Functional Relevance of Different Basal Ganglia Pathways Investigated in a Spiking Model with Reward Dependent Plasticity

Frontiers in Neural Circuits

Jeanette Hellgren Kotaleski²  Mikael Lindahl³  Anders Lansner³  Pierre Berthet³  Philip Joseph Tully⁵ 

[1] KTH Royal Institute of Technology;Karolinska Institute;Stockholm Brain Institute;Stockholms Universitet;University of Edinburgh;

关键词: Basal Ganglia;    Dopamine;    Parkinson Disease;    reinforcement learning;    synaptic plasticity;    action selection;   

DOI  :  10.3389/fncir.2016.00053

来源: DOAJ

【 摘 要 】

The brain enables animals to behaviourally adapt in order to survive in a complex and dynamic environment, but how reward-oriented behaviours are achieved and computed by its underlying neural circuitry is an open question. To address this concern, we have developed a spiking model of the basal ganglia (BG) that learns to dis-inhibit the action leading to a reward despite ongoing changes in the reward schedule. The architecture of the network features the two pathways commonly described in BG, the direct (denoted D1) and the indirect (denoted D2) pathway, as well as a loop involving striatum and the dopaminergic system. The activity of these dopaminergic neurons conveys the reward prediction error (RPE), which determines the magnitude of synaptic plasticity within the different pathways. All plastic connections implement a versatile four-factor learning rule derived from Bayesian inference that depends upon pre- and postsynaptic activity, receptor type and dopamine level. Synaptic weight updates occur in the D1 or D2 pathways depending on the sign of the RPE, and an efference copy informs upstream nuclei about the action selected. We demonstrate successful performance of the system in a multiple-choice learning task with a transiently changing reward schedule. We simulate lesioning of the various pathways and show that a condition without the D2 pathway fares worse than one without D1. Additionally, we simulate the degeneration observed in Parkinson’s disease (PD) by decreasing the number of dopaminergic neurons during learning. The results suggest that the D1 pathway impairment in PD might have been overlooked. Furthermore, an analysis of the alterations in the synaptic weights shows that using the absolute reward value instead of the RPE leads to a larger change in D1.

【 授权许可】

Unknown