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Blair Shevlin

@bshev.bsky.social
511 followers 501 following 53 posts

Faculty @ Icahn School of Medicine. Computational Psychiatry. Neuroeconomics. Decision-Making

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Reposted by Blair Shevlin
Igor Brodsky @brodskyigorlab.bsky.social · 19h
6 days to register a comment on NIH Request for Information (RFI) on Changing Reporting Outcomes for Peer Review. They are proposing to hide the impact scores and percentiles. 🤔 funding decisions will not be transparent👎🏼. Register a comment while you still can rfi.grants.nih.gov?s=6a2b1c22c3...
rfi.grants.nih.gov
Request For Information
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Reposted by Blair Shevlin
bioRxiv Neuroscience @biorxiv-neursci.bsky.social · 4h
Neural latent representation of implicit perceptual decision confidence signatures from brain-wide intracranial EEG www.biorxiv.org/content/10.64898/20…
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David Colaço @davidcolaco.bsky.social · 02/10/2026
The complete version of @phaueis.eurosky.social and my BBS target article, "Metabolic considerations for cognitive modeling," is now available. It includes 32 commentaries and our response. Please share #philsci #philsky #cogsci
cambridge.org
Metabolic considerations for cognitive modeling | Behavioral and Brain Sciences | Cambridge Core
Metabolic considerations for cognitive modeling - Volume 49
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Omid V. Ebrahimi @omidvebrahimi.bsky.social · 07/10/2026
⚡ Out now: Psychological and health sciences increasingly study how phenomena dynamically influence and reinforce one another over time: for example, to understand the mechanisms maintaining mental disorders. Can we identify reliable clusters of these dynamics? A thread 🧵 osf.io/preprints/ps...
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PLOS Biology @plosbiology.org · 07/10/2026
Moral and perceptual decisions may share computational mechanisms, but do they rely on the same neural systems? This study shows that both follow similar evidence-accumulation computations, yet engage distinct neural representations. 🧪 #NeuroSky #morality #cognition plos.io/4AM2V57
Moral and perceptual task-relevant conflict are represented by distinct brain areas. The two right temporoparietal junction clusters (rpTPJ and raTPJ) identified in different analyses had no overlap.
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Climate, Ecology, War & More: Dr. Glen Barry BigEarthData.ai @bigearthdata.ai · 05/10/2026
Metabolic and neural responses to ultraprocessed foods: a randomized, controlled, crossover study ->Nature | More on "Ultraprocessed foods and brain response" at BigEarthData.ai | #Food
nature.com
Metabolic and neural responses to ultraprocessed foods: a randomized, controlled, crossover study
The full study comprised 57 participants; of these, 32 completed both metabolic sessions in a randomized crossover design and 52 completed the functional magnetic resonance imaging (fMRI) session (Extended Data Fig. 1). Every participant who completed the metabolic sessions also completed the fMRI session. The overall participant sample was 31.6% male, with a mean age of 26.21 ± 6.85 years and body mass index (BMI) of 22.75 ± 1.87 kg m−2 (Extended Data Table 1). Participants’ habitual energy intake on average comprised 54.4 ± 18.4% UPFs, similar to the national average of 55.0% (ref. 2). Additional participant characteristics are described in Extended Data Table 1. Exclusions and final analytic samples for each modality are summarized in the CONSORT diagram (Extended Data Fig. 1). Acute metabolic effects of UPFs and non-UPFs To investigate the effect of processing level on post-ingestive metabolic response to foods with matched nutrient content, 32 participants consumed, and were required to finish within 10 min, ~300 kcal nutritionally matched meals composed entirely of either UPF or non-UPF while undergoing 4 h (50 min baseline followed by a 3 h postprandial period) of whole-room indirect calorimetry (WRIC) and concomitant blood collection by intravenous catheter (Fig. 1a). The non-UPF...
