Associative accounts of recovery-from-extinction effects

McConnell, Bridget L., and Miller, Ralph R. (2014) Associative accounts of recovery-from-extinction effects. Learning and Motivation, 46. pp. 1-15.

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Recovery-from-extinction effects (e.g., spontaneous recovery, renewal, reinstatement, and facilitated reacquisition) have become the focus of much research in recent years. How-ever, despite a great deal of empirical data, there are few theoretical explanations for these effects. This paucity poses a severe limitation on our understanding of these behavioral effects, impedes advances in uncovering neural mechanisms of response recovery, and reduces our potential to prevent relapse after exposure therapy. Toward correcting this oversight, this review takes prominent models of associative learning that have been used in the past and continue to be used today to explain Pavlovian conditioning and extinction, and assesses how each model can be applied to account for recovery-from-extinction effects.The models include the Rescorla–Wagner (1972) model, Mackintosh’s (1975) attentional model, Pearce and Hall’s (1980) attentional model, Wagner’s (1981) SOP model, Pearce’s(1987) configural model, McLaren and Mackintosh’s (2002) elemental model, and Stout and Miller’s (2007) SOCR (comparator hypothesis) model. Each model is assessed for how well it explains or does not explain the various recovery-from-extinction phenomena. We offer some suggestions for how the models might be modified to account for these effects in those instances in which they initially fail.

Item ID: 31572
Item Type: Article (Research - C1)
ISSN: 1095-9122
Keywords: extinction, recovery from extinction, spontaneous recovery, renewal, reinstatement, associative theories
Date Deposited: 28 Mar 2014 01:45
FoR Codes: 17 PSYCHOLOGY AND COGNITIVE SCIENCES > 1799 Other Psychology and Cognitive Sciences > 179999 Psychology and Cognitive Sciences not elsewhere classified @ 100%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970117 Expanding Knowledge in Psychology and Cognitive Sciences @ 100%
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