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Richard Huskey

@richardhuskey.bsky.social

Associate Professor, UC Davis. PI, Cognitive Communication Science Lab. Associate Editor, Journal of Communication. Ski bum at heart. https://cogcommscience.com/

279 Posts2237 Follower 1772 Folgt

Psyche Loui @psycheloui.bsky.social · 4mo ago

Why does live music hit different? Our new paper has a neural answer: EEG in a concert hall showed stronger brain-rhythm phase locking during live vs. recorded Bach violin — and that predicts higher pleasure & engagement. 1/2

Mark Thornton @markthornton.bsky.social · 2d ago

Very excited to share this preprint from me, @emmatempleton.bsky.social, @lindseytepfer.bsky.social & @thaliawheatley.bsky.social! "Friends and strangers engage in distinct regimes of body motion synchrony during conversation" osf.io/preprints/ps...

Forms of body motion synchrony. A) Motion quantity synchrony – synchrony in the amount of motion (orange) people engage in over time. This form of synchrony is agnostic to the direction of this movement, may be positive or negative, occurs at varying time lags, and is not specific to matched body parts across members of the dyad. B) Pseudo-synchrony – motion quantity synchrony between people who are not actually interacting. That is, members of different conversations engaging in similar amounts of motion at similar points in the conversation relative to its initiation. And C) directional synchrony – people moving the same body parts in the same direction (or along the same axis in the opposite direction) at the same time (or at some specific time lag).

Mechanisms of synchrony. A) Turn-taking, which causes increases in motion around the time of speaker role exchanges, as participants gesture to hand over or take over the floor. B) Conservation of motion in which one participant moves less when the other moves more, holding the total motion quantity relatively constant over time (note that the total amount of motion across the dyad is similar in the two panels, because one person reduces their motion to balance out the increase in the other’s motion). C) Entrainment, in which mutual following of the same conversational script leads to synchronized movement among people who are not directly interacting (i.e. pseudo-synchrony). Greeting gestures such as the handshakes depicted are one acute manifestation of this entrainment. D) Station-keeping, which maintains proxemic distance and eye level between members of the dyad. This mechanism accounts for directional synchrony, particularly between strangers who feel uncomfortable within each other’s personal space.

Motion quantity synchrony among friends and strangers. A) Friends displayed significant positive synchrony in total motion quantity at short time lags (< 2.5 s) and B) this effect generalized across the majority of body part pairs (each line represents one pair). For example, one series of points might represent the synchrony between the amount of motion in one participant’s left hand and the other’s right foot. C) Strangers displayed significant positive synchrony in total motion quantity at short time lags (< 1 s) and significant negative total motion quantity synchrony at longer time lags (2.5 – 16.6 s). D) Again, this effect generalized to most body part pairs.

Directional synchrony among friends and strangers. A) Among friends, we observed statistically significant directional synchrony in only two body parts (nose and eye) and only in the vertical axis. B) Among strangers, we observed statistically significant directional synchrony in a large number of body parts in the horizontal, vertical, and depth axes.

Alice Schwarze @aliceschwarze.bsky.social · 3w ago

Today marks a first in that I have found a mildly entertaining post on LinkedIn

Photo of a page in an Agatha Christie novel with em-dashes circled. The comment on the photo: "Not you too, Agatha Christie! Not you too"

MꙬse Allain @mooseallain.bsky.social · 3w ago

Going to see the Disney remake “Aphantasia”, which is the same as the 1940 “Fantasia”, but without any pictures.

It's The Weekend 😌@craigweekend.bsky.social · 4w ago

Ladies and gentlemen... the weekend. (also: you are important and are not alone 🧡)

Mark Thornton @markthornton.bsky.social · last mo.

Now in press at Cortex! "False discovery rate correction promotes confounded neuroimaging designs" Paper 🔓: www.sciencedirect.com/science/arti...

Effect of confound mass on true positive rates under test-wise FDR correction in completely arbitrary data. Confound mass represents how large a confound is in terms of the product of the number of tests it is present in, and its mean effect size across these tests. Results are shown at differing combinations of true effect size, number of tests with true (i.e., non-confound) effects, and sample size.

