Abstract
Fear conditioning is a successful paradigm for studying neural substrates of emotional learning. In this thesis, two computational models of the underlying neural circuitry are presented. First, the effects of changes in neuronal membrane conductance on input processing are analyzed in a biologically realistic model. We show that changes in tonic inhibitory conductance increase the responsiveness of the network to inputs. Then, the model is analyzed from a functional perspective and predictions that follow from this proposition are discussed. Next, a systems level model is presented based on a recent high-level approach to conditioning. It is proposed that the interaction between fear and extinction neurons in the basal amygdala is a neural substrate of the switching between latent states, allowing the animal to infer causal structure. Important behavioral and physiological results are reproduced and predictions and questions that follow from the main hypothesis are considered.
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