Multiple fragment statistical analysis of post-spike effects in spike-triggered averages of rectified EMG

Journal of Neuroscience Methods
A V Poliakov, Marc H Schieber

Abstract

Spike-triggered averaging of EMG is a useful experimental technique for revealing functional connectivity from central neurons to motoneurons. Because EMG waveforms constitute time series, statistical analysis of spike-triggered averages is complicated. Empirical methods generally have been employed to detect the presence of post-spike effects (PSEs), since, as we argue in this report, it is not feasible to develop a rigorous yet sensitive statistical test that detects PSEs in a single grand average of rectified EMG. We have developed a method of multiple fragment statistical analysis (MFSA) of PSEs, based on dividing an experimental record into a large numbers of non-overlapping fragments. The calculations necessary to obtain accurate P-values using the multiple fragment method are simple and efficient, and therefore preliminary results can be obtained while recording. In this report, we present the rationale for MFSA, and give examples of its application. We found MFSA to have considerable utility in accurately testing the significance of small PSEs, and in detecting PSEs in shorter recordings. Statistical corrections that should be used when recording multiple channels simultaneously are discussed. MFSA could be implemented ...Continue Reading

References

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Citations

Nov 24, 2006·Journal of Neurophysiology·M M MorrowL E Miller
Oct 10, 2013·Neural Computation·Sagi PerelValérie Ventura
May 5, 2007·Journal of Neuroscience Methods·Adam G DavidsonMarc H Schieber
Oct 13, 2006·Journal of Neurophysiology·Marc H Schieber, Gil Rivlis
Jan 10, 2019·International Journal of Environmental Research and Public Health·Miloš GejdošŽaneta Balážová
Jul 26, 2017·Proceedings of the National Academy of Sciences of the United States of America·Tomohiko TakeiKazuhiko Seki
Apr 25, 2014·Journal of Neurophysiology·Sagi PerelValérie Ventura

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