Acosta","doi":"10.1007/s40614-025-00448-2","DOIUrl":"10.1007/s40614-025-00448-2","url":null,"abstract":"<p><p>This article presents a model of consumer behavior that incorporates anchoring and price effects in describing purchase demand. The model, called F-Cap, for Finite Consumption Anchored to Price, offers an alternative to traditional microeconomic models of demand. This model is based on recent findings in psychology and behavioral economics and connects concepts from behavioral and traditional economics to the language and findings of behavior analysis. In particular, the model incorporates the idea of maximum consumption and reinforcement power developed in the exponential and exponentiated models of demand, and adds the possibility to estimate reference prices using a new, simpler estimation method. These elements are organized in a model based on the sigmoid function. A function estimation algorithm is proposed. This algorithm linearizes the function and estimates the parameters using ordinary least squares regressions. A core feature of the algorithm is that it allows the identification of reference prices, which is not possible in prior models. First, this article illustrates how the parameters of F-Cap modify the maximum level of consumption, the anchor point, and the decrease in consumption after that point, as proposed in the model. Next, using simulated data, the article shows that the algorithm estimates these parameters correctly both in standard and in mixed models. Third, the article presents evidence that F-Cap describes the behavior of human subjects in the hypothetical purchase task with less unexplained variance than alternative demand models. This function correctly estimates the parameters associated with the good's contribution to utility, which in behavior analysis language is equivalent to reinforcing power. It also estimates the response to reference prices, which can be interpreted as behavior governed by rules in the tradition of behavior analysis. The F-Cap model overall helps connecting the findings of operant behavioral economics with the practices of mainstream economics.</p>","PeriodicalId":44993,"journal":{"name":"Perspectives on Behavior Science","volume":"48 2","pages":"389-422"},"PeriodicalIF":2.5,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12162403/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144303132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SQAB 2024: Quantitative Frontiers in the Analysis of Behavior.","authors":"Federico Sanabria, David J Cox, Rusty W Nall","doi":"10.1007/s40614-025-00457-1","DOIUrl":"https://doi.org/10.1007/s40614-025-00457-1","url":null,"abstract":"","PeriodicalId":44993,"journal":{"name":"Perspectives on Behavior Science","volume":"48 2","pages":"169-171"},"PeriodicalIF":2.5,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12162389/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144303168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explaining Performance on Interval and Ratio Schedules with a Molar View of Behavior.","authors":"William M Baum","doi":"10.1007/s40614-025-00455-3","DOIUrl":"10.1007/s40614-025-00455-3","url":null,"abstract":"<p><p>Some of the most basic phenomena in behavior analysis are the differences between performance on interval and ratio schedules. They have long been known and long puzzled over. Previous attempts to explain the performances have foundered either because they lacked a mechanism or because they adopted a molecular view of behavior based on discrete responses and contiguity. The molar view of behavior offers the sought-for explanation of differences in activity rate and the inability of ratio schedules to maintain activity at low food rates. The present account relies on induction by phylogenetically important events (PIE) according to power functions, molar feedback functions, and the framework of matching theory. A model described by a feedback system with all parameters the same predicts the relations between activity rate and PIE rate. The difference in overall activity rate arises from a difference in units of activities selected by ratio and interval schedules. The results demonstrate the greater explanatory power of the molar view of behavior.</p>","PeriodicalId":44993,"journal":{"name":"Perspectives on Behavior Science","volume":"48 2","pages":"173-202"},"PeriodicalIF":2.5,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12162439/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144303136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Exploration of Individual and Collective Reversal Learning in Rats.","authors":"Matthew Gildea, Cristina Santos, Carter D Bower, Adeline Hibshman, Takao Sasaki, Federico Sanabria","doi":"10.1007/s40614-025-00450-8","DOIUrl":"10.1007/s40614-025-00450-8","url":null,"abstract":"<p><p>Although associative learning research has been conducted for more than a century, little is known about learning processes when subjects are not alone, but in a group-a phenomenon termed <i>collective learning</i>. In collective learning situations, the behavior of conspecifics may serve as an associative cue for learning, like any other stimulus during individual learning. Two experiments investigated how individual versus collective training affects associative learning. Experiment 1 utilized a simultaneous discrimination task, whereas Experiment 2 implemented a serial go/no-go discrimination task. In both experiments, rats were trained either individually or collectively, exposing them to two distinct stimuli with only one of them signaling the availability of food reinforcement. Following acquisition training, all rats were tested both individually and collectively. Contingencies were then reversed: the previously nonreinforced stimulus now signaled the availability of food, and the previously reinforced stimulus now signaled the absence of food. Following reversal training, the rats were again tested individually and collectively. Results from both experiments suggest that the training condition (individual or collective) had little effect on learning the cue-outcome association. However, individual training negatively affected test performance in a collective context. These results suggest that collective training may have a facilitative effect on learning and points out key methodological considerations for more in-depth examination of this effect.