Properties of Neurons in External Globus Pallidus Can Support Optimal Action Selection

The external globus pallidus (GPe) is a key nucleus within basal ganglia circuits that are thought to be involved in action selection. A class of computational models assumes that, during action selection, the basal ganglia compute for all actions available in a given context the probabilities that they should be selected. These models suggest that a network of GPe and subthalamic nucleus (STN) neurons computes the normalization term in Bayes’ equation. In order to perform such computation, the GPe needs to send feedback to the STN equal to a particular function of the activity of STN neurons. However, the complex form of this function makes it unlikely that individual GPe neurons, or even a single GPe cell type, could compute it. Here, we demonstrate how this function could be computed within a network containing two types of GABAergic GPe projection neuron, so-called ‘prototypic’ and ‘arkypallidal’ neurons, that have different response properties in vivo and distinct connections. We compare our model predictions with the experimentally-reported connectivity and input-output functions (f-I curves) of the two populations of GPe neurons. We show that, together, these dichotomous cell types fulfil the requirements necessary to compute the function needed for optimal action selection. We conclude that, by virtue of their distinct response properties and connectivities, a network of arkypallidal and prototypic GPe neurons comprises a neural substrate capable of supporting the computation of the posterior probabilities of actions.Author Summary: Choosing an appropriate action as quickly and accurately as possible in a given situation is critical for the survival of animals and humans. One of the brain regions involved in action selection is a set of subcortical nuclei known as the basal ganglia. The importance of understanding information processing in the basal ganglia is further emphasised by the fact that their disturbed interactions in Parkinson’s disease results in profound difficulties in movement. Computational models have suggested how the basal ganglia could select actions in the fastest possible way for the required accuracy level. These models further predict that a part of basal ganglia, called the external globus pallidus (GPe), needs to calculate a particular function of its inputs. This paper proposes how this function could be computed in a mathematical model of a network within GPe. Furthermore, it shows that the experimentally observed connectivity and response properties of GPe neurons fulfil the requirements necessary to support optimal action selection. This suggests the GPe neurons have properties that allow them to contribute to optimal action selection in the whole basal ganglia.