Quantifying nonlinear contributions to cortical responses evoked by continuous wrist manipulation

Journal article (2017)

Authors

M.P. Vlaar Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering
T. Solis Escalante Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering
A.N. Vardy Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering
F.C.T. van der Helm Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering
A.C. Schouten Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering
Research Group
Biomechatronics & Human-Machine Control (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2017 M.P. Vlaar, T. Solis Escalante, A.N. Vardy, F.C.T. van der Helm, A.C. Schouten
DOI: https://doi.org/10.1109/TNSRE.2016.2579118
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Published Date

2017

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Biomechanical Engineering

Research Group

Biomechatronics & Human-Machine Control

Abstract

Cortical responses to continuous stimuli as recorded using either magneto- or electroencephalography (EEG) have shown power at harmonics of the stimulated
frequency, indicating nonlinear behavior. Even though the selection of analysis techniques depends on the linearity of the system under study, the importance of nonlinear contributions to cortical responses has not been formally
addressed.The goal of this paper is to quantify the nonlinear contributions to the cortical response obtained fromcontinuous sensory stimulation. EEG was used to record the cortical response evoked by continuousmovement of the wrist joint of healthy subjects applied with a robotic manipulator. Multisine stimulus signals (i.e., the sum of several sinusoids) elicit a periodic cortical response and allowto assess
the nonlinear contributions to the response.Wrist dynamics (relation between joint angle and torque) were successfully linearized, explaining 99% of the response. In contrast, the cortical response revealed a highly nonlinear relation;
where most power ( ∼ 80%) occurred at non-stimulated frequencies. Moreover, only 10% of the response could be explained using a nonparametric linear model. These results indicate that the recorded evoked cortical responses
are governed by nonlinearities and that linear methods do not suffice when describing the relation between mechanical stimulus and cortical response.