In most vertebrates, social play among peers is considered essential for behavioral development. Yet in solitary species bearing single offspring, ...

Explore research on how emotions influence social cognition, decision-making, and AI interactions at the Emotions, Computation, and Choice Lab at Stanford University. Join us to study emotions and beh...

Mice spontaneously form leader and follower roles during cooperation, and the medial prefrontal cortex encodes these role dynamics and an egocentric social value map of the partner’s position.

Brain activity in the pre-supplementary motor area and dorsolateral prefrontal cortex represents gaze-weighted accumulated evidence signals in value-based decision-making.

An essay, based on a public lecture delivered at the 2026 International Congress of Mathematicians, on how the mathematical community might respond to the arrival of artificial intelligence tools that...

Mizrachi et al. show that directing attention to bodily sensations, rather than away, promotes more regulated acute inflammatory responses in healthy volunteers, revealing sensory and vagal pathways l...

Abstract. A generative model can be defined as a model of the latent causes of sensory input that can be used to generate new data samples. By examining em

Reinforcement learning models often ignore affect’s well-established role in shaping behavior. This study shows evidence that affective valence serves as a computational signal that tracks learning in...

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Learning transforms prefrontal cortex activity from flexible, high-dimensional representations into compact, task-relevant and abstract codes, enabling efficient generalization of learned rules to new...

By combining magnetoencephalography and eye tracking, this study sheds light on why people fixate on some parts of natural scenes longer than others. Rather than visual complexity, fixation durations ...

Reinforcement learning models often ignore affect’s well-established role in shaping behavior. This study shows evidence that affective valence serves as a computational signal that tracks learning in...

Successful strategic behavior must be grounded in beliefs about the opponent and her intentions. While many potential models have been proposed to explain choices in such situations, the neural mechanisms that govern learning and choice in complex strategic contexts remain poorly understood. Here, we use a computational model that combines dynamic learning and choice mechanisms to explain both choices and response times of human participants engaged in a competitive strategic task. Using electroencephalography (EEG), we identify temporally structured stages of neural processing that support an evolving value-based decision process, corresponding to first- and second-order belief updates and evidence accumulation related to the comparison of action values. Gamma-band phase coupling between central and parietal EEG signals varied with individual winning rate, suggesting that strategic behavior involves coordinated information transfer across spatially remote areas. Together, our data characterize the temporally evolving neural dynamics of belief and valuation processes that underlie strategic choice and provide neural validation for assumptions embedded in computational models of this behavior. ### Competing Interest Statement The authors have declared no competing interest. European Research Council, 725355

In the online attention economy, new research from the UC San Diego Rady School finds that making science more clickable or shareable can help some readers learn more – but leaves many others with an ...

When forming a cognitive map, a trade-off exists between facilitating novel inferences and storing veridical copies of past experience. Here the authors show that the neuromodulator noradrenaline sets...

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Department SSD Institute for Mind and Biology: Staff and Temporary Employees About the Department The Eating Disorders Program in the Department of Psychiatry and Behavioral Neuroscience at the Univer...