Beudel, M. | Search bioRxiv

bioRxiv2022

A comparison of methods to suppress electrocardiographic artifacts in local field potential recordings

ObjectiveSensing-enabled neurostimulators for deep brain stimulation (DBS) therapy record neural activity directly from the stimulating electrodes in the form of local field potentials (LFPs). However, these LFPs are often contaminated with electrocardiographic (ECG) artifacts that impede the detection of physiomarkers for adaptive DBS research. This study systematically compared the ability of different ECG suppression methods to recover disease-specific electrical brain activity from ECG-contaminated LFPs. ApproachThree ECG suppression methods were evaluated: (1) QRS interpolation of the Perceive toolbox, (2) four variants of a template subtraction method, and (3) sixteen variants of a singular value decomposition (SVD) method. The performance of these methods was examined using LFPs recorded with the Medtronic PerceptTM PC system from the subthalamic nucleus in nine patients with Parkinsons disease while stimulation was turned off ("OFF-DBS"; anode disconnected) and while stimulation was turned on at 0 mA ("ON-DBS 0 mA"; anode connected). In addition, ECG-contaminated LFPs were simulated by scaling a co-recorded external ECG signal and adding it to the OFF-DBS LFPs. Main ResultsECG artifacts were present in 10 out of 18 ON-DBS 0 mA recordings. All ECG suppression methods were able to drastically reduce the percent difference of beta band (13 - 35 Hz) spectral power and at least partly recover the beta peak and beta burst dynamics. Using predetermined R-peaks improved the performance of the ECG suppression methods. Lengthening the time window around the R-peaks resulted in stronger reduction in artifact-induced beta band power but at an increased risk of flattening the beta peak and loss of beta burst dynamics. SignificanceThe SVD method formed the preferred trade-off between artifact cleaning and signal loss, as long as its parameter settings (time window around the R-peaks; number of components) are adequately chosen.

neuroscience↗

bioRxiv2019

Adaptive Deep Brain Stimulation as an Advanced Parkinson’s disease Treatment (ADAPT): a pseudorandomised clinical trial

BackgroundBeta-based adaptive Deep Brain Stimulation (aDBS) is effective in Parkinsons disease (PD), when assessed in the immediate post-implantation phase. However, the potential benefits of aDBS in patients with electrodes chronically implanted, in whom the benefits of the microlesion effect have disappeared, are yet to be assessed. MethodsTo determine the acute effectiveness and side-effect profile of aDBS in PD compared to conventional continuous DBS (cDBS) and no stimulation (NoStim), years after DBS implantation. 13 PD patients undergoing battery replacement were pseudo-randomised in a crossover fashion, in- to three conditions (NoStim, aDBS or cDBS). Patient videos were blindly evaluated using a short version of the Unified Parkinsons Disease Rating Scale (subUPDRS) and the Speech Intelligibility Test (SIT). ResultsPatients had a mean disease duration of 16 years, and the mean time since DBS implantation was 6.9 years. subUPDRS scores (11 patients tested) were significantly lower both in aDBS (p=<.001), and cDBS (p=.001), when compared to NoStim. Bradykinesia subscores were significantly lower in aDBS (p=.002), but not in cDBS (p=.08), when compared to NoStim. Two patients presented re-emerging tremor during NoStim. SIT scores of patients with stimulation-induced dysarthria (11 patients tested) significantly worsened in cDBS (p=.009), but not in aDBS (p=.407), when compared to NoStim. Overall, stimulation was applied 48.8% of the time during aDBS. ConclusionBeta oscillations is effective in PD patients with bradykinetic phenotypes, delivers less stimulation than cDBS, and potentially has a more favourable speech side-effect profile. Patients with prominent tremor may require a modified adaptive control strategy.

neuroscience↗