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.


47th Annual Convention; Online; 2021

All times listed are Eastern time (GMT-4 at the time of the convention in May).

Event Details

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Symposium #116
CE Offered: BACB
Theories, Models, and Their Uses in Behavior Science
Saturday, May 29, 2021
3:00 PM–4:50 PM
Area: EAB/BPN; Domain: Theory
Chair: M. Christopher Newland (Auburn University)
Discussant: Lewis A. Bizo (University of Technology Sydney)
CE Instructor: M. Christopher Newland, Ph.D.

Orderly, precise data invite models, such as Mathematical Principles of Reinforcement (MPR). From first principles, MPR derives equations describing how biophysical properties of responding, the retroactive actions of reinforcement contingencies, and reinforcer quality can predict response rate under many schedules. The memory-as-discrimination model places forgetting in a framework of temporal generalization and makes surprising predictions about “forgetting” at short intervals. Presenters will examine theory and its utility in understanding otherwise incomprehensible results. A tutorial on MPR will be provided by its originator, Peter Killeen. Federico Sanabria will describe an extension that incorporates probabilistic, response-by-response modeling. Chris Newland will show that MPR’s parameters are independent and reveal important information about such interventions as chemical exposure or genetic differences. Forgetting and attending are shown by Dalisa Kendricks to comprise separable processes, including temporal generalization and choice. Finally, Lewis Bizo will discuss the how and why of the insights that quantitative models provide into hidden structures and forces on behavior in ways that purely descriptive and inductive methodologies cannot, and their realized and potential applications. Together, these presentations will show the importance of theory in understanding behavior and how it responds to powerful interventions.

Instruction Level: Intermediate
Keyword(s): MPR, Quantitative Models, Remembering, Sustained Attention
Target Audience:

The target audiences are basic researchers interested in quantitative theories of behavior and all investigators in how these theories can be extended to understand disparate phenomena. In goth cases, the target audience is advanced.

Learning Objectives: At the conclusion of the presentation, participants will be able to: 1. Explain why a principled approach to theory construction is valuable. 2. Describe the original, molor, implementation of MPR and its extension to a response-by-response analysis. 3. Understand how MPR is helpful in other applications. 4. Explain a behavioral definition of attending, its independence from memory, and how the discrimination model of remembering is supported.
Tutorial Introduction to the Mathematical Principles of Reinforcement
PETER R. KILLEEN (Arizona State University)
Abstract: Behavior on schedules of reinforcement is some of the most orderly in the field of psychology as a whole. According to the first modern scientist Galileo, the ideal language for such replicable data is mathematics. Accordingly, I generated a mathematical model of reinforcement schedules ages ago. For transparency, it is predicated on three principles, or axioms stated general enough to be uncontroversial (e.g., reinforcers direct behavior). I note their relationship to Baum’s multimodal model, and Catania’s reflex reserve model. I generated mathematical models for each principle, and for their interaction. Unlike the principles, the models were specific enough to be tested, and expected to eventually fail and be replaced by better models, or models that extended them into new domains. I discuss one or two of the models of basic schedules to give a sense of the machinery; and note how the theory has been extended into those new domains, including adjunctive behaviors, contrast, and behavioral momentum. Finally, I introduce the model for progressive ratio schedules, which will be used by subsequent panelists. In this presentation the subjects were animals; the procedures were exposure to various schedules of reinforcement; the data showed general conformity to the principles and models.

Can Mathematical Principles of Reinforcement Inform Us About Chemical and Genetic Effects on Behavior?

M. CHRISTOPHER NEWLAND (Auburn University)

Drugs and environmental contaminants can have long-lasting, sometimes irreversible, behavioral effects and mouse strains are well-known for their behavior profiles. Characterizing these in ways that are behaviorally meaningful, that is, linking them to behavioral mechanisms and neural corelates often proves challenging. Mathematical Principles of Reinforcement (MPR), a theoretical framework built from first principles, claims that three independent parameters are uniquely linked to specific behavioral mechanisms. To be useful, these parameters should reveal specific and independent information about chemical interventions or genetic differences in behavioral profiles. Here, I summarize how MPR has been used to characterize the impact of cocaine, d-amphetamine, and methylmercury during adolescence in rodent models as well as how these parameters differ across three mouse strains. Adolescent exposure to methylmercury is related to an increased in the saturation rate in two studies and minimum response time in one. Adolescent cocaine exposure increased saturation rate and steepened discounting in the same animals. In a comparison of different mouse strains, higher saturation rates in BALB/c mice, as compared with C57Bl/6 mice, as well as higher discounting rates were observed. The MPR parameters are sensitive to a variety of interventions and unmask the determinants of differing behavioral profiles.


Theory, Models, and Scientific Progress: The Case of Mathematical Principles of Reinforcement 2.0

FEDERICO SANABRIA (Arizona State University)

Scientific progress is an upward spiral that cycles between problem identification, hypothesis formulation, model specification, and empirical evaluation. This process is partially self-contained (empirical failures lead to new problems, and so on) and partially feeds from external factors (new empirical and analytical techniques). An example of upward-spiral progress in behavior analysis is the Mathematical Principles of Reinforcement (MPR): It originates with the problem of schedule control over aggregated performance, it formulates principles that govern such performance, and it specifies the mathematical properties of those principles, motivating empirical research on those properties. Self-contained progress is reflected on refinements in model specification. Developments in the microstructure of motivated behavior constitute external factors that may contribute to the evolution of MPR. These developments suggest new problems (e.g., how does the organization of behavior in bouts emerge?) and new data (e.g., response-by-response changes in inter-response times) that may be incorporated into the scope and models of MPR 2.0. For MPR 2.0 to address these new problems and leverage these new data, it must specify not only the central tendency of model parameters but also their distribution and sequential dependency. Examples and simulations of such specifications are presented and contrasted against extant behavioral data.


Distracted Recall and Choosing to Ignore: Differentiable Determinants of Forgetting and Sustained Attending

DALISA KENDRICKS (Auburn University), M. Christopher Newland (Auburn University)

White’s quantitative model of remembering holds that delay-related errors are due to both forgetting and temporal generalization deficits, and that this becomes noticeable when training is conducted with delays longer than 0s. Accuracy is theorized to peak close to the trained delay and decrease at longer and, remarkably, shorter delays. The construct of sustained attention may also emerge from processes like forgetting, generalization, and choice. Can these processes be isolated? In rodent (mouse and rat) models, both attending and forgetting were assessed simultaneously in a single preparation. Forgetting (errors after long delays) and temporal generalization (errors after short delays) were uniquely affected by changing testing and training delays, interventions that did not affect detection at a 0 sec delay (termed sustained attention). Attending was uniquely affected by concurrently available reinforcers and changing the duration of the stimulus to be detected but not by adding visual distractors. What is referred to as sustained attention may emerge from behavioral processes of generalization and choice and can be distinguished from forgetting and temporal generalization. Understanding the determinants of these phenomena is important in interpreting drug and neurotoxicant effects.




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