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Krishn Bera @krishnbera.bsky.social · 05/10/2026
How fast we decide reveals how we learn. New in @plos.org #PLoSCompBio : modeling response times alongside choices disentangles working memory, reinforcement learning and cognitive control, and reveals differences in schizophrenia that choices alone missed. 🧵 t.co/BTOgmpd4YH
t.co
https://doi.org/10.1371/journal.pcbi.1014796
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Andrey Chetverikov @achetverikov.bsky.social · 02/10/2026
Some months ago, I wrote a skeptical reply to a commentary on bots in online studies in PNAS, arguing that no evidence yet exists for such bots. Together with the authors of the original commentary, we now show that bots can pass (almost?) all online cognitive studies with human-like performance 1/n
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Blair Shevlin @bshev.bsky.social · 02/10/2026
Thank you to my co-authors who ran the original study and curated the data: Loren Gianini, Joanna Steinglass, Karin Foerde, Caitlin Lloyd, and Kelsey Hagan. Huge thanks to @lauraaberner.bsky.social, who conceived these analyses and supported me throughout. Paper: elifesciences.org/articles/105...
elifesciences.org
Client Challenge
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Blair Shevlin @bshev.bsky.social · 02/10/2026
Our main takeaway: when mood drops, taste may take over the decision process in women with BN, which could help explain the shift from restriction to binge eating. We hope this points toward new targets for intervention.
Two simulated evidence-accumulation plots comparing low and high negative affect. With low negative affect, health information enters early enough to push a high-fat food toward rejection. With high negative affect, health information is delayed, so evidence for the high-fat food keeps building on taste alone and it is accepted before health information has much effect.
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Blair Shevlin @bshev.bsky.social · 02/10/2026
Importantly, the size of this mood-driven taste bias tracked with how many binge episodes people self-reported over the past three months.
Scatterplot relating attribute onset estimates to self-reported binge episodes over the past three months, separately for neutral and negative mood. Under negative mood, participants whose taste information entered earlier for high-fat foods tended to report more binge episodes, shown by a steep downward dashed red trend. Under neutral mood the relationships are weaker and run in different directions.
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Blair Shevlin @bshev.bsky.social · 02/10/2026
Participants with BN let taste information into the decision earlier than health information, more so than controls. And under negative mood, this taste bias got stronger!
Plot of when taste versus health information enters the decision (attribute onset) for controls (green) and BN (purple), by mood and food type. Values below zero mean taste enters first. Under neutral mood, taste generally enters before health, with the two groups differing by food type. Under negative mood, taste enters even earlier in both groups, and the shift is largest in the BN group.
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Blair Shevlin @bshev.bsky.social · 02/10/2026
We fit a cognitive model (a sequential sampling / diffusion decision model) that tracks when different attributes, like taste and health, enter a decision as it's being made.
Four-panel schematic of a sequential sampling model, in which evidence for accepting or rejecting a food accumulates over time until it hits a threshold. Attributes can enter the decision at different times. Panels A and B contrast health information entering first with taste information entering first, and show that a high-fat food can be accepted on taste alone but rejected once health information arrives. Panels C and D show hypothesized effects of negative affect: giving taste more weight, giving health less weight, or delaying health information. Each pushes evidence toward accepting the food.
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Blair Shevlin @bshev.bsky.social · 02/10/2026
The mood induction worked: everyone felt worse afterward. But choices didn't change. That's where we came in. Focusing on choices alone can hide how a decision unfolds.
Bar chart of how often healthy controls (green) and women with bulimia nervosa (purple) chose foods over a reference item, split by neutral versus negative mood and low-fat versus high-fat foods. Women with BN chose high-fat foods much less often than controls in both moods, and this barely changed after the negative induction. Overall, the negative mood induction produced little visible shift in choices.
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Blair Shevlin @bshev.bsky.social · 02/10/2026
In earlier work, our Columbia colleagues had women with BN and matched controls rate foods for taste and healthiness, then make food choices, after both a neutral and a negative mood induction (on separate days).
