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 …

The last ten years of attention research have witnessed a revolution, replacing a theoretical
dichotomy (top-down vs. bottom-up control) with a trichotomy (biased by current goals …

Neuroscience has focused on the detailed implementation of computation, studying neural
codes, dynamics and circuits. In machine learning, however, artificial neural networks tend …

Most elementary behaviors such as moving the arm to grasp an object or walking into the
next room to explore a museum evolve on the time scale of seconds; in contrast, neuronal …

The visual expertise of adult humans is jointly determined by evolution, visual development
and visual perceptual learning. Perceptual learning refers to performance improvements in …

Visual attention enables us to selectively prioritize or suppress information in the
environment. Prominent models concerned with the control of visual attention differentiate …

While humans have an incredible capacity to acquire new skills and alter their behavior as a
result of experience, enhancements in performance are typically narrowly restricted to the …

Learning to read is extremely difficult for about 10% of children; they are affected by a
neurodevelopmental disorder called dyslexia [1, 2]. The neurocognitive causes of dyslexia …

Humans and many other animals have an enormous capacity to learn about sensory stimuli
and to master new skills. However, many of the mechanisms that enable us to learn remain …

Reading is a unique, cognitive human skill crucial to life in modern societies, but, for about
10% of the children, learning to read is extremely difficult. They are affected by a …