Trying out a live demo in the documentation site.

Josh de Leeuw@joshdeleeuw.bsky.social · 2w ago

I've been working on improving webcam eye tracking for 3+ years and it's nearly ready to go. After a lot of ups and downs I'm in the excited phase again after the latest validation study!

Excited to give this a spin when it’s released!

Josh de Leeuw@joshdeleeuw.bsky.social · 2w ago

I've been working on improving webcam eye tracking for 3+ years and it's nearly ready to go. After a lot of ups and downs I'm in the excited phase again after the latest validation study!

Our paper is out in Nature Communications! In our messy, noisy world, do you find planning difficult/less worthwhile? It's not just you. As we increased the stochasticity in a planning environment, we found that people spent less effort planning: www.nature.com/articles/s41... #cogsci #planning

I think it's clear at this point that someone *could* get a bot to do online cognitive tasks without being detected. My question is: *would* anyone do this? Are cogpsych experiments (vs. surveys) really an appealing target for bad actors?

Ata Karagoz@atabk.bsky.social · 3w ago

I just had Opus 5.5 one shot a Human-Like mousetracking driver by looking at my code on cognition. Right now it's choosing left or right randomly. It's still not perfect but this took it literally a simple prompt and 1.5 mins to code a script. It can then be randomized and used across bot accounts.

I can't remember the last time I enjoyed a paper as much as this one. Such clear thinking. Beyond the compelling nativism-empiricism argument, it's among the best illustrations/explanations of levels of analysis I've seen. www.cell.com/trends/cogni...

The nativist–empiricist debate is broken

The nativist–empiricist debate has long organized cognitive science, framing cognitive mechanisms as either innate or learned. Recent advances in controlled rearing and scalable domain-general neural ...

cell.com

I take great joy in using a pullout faucet to create a "whirlpool" in the pot I'm washing, with peak joy ~exponential in rotational velocity. This surely points to something deep about human cognition, but I'm not sure what.

🚨New preprint with Fei Dai, @hanqizhou.bsky.social and @alisongopnik.bsky.social We extend empowerment (control over external states) by turning it inward. *Representational empowerment* asks which representations a learner should acquire and curate to solve future problems arxiv.org/abs/2609.02322

Alison Gopnik@alisongopnik.bsky.social · last mo.

New paper with really interesting ideas from Fei and Hanqui, empowerment as a way of discovering representations as well as actions

Excited to share the first first-author preprint of my PhD at NYU with @s-michelmann.bsky.social andDaryl Fougnie. Using eye-tracking in a novel behavioral paradigm, we reveal the mechanisms by which episodic memory (EM) and working memory (WM) interact. 🧠 doi: doi.org/10.64898/202...

bioRxiv Neuroscience@biorxiv-neursci.bsky.social · last mo.

Episodic memory rescues working memory via pattern separation, pattern completion, and predictive recall https://www.biorxiv.org/content/10.64898/2026.08.26.746101v1

How do we make good decisions with little experience? Adults can rely on memories of past choices. In our new study in @pnas.org we show kids & teens do something similar–but what they remember turns out to be quite different! www.pnas.org/doi/10.1073/...

Developmental changes in memory structure and precision alter the use of retrieved episodes during decisions for reward | PNAS

Most widely studied option evaluation strategies rely on knowledge accumulated across repeated experiences. But how should options be evaluated in ...

pnas.org

Why do societies reliably develop strikingly similar traditions like dance songs, hero stories, shamanism & justice institutions? In a new BBS target article, I propose a theory for such "super-attractors" + cultural evolution more broadly. Now open for commentary: www.cambridge.org/core/journal...

This. But I’d take it further. Most humans are most often substantially less logical and more biased than frontier models. Humans are still much smarter in many crucial ways, but internal consistency is not one of them.

Andrew Lampinen@lampinen.bsky.social · 2mo ago

Yet another (popular) article on human/LM reasoning that (as usual) I'm deeply disappointed to see casually presupposes that humans do something called "reasoning" that's implied to be linking together steps that logically follow without any qualification, then proceeds to be dismissive 1/

like us! No one is doing computer science and math with their naked brains. Pen & paper, math notation, computer language—these are our neurosymbolic add ons! @lampinen.bsky.social , @blaiseaguera.bsky.social , @kmahowald.bsky.social all get it. Not sure why this isn’t more obvious to folks

Andrea Lathrop@cabernet.bsky.social · 2mo ago

This is a very good point. It's an LLM-system, at this point, not a pure LLM, so theoretical critiques about what an LLM can or cannot do should not be taken to be predictions of what an LLM-plus-a-bunch-of-stuff can or cannot do.

So thrilled to be joining the Psychology Department at @columbiauniversity.bsky.social as an assistant prof next summer! I'll be recruiting for PhD/postdoc to start in Autumn 2027, so if you're interested in using computational approaches to studying human cognition please get in touch!

Tired of doom-scrolling bluesky? Try mitpuzzles.com!

