Cognitive neuroscience seeks generalizable theories explaining the relationship between
behavioral, physiological and mental states. In pursuit of such theories, we propose a …

A central goal of neuroscience is to understand the representations formed by brain activity
patterns and their connection to behaviour. The classic approach is to investigate how …

A few years ago, the first CNN surpassed human performance on ImageNet. However, it
soon became clear that machines lack robustness on more challenging test cases, a major …

Biological and artificial information processing systems form representations that they can
use to categorize, reason, plan, navigate, and make decisions. How can we measure the …

Understanding object representations requires a broad, comprehensive sampling of the
objects in our visual world with dense measurements of brain activity and behavior. Here …

Objects are the core meaningful elements in our visual environment. Classic theories of
object vision focus upon object recognition and are elegant and simple. Some of their …

Object vision is commonly thought to involve a hierarchy of brain regions processing
increasingly complex image features, with high-level visual cortex supporting object …

Deep neural networks have reached human-level performance on many computer vision
tasks. However, the objectives used to train these networks enforce only that similar images …

Humans possess a remarkable ability to make decisions within real-world environments that
are expansive, complex, and multidimensional. Human cognitive computational …

Today's computer vision models achieve human or near-human level performance across a
wide variety of vision tasks. However, their architectures, data, and learning algorithms differ …