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David Richter

@davidrichter.bsky.social
300 followers 230 following 47 posts

Cognitive Neuroscientist | Predictive Processing & Perception Researcher. At: Donders Institute. Formerly: CIMCYC, Granada & VU Amsterdam. www.richter-neuroscience.com

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David Richter @davidrichter.bsky.social · 18/09/2026
Very much recommended ❤️
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Alireza Modirshanechi @modirshanechi.bsky.social · 15/08/2026
Excited to share that I'll be starting as a junior professor and Emmy Noether awardee at the University of Göttingen this October! 🥳 🚀 I'll be hiring #phd students and #postdoc across #machinelearning, #neuroscience and #cogsci: modirlab.github.io/open-positio... Please spread the word! 🙏
PhD ad informationPostdoc ad informationInformation