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Int J Neural Syst. 2006 Apr;16(2):111-24.

The role of the basal ganglia in exploration in a neural model based on reinforcement learning.

Author information

Program in Neuroscience, Stanford University School of Medicine, California 94305, USA.

Erratum in

  • Int J Neural Syst. 2006 Jun;16(3):227.


We present a computational model of basal ganglia as a key player in exploratory behavior. The model describes exploration of a virtual rat in a simulated water pool experiment. The virtual rat is trained using a reward-based or reinforcement learning paradigm which requires units with stochastic behavior for exploration of the system's state space. We model the Subthalamic Nucleus-Globus Pallidus externa (STN-GPe) segment of the basal ganglia as a pair of neuronal layers with oscillatory dynamics, exhibiting a variety of dynamic regimes such as chaos, traveling waves and clustering. Invoking the property of chaotic systems to explore state-space, we suggest that the complex exploratory dynamics of STN-GPe system in conjunction with dopamine-based reward signaling from the Substantia Nigra pars compacta (SNc) present the two key ingredients of a reinforcement learning system.

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