Inflated surface maps of meta-analytic z-statistics from Neurosynth for low-level confounds (top) and high-level cognitive tasks (bottom). Red reflects positive activations, blue reflects negative (de)activations, and darker colors indicate larger z-statistics. Maps are thresholded at |z| = 1 for visualization purposes.

The difference in integrated true positive rate between parcel-wise FDR and parcel-wise FWER (y-axis) is plotted as a function of confound effect size. Each point represents 1 out of 5000 studies simulated for each combination of task and confound. Smoothed loess lines are used to better show the overall trends.

Effect of FDR-based publication bias on observed confound effects sizes. Simulated meta-analytic confound effect sizes are visualized through violin plots for each combination of task effect and confound effect examined in the neural data simulations. Meta-analyses featuring publication bias (orange) substantially inflate these effect size estimates in all cases, relative to meta-analyses featuring no publication bias (blue). Moreover, this bias was present – and in most cases larger – in the subset of studies that were included in the meta-analysis specifically when the publication bias was based on FDR instead of FWER integrated true positive rates (green).

Mark Thornton@markthornton.bsky.social · 11mo ago

After 5 years, I finally carved out time to turn this blog post on FDR (markallenthornton.com/blog/fdr-pro...) into a manuscript. The preprint features a much broader range of simulations showing how FDR promotes confounds, and how this effect compounds with publication bias: osf.io/preprints/ps...

Effect of confound mass on true positive rates under FDR correction. Confound mass represents how large a confound is in terms of the product of its voxel extent and effect size. Results are shown at differing combinations of true effect size, true effect voxel extent, and sample size.

Ethan Mollick @emollick.bsky.social · 4w ago

Unsurprising but still big: MTurk is on its way out, killed by AI. Mechanical Turk was a mainstay of social & survey research through the 2010s, as it allowed you to quickly buy access to many representative humans. It was pretty good at it, until LLMs came along and everyone started using AI

Chaz Firestone @chazfirestone.bsky.social · last mo.

You press ‘send’ on a high-stakes email but hesitate when lifting your finger. You make a chess move but linger on the piece before letting go. Familiar? In @pnas.org, Hanbei Zhou @ruizhegoh.bsky.social @ianbphillips.bsky.social & I show that response *duration* tracks confidence! shorturl.at/A9NVe

Two images, one of a finger pressed a key, another of a hand on a chess piece

Screenshot of first page of paper, "Response duration tracks confidence"

John Henderson @jmhenderson.bsky.social · last mo.

New research article from my lab out in elife. This is the result of a fun new collaboration with Xiaomo Chen's lab. elifesciences.org/reviewed-pre...

Meaning-based guidance of attention in rhesus monkeys during naturalistic scene viewing

elifesciences.org

Nico @nicolasrestrepo.bsky.social · last mo.

This is such an important paper. A lot of key disagreements are not about desired outcomes, but rather about the strategies for securing those outcomes. And the rifts often come down to how much we are willing to risk in trying to secure those ends. Ketika and co explore this brilliantly!

Ketika Garg@ketikagarg.bsky.social · last mo.

🚨This preprint is now out in PNAS: www.pnas.org/doi/full/10.... We combine a dyadic foraging paradigm w/ computational modeling + ABM to study how people navigate differing preferences, share responsibility for shared outcomes & what that means for the group! more in 🧵⬇️ @fearbrain.bsky.social

Ketika Garg @ketikagarg.bsky.social · last mo.

Ketika Garg@ketikagarg.bsky.social · 8mo ago

🚨 Excited to end the year with a new preprint w/ Wenning Deng (not on bsky) and Dean Mobbs @fearbrain.bsky.social 🎉 🎉 "Blame and Compromise During Risky Dyadic Foraging" osf.io/preprints/ps... Feedback is very welcome! Thread: 🧵 1/n

Ketika Garg @ketikagarg.bsky.social · 8mo ago

Richard Huskey @richardhuskey.bsky.social · last mo.

What have you read? What will you read next? Why? In a new paper in @pnasnexus.org, led by the brilliant @gongxuanjun.bsky.social, we show that people forage for books using the same mechanisms they forage for food. What will you read next? Start with this 🧵

Xuanjun (Jason) Gong@gongxuanjun.bsky.social · last mo.

