K E Brown1, K R Lohse2, I M S Mayer3, G Strigaro4, M Desikan4, E P Casula4, S Meunier5, T Popa5, J-C Lamy5, O Odish6, B R Leavitt7, A Durr5, R A C Roos6, S J Tabrizi8, J C Rothwell4, L A Boyd1, M Orth9. 1. Department of Physical Therapy, University of British Columbia, Vancouver, BC, Canada. 2. College of Health, University of Utah, Salt Lake City, UT, USA. 3. Department of Neurology, Ulm University Hospital, Ulm, Germany; Sobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, University College London, London, UK. 4. Sobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, University College London, London, UK. 5. APHP Department of Genetics, Groupe Hospitalier Pitié-Salpêtrière, Institut du Cerveau et de la Moelle, INSERM U1127, CNRS UMR7225, Sorbonne Universités - UPMC Université Paris VI UMR_S1127, Paris, France. 6. Department of Neurology, Leiden University Medical Centre, 2300RC Leiden, The Netherlands. 7. Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, University of British Columbia, 950 West 28th Avenue, Vancouver, BC V5Z 4H4, Canada. 8. Huntington's Disease Research Centre, UCL Institute of Neurology, London, UK. 9. Department of Neurology, Ulm University Hospital, Ulm, Germany. Electronic address: michael.orth@uni-ulm.de.
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.
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.
Authors: Andris Cerins; Daniel Corp; George Opie; Michael Do; Bridgette Speranza; Jason He; Pamela Barhoun; Ian Fuelscher; Peter Enticott; Christian Hyde Journal: Sci Rep Date: 2022-06-15 Impact factor: 4.996
Authors: Daniel T Corp; Hannah G K Bereznicki; Gillian M Clark; George J Youssef; Peter J Fried; Ali Jannati; Charlotte B Davies; Joyce Gomes-Osman; Julie Stamm; Sung Wook Chung; Steven J Bowe; Nigel C Rogasch; Paul B Fitzgerald; Giacomo Koch; Vincenzo Di Lazzaro; Alvaro Pascual-Leone; Peter G Enticott Journal: Brain Stimul Date: 2020-08-03 Impact factor: 8.955
Authors: Joyce Gomes-Osman; Aprinda Indahlastari; Peter J Fried; Danylo L F Cabral; Jordyn Rice; Nicole R Nissim; Serkan Aksu; Molly E McLaren; Adam J Woods Journal: Front Aging Neurosci Date: 2018-06-08 Impact factor: 5.750
Authors: Martin Hardmeier; François Jacques; Philipp Albrecht; Habib Bousleiman; Christian Schindler; Letizia Leocani; Peter Fuhr Journal: Mult Scler J Exp Transl Clin Date: 2019-05-01
Authors: Susan M Hunter; Heidi Johansen-Berg; Nick Ward; Niamh C Kennedy; Elizabeth Chandler; Christopher John Weir; John Rothwell; Alan M Wing; Michael J Grey; Garry Barton; Nick Malachy Leavey; Claire Havis; Roger N Lemon; Jane Burridge; Amy Dymond; Valerie M Pomeroy Journal: Front Neurol Date: 2018-01-25 Impact factor: 4.003
Authors: Tulika Nandi; Claudine J C Lamoth; Helco G van Keeken; Lisanne B M Bakker; Iris Kok; George J Salem; Beth E Fisher; Tibor Hortobágyi Journal: Front Hum Neurosci Date: 2018-07-30 Impact factor: 3.169