Automatic scan test for detection of functional connectivity between cortex and muscles

Postspike effects (PSEs) in averages of spike-triggered EMG snippets provide physiological evidence of connectivity between CMN cells and spinal motoneurons innervating skeletal muscles. They are typically detected by visual inspection of spike-triggered averages (SpTAs) or by multiple-fragment/single-snippet analyses [MFA (Poliakov AV, Schieber MH. J Neurosci Methods 79: 143–150, 1998) and SSA (Perel S, Schwartz AB, Ventura V. Neural Comput 26: 40–56, 2014)]; the latter are automatic tests that yield P values. However, MFA/SSA are only effective to detect PSEs that occur at about 6–16 ms posttrigger. Our first contribution is the scan test, an automatic test that has the same utility as SpTA, i.e., it can detect a wide range of PSEs at any latency, but it also yields a P value. Our second contribution is a thorough investigation of the statistical properties of PSE detection tests. We show that when the PSE is weak or the sample size is small, visual inspections of SpTAs have low power, because it is difficult to distinguish PSEs from background EMG variations. We also show that the scan test has better power and that its rate of spurious detections matches the chosen significance level α. This is especially important for investigators because, when a PSE is detected, this guarantees that the probability of a spurious PSE is less than α. Finally, we illustrate the operational characteristics of the PSE detection tests on 2,059 datasets from 5 experiments. The scan test is particularly useful to identify candidate PSEs, which can then be subject to further evaluation by SpTA inspection, and when PSEs are small and visual detection is ambiguous.