The controversial question of whether machines may ever be conscious must be based on a
careful consideration of how consciousness arises in the only physical system that …

Cognitive biases, such as the anchoring bias, pose a serious challenge to rational accounts
of human cognition. We investigate whether rational theories can meet this challenge by …

Recent progress in artificial intelligence has renewed interest in building systems that learn
and think like people. Many advances have come from using deep neural networks trained …

Bayesian explanations have swept through cognitive science over the past two decades,
from intuitive physics and causal learning, to perception, motor control and language. Yet …

Neural responses in the visual cortex are variable, and there is now an abundance of data
characterizing how the magnitude and structure of this variability depends on the stimulus …

Most models of sensory processing in the brain have a feedforward architecture in which
each stage comprises simple linear filtering operations and nonlinearities. Models of this …

Behavior varies from trial to trial even when the stimulus is maintained as constant as
possible. In many models, this variability is attributed to noise in the brain. Here, we propose …

There is strong behavioral and physiological evidence that the brain both represents
probability distributions and performs probabilistic inference. Computational neuroscientists …

Organisms must act in the face of sensory, motor, and reward uncertainty stemming from a
pandemonium of stochasticity and missing information. In many tasks, organisms can make …

Neural activity and behavior in laboratory experiments are surprisingly variable across trials.
This variability and its potential causes have been the focus of a spirited debate. Here we …