We have only limited understanding of how and why large language models (LLMs) respond in the ways that they do. Their neural networks have proven challenging to interpret, and we are only beginning t...

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...

Human motivation is fundamentally shaped by one's expectations of the reward they could earn for good performance or the punishment they would avoid for poor performance. However, the extent to which ...

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The Concealed Information Test (CIT) is frequently used to determine the presence of crime-related information in a suspect's memory. In this paper, w…

In individuals with moderately low baseline performance, methamphetamine reduces the tendency to misinterpret high outcome noise.

Modelling biological decision-making with tiny recurrent neural networks enables more accurate predictions of animal choices than classical cognitive models and offers insights into the underlying cog...

Programming is essential for modern research in neuroscience and psychology, but it can quickly become a source of frustration and error. This Primer introduces ten practical principles guiding resear...

Using single-trial analysis in fMRI, this study shows that activity in brain areas associated with error monitoring and cognitive control differentiates between items that are later remembered correct...

The ability to use subjective, latent contextual representations to influence decision-making is crucial for everyday life. The hippocampus is hypothesized to bind together otherwise abstract combinat...

University of Minnesota (July 16-18, 2024)