Association for Behavior Analysis International

The Association for Behavior Analysis International® (ABAI) is a nonprofit membership organization with the mission to contribute to the well-being of society by developing, enhancing, and supporting the growth and vitality of the science of behavior analysis through research, education, and practice.

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50th Annual Convention; Philadelphia, PA; 2024

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Invited Symposium #203A
CE Offered: BACB
The Matching Law: Past, Present, and Future
Sunday, May 26, 2024
4:00 PM–5:50 PM
Convention Center, 300 Level, Ballroom B
Area: SCI; Domain: Theory
Chair: Jonathan W. Pinkston (University of Kansas)
Discussant: Jack J McDowell (Emory University)
CE Instructor: Jonathan W. Pinkston, Ph.D.
Abstract:

The Matching Law was developed in the early days of behavior analytic research to describe the allocation of behavior across response alternatives as a function of relative reinforcement available from those alternatives. Today, the Matching Law and other quantitative accounts of behavior have surpassed their beginnings as mathematical descriptions of behavior and serve as important conceptual tools that build bridges to other disciplines and solve significant clinical and social problems. In recognition of ABAI’s 50th year, this symposium highlights the history, conceptual advances, and future of the Matching Law with respect to research, application, and the development of public policy.

Instruction Level: Intermediate
Target Audience:

Researchers, BACBAs, practitioners, and graduate students

Learning Objectives: At the conclusion of the presentation, participants will be able to: (1) Define the Matching Law; (2) Describe how the Matching Law can be used to predict choice; (3) Describe applications of the Matching Law to understand complex behavior; (4) Describe how the Matching Law can be used to guide the development of novel therapeutics
 
The Matching Law and Neuroscience
PAUL L. SOTO (Louisiana State University)
Abstract: Since the publication of Herrnstein’s 1961 paper on the relation between relative and absolute rates of responding and rates of reinforcement, there have been many studies extending the matching law to a variety of domains, many studies refining the matching law, and many studies focused on explaining matching as the outcome of other behavioral processes. The precision and robustness of the phenomenon of matching has made it particularly conducive for the investigation of biological variables, primarily variables of the central nervous system, that mediate and moderate matching. Some of the work on the matching law and neuroscience will be highlighted for this symposium on the matching law.
Dr. Soto completed a Ph.D. at Emory University and postdoctoral training at the National Institute on Drug Abuse and the Johns Hopkins University School of Medicine. Dr. Soto is an assistant professor in the Department of Psychology at Louisiana State University (LSU). Dr. Soto previously held positions in the School of Medicine at Johns Hopkins University and at Texas Tech University. Dr. Soto’s research interests are in (1) the use of laboratory animal models of psychiatric diseases and symptoms for the evaluation of potential therapeutic approaches, (2) the use of drugs and genetically engineered animals to identify the neurobiological contributors to basic and complex behavioral processes, and (3) the investigation of short- and long-term effects of exposure to psychiatric medications. Recently, Dr. Soto has begun advocating for the use of single-case experimental designs in areas outside of behavior analysis, such as behavioral neuroscience, because of the scientific and ethical benefits provided by these designs.
 
Applying the Matching Law to Quantify the Influence of Socially Mediated Reinforcement on Behavioral Disorders & Differences
SAMUEL L MORRIS (Louisiana State University)
Abstract: Quantitative models of behavior allow for precise descriptions of behavior-environment functional relations and facilitate improvement in our ability to predict and influence behavior. These characteristics are evident in basic research on the matching law and may be especially beneficial in its application to problems of societal importance. This talk will explore how the matching law can quantify the influence of socially mediated reinforcement across diverse contexts of applied significance, including assessment and intervention for (a) conversational behaviors, (b) social time allocation, and (c) disruptive or challenging behaviors. Previous research, ongoing projects, and important future directions related to each area of application will be discussed. The ultimate aim of this talk is to highlight how continued application of the matching law can facilitate progress in research and clinical practice.
Sam Morris obtained his Ph.D. in Psychology with a specialization in Behavior Analysis at the University of Florida under the mentorship of Dr. Tim Vollmer. He was an Assistant Professor and the Applied Behavior Analysis Program Coordinator at Southeastern Louisiana University before beginning his current position as an Assistant Professor in the Department of Psychology at Louisiana State University in 2022. Dr. Morris' laboratory utilizes experimental manipulations of the environment to investigate causal influences on choice and inform methods of facilitating behavior change. The individualization of reinforcement procedures and relative efficacy of different types and parameters of reinforcement have proven uniting themes underlying his research to date. Dr. Morris teaches a variety of behavior-analytic courses at the undergraduate and graduate level, serves on the editorial board for the Journal of Applied Behavior Analysis, and frequently serves as a reviewer for top behavior-analytic journals.
 
