This review integrates computational approaches to provide a unified view on how data analysis methods, biophysical mechanistic models and machine learning approaches can help to uncover the origins a...

Midbrain dopamine neurons are thought to implement a temporal difference (TD) reward prediction error (RPE) that updates cached values stored in striatum. This has been challenged by evidence that dop...

Action selection using predictive models of the environment plays a fundamental role in human and animal behaviour, yet is poorly understood at circuit and algorithmic levels. Spatial navigation is an...

Perceptual multistability, observed across species and sensory modalities, offers valuable insights into numerous cognitive functions and dysfunctions. For instance, differences in temporal dynamics a...

The neuroscience of planning has long been analogized to search algorithms in artificial intelligence (AI), which simulate future actions to guide immediate choices. We argue that advances in both neu...

This study shows that cerebellar circuits learn and encode prior probabilities of event timing. Cell-type-specific neural activity reflects environmental statistics and guides predictive motor behavio...

Categorization, the grouping of objects, living organisms, actions or events into equivalence clusters, is fundamental to adaptive behaviour. In this Perspective, Barrett and Miller discuss evidence t...

Appeals to representation are widespread, despite neuroscientists’ uncertainty about what kind of findings count as evidence for such claims. In this Perspective, Pohl and colleagues develop a unified...

The authors analytically determine how neuronal correlations and geometry collectively determine readout generalization across tasks and show how these geometric features follow distinct trajectories ...

Nature Communications - Normative theory predicts that feedback should not affect decisions under risk, but past findings disagree. Here, the authors show that feedback shifts risk-taking by...

Deep neural networks (DNNs) once showed increasing alignment with primate perception as they improved on vision benchmarks, raising hopes that advance…

The brain can flexibly perform multiple tasks by compositionally combining task-relevant neural representations.

Brain-wide recordings in mice reveal that prior expectations are distributed through recurrent loops across all levels of cortical and subcortical processing.

Nature Communications - How the brain creates compositional cognitive maps that support both flexible and efficient planning remains poorly understood. Here, authors propose a...

UCL is consistently ranked as one of the top ten universities in the world (QS World University Rankings 2010-2022) and is No.2 in the UK for research power (Research Excellence Framework 2021).

Differences in neuroeconomic decision-making influence nucleus accumbens dopamine dynamics and reflect choice confidence during evaluation, as well as past and future value during re-evaluation, which...

Disordered eating can disrupt the rewarding value of food. Here, the authors show in a female sample that eating disorder symptoms, emotional arousal, and interoceptive awareness modulate goal-ir...

Reinforcement learning task-based behavioral and computational measures displayed low test–retest reliability at the individual level. Also in contrast to self-assessed personality measures, behaviora...

Reinforcement learning models of human behavior are limited in explaining the capacity for generalization. Here, the authors propose an efficient coding principle for reinforcement learning, whereby a...

Inactivation of the ventral subiculum does not change existing schema cells in the orbitofrontal cortex (OFC) but aids their formation during new learning. This challenges the idea that the OFC relies...

Previous studies indicate that rewards and punishments in reinforcement learning are encoded in a relative manner. Reference point-dependence, a valuation bias shared by eminent adaptation level and p...