Rubén Moreno-Bote

@morenobote.bsky.social

Bluesky in Barcelona Computational Neuroscience & Natural and Artificial Intelligence Serra Hunter Professor Center for Brain and Cognition, Universitat Pompeu Fabra https://sites.google.com/view/morenobotecompneuro?pli=1

Using a reference-dependent model based on Prospect Theory (PT), we reveal a functional asymmetry: More neurons encoded potential gains than losses, and gain-related signals were more tightly aligned with choices. This highlights a bias toward positive, goal-relevant outcomes in dACC value coding.

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The core novelty of our model stands in the definition of a Prospect Theory (Kahneman & Tversky 1979) inspired reference r(ATC) that dynamically models the utility u(v,ATC) as the comparison of alternative offers for ATC<3 🤑 (r(ATC)→0) and of offer value to missing tokens (r(ATC)→6-ATC) for ATC≥3 😬.

Even when explicitly modeling interactions between value and token accumulation, neural encoding remained primarily driven by value signals. However, these signals were subtly reshaped across the task, suggesting that token accumulation modulates, but does not simply scale, value representations.

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At the neural level we found that dorsal anterior cingulate cortex (dACC) encodes subjective value (SV) and ATC. SV-related signals peak during offer presentation, while ATC signals are sustained across the task, indicating progress monitoring. SV- but not ATC-related signals correlate with choices.

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Importantly, this change followed a structured pattern: risk-taking attitude 🤑 increased early on (ATC<3), peaked around ATC=3, and decreased 😬 near jackpot (ATC≥3). This inverse-u profile clearly outlines that choices are guided by a shifting internal reference point tied to progress toward reward.

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Accumulating tokens also reshapes risk preferences. Subjects are more risk-seeking when far from the jackpot, but became increasingly risk-averse as they approached it, especially when decisions were easier. This reveals a dynamic shift in strategy as ATC increases ↗️ and the goal becomes attainable.

Looking more closely, a clear pattern emerges: errors (i.e.,best choice misses) decrease as ATC increases, particularly when choices were not so trivial 🎰 (A). This improvement was most prominent at intermediate difficulty, indicating improved ability to discriminate between competing options 🧐 (B).

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We adopted a task where risky decisions don’t pay off immediately, but deliver virtual tokens 🪙 to collect across trials. Hitting accumulated tokens count (ATC) = 6 leads to a jackpot reward delivery 💰, and ATC reset. Leading question: do decision strategies depend on such dynamic ATC reference?

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This work led by @d-ferro.bsky.social with @benhayden.bsky.social shows how current wealth modulates behavior and value encoding. Kudos @d-ferro.bsky.social

Demetrio Ferro@d-ferro.bsky.social · 2w ago

Excited to share our latest publication, out now in @natcomms.nature.com !🧠🔍 Accumulating virtual rewards enhances both decision-making accuracy and neural value encoding in dorsal anterior cingulate cortex by dynamically shifting a goal-dependent internal reference point. doi.org/10.1038/s414...

1/2 Brain and Cognition Master at @UPFBarcelona Why to enroll here? Nuria Sebastian-Galles (language, Premio Nacional) Gustavo Deco (comp neuro) Chris Summerfield (cognition & AI) Salva Soto-Faraco (attention) Rubén Moreno-Bote (comp neuro & AI)

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New open PhD position in Theoretical and Computational Neuroscience in my lab. We want to discover the basis of natural intelligence. Please, spread the word, and apply if interested. See more details below.

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Open PhD position in Theoretical and Computational Neuroscience in my lab. We want to discover the basis of natural intelligence. Please, spread the word, and apply if interested. See more details below.

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