Learning and interpreting the structure of the environment is an innate feature of biological
systems, and is integral to guiding flexible behaviors for evolutionary viability. The concept of …

In this article, we aim to provide a literature review of different formulations and approaches
to continual reinforcement learning (RL), also known as lifelong or non-stationary RL. We …

Recently an influx of studies claims emergent cognitive abilities in large language models
(LLMs). Yet, most rely on anecdotes, overlook contamination of training sets, or lack …

The hippocampal-entorhinal system is important for spatial and relational memory tasks. We
formally link these domains, provide a mechanistic understanding of the hippocampal role in …

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

Humans and animals use mental representations of the spatial structure of the world to
navigate. The classical view is that these representations take the form of Euclidean …

The emergence of powerful artificial intelligence (AI) is defining new research directions in
neuroscience. To date, this research has focused largely on deep neural networks trained …

An organism's survival can depend on its ability to recall and navigate to spatial locations
associated with rewards, such as food or a home. Accumulating research has revealed that …

Replay is the reactivation of one or more neural patterns that are similar to the activation
patterns experienced during past waking experiences. Replay was first observed in …

Extracting the underlying temporal structure of experience is a fundamental aspect of
learning and memory that allows us to predict what is likely to happen next. Current …