🚀 We are hiring! 🚀

🔍 Join us as a Postdoctoral Researcher (fully-funded) at the Helmholtz Institute for Human-Centered AI in Munich.

Leveling up fun: learning progress, expectations, and success influence enjoyment in video games Scientific Reports - Leveling up fun: learning progress, expectations, and success influence enjoyment in video games

What influences whether people have fun with a task?

Our paper “Leveling up fun: learning progress, expectations and success influence enjoyment in video games” with @thecharleywu.bsky.social and @ericschulz.bsky.social now in Scientific Reports!

rdcu.be/eI069

Paper summary below 1/4

Also happy to announce that our Automated scientific minimization of regret paper got accepted to the AI4Science workshop at #NeurIPS - arxiv.org/abs/2505.17661 with @marcelbinz.bsky.social, @akjagadish.bsky.social & @ericschulz.bsky.social

New in @pnas.org: doi.org/10.1073/pnas...

We study how humans explore a 61-state environment with a stochastic region that mimics a “noisy-TV.”

Results: Participants keep exploring the stochastic part even when it’s unhelpful, and novelty-seeking best explains this behavior.

#cogsci #neuroskyence

I don't know much about those fields specifically, but there are some examples www.nature.com/articles/s42..., arxiv.org/abs/2504.096..., www.sciencedirect.com/science/arti...

Generating Computational Cognitive Models using Large Language Models Computational cognitive models, which formalize theories of cognition, enable researchers to quantify cognitive processes and arbitrate between competing theories by fitting models to behavioral data....

Happy to announce our paper got accepted to #NeurIPS!
@akjagadish.bsky.social @marvinmathony.bsky.social @ericschulz.bsky.social & Tobi Ludwig

arxiv.org/abs/2502.00879

congratulations dude!!!!! 🐣🐣🐣

Excited to see our Centaur project out in @nature.com.
TL;DR: Centaur is a computational model that predicts and simulates human behavior for any experiment described in natural language.

Dopamine encodes deep network teaching signals for individual learning trajectories Longitudinal tracking of long-term learning behavior and striatal dopamine reveals that dopamine teaching signals shape individually diverse yet systematic learning trajectories, captured mathematical...

Does the brain learn by gradient descent?

It's a pleasure to share our paper at @cp-cell.bsky.social, showing how mice learning over long timescales display key hallmarks of gradient descent (GD).

The culmination of my PhD supervised by @laklab.bsky.social, @saxelab.bsky.social and Rafal Bogacz!

Generating Computational Cognitive Models using Large Language Models Computational cognitive models, which formalize theories of cognition, enable researchers to quantify cognitive processes and arbitrate between competing theories by fitting models to behavioral data....

Preprint update, co-led with @akjagadish.bsky.social, with @marvinmathony.bsky.social, Tobias Ludwig and @ericschulz.bsky.social!

🚨 New in Nature Human Behavior! 🚨

Binary climate data visuals amplify perceived impact of climate change.

Both graphs in this image reflect equivalent climate change trends over time, yet people consistently perceive climate change as having a greater impact in the right plot than the left.

👇1/n

We are looking for two PhD students at our institute in Munich.

Both postions are open-topic, so anything between cognitive science and machine learning is possible.

More information: hcai-munich.com/PhDHCAI.pdf

Feel free to share broadly!

Nestlé Buys E.Coli For $2.3 Billion VEVEY, SWITZERLAND—With the food conglomerate saying the acquisition made sense given its longstanding strategic partnership with the pathogen, Nestlé released a statement Friday confirming it had pur...

Nestlé Buys E.Coli For $2.3 Billion

hear hear

very happy to be presenting this at @cosynemeeting.bsky.social

Son-Of-A-Bitch Mouse Solves Maze Researchers Spent Months Building

Son-Of-A-Bitch Mouse Solves Maze Researchers Spent Months Building
theonion.com/son-of-...

Every experience is unique 🌟 light shifts, angles change, yet we recognize objects effortlessly. How do our minds do this? And (how) do they differ from machines? In our new preprint with @ericschulz.bsky.social, we review human generalization and compare it to machine generalization: osf.io/k6ect

Towards Automation of Cognitive Modeling using Large Language Models Computational cognitive models, which formalize theories of cognition, enable researchers to quantify cognitive processes and arbitrate between competing theories by fitting models to behavioral data....

