Correlation Transfer in Striatal Network via Morphology Changes

Abstract: The activity of striatum is significantly modulated by dopamine, and long- term effects if an altered dopamine signalling can also lead to degeneration and regeneration of synapses. This thesis report investigates the signal transfer, especially correlation transfer, in the striatum. Simulations using a biophysically detailed MSN model and a simplified striatal network model are conducted to generate data to form hypotheses. At the single neuron level, synaptic pruning reduces the effects of the input. Compensation through regeneration of new synapses is much more effective than scaling up the existing synaptic strengths. At the network level, mutual inhibition between different neuron populations enhances the difference of their output firing rates when inputs are weakly correlated, and reduces the difference of output correlations when inputs are strongly correlated. In addition, the purely inhibitory striatal network can potentially either increase or decrease output correlations when changing the connection probability. The recurrent inhibition within a certain population plays a more important role in modulating the correlation transfer compared to mutual inhibition between populations. Finally, limitations of the models are discussed, and this motivates the introduction of connectivity preferences and neuron type diversity in future work.