‼️New preprint‼️
There does not seem to be an effect of ghrelin on risky decision-making in probability discounting. Not in behaviour, underlying computational processes, or neural activity.
More details ⬇️

Interoception vs. Exteroception: Cardiac interoception competes with tactile perception, yet also facilitates self-relevance encoding https://www.biorxiv.org/content/10.1101/2025.06.25.660685v1

Lucky for you, lazy people at #RLDM2025, two of the best posters have apparently been put side-by-side: go check @maevalhotellier.bsky.social and @constancedestais.bsky.social posters!

🧵 New preprint out!
📄 "Elucidating attentional mechanisms underlying value normalization in human reinforcement learning"
👁️ We show that visual attention during learning causally shapes how values are encoded
w/ @sgluth.bsky.social & @stepalminteri.bsky.social
🔗 doi.org/10.31234/osf...

🚨 New preprint on bioRxiv!

We investigated how the brain supports forward planning & structure learning during multi-step decision-making using fMRI 🧠

With A. Salvador, S. Hamroun, @mael-lebreton.bsky.social & @stepalminteri.bsky.social

📄 Preprint: submit.biorxiv.org/submission/p...

@magdalenasabat.bsky.social used 🔌 ephys to show that ferret auditory cortex neurons integrate sounds within fixed windows (~15–150 ms) that increase in non-primary auditory cortex, independent of information rate.
▶️ www.biorxiv.org/content/10.1...
#Neuroscience

🎉 I'm excited to share that 2 of our papers got accepted to #RLDM2025!

📄 NORMARL: A multi-agent RL framework for adaptive social norms & sustainability.
📄 Selective Attention: When attention helps vs. hinders learning under uncertainty.

Grateful to my amazing co-authors! *-*

🚨 Finally out! My new @annualreviews.bsky.social in Psychology paper:
www.annualreviews.org/content/jour...
We unpack why psych theories of generalization keep cycling from rigid rule-based models to flexible similarity-based ones, then culminating in Bayesian hybrids. Let's break it down 👉 🧵

Epistemic biases in human reinforcement learning: behavioral evidence, computational characterization, normative status and possible applications.

A quite self-centered review, but with a broad introduction and conclusions and very cool figures.

Few main takes will follow

osf.io/preprints/ps...

New preprint! 🚨

Performance of standard reinforcement learning (RL) algorithms depends on the scale of the rewards they aim to maximize.
Inspired by human cognitive processes, we leverage a cognitive bias to develop scale-invariant RL algorithms: reward range normalization.
Curious? Have a read!👇

🚨New preprint alert!🚨

Achieving Scale-Invariant Reinforcement Learning Performance with Reward Range Normalization.

Where we show that things we discover in psychology can be useful for machine learning.

By the amazing
@maevalhotellier.bsky.social and Jeremy Perez.
doi.org/10.31234/osf...