Deep learning to overcome human error and bias in electrode position extraction in tDCS-fMRI studies
Filip Niemann, Steffen Riemann, Sophie Dabelstein, Kira Hering, Harun Kocataş, Mohamed Abdelmotaleb, Leonardo M. Caisachana Guevara, Rico Fischer, Axel Thielscher, Daria Antonenko, Agnes Flöel, Marcus Meinzer
The paper develops a deep learning model to automate electrode detection in tDCS-fMRI studies, outperforming manual and semi-automated methods in precision and reducing human bias.
bioRxiv · Dec 25, 2025 · PreprintNeuroscience