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Tremor is thought to be an effect of oscillatory activity within the sensorimotor network. To date, the underlying pathological brain networks are not fully understood. Disentangling tremor activity from voluntary motor output and sensorimotor feedback systems is challenging. To better understand the intrinsic sensorimotor fingerprint underlying tremor, we aimed to disentangle the sensorimotor system into driving (motor) and feedback/compensatory (sensory) neuronal involvement, and aimed to pinpoint tremor activity in essential tremor (ET) and tremor-dominant Parkinson's disease (PD) with a novel closed-loop approach. Eighteen ET patients, 14 tremor-dominant PD patients, and 18 healthy controls were included. An MR-compatible wrist manipulator was employed during functional MRI (fMRI) while muscle activity during (in)voluntary movements was concurrently recorded using electromyography (EMG). Tremor was quantified based on EMG and correlated to brain activity. Participants performed three tasks: an active wrist motor task, a passive wrist movement task, and rest (no wrist movement). The results in healthy controls proved that our experimental paradigm activated the expected motor and sensory networks separately using the active (motor) and passive (sensory) task. ET patients showed similar patterns of activation within the motor and sensory networks. PD patients had less activity during the active motor task in the cerebellum and basal ganglia compared to ET and healthy controls. EMG showed that in ET, tremor fluctuations correlated positively with activity in the inferior olive region, and that in PD tremor fluctuations correlated positively with cerebellar activity. Our novel approach with an MR-compatible wrist manipulator, allowed to investigate the involvement of the motor and sensory networks separately, and as such to better understand tremor pathophysiology. In ET sensorimotor network function did not differ from healthy controls. PD showed less motor-related activity. Focusing on tremor, our results indicate involvement of the inferior olive in ET tremor modulation, and cerebellar involvement in PD tremor modulation.

Introduction: For deep brain stimulation (DBS) surgery of the subthalamic nucleus (STN) in Parkinson’s disease (PD), many centers employ visualization of the nucleus on magnetic resonance imaging (MRI), intraoperative microelectrode recordings (MER), and test stimulation in awake patients. The value of these steps is a subject for ongoing debate. In the current study, we determined the relative contribution of MRI targeting, multitrack MER, and awake test stimulation in final lead placement during STN DBS surgery for PD. Methods: Data on PD patients undergoing MRI-targeted STN DBS surgery with three-channel MER and awake test stimulation between February 2010 and January 2014 were analyzed to determine in which MER trajectory final leads were implanted and why this tract was chosen. Results: Seventy-six patients underwent implantation of 146 DBS leads. In 92% of the STN, the final leads were implanted in one of the three planned channels. In 6%, additional channels were needed. In 2%, surgery was aborted before final lead implantation due to anxiety or fatigue. The final leads were implanted in the channels with the longest STN MER signal trajectory in 60% of the STN (38% of the bilaterally implanted patients). This was the central channel containing the MRI target in 39% of the STN (18% bilaterally). The most frequently noted reasons why another channel than the central channel was chosen for final lead placement were (1) a lower threshold for side effects (54%) and (2) no or a too short trajectory of the STN MER signal (40%) in the central channel. The latter reason correlated with larger 2D (x and y) errors in our stereotactic method. Conclusions: STN DBS leads were often not implanted in the MRI-planned trajectory or in the trajectory with the longest STN MER signal. Thresholds for side effects during awake test stimulation were decisive for final target selection in the majority of patients.

Background: In deep brain stimulation of the subthalamic nucleus (STN-DBS) for Parkinson’s Disease (PD), often microelectrode recordings (MER) are used for STN identification. However, for advanced target identification of the sensorimotor STN, it may be relevant to use local field potential (LFP) recordings. Then, it is important to assure that the measured oscillations are coming from the close proximity of the electrode. New method: Through multiple simultaneous recordings of LFP and neuronal spiking, we investigated the temporal relationship between local neuronal spiking and more global LFP. We analyzed the local oscillations in the LFP by calculating power only over specific frequencies that show a significant coherence between LFP and neuronal spiking. Using this ‘coherence method’, we investigated how well measurements in the sensorimotor STN could be discriminated from measurements elsewhere in the STN. Results/comparison with existing methods: The ‘sensorimotor power index’ (SMPI) of beta frequencies, representing the ability to discriminate sensorimotor STN measurements based on the beta power, was significantly larger using the ‘coherence method’ for LFP spectral analysis compared to other methods where either the complete LFP beta spectrum or only the prominent peaks in the LFP beta spectrum were used to calculate beta power. Conclusions: The results suggest that due to volume conduction of beta frequency oscillations, proper localization of the sensorimotor STN with only LFP recordings is difficult. However, combining recordings of LFP and neuronal spiking and calculating beta power over the coherent parts of the LFP spectrum can be beneficial in discriminating the sensorimotor STN.

Clinitron beds, often used to prevent decubitus ulcers, may cause an EEG artefact by static electricity. The best way to prevent this artefact is to turn off the bed during EEG registrations.