A spatially-tuned normalization model accounts for neuronal responses to attended or unattended stimuli that are presented inside the classical receptive field or the surround, and explains various other observations.

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.

In the retina, the receptive field surround preserves the spatial contrast sensitivity of the center in the face of naturalistic changes in local luminance.

The multiple component mechanisms of extra-classical receptive field modulation, with distinct dynamics, discovered in the monkey visual cortex have important implications for understanding contextual perceptual processing.

The A1 of ferrets and mice show similar tonotopic organizations, with neurons preferring a single frequency being more precisely organized into a tonotopic map than multipeaked neurons.

The development of neural responses proceeds through both the expansion and contraction of receptive field structure, and in addition depends upon changes in excitability of individual cells.

Moving covert attention can activate spatial representations in the Entorhinal cortex.

Multi-electrode recordings and modeling are combined to reveal the transformations of signals from cones to bipolar cells and then to ganglion cells within the primate retina.

The human visual system groups the individual features of objects together into a coherent whole via a serial, attention-demanding process.

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.