Vasilisa Skvortsova

This study identifies distinct microstructural brain correlates of learning rate and learning noise in reward-based decision-making using computational modeling and quantitative MRI.

This study investigates how dopamine affects reinforcement learning in humans using L-DOPA and finds it reduces switching after low rewards and influences learning rate and precision.

The paper shows that computational noise in reward-guided learning causes behavioral variability in volatile environments rather than reflecting exploration.

The paper shows that price cues influence taste pleasantness by engaging the brain's valuation system and affective regulation networks.