Efficient Computation of the Neural Activation During Deep Brain Stimulation for Dispersive Electrical Properties of Brain Tissue

Deep brain stimulation (DBS) is a widely employed neurosurgical method to treat symptoms of neurodegenerative disorders. Computational modeling of DBS can help to gain insight into the mechanisms of its action. Among these models, the estimation of the volume of tissue activated (VTA) comprises a method to predict the extent of beneficial stimulation and unwanted side effects. This method requires the computation of the time-dependent extracellular potential in the proximity of the stimulation electrode, which is, in general, computationally expensive due to the dispersive electrical properties of brain tissue. We present an adaptive scheme based on two interpolation methods, which approximates the transfer function of the extracellular potential distribution in the frequency domain. The results suggest that the proposed method is able to substantially reduce the computational expense for the computation of the extracellular field distribution and VTA compared with the standard approach.