Although microelectrode recordings (MER) are commonly used to confirm stereotactic targets during surgery for movement disorders, there is no consensus on whether the additional risks and cost of MER are worth the benefits. This may be due, in part, to the inconsistency and inefficiency of subjective interpretation of MER data that is currently used in practice. We describe several fully automatic visualization methods for MER that efficiently and clearly indicate segments of the microelectrode trajectories with homogeneous neural activity that correspond to expected deep brain nuclei. Specifically we demonstrate that these visualization methods can help identify the subthalamic nucleus in Parkinson's disease patients. These methods have the potential to significantly improve patient outcome by helping neurosurgeons objectively identify target structures more quickly and accurately.
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