Back

Large-scale analysis of interindividual variability in single and paired-pulse TMS data: results from the 'Big TMS Data Collaboration'

Corp, D. T.; Bereznicki, H. G. K.; Clark, G. M.; Youssef, G. J.; Fried, P. J.; Jannati, A.; Davies, C. B.; Gomes-Osman, J.; Kirkovski, M.; Albein-Urios, N.; Fitzgerald, P. B.; Koch, G.; Di Lazzaro, V.; Pascual-Leone, A.; Enticott, P. G.; The Big TMS Data Collaboration,

2021-01-26 neuroscience
10.1101/2021.01.24.428014 bioRxiv
Show abstract

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 participants TMS data was pooled across 35 studies. Target muscle, pulse waveform, neuronavigation use, and TMS machine significantly predicted an individuals 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. HighlightsO_LI687 healthy participants TMS data was pooled across 35 studies C_LIO_LISignificant relationships between age and resting motor threshold C_LIO_LISignificant relationships between baseline MEP amplitude and SICI/ICF C_LI

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.