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The Basal Ganglia is a central structure involved in multiple cortical andsubcortical loops. Some of these loops are believed to be responsible forsaccade target selection. We study here how the very specific structuralrelationships of these saccadic loops can affect the ability of learningspatial and feature-based tasks.  We propose a model of saccade generation with reinforcement learningcapabilities based on our previous basal ganglia and superior colliculusmodels. It is structured around the interactions of two parallel cortico-basalloops and one tecto-basal loop. The two cortical loops separately deal withspatial and non-spatial information to select targets in a concurrent way. Thesubcortical loop is used to make the final target selection leading to theproduction of the saccade. These different loops may work in concert or disturbeach other regarding reward maximization. Interactions between these loops andtheir learning capabilities are tested on different saccade tasks.  The results show the ability of this model to correctly learn basic targetselection based on different criteria (spatial or not). Moreover the modelreproduces and explains training dependent express saccades toward targetsbased on a spatial criterion.  Finally, the model predicts that in absence of prefrontal control, thespatial loop should dominate.

Saccade learning with concurrent cortical and subcortical basal ganglia loops