ArticleJournal of neurophysiology2014
Statistically rigorous calculations do not support common input and long-term synchronization of motor-unit firings.
Article in Journal of neurophysiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Neuromuscular control: from a biomechanist's perspective.Frontiers in sports and active living · 2023Review
- Exact inter-discharge interval distribution of motor unit firing patterns with gamma model.Medical & biological engineering & computing · 2019Article
- Correlation between discharge timings of pairs of motor units reveals the presence but not the proportion of common synaptic input to motor neurons.Journal of neurophysiology · 2017Article
- Dynamic Increase in Corticomuscular Coherence during Bilateral, Cyclical Ankle Movements.Frontiers in human neuroscience · 2017Article
- The human motor neuron pools receive a dominant slow-varying common synaptic input.The Journal of physiology · 2016Article
- The common input notion, conceived and sustained by conjecture.Journal of neurophysiology · 2016Article
- Synchronization of motor unit firings: an epiphenomenon of firing rate characteristics not common inputs.Journal of neurophysiology · 2016Article
- A Novel Framework Based on FastICA for High Density Surface EMG Decomposition.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2016Article
- Decomposition of surface EMG signals from cyclic dynamic contractions.Journal of neurophysiology · 2015Article
- Error reduction in EMG signal decomposition.Journal of neurophysiology · 2014Article
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2 authors.
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Abstract
Over the past four decades, various methods have been implemented to measure synchronization of motor-unit firings. In this work, we provide evidence that prior reports of the existence of universal common inputs to all motoneurons and the presence of long-term synchronization are misleading, because they did not use sufficiently rigorous statistical tests to detect synchronization. We developed a statistically based method (SigMax) for computing synchronization and tested it with data from 17,736 motor-unit pairs containing 1,035,225 firing instances from the first dorsal interosseous and vastus lateralis muscles--a data set one order of magnitude greater than that reported in previous studies. Only firing data, obtained from surface electromyographic signal decomposition with >95% accuracy, were used in the study. The data were not subjectively selected in any manner. Because of the size of our data set and the statistical rigor inherent to SigMax, we have confidence that the synchronization values that we calculated provide an improved estimate of physiologically driven synchronization. Compared with three other commonly used techniques, ours revealed three types of discrepancies that result from failing to use sufficient statistical tests necessary to detect synchronization. 1) On average, the z-score method falsely detected synchronization at 16 separate latencies in each motor-unit pair. 2) The cumulative sum method missed one out of every four synchronization identifications found by SigMax. 3) The common input assumption method identified synchronization from 100% of motor-unit pairs studied. SigMax revealed that only 50% of motor-unit pairs actually manifested synchronization.
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