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  • Open Access

Improved conditions for the generation of beta oscillations in the subthalamic nucleus-globus pallidus network

BMC Neuroscience201213 (Suppl 1) :P116

  • Published:


  • Brain Region
  • Stability Condition
  • Network Model
  • Analytic Stability
  • Globus Pallidus

A key pathology in the development of Parkinson’s disease is the occurrence of persistent beta oscillations, which are correlated with the difficulty of movement initiation. We investigate the network model composed of subthalamic nucleus (STN) and globus pallidus (GP) developed by Nevado Holgado et al. [1] who identified the conditions under which this circuit could generate beta oscillations. Our work extends their analysis by deriving improved analytic stability conditions for realistic values of the synaptic transmission delay between STN and GP neurons. For the range of synaptic transmission delays measured experimentally, the improved conditions are significantly closer to the results of simulations. Furthermore, our analysis explains how changes in cortical and striatal input to the STN-GP network influence oscillations generated by the circuit. Since we have identified when a system of mutually connected populations of excitatory and inhibitory neurons can generate oscillations, our results may also find applications in the study of neural oscillations produced by assemblies of excitatory and inhibitory neurons in other brain regions.

Authors’ Affiliations

Bristol Centre for Complexity Sciences and Department of Computer Science, University of Bristol, Bristol, UK
Department of Engineering Mathematics, University of Bristol, Bristol, UK
Department of Computer Science, University of Bristol, Bristol, UK


  1. Nevado Holgado A, Terry J, Bogacz R: Conditions for the Generation of Beta Oscillations in the Subthalamic Nucleus-Globus Pallidus Network. Journal of Neuroscience. 2010, 30 (37): 12340-12352. 10.1523/JNEUROSCI.0817-10.2010.View ArticleGoogle Scholar


© Pavlides et al; licensee BioMed Central Ltd. 2012

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.