Conditioning, how animals learn to associate two or more events, is one of the most influential paradigms in learning theory. It is nevertheless unclear how current models of associative learning can accommodate complex phenomena without ad hoc representational assumptions. We propose to embrace deep neural networks to negotiate this problem. Read Full Article (External Site) […]

Chinese reading experiments have introduced important caveats to theories of reading that have been largely informed by studies of English reading – especially in relation to our understanding of lexical processing and eye-movement control. This article provides a brief primer on Chinese reading and examples of questions that arise from its study. Read Full Article […]

We explore the hypothesis that many intuitive physical inferences are based on a mental physics engine that is analogous in many ways to the machine physics engines used in building interactive video games. We describe the key features of game physics engines and their parallels in human mental representation, focusing especially on the intuitive physics […]