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Juan Vidal-Perez

@vipejuan.bsky.social
59 followers 138 following 14 posts

PhD student @Max Planck UCL || RL and decision-making || Trying to understand how we process (dis)information 🧠🗞️

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Reposted by Juan Vidal-Perez
Wanjun Lin @wanjunlin.bsky.social · 23/06/2026
Very happy to share this work on a preprint! Coauthored with @mikebrowning.bsky.social @Erdem Pulcu @lhuntneuro.bsky.social www.biorxiv.org/content/10.6... How do we learn when rewards and punishments change independently—and how does this go awry in anxiety and depression?
biorxiv.org
Valence-specific representation of uncertainty in the anterior cingulate is impaired in those with affective symptoms
The ability to seek reward and avoid punishment is a fundamental survival instinct. In natural environments, however, the statistics of rewards and punishments can change independently of one another....
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Yongling Lin @yongling.bsky.social · 11/06/2026
😀Excited to share the new preprint!!!🥳 We show preserved self–other integration in social decision-making among individuals with elevated autistic traits (N = 1,621), highlighting the importance of large samples to validate null effects. www.biorxiv.org/content/10.6...
biorxiv.org
Preserved self-other integration during social decision making among individuals with elevated autistic traits
Autistic people can find social interactions difficult to navigate, traditionally attributed to difficulties in taking others' perspectives. However, we have a limited understanding of how autistic pe...
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Reposted by Juan Vidal-Perez
Hadeel Haj Ali هديل حاج علي @hadeelhajali.bsky.social · 03/05/2026
New Preprint! 🙌 People's risk aversion causes them to make irrational decisions. Yet they get closer to rationality when...Read more here: www.researchsquare.com/article/rs-9...
researchsquare.com
Risk escalation is amplified by stakes, not by a sense of control
People are often faced with the same risky choices repeatedly: how much to invest, how much to drink, how fast to drive. These decisions are not made just once, but dozens of times. How does repetitio...
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ranimo.bsky.social @ranimo.bsky.social · 07/04/2026
⭐️PhD Cognitive/Computational Psychology ⭐️ Use Reinforcement Learning + computational modelling to study how we form beliefs in the face of unreliable information (with me +Tali Sharot). Full funding for those eligible for UK home fees. Deadline 18/5. Please share! @queenmarycbb.bsky.social
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Stefano Palminteri @stepalminteri.bsky.social · 07/12/2025
Prakhar, in a recent thought-provoking paper and thread, boldly claimed that the learning-rate biases may be mere “statistical ghosts” of decaying learning rates We took up the challenge and put this claim to the test. Here are our findings (w/ @romanececchi.bsky.social). 1/n osf.io/preprints/ps...
Genuine Learning Biases Persist After Accounting for Temporally Decreasing Learning Rates: insight from fitting six datasets. 

