A physiologically realistic computational model of the basal ganglia network

  • Azevedo Carvalho Nathalie
  • Buhry Laure
  • Contassot-Vivier Sylvain
  • Baufreton Jérôme
  • Martinez Dominique

  • Physiological realistic model
  • Basal ganglia
  • Neuroscience


The basal ganglia (BG) are a set of nuclei that process movement information: they refine and adjust simple movement actions. The BG has two major pathways: the striatum (STR)-indirect neuron pathway and the subthalamic (STN)-hyperdirect nucleus pathway. The GPe is the connecting nucleus between the two pathways. The STR inhibits the GPe and the STN excites the GPe which is divided into two types of neurons [1, 4], the prototypical and the arkypallidal. This discovery allows for a better understanding of the functioning of this neural network. We model the STN-GPeA-GPeP-STR(D2) network and study the influence of the nucleus on each other like in [2]. The neurons have been modeled as point neurons using the Hodgkin-Huxley formalism and the synapses as exponential functions. From extensive simulations performed with the SiReNe software (Neural network simulator, in french: Simulateur de Réseaux de Neurones [3]), we show that our network is in good agreement with the physiological results of [2]. This simulator is based on a hybrid method combining time-step and event-driven computations with a Runge-Kutta numerical method at inner level. GPe is mainly inhibited by GABAergic inputs of the STR and we study the impact of STR connectivity on GPe. We observe that the GPeP and GPeA react in opposite ways when the STR is activated, i.e. GPeP is entirely inhibited whereas the GPeA and STN are completely excited, as observed in [2]. This work aims at better understanding the synaptic connectivity scheme. This model will allow us to test hypotheses regarding the pathological rhythmogenesis in Parkinson disease, both at the cellular and connectivity levels.