Computational Field Shaping for Deep Brain Stimulation With Thousands of Contacts in a Novel Electrode Geometry.

Objective: Deep brain stimulation (DBS) alleviates symptoms associated with some neurological disorders by stimulating specific deep brain targets. However, incomplete stimulation of the target region can provide suboptimal therapy, and spread of stimulation to tissue outside the target can generate side-effects. Existing DBS electrodes generate stimulation profiles that are roughly spherical, neither matching nor enabling the mapping of therapeutic targets. We present a novel electrode design and will perform computational modeling of the new design to investigate its use as a next generation DBS electrode.

Materials And Methods: Computational simulations of a finite element model are performed for both the novel electrode and for a commercially available DBS electrode.

Results: Computational modeling results show that this new electrode design is able to steer stimulation radially around the device, creating voltage distributions that may more closely match deep brain targets.

Conclusion: The ability to better match the anatomy and compensate for targeting errors during implantation will enable strict localization of the generated stimulation fields to within target tissues, potentially providing more complete symptom alleviation while reducing the occurrence of side-effects.