Xinhao Fan

This paper develops a theoretical framework to quantify information stored in synaptic connections of neural networks, showing synergistic interactions among synapses.

This study investigates decision-making under uncertainty by measuring overt attention and comparing models to predict choices in simple and complex tasks.

This paper proposes a neuroplasticity rule that mathematically replicates backpropagation in neural networks without requiring biologically implausible assumptions.