Foivos Kotsogiannis

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 study compares resting-state functional connectivity and networks derived from fNIRS and fMRI, showing fNIRS captures key features of fMRI-based networks with partial correlations improving edge-level agreement.

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.