Department of Statistics Unitmark
Dietrich College of Humanities and Social Sciences

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

Publication Date

April, 2014

Publication Type

Tech Report

Author(s)

Sagi Perel, Andrew B. Schwartz, Valerie Ventura

Abstract

Post-spike 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 and Schieber 1998; SSA, Perel et al. 2014); the latter are automatic tests that yield p-values. But MFA/SSA are only effective to detect PSEs that occur about 6-16ms post-trigger. 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 that 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 has 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 2059 datasets from five 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.