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 ¼ 41.9; range ¼ 17 e82; females ¼ 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 cTBSinduced 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.
ObjectiveInterindividual variability of single and paired-pulse TMS data has limited the clinical and experimental applicability of these methods. This study brought together over 60 TMS researchers to create the largest known sample of individual participant single and paired-pulse TMS data to date, enabling a more comprehensive evaluation of factors driving response variability.Methods118 corresponding authors provided deidentified individual TMS data. Mixed-effects regression investigated a range of individual and study level variables for their contribution to variability in response to single and pp TMS data.Results687 healthy participant’s TMS data was pooled across 35 studies. Target muscle, pulse waveform, neuronavigation use, and TMS machine significantly predicted an individual’s single pulse TMS amplitude. Baseline MEP amplitude, M1 hemisphere, and biphasic AMT significantly predicted SICI response. Baseline MEP amplitude, test stimulus intensity, interstimulus interval, monophasic RMT, monophasic AMT, and biphasic RMT significantly predicted ICF response. Age, M1 hemisphere, and TMS machine significantly predicted motor threshold.ConclusionsThis large-scale analysis has identified a number of factors influencing participants’ responses to single and paired pulse TMS. We provide specific recommendations to increase the standardisation of TMS methods within and across laboratories, thereby minimising interindividual variability in single and pp TMS data.Highlights687 healthy participant’s TMS data was pooled across 35 studiesSignificant relationships between age and resting motor thresholdSignificant relationships between baseline MEP amplitude and SICI/ICF
Background: Off-time puberty is considered to be an important risk factor for mental health problems during early adolescence. The current study undertook a comprehensive investigation of whether the social environment can buffer or amplify the potential consequences of off-time puberty for mental health. Methods: Research questions were examined in the Adolescent Brain Cognitive Development (ABCD) Study, a large population representative sample in the United States. We examined interactions between pubertal timing and the shared and unique effects of a range of proximal and distal social environmental influences (i.e., parents, peers, schools, neighborhoods, socioeconomic status) in 10- to 13-year-olds. Results: Results revealed significant interaction between timing and proximal social influences (i.e., the “microsystem”) in predicting mental health problems. In general, adolescents with early pubertal timing and unfavorable (high levels of negative and low levels of positive) influences in the microsystem exhibited greater problems. Both males and females exhibited such associations for rule-breaking delinquency, while females alone exhibited associations for depression. Results also illustrate the relative strength of each social context at modulating risk for mental health problems in early vs late pubertal maturers.Conclusions: These findings highlight the importance of proximal social influences in buffering vulnerability for mental health problems related to off-time puberty. Findings also illustrate the broad implications of latent environmental factors, reflecting common variance of multiple social influences that typically covary with one another.
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