Highlights•Recurrent neural networks (RNNs) are powerful models of neural systems.•RNNs
can be either designed or trained to perform a task.•In both cases, low dimensional …

The visual system can only accurately represent a handful of objects at once. How do we
cope with this severe capacity limitation? One possibility is to use selective attention to …

With the advent of the Internet, billions of images are now freely available online and
constitute a dense sampling of the visual world. Using a variety of non-parametric methods …

High-performance computing has recently seen a surge of interest in heterogeneous
systems, with an emphasis on modern Graphics Processing Units (GPUs). These devices …

Aims and Scope This book is both an introductory textbook and a research monograph on
modeling the statistical structure of natural images. In very simple terms,“natural images” are …

The information that individuals can hold in working memory is quite limited, but researchers
have typically studied this capacity using simple objects or letter strings with no associations …

The goal of natural image denoising is to estimate a clean version of a given noisy image,
utilizing prior knowledge on the statistics of natural images. The problem has been studied …

There is a great deal of structural regularity in the natural environment, and such regularities
confer an opportunity to form compressed, efficient representations. Although this concept …

Since at least 1935, vision researchers have used art stimuli to test human response to
complex scenes. This is sensible given the “inherent interestingness” of art and its relation to …

Previous research has shown that interacting with natural environments vs. more urban or
built environments can have salubrious psychological effects, such as improvements in …