Navigating the Maze: Identifying Potential Pitfalls in Attention State Classification from fMRI Brain Patterns
Ruben Andreas Bressler, Assunta Ciarlo, Sophie Raible, Giancarlo Valente, Michael Lührs, Ralph Tier, David E.J. Linden, Rainer Goebel
This study identifies classification inaccuracies in fMRI-based attention state decoding due to design choices and confounders like motion artifacts and task timing.
bioRxiv · Dec 20, 2024 · PreprintNeuroscience