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40614-025-00450-8.</p>","PeriodicalId":44993,"journal":{"name":"Perspectives on Behavior Science","volume":"48 2","pages":"269-288"},"PeriodicalIF":2.5,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12162449/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144303134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting the Next Response: Demonstrating the Utility of Integrating Artificial Intelligence-Based Reinforcement Learning with Behavior Science.","authors":"David J Cox, Carlos Santos","doi":"10.1007/s40614-025-00444-6","DOIUrl":"10.1007/s40614-025-00444-6","url":null,"abstract":"<p><p>The concepts of reinforcement and punishment arose in two disparate scientific domains of psychology and artificial intelligence (AI). Behavior scientists study how biological organisms <i>do</i> behave as a function of their environment, whereas AI focuses on how artificial agents <i>should</i> behave to maximize reward or minimize punishment. This article describes the broad characteristics of AI-based reinforcement learning (RL), how those differ from operant research, and how combining insights from each might advance research in both domains. To demonstrate this mutual utility, 12 artificial organisms (AOs) were built for six participants to predict the next response they emitted. Each AO used one of six combinations of feature sets informed by operant research, with or without punishing incorrect predictions. A 13^th predictive approach, termed \"human choice modeled by Q-learning,\" uses the mechanism of Q-learning to update context-response-outcome values following each response and to choose the next response. This approach achieved the highest average predictive accuracy of 95% (range 90%-99%). The next highest accuracy, averaging 89% (range: 85%-93%), required molecular and molar information and punishment contingencies. Predictions based only on molar or molecular information and with punishment contingencies averaged 71%-72% accuracy. Without punishment, prediction accuracy dropped to 47%-54%, regardless of the feature set. This work highlights how AI-based RL techniques, combined with operant and respondent domain knowledge, can enhance behavior scientists' ability to predict the behavior of organisms. These techniques also allow researchers to address theoretical questions about important topics such as multiscale models of behavior and the role of punishment in learning.</p>","PeriodicalId":44993,"journal":{"name":"Perspectives on Behavior Science","volume":"48 2","pages":"241-267"},"PeriodicalIF":2.5,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12162397/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144303165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Evolutionary Theory of Behavior Dynamics Predicts Delay Discounting.","authors":"Ryan Higginbotham, Jesse Dallery, J J McDowell","doi":"10.1007/s40614-025-00443-7","DOIUrl":"10.1007/s40614-025-00443-7","url":null,"abstract":"<p><p>Delay discounting is a behavioral phenomenon in which the subjective value of a reinforcer decreases as the reinforcer becomes more delayed. Two procedures are commonly used to assess how the value of a reinforcer changes as a function of delay: adjusting-delay and adjusting-amount. The evolutionary theory of behavior dynamics (ETBD) is a complex systems theory that uses an algorithm based on Darwinian principles of natural selection to animate artificial organisms. The behavior of artificial organisms animated by the theory are its predictions, and the theory has been shown to make accurate predictions about how living organisms behave in a variety of experimental arrangements. In the present article, we generated predictions with the ETBD for adjusting-delay and adjusting-amount procedures and evaluated whether these predictions align with live-organism delay discounting. The predictions were generated using modified procedures that could be conducted with continuous choice arrangements rather than discrete trials; however, despite these procedural differences, the ETBD's predictions were generally consistent with equations known to describe live-organism delay discounting well. This suggests that the ETBD might be used to generate other predictions that could expand our understanding of delay discounting.</p>","PeriodicalId":44993,"journal":{"name":"Perspectives on Behavior Science","volume":"48 2","pages":"423-446"},"PeriodicalIF":2.5,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12162430/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144303169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Review of Behavioral Economic Manipulations Affecting Drug versus Nondrug Choice in Rats.","authors":"David N Kearns","doi":"10.1007/s40614-025-00445-5","DOIUrl":"10.1007/s40614-025-00445-5","url":null,"abstract":"<p><p>Many recent studies have investigated rats' choice between drug and nondrug reinforcers to model variables influencing drug taking in humans. As research using this model accumulates, the complexity of factors affecting drug choice has become increasingly apparent. This review applies a behavioral economic perspective to research that has used this model. The focus is on experiments that have manipulated behavioral economic variables in studies of rats' choice between drugs like cocaine or heroin and nondrug reinforcers like saccharin or social interaction. Price effects, reinforcer interactions (i.e., as substitutes or complements), economy type, and income effects are described. Results of experiments testing the impact of these variables on rats' choice are presented and analyzed. Although rats' behavior in this model often conforms well with behavioral economic principles, there have also been instances where further explanation is required. By appreciating the behavioral economic context in which rats' choice between drug and nondrug reinforcers occurs, and by recognizing that both consequences and antecedents can play important roles in this behavior, our understanding of the complexity of factors involved in drug choice can be increased.</p>","PeriodicalId":44993,"journal":{"name":"Perspectives on Behavior Science","volume":"48 2","pages":"341-366"},"PeriodicalIF":2.5,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12162441/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144303133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}