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Rochelle Kaper

@rochellekaper.bsky.social
712 followers 409 following 117 posts

phd student @ UCL experimental psych w/ Megan Peters (prev uc-irvine) 🧠 structure learning, metacognition, temporal dynamics, comp cog neuro. www.rochellekaper.com she/her

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Reposted by Rochelle Kaper
dorottya hetenyi @dotproduct.bsky.social · 14/10/2026
Friday’s a bad day to be a Guinness, but a good day to be a Brain Meeting. Please come along if you are interested in oscillations and perceptual predictions!👀
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Rochelle Kaper @rochellekaper.bsky.social · 12/10/2026
another core ability imo is to be able to monitor our errors, change our minds, reflect upon what we have learned. do you have thoughts on how this might be instantiated in CORE or on the contrary why CORE doesn't need it?
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Rochelle Kaper @rochellekaper.bsky.social · 12/10/2026
a huge part of our "core models" (particularly from associative learning & hierarchical representations) is that it lets us be able to transfer info across contexts.
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Rochelle Kaper @rochellekaper.bsky.social · 12/10/2026
this is interesting! I'm wondering if you thought about testing not just whether a model can predict behavior on stand-alone experiments but predict how humans generalize info across experiments or tasks?
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Department of Imaging Neuroscience @imagingneuroucl.bsky.social · 12/10/2026
#BrainMeeting 🧠 Alert! 🎺 This Friday, October 16th, the Brain Meeting speaker will be Dorottya Hetenyi giving a talk entitled "The oscillatory dynamics of perceptual predictions in the visual brain". Join us in person or online. Read more: www.in.fil.ion.ucl.ac.uk/events/gw2fa...
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ari ☀️ @khoudary.bsky.social · 07/10/2026
if you want to hear more of my thoughts in this space, I'll be giving a talk at #PSA2026 in the Friday morning symposium on "A “metabolic turn” in studying cognition and computation" -- more details available here! virtual.oxfordabstracts.com/event/75802/...
virtual.oxfordabstracts.com
OA Virtual conferences
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ari ☀️ @khoudary.bsky.social · 07/10/2026
very excited that the full version of this is now online! and especially so bc it includes a commentary by yours truly (with support from @aaronbornstein.bsky.social and @meganakpeters.bsky.social) - www.cambridge.org/core/journal...
cambridge.org
Blind ignorance or rational inattention? On the history and future of metabolic considerations for cognitive models | Behavioral and Brain Sciences | Cambridge Core
Blind ignorance or rational inattention? On the history and future of metabolic considerations for cognitive models - Volume 49
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Open Encyclopedia of Cognitive Science bot @oecs-bot.bsky.social · 07/10/2026
Learning from trial and error involves a complex interplay of neural circuits and computational processes that extend far beyond simple reward… Reinforcement Learning by Anne GE Collins doi.org/10.21428/e2759450.36d1ca92 #CognitiveScience
Open Encyclopedia of Cognitive Science: "Reinforcement Learning" by Anne GE Collins. Reinforcement learning (RL) refers to a process in which an agent (biological or artificial) learns how to behave in its environment by using a simple type of information: reinforcers, which index how
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Rochelle Kaper @rochellekaper.bsky.social · 07/10/2026
yeah and Michelle is even a standard keychain name!
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Rochelle Kaper @rochellekaper.bsky.social · 07/10/2026
yeahh it actually has happened before🥲 first time was when i tried to make a webkinz account when i was 6
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Rochelle Kaper @rochellekaper.bsky.social · 07/10/2026
well this is a new one😑
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Rochelle Kaper @rochellekaper.bsky.social · 06/10/2026
joining this lab & working with megan was the best decision i've ever made👇!!
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Rochelle Kaper @rochellekaper.bsky.social · 05/10/2026
woohoooo🎉congrats!
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Reposted by Rochelle Kaper
Alish Dipani @alishdipani.bsky.social · 03/10/2026
Finding a "face neuron" in an ANN doesn't mean it encodes faces like we do. 🧵 In my first project with @apurvaratan.bsky.social, we show that category selectivity in ANNs ≠ category selectivity in brains. Details in thread + preprint: www.biorxiv.org/content/10.6... Feedback or questions welcome!
biorxiv.org
Category selectivity observed in the human brain is distinct from category selectivity observed in artificial neural networks
Category selectivity for images of faces, scenes, and bodies is among the most striking and reproducible findings in vision neuroscience. Artificial neural networks (ANNs) trained on visual tasks also...
