Date of Award:

5-2013

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Psychology

Committee Chair(s)

Timothy A. Shahan

Committee

Timothy A. Shahan

Committee

Amy L. Odum

Committee

Gregory J. Madden

Abstract

Behavioral momentum theory states that the Pavlovian stimulus-reinforcer relation governs resistance to extinction. Thus, higher baseline reinforcer rates should produce more persistent behavior than lower baseline reinforcer rates. Though this positive relation generally is observed when behavior is maintained and subsequently disrupted in multiple schedules, the opposite relation is observed when single schedules are used. An alternative framework of extinction performance based on Bayesian change detection may be applied intuitively to describe resistance to extinction in single schedules of reinforcement. This approach asserts that detection of changes in reinforcer rates during extinction should be easier following training with rich reinforcer rates than lean reinforcer rates. Further, the Bayesian-based approach to understanding operant extinction implies that experience with changing reinforcer rates during baseline should further facilitate change detection and thereby hasten extinction. The current experiment tested this prediction. Pigeons pecked keys for food according to both static (i.e., reinforcer rates were held constant) and dynamic (i.e., reinforcer rates changed both between and within session) variable-interval schedules across successive baseline conditions. Following each baseline condition, extinction was assessed. Proportion-of-baseline response rates in extinction following static training generally were higher than these rates following dynamic training. These data provide tentative support for the Bayesian-based approach to understanding operant extinction. They do not, however, challenge the underlying, quantitative framework of behavioral momentum theory if change detection is considered an additional mechanism through which extinction occurs.

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