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Interval Timing and Memory Dynamics |
| Monday, May 31, 2004 |
| 1:30 PM–2:20 PM |
| Commonwealth |
| Area: EAB; Domain: Applied Research |
| CE Instructor: Michael C. Davison, Ph.D. |
| Chair: Michael C. Davison (University of Auckland) |
| JENNIFER J. HIGA (Honolulu Community College) |
 Dr. Jennifer Higa received her MS and PhD from Washington State University, with her research supervised by Frances McSweeney and John Hinson. After several years in postdoctoral and research faculty positions at Duke University with John Staddon, she joined the faculty in the Department of Psychology at Texas Christian University where she is an Assistant Professor. Her research has covered topics on behavioral contrast, stimulus control, transitive inference, and, more recently, the dynamics of interval timing. Pigeons and rats are her primary subjects, although she has recently begun to study timing in Betta splendens. Jennifer serves on the Board of Editors for the Journal of the Experimental Analysis of Behavior, Learning and Behavior, and the International Journal of Comparative Psychology, and was the Guest Editor for a special issue on timing for the journal Behavioral Processes. She is the recipient of a NRSA and Neurobehavioral Sciences Research Training Fellowship, as well as several teaching awards. |
| Abstract: Psychologists studying learning and memory have been increasingly interested in how animals - human and non-human - detect, integrate, and use temporal information. The importance of understanding interval timing is underscored by the fact that the time between events, responses, rewards, and punishers determine what is learned, what associations are made, and how learning progresses. Until recently, the majority of experimental and theoretical work has been aimed at understanding results obtained from procedures designed to measure steady state timing behavior. In contrast, relatively little is known about timing under changing conditions. I plan to review the results from temporal tracking and gap procedures and discuss the data in terms of a model for interval timing that is based on memory dynamics called the multiple time scale (MTS) model. |
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