Konstantina Sokratous

Internal World Models as Imagination Networks in Cognitive Agents What is the computational objective of imagination? While classical interpretations suggest imagination is useful for maximizing rewards, recent findings challenge this view. In this study, we propose...

World models are a highly speculative topic in AI as well as in cognitive science. I’m excited to share my manuscript on investigating internal world models using imagination networks in humans and LLMs! 🧵1/n

arxiv.org/abs/2510.04391

Screenshot of the article "How Convincing Is a Crowd? Quantifying the Persuasiveness of a Consensus for Different Individuals and Types of Claims"

We know that a consensus of opinions is persuasive, but how reliable is this effect across people and types of consensus, and are there any kinds of claims where people care less about what other people think? This is what we tested in our new(ish) paper in @psychscience.bsky.social

Congratsss, great work!!

Would love to be included Katharina!

Cover page for the manuscript: Morey, R. D., & Davis-Stober, C. P. (2025). On the poor statistical properties of the P-curve meta-analytic procedure. Journal of the American Statistical Association, 1–19. https://doi.org/10.1080/01621459.2025.2544397

Abstract for the paper: The P-curve (Simonsohn, Nelson, & Simmons, 2014; Simonsohn, Simmons, & Nelson, 2015) is a widely-used suite of meta-analytic tests advertised for detecting problems in sets of studies. They are based on nonparametric combinations of p values (e.g., Marden, 1985) across significant (p < .05) studies and are variously claimed to detect “evidential value”, “lack of evidential value”, and “left skew” in p values. We show that these tests do not have the properties ascribed to them. Moreover, they fail basic desiderata for tests, including admissibility and monotonicity. In light of these serious problems, we recommend against the use of the P-curve tests.

Paper drop, for anyone interested in #metascience, #statistics, or #metaanalysis! @clintin.bsky.social and I show in a new paper in JASA that the P-curve, a popular forensic meta-analysis method, has deeply undesirable statistical properties. www.tandfonline.com/doi/full/10.... 1/?

Josh Tenenbaum's inspiring keynote at #cogsci2025 on growing vs scaling AI, the big questions of cognitive science, and the many open questions for the field.

Xiaomin Li, Xupeng Chen, Jingxuan Fan, Eric Hanchen Jiang, Mingye Gao
Multi-head Reward Aggregation Guided by Entropy
https://arxiv.org/abs/2503.20995

Theory: Whtat to read The role of theory in cognitive science Or: my guide to what to read if you really want to understand how to do good, robust , theory-driven cognitive science. (disclaimer: this is an aspirational gu...

Inspired by my reading this week, I wrote a list of the resources I think every cognitive science researcher should read/listen to about theory development. It's in this google.doc (feel free to add your own suggestions) and in the thread below. docs.google.com/document/d/1...

How does exercise and fitness promote healthy brain aging?
An outstanding, comprehensive review @thelancet.bsky.social
reduced neuroinflammmation, preserves blood-brain-barrier, neurogenesis, role of exerkines, and much more
www.thelancet.com/journals/lan...

I'm excited about this new analysis approach because we can now estimate when changes in strategy, goal choice, conflict etc. occur in open state spaces. Providing metrics for studies with patients & sec-sec metrics for upcoming fMRI data and existing iEEG data with Sea Hero Quest
#neuroskyence

Nothing helps beat the pseudoscience label like humbly comparing your theory with no empirical support to the theory of general relativity 😂

🤣🤣

We had a wonderful time at this workshop w/ @blackinneuro.bsky.social!

If you missed seeing me & @shahana-ansari.bsky.social talk about how to give constructive & kind feedback on manuscripts, check out the recording – coming soon!

Huge thanks to the @blackinneuro.bsky.social team for having us! ❤️

AI-driven early detection of dementia using multimodal data at University of Bristol on FindAPhD.com PhD Project - AI-driven early detection of dementia using multimodal data at University of Bristol, listed on FindAPhD.com

Funded PhD opportunity for AI-driven early detection of dementia using multimodal data supervised by my colleague and friend Qiang Liu. Cannot recommend him more highly, I co-supervise a PhD student with him and this is an absolute bomb of an opportunity www.findaphd.com/phds/project...

Would love to be added!

I’d like to be added please :)

I’d like to be added please :)

I’d like to be added please :)

I’d like to be added as well :)

I’d like to be added please :)

Grant agency: "In the end, despite some initial enthusiasm, the panel was not convinced [...], and expected that the impact in the field is likely to be low."
Despite evidence to the contrary, funding bodies remain confident they can predict the success of a project.
elifesciences.org/articles/13323

I wish that I was able to convince the students in my class that the ultimate goal of science isn't accumulation of facts but the compression of facts into theories. Mel summarizes it well here:
www.nature.com/articles/nn1...
Unfortunately, I think this is a minority viewpoint within neuroscience.

This looks great, would love to be added!

Thank you for this! I would love to join

Would love to join the list!

Would love to join!

Would love to join!

👋

Open Encylopedia of Cognitive Science

Announcing the launch of the Open Encyclopedia of Cognitive Science: oecs.mit.edu! OECS is a freely-available, growing collection of peer-reviewed articles introducing key topics in cogsci to a broad audience of students and scholars.