Influence of High Pass Filter Settings on Motor Evoked Potentials

Nikolov, Petyo; Hassan, Shady Safwat; Schnitzler, Alfons; Groiss, Stefan Jun

doi:10.3389/fnins.2021.665258

Cited by 5 publications

(4 citation statements)

References 11 publications

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“…The derivative-based method provided very small errors across the full spectrum of signal-to-noise ratios (SNRs) computed as the ratio between the MEP peak-to-peak amplitude and the maximum noise in the baseline as suggested by [21]. In particular, the largest errors occurred at very low SNR and never at high values, in a comparable fashion to human raters (see additional file 3).…”

Section: Algorithms' Performancementioning

confidence: 79%

“…The latter risks to be present especially when latency is used to make comparisons: as a diagnostic measure to differentiate healthy from pathological; or in a research setting to study stimulation paradigms effects (e.g. to evaluate the effect of different current directions of TMS on excitability of the corticospinal tract [21]). Given the high accuracy in the healthy dataset, this new tool opens possibilities to answering further research questions related to cortico-spinal tract conduction times and brainnetwork science.…”

Section: Discussionmentioning

confidence: 99%

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An automatized method to determine latencies of motor-evoked potentials under physiological and pathophysiological conditions

et al. 2022

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Background: Latencies of motor evoked potentials (MEP) can provide insights into the motor neuronal pathways activated by transcranial magnetic stimulation (TMS). Notwithstanding its clinical relevance, accurate, unbiased methods to automatize latency detection are still missing. Objective: We present a novel open-source algorithm suitable for MEP onset/latency detection during resting state that only requires the post-stimulus electromyography signal and exploits the approximation of the first derivative of this signal to find the time point of initial deflection of the MEP. Methods: The algorithm has been benchmarked, using intra-class coefficient (ICC) and effect sizes, to manual detection of latencies done by three researchers independently on a dataset comprising almost 6500 MEP trials from healthy participants (n=18) and stroke patients (n=31) acquired during rest. The performance was further compared to currently available automatized methods, some of which created for active contraction protocols. Results: The unstandardized effect size between the human raters and the present method is smaller than the sampling period for both healthy and pathological MEPs. Moreover, the ICC increases when the algorithm is added as a rater. Conclusion: The present algorithm is comparable to human expert decision and outperforms currently available methods. It provides a promising method for automated MEP latency detection under physiological and pathophysiological conditions.

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Section: Algorithms' Performancementioning

confidence: 79%

Section: Discussionmentioning

confidence: 99%

An automatized method to determine latencies of motor-evoked potentials under physiological and pathophysiological conditions

et al. 2022

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“…A very recently published study [35] investigated the problem of filtering MEPs with a view to reducing the signal-to-noise ratio. Here, too, it could be shown that the filters with the lowest cutoff frequency (10 Hz and 20 Hz in this case) showed the lowest amplitude distortion and, moreover, they were able to show that better signal-to-noise ratio could be achieved for these filter parameters as well.…”

Section: Discussionmentioning

confidence: 99%

Comparing Different Filter-Parameter for Pre-Processing of Brain-Stimulation Evoked Motor Potentials

Zschorlich

Wolff

2021

Brain Sciences

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Background: Brain stimulation motor-evoked potentials (MEPs) are transient signals and not periodic signals, and thus, they differ significantly in their properties from classical surface electromyograms. Unsuitable pre-processing of MEPs due to inappropriate filter settings leads to distortions. Filtering of extensor carpi radialis MEPs with transient signal characteristics of 20 subjects was examined. The effects of a 1st-order Butterworth high-pass filter (HPF) with different cut-off frequencies 1 Hz, 20 Hz, 40 Hz, and 80 Hz and a 5 Hz Butterworth high-pass filter with degrees 1st, 2nd, 4th, 8th-order are investigated for the filter output. Results: The filtering of the MEPs with an inappropriate filter setting led to distortions on the parameters peak-to-peak amplitudes of the MEP (MEPpp) and the absolute integral of the MEP (MEParea). The lowest distortions of all of the examined filter parameters were revealed after filtering with the lowest filter order and the lowest cut-off frequency. The 1st-order 1 Hz HPF calculation results in a difference of −0.53% (p < 0.001) for the MEPpp and −1.94% (p < 0.001) for the MEParea. Significance: Reproducibility is a major concern in science, including brain stimulation research. Only the filtering of the MEPs with appropriate filter settings led to mostly undistorted MEPs.

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“…RMT is defined as the minimum stimulation intensity that motor-evoked potential (MEP) is significant in at least half of the trials. A trial is considered a success when MEP has minimal value of 50 μV (usually 50–100 μV) [ 25 , 26 ]. Thanks to neuronavigation, it was easy to find a hotspot and achieve a high MEP for all participants in almost all trials.…”

Section: Methodsmentioning

confidence: 99%

Recognition and Processing of Visual Information after Neuronavigated Transcranial Magnetic Stimulation Session

et al. 2022

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Background: Transcranial magnetic stimulation (TMS) is a method of noninvasive and painless stimulation of the nervous system, which is based on Faraday’s law of electromagnetic induction. Over the past twenty years, the TMS technique has been deployed as a tool for the diagnosis and therapy of neurodegenerative diseases, as well as in the treatment of mental disorders (e.g., depression). Methods: We tested the inhibitory effects of repetitive TMS (rTMS) on reaction times to militarily relevant visual stimuli amidst distractors and on accompanying blood oxygenation level dependent (BOLD) signal functional magnetic resonance imaging (fMRI) in 20 healthy people. rTMS was applied over the visual cortices, V1, on both hemispheres with the inhibitory theta burst paradigm with the intensity of 70% of the active motor threshold fMRI in 20 healthy people. Results: Analysis of the reaction time to visual stimuli after using TMS to the V1 visual cortex revealed an increase in the number of incorrect recognitions, and the reaction time was from 843 to 910 ms. In the subgroup of participants (n = 15), after the stimulation, there were significant reductions of BOLD signal in blood flow within V1 cortices. Conclusions: The studies of reaction times after the rTMS revealed the inhibitory effect of rTMS on the reaction times and recognition performance of significant (military) objects in the visual field.

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Influence of High Pass Filter Settings on Motor Evoked Potentials

Cited by 5 publications

References 11 publications

An automatized method to determine latencies of motor-evoked potentials under physiological and pathophysiological conditions

An automatized method to determine latencies of motor-evoked potentials under physiological and pathophysiological conditions

Comparing Different Filter-Parameter for Pre-Processing of Brain-Stimulation Evoked Motor Potentials

Recognition and Processing of Visual Information after Neuronavigated Transcranial Magnetic Stimulation Session

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