The emergence of two anti-phase oscillatory neural populations in a computational model of the Parkinsonian globus pallidus

Robert Merrison-Hort,Roman Borisyuk

doi:10.3389/fncom.2013.00173

Abstract

Experiments in rodent models of Parkinson's disease have demonstrated a prominent increase of oscillatory firing patterns in neurons within the Parkinsonian globus pallidus (GP) which may underlie some of the motor symptoms of the disease. There are two main pathways from the cortex to GP: via the striatum and via the subthalamic nucleus (STN), but it is not known how these inputs sculpt the pathological pallidal firing patterns. To study this we developed a novel neural network model of conductance-based spiking pallidal neurons with cortex-modulated input from STN neurons. Our results support the hypothesis that entrainment occurs primarily via the subthalamic pathway. We find that as a result of the interplay between excitatory input from the STN and mutual inhibitory coupling between GP neurons, a homogeneous population of GP neurons demonstrates a self-organizing dynamical behavior where two groups of neurons emerge: one spiking in-phase with the cortical rhythm and the other in anti-phase. This finding mirrors what is seen in recordings from the GP of rodents that have had Parkinsonism induced via brain lesions. Our model also includes downregulation of Hyperpolarization-activated Cyclic Nucleotide-gated (HCN) channels in response to burst firing of GP neurons, since this has been suggested as a possible mechanism for the emergence of Parkinsonian activity. We found that the downregulation of HCN channels provides even better correspondence with experimental data but that it is not essential in order for the two groups of oscillatory neurons to appear. We discuss how the influence of inhibitory striatal input will strengthen our results.

Highlights

Parkinson’s disease is a neurodegenerative disorder which causes a range of movement-related disturbances such as tremor and slowness
We have presented what we believe to be a novel model of globus pallidus (GP) neurons that features much of the biological realism of previous detailed multi-compartmental models but considerably reduced complexity
We have introduced a possible computational mechanism for simulating the downregulation of Hyperpolarization-activated Cyclic Nucleotide-gated (HCN) channels and shown that this improves how closely our results fit with biological evidence

Summary

Introduction

Parkinson’s disease is a neurodegenerative disorder which (amongst other symptoms) causes a range of movement-related disturbances such as tremor and slowness (bradykinesia). One very successful hypothesis for this was the so-called “rate” hypothesis (DeLong, 1990), which held that motor areas of the basal ganglia are divided into two feed-forward pathways that transfer information from the cortex to the thalamus: a pro-kinetic “direct” and an anti-kinetic “indirect” pathway. According to this model, loss of dopamine input to the striatum upsets the balance of these two pathways, resulting in movement abnormalities. While the rate hypothesis makes predictions that have resulted in successful treatments, such as lesioning of hyperactive nuclei on the indirect pathway (Lozano et al, 1995; Gill and Heywood, 1997), more recent electrophysiological studies have demonstrated that the changes in neuronal activity that underlie Parkinsonian motor impairment are likely to be considerably more complex than those implied by the rate model [see Rubin et al (2012) for review]

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