Lucas Castillo

Thank you! And thanks @pleonv.bsky.social, Nick Chater, and @asanborn.bsky.social who were an essential part of this paper

See samplr package: lucas-castillo.github.io/samplr/

🚀🚀 Very excited about this new preprint with @yunxiao-li.bsky.social and @asanborn.bsky.social!

Months ago we released the samplr package on CRAN (helps you use sampling algorithms + cogn. models for human data). Here we explain the theoretical background and show how to use the pkg

osf.io/ax8hm

Our lab has a list of papers that use statistical sampling algorithms like MCMC to explain human behaviour. Thanks to @lcastillo.bsky.social, you can select by behaviour or algorithm.

If we've missed any, please let us know!

sampling.warwick.ac....

YouTube video by Michael Spicer Tory MP IT Support

Tory MP IT Support

Thrilled to share my first post here with something I’m truly proud of; My PhD paper is finally out in @commspsychol.bsky.social. Thanks to amazing @ktsetsos.bsky.social for his wise insights and our reviewers for their constructive comments.
You can read the full paper here: rdcu.be/eguDX
1/10

🚀 Revised Reviewed Preprint out in eLife 🚀
Excited to announce that my paper on the cognitive mechanisms underlying hunger-driven dietary choice is now available on @elife.bsky.social
elifesciences.org/reviewed-pre...

"Noise in Cognition: Bug or Feature?" is now available in Perspectives on Psychological Science
doi.org/10.1177/1745... (1/4)

🚀 New paper out in Psychological Review!

How does learning change across the lifespan? We propose that resource rationality—adapting belief updating to cognitive limitations—can explain age-related differences in learning.

📖 doi.org/10.1037/rev0...

👇 A short thread:

🚨 A new preprint is out!

How does utility influence mental simulations of risky events? 🤔🎲

We tested this across 4 experiments & found that most people simulate probabilities accurately, but biases emerge in key conditions!

If you want to learn more, keep reading!
doi.org/10.31234/osf...

with @pleonv.bsky.social, Johanna Falbén, Nick Chater and @asanborn.bsky.social. Thank you!
(8/8)

If you use randomness in cognitive models: if you were using it as a catch-all for unexplained variance then keep at it, but if your model postulates that people use random draws then consider the time frame used and if lower than 2s consider autocorrelated noise instead. (7/8)

If you like to be creative, explore the world, make good choices, be protected from agents exploiting patterns in your behavior: this is good news! We now know that the strategy of behaving randomly is available to humans and doesn't need much time, which is useful in all these domains.

(6/8)

We found people's sequences are random if 2-4s elapse between items! 🤯🤯

In the experiment we ran we asked people to do the task at two different speeds and so we could test whether it's time that matters (as in the weather) or number of items (as in card shuffles). The answer: time ⌛⌛⌛(5/8)

Schematic representing the process of thinning sequences: on top, the original sequence reads 1, 8, 6, 2, 5, etc. Below, a thinned sequence reads 1, 6, 5 (every second item). Sequences below show thinning every third item and every seventh item.

We analysed previous data from experiments asking people to generate sequences at random, and did our own experiment: we looked at altered versions of the sequences where we skipped some items (thinned sequences). This way we could evaluate sequences at different delays between items. (4/8)

We thought: actual random stuff isn't random instantaneously (the weather is unpredictable some time from now; a deck of cards needs a few shuffles). Maybe we haven't given people enough time? (3/8)

Being able to generate randomness would be quite useful (to avoid others taking advantage of patterns in your behavior, to be creative, to explore your environment...) -- BUT! Research on human random generation says people cannot do this (2/8)

New Preprint Out! 🚀🚀
Can people generate a random sequence if given enough time?

Keep reading if
- You make cognitive models with randomness in them
- You like to explore the world, be creative, choose well
- You want protection from clever agents exploiting patterns in your behavior.
osf.io/awg9j

Michaela Pawley is awarded a UK Data Impact Fellowship 2025-26. Congratulations!

🎉 Congratulations to @michaelapawley.bsky.social, a PhD student of the Warwick Sleep and Pain Lab @nkytang.bsky.social, on being awarded a UK Data Impact Fellowship from the @ukdataservice.bsky.social! This competitive programme supports 5 early career researchers using UK Data Service resources.

In our new preprint, my co-authors and I explore how people’s probability judgments sometimes don’t add up the way they should, and how these violations can help us compare different models of how people make these judgments!

osf.io/preprints/ps...