TY - JOUR T1 - Optimal Balance of the Striatal Medium Spiny Neuron Network A1 - Ponzi, Adam A1 - Wickens, Jeffery R. Y1 - 2013/04/11 N2 - Author Summary The striatum forms the main input to the Basal Ganglia (BG), a subcortical structure involved in reinforcement learning and action selection. It is composed of medium spiny neurons (MSNs) which inhibit each other through a network of collaterals, receive excitatory projections from the cerebral cortex, and are the only cells which project outside the striatum. Because of its inhibitory structure, the MSN network is often thought to act selectively, transmitting the most active cortical inputs downstream in the BG while suppressing others. However, studies show that local MSN network connections are too sparse and weak to perform global selection and their function remains puzzling. Here we investigate a different hypothesis. Rather than generating a static stimulus dependent activity pattern, we suggest the MSN network is optimized to generate stimulus dependent dynamical activity patterns for long time periods after variations in cortical excitation. We demonstrate, using simulations, that the MSN network has special characteristics. It is neither too stable to respond in a dynamically complex temporally extended way to cortical variations, nor is it too unstable to respond in a consistent repeatable way. We discuss how these properties may be utilized in temporally delayed reinforcement learning tasks strongly recruiting the striatum. JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 9 IS - 4 UR - https://doi.org/10.1371/journal.pcbi.1002954 SP - e1002954 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1002954 ER -