Large-scale analysis of interindividual variability in theta-burst stimulation data: Results from the ‘Big TMS Data Collaboration’

Autor: Steven J. Bowe, Charlotte B. Davies, Giacomo Koch, Peter G. Enticott, Vincenzo Di Lazzaro, Nigel C. Rogasch, Ali Jannati, Sung Wook Chung, George J. Youssef, Daniel T. Corp, Julie Stamm, Alvaro Pascual-Leone, Paul B. Fitzgerald, Peter J. Fried, Joyce Gomes-Osman, Gillian M. Clark, Hannah G.K. Bereznicki
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Data Analysis
Male
CTBS
Individuality
Audiology
0302 clinical medicine
Time of day
Transcranial
and magnetic stimulation
Theta Rhythm
Intersectoral Collaboration
Aged
80 and over
Neuronal Plasticity
General Neuroscience
05 social sciences
Motor Cortex
Middle Aged
16. Peace & justice
Transcranial Magnetic Stimulation
Response Variability
Healthy Volunteers
Regression
Big data
Theta-burst stimulation
Transcranial and magnetic stimulation
Variability
Female
Psychology
Adult
medicine.medical_specialty
Data collaboration
Adolescent
Biophysics
Article
050105 experimental psychology
NO
Transcranial and magnetic stimulation
lcsh:RC321-571
Scale analysis (statistics)
Young Adult
03 medical and health sciences
Big data
medicine
Humans
0501 psychology and cognitive sciences
Variability
lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry
Aged
Theta-burst stimulation
Small sample
Evoked Potentials
Motor
Theta burst
Neurology (clinical)
030217 neurology & neurosurgery
Zdroj: Brain Stimulation, Vol 13, Iss 5, Pp 1476-1488 (2020)
Brain Stimul
Popis: Background Many studies have attempted to identify the sources of interindividual variability in response to theta-burst stimulation (TBS). However, these studies have been limited by small sample sizes, leading to conflicting results. Objective/Hypothesis This study brought together over 60 TMS researchers to form the ‘Big TMS Data Collaboration’, and create the largest known sample of individual participant TBS data to date. The goal was to enable a more comprehensive evaluation of factors driving TBS response variability. Methods 118 corresponding authors of TMS studies were emailed and asked to provide deidentified individual TMS data. Mixed-effects regression investigated a range of individual and study level variables for their contribution to iTBS and cTBS response variability. Results 430 healthy participants’ TBS data was pooled across 22 studies (mean age = 41.9; range = 17–82; females = 217). Baseline MEP amplitude, age, target muscle, and time of day significantly predicted iTBS-induced plasticity. Baseline MEP amplitude and timepoint after TBS significantly predicted cTBS-induced plasticity. Conclusions This is the largest known study of interindividual variability in TBS. Our findings indicate that a significant portion of variability can be attributed to the methods used to measure the modulatory effects of TBS. We provide specific methodological recommendations in order to control and mitigate these sources of variability.
Databáze: OpenAIRE
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