A general approach for quantifying nonlinear connectivity in the nervous system based on phase coupling

Journal Article (2016)
Author(s)

Y. Yang (TU Delft - Biomechatronics & Human-Machine Control)

T Solis-Escalante (TU Delft - Biomechatronics & Human-Machine Control)

J Yao (External organisation)

A Daffertshofer (External organisation)

A.C. Schouten (TU Delft - Biomechatronics & Human-Machine Control)

F. C.T. Van Der Helm (TU Delft - Biomechatronics & Human-Machine Control)

Research Group
Biomechatronics & Human-Machine Control
DOI related publication
https://doi.org/10.1142/S0129065715500318
More Info
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Publication Year
2016
Language
English
Research Group
Biomechatronics & Human-Machine Control
Issue number
1
Volume number
26

Abstract

Interaction between distant neuronal populations is essential for communication within the nervous system and can occur as a highly nonlinear process. To better understand the functional role of neural interactions, it is important to quantify the nonlinear connectivity in the nervous system. We introduce a general approach to measure nonlinear connectivity through phase coupling: the multi-spectral phase coherence (MSPC). Using simulated data, we compare MSPC with existing phase coupling measures, namely n : m synchronization index and bi-phase locking value. MSPC provides a system description, including (i) the order of the nonlinearity, (ii) the direction of interaction, (iii) the time delay in the system, and both (iv) harmonic and (v) intermodulation coupling beyond the second order; which are only partly revealed by other methods. We apply MSPC to analyze data from a motor control experiment, where subjects performed isotonic wrist flexions while receiving movement perturbations. MSPC between the perturbation, EEG and EMG was calculated. Our results reveal directional nonlinear connectivity in the afferent and efferent pathways, as well as the time delay (43±8ms) between the perturbation and the brain response. In conclusion, MSPC is a novel approach capable to assess high-order nonlinear interaction and timing in the nervous system.

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