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.@en

Background: The basal ganglia and cerebellum are brain structures involved in movement initiation, execution and termination. They are thought to be involved in the tremor generation and movement deficits in Parkinson's disease (PD) and essential tremor (ET). Especially in PD, maintaining cyclic movement, such as walking or tapping can be significantly disturbed. Providing external cues improves timing of these movements in PD but its effect on ET has not yet been studied in depth. The aim of this study is to evaluate the usefulness of a bimanual tapping task as a tool during clinical decision making. Method: Hand movements and tremor was recorded using accelerometers and EMG (m. extensor carpi ulnaris) from PD and ET patients and healthy controls during a bimanual tapping task as a way to distinguish PD from ET. All subjects performed the tapping task at two different frequencies, 2 Hz and 4 Hz, with and without the presence of auditory cues. Results: No significant intra-group differences were found in the patient groups. Acceleration data revealed significantly less accurate tapping and more variable tapping in PD than in ET and healthy controls. ET subjects tapped less accurate and with a greater variability than healthy controls during the 4 Hz tapping task. Most interestingly the tapping accuracy improved in PD patients when kinetic tremor was recorded with EMG during the task. Conclusion: Providing ET and PD patients with an external cue results in different tapping performances between patient groups and healthy controls. Furthermore, the findings suggest that kinetic tremor in PD enables patients to perform the task with a greater accuracy. So far this has not been shown in other studies.@en

Objective: A role of the motor cortex in tremor generation in essential tremor (ET) is assumed, yet the directionality of corticomuscular coupling is unknown. Our aim is to clarify the role of the motor cortex. To this end we also study ‘familial cortical myoclonic tremor with epilepsy’ (FCMTE) and slow repetitive voluntary movements with a known cortical drive. Methods: Directionality of corticomuscular coupling (EEG-EMG) was studied with renormalized partial directed coherence (rPDC) during tremor in 25 ET patients, 25 healthy controls (mimicked) and in seven FCMTE patients; and during a self-paced 2 Hz task in eight ET patients and seven healthy controls. Results: Efferent coupling around tremor frequency was seen in 33% of ET patients, 45.5% of healthy controls, all FCMTE patients, and, around 2 Hz, in all ET patients and all healthy controls. Ascending coupling, seen in the majority of all participants, was weaker in ET than in healthy controls around 5–6 Hz. Conclusions: Possible explanations are that tremor in ET results from faulty subcortical output bypassing the motor cortex; rate-dependent transmission similar to generation of rhythmic movements; and/or faulty feedforward mechanism resulting from decreased afferent (sensory) coupling. Significance: A linear cortical drive is lacking in the majority of ET patients.@en

Background: Parkinson's disease (PD) and essential tremor (ET) are neurodegenerative diseases characterized by movement deficits. Especially in PD, maintaining cyclic movement can be significantly disturbed due to pathological changes in the basal ganglia and the cerebellum. Providing external cues improves timing of these movements in PD and also affects ET. The aim of this study is to determine differences in cortical activation patterns in PD and ET patients during externally and internally cued movements. Methods: Eleven PD patients, twelve ET patients, OFF tremor suppressing medication, and nineteen age-matched healthy controls (HC) were included and asked to perform a bimanual tapping task at two predefined cue frequencies. The auditory cue, a metronome sound presented at 2 or 4 Hz, was alternately switched on and off every 30 s. Tapping at two different frequencies were used since it is expected that different brain networks are involved at different frequencies as has been shown in previous studies. Cortical activity was recorded using a 64-channel EEG cap. To establish the cortical activation pattern in each group, the task related power (TRP) was calculated for each subject. For inter-groups analysis, EEG electrodes for divided into 5 different areas. Results: Inter-group analysis revealed significant differences in areas responsible for motor planning, organization and regulation and involved in initiation, maintenance, coordination and planning of complex sequences of movements. Within the area of the primary motor cortex the ET group showed a significantly lower TRP than the HC group. In the area responsible for combining somatosensory, auditory and visual information both patient groups had a higher TRP than the HC group. Conclusions: Different neurological networks are involved during cued and non-cued movements in ET, PD and HC. Distinct cortical activation patterns were revealed using task related power calculations. Different activation patterns were revealed during the 2 and 4 Hz tapping task indicating different strategies to execute movements at these rates. The results suggest that a including a cued/non-cued tapping task during clinical decision making could be a valuable tool in an objective diagnostic protocol.@en

There is no objective gold standard to detect tremors. This concerns not only the choice of the algorithm and sensors, but methods are often designed to detect tremors in one specific group of patients during the performance of a specific task. Therefore, the aim of this study is twofold. First, an objective quantitative method to detect tremor windows (TWs) in accelerometer and electromyography recordings is introduced. Second, the tremor stability index (TSI) is determined to indicate the advantage of detecting TWs prior to analysis. Ten Parkinson's disease (PD) patients, ten essential tremor (ET) patients, and ten healthy controls (HC) performed a resting, postural and movement task. Data was split into 3-s windows, and the power spectral density was calculated for each window. The relative power around the peak frequency with respect to the power in the tremor band was used to classify the windows as either tremor or non-tremor. The method yielded a specificity of 96.45%, sensitivity of 84.84%, and accuracy of 90.80% of tremor detection. During tremors, significant differences were found between groups in all three parameters. The results suggest that the introduced method could be used to determine under which conditions and to which extent undiagnosed patients exhibit tremors.@en