Convolutional neural networks (CNNs) were inspired by early findings in the study of
biological vision. They have since become successful tools in computer vision and state-of …

Cortical gain regulation allows neurons to respond adaptively to changing inputs. Neural
gain is modulated by internal and external influences, including attentional and arousal …

For more than 100 years we have known that the visual field is mapped onto the surface of
visual cortex, imposing an inherently spatial reference frame on visual information …

Others' observed actions cause continuously changing retinal images, making it challenging
to build neural representations of action identity. The monkey anterior intraparietal area …

As one of the most effective models for human collective motion, the social force model
(SFM) simulates the dynamics of crowd evacuation from a microscopic perspective …

The last two decades have established that a network of face-selective areas in the temporal
lobe of macaque monkeys supports the visual processing of faces. Each area within the …

Humans accurately identify observed actions despite large dynamic changes in their retinal
images and a variety of visual presentation formats. A large network of brain regions in …

Statistically summarizing information from a stimulus array into an ensemble representation
(eg, the mean) improves the efficiency of visual processing. However, little is known about …

Human visual cortex is organised broadly according to two major principles: retinotopy (the
spatial mapping of the retina in cortex) and category-selectivity (preferential responses to …

A fundamental question for any visual system is whether its image representation can be
understood in terms of its components. Decomposing any image into components is …