Publications

in prep

Gagl, B., & Draschkow, D. (in prep). Extension for eye tracking including gaze position and pupil size of the brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments. check out the existing BIDS

     

2020

Sauter, M., Draschkow, D., & Mack, W. (2020). Building, Hosting and Recruiting: A Brief Introduction to Running Behavioral Experiments Online. Brain Sciences, Vol. 10, Page 251, 10(4), 251. https://doi.org/10.3390/BRAINSCI10040251

Kumle, L., Vo, M. L., & Draschkow, D. (2020, April 8). Estimating power in (generalized) linear mixed models: an open introduction and tutorial in R. https://doi.org/10.31234/osf.io/vxfbh preprint

Kallmayer, M., Zacharias, L., Nobre, A.C., & Draschkow, D. (2020). Introduction to Online Experiments. https://doi.org/10.17605/OSF.IO/XFWHB resources

     

2019

Kent, J. & Herholz, P. (2019). NiBetaSeries: task related correlations in fMRI. Journal of Open Source Software. 2019, 4, 41. doi: doi.org/10.21105/joss.01295 download Github repository

Vogelbacher C., Bopp M.H.A., Schuster V., Herholz P., Jansen A. & Sommer Jens (2019). LAB–QA2GO: A Free, Easy-to-Use Toolbox for the Quality Assessment of Magnetic Resonance Imaging Data. Frontiers in Neuroscience. 2019, 13. doi: doi.org/10.3389/fnins.2019.00688 download preprint Github repository

Notter, M., Gale, D., Herholz, P., Markello, R., Notter-Bielser, ML., Whitaker, K. (2019). AtlasReader: A Python package to generate coordinate tables, region labels, and informative figures from statistical MRI images Journal of Open Source Software. 2019, 4, 34. doi: doi.org/10.21105/joss.01257 download Github repository

Sassenhagen, J. & Draschkow, D. (2019). Cluster-based permutation tests of MEG/EEG data do not establish significance of effect latency or location. Psychophysiology. 2019; e13335. doi: doi.org/10.1111/psyp.13335 download

     

2018

Kumle, L., Võ, M. L-H., & Draschkow, D. (2018). Mixedpower: a library for estimating simulation-based power for mixed models in R. https://doi.org/10.5281/zenodo.1341047 GitHub

Sassenhagen, J. (2018). How to analyse electrophysiological responses to naturalistic language with time-resolved multiple regression. Language, Cognition and Neuroscience, DOI: 10.1080/23273798.2018.1502458 download

     

2016

Sassenhagen, J., and Alday, P. M. (2016). A common misapplication of statistical inference: Nuisance control with null-hypothesis significance tests. Brain and Language,162, 42-45 link