Jozsef Arato

while most people become less accurate. We did not find the expected effects, that is a beneficial effect of observation on the easier (2-back), but a hindering in the more difficult (3-back) condition. Individual differences in how people react to observation seem stronger than our manipulation.

while either being observed via a video call or not. We found that social pressure results in an overall less accurate but faster performance in the n-back task. It turns out that this is not due to a speed accuracy trade-off, as some people actually get faster and more accurate under pressure,

Preprint! My first paper as a senior author, work by my first master student, Nikita Podolin! Facilitation or impairment: Social evaluation affects working memory through factors beyond task difficulty osf.io/preprints/ps... In this preregistered study, subjects performed a working memory task

Nice to see some commentary on the recent @theguardian.com piece by @iansample.bsky.social on #SciPub #AcademicPublishing #OpenAccess #ACADEMICsky

www.theguardian.com/science/2025...

Lions and Dolphins can not make babies: Why human connectomes can probably not be useful for AI How evolutionary thinking can make the debate more precise

Why human connectomes can probably not be useful for AI
open.substack.com/pub/kording/...

highly recommended summer school!

🚨 #Internship alert in #MachineLearning
I am recruiting a BSc (or MSc) student in #ComputerScience #DataScience for an internship this Spring
On-site @univie.ac.at or remotely
Possibility to develop a BSc/MSc thesis project
Please share around & reach out if you have any questions!
More details 🔽

Re the Tononi paper: Both Tononi’s IIT (phi) and Friston’s FEP start from fundamental, axiomatic, and debatable assumptions. These assumptions are generally made without any humility. This logic allows them to make exceptionally broad claims. Which contributes to my unease about them.

"Large language models surpass human experts in predicting neuroscience results" w @ken-lxl.bsky.social
and braingpt.org. LLMs integrate a noisy yet interrelated scientific literature to forecast outcomes. nature.com/articles/s41... 1/8

We show this effect both with explicit and implicit learning, that over-time show similar eye movement changes. At the same time, there is robust statistical learning, without any influence on eye movements. 3/3

Using a gaze contingent stimulus paradigm, we show that eye movements adapt to hidden spatial regularities of visual scenes, predicting individual statistical learning performance. 2/3

My main phd project is finally out in JOV! Eye movements reflect active statistical learning. co-authors: Constantin Rothkopf and József Fiser jov.arvojournals.org/article.aspx....

I guess the number of reactions answer your question regarding bsky..

Large language models surpass human experts in predicting... Scientific discoveries often hinge on synthesizing decades of research, a task that potentially outstrips human information processing capacities. Large language models (LLMs) offer a solution....

"Large language models surpass human experts in predicting neuroscience results" w @ken-lxl.bsky.social and braingpt.org. LLMs integrate a noisy yet interrelated scientific literature to forecast outcomes. arxiv.org/abs/2403.03230 1/6

🤦‍♂️

Table with 3 rows and 3 columns. Rows: (1) Algorithm purist (mimic human cognition), (2) Algorithm netural (learns & generalizes), (3) Algorithm rebel (method irrelevant) Cols: (1) Ability purist (exceeds human ability), (2) Ability neutral (makes task easier), (3) Ability rebel (usefullness questionable) Cells: [1,1] "Terminator is AI" [1,2] "C3PO is AI" [1,3] "WALL-E is AI" [2,1] "AlphaGo is AI" [2,2] "XGBOOST is AI" [2,3] "Tinder is AI" [3,1] "A metal detector is AI" [3,2] "Bubble sort is AI" [3,3] "Magic 8 Ball is AI"

I told a colleague that logistic regression is AI and they got mad at me, so I made a chart. Find yourself. I am "Tinder is AI". (I posted this on that other site and a friend complained "y u no skeet this too!?!!?" so here you go)

2023 Seed Grant Call 2023 Seed Grant Call

Hello #CogSci,
We just announced our 2023 Seed Grant Call which provides funds for applicants to develop, write, and submit an interdisciplinary research proposal in the broad field of cognitive science that will help them move their career forward.
Feel free to share with interested colleagues!