Schematic of the study design. Panel A: a timeline of initial mood assessment, an 8-minute mood induction, mood reassessment, and a food choice task. Each participant completed a neutral and a negative induction on separate days, in counterbalanced order, each combining a song with a writing prompt. Panel B: example trials in which participants rate foods for tastiness and healthiness, then choose whether they would eat a food instead of a reference item.
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Blair Shevlin @bshev.bsky.social · 02/10/2026
But outside of binges, the same people typically restrict their eating and avoid high-fat foods. Why the flip? That's what we set out to understand.
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Blair Shevlin @bshev.bsky.social · 02/10/2026
Bulimia nervosa (BN) is closely tied to negative mood. People often report emotional distress right before a binge, and binges typically involve highly palatable, high-fat foods.
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Blair Shevlin @bshev.bsky.social · 02/10/2026
Women with bulimia nervosa typically avoid high-fat foods, yet binge on them during periods of negative mood. Why? In our new paper in @elife.bsky.social, we used computational modeling to find out 🧵 elifesciences.org/articles/105...
elifesciences.org
Client Challenge
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Christoph Strauch @cstrauch.bsky.social · 02/10/2026
How much of a risk are LLM-generated bots for online behavioral experiments? We present results of an entirely natural language prompt-generated agent, capable of absolving any of the 26 experiments we tested it on. Most tasks are passed with data that can pass as human osf.io/preprints/ps... (1/)
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Denise J. Cai, Ph.D. @denisejcai.bsky.social · 30/09/2026
NEW: The anterior hypothalamic nucleus acts like a volume knob for stress, scaling the brain’s response to threatening events 🧠 Read the Cai Lab's latest paper, led by @zachtpennington.bsky.social, in @nature.com 🎉 www.nature.com/articles/s41... More: bsky.app/profile/did:...
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bioRxiv Neuroscience @biorxiv-neursci.bsky.social · 25/09/2026
Apparent food selectivity reflects multiple non-food image properties www.biorxiv.org/content/10.64898/20…
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Kianté @kiante.bsky.social · 25/09/2026
I think it comes down to opportunity cost. In our recent paper (Zhang et al., PNAS, cond. accepted), data from a few months ago suggest some people are already doing this (caveat: some may be non-compliant humans, and things move fast).
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Ata Karagoz @atabk.bsky.social · 24/09/2026
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.
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Blair Shevlin @bshev.bsky.social · 24/09/2026
Like I've been saying - many of the tools we've been using for bot detection are no match for today's LLM agents. We need to work together to build new standards!
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Sam Gershman @gershbrain.bsky.social · 24/09/2026
I'm excited about this work that an amazing undergrad, @ariazhang.bsky.social, did with me and @tomerullman.bsky.social: www.biorxiv.org/content/10.6... Aria showed how a neural net can discover abstractions for intuitive physics and use its own reliability estimates to decide when to deploy them.
biorxiv.org
Reliability-guided meta-control in intuitive physics
Intuitive physical reasoning is an important part of daily life, but the computations underlying it remain debated. Some prominent accounts propose intuitive physics relies on mental simulation, with ...
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Omid V. Ebrahimi @omidvebrahimi.bsky.social · 24/09/2026
Tired of the centrality debate? Of seeing one application where centrality is influential & others where it's more arbitrary? We have the article for you: osf.io/preprints/ps... Turns out centrality can indeed matter; but when it does depends on underlying network structure & mechanism of spread 🧵
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Blair Shevlin @bshev.bsky.social · 22/09/2026
This sort of logic is the motivation behind tools like felipemaffonso.github.io/cognitive-tr... There's also a lot of work in developing 'reverse-shibboleths' that catch bots doing things well where a human might struggle. Unfortunately if you tell them to act human, the agents can still pass
felipemaffonso.github.io
Cognitive Trap Repository
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Blair Shevlin @bshev.bsky.social · 22/09/2026
Eye-tracking is definitely part of the solution! Just need an IRB to get on-board re: potential privacy concerns. Even then, not all data collection platforms can adopt eye-tracking (eg, REDCap).