Dynamics of Behavioral Persistence in Self-Injury
JOHN FALLIGANT (Kennedy Krieger Institute/Johns Hopkins University School of Medicine)
Abstract: In the majority of cases, self-injurious behavior (SIB) is maintained by social positive or social negative reinforcement. However, in some cases SIB persists in the absence of socially mediated consequences. This latter functional class of behavior is said to be automatically maintained because the response dynamics imply the behavior produces its own reinforcement. Researchers have long noted distinct patterns of automatically maintained SIB within the functional analysis and other assessments. One pattern is characterized by elevated levels of SIB in environments with minimal stimulation, and low levels of SIB in highly enriched environments. This differentiated pattern is referred to as Subtype 1 SIB. Another pattern is characterized by invariant SIB that occurs across environmental conditions irrespective of the degree of stimulation present. This intransient and undifferentiated pattern is referred to as Subtype 2 SIB. Notably, Subtype 1 SIB is far more responsive to treatment using reinforcement alone, rarely requires protective equipment and restraint, and presents with less serious injuries at the time of intake relative to Subtype 2 SIB. The contrasting dynamics of Subtypes 1 and 2 with respect to how SIB is disrupted by alternative reinforcement has led to speculation about possible differences in the type or magnitude of sensory consequences that SIB produces across subtypes. In this presentation I will summarize some evidence in support of this hypothesis, and discuss recent developments, informed by matching theory, that may shed additional light on the typologies of automatically maintained SIB.
Dr. Falligant is a clinical psychologist and Board Certified Behavior Analyst (BCBA-D). He received his Ph.D. from Auburn University, and is an Assistant Professor in the Department of Psychiatry and Behavioral Sciences at the Johns Hopkins University School of Medicine and a Senior Behavior Analyst in the Neurobehavioral Unit at the Kennedy Krieger Institute. The Neurobehavioral Programs at the Kennedy Krieger Institute serve individuals with intellectual and developmental disabilities (IDD) who suffer from severe behavioral dysfunction, including self-injury. Dr. Falligant’s work coalesces around the assessment and treatment of challenging behavior in individuals with IDD. His research focuses on the analysis of transdiagnostic neurobehavioral variables underlying behavioral dysfunction, persistence and relapse, and the identification of functional behavioral phenotypes pertinent to treatment-resistant behavior. A unifying theme across these areas is the fine-grained analysis of behavioral events, including the microstructural analysis of behavior and its dynamics.
 
The Scalability of Quantitative Models of Choice: Implications for Public Policy, Big Data, and Beyond
DEREK D. REED (Institutes for Behavior Resources, Inc.)
Abstract: Matching Theory is the foundational concept for most modern quantitative models of choice in behavior analysis. In particular, Matching Theory is responsible for two leading behavioral economic models that have robust literature in taking behavior analysis to scale: delay discounting and operant demand. Despite the proliferation of behavioral economic models to large-scale issues of social importance, the direct translation of the Matching Law to these issues remains relatively scant. This presentation will provide an overview of the Matching Theory underpinnings of modern behavioral economics and briefly showcase the scalability afforded by these studies. The bulk of the presentation will focus on the translational promise of Matching Theory, specifically. A discussion of previous translations outside the operant lab will serve as models for continued application. The presentation will conclude with specific areas in which Matching Theory could have translational success.
Dr. Derek Reed is Director of Applied Behavioral Sciences at Institutes for Behavior Resources, Inc., with over 20 years of experience in behavior analysis and behavioral economics. He has served as Associate Editor for the Journal of the Experimental Analysis of Behavior, Journal of Applied Behavior Analysis, Behavior Analysis in Practice, and The Psychological Record. Dr. Reed has over 180 publications, coauthored three edited books and one textbook, and has won numerous awards for his scholarship, such as the American Psychological Association Division 25 B. F. Skinner Foundation New Applied Researcher Award, the Society for the Experimental Analysis of Behavior Don Hake Award for Translational Research, and the Federation of Associations in Behavioral and Brain Sciences Early Career Award. He served as Coordinator of the Association for Behavior Analysis International’s Science Board and on the Board of Directors for the Society for the Quantitative Analyses of Behavior, of which he was previously Executive Director. Dr. Reed’s research focuses on the application of behavioral economic principles to improve issues of societal concern.
 

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