Computational Modeling of Deep Brain Stimulation in the Globus Pallidus Internus

Abstract

Deep brain stimulation (DBS) is a neural interface technology developed to improve the quality of life for people with movement disorders (e.g., Parkinson’s disease, dystonia, essential tremor). The general procedure involves placing small electrodes in regions of the brain exhibiting pathological activity and then stimulating those regions with continuous pulses of electricity. Treatment outcome is strongly dependent on the precise placement of the electrodes in the brain and subsequent adjustment of the stimulation settings to fine-tune the therapy. Stimulation of the globus pallidus internus (GPi) has yielded promising results for people with dystonia, a neurological movement disorder in which sustained muscle contractions cause twisting and repetitive movements or abnormal postures. However, specific stimulation settings that provide maximum GPi modulation and have minimal side-effects have yet to be determined. Here we use computational models to show how altering the DBS lead electrode configuration affects GPi modulation and activation of the cortical spinal tract (CST) (i.e., the side-effect pathway). GPi DBS simulations yielded a combination of cell activation and inhibition. Activation was found to be greatest around the cathode of the DBS lead. Modulated cells were localized relative to the lead and the degree of modulation decreased farther away. These results can provide a framework for neurosurgeons and neurologists to improve current techniques that will optimize treatment outcome.