title: A computational model of the temporal dynamics of plasticity in procedural learning: sensitivity to feedback timing.
abstract: The evidence is now good that different memory systems mediate the learning of different types of category structures. In particular, declarative memory dominates rule-based (RB) category learning and procedural memory dominates information-integration (II) category learning. For example, several studies have reported that feedback timing is critical for II category learning, but not for RB category learning-results that have broad support within the memory systems literature. Specifically, II category learning has been shown to be best with feedback delays of 500 ms compared to delays of 0 and 1000 ms, and highly impaired with delays of 2.5 s or longer. In contrast, RB learning is unaffected by any feedback delay up to 10 s. We propose a neurobiologically detailed theory of procedural learning that is sensitive to different feedback delays. The theory assumes that procedural learning is mediated by plasticity at cortical-striatal synapses that are modified by dopamine-mediated reinforcement learning. The model captures the time-course of the biochemical events in the striatum that cause synaptic plasticity, and thereby accounts for the empirical effects of various feedback delays on II category learning.
authors: Department of Psychological and Brain Sciences, University of California Santa Barbara Santa Barbara, CA, USA.
authors: Vivian V
authors: VV
authors: Valentin
authors: Department of Psychology, University of Texas Austin Austin, TX, USA.
authors: W Todd
authors: WT
authors: Maddox
authors: Department of Psychological and Brain Sciences, University of California Santa Barbara Santa Barbara, CA, USA.
authors: F Gregory
authors: FG
authors: Ashby
keywords: category learning; computational modeling; dopamine; feedback timing; procedural learning; striatum; synaptic plasticity