Much evidence has shown that perception is biased towards previously presented similar
stimuli, an effect recently termed serial dependence. Serial dependence affects nearly every …

This perspective describes predictive processing as a computational framework for
understanding cortical function in the context of emerging evidence, with a focus on sensory …

The ability to predict future visual observations conditioned on past observations and motor
commands can enable embodied agents to plan solutions to a variety of tasks in complex …

Sequential decision making, commonly formalized as Markov Decision Process (MDP)
optimization, is an important challenge in artificial intelligence. Two key approaches to this …

When experts are immersed in a task, do their brains prioritize task-related activity? Most
efforts to understand neural activity during well-learned tasks focus on cognitive …

In many real-world scenarios, rewards extrinsic to the agent are extremely sparse, or absent
altogether. In such cases, curiosity can serve as an intrinsic reward signal to enable the …

Context is widely regarded as a major determinant of learning and memory across
numerous domains, including classical and instrumental conditioning, episodic memory …

Fueled by developments in computational neuroscience, there has been increasing interest
in the underlying neurocomputational mechanisms of psychosis. One successful approach …

How is it that thoroughly physical material beings such as ourselves can think, dream, feel,
create and understand ideas, theories and concepts? How does mere matter give rise to all …

How can a machine learn from experience? Probabilistic modelling provides a framework
for understanding what learning is, and has therefore emerged as one of the principal …