Deep brain stimulation-induced local evoked potentials outperform spectral features in spatial and clinical STN mapping

Objective: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an established therapy for Parkinson′s Disease (PD). Yet, optimizing lead placement and stimulation programming remains challenging. Current techniques rely on imaging and intraoperative microelectrode recordings (MER), while programming rely on trial-and-error clinical testing, which can be time-consuming. DBS-induced local evoked potentials (DLEP), also known as evoked resonant neural activity (ERNA), have emerged as a potential alternative electrophysiological marker for mapping. However, direct comparisons with traditional spectral features, such as beta-band, high-frequency oscillations (HFOs), and aperiodic component have been lacking. Approach: We evaluated DLEP across 39 STN DBS leads across 31 subjects with PD undergoing DBS surgery, using both a single-pulse and high-frequency burst stimulation paradigms. We developed a novel artifact-removal method to enable monopolar DLEP recovery, including estimating the DLEP amplitudes at stimulated contacts, further enhancing spatial sampling of DLEP. We evaluated spectral features and DLEP in respect to imaging-based and MER-based localization, and its predictive power for post-operative programming. Main Results: DLEP showed great spatial consistency, maximizing within STN with 100% accuracy for single-pulse and 84.62% for burst stimulation, surpassing spectral measures including beta (89.74%) and HFO (82.05%). DLEP better correlated with clinical outcomes (single-pulses ρ=-0.33, high-frequency bursts ρ=-0.26), than spectral measures (beta ρ=-0.25, HFO ρ=0.05). Furthermore, single-pulses at low-frequencies are sufficient for DLEP-based mapping. Significance: We show how DLEP provide higher STN-spatial specificity and correlation with postoperative programming compared to spectral features. To support clinical translation of DLEP, we developed two methods aimed to recover artifact-free DLEP and estimating DLEP amplitudes at stimulating contacts. DLEP appear distinct from beta and HFO activity, yet strongly tied to aperiodic spectral components, suggesting that DLEP amplitude reflects underlying STN excitability. This study highlights that DLEP are a robust and clinically valuable marker for DBS targeting and programming.