The convergence of two visual pathways at the level of retinal bipolar cells accounts for key features of ganglion cell responses.

The conductance-based encoding model creates a new bridge between statistical models and biophysical models of neurons, and infers visually-evoked excitatory and inhibitory synaptic conductances from spike trains in macaque retina.

Nonlinear receptive field subunits in retinal ganglion cells are isolated and characterized by clustering spike-triggered stimuli, and validated on population responses to naturalistic and novel closed loop stimuli.

A comprehensive, data-driven and interpretable nonlinear computational modeling framework based on deep neural networks uncovers different nonlinear transformations of speech signal in the human auditory cortex.