Learning is using past experiences to inform new behaviors and actions. Because all
experiences are unique, learning always requires some generalization. An effective way of …

The spontaneous replay of patterns of activity related to past experiences and memories is a
striking feature of brain activity, as is the coherent activation of sets of brain areas …

Modern machine learning has subverted and bypassed the theoretical framework of
Chomsky's generative approach to linguistics, including its core claims to particular insights …

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 …

Neuroscience research is undergoing a minor revolution. Recent advances in machine
learning and artificial intelligence research have opened up new ways of thinking about …

Semantic cognition refers to our ability to use, manipulate and generalize knowledge that is
acquired over the lifespan to support innumerable verbal and non-verbal behaviours. This …

Humans are remarkably limited in:(i) how many control-dependent tasks they can execute
simultaneously, and (ii) how intensely they can focus on a single task. These limitations are …

Semantic control, the ability to selectively access and manipulate meaningful information on
the basis of context demands, is a critical component of semantic cognition. The precise …

We propose the self-regulation view in writing-to-learn as a promising theoretical
perspective that draws on models of self-regulated learning theory and cognitive load …

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 …