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Blair Shevlin @bshev.bsky.social · 22/09/2026
You don't even need a model as advanced as Claude. Try it for free with something like manus.im and you'll quickly see how spoofing online studies is basically free
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Blair Shevlin @bshev.bsky.social · 22/09/2026
I think a lot of people have been having the same experience lately - realizing that LLM-based agents can easily complete online tasks and assessments. Glad you are helping raise awareness!
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Blair Shevlin @bshev.bsky.social · 22/09/2026
Sure these platforms will ban those users, but first researchers need evidence that someone is using AI to complete your tasks. It's not so straightforward to make that case right now!
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Blair Shevlin @bshev.bsky.social · 22/09/2026
Been raising that alarm internally at Sinai and Yale, but if our field wants to continue to rely on virtual data collection then we need to develop better bot detection tools. Glad to be collaborating with @kiante.bsky.social on these efforts. His work at UCLA is leading the way survey-shield.com
survey-shield.com
Survey Shield
Survey Shield - AI-powered survey bot-detection analysis
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Blair Shevlin @bshev.bsky.social · 22/09/2026
Unfortunately, LLM agents can already pass these checks. Video instructions can be decoded just as easily as text. You can try it yourself by asking one to identify objects in a youtube video
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Blair Shevlin @bshev.bsky.social · 22/09/2026
Relatedly - we also found that if you give LLM agents a specific diagnosis, they can answer questionnaires commonly-used mental health screeners consistent with the disorder osf.io/preprints/ps...
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Blair Shevlin @bshev.bsky.social · 22/09/2026
Highly recommend checking out some of @kiante.bsky.social recent work. He's developing some great tools for bot detection, including survey-shield.com and kiante-fernandez.github.io/webgazer-qua...
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gillesdehollander.bsky.social @gillesdehollander.bsky.social · 21/09/2026
New paper in Nature Communications 🧠 Rapid Changes in Risk Attitudes Originate from Bayesian Inference on Parietal Magnitude Representations. Why the same person can flip between a safe bet and a gamble, and what parietal cortex has to do with it. 🧵 www.nature.com/articles/s41...
nature.com
Rapid changes in risk attitudes originate from Bayesian inference on parietal magnitude representations - Nature Communications
Risk attitudes can shift across contexts and even between identical choices. Here, the authors show that as parietal payoff representations grow noisier, the brain leans more on prior beliefs, biasing...
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Ken Paller @paller.bsky.social · 20/09/2026
Announcing two tenure-track faculty openings in the Psych Dept at Northwestern University: Cognitive/Affective Neuroscience and Clinical Psychology psychology.northwestern.edu/people/facul...
psychology.northwestern.edu
Job Opportunities: Department of Psychology - Northwestern University
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Blair Shevlin @bshev.bsky.social · 18/09/2026
Sharing this event - looks very interesting! Interpretability in Psychological Models Online, 15 October 2026, 15:30–19:20 CEST tmmpsych.vercel.app/events/inter...
tmmpsych.vercel.app
Interpretability in Psychological Models | TMM - Theory, Model, Measurement
Four talks and four panel discussions on what it means for a psychological model to be interpretable, and whether the idea still holds in an era of machine-learned cognition.
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Jordan Deakin @jordantdeakin.bsky.social · 17/09/2026
📣 NEW PREPRINT ALERT! 📣 📝Preprint: www.biorxiv.org/content/10.6... When choosing between options with multiple attributes, what does the brain actually compare - individual attributes or integrated option values? We combined EEG + eye-tracking to find out... and found evidence for the latter 🧠
biorxiv.org
Fixation-evoked potentials reveal neural signatures of hierarchical value-integration during decision-making
Many decisions require maintaining beliefs across multiple levels of representation, from sampling and integrating information to forming action plans. To elucidate these processes and reveal the neur...
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Blair Shevlin @bshev.bsky.social · 17/09/2026
Incredibly excited to host this event next week! Dr. Rust's work is both rigorous and inspiring
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The Friedman Brain Institute @sinaibrain.bsky.social · 17/09/2026
ONE WEEK AWAY! On Thursday, September 24, 1pm, the #FBISeminarSeries and host Dr. @bshev.bsky.social welcome @upenn.edu's Dr. @nicolecrust.bsky.social. Dr. Rust will present "From Subjective Feelings to Brain Mechanisms: Advancing the Science of Mood through Epistemic Iteration". ✨NOT TO MISS!
