motoRneuron: motoRneuron: A package for computing motor unit analyses
In tweedell/motoRneuron: Analyzing Paired Neuron Discharge Times for Time-Domain Synchronization
Description
About
Details
Methods for Peak Determination
Synchronization Indices
Authors
References
Description
The motoRneuron package provides functions for time-domain analyses of motor
units.
About
The motoRneuron package was developed at the United States
Army Research Laboratory.
Details
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.
Methods for Peak Determination
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)
Synchronization Indices
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)
Authors
Andrew Tweedell and Matthew Tenan, maintainer: Andrew Tweedell
(andrew.j.tweedell.civ@mail.mil)
References
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
tweedell/motoRneuron documentation built on June 21, 2019, 10:43 p.m.
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Description About Details Methods for Peak Determination Synchronization Indices Authors References
Description
The motoRneuron package provides functions for time-domain analyses of motor units.
About
The motoRneuron package was developed at the United States Army Research Laboratory.
Details
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.
Methods for Peak Determination
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)
Synchronization Indices
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)
Authors
Andrew Tweedell and Matthew Tenan, maintainer: Andrew Tweedell (andrew.j.tweedell.civ@mail.mil)
References
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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