Lénárd Döme

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'

1/

First-ever ranking of journals by impact factor, published by Garfield in Science in 1972.

Science is ranked #77, impact factor 2.99
Nature is #114, impact factor 2.34

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!

Academia will form these little pockets -- people whose theorizing is outrageous & supported by methods outdated since the 90s -- but once it reaches a critical size those people just review each others papers & grants, form societies, hand out awards etc, like a self-contained parallel society.

Table 1 Typology of traps, how they can be avoided, and what goes wrong if not avoided. Note that all traps in a sense constitute category errors (Ryle & Tanney, 2009) and the success-to-truth inference (Guest & Martin, 2023) is an important driver in most, if not all, of the traps.

NEW paper! 💭🖥️

“Combining Psychology with Artificial Intelligence: What could possibly go wrong?”

— Brief review paper by @olivia.science & myself, highlighting traps to avoid when combining Psych with AI, and why this is so important. Check out our proposed way forward! 🌟💡

osf.io/preprints/ps...

📢 We still have some places left, but they are limited – so don't miss out!

New to computational modelling? Or want to sharpen your workflow? This workshop is for you – based on our easy-to-use library that does modelling for you: cpm-toolbox.net

Extend your stay at #CPConf2025
Sign up now👇

Individuals with substance use disorders experience an increased urge to move to complex music Jan Stupacher https://orcid.org/0000-0002-2179-2508 stupacher@clin.au.dk, Benedetta Matarrelli, Danilo Cozzoli, +4 , and Elvira Brattico https://orcid.org/0000-0003-0676-6464 elvira.brattico@clin.au.dkAuthors Info & Affiliations Edited by Peter Strick, University of Pittsburgh Brain Institute, Pittsburgh, PA; received February 4, 2025; accepted March 25, 2025 May 12, 2025 122 (20) e2502656122 https://doi.org/10.1073/pnas.2502656122

"data: everything that happened in the 1990s"

Deportation for honking his horn at an undercover ICE officer

The Surveillance AI Pipeline A rapidly growing number of voices argue that AI research, and computer vision in particular, is powering mass surveillance. Yet the direct path from computer vision research to surveillance has remai...

we did a systematic analysis of over 40k CV & CV research based patents and found that the field is not advancing cancer research or anything useful but rather powering surveillance arxiv.org/abs/2309.15084

There was a paper shared on BlueSky a few months ago with an example of a #LLM happily proving a false variation of a basic calculus theorem (was it the intermediate value theorem?). Now I can't find it. Anyone remember this? #AI

Happy to share some new theoretical work with @andyperfors.bsky.social
that will appear at CogSci this year! We argue (and demonstrate through simulations) that people can determine how much to trust other agents by thinking about how those agents have acquired their knowledge. 1/3