Adaptive deep brain stimulation (aDBS) is a promising concept for feedback-based neurostimulation, with the potential of clinical implementation with the sensing-enabled Percept neurostimulator. We aim to characterize chronic electrophysiological activity during stimulation and to validate beta-band activity as a biomarker for bradykinesia. Subthalamic activity was recorded during stepwise stimulation amplitude increase OFF medication in 10 Parkinson’s patients during rest and finger tapping. Offline analysis of wavelet-transformed beta-band activity and assessment of inter-variable relationships in linear mixed effects models were implemented. There was a stepwise suppression of low-beta activity with increasing stimulation intensity (p = 0.002). Low-beta power was negatively correlated with movement speed and predictive for velocity improvements (p < 0.001), stimulation amplitude for beta suppression (p < 0.001). Here, we characterize beta-band modulation as a chronic biomarker for motor performance. Our investigations support the use of electrophysiology in therapy optimization, providing evidence for the use of biomarker analysis for clinical aDBS.

Objectives Deep brain stimulation (DBS) of the posterior subthalamic area (PSA) and the ventral intermediate thalamic nucleus (VIM) is a well‐established therapy for essential tremor (ET), but it is frequently associated with side effects like dysarthria or gait ataxia. Directional DBS (dDBS) may be a way to activate fiber tracts more selectively. Is dDBS for ET superior to omnidirectional DBS (oDBS) regarding therapeutic window and clinically as effective as oDBS? Materials and Methods Ten patients with ET treated with PSA/VIM‐DBS were recruited. Therapeutic window served as primary outcome parameter; clinical efficacy, volume of neuronal activation, and total electrical energy delivered (TEED) served as secondary outcome parameters. Therapeutic window was calculated for all three dDBS directions and for oDBS by determining therapeutic thresholds and side effect thresholds. Clinical efficacy was assessed by comparing the effect of best dDBS and oDBS on tremor and ataxia rating scales, and accelerometry. Volume of neural activation and TEED were also calculated for both paradigms. Results For best dDBS, therapeutic window was wider and therapeutic threshold was lower compared to oDBS. While side effect threshold did not differ, volume of neural activation was larger for dDBS. In terms of clinical efficacy, dDBS was as effective as oDBS. Conclusions dDBS for ET widens therapeutic window due to reduction of therapeutic threshold. Larger volume of neural activation for dDBS at side effect threshold supports the notion of persistent directionality even at higher intensities. dDBS may compensate for slightly misplaced leads and should be considered first line for PSA/VIM‐DBS.

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ObjectiveMotor evoked potentials (MEP), obtained by transcranial magnetic stimulation (TMS) are a common tool in clinical research and diagnostic. Nevertheless, reports regarding the influence of filter settings on MEP are sparse. Here, we compared MEP amplitudes and signal to noise ratio (SNR) using multiple high pass filter (HPF) and notch filter settings.Materials and MethodsTwenty healthy subjects were enrolled in the study. Recruitment curves were obtained with HPF settings varied at 10, 20, 50, and 100 Hz. The four HPF settings were tested both with and without 50 Hz active notch filter. Low pass filter was kept constant at 5 kHz.ResultsMEP amplitudes with HPF at 10 and 20 Hz were significantly higher than at 100 Hz, regardless of the notch filter. However, SNR did not differ among HPF settings. An active notch filter significantly improved SNR.ConclusionThe reduction in MEP amplitudes with HPF above 20 Hz may be due to noise reduction, since the different HPF conditions did not alter SNR. Thus, higher HPF above 50 Hz may be an option to reduce noise, the use of a notch filter may even improve SNR.SignificanceOur findings are relevant for the selection of filter settings and might be of importance to any researcher who utilizes TMS-MEP.