Simon H. Kohl

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 shows that fNIRS-based neurofeedback can modulate rTPJ activity and affect attention reorienting, with learning differences between up- and downregulation groups.

This study identifies brain regions and molecular mechanisms associated with interpersonal neural synchronization using multimodal data fusion and meta-analysis.

The paper curates and provides analysis-ready diffusion MRI data for pediatric brain white-matter research, including automated quality control using a trained neural network.

This study uses machine learning to analyze 608 participants and identifies two factors improving neurofeedback performance: pre-training no-feedback runs and training patients over healthy participants.