The motoRneuron package provides functions for time-domain analyses of motor units.
The motoRneuron package was developed at the United States Army Research Laboratory.
The motoRneuron package provides functions to compute time-domain synchronization between the two motor unit discharge trains. MotoRneuron's primary functions configure and assess the cross correlation histogram between motor unit discharge trains for a "peak". Peaks indicate more synchronized firing at that latency than would be expected due to chance. The magnitude of the peak is also thought to indicate the strength of common input between the motor units and is characterized by synchronization "indices", listed below. Three methods are available for assessing the peak in the histogram. Details of specific methods are documented in their respective help files. Motor unit characteristic data and interspike intervals are automatically output.
'Recurrence_intervals', 'bin', and 'plot_bins' are support functions used within the core functions, but can also be called separately for individual use. Recurrence_intervals() calculates recurrence intervals between two motor unit discharge trains. Bin() discretizes the recurrence intervals into user-specified bins. Plot_bins() leverages ggplot2 to plot the resulting histogram.
Visual method - subjective analysis of normalized cumulative sum graph to determine peak location. (Nordstrom, Fuglevand, and Enoka, 1992)
Z-score method - a random uniform distribution is used to calculate a mean + 1.96 standard deviation threshold for the experimental cross correlation histogram. Any bins of the experimental histogram within +/- 10 ms of 0 that crossed the threshold are considered to be significantly greater than expected due to chance and subsequently used for analysis. (Defreitas, Beck, Xin, and Stock, 2013)
Cumulative Sum (cumsum) method - the cumulative sum of the bin count of the histogram is calculated. The peak boundaries are calculated as 10 the range (maximum minus minimum) of the cumulative sum. The peak is considered significant if its mean bin count exceeds the sum of the mean and 1.96 * standard deviation of the baseline bins (<= -60 ms and >= 60 ms). If no significant peak is detected, a default +/- 5 ms peak is used. (Keen, D.A., Chou, L., Nordstrom, M.A., Fuglevand, A.J., 2012)
CIS = frequency of synchronized discharges. (Nordstrom, Fuglevand, and Enoka, 1992)
k' = ratio of synchronized discharges to expected discharges in peak. (Kamen & Roy, 2000)
k'-1 = ratio of extra synchronized discharges to expected discharges in peak. (Kamen & Roy, 2000)
S = ratio of synchronized discharges to total number of discharges of both motor units. (Nordstrom, Fuglevand, and Enoka, 1992)
E = ratio of synchronized discharges to non-synchronized discharges. (Datta & Stephens 1990)
SI = ratio of synchronized discharges to reference motor unit discharges. (Defreitas, Beck, Xin, and Stock, 2013)
Andrew Tweedell and Matthew Tenan, maintainer: Andrew Tweedell (email@example.com)
Datta, A.K., & Stephens, J.A. (1990) Synchronization of Motor Unit Activity During Voluntary Contraction in Man. Journal of Physiology 422: 397-419
DeFreitas, J.M., Beck, T.W., Xin, Y., Stock, M.S. (2013) Synchronization of Low- and High-Threshold Motor Units. Muscle & Nerve DOI 10.1002/mus.23978
Kamen, G. & Roy, A. (2000) Motor Unit Synchronization in Young and Elderly Adults. European Journal of Applied Physiology. 81: 403-410
Keen, D.A., Chou, L., Nordstrom, M.A., Fuglevand, A.J. (2012) Short-term Synchrony in Diverse Motor Nuclei Presumed to Receive Different Extents of Direct Cortical Input. Journal of Neurophysiology 108: 3264-3275
Nordstrom, M.A., Fuglevand, A.J., Enoka, R.M. (1992) Estimating the Strength of Common Input to Human Motoneurons from the Cross-Correlogram. Journal of Physiology 453, pp. 547-574
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