Ruohan Zhang

The paper shows that phase delays in cortical spikes during gamma oscillations match sparse coding models, linking experimental data to receptive field structures.

The paper proposes a modular reinforcement learning model to estimate rewards and discount factors from human behavior data, enabling accurate prediction of navigation decisions in virtual reality.

The paper introduces a model called gamma spike multiplexing to explain how cortical networks use gamma frequency latencies to modulate fast communication, offering advantages in parallel processing and speed.