Center for Integrative Biomedical Computing

Systems-Level Model of Deep Brain Stimulation

Cameron McIntyre

Cleveland Clinic

Deep brain stimulation (DBS) is an effective treatment for Parkinson's disease (PD); however, numerous questions remain on the therapeutic mechanisms of the technology. The goal of this project is to use detailed computer modeling techniques to augment neurophysiological investigation on the mechanisms of DBS. These models will be assembled within the SCIRun/BioPSE environment. We hypothesize that therapeutic DBS induces basal ganglia (BG) network activity consistent with activation of axonal processes near the stimulating electrode, resulting in a regularization of BG input to the thalamus. In turn, thalamocortical processing can occur with reduced pathological interference from the BG during DBS. We propose to address this hypothesis with the integration of complementary data from three research modalities (experimental electrophysiology, computational modeling, and functional magnetic resonance imaging (fMRI)). First, we will parameterize a large scale neural network model to coincide with simultaneous multi-unit microelectrode recordings from the BG and thalamus of parkinsonian non-human primates. Next, we will develop detailed patient-specific DBS models of the spread of stimulation in a cohort of 30 individuals. These patient-specific predictions of the neural tissue directly activated by their DBS will then be applied to the network model, allowing for evaluation of the network activity patterns generated by the stimulation. Finally, the integrated synaptic activity of the network model will be compared to fMRI data acquired in these same patients during DBS. We will use our model system to decipher the underlying neurophysiological changes responsible therapeutic benefit and define novel stimulation strategies that could improve clinical outcomes.

Model-Based Optimization of Clinical Deep Brain Stimulation Deep brain stimulation (DBS) of the subthalamic nucleus (STN) or globus pallidus inturnus (GPi) represent established therapies for medically refractory Parkinson's disease (PD). However, selection of therapeutic stimulation parameters is primarily based on clinical intuition, and the DBS electrode design is not optimized to either nucleus. The fundamental goal of this project is to quantify the volume of tissue activated (VTA) by DBS in PD patients. We will create a patient-specific model of DBS, using SCIRun/BioPSE, for each subject enrolled in an NIH sponsored clinical trial comparing the therapeutic efficacy of STN DBS to GPi DBS (R01 NS-37959 PI: Vitek). Our central hypothesis is that there exists a target volume of tissue that should be stimulated for maximal therapeutic benefit from DBS, and the size and shape of the target VTA is specific to each nucleus. Characterization of the different anatomical structures activated by DBS across a large patient population (60 STN and 60 GPi) will allows us to define probabilistic maps of therapeutic and non-therapeutic regions for stimulation. These results will allow definition of the therapeutic target VTA for each nucleus. The scientific knowledge gained from this project will advance the clinical utility of DBS for PD. In addition, the methodology and technology developed in this study will be directly applicable to the study of DBS in other disorders such as essential tremor, dystonia, epilepsy, obsessive-compulsive disorder, depression, and Tourette's syndrome.


  1. C. R. Butson, A. M. Noecker, C. B. Maks, and C. C. McIntyre. "Stimexplorer: Deep brain stimulation parameter selection software system". Acta Neurochir Suppl (Wien), 97:569–574, 2007.
  2. C. R. Butson and C. C. McIntyre. "Current steering to control the volume of tissue activated during deep brain stimulation". Brain Stimulat., 1:7–14, 2008.
  3. C. B. Maks, C. R. Butson, B.L. Walter, J.L. Vitek, and C. C. McIntyre. "Deep brain stimulation activation volumes and their association with neurophysiological mapping and therapeutic outcomes". J. Neurol. Neurosurg. Psychiatry, 80:659–666, 2009.