Rectification of EMG in low force contractions improves detection of motor unit coherence in the beta-frequency band

Rectification of surface EMG before spectral analysis is a well-established preprocessing method used in the detection of motor unit firing patterns. A number of recent studies have called into question the need for rectification before spectral analysis, pointing out that there is no supporting experimental evidence to justify rectification. We present an analysis of 190 records from 13 subjects consisting of simultaneous recordings of paired single motor units and surface EMG from the extensor digitorum longus muscle during middle finger extension against gravity (unloaded condition) and against gravity plus inertial loading (loaded condition). We directly examine the hypothesis that rectified surface EMG is a better predictor of the frequency components of motor unit synchronization than the unrectified (or raw) EMG in the beta-frequency band (15–32 Hz). We use multivariate analysis and estimate the partial coherence between the paired single units using both rectified and unrectified surface EMG as a predictor. We use a residual partial correlation measure to quantify the difference between raw and rectified EMG as predictor and analyze unloaded and loaded conditions separately. The residual correlation for the unloaded condition is 22% with raw EMG and 3.5% with rectified EMG and for the loaded condition it is 5.2% with raw EMG and 1.4% with rectified EMG. We interpret these results as strong supporting experimental evidence in favor of using the preprocessing step of surface EMG rectification before spectral analysis.

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Rectification is required to extract oscillatory envelope modulation from surface electromyographic signals

Journal of Neurophysiology ◽

10.1152/jn.00296.2014 ◽

2014 ◽

Vol 112 (7) ◽

pp. 1685-1691 ◽

Cited By ~ 19

Author(s):

Christopher J. Dakin ◽

Brian H. Dalton ◽

Billy L. Luu ◽

Jean-Sébastien Blouin

Keyword(s):

Motor Unit ◽

Stimulus Frequency ◽

Motor Units ◽

Surface Emg ◽

Medial Gastrocnemius ◽

Single Motor Unit ◽

Single Motor ◽

Single Motor Units ◽

Emg Signal ◽

Envelope Modulation

Rectification of surface electromyographic (EMG) recordings prior to their correlation with other signals is a widely used form of preprocessing. Recently this practice has come into question, elevating the subject of EMG rectification to a topic of much debate. Proponents for rectifying suggest it accentuates the EMG spike timing information, whereas opponents indicate it is unnecessary and its nonlinear distortion of data is potentially destructive. Here we examine the necessity of rectification on the extraction of muscle responses, but for the first time using a known oscillatory input to the muscle in the form of electrical vestibular stimulation. Participants were exposed to sinusoidal vestibular stimuli while surface and intramuscular EMG were recorded from the left medial gastrocnemius. We compared the unrectified and rectified surface EMG to single motor units to determine which method best identified stimulus-EMG coherence and phase at the single-motor unit level. Surface EMG modulation at the stimulus frequency was obvious in the unrectified surface EMG. However, this modulation was not identified by the fast Fourier transform, and therefore stimulus coherence with the unrectified EMG signal failed to capture this covariance. Both the rectified surface EMG and single motor units displayed significant coherence over the entire stimulus bandwidth (1–20 Hz). Furthermore, the stimulus-phase relationship for the rectified EMG and motor units shared a moderate correlation ( r = 0.56). These data indicate that rectification of surface EMG is a necessary step to extract EMG envelope modulation due to motor unit entrainment to a known stimulus.

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Depth of anaesthesia assessment based on adult electroencephalograph beta frequency band

Australasian Physical & Engineering Sciences in Medicine ◽

10.1007/s13246-016-0459-5 ◽

2016 ◽

Vol 39 (3) ◽

pp. 773-781 ◽

Cited By ~ 1

Author(s):

Tianning Li ◽

Peng Wen

Keyword(s):

Frequency Band ◽

Depth Of Anaesthesia ◽

Beta Frequency Band ◽

Beta Frequency

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An experimental and model based investigation of the potential and limitations of surface EMG spectral analysis for assessment of motor unit recruitment strategy

2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society ◽

10.1109/iembs.2001.1020410 ◽

2005 ◽

Author(s):

D. Farina ◽

R. Merletti

Keyword(s):

