Computational analysis of electrode structure and configuration for efficient and localized neural stimulation

Neuromodulation technique using electric stimulation is widely applied in neural prosthesis, therapy, and neuroscience research. Various stimulation techniques have been developed to enhance stimulation efficiency and to precisely target the specific area of the brain which involves optimizing the geometry and the configuration of the electrode, stimulation pulse type and shapes, and electrode materials. Although the effects of electrode shape, size, and configuration on the performance of neural stimulation have individually been characterized, to date, there is no integrative investigation of how this factor affects neural stimulation. In this study, we computationally modeled the various types of electrodes with varying shapes, sizes, and configurations and simulated the electric field to calculate the activation function. The electrode geometry is then integratively assessed in terms of stimulation efficiency and stimulation focality. We found that stimulation efficiency is enhanced by making the electrode sharper and smaller. A center-to-vertex distance exceeding 100 µm shows enhanced stimulation efficiency in the bipolar configuration. Additionally, the separation distance of less than 1 mm between the reference and stimulation electrodes exhibits higher stimulation efficiency compared to the monopolar configuration. The region of neurons to be stimulated can also be modified. We found that sharper electrodes can locally activate the neuron. In most cases, except for the rectangular electrode shape with a center-to-vertex distance smaller than 100 µm, the bipolar electrode configuration can locally stimulate neurons as opposed to the monopolar configuration. These findings shed light on the optimal selection of neural electrodes depending on the target applications.