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Uma Mohan @umamohan.bsky.social · 17/09/2026
We are hiring a data engineer! If you are interested in working with human intracranial data, processing pipelines, and an awesome team, please apply! neurojobs.sfn.org/job/39840/sc...
neurojobs.sfn.org
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Xiaosi Gu @xiaosigu.bsky.social · 16/09/2026
📣We are hiring!! I am accepting applications for a postgraduate research associate (PGA) position. If you are interested in pursue research experience in computational psychiatry, plz apply here - yalesurvey.ca1.qualtrics.com/jfe/form/SV_... #Computation #MentalHealth #Neuroscience #Yale #Jobs
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Aaron Blackshear @aaronblackshear.bsky.social · 16/09/2026
DMs are open if you have questions or candidates www.teamworkonline.com/basketball-j...
teamworkonline.com
Data Scientist, Basketball Operations - Los Angeles Sparks
POSITION SUMMARY:The 3-time WNBA Champions Los Angeles Sparks are seeking a Data Scientist to help elevate the team’s competitive decision-making through statistical modeling, automated reporting, and...
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Tom Kash @superkash.bsky.social · 15/09/2026
new paper out, led by @jobeneuro.bsky.social , exploring 5HT dynamics in cingulate and central amygdala, and how a history of alcohol consumption changes them! www.nature.com/articles/s41...
nature.com
Selective dysregulation of serotonin dynamics in the anterior cingulate cortex and central amygdala following binge alcohol consumption - Neuropsychopharmacology
Neuropsychopharmacology - Selective dysregulation of serotonin dynamics in the anterior cingulate cortex and central amygdala following binge alcohol consumption
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Wouter Kool @wouterkool.bsky.social · 15/09/2026
I expect to recruit a PhD student this cycle! The Control and Decision Making Lab at WashU studies control, effort, and decision making, combining behavioral experiments with modeling and neuroimaging. If that sounds cool, check out our work: cdmlab.wustl.edu. How to apply: psych.washu.edu/apply
cdmlab.wustl.edu
Control and Decision Making Lab
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Salman Qasim @qasimetal.bsky.social · 13/09/2026
Another preprint! This one from my postdoc with @ignaciosaezphd.bsky.social and @xiaosigu.bsky.social. Here we asked how the reward outcomes driving trial-by-error learning leave a lasting imprint on memory strength in the human brain. We used iEEG/computational models of cognition to find:
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The Friedman Brain Institute @sinaibrain.bsky.social · 11/09/2026
OUT NOW! Study of #WorldTradeCenter responders shows that how the brain anticipates positive experiences may contribute to #Resilience after #Trauma, pointing to potential new targets for #PostTraumaticStressDisorder (PTSD) treatment. 👉 www.mountsinai.org/about/newsro...
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Salman Qasim @qasimetal.bsky.social · 10/09/2026
First preprint from the lab from postdoc Carlo Cerquetella! Demonstrating that neuronal spiking in the human medial temporal lobe and prefrontal cortex cohere into a redundant, low-dimensional neural correlate of visual attention (captured mostly by saccades) during naturalistic movie viewing.
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Henrik Singmann @singmann.bsky.social · 09/09/2026
A new version of rtdists is now on CRAN: cran.r-project.org/package=rtdi... Big thanks to @kiante.bsky.social who added a new distribution, the racing diffusion model, fixed a number of long-standing bugs, and increased the speed of the diffusion model. All news: cran.r-project.org/web/packages...
cran.r-project.org
rtdists: Response Time Distributions
Provides response time distributions (density/PDF, distribution function/CDF, quantile function, and random generation): (a) Ratcliff diffusion model (Ratcliff &amp; McKoon, 2008, &lt;<a href="https:/...
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