We recently proposed that attention control uses object-category representations consisting
of category-consistent features (CCFs), those features occurring frequently and consistently …

Human ventral temporal cortex shows a categorical organization, with regions responding
selectively to faces, bodies, tools, scenes, words, and other categories. Why is this …

While feedforward deep convolutional neural networks (CNNs) have been a great success
in computer vision, it is important to remember that the human visual contex contains …

Extensive research has revealed that the ventral visual stream hierarchically builds a robust
representation for supporting visual object categorization tasks. We systematically explored …

The mechanism of attention control is best described by biased-competition theory (BCT),
which suggests that a top-down goal state biases a competition among object …

Anterior regions of the ventral visual stream have substantial information about object
categories, prompting theories that category-level forces are critical for shaping visual …

Human visual object recognition is subserved by a multitude of cortical areas. To make
sense of this system, one line of research focused on response properties of primary visual …

The visual attention network untangled | Nature Neuroscience Skip to main content Thank you
for visiting nature.com. You are using a browser version with limited support for CSS. To obtain …

Visual attention is an essential and critical mechanism that allows humans to select the most
relevant visual information of potential interest to focus on certain aspects of the …

Learning about visual object categories causes changes in the way we perceive those
objects. One likely mechanism by which this occurs is the application of attention to …