Performance factors in associative learning: assessment of the sometimes competing retrieval model

Abstract

Previous simulations revealed that the sometimes competing retrieval model (SOCR; Stout & Miller, Psychological Review, 114, 759-783, 2007), which assumes local error reduction, can explain many cue interaction phenomena that elude traditional associative theories based on total error reduction. Here, we applied SOCR to a new set of Pavlovian phenomena. Simulations used a single set of fixed parameters to simulate each basic effect (e.g., blocking) and, for specific experiments using different procedures, used fitted parameters discovered through hill climbing. In simulation 1, SOCR was successfully applied to basic acquisition, including the overtraining effect, which is context dependent. In simulation 2, we applied SOCR to basic extinction and renewal. SOCR anticipated these effects with both fixed parameters and best-fitting parameters, although the renewal effects were weaker than those observed in some experiments. In simulation 3a, feature-negative training was simulated, including the often observed transition from second-order conditioning to conditioned inhibition. In simulation 3b, SOCR predicted the observation that conditioned inhibition after feature-negative and differential conditioning depends on intertrial interval. In simulation 3c, SOCR successfully predicted failure of conditioned inhibition to extinguish with presentations of the inhibitor alone under most circumstances. In simulation 4, cue competition, including blocking (4a), recovery from relative validity (4b), and unblocking (4c), was simulated. In simulation 5, SOCR correctly predicted that inhibitors gain more behavioral control than do excitors when they are trained in compound. Simulation 6 demonstrated that SOCR explains the slower acquisition observed following CS-weak shock pairings.