About a month late posting this, but here's a new project with @ericschulz.bsky.social, @akjagadish.bsky.social, @marvinmathony.bsky.social and Tobias Ludwig

We are using LLMs to propose cognitive models in learning and decision making data. Presenting this work at RLDM!

arxiv.org/abs/2502.00879

Scatterplot titled “Empirical Evidence of Ideological Targeting in Federal Layoffs: Agencies seen as liberal are significantly more likely to face DOGE layoffs.” • The x-axis represents Perceived Ideological Leaning of federal agencies, ranging from -2 (Most Liberal) to +2 (Most Conservative), based on survey responses from over 1,500 federal executives. • The y-axis shows Agency Size (Number of Staff) on a logarithmic scale from 1,000 to 1,000,000. Each point represents a federal agency: • Red dots indicate agencies that experienced DOGE layoffs. • Gray dots indicate agencies with no layoffs. Key Observations: • Liberal-leaning agencies (left side of the plot) are disproportionately represented among red dots, indicating higher layoff rates. • Notable targeted agencies include: • HHS (Health & Human Services) • EPA (Environmental Protection Agency) • NIH (National Institutes of Health) • CFPB (Consumer Financial Protection Bureau) • Dept. of Education • USAID (U.S. Agency for International Development) • The National Nuclear Security Administration (DOE), despite its conservative leaning (+1 on the scale), is an exception among targeted agencies. • A notable outlier: the Department of Veterans Affairs (moderately conservative) also faced layoffs despite its size. Takeaway: The figure visually demonstrates that DOGE layoffs disproportionately targeted liberal-leaning agencies, supporting claims of ideological bias. The pattern reveals that layoffs were not driven by agency size or budget alone but were strongly associated with perceived ideology. Source: Richardson, Clinton, & Lewis (2018). Elite Perceptions of Agency Ideology and Workforce Skill. The Journal of Politics, 80(1).

The DOGE firings have nothing to do with “efficiency” or “cutting waste.” They’re a direct push to weaken federal agencies perceived as liberal. This was evident from the start, and now the data confirms it: targeted agencies overwhelmingly those seen as more left-leaning. 🧵⬇️

Dual process impairments in reinforcement learning and working memory systems underlie learning deficits in physiological anxiety Anxiety has been robustly linked to deficits in frontal executive function including working memory (WM) and attentional control processes. However, although anxiety has also been associated with impa...

Check out our new work from Jennifer Senta, with Sonia Bishop, looking at how physiological anxiety relates to impairments in both working memory and reinforcement learning processes

www.biorxiv.org/content/10.1...

Apologies for the lack of tags for folks w Bluesky accounts, I still don’t know how this thing works, I fear my inner boomer is showing

Dual process impairments in reinforcement learning and working memory systems underlie learning deficits in physiological anxiety Anxiety has been robustly linked to deficits in frontal executive function including working memory (WM) and attentional control processes. However, although anxiety has also been associated with impa...

Second preprint (with Anne Collins and Sonia Bishop) explores different anxiety-related deficits in RL and working memory:

www.biorxiv.org/content/10.1...

Not one, but TWO cool preprints by Jennifer Senta!

First preprint (with Anne Collins, Peter Dayan and Sonia Bishop) has a really cool use of modeling aimed at dissociating mechanisms underlying depression and anxiety-related phenotypes:

osf.io/preprints/ps...

In our latest article, published in @pnas.org and led by @marcelbinz.bsky.social and Stephan Alaniz, we got together four diverse groups of scientists to reflect on how LLMs should affect science. From treating them like co-authors to using other tools instead, many interesting arguments emerged.

What do you suppose they are talking about?

👏👏👏👏👏

Would it violate the ethics protocol to reveal participant’s name? 🐈

Home The Translational Lab focuses on when and why decision-making goes awry in depression and anxiety disorders and on developing potent and scalable interventions to improve it. We leverage careful expe...

Hi new followers! 👋 My lab has lots of projects underway studying why *mental behavior* goes off the rails — leading to thinking patterns like rumination and worry 🌀 — and how we can make it more effective.

* Sketch of our approach: tinyurl.com/r3tvmbn9

* Lab website: www.translational-lab.com

Even a good advisor and a nice lab likely won't make a difference if one can't check off the 3 points above (and probably a few others, but who has time) and say 'I am fine with all of this and I can do it'.

4. A super common advice one always hears is "Find a good advisor, it is what makes or breaks a grad school experience" and "Lab culture is important". This is true. However, seems like the 3 points above are precursors to this being something that actually matters.