Recent claims suggest that learning-rate asymmetries observed in human reinforcement learning may be artefactual, arising from a failure to account for temporally decreasing learning rates in Bayes-optimal agents. Here, we re-analyzed six datasets and found that models incorporating learning biases systematically outperformed both Bayes-derived and decay-based models, and that learning biases persisted even when temporal decay was explicitly included. These results demonstrate that temporally decreasing learning rates cannot account for learning asymmetries, which instead emerge as robust and reproducible features of human reinforcement learning.
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Henrik Singmann @singmann.bsky.social · 27/04/2025
Honey, we fixed Signal Detection Theory (SDT)! In this preprint, Constantin Meyer-Grant, David Kellen, Sam Harding, and I critically evaluate the (unequal-variance) Gaussian SDT model in recognition memory and pursue the Gumbel-min model as a principled alternative: doi.org/10.31234/osf... 🧵
doi.org
Extreme-Value Signal Detection Theory for RecognitionMemory: The Parametric Road Not Taken
Signal Detection Theory has long served as a cornerstone of psychological research, particularly in recognition memory. Yet its conventional application hinges almost exclusively on the Gaussian…
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Reposted by Juan Vidal-Perez
Stefano Palminteri @stepalminteri.bsky.social · 14/04/2025
🚨 New study alert! 🚨 Ever wondered if rats and humans learn in the same way? 🐭🧑‍🔬 We tested this — and the answer is yes, at least when it comes to how we value rewards in context. (with @shaunaparkes.bsky.social Lachlan Ferguson, Magdalena Soukupova) 🧵Thread 👇 1/ www.biorxiv.org/content/10.1...
biorxiv.org
Reference Point-Dependent Reinforcement Learning in Humans and Rats
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...
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Reposted by Juan Vidal-Perez
Stephan Lewandowsky @lewan.uk · 10/04/2025
Honest people don’t lie. Or do they? Liars aren’t honest. Or are they? One puzzling conundrum in contemporary politics is that politicians who seem to be estranged from facts and evidence are nonetheless considered honest by their followers. 1/n
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Juan Vidal-Perez @vipejuan.bsky.social · 07/04/2025
Again, a big thank you to @ranimo.bsky.social and Ray Dolan for guiding this work! In the full paper, we go in depth into these results, and propose several mechanisms of how some of these biases can emerge, escalate and progressively bias our beliefs. osf.io/preprints/psya… 13/13
osf.io
OSF
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Juan Vidal-Perez @vipejuan.bsky.social · 07/04/2025
However, you may still under-correct these news, perceive neutral sources as biased in favor of vaccines, and, when receiving factual information, revise your opinion of the source rather than your vaccine beliefs. This will make you more vaccine-skeptical over time! 12/13
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Juan Vidal-Perez @vipejuan.bsky.social · 07/04/2025
So what does this mean in the real world? Imagine you frequently read anti-vax news. You know it’s biased. You think you’re reading critically. 11/13
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Juan Vidal-Perez @vipejuan.bsky.social · 07/04/2025
We found that biases systematically distorts beliefs, even when: ✔️Biases are non-ideological, simple and additive ✔️Participants are highly motivated to learn ✔️They have clear chances to detect/correct biases Bias silently takes hold—even when we're trying to resist it! 10/13
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Juan Vidal-Perez @vipejuan.bsky.social · 07/04/2025
3️⃣Third finding: People care for learning about the sources over getting money Participants directed too many cognitive resources to learn how sources are biased, but this hurt their ability to make good bandit choices. Sometimes attempts to correct for biases may backfire! 9/13
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Juan Vidal-Perez @vipejuan.bsky.social · 07/04/2025
2️⃣Second finding: people misperceive neutral sources as being biased. After interacting with a biased source (e.g., favorable), a neutral source was perceived as biased in the opposite direction (e.g., unfavorable). And this only emerged after the ground truth was withheld. 8/13
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Juan Vidal-Perez @vipejuan.bsky.social · 07/04/2025
So, what did we find? 1️⃣First big finding: People don't fully correct for bias. Even when they’ve had ample opportunity to learn that a source is biased, they still under-debiased. Participants became biased in the same directions as the sources that informed them! 7/13
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Juan Vidal-Perez @vipejuan.bsky.social · 07/04/2025
In phase 2, these feedback sources can be treated like our "biased weight scale". By adding/subtracting 3£ to estimates of unfavorable/favorable sources respectively one can fully correct for their reports and learn the true value of paintings! 6/13
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Juan Vidal-Perez @vipejuan.bsky.social · 07/04/2025
The task had two phases: 🟢Phase 1: true outcomes and source feedback were shown, so that could learn about source biases. 🟠Phase 2: only source feedback was shown (no true outcomes), so they had to infer the values of paintings. We also asked them to classify the bias of each source. 5/13
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Juan Vidal-Perez @vipejuan.bsky.social · 07/04/2025
Instead, they relied on external sources that estimated the selling price of selected paintings. But these sources could give biased estimates: ➕Favorable sources overestimated true selling prices by ~3$. ⚫Neutral sources (unbiased) ➖Unfavorable sources underestimated by ~3$ 5/13
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Juan Vidal-Perez @vipejuan.bsky.social · 07/04/2025
We tested this using a multi-armed bandit reinforcement learning game where participants played art dealers selling painting copies (=bandits).🖼️ Paintings varied in price. The goal: to choose more expensive paintings. The challenge: they didn’t get to see the TRUE prices 4/13
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Juan Vidal-Perez @vipejuan.bsky.social · 07/04/2025
Even more interesting, bias is theoretically correctable! Imagine a scale that always adds 5kg. If the scale reads 75kg, you can infer your true weight is 70 kg. So, in principle, if we know an info-source is biased, we should be able to adjust for it. Right? Not quite… 3/13
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Juan Vidal-Perez @vipejuan.bsky.social · 07/04/2025
First, bias is not noise. •Noise is like a coin flip—random and directionless. •Bias is systematic—it consistently skews things in a certain direction. And here's the kicker: while noise cancels out over time, bias can accumulate. 2/13
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Juan Vidal-Perez @vipejuan.bsky.social · 07/04/2025
🚨 New preprint alert! 🚨 w/ @ranimo.bsky.social 📝 osf.io/preprints/psya… From partisan news to algorithmically curated content, we constantly receive biased misinformation. With biased input, can our beliefs be accurate? Turns out, biased misinformation distorts our beliefs! 👇🧵 1/13
osf.io
OSF
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ranimo.bsky.social @ranimo.bsky.social · 26/03/2025
⭐️PhD in Cognitive/Computational Psychology⭐️ Use Reinforcement Learning to study how mis/misinformation affects us. For full funding, one has to be eligible for UK home fees. Please Share!! @queenmarycbb.bsky.social Deadline: April 20. For more information: www.findaphd.com/phds/project...
findaphd.com
Characterising Cognitive Biases Elicited by Misinformation Using Reinforcement Learning at Queen Mary University of London on FindAPhD.com
PhD Project - Characterising Cognitive Biases Elicited by Misinformation Using Reinforcement Learning at Queen Mary University of London, listed on FindAPhD.com
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Michael Bang Petersen @m-b-petersen.bsky.social · 16/03/2025
When populist regimes target scientific institutions - as is happening in the US today - it is not because their core constituency is anti-science but exactly because even they respect the authority of science. Science is a dangerous counter-power for the populist leaders. (2/4)
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Michael Bang Petersen @m-b-petersen.bsky.social · 13/03/2025
We know that economic anxiety & conspiracy beliefs are related. Often this is used to argue that it is key to fix economic conditions to avoid widespread conspiracy beliefs. But a new study shows that causality runs the other way. The conspiracy beliefs drive the anxiety: doi.org/10.1111/pops...
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Tom Costello @tomcostello.bsky.social · 18/02/2025
Last year, we published a paper showing that AI models can "debunk" conspiracy theories via personalized conversations. That paper raised a major question: WHY are the human<>AI convos so effective? In a new working paper, we have some answers. TLDR: facts osf.io/preprints/ps...
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