Closing the loop

Novel quantitative fMRI approach for manipulation of the sensorimotor loop in tremor

Journal article (2022)

Authors

Sarvi Sharifi Amsterdam UMC, Universiteit van Amsterdam
Frauke Luft University of Twente, Amsterdam UMC
L. de Boer Universiteit van Amsterdam
A. W.G. Buijink Universiteit van Amsterdam
W. Mugge Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering
AC Schouten Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering
Alfred C. Schouten Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering
A.C. Schouten Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering
Tijtske Heida University of Twente
Lo J. Bour Universiteit van Amsterdam
Anne Fleur Van Rootselaar Universiteit van Amsterdam, Amsterdam UMC
Research Group
Biomechatronics & Human-Machine Control (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2022 S. Sharifi, F. Luft, L. de Boer, A. W.G. Buijink, W. Mugge, A.C. Schouten, T. Heida, L. J. Bour, A. F. van Rootselaar
DOI: https://doi.org/10.1016/j.neuroimage.2022.119554
More Info
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Published Date

2022

Language

English

Faculty

Mechanical, Maritime and Materials Engineering

Department

Biomechanical Engineering

Research Group

Biomechatronics & Human-Machine Control

Abstract

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.