title: Normalization between stimulus elements in a model of Pavlovian conditioning: showjumping on an elemental horse.
abstract: Harris and Livesey. Learning & Behavior, 38, 1-26, (2010) described an elemental model of associative learning that implements a simple learning rule that produces results equivalent to those proposed by Rescorla and Wagner (1972), and additionally modifies in "real time" the strength of the associative connections between elements. The novel feature of this model is that stimulus elements interact by suppressively normalizing one another's activation. Because of the normalization process, element activity is a nonlinear function of sensory input strength, and the shape of the function changes depending on the number and saliences of all stimuli that are present. The model can solve a range of complex discriminations and account for related empirical findings that have been taken as evidence for configural learning processes. Here we evaluate the model's performance against the host of conditioning phenomena that are outlined in the companion article, and we present a freely available computer program for use by other researchers to simulate the model's behavior in a variety of conditioning paradigms.
authors.affiliation: University of Sydney, Sydney, New South Wales, Australia.
authors.forename: Anna
authors.initials: A
authors.lastname: Thorwart
authors.forename: Evan J
authors.initials: EJ
authors.lastname: Livesey
authors.forename: Justin A
authors.initials: JA
authors.lastname: Harris
mesh_terms: D000818:Animals; D001245:Association Learning; D001288:Attention; D003198:Computer Simulation / Q000706:statistics & numerical data; D003214:Conditioning, Classical; D008960:Models, Psychological; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D013997:Time Factors