Lénárd Döme

📢 NEW PREPRINT 📢 We show a metacognitive paradox (not blanket deficit!) in OCD: confidence is persistently lower, but fluctuations track evidence more tightly and are nearer Bayes-optimal.

www.researchsquare.com/article/rs-7...
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A new preprint 📝 with @tobiasuhauser.bsky.social @kenzakdr.bsky.social @benjwagner.bsky.social
and Andrew Webb accompanying our cpm-toolbox.net python modelling library - including details about our motivations, toolbox features, framework and workflows!

👉 osf.io/preprints/ps...

Some really cool stuff here! Really glad to have been involved in the making 📝🥳

day-to-day fluctuations of confidence (across multiple domains) relate to OCD symptom reports

Journal publishers *are* bundling your papers up in "data licensing agreements" for big tech companies to use for AI model training. Our publisher, T&F, got £75m from Microsoft for that last year alone.

2 Reasons Behind The Sudden ‘Labubu’ Craze, According To A Psychologist Some are baffled by how quickly Labubu’s have taken the world by storm. But, psychologically, trends like these are anything but surprising.

Our research on video game loot boxes was cited in a recent Forbes article about Labubus. The article was a systematic review exploring the links between loot boxes, problem gambling and problem video gaming. In other words, purchases with chance-based outcomes. 1/2

www.forbes.com/sites/traver...

Release v0.23.18 - New Prospect Models, improved parameter management, and a few bug fixes · DevComPsy/cpm Install You can install the new release straight from the PyPi repository: pip install cpm-toolbox Added Add input validation and error handling in all cpm.optimisation.minimise methods Add test u...

New models (three variants of Prospect Theory), new features (more ways to manage parameters, more model components to use), and of course bug fixes. If you want to make your computational modelling reproducible and robust, check out and install the new version of *cpm*:

github.com/DevComPsy/cp...

AI slop and the destruction of knowledge This week I was looking for info on what cognitive scientists mean when they speak of ‘domain-general’ cognition. I was curious, because the nuances are relevant for something I am researching at t…

AI slop and the destruction of knowledge irisvanrooijcogsci.com/2025/08/12/a...

Don’t think too much … it might make you irrational Every so often, I get random chest pain and immediately spiral – is this it? Am I having a heart attack? Then I remind myself that I’m 25, probably overcaffeinated, and maybe just a little stressed…

Ever have a symptom & assume the worst? That’s the Inverse Base Rate Effect—we over-focus on rare outcomes. A new #psynomPBR study by Dome @lenarddome.bsky.social & Wills finds distraction & time pressure can reduce this bias. Post by Alyssa Asmar. buff.ly/FTDQE25

I wonder how much tax money goes into research programmes likely this? In Europe for example? A shame indeed

So excited to share that the NeNa registrations are open now! Can’t wait to see everyone in Heidelberg this October. 🎓🍂

5. The right-wing enthusiasm for AI science is not about doing better science faster. It’s about eliminating one of the most effective forms of societal resistance to authoritarian control.

“Even the term 'Artificial Intelligence' … is widely misused, with conceptual unclarity coopted to advance industry agendas and undermine scholarly discussions. It is our task to demystify and to challenge 'AI' in our teaching, research & engagement with society.” openletter.earth/open-letter-...

Models should be constrained on their behavioural heterogeneity and we should be concerned about the number of Unobserved Model Prediction (UMP) they can produce

A quote from Rumelhart/McClelland: "...real biological systems cannot be Turing machines because they have finite hardware."

A sentiment somewhat related to our g-distance framework. What portion of unobserved but possible results your model rejects?

#CPConf2025 is exploring multidimensional reward functions #RufusTempleOrchestra

I'm very excited to share that @wellcometrust.bsky.social has awarded us a big grant on studying information gathering biases in #OCD and #Schizophrenia in patients, rodents, using modelling & clinical interventions.
More details here: devcompsy.org/2025/07/15/n...

