ReviewBridging the interval: Theory and neurobiology of trace conditioning
Introduction
A key feature of associative learning is its sensitivity to the temporal arrangement of stimuli. In Pavlovian conditioning procedures, research has focused on the temporal relation between the conditioned stimulus (CS) and the unconditioned stimulus (US). Pavlov (1927) noted that as the trace interval, the interval between CS offset and US onset, was increased, responding during the CS decreased. This pattern of results is a textbook finding that has been replicated across many different Pavlovian preparations (e.g., Ellison, 1964, Kamin, 1961). The study of trace conditioning has had a major impact on theories of learning and timing, and has revealed novel neurobiological mechanisms of learning and memory. In this review, we focus primarily on trace fear conditioning, where a subtle change in the interval between the CS and US results in the recruitment of distinct neurobiological circuitry.
Trace conditioning has been studied with multiple behavioral approaches that reveal common and unique characteristics. At a behavioral level, trace conditioning procedures generally slow the rate of acquisition of a behavioral response and lead to less behavior during subsequent tests, relative to delay conditioning procedures. As with delay procedures, however, trace conditioning often results in the emergence of response patterns consistent with precise timing of the CSāUS relation (e.g., Balsam, 1984) and this timing is stimulus and contingency specific (e.g., Kehoe et al., 2009, Woodruff-Pak and Disterhoft, 2008). There is a growing literature from neurobiological studies of trace fear conditioning suggesting that the neural, molecular, and biochemical mechanisms that support long-term learning and anxiety may differ in trace and delay conditioning (Raybuck and Lattal, 2011).
Section snippets
Theoretical mechanisms of trace fear conditioning
In trace fear conditioning, the CS and US are temporally discontiguous. Thus, CS offset and US onset are separated by a stimulus-free interval. During subsequent testing, responding is weaker compared to that of delay conditioned subjects, where the CS and US co-terminate, thus overlapping in presentation. This is a robust behavioral difference that occurs after relatively few or many trials (Ellison, 1964, Kamin, 1961, Pavlov, 1927). The difference between trace and delay conditioning has led
Neurobiology of trace fear conditioning
Just as there are multiple theoretical accounts for the learning that underlies trace fear conditioning, there are multiple neurobiological circuits that support it. Much of what is known about the circuits of fear conditioning comes from the study of delay fear conditioning (Fanselow and Gale, 2003). While trace fear conditioning has been influential in theoretical approaches to learning, remarkably little is known about its neurobiology, though a great deal is known about the neurobiology of
Bridging the gap between theoretical and neurobiological approaches
The complicated circuitry that underlies trace fear conditioning provides some insight into how and where different theoretical mechanisms may occur. For example, the idea that a stimulus trace must be maintained in working memory until the US occurs is consistent with literature on hippocampal and prefrontal cortical involvement in working memory and attention. If the function of these structures is impaired, the ability to maintain that stimulus trace in working memory is lost, resulting in
Applications and conclusion
The simple insertion of a temporal gap between a CS and a US alters the theoretical and neurobiological systems that underlie learning. The study of trace fear conditioning has revealed novel insights about the ways in which animals encode temporal information, as well as the ways in which these signals are processed in the brain. A clear conclusion from behavioral work is that differences in performance as a function of the time of CS and US delivery may reflect any of several mechanisms.
Acknowledgements
Preparation of this article was supported by grants DA007262 and DA031537 to JDR and by grants MH077111, DA025922, and DA018165 to KML.
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