Brown, KE;
Lohse, KR;
Mayer, IMS;
Strigaro, G;
Desikan, M;
Casula, EP;
Meunier, S;
... Orth, M; + view all
(2017)
The reliability of commonly used electrophysiology measures.
Brain Stimulation
, 10
(6)
pp. 1102-1111.
10.1016/j.brs.2017.07.011.
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Abstract
Background: Electrophysiological measures can help understand brain function both in healthy individuals and in the context of a disease. Given the amount of information that can be extracted from these measures and their frequent use, it is essential to know more about their inherent reliability. / Objective/Hypothesis: To understand the reliability of electrophysiology measures in healthy individuals. We hypothesized that measures of threshold and latency would be the most reliable and least susceptible to methodological differences between study sites. / Methods: Somatosensory evoked potentials from 112 control participants; long-latency reflexes, transcranial magnetic stimulation with resting and active motor thresholds, motor evoked potential latencies, input/output curves, and short-latency sensory afferent inhibition and facilitation from 84 controls were collected at 3 visits over 24 months at 4 Track-On HD study sites. Reliability was assessed using intra-class correlation coefficients for absolute agreement, and the effects of reliability on statistical power are demonstrated for different sample sizes and study designs. / Results: Measures quantifying latencies, thresholds, and evoked responses at high stimulator intensities had the highest reliability, and required the smallest sample sizes to adequately power a study. Very few between-site differences were detected. / Conclusions: Reliability and susceptibility to between-site differences should be evaluated for electrophysiological measures before including them in study designs. Levels of reliability vary substantially across electrophysiological measures, though there are few between-site differences. To address this, reliability should be used in conjunction with theoretical calculations to inform sample size and ensure studies are adequately powered to detect true change in measures of interest.
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