Come check out my poster on an accessible new python library cpm (cpm-toolbox.net) designed to ease you into modelling in computational psychiatry #CPConf2025

I’m poster 1.2 👀

A packed cinema for Charlotte Fraza's tutorial on normative modelling #CPConf2025

Serious FOMO here #CPConf2025

a couple of hours before my keynote, I went through an intense negotiation with the organisers (for over a hour) where we went through my slides and had to remove anything that mentions 'Palestine' 'Israel' and replace 'genocide' with 'war crimes'

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Save the date: Australiasian Mathematical Psychology Conference. 23-25 Feburary 2026. Singapore. "Applying mathematical and quantitative psychology to real-world complex problems"

Save the date! The 2026 *gasp* Australasian MathPsych conference will be in Singapore -- looks to be a great one :)
@ozmathpsych.bsky.social

New paper accepted at ACL Findings! TL;DR: While language models generally predict sentences describing possible events to have a higher probability than impossible (animacy-violating) ones, this is not robust for generally unlikely events and is impacted by semantic relatedness. 1/3

Mental graphs structure the storage and retrieval of visuomotor associations - Nature Human Behaviour Trach and McDougle show that motor responses can form part of structured, graph-like memory representations.

Thrilled to share the new paper from the lab out today in
@nathumbehav.nature.com, led by the great @jetrach.bsky.social!

"Mental graphs structure the storage and retrieval of visuomotor associations"

www.nature.com/articles/s41...

I'm excited to announce that my lab's open textbook on Scientific Computing for Cognitive Neuroscience (v1.0) has just gone live! Our goal is to help mend the gap between the computational skills needed by cognitive neuroscience, and typical curricula that don't yet include it. 1/3

Greta Thunberg. Overlaid text reads: Israel’s navy has intercepted a Gaza-bound aid ship and detained Greta Thunberg

Israeli commandos boarded the ship, which was attempting to break the blockade of Gaza, in international waters off the coast of the territory, according to the move's organisers. www.ft.com/content/16a4...

sam.hall-mcmaster (Sam Hall-McMaster) sam.hall-mcmaster has 0 followers and is following 0 people.

Special kudos for Sam to release 1.3T of carefully organised and documented neuroimaging data that other researchers can use for future discoveries: gin.g-node.org/sam.hall-mcm...

Builder.ai® - Composable Software Development Platform Get your software applications developed easily. AI makes developing your software applications on our award-winning platform faster and more cost-effective. See how it works.

For eight years, Builder .ai marketed its "Natasha" AI system as a fully autonomous tool that could build software "as easily as ordering pizza." In reality, engineers in Noida and Bangalore manually coded client projects while being instructed to mimic AI-generated responses.

I’m starting to think this is a systemic issue

www.yusufimaadkhan.com/posts/mills-...

Overview of the simulation strategy and analysis. a) Pial and white matter boundaries surfaces are extracted from anatomical MRI volumes. b) Intermediate equidistant surfaces are generated between the pial and white matter surfaces (labeled as superficial (S) and deep (D) respectively). c) Surfaces are downsampled together, maintaining vertex correspondence across layers. Dipole orientations are constrained using vectors linking corresponding vertices (link vectors). d) The thickness of cortical laminae varies across the cortical depth (70–72), which is evenly sampled by the equidistant source surface layers. e) Each colored line represents the model evidence (relative to the worst model, ΔF) over source layer models, for a signal simulated at a particular layer (the simulated layer is indicated by the line color). The source layer model with the maximal ΔF is indicated by “˄”. f) Result matrix summarizing ΔF across simulated source locations, with peak relative model evidence marked with “˄”. g) Error is calculated from the result matrix as the absolute distance in mm or layers from the simulated source (*) to the peak ΔF (˄). h) Bias is calculated as the relative position of a peak ΔF(˄) to a simulated source (*) in layers or mm.

🚨🚨🚨PREPRINT ALERT🚨🚨🚨
Neural dynamics across cortical layers are key to brain computations - but non-invasively, we’ve been limited to rough "deep vs. superficial" distinctions. What if we told you that it is possible to achieve full (TRUE!) laminar (I, II, III, IV, V, VI) precision with MEG!