Learning and Reversal in the Sub-cortical Limbic System: A Computational Model

The basal ganglia are a group of nuclei that signal to and from the cerebral cortex. They play an important role in cognition and in the initiation and regulation of normal motor activity. A range of characteristic motor diseases such as Parkinson’s and Huntington’s have been associated with the degeneration and lesioning of the dopaminergic neurons that target these regions. The study of dopaminergic activity has numerous benefits from understanding how and what effects neurodegenerative diseases have on behavior to determining how the brain responds and adapts to rewards. The study is also useful in understanding what motivates agents to select actions and do the things that they do. The striatum is a major input structure of the basal ganglia and is a target structure of dopaminergic neurons which originate from the mid brain. These dopaminergic neurons release dopamine which is known to exert modulatory influences on the striatal projections. Action selection and control are involved in the dorsal regions of the striatum while the dopaminergic projections to the ventral striatum are involved in reward based learning and motivation. There are many computational models of the dorsolateral striatum and the basal ganglia nuclei which have been proposed as neural substrates for prediction, control and action selection. However, there are relatively few models which aim to describe the role of the ventral striatal nucleus accumbens and its core and shell sub divisions in motivation and reward related learning. This thesis presents a systems level computational model of the sub-cortical nuclei of the limbic system which focusses in particular, on the nucleus accumbens shell and core circuitry. It is proposed that the nucleus accumbens core plays a role in enabling reward driven motor behaviour by acquiring stimulus-response associations which are used to invigorate responding. The nucleus accumbens shell mediates the facilitation of highly rewarding behaviours as well as behavioural switching.