Essential tremor is associated with disruption of functional connectivity in the ventral intermediate Nucleus--Motor Cortex--Cerebellum circuit.

The clinical benefits of targeting the ventral intermediate nucleus (VIM) for the treatment of tremors in essential tremor (ET) patients suggest that the VIM is a key hub in the network of tremor generation and propagation and that the VIM can be considered as a seed region to study the tremor network. However, little is known about the central tremor network in ET patients. Twenty-six ET patients and 26 matched healthy controls (HCs) were included in this study. After considering structural and head-motion factors and establishing the accuracy of our seed region, a VIM seed-based functional connectivity (FC) analysis of resting-state functional magnetic resonance imaging (RS-fMRI) data was performed to characterize the VIM FC network in ET patients. We found that ET patients and HCs shared a similar VIM FC network that was generally consistent with the VIM anatomical connectivity network inferred from normal nonhuman primates and healthy humans. Compared with HCs, ET patients displayed VIM-related FC changes, primarily within the VIM-motor cortex (MC)-cerebellum (CBLM) circuit, which included decreased FC in the CBLM and increased FC in the MC. Importantly, tremor severity correlated with these FC changes. These findings provide the first evidence that the pathological tremors observed in ET patients might be based on a physiologically pre-existing VIM - MC - CBLM network and that disruption of FC in this physiological network is associated with ET. Further, these findings demonstrate a potential approach for elucidating the neural network mechanisms underlying this disease.

Multiple Resting-State Networks Are Associated With Tremors and Cognitive Features in Essential Tremor.

INTRODUCTION: The heterogeneous clinical features of essential tremor indicate that the dysfunctions of this syndrome are not confined to motor networks, but extend to nonmotor networks. Currently, these neural network dysfunctions in essential tremor remain unclear. In this study, independent component analysis of resting-state functional MRI was used to study these neural network mechanisms. METHODS: Thirty-five essential tremor patients and 35 matched healthy controls with clinical and neuropsychological tests were included, and eight resting-state networks were identified. After considering the structure and head-motion factors and testing the reliability of the selected resting-state networks, we assessed the functional connectivity changes within or between resting-state networks. Finally, image-behavior correlation analysis was performed. RESULTS: Compared to healthy controls, essential tremor patients displayed increased functional connectivity in the sensorimotor and salience networks and decreased functional connectivity in the cerebellum network. Additionally, increased functional network connectivity was observed between anterior and posterior default mode networks, and a decreased functional network connectivity was noted between the cerebellum network and the sensorimotor and posterior default mode networks. Importantly, the functional connectivity changes within and between these resting-state networks were correlated with the tremor severity and total cognitive scores of essential tremor patients. CONCLUSIONS: The findings of this study provide the first evidence that functional connectivity changes within and between multiple resting-state networks are associated with tremors and cognitive features of essential tremor, and this work demonstrates a potential approach for identifying the underlying neural network mechanisms of this syndrome.