cybernetic cognitive control 🤖 computational cognitive neuroscience 🧠 postdoc princeton neuro 🍕 he/him 🇨🇦
Princeton, NJ
Joined April 2016
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Excited to share a new project! 🎉🎉
doi.org/10.1101/2024.09.29.6…
How do we navigate between brain states when we switch tasks? Are dynamics driven by control, or passive decay of the prev task?
To answer, we compare high-dim linear dynamical systems fit to EEG and RNNs🌀
⏬
Harrison Ritz retweeted
In our new @CommsPsychol review, we explore how humans adjust learning to different types of uncertainty, why biases arise, and what this reveals about learning and psychiatric conditions.
📖 Read more: nature.com/articles/s44271-0…
With @NassarLab & @haukeren
Harrison Ritz retweeted
Excited to share (over here) that in January, I'll start as an Asst Professor @SFU Psych! 🏞️
I'm recruiting a lab manager & my 1st grad student. If you're interested in social cognition/perception, stereotyping, & transformative experiences, check out socosci.com~🦉
Harrison Ritz retweeted
If you've used @IntlBrainLab data or tools in some way, could you spare 1 minute to tell us how?
short survey: docs.google.com/forms/d/e/1F…
Thanks in advance! 🙏
Harrison Ritz retweeted
From double descent to grokking, deep learning sometimes works in unpredictable ways.. or does it?
For NeurIPS,@Jeffaresalan & I explored if&how statistics + smart linearisation can help us better understand&predict numerous odd deep learning phenomena — and learned a lot..🧵1/n
Harrison Ritz retweeted
(1/5) Very excited to announce the publication of Bayesian Models of Cognition: Reverse Engineering the Mind. More than a decade in the making, it's a big (600+ pages) beautiful book covering both the basics and recent work: mitpress.mit.edu/97802620494…
Harrison Ritz retweeted
uploaded later than i hoped, but here's my step-by-step video guide on ✨HOW TO WRITE A STATEMENT OF PURPOSE!✨ in it, i analyze my very own SoP that got me into Harvard + other top schools 😍 please share widely! #phdchat #admissions youtube.com/watch?v=fQP1rXzZ… – at Onna-son, Okinawa
Harrison Ritz retweeted
Do you want to understand how language models work, and how they can change language science? I'm recruiting PhD students at UBC Linguistics! The research will be fun, and Vancouver is lovely. So much cool NLP happening at UBC across both Ling and CS! linguistics.ubc.ca/graduate/…
Harrison Ritz retweeted
🤖🧠 I'll be considering applications for postdocs & PhD students to start at Yale in Fall 2025!
If you are interested in the intersection of linguistics, cognitive science, & AI, I encourage you to apply!
Postdoc link: rtmccoy.com/prospective_post…
PhD link: rtmccoy.com/prospective_stud…
ALT Top: A syntax tree for the sentence "the doctor by the lawyer saw the artist". Bottom: A continuous vector.
Harrison Ritz retweeted
Dear colleagues: we just released a call for an exciting Special Issue for #psynomCABN: “Trying in the 21st Century: A New Look at the Neuroscience of Effort”, with an outstanding group of guest editors. Abstract submission due 12/15/24. Details at tinyurl.com/44r6mw4y. Pls RT
Harrison Ritz retweeted
Our latest pre-print to be presented at hashtag #Neurips2024. Check it out! RTify: Aligning Deep Neural Networks with Human Behavioral Decisions. arxiv.org/abs/2411.03630
Harrison Ritz retweeted
👀🍟Now out in Cognitive Science 😋🤖
We present a new approach that combines cognitive models and neural networks to predict latent preferences.
onlinelibrary.wiley.com/doi/…
ALT Inverting Cognitive Models With Neural Networks to Infer Preferences From Fixations Evan M. Russek, Frederick Callaway, Thomas L. Griffiths Neural networks can be pretrained on simulated data from cognitive models to infer people’s preferences from their behavior. This approach enables the prediction of preferences from eye fixations made before a choice, even with limited human data.
Harrison Ritz retweeted
New preprint with @DaniSBassett and @nathanieldaw!
How do humans learn predictive representations? We propose a trial-by-trial learning rule that incorporates trace updating to learn the SR.
biorxiv.org/content/10.1101/…
Harrison Ritz retweeted
Bluesky adds 700,000 new users in a week trib.al/HlfBOpD
Harrison Ritz retweeted
NSF makes you say who you got conflicts (coauthored) with. We (really just Jordan Matelsky @j6m8 ) just built you a tool for that. Literally one click (on top of revealing your name): bib.experiments.kordinglab.c… - one of the most useful tools the lab ever built.
Harrison Ritz retweeted
🔥 This is now out on @eLife as a reviewed preprint. We got some really interesting comments that we’re planning to address, all public, and see how it goes!
elifesciences.org/reviewed-p…
2 years into making, the last chapter of my PhD thesis, and a set of wonderful collaborators: @m00rcheh, @ShreyDixitAI, @misicbata, @caioseguin, @GZamora_Lopez, @CCHilgetag.
🧵 What can we learn about communication in brain networks from 7000 million virtual lesions:
Harrison Ritz retweeted
Modeling brain signaling as Markovian helps explain its structure-function relationship biorxiv.org/cgi/content/shor… #biorxiv_neursci
Harrison Ritz retweeted
1 monkey recovered safely, 42 others remain on the run from South Carolina lab apnews.com/article/escaped-r…
Harrison Ritz retweeted
🌟 Cai Lab @Nature paper alert! In new work led by @mysteriousjoe_, we find that rest periods after learning not only stabilize new memories BUT ALSO integrate new memories with older ones from days past! (1/9)
Read it here: nature.com/articles/s41586-0…