📚 New paper out in PNAS Nexus! How do we choose what to read next? Turns out picking your next book works a lot like how humans forage for food. And it is driven by your curiosity. We analyzed ~2 million real reading choices to find out doi.org/10.1093/pnasnexus/pgag226

Erica Busch @elbusch.bsky.social · 2mo ago

Our new paper is out this week in Nature Neuroscience! www.nature.com/articles/s41... We built a BCI that works with the brain's natural geometry — and we found that people could learn to play a video game with their brains in <1 hr of training. This efficiency is groundbreaking & here's why:

Human learning of noninvasive brain–computer interfaces via manifold geometry - Nature Neuroscience

Busch et al. use nonlinear neural manifolds to help humans gain rapid control over a noninvasive brain–computer interface, allowing them to learn how to play a video game with real-time fMRI neurofeed...

nature.com

Media Neuroscience Lab @medianeuro.bsky.social · last mo.

How does the brain orchestrate flow states? Two new publications in the journal NeuroImage, one in our upcoming special issue on the Neural Correlates of Risks and Benefits of Media Use (#1), and one in the regular issue (#2) dive into flow experiences using a complexity science lens ...

Richard Huskey @richardhuskey.bsky.social · last mo.

🚨1/7 New paper(s) alert! What is our brain doing when we feel flow? I've been trying to understand this question for more than 15 years now. I wish I had the answer, but in many ways, much of my research has clarified what the brain *isn't* doing during flow.

Nico Dosenbach @ndosenbach.bsky.social · 2mo ago

We've known that socioeconomics (SES) matters for the 🧠. New & 🤯 is that SES drowns out all other brain associations, incl. IQ. If you train an algorithm to predict IQ from brain data, it's still way better at predicting SES. Science Mag: www.science.org/doi/10.1126/... @smarek0502.bsky.social 👀🧵👇

Scott Marek@smarek0502.bsky.social · 2mo ago

What matters most for childhood brain organization? We analyzed 649 variables. The answer: Socioeconomics (SES); with brain patterns pointing at sleep & stress as drivers. Even brain-IQ associations were better explained by SES. In Science today: www.science.org/doi/10.1126/...

William J. Brady @williambrady.bsky.social · 2mo ago

✨New paper out @nature.com ✨ For 8 weeks around the 2024 US election, we randomly assigned 2,000 people to use social media algos we built ourselves. Do engagement-based algorithms amplify intergroup, moral & emotional (IME) content—and does that distort how we see political norms? 🧵🔗 👇

Science News @scinews.bsky.social · 2mo ago

At one point, a student joked that if I kept “editing” so much, I might as well submit the article under my own name and save us both time.

warrior cop @wyattprivilege.bsky.social · 3mo ago

I GET LOGGED OUT. BUT I LOG IN AGAIN

Rodrigo Braga @rodbraga.bsky.social · 3mo ago

Excellent explainer of the recent BOLD x metabolism controversy... worth a read! “Does the evidence presented by Epp et al. warrant a wholesale dismissal of BOLD-fMRI? The answer is: certainly not.”

practiCal fMRI@practicalfmri.bsky.social · 3mo ago

Richard Huskey @richardhuskey.bsky.social · 3mo ago

Too provocative a title, but the take home message is spot on: “Our brains are equipped with a suite of decision making algorithms. Different contexts call for different algorithms. Tech companies are adept at hijacking those algorithms for their benefit, not ours” www.nytimes.com/2026/05/12/o...

Opinion | Your Decision Making Is All Wrong

nytimes.com

Berna Devezer @devezer.bsky.social · 3mo ago

now that canvas is up again (but who knows for how long) we keep receiving emails from the uni telling us to back everything up on our computers are you f*#king kidding me various organizations/institutions fail so they can hold us responsible for making up for their errors i just can't

Berna Devezer@devezer.bsky.social · 3mo ago

Don'T kEEp sTudENt InfO oN YoUr cOMputER BeCAusE SEcuRItY

Katie Corker @katiecorker.bsky.social · 3mo ago

Fascinating deep dive into the characteristics of papers and peer reviews at a journal, with a lookback pre-COVID and pre-chatGPT. Papers and reviews showing more signs of AI over time, but also lower writing quality. orgsci.substack.com/p/more-versu... orgsci.substack.com/p/more-versu...

