Proceedings of the Annual Meeting of the Cognitive Science Society

We propose a computational theory of hippocampalsystem function in mediating stimulus representation in associative learning. A connectionist model based on this theory is described here, in which the hippocampal system develc^s new and adaptive stimulus repesentations which are predictive, distributed, and compressed: other cortical and cerebellar modules are presumed to use these hippocampal representations to recode their o w n stimulus representations. This computational theory can been seen as an extension and/or refinement of several prior characterizations of hippocampal function. including theories of chunking, stimulus selection, cue-configuration, and contextual coding. The theory does not address temporal aspects of hippocampal function. SimulaticMis of the intact and lesioned model provide an account of data on diverse effects of hippocampal-region lesions, including simple discrimination learning, sensory preconditioning. reversal training, latent inhibition, contextual shifts, and ccMifigural learning. Potential implications of this theory for understanding human declarative m e m o y , temporal processing. and neural mechanisms are briefly discussed.