Sophie Raible

The paper examines how signal quality affects inter-individual variability in fNIRS data and introduces an open dataset with multi-task recordings and peripheral physiology measures.

This paper compares methods for detecting resting-state functional connectivity using fNIRS, finding that independent component analysis (ICA) outperforms seed-based approaches in accuracy and cross-chromophore consistency.

This study identifies classification inaccuracies in fMRI-based attention state decoding due to design choices and confounders like motion artifacts and task timing.