Hongjie Bi

This paper investigates the dynamics of excitatory-inhibitory neural networks, showing how balanced E-I populations can exhibit asynchronous and coherent behaviors, including oscillations and chaos, under different conditions.

This paper studies theta-nested gamma oscillations in neural mass models, showing they can emerge from two network configurations with distinct locking behaviors and frequency dynamics.

This paper shows that a single inhibitory neuron population can generate both slow and fast gamma oscillations through different mechanisms, and demonstrates how external stimuli can switch between these rhythms.