Deep brain stimulation (DBS) is a highly efficacious treatment option for movement disorders and a growing number of other indications are investigated in clinical trials. To ensure optimal treatment outcome, exact electrode placement is required. Moreover, to analyze the relationship between electrode location and clinical results, a precise reconstruction of electrode placement is required, posing specific challenges to the field of neuroimaging. Since 2014 the open source toolbox Lead-DBS is available, which aims at facilitating this process. The tool has since become a popular platform for DBS imaging. With support of a broad community of researchers worldwide, methods have been continuously updated and complemented by new tools for tasks such as multispectral nonlinear registration, structural / functional connectivity analyses, brain shift correction, reconstruction of microelectrode recordings and orientation detection of segmented DBS leads. The rapid development and emergence of these methods in DBS data analysis require us to revisit and revise the pipelines introduced in the original methods publication. Here we demonstrate the updated DBS and connectome pipelines of Lead-DBS using a single patient example with state-of-the-art high-field imaging as well as a retrospective cohort of patients scanned in a typical clinical setting at 1.5T. Imaging data of the 3T example patient is co-registered using five algorithms and nonlinearly warped into template space using ten approaches for comparative purposes. After reconstruction of DBS electrodes (which is possible using three methods and a specific refinement tool), the volume of tissue activated is calculated for two DBS settings using four distinct models and various parameters. Finally, four whole-brain tractography algorithms are applied to the patient’s preoperative diffusion MRI data and structural as well as functional connectivity between the stimulation volume and other brain areas are estimated using a total of eight approaches and datasets. In addition, we demonstrate impact of selected preprocessing strategies on the retrospective sample of 51 PD patients. We compare the amount of variance in clinical improvement that can be explained by the computer model depending on the method of choice. This work represents a multi-institutional collaborative effort to develop a comprehensive, open source pipeline for DBS imaging and connectomics, which has already empowered several studies, and may facilitate a variety of future studies in the field.

Enhanced beta-band activity recorded in patients suffering from Parkinson's Disease (PD) has been described as a potential physiomarker for disease severity. Beta power is suppressed by Levodopa intake and STN deep brain stimulation (DBS) and correlates with disease severity across patients. The aim of the present study was to explore the promising signature of the physiomarker in the spatial domain. Based on local field potential data acquired from 54 patients undergoing STN-DBS, power values within alpha, beta, low beta, and high beta bands were calculated. Values were projected into common stereotactic space after DBS lead localization. Recorded beta power values were significantly higher at posterior and dorsal lead positions, as well as in active compared with inactive pairs. The peak of activity in the beta band was situated within the sensorimotor functional zone of the nucleus. In contrast, higher alpha activity was found in a more ventromedial region, potentially corresponding to associative or premotor functional zones of the STN. Beta- and alpha-power peaks were then used as seeds in a fiber tracking experiment. Here, the beta-site received more input from primary motor cortex whereas the alpha-site was more strongly connected to premotor and prefrontal areas. The results summarize predominant spatial locations of frequency signatures recorded in STN-DBS patients in a probabilistic fashion. The site of predominant beta-activity may serve as an electrophysiologically determined target for optimal outcome in STN-DBS for PD in the future. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc.

Objective-Beta band oscillations in the subthalamic nucleus (STN) have been proposed as a pathophysiological signature in patients with Parkinson's disease (PD). The aim of this study was to investigate the potential association between oscillatory activity in the STN and symptom severity in PD.Methods-Subthalamic local field potentials were recorded from 63 PD patients in a dopaminergic OFF state. Power-spectra were analyzed for the frequency range from 5 to 95 Hz and correlated with individual UPDRS-III motor scores in the OFF state.Results-A correlation between total UPDRS-III scores and 8 to 35 Hz activity was revealed across all patients (ρ = 0.44, P <.0001). When correlating each frequency bin, a narrow range from 10 to 15 Hz remained significant for the correlation (false discovery rate corrected P <.05). Conclusion-Our results show a correlation between local STN 8 to 35Hz power and impairment in PD, further supporting the role of subthalamic oscillatory activity as a potential biomarker for PD. Keywords Europe PMC Funders Author ManuscriptsEurope PMC Funders Author Manuscripts Deep brain stimulation (DBS) is an effective treatment for patients with Parkinson's disease (PD).1 One of the hypothesized mechanisms of actions of DBS is a suppression of aberrant oscillatory activity in the target structure.2 Enhanced subthalamic oscillations at beta frequency have been proposed as a pathophysiological signature for PD.3 A multitude of studies have revealed abnormally synchronized activity in the subthalamic nucleus (STN) over a broad range of 8 to 35 Hz in the PD OFF state,2,4,5 and this band, or portions of it, is generally referred to as beta activity. Dopaminergic therapy and DBS both lead to a decrease of spectral power in this frequency band at the same time that the patient experiences clinical symptom alleviation.6,7 The relative difference of 8 to 35 Hz band power between the ON and OFF states has been shown to correlate with the difference in symptom severity as measured by the Unified Parkinson's Disease Rating Scale (UPDRS III).5 Moreover, DBSinduced suppression of beta band activity correlated with motor performance in PD.8 This has led to the idea that subthalamic oscillatory activity could serve as an index of symptom severity for adaptive stimulation in a closed-loop system.9-13 Using this approach, an individual threshold of local field potential (LFP) activity would serve as a biomarker to trigger DBS. Whether the scale of 8 to 35 Hz activity in the OFF state correlates with motor impairment within the same state is less clear. Such a correlation is more consistently reported with more complex measures such as LFP complexity14 or standard deviation.15 The observation that dystonia patients also exhibit peaks in the beta frequency band has recently questioned the specificity of beta activity as a biomarker in PD.16 To corroborate previous findings, this study aims to investigate the association between subthalamic oscillatory activity and parkinsonian symptom severity in a large cohort...

Deep brain stimulation of the globus pallidus internus alleviates involuntary movements in patients with dystonia. However, the mechanism is still not entirely understood. One hypothesis is that deep brain stimulation suppresses abnormally enhanced synchronized oscillatory activity within the motor cortico-basal ganglia network. Here, we explore deep brain stimulation-induced modulation of pathological low frequency (4-12 Hz) pallidal activity that has been described in local field potential recordings in patients with dystonia. Therefore, local field potentials were recorded from 16 hemispheres in 12 patients undergoing deep brain stimulation for severe dystonia using a specially designed amplifier allowing simultaneous high frequency stimulation at therapeutic parameter settings and local field potential recordings. For coherence analysis electroencephalographic activity (EEG) over motor areas and electromyographic activity (EMG) from affected neck muscles were recorded before and immediately after cessation of high frequency stimulation. High frequency stimulation led to a significant reduction of mean power in the 4-12 Hz band by 24.8 ± 7.0% in patients with predominantly phasic dystonia. A significant decrease of coherence between cortical EEG and pallidal local field potential activity in the 4-12 Hz range was revealed for the time period of 30 s after switching off high frequency stimulation. Coherence between EMG activity and pallidal activity was mainly found in patients with phasic dystonic movements where it was suppressed after high frequency stimulation. Our findings suggest that high frequency stimulation may suppress pathologically enhanced low frequency activity in patients with phasic dystonia. These dystonic features are the quickest to respond to high frequency stimulation and may thus directly relate to modulation of pathological basal ganglia activity, whereas improvement in tonic features may depend on long-term plastic changes within the motor network.

Deep brain stimulation has local effects on the target structure, but also global effects via distributed brain networks. Horn et al. show that modulating the activity of the subthalamic nucleus in patients with Parkinson’s disease normalizes signatures of widespread network connectivity towards those found in healthy controls.