title: Neuroinformatics and modeling of the basal ganglia: bridging pharmacology and physiology.
abstract: The subthalamic nucleus (STN) is the primary target for the chronic deep brain stimulation treatment of Parkinson's disease. STN neurons exhibit a variety of characteristic properties that may play a key role in the overall population response to deep brain stimulation. Neuroinformatics techniques, in particular computational modeling, provide a method of bringing together pharmacological phenomena, such as the loss of dopamine, with electrophysiological characteristics. Developing accurate models of STN neurons plays an important part in the process of uncovering the link between the changes in STN pharmacology, physiology and synaptic input that occurs with Parkinson's disease and the effectiveness of treatments targeting the STN. We review a general procedure for developing computational models and present a model of STN neurons that reveals important membrane channel interactions. In particular, changes in these channel interactions under parkinsonian conditions may underlie changes in characteristic physiology, critical in determining the mechanisms of deep brain stimulation.
authors.affiliation: Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh EH1 2QL, UK. andrew@anc.ed.ac.uk
authors.forename: Andrew
authors.initials: A
authors.lastname: Gillies
authors.forename: David
authors.initials: D
authors.lastname: Willshaw
mesh_terms: D000818:Animals; D001479:Basal Ganglia / Q000187:drug effects / Q000503:physiopathology; D019295:Computational Biology / Q000379:methods*; D046690:Deep Brain Stimulation; D006801:Humans; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology; D020734:Parkinsonian Disorders / Q000503:physiopathology*; D051381:Rats; D020531:Subthalamic Nucleus / Q000166:cytology / Q000187:drug effects* / Q000503:physiopathology*