A rich behavioral literature has shown that human object recognition is supported by a
representation of shape that is tolerant to variations in an object's appearance …

Periodic visual stimulation and analysis of the resulting steady-state visual evoked potentials
were first introduced over 80 years ago as a means to study visual sensation and …

Contemporary neural networks still fall short of human-level generalization, which extends
far beyond our direct experiences. In this paper, we argue that the underlying cause for this …

Deep neural networks (DNNs) have had extraordinary successes in classifying
photographic images of objects and are often described as the best models of biological …

Memory is fleeting. New material rapidly obliterates previous material. How, then, can the
brain deal successfully with the continual deluge of linguistic input? We argue that, to deal …

To understand visual consciousness, we must understand how the brain represents
ensembles of objects at many levels of perceptual analysis. Ensemble perception refers to …

Is it possible to learn something without being aware of it? How does emotion influence the
way we think? How can we improve our memory? Fundamentals of Cognition, third edition …

Purpose The purpose of this paper is to investigate the effects of visual communications on
Instagram users' propensity to engage with image-based content through online behaviors …

What is attention? How does attention shape consciousness? In an approach that engages
with foundational topics in the philosophy of mind, the theory of action, psychology, and the …

Recent progress in deep learning is essentially based on a “big data for small tasks”
paradigm, under which massive amounts of data are used to train a classifier for a single …