ABSTRACT
Our long-term goal is to analyze how the mammalian brain codes, stores, and retrieves memories. The neural system that forms the core of our research is the cerebellar and brain stem circuits essential for the development and expression of one category of classical conditioning, the most basic form of associative learning. In attempting to identify and characterize the neural substrates of this elementary form of learning, we have found it useful to integrate neurobiological analyses with computational modeling. The resulting computational neural-network models are constrained by both the neurobiological properties of the brain substrates and by the emergent behavioral phenomena exhibited in animals, including humans.
