Neural Network Approaches to Eyeblink Classical Conditioning

We have described our efforts to further the understanding of the neural substrates of rabbit eyeblink conditioning (in particular the cerebellum and hippocampus) through the use of neural networks. Over the years, the initial theoretical assumptions of the computational models have been maintained while more anatomically and physiologically detailed instantiations of these models have been developed. These neural networks have increased our understanding of how classical conditioning occurs in the cerebellum and hippocampus while making novel predictions which are guiding ongoing and future empirical studies. Neural networks result in simulations of various lesion conditions which offer subtle distinctions which may not be evident in a purely qualitative theory.