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Stefano Palminteri on Muck Rack

Stefano Palminteri

France, Paris
As seen in: Nature, arXiv, PLOS ONE, The Conversation, Science Magazine, BioRxiv, Numerama, JNeurosci, eLife, Pour la Science and
Behavioral scientist interested in learning and decision-making. Co-author of Decision Making: a Very Short Introduction shorturl.at/Dxbif
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Articles

Attention modulates value normalization in human reinforcement learning by shaping reward encoding

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By Romane Cecchi, Sebastian Gluth, Stefano Palminteri
| Nature Verified
Abstract Contextual valuation is a well-documented phenomenon in reinforcement learning, typically manifesting as range normalization in outcome representation. However, recent findings have revealed systematic deviations from this model, particularly when three options with equally spaced values are presented. In this study, we hypothesize that these distortions in outcome normalization arise from attentional processes.
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A computational model of reward learning and habits on social media

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By Georgia Turner, Lukas Gunschera, Johannes C. Eichstaedt, Stefano Palminteri, Amy C Orben, Shashanka Subrahmanya, Aadesh Salecha
| Nature Verified
Abstract Social media have fundamentally transformed how we live and communicate. However, the methods to study how our cognitive systems interact with technology platforms are very limited. Computational modelling represents a new avenue to uncover the finegrained cognitive processes driving social media behaviour. Here, we develop a computational model of real-world social media posting data, adapted from the animal reward learning literature.
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Reference-point dependent reinforcement learning in humans and rats

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By Lachlan A. Ferguson, Magdaléna Soukupová, Sébastien Bouret, Stefano Palminteri, Shauna L Parkes
| Nature Verified
Abstract Rewards and punishments in reinforcement learning are encoded in both absolute and relative manners. Reference-point dependence, a valuation bias shared by adaptation-level and prospect theories, is often proposed as the computational mechanism underlying relative value encoding. However, the extent to which these behavioural and computational mechanisms are conserved across species remains to be fully understood.
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