Frequency and wavelet based analyses of partial and complete measure synchronization in a system of three nonlinearly coupled oscillators

2018 ◽  
Vol 28 (11) ◽  
pp. 113108 ◽  
Author(s):  
Sadhitro De ◽  
Shraddha Gupta ◽  
M. S. Janaki ◽  
A. N. Sekar Iyengar
Keyword(s):  
Coupled Oscillators ◽  
Measure Synchronization

Temperature, heat, and work, for a system of two coupled oscillators

2021 ◽  
Vol 572 ◽  
pp. 125905
Author(s):  
Seyyedeh Fatemeh Hoseini ◽  
Mohammad Khorrami ◽  
Amir Aghamohammadi
Keyword(s):  
Coupled Oscillators ◽  
Temperature Heat

Multi-headed loop chimera states in coupled oscillators

2021 ◽  
Vol 31 (1) ◽  
pp. 013135
Author(s):  
Dawid Dudkowski ◽  
Krzysztof Czołczyński ◽  
Tomasz Kapitaniak
Keyword(s):  
Coupled Oscillators ◽  
Chimera States

scholarly journals Statistically rigorous calculations do not support common input and long-term synchronization of motor-unit firings

2014 ◽  
Vol 112 (11) ◽  
pp. 2729-2744 ◽  
Author(s):  
Carlo J. De Luca ◽  
Joshua C. Kline
Keyword(s):  
Motor Unit ◽  
Statistical Tests ◽  
Vastus Lateralis ◽  
Common Input ◽  
Data Set ◽  
Order Of Magnitude ◽  
Score Method ◽  
Surface Electromyographic Signal ◽  
Measure Synchronization

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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