More Versus Better, Part I

AI Is Overwhelming Academic Peer Review. What Next?

orgsci.substack.com

Richard Huskey @richardhuskey.bsky.social · 3mo ago

Fascinating. Important. The stunning thing I’ve seen as an editor, reviewer, & educator, is the use of generative AI to accelerate low quality work. Rather than use these tools to do more ambitious scholarship, there is a race to the bottom. This post, the first in its series, documents exactly that

Katie Corker@katiecorker.bsky.social · 3mo ago

Julia M. Rohrer @dingdingpeng.the100.ci · 4mo ago

Good news everyone 🥳 Our (w @vincentab.bsky.social) primer on models as prediction machines (with the marginaleffects package) is finally officially published!> journals.sagepub.com/doi/10.1177/...

Models as Prediction Machines: How to Convert Confusing Coefficients Into Clear Quantities - Julia M. Rohrer, Vincent Arel-Bundock, 2026

Psychological researchers usually make sense of regression models by interpreting coefficient estimates directly. This works well enough for simple linear model...

journals.sagepub.com

Russ Poldrack @russpoldrack.org · 3mo ago

People in the AI world seem to adore the System 1/2 dichotomy. I love this quote from Gerd Gigerenzer about the concept:

“What is system one and system two? It’s a list of dichotomies. Heuristic versus calculated rationality, unconscious versus conscious, error-prone versus always right, and so on. Usually, science starts with these vague dichotomies and works out a precise model. This is the only case I know where one progresses in the other direction. We have had, and still have, precise models of heuristics, like one over N. And at the same time, we have precise models for so-called rational decision making, which are quite different: Bayesian, Neyman-Pearson, and so on. What the system one, system two story does, it lumps all of these things into two black boxes, and it’s happy just saying it’s system one, it’s system two. It can predict nothing. It can explain after the fact almost everything. I do not consider this progress." - Gerd Gigerenzer

Julius Klingelhoefer @klingelhoefer.bsky.social · 3mo ago

Interested in intensive longitudinal studies (ESM, EMA, ...)? We will host a GESIS seminar in September that will teach you how to conduct and analyze these studies. Check it out here ⬇️

GESIS Training@gesistraining.bsky.social · 3mo ago

Learn from @lukotto.bsky.social and @klingelhoefer.bsky.social how to study people's behaviors and experiences in real time with smartphone-based data collection and multilevel modelling at the #GESISfallseminar. More information & registration ➡️ t1p.de/MobileDataCo... @gesis.org

GESIS Fall Seminar in Computational Social Science
Mobile Data Collection and Analysis: Intensive Longitudinal Methods
21 to 25 September 2026 in Mannheim
Lukas Otto (GESIS) & Julius Klingelhoefer (Friedrich-Alexander-Universität Erlangen-Nürnberg)

Harrison Ritz @hritz.bsky.social · 3mo ago

🚨 Tom Griffiths has a podcast where he interviews cognitive scientists podcasts.apple.com/ca/podcast/t... This just went to the top of my list.

The Cognition Project

Science Podcast · How can we study the mind, something we can never see or touch? This podcast tells the story of how psychologists, neuroscientists, computer scientists, linguists, and philosophers w...

podcasts.apple.com

Shahab Bakhtiari@shahabbakht.bsky.social · 3mo ago

I’ve been really enjoying Tom Griffith’s "The Cognition Project" lately. A couple of observations: - Hearing the history of the cognitive revolution directly from the giants who lived it is priceless. - Recent AI advances have sort of robbed us of the joy of being amazed by human cognition. 🧠🤖

Yuan Chang Leong @ycleong.bsky.social · 4mo ago

Deeply honored that our paper was recognized with the #SANS2026 Award! SANS was an important part of this paper's journey! @jadynpark.bsky.social first presented this work at SANS2023, and again in SANS2025, and we benefited greatly from the feedback and discussion!

SANS@sansmeeting.bsky.social · 4mo ago

Congratulations to @jadynpark.bsky.social and colleagues for winning the #SANS2026 Innovation Award for their paper: www.nature.com/articles/s41...