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Maria M. Robinson

@mmrobinson93.bsky.social
359 followers 327 following 14 posts

Interested in mathematical psychology and best practices in theory assessment and measurement in social sciences. Research website: mrobinson93.github.io

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Reposted by Maria M. Robinson
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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Tal Golan @talgolanneuro.bsky.social · 28/08/2026
How can we design experiments that make computational models disagree? One section of our new @natrevneuro.nature.com Review with @kriegeskorte.bsky.social and @heikoschuett.bsky.social examines studies that used stimulus sets designed to elicit distinct predictions from competing models. 1/16
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Maria M. Robinson @mmrobinson93.bsky.social · 15/08/2026
This is 👌
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Tianyuan Teng @tyteng.bsky.social · 13/08/2026
You'd think people prefer the simplest explanation of an uncertain world — Occam's razor. Our data says no, across 2 modalities, 2 tasks, 8 experiments: people often perceive illusory structure that isn't there and prefer moderate complexity. Out now in Nature Comms! www.nature.com/articles/s41...
nature.com
Human learning of probability distributions is biased toward moderate structural complexity - Nature Communications
Humans build internal models from online observations to adapt to new environments. Here, the authors show that individuals are biased towards building models with moderate structural complexity, rega...
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Nicole Rust @nicolecrust.bsky.social · 23/07/2026
Fascinating and important. Including the provocative finding “What we believe about our bodily sensing may have little to do with how we actually sense it.” A place where subject report diverges (read the thread). Congrats to this team!!
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Aline Bompas @alinebompas.bsky.social · 18/07/2026
Congratulations to Julia Haaf @juliaha.bsky.social for winning the Estes early career fellow award this year! Julia will formally receive her award at her guest lecture at mathpsych 2027 @mathpsych.org
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Aline Bompas @alinebompas.bsky.social · 18/07/2026
And congratulations to Betsy Fox @elfox89.bsky.social, new president elect of the mathematical psychology society @mathpsych.org !
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Aline Bompas @alinebompas.bsky.social · 18/07/2026
Congratulations to Hans Colonius on winning the senior fellow award @mathpsych.org . Hans will formally receive his award at his guest fireside chat at mathpsych 2027 in Leeds
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Maria M. Robinson @mmrobinson93.bsky.social · 19/07/2026
Beyond honored, thank you!
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Nicole Rust @nicolecrust.bsky.social · 16/07/2026
Now up at @oecs-bot.bsky.social ! Looking to wrap your head around concepts & terms (and debates) in emotion & mood research (“affective science”)? Here’s a go to. oecs.mit.edu/pub/bhn7j5s7...
Emotions, Moods, and Affective States
by Nicole C. Rust
Published on
Jul 16, 2026
Emotions, Moods, and Affective States

Contents
·

The phenomena that comprise emotions, moods, and affective states are united by their valence—their pleasantness or unpleasantness—such as the pleasure of seeing a baby laugh or the aversion to smelling feces. Beyond this broadly accepted defining characteristic, the researchers who study them have a multitude of ideas about how to best define their constructs, what shapes them, and the most promising path toward understanding them scientifically. For instance, many researchers agree that emotions should be distinguished from moods, but not all agree on the criteria that differentiate them. Similarly, some restrict the terms emotion and mood to instances in which subjective
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Felipe De Brigard @felipedebrigard.bsky.social · 01/07/2026
My new article on remembering as inverse causal inference has been published, and the first 50 downloads are free here: www.tandfonline.com/eprint/YEHFQ...
tandfonline.com
Remembering as inverse causal inference
The causalism/simulationism debate has become central in contemporary philosophy of memory. Recently, however, I have suggested that the debate is largely ill-construed and have offered instead a p...
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Igor Utochkin @utochkin.bsky.social · 01/07/2026
In a new preprint, @keisukefukuda.bsky.social and I investigated stimulus-specific memorability with ROC analysis. We find that the variability of latent memory effects (familiarity) caused by individual memory items across people is a game-changing dimension of memorability osf.io/c62an/files/...
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Naomi Saphra @nsaphra.bsky.social · 15/06/2026
We don’t always know what problems are hard for LLMs. So devs evaluate on tasks HUMANS find hard or on broad benchmarks. What if we could instead anticipate which scenarios a model will fail on—all without evaluating specific input examples? 🧵NEW PAPER by @jenniferlumeng.bsky.social
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Dynamic Cognition Lab @dynacog-lab.bsky.social · 11/06/2026
Attention operates in a changing world, so attentional priority maps must likewise be dynamic. Our (Sage Boettcher, @visualattentionlab.bsky.social, @gwenlliams.bsky.social, Nir Shalev) TiCS paper argues this and propose key questions for future work hoping to account for dynamic priority maps.
sciencedirect.com
Making time for a dynamic attentional priority map
Attentional priority is typically conceived as a static spatial map, despite attention operating in a continuously changing world. We propose a dynami…
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Princeton University Press @princetonupress.bsky.social · 11/06/2026
Congratulations to @nicolecrust.bsky.social, whose book Elusive Cures is a Silver Winner of the Nautilus Book Awards, Science and Cosmology category! This work is bold proposal for tackling one of the greatest challenges of our time—brain and mental illnesses. Learn more here: hubs.ly/Q04k-MXW0
Elusive Cures: Why Neuroscience Hasn't Solved Brain Disorders—And How We Can Change That by Nicole C. RustNicole C. Rust
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Russ Poldrack @russpoldrack.org · 09/06/2026
Simulation-based inference russpoldrack.substack.com/p/simulation... - the latest in my Better Code, Better Science series
russpoldrack.substack.com
Simulation-based inference
Better Code, Better Science: Chapter 9, Part 5
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hakwan lau @hakwan.bsky.social · 07/06/2026
LLM introspection revisited. if we do the controls properly we may not have strong enough evidence just yet arxiv.org/html/2605.26...
arxiv.org
Can LLMs Introspect? A Reality Check
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Kevin J Miller @kevinjmiller.bsky.social · 03/06/2026
Computational models are a key part of science but discovering new ones is hard! DataDIVER discovers concise models from data, which surface new mechanistic ideas and clear predictions for future experiments From Google Deepmind Neuroscience Lab + collaborators www.biorxiv.org/content/10.6...
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Sam Verschooren @samversc.bsky.social · 04/06/2026
🎉New paper out today in Nature Reviews Psychology🎉 with @mjdahl.bsky.social, @mariamaly.bsky.social, and @thiasmittner.bsky.social. We've been working on a unified framework for attentional states and the dynamics of transitions between them. 🧵
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Adam Sanborn @asanborn.bsky.social · 03/06/2026
Generated examples from described risky choices have "flatter" probabilities
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Nathaniel Haines @natehaines.bsky.social · 03/06/2026
giving a talk later this year and this is gonna be so fun
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Michelle Greene @mgreenephd.bsky.social · 02/06/2026
🚨New dataset just dropped🚨 Introducing Places in the Wild: 67,000 RAW-format photographs (45 mpix) densely sampled from 810 places (260 basic-level categories). This is 11x the number of pixels in ImageNet! Preprint is here: arxiv.org/abs/2606.02481 1/
arxiv.org
Places in the Wild: A Large, High-Resolution RAW Photograph Dataset for Ecologically Valid Vision Research
Large image datasets have accelerated progress in cognitive neuroscience and computer vision. However, most datasets are low-resolution, internet-sourced JPEGs with unknown capture conditions and limi...
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Warwick Psychology @warwickpsych.bsky.social · 01/06/2026
We’re kicking off the #ETHOLANG Away Day with an invited talk by Professor Sotaro Kita (@sotarokita.bsky.social), Professor of Psychology of Language and Director of the Language and Learning Group at Warwick. #BehaviouralSpotlight #ETHOLANG
Professor Sotaro Kita presenting the Etholang framework
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Warwick Psychology @warwickpsych.bsky.social · 19/05/2026
Thanks Dr Deborah Talmi @dtalmi.bsky.social @campsydept.bsky.social for such an interesting talk on Bayesian modelling of subjective pain experiences. Nice to see the integration of basic and clinical science. 🧪
Dr Deborah Talmi presenting
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Ven Popov @venpopov.bsky.social · 11/02/2026
In this essay I try to articulate some thoughts about how meaning can arise in symbolic systems without external referents. The core idea: "A mathematical object is what it does inside a system of relations and operations" venpopov.com/posts/2026/s...
venpopov.com
Simple rules, hard problems and the emergence of meaning in mathematics – Ven Popov
Ven Popov is a senior scientist in computational modeling at the Department of Psychology, University of Zurich.
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Science News @scinews.bsky.social · 06/02/2026
Synthesizing scientific literature with retrieval-augmented language models www.nature.com/articles/s41...
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Nicole Rust @nicolecrust.bsky.social · 21/01/2026
I met @russpoldrack.org after this effort and before I knew this particular story. I was blown away when I first read about it. Some scientific efforts “expand the domain of the understandable”. This was one of them. So great to see it profiled by @thetransmitter.bsky.social!
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Anna Schapiro @annaschapiro.bsky.social · 15/01/2026
Really thrilled that this paper led by @neurozz.bsky.social is now published in its final version in @elife.bsky.social!! This is a memory-focused (as opposed to RL-focused) account of the detailed characteristics of forward and backward awake and sleep replay! elifesciences.org/articles/99931
elifesciences.org
A unifying account of replay as context-driven memory reactivation
A context-driven memory model simulates a wide range of characteristics of waking and sleeping hippocampal replay, providing a new account of how and why replay occurs.
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Andrew Lampinen @lampinen.bsky.social · 13/01/2026
When are impossibility proofs misleading? In infinitefaculty.substack.com/p/be-wary-of..., I discuss a common issue I see: proofs that are logically valid, but where the underlying assumptions are unjustified. I discuss ‘proofs’ that cognition cannot be tractably learned, and that LMs are 1/
infinitefaculty.substack.com
Be wary of assumptions in impossibility arguments
A proof is only as good as its assumptions
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Stella Wernicke @stellawernicke.bsky.social · 12/01/2026
I am happy to share that our preprint “𝗪𝗼𝗿𝗸𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗖𝗶𝗿𝗰𝘂𝗹𝗮𝗿 𝗗𝗮𝘁𝗮: 𝗔 𝗧𝘂𝘁𝗼𝗿𝗶𝗮𝗹 𝗳𝗼𝗿 𝗖𝗼𝗴𝗻𝗶𝘁𝗶𝘃𝗲 𝗮𝗻𝗱 𝗕𝗲𝗵𝗮𝘃𝗶𝗼𝗿𝗮𝗹 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵” is now out. Huge thanks to @bayslab.org, Julie de Falco, Zahara, @cjungerius.bsky.social, @ivntmc.bsky.social, Adam, and Xiaolu for the lovely collaboration. doi.org/10.31234/osf...
doi.org
OSF
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Jim Thompson @jimthommo.bsky.social · 05/01/2026
On a more positive note, this NN is worth a read. It takes a similar approach to Ashwood, Calhoun etc to explore diff behavioral states using HMM, but here using a hierarchical Dirichlet process to infer number of states www.nature.com/articles/s41...
nature.com
Infinite hidden Markov models can dissect the complexities of learning - Nature Neuroscience
Bruijns et al. present a modeling tool that enables the tracking of learning dynamics across subjects to reveal how behaviors emerge and adapt. Applying the tool to a decision-making task in mice unco...
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Kanaka Rajan @kanakarajanphd.bsky.social · 16/12/2025
New paper for #neurips2025! AI models adjust millions of internal settings to get better at a task. But how are these adjustments determined? For decades, we've mostly figured this out through trial & error. We took a different approach...🧵 (1/6) 🔗 openreview.net/forum?id=oMi...
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Ido Shalev @idoshal.bsky.social · 16/12/2025
New preprint 🎉 Psych constructs are complex. Symptoms overlap, people rarely fit neat categories, and patterns are non-linear. Most methods compromise this richness. Self-Organising Maps don't. We provide a step-by-step tutorial with annotated R code to make them accessible. doi.org/10.31234/osf...
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Maria M. Robinson @mmrobinson93.bsky.social · 19/11/2025
This was a great talk and project.
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Henrik Singmann @singmann.bsky.social · 03/11/2025
Short thread on today's HotFresh SJDM paper: bsky.app/profile/maxm...
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Thomas Luo @thomas-zhihao-luo.bsky.social · 17/09/2025
How does the brain decide? 🧠 Our new @nature.com paper shows that neural activity switches from an 'evidence gathering' to a 'commitment' state at a precise moment we call nTc. After nTc, new evidence is ignored, revealing a neural marker for the instant when the mind is made up. rdcu.be/eGUrv
nature.com
Transitions in dynamical regime and neural mode during perceptual decisions - Nature
Simultaneous recordings were made of hundreds of neurons in the rat frontal cortex and striatum, showing that decision commitment involves a rapid, coordinated transition in dynamical regime and neura...
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Urte Laukaityte @laukas.bsky.social · 18/09/2025
Inferential theories are on the rise in cognitive science. But what does it mean to infer? Check out our take on inference across a variety of (neuro)cognitive systems.
taylorfrancis.com
Inference in (neuro)cognitive systems | 9 | Neurocognitive Foundations
Cognitive scientists ascribe inferential processes to (neuro)cognitive systems to explain many of their capacities. Since these ascriptions have different
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Steve Fleming @smfleming.bsky.social · 21/02/2025
Excited to see this now out in the world! We identify a computational basis for how persistent underconfidence is maintained in the face of intact performance, finding that it is grounded in impaired updating of global self-beliefs from local metacognition www.nature.com/articles/s41... 1/N
nature.com
Distorted learning from local metacognition supports transdiagnostic underconfidence - Nature Communications
Individuals with symptoms of anxiety and depression exhibit persistent underconfidence. Here, the authors show that distortions in learning from local metacognition can explain how underconfidence is ...
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The Viking (Gunnar Blohm) @gunnarblohm.bsky.social · 03/09/2025
Our multi-sensory integration Neuro-AI paper is now published in J Neurosci www.jneurosci.org/content/earl...
jneurosci.org
Beyond divisive normalization: Scalable feed-forward networks for multisensory integration across reference frames
The integration of multiple sensory inputs is essential for human perception and action in uncertain environments. This process includes reference frame transformations as different sensory signals ar...
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Gidon Frischkorn @gidon-frischkorn.bsky.social · 24/07/2025
Super excited to share that Ven Popov & me published a new release of the #bmm R package: venpopov.github.io/bmm/ We have added the Memory Measurement Model for categorical #workingmemory tasks to the package! Apart from that there are some minor fixes to already implemented models and functions.
venpopov.github.io
Easy and Accessible Bayesian Measurement Models Using brms
Fit computational and measurement models using full Bayesian inference. The package provides a simple and accessible interface by translating complex domain-specific models into brms syntax, a powerfu...
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PessoaBrain @pessoabrain.bsky.social · 30/07/2025
𝗖𝗮𝗻 𝘁𝗵𝗲 𝗯𝗿𝗮𝗶𝗻 𝗿𝗲𝘀𝗽𝗼𝗻𝗱 𝗶𝗻 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 𝘄𝗮𝘆𝘀 𝘁𝗼 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝘁𝗮𝘀𝗸/𝗰𝗼𝗻𝗱𝗶𝘁𝗶𝗼𝗻𝘀? Some papers suggesting that it can. #neuroskyence www.nature.com/articles/s41...
nature.com
Multiple brain activation patterns for the same perceptual decision-making task - Nature Communications
Here, the authors show the brain uses multiple activation patterns to perform the same task. Even the default mode network, which is often inactive during focus, plays a role.
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Jonathan A. Michaels @jonathanamichaels.bsky.social · 28/05/2025
"It is thus as if nature smiled and gave the cerebellum-studying neuroscientist the ideal tool for testing null space hypotheses..." www.science.org/doi/10.1126/...
science.org
Math and biology meet in the cerebellum
There can be surprising differences between what neurons do and what neurons cause
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Warwick Psychology @warwickpsych.bsky.social · 28/05/2025
New work by Sudeep Bhatia @sdpbht.bsky.social, Simon van Baal @svanbaal.bsky.social, Feiyi Wang, and @lukaszwalasek.bsky.social Lukasz Walasek -- now out in Proceedings of the National Academy of Sciences! www.pnas.org/doi/10.1073/...
pnas.org
PNAS
Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans...
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Warwick Psychology @warwickpsych.bsky.social · 23/05/2025
Hey #AcademicSky #PsySky. All is ready for the start of the PG Research Day @warwickpsych.bsky.social @uni-of-warwick.bsky.social we’ll be covering the event live from 10am UK time
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Lucas Castillo @lcastillo.bsky.social · 21/05/2025
🚀🚀 Very excited about this new preprint with @yunxiao-li.bsky.social and @asanborn.bsky.social! Months ago we released the samplr package on CRAN (helps you use sampling algorithms + cogn. models for human data). Here we explain the theoretical background and show how to use the pkg osf.io/ax8hm
osf.io
OSF
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Maria M. Robinson @mmrobinson93.bsky.social · 20/05/2025
Excited to share some work presented at @vssmtg.bsky.social this year #VSS2025. A great talk by Anxin Miao on a model codeveloped with @timbrady.bsky.social that bridges Bayesian and representational theories of memory, and makes parameter free predictions of visual memory biases.
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Joey Saito @jsaito25.bsky.social · 14/05/2025
The Brady Lab @timbrady.bsky.social will be at #VSS2025 @vssmtg.bsky.social this year! Here's a thread with some of the cool work we're coming to share:
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Joey Saito @jsaito25.bsky.social · 14/05/2025
On Sat., 05/17 at 2:30PM in Visual Memory: General, former undergrad Anxin Miao will tell us how to predict gist biases in memory APRIORI through independent measurements of memory biases at the level of items and ensembles. CC: @mmrobinson93.bsky.social
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Henrik Singmann @singmann.bsky.social · 27/04/2025
Honey, we fixed Signal Detection Theory (SDT)! In this preprint, Constantin Meyer-Grant, David Kellen, Sam Harding, and I critically evaluate the (unequal-variance) Gaussian SDT model in recognition memory and pursue the Gumbel-min model as a principled alternative: doi.org/10.31234/osf... 🧵
doi.org
Extreme-Value Signal Detection Theory for RecognitionMemory: The Parametric Road Not Taken
Signal Detection Theory has long served as a cornerstone of psychological research, particularly in recognition memory. Yet its conventional application hinges almost exclusively on the Gaussian…
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