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Dr Anna Leshinskaya @annaleshinskaya.bsky.social · 02/10/2026
I am recruiting graduate students for UCI's PhD in Cognitive Sciences - www.cogsci.uci.edu/graduate/pro... The lab's focus is on how relational structure and combinatorial reasoning is implemented in human brains and large language models--and if they are similar.
cogsci.uci.edu
GRADUATE PROGRAM
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Open Encyclopedia of Cognitive Science bot @oecs-bot.bsky.social · 02/10/2026
The human mind instinctively extracts order from chaos, tracking probabilities across sounds and scenes to build complex knowledge from raw input. Statistical Learning by Jenny Saffran doi.org/10.21428/e2759450.7a74eed8 #CognitiveScience
Open Encyclopedia of Cognitive Science: "Statistical Learning" by Jenny Saffran. Statistical learning refers to the ability to track patterns in the environment. These patterns occur in a wide array of domains (e.g., speech, scenes, melodies). Humans track statistics over stimuli
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Henrik Singmann @singmann.bsky.social · 02/10/2026
New preprint: When should you use linear mixed models (LMMs), and when is repeated-measures (RM) ANOVA enough? LMMs offer greater flexibility. But does that make them a better default? My paper argues for statistical parsimony: use RM-ANOVA when both methods are appropriate. osf.io/preprints/ps...
osf.io
When to Use Mixed Models and When RM-ANOVA - An Argument for Statistical Parsimony
When should researchers use linear mixed-effects models (LMMs) versus repeated-measures analysis of variance (RM-ANOVA) for analysing repeated-measures data? I first outline the conceptual and statist...
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Ari Kahn @arikahn.bsky.social · 02/10/2026
This was an incredibly fun paper to collaborate on the modeling for, thrilled to see it finally out in Neuron!
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Rochelle Kaper @rochellekaper.bsky.social · 01/10/2026
go work with Jorge🧠!!
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Nature Human Behaviour @nathumbehav.nature.com · 01/10/2026
Intrinsic rewards guide visual resource allocation via reinforcement learning
dlvr.it
Intrinsic rewards guide visual resource allocation via reinforcement learning
Nature Human Behaviour, Published online: 01 October 2026; doi:10.1038/s41562-026-02573-7Tangible rewards are known to sharpen visual processing of associated objects. Tomić et al. show that an internal sense of confidence—acting as an intrinsic reward—similarly biases attention, revealing how the brain prioritizes limited resources.
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Caroline Pioger @carolinepioger.bsky.social · 29/09/2026
🚨 New preprint! Public debate on decarbonization often rests on inaccurate beliefs about energy sources. We tested whether a reinforcement-learning-based intervention can correct them. 🧵👇 📄 Preprint: zenodo.org/records/2303...
zenodo.org
Correcting misconceptions and shaping preferences about energy with reinforcement learning
Addressing the climate crisis requires citizens to make informed choices about sustainable energy policy, yet public debates are often shaped by inaccurate beliefs about the environmental and health i...
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Ziyao Zhang @bulezz.bsky.social · 30/09/2026
a fun collaboration with yanni and the self-regulation lab. We tested neural distinctions between anticipating social and monetary reward in a large sample study
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Neuromatch @neuromatch.bsky.social · 29/09/2026
⏰ Reminder: Impact Scholars Supervisor applications close this Sunday, 4 October 2026! We're especially interested in hearing from Supervisors for these two projects: 🧠 A #CompNeuro project: airtable.com/app7MJ7encL0... 🤖 A #NeuroAI project: airtable.com/app7MJ7encL0...
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ari ☀️ @khoudary.bsky.social · 29/09/2026
how does memory support perceptual decisions made under uncertainty? this question has scaffolded my entire PhD, and I'm so excited to share part of it in this ✨new preprint ✨ w/ @meganakpeters.bsky.social and @aaronbornstein.bsky.social! link: www.biorxiv.org/content/10.6...
biorxiv.org
Memory retrieval explains dynamic effects of expectations on perceptual decisions
Expectations—prior knowledge of environmental statistics—support adaptive behavior by reducing uncertainty during inference. However, the questions of where expectations come from and how that ought t...