Sam Cheyette@samcheyette.bsky.social · 3mo ago

are you a puzzle-enjoyer, or would you like to become one? try out a game or two at mitpuzzles.com! we're trying to figure out the factors that separate novice from expert problem solving, and what changes with experience, using self-motivated puzzle solving

So proud of Ted @languagemit.bsky.social! <3

We make flexible choices in new situations by knitting together information from separate relevant memories. But what governs which memories are retrieved and when? In a new preprint, we captured how people build decision variables from different memories by tracking their gaze on a blank screen.

Flexible decisions arise from resource-rational memory sampling

Flexible decision making depends on retrieving and recombining memories. Yet because this process unfolds covertly, its governing principles remain unknown. Here we use gaze reinstatement to uncover t...

biorxiv.org

How do human minds make sense of big, messy problems? 😵‍💫🌀 How do we distill complexity into something simple enough to solve? 🤔💡 We’ll be tackling these questions (and more!) at two workshops on task representations, abstractions, and construals #CogSci2026 #CCN2026 🧵 framing-the-problem.github.io

Framing the Problem — Workshop Series

A workshop series on representation construction in cognitive science and AI. CogSci 2026 (Rio) and CCN 2026 (NYU).

framing-the-problem.github.io

Pleased to share that this work is now published in TMLR! openreview.net/forum?id=RuW...

Andrew Lampinen@lampinen.bsky.social · last yr.

Why does AI sometimes fail to generalize, and what might help? In a new paper (arxiv.org/abs/2509.16189), we highlight the latent learning gap — which unifies findings from language modeling to agent navigation — and suggest that episodic memory complements parametric learning to bridge it. Thread:

I'm making a website for my new lab (!!!). Who should I steal ideas from? (Self-nominations welcome)

This is an actual line that was added to the official system prompt for Codex for GPT-5.5 by OpenAI. Usually the system prompt is as minimal as possible, so I assume it would otherwise mention goblins a lot. AIs are weird.

Good read. I'd go further and suggest that scientific evidence against behaviorism is impossible in principle. Behaviorism simply says that you can model behavior as p(behavior | experience, genes). Cognitivism just adds a latent state, r (representation): p(b|e,g) = ∫ p(b|r) p(r|e,g) dr. (1/4)

Stefano Palminteri@stepalminteri.bsky.social · 6mo ago

The more I study the issue and the original texts, the more the scientific arguments against behaviorism (and, conversely, in favor of the cognitive “revolution”) seem weaker to me. This is one of my favorite papers across all fields (and very convincing IMHO) www.academia.edu/75630727/The...

New preprint from my lab! We study how reinforcement learning & selective attention interact. To do so, we built a set of models describing different ways that value & reward prediction error can modulate top-down attention. We compare model outcomes to monkey data from a color value learning task

bioRxiv Neuroscience@biorxiv-neursci.bsky.social · 6mo ago

Modulation of feature attention by reward prediction error explains value learning behavior https://www.biorxiv.org/content/10.64898/2026.04.10.717847v1

📢📢 Announcing this year's conference on the Mathematics of Neuroscience & AI (Rome, 9-12th June). We’ve got a stellar line-up and venue, and invite everyone to join: www.neuromonster.org

I'm excited to announce that I had my first (co-authored) book published today! "The Rational Use of Cognitive Resources" with Falk Lieder and Tom Griffiths (@cocoscilab.bsky.social ). You can read it for free! (see thread)

Hybrid neural–cognitive models reveal how memory shapes human reward learning

Hybrid neural–cognitive models reveal how memory shapes human reward learning

Nature Human Behaviour, Published online: 05 February 2026; doi:10.1038/s41562-025-02324-0Using artificial neural networks applied to human data, Eckstein et al. show that good models of reinforcement learning require memory components that track representations of the past.

dlvr.it

Convincing evidence that people recall individual past experiences to inform decisions—specifically when an easier incremental learning strategy isn’t available. Also, a masterclass in experimental design.

Jonathan Nicholas@jonathannicholas.bsky.social · 9mo ago

Our experiences have countless details, and it can be hard to know which matter. How can we behave effectively in the future when, right now, we don't know what we'll need? Out today in @nathumbehav.nature.com , @marcelomattar.bsky.social and I find that people solve this by using episodic memory.

With some trepidation, I'm putting this out into the world: gershmanlab.com/textbook.html It's a textbook called Computational Foundations of Cognitive Neuroscience, which I wrote for my class. My hope is that this will be a living document, continuously improved as I get feedback.

Writing is thinking Outsourcing the entire task of writing to LLMs will deprive us of the essential creative task of interpreting our findings and generating a deeper theoretical understanding of the world.

How do we achieve few-shot generalization? New work led by @fabianrenz.bsky.social dives into the role of replay in learning and using structure to generalize reward. Dream team effort with Shany Grossman @nathanieldaw.bsky.social Peter Dayan & @doellerlab.bsky.social www.biorxiv.org/content/10.6...

Now out in JEP: General, "How working memory and reinforcement learning interact when avoiding punishment and pursuing reward concurrently" psycnet.apa.org/record/2026-... Preprint with final version: osf.io/preprints/ps... 1/n