Learning the temporal dynamics of behavior.

Abstract

This study presents a dynamic model of how animals learn to regulate their behavior under time-based reinforcement schedules. The model assumes a serial activation of behavioral states during the interreinforcement interval, an associative process linking the states with the operant response, and a rule mapping the activation of the states and their associative strength onto response rate or probability. The model fits data sets from fixed-interval schedules, the peak procedure, mixed fixed-interval schedules, and the bisection of temporal intervals. The major difficulties of the model came from experiments that suggest that under some conditions animals may time 2 intervals independently and simultaneously.

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   Vallesi, A., Shallice, T., Walsh, V. · 2006 · Cerebral Cortex
3. Representation and timing in theories of the dopamine system
   Daw, Nathaniel D., Courville, Aaron C., Touretzky, David S. · 2006 · Neural Computation
4. Stimulus representation and the timing of reward-prediction errors in models of the dopamine system
   Ludvig, Elliot A., Sutton, Richard S., Kehoe, E. James · 2008 · Neural Computation
5. Intentional and Unintentional Contributions to Nonspecific Preparation: Electrophysiological Evidence.
   Los, Sander A., Heslenfeld, Dirk J. · 2005 · Journal of Experimental Psychology: General

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