Engemann DA, Mellot A, Höchenberger R, Banville H, Sabbagh D, Gemein L, Ball T, and Gramfort A. A reusable benchmark of brain-age prediction from M/EEG resting-state signals. NeuroImage 2022;262:119521.
Glanz O, Hader M, Schulze-Bonhage A, Auer P, and Ball T. A Study of Word Complexity Under Conditions of Non-experimental, Natural Overt Speech Production Using ECoG. Frontiers in Human Neuroscience 2022;15:711886
Gemein LA, Schirrmeister RT, Chrabąszcz P, Wilson D, Boedecker J, Schulze-Bonhage A, Hutter F, and Ball T. Machine-learning-based diagnostics of EEG pathology. NeuroImage 2020;220:117021.
Behncke J, Kern M, Ruescher J, Schulze-Bonhage A, and Ball T. Probabilistic neuroanatomical assignment of intracranial electrodes using the ELAS toolbox. Journal of Neuroscience Methods 2019;327:108396.
Kuhner D, Fiederer L, Aldinger J, Burget F, Völker M, Schirrmeister R, Do C, Boedecker J, Nebel B, Ball T, et al. A service assistant combining autonomous robotics, flexible goal formulation, and deep-learning-based brain–computer interfacing. Robotics and Autonomous Systems 2019;116:98–113.
Behncke J, Schirrmeister RT, Burgard W, and Ball T. The signature of robot action success in EEG signals of a human observer: Decoding and visualization using deep convolutional neural networks. In: 2018 6th International Conference on Brain-Computer Interface (BCI’18). IEEE. 2018:1–6.
Behncke J, Schirrmeister RT, Volker M, Hammer J, Marusic P, Schulze-Bonhage A, Burgard W, and Ball T. Cross-paradigm pretraining of convolutional networks improves intracranial EEG decoding. In: 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC’18). IEEE. 2018:1046–1053.
Heilmeyer FA, Schirrmeister RT, Fiederer LDJ, Völker M, Behncke J, and Ball T. A framework for large-scale evaluation of deep learning for EEG. In: 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC’18). IEEE. 2018:1039–1045.
Völker M, Schirrmeister RT, Fiederer LDJ, Burgard W, and Ball T. Deep transfer learning for error decoding from non-invasive EEG. In: 2018 6th International Conference on Brain-Computer Interface (BCI’18). IEEE. 2018:37–42.
Schirrmeister RT, Springenberg JT, Fiederer LDJ, Glasstetter M, Eggensperger K, Tangermann M, Hutter F, Burgard W, and Ball T. Deep learning with convolutional neural networks for EEG decoding and visualization. Human Brain Mapping 2017;38:5391–5420
Institute of Medical Biometry and Statistics,
Faculty of Medicine and Medical Center –
University of Freiburg