Spectral Analysis ◽

Motor Unit ◽

Surface Emg ◽

Motor Unit Recruitment ◽

Recruitment Strategy ◽

Model Based

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Effects of sertraline on brain current source of the high beta frequency band: analysis of electroencephalography during audiovisual erotic stimulation in males with premature ejaculation

International Journal of Impotence Research ◽

10.1038/ijir.2011.30 ◽

2011 ◽

Vol 23 (5) ◽

pp. 213-219 ◽

Cited By ~ 8

Author(s):

O Y Kwon ◽

S C Kam ◽

J H Choi ◽

J M Do ◽

J S Hyun

Keyword(s):

Frequency Band ◽

Premature Ejaculation ◽

Current Source ◽

Beta Frequency Band ◽

Erotic Stimulation ◽

High Beta ◽

Beta Frequency

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Analysis of correlation between body mass index (BMI) and brain wave using EEG for Alpha and Beta frequency band

2009 5th International Colloquium on Signal Processing & Its Applications ◽

10.1109/cspa.2009.5069234 ◽

2009 ◽

Cited By ~ 1

Author(s):

Ros Shilawani S. Abdul Kadir ◽

Azlan Hakimi Yahaya Rashid ◽

Husna Abdul Rahman ◽

Mohd Nasir Taib ◽

Zunairah Hj. Murat ◽

...

Keyword(s):

Body Mass Index ◽

Body Mass ◽

Frequency Band ◽

Brain Wave ◽

Beta Frequency Band ◽

Beta Frequency

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Surprise About Sensory Event Timing Drives Cortical Transients in the Beta Frequency Band

10.1101/254060 ◽

2018 ◽

Author(s):

T. Meindertsma ◽

N.A. Kloosterman ◽

A.K. Engel ◽

E.J. Wagenmakers ◽

T.H. Donner

Keyword(s):

Frequency Band ◽

Ideal Observer ◽

Beta Band ◽

Statistical Structure ◽

Population Activity ◽

Sensory Event ◽

Event Timing ◽

Beta Frequency Band ◽

Observer Model ◽

Beta Frequency

AbstractLearning the statistical structure of the environment is crucial for adaptive behavior. Humans and non-human decision-makers seem to track such structure through a process of probabilistic inference, which enables predictions about behaviorally relevant events. Deviations from such predictions cause surprise, which in turn helps improve inference. Surprise about the timing of behaviorally relevant sensory events drives phasic responses of neuromodulatory brainstem systems, which project to the cerebral cortex. Here, we developed a computational model-based magnetoencephalography (MEG) approach for mapping the resulting cortical transients across space, time, and frequency, in the human brain (N=28, 17 female). We used a Bayesian ideal observer model to learn the statistics of the timing of changes in a simple visual detection task. This model yielded quantitative trial-by-trial estimates of temporal surprise. The model-based surprise variable predicted trial-by trial variations in reaction time more strongly than the externally observable interval timings alone. Trial-by-trial variations in surprise were negatively correlated with the power of cortical population activity measured with MEG. This surprise-related power suppression occurred transiently around the behavioral response, specifically in the beta frequency band. It peaked in parietal and prefrontal cortices, remote from the motor cortical suppression of beta power related to overt report (button press) of change detection. Our results indicate that surprise about sensory event timing transiently suppresses ongoing beta-band oscillations in association cortex. This transient suppression of frontal beta-band oscillations might reflect an active reset triggered by surprise, and is in line with the idea that beta-oscillations help maintain cognitive sets.Significance statementThe brain continuously tracks the statistical structure of the environment to anticipate behaviorally relevant events. Deviations from such predictions cause surprise, which in turn drives neural activity in subcortical brain regions that project to the cerebral cortex. We used magnetoencephalography in humans to map out surprise-related modulations of cortical population activity across space, time, and frequency. Surprise was elicited by variable timing of visual stimulus changes requiring a behavioral response. Surprise was quantified by means of an ideal observer model. Surprise predicted behavior as well as a transient suppression of beta frequency band oscillations in frontal cortical regions. Our results are in line with conceptual accounts that have linked neural oscillations in the beta-band to the maintenance of cognitive sets.

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