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Kobe Desender @kobedesender.bsky.social · 29/09/2026
"Adaptive Regulation of Confidence Following Metacognitive Conflict: Evidence From Behavior and Computational Modeling"! Now out in #JEPGeneral led by @jintaoxing.bsky.social @stefherregods.bsky.social @lucvermeylen.bsky.social and me. PDF: desenderlab.com/wp-content/u.... "Conflicting" Thread ↓↓↓
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RLDM @rldmparis2027.bsky.social · 29/09/2026
📣 Save the date! RLDM 2027, the Multi-disciplinary Conference on Reinforcement Learning and Decision Making, is coming to Paris, July 6-9, 2027 🎉 Stay tuned for submission deadlines and more updates on our website rldm.org 👀
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Rochelle Kaper @rochellekaper.bsky.social · 28/09/2026
congratulations!!!
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Sandra Romero Pinto @sromeropinto.bsky.social · 25/09/2026
Happy to have this finally out! TL;DR: The evolution of beliefs over time can be formulated as a dynamical system, and OFC neural activity appears to implement this system with its own dynamics. These emerge without explicit supervision—when animals learn to predict value in simple Pavlovian tasks
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Ryszard Auksztulewicz @auksz.bsky.social · 25/09/2026
What can DNNs tell us about how the brain learns? Our new results show that predictive local learning better captures changes in brain representations during statistical learning than supervised or contrastive approaches. Excellent work by @denisekittelmann.bsky.social and @gutlin.bsky.social
biorxiv.org
Predictive coding networks capture human neural representations missing in supervised DNNs
Neuroscientific learning theories propose that the brain acquires knowledge by constructing internal world models. Supervised learning, the dominant approach in deep neural networks (DNN), relies on e...
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Reposted by Rochelle Kaper
Mustafa Alperen Ekinci @alpekinci.bsky.social · 18/09/2026
The first paper of my PhD work! We show that our aesthetic experiences while watching movies can be partly explained by shared perceptual mechanisms: a combination of image-based visual features predicts our moment-to-moment aesthetic experiences, even across different movies.
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Alex Hyafil @alexhyafil.bsky.social · 23/09/2026
📣2 postdoc and 1 phD positions on computational mechanisms of human perception in Barcelona. One postdoc position (2-y) is joint w Chris Summerfield ( @summerfieldlab.bsky.social) on visual scene perception, mixing modelling w ANN and behavioral experiments.
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Neuromatch @neuromatch.bsky.social · 22/09/2026
📣 Neuromatch is looking for Impact Scholars Supervisors for our 2026-2027 cohort. Apply by 4 Oct 2026 or share with someone who'd be great at it! ➡️ Learn more: neuromatch.io/impact-schol..., docs.neuromatch.io/p/NiH1Z1N6bB... ➡️ Apply here: airtable.com/app7MJ7encL0...
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Rochelle Kaper @rochellekaper.bsky.social · 22/09/2026
congratulations🎉!!
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Kevin O’Neill @kevingoneill.github.io · 17/09/2026
New commentary! Are scientists and laypeople alike under persistent illusions of understanding? Shiffrin, Stigler, & Keil (2026) seem to think so. I argue this isn't the case w/ @sharonchungsl.bsky.social, Adam Harris, @davidlagnado.bsky.social & @singmann.bsky.social: rdcu.be/3swzbgH3ePva
rdcu.be
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Pascal Mamassian @mamassian.bsky.social · 17/09/2026
Congratulations to Dr Tarryn Balsdon for beautifully defending her “Habilitation à Diriger des Recherches”, i.e. autorisation to officially supervise her own PhD students!!!
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Rochelle Kaper @rochellekaper.bsky.social · 16/09/2026
thank you to @meganakpeters.bsky.social for her support & sharing my excitement🤗!
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Rochelle Kaper @rochellekaper.bsky.social · 16/09/2026
in this revamped version, we highlight how our task speaks to refining pre-existing assumptions of structure learning & metacognition! we discuss the computational role of metacognition that goes beyond a singular role in learning to be adaptive & context-dependent💪
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Rochelle Kaper @rochellekaper.bsky.social · 16/09/2026
PREPRINT UPDATE🥳👇: 🧠learning under uncertainty & metacognitive processes are not as generalizable as previously thought! both evolve differently depending on structure & stimulus set osf.io/preprints/ps...
osf.io
OSF
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Steve Fleming @smfleming.bsky.social · 16/09/2026
📖 New review out today in @natrevneuro.nature.com: Towards an integrative neuroscience of metacognition 🧠🧪 Full-text link to the paper is here: rdcu.be/9YK3mF7dYhFa
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Kevin O’Neill @kevingoneill.github.io · 15/09/2026
delighted to have been able to chip in on this newly published paper by @wiktoriakozyra.bsky.social & @smfleming.bsky.social on how confidence “biases” arise from normative Bayesian models!
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ARC ETHOS @arcethos.bsky.social · 14/09/2026
Meet the Team: @rochellekaper.bsky.social is a PhD student in Experimental Psychology at the University College London. She is interested in applying computational cognitive neuroscience approaches to study adaptive learning, metacognition, and (meta)-representational processes.
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Renzo Lanfranco @renzolanfranco.bsky.social · 14/09/2026
How much information about a stimulus is available to a perceptual system, and how much of that information becomes consciously accessible? In this new Perspective, “Perceptual awareness as an information-distribution problem,” I propose an information-theoretic framework. 🧵Preprint: osf.io/zmf5h
osf.io
OSF
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Steve Fleming @smfleming.bsky.social · 14/09/2026
Our paper “Confidence is detection-like in high-dimensional spaces” is now published in Open Mind, led by @wiktoriakozyra.bsky.social and @kevingoneill.github.io direct.mit.edu/opmi/article...
direct.mit.edu
Confidence Is Detection-Like in High-Dimensional Spaces
Abstract. Confidence estimates are often “detection-like”—driven by positive evidence in favour of a decision. This empirical observation has been interpreted as showing that human metacognition is li...
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Steve Fleming @smfleming.bsky.social · 08/09/2026
and... our paper with @nicoschuck.bsky.social and Marit Petzka on the relationship between replay and conscious thought! www.cell.com/trends/cogni...
cell.com
What can we learn from studying replay in humans?
Noninvasive methods are making it possible to study neural replay in humans. Although focused on alignment with rodent findings, human research often tacitly assumes that replay is linked to conscious, deliberate thought. This assumption represents a missed opportunity to investigate the links between replay and consciousness, as well as cross-species differences more broadly.
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Steve Fleming @smfleming.bsky.social · 09/09/2026
Glad to be part of this elegant study that is reshaping the way I think about metacognition. Confidence is strikingly goal-sensitive, with supposedly sensory biases such as PEB being readily flipped through instruction. Led by Prady Sepulveda and Benedetto De Martino www.biorxiv.org/content/10.6...
biorxiv.org
Goals shape human confidence
Confidence guides our decisions: it determines when we commit to a choice, gather more information, or change our minds. Prominent models treat confidence as a readout of the evidence in support of a ...
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Ido Ben-Artzi @idoba.bsky.social · 09/09/2026
Excited to share our recent publication in @natcomms.nature.com We started by trying to make people stop associating the money rewards they obtain with irrelevant features of their behavior. In the first experiment, we used clear instructions framed as a story, and it didn't help...
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Rochelle Kaper @rochellekaper.bsky.social · 04/09/2026
thank you! will have to meet up soon🥳!
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Rochelle Kaper @rochellekaper.bsky.social · 03/09/2026
ft @meganakpeters.bsky.social 's office 😉
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Rochelle Kaper @rochellekaper.bsky.social · 03/09/2026
finalllly in london🇬🇧🤩 super pumped & ready to get started at @uclpals.bsky.social 🤓!
UCLUCL student centreBig Ben
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Zihan Bai @zihanbai.bsky.social · 03/09/2026
Excited to share the first first-author preprint of my PhD at NYU with @s-michelmann.bsky.social andDaryl Fougnie. Using eye-tracking in a novel behavioral paradigm, we reveal the mechanisms by which episodic memory (EM) and working memory (WM) interact. 🧠 doi: doi.org/10.64898/202...
doi.org
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