μ-Rhythm Extracted With Personalized EEG Filters Correlates With Corticospinal Excitability in Real-Time Phase-Triggered EEG-TMS

Natalie Schaworonkow,Paolo Belardinelli,Christoph Zrenner,Ulf Ziemann,Til Ole Bergmann,Pedro Caldana Gordon

doi:10.3389/fnins.2018.00954

Abstract

Ongoing brain activity has been implicated in the modulation of cortical excitability. The combination of electroencephalography (EEG) and transcranial magnetic stimulation (TMS) in a real-time triggered setup is a novel method for testing hypotheses about the relationship between spontaneous neuronal oscillations, cortical excitability, and synaptic plasticity. For this method, a reliable real-time extraction of the neuronal signal of interest from scalp EEG with high signal-to-noise ratio (SNR) is of crucial importance. Here we compare individually tailored spatial filters as computed by spatial-spectral decomposition (SSD), which maximizes SNR in a frequency band of interest, against established local C3-centered Laplacian filters for the extraction of the sensorimotor μ-rhythm. Single-pulse TMS over the left primary motor cortex was synchronized with the surface positive or negative peak of the respective extracted signal, and motor evoked potentials (MEP) were recorded with electromyography (EMG) of a contralateral hand muscle. Both extraction methods led to a comparable degree of MEP amplitude modulation by phase of the sensorimotor μ-rhythm at the time of stimulation. This could be relevant for targeting other brain regions with no working benchmark such as the local C3-centered Laplacian filter, as sufficient SNR is an important prerequisite for reliable real-time single-trial detection of EEG features.

Highlights

Electroencephalography (EEG) provides access to neural dynamics on a millisecond timescale
For computation of participant-specific spatial filters, we chose spatial-spectral decomposition (SSD) (Nikulin et al, 2011), a method designed to maximize the spectral power in a frequency band of interest while minimizing the power in neighboring (“noise”) frequency bands
Consistent with Zrenner et al (2018), for the Laplacian filter, we found larger motor evoked potential (MEP) amplitudes for N-trials compared to P-trials (Wilcoxon signed-rank test, α = 0.05, p = 0.018, Figure 1D)

Summary

Introduction

Electroencephalography (EEG) provides access to neural dynamics on a millisecond timescale. The relationship between TMS-evoked responses and ongoing oscillatory activity has previously been investigated with different methods regarding spatial filtering, e.g., in channel space (Dugué et al, 2011; Bergmann et al, 2012; Keil et al, 2014), average over channel groups (Mäki and Ilmoniemi, 2010), with current source density (Berger et al, 2014), and with local spatial filters (Thies et al, 2018; Zrenner et al, 2018) These different approaches for defining brain states may explain some of the inconsistent results regarding the relationship between corticospinal excitability as measured by motor evoked potential (MEP) amplitude and features of EEG oscillations. The aim was to compare the degree of modulation of MEP amplitudes by the ongoing phase of the sensorimotor μ-rhythm (μ-phase) (Zrenner et al, 2018) as extracted by the two methods

Methods

Results

Conclusion