Quantifying neuro-motor correlations during awake deep brain stimulation surgery using markerless tracking.

ABSTRACT: The expanding application of deep brain stimulation (DBS) therapy both drives and is informed by our growing understanding of disease pathophysiology and innovations in neurosurgical care. Neurophysiological targeting, a mainstay for identifying optimal, motor responsive targets, has remained largely unchanged for decades. Utilizing deep learning-based computer vision and related computational methods, we developed an effective and simple intraoperative approach to objectively correlate neural signals with movements, automating and standardizing the otherwise manual and subjective process of identifying ideal DBS electrode placements. Kinematics are extracted from video recordings of intraoperative motor testing using a trained deep neural network and compared to multi-unit activity record

SUBMITTER: Tekriwal A 

PROVIDER: S-EPMC9613670 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature