Yutao He

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 introduces DeepDAM, a framework that improves neural connectivity inference by aligning synthetic and in vivo data domains, achieving high accuracy in rodent and other systems.

This paper introduces a computational framework to model synaptic adaptation in the early visual system, revealing diverse adaptive time constants and a frequency-sensitive gain-control strategy in ribbon synapses.