Abstract General anesthesia increasingly facilitates asleep deep brain stimulation (DBS) surgery but suppresses spontaneous electrophysiological signals used to guide lead placement. Here, we investigated whether evoked resonant neural activity (ERNA), a stimulation-evoked biomarker of basal ganglia circuitry, remains informative during asleep DBS. We analyzed intraoperative recordings from a multisite cohort of 45 patients (86 hemispheres) undergoing subthalamic nucleus or globus pallidus internus DBS under awake and anesthetized conditions. Anesthesia markedly attenuated spontaneous beta and high-frequency oscillatory activity. Although ERNA amplitude was reduced at matched stimulation intensities, increasing stimulation current restored high-amplitude, spatially localized responses while preserving anatomical specificity. Across both targets, ERNA spatial distributions remained stable across awake and anesthetized states, co-localized with established motor-network biomarkers, and retrospectively identified electrode levels associated with the greatest postoperative therapeutic window. These retrospective findings position stimulation-evoked circuit interrogation as a complement to imaging for physiology-guided asleep DBS and as a candidate signal for contact prioritization. Prospective studies are warranted to determine whether ERNA-guided decisions improve placement, programming efficiency and clinical outcomes.
A Low-Cost, Open-Source Wireless Platform for Real-Time Tremor Monitoring in Parkinson's Disease
2025 12th International IEEE/EMBS Conference on Neural Engineering (NER) | July 9, 2026 | Volume: No volume available | Issue: No issue available | Pages: 587-591
The Journal of Neuropsychiatry and Clinical Neurosciences | March 16, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available
Abstract Deep brain stimulation (DBS) is a targeted manipulation of brain circuitry to treat neurological and neuropsychiatric conditions. Optimal DBS lead placement is essential for treatment efficacy. Current targeting practice is based on preoperative and intraoperative brain imaging, intraoperative electrophysiology, and stimulation mapping. Electrophysiological mapping using extracellular microelectrode recordings aids in identifying functional subdomains, anatomical boundaries, and disease-correlated physiology. The shape of single-unit action potentials may differ due to different biophysical properties between cell-types and brain regions. Here, we describe a technique to parameterize the structure and duration of sorted spike units using a novel algorithmic approach based on canonical response parameterization, and illustrate how it may be used on DBS microelectrode recordings. Isolated spike shapes are parameterized then compared using a spike similarity metric and grouped by hierarchical clustering. When spike morphology is associated with anatomy, we find regional clustering in the human globus pallidus. This method is widely applicable for spike removal and single-unit characterization and could be integrated into intraoperative array-based technologies to enhance targeting and clinical outcomes in DBS lead placement. Author summary We developed a new algorithmic approach to capture the structure of single neuron electrophysiology from microelectrode recordings during deep brain stimulation surgery. This method has broad applications for spike characterization, clustering, removal from the background field potential, and comparison across recording sites. Using this technique, we illustrate regional clustering of spike morphologies in the human globus pallidus.