Lihao Guo

This study investigates how fast-spiking interneurons (FSIs) in the striatum modulate input correlation and trial-to-trial variability, revealing their role in both exploration and stability during learning.

This in-silico study predicts how Parkinson's disease alters striatal network connectivity and glutamatergic drive to striatal projection neurons.

The paper shows that input variance ratios and covariances determine output trial-by-trial variability in a cortical microcircuit model with different interneuron subtypes.