Gan He

This paper demonstrates that synaptic credit assignment can be implemented online through voltage dynamics in detailed neurons, enabling supervised learning in recurrent networks.

The paper develops an analytical framework to understand how inhibition affects neuronal computation across dendritic compartments, revealing a unified law that explains inhibitory leverage in active dendrites.

This paper introduces a GPU-based framework that accelerates neuron simulations and applies it to neuroscience and AI tasks, showing significant speed improvements over traditional methods.

This paper develops a computational model of retinal gap junctions (G-filter) that improves deep neural networks' performance in blind denoising tasks.