Martin Krentz

The paper links changes in large-scale neural networks during lab stress to real-life affective reactivity.

This study compares fMRI noise correction methods using peripheral physiological signals and data-driven approaches, finding that peripheral-based methods offer more reliable noise reduction, especially in high-noise regions.

This study shows participants can learn to self-regulate stress-related brain network balance using real-time fMRI neurofeedback and transfer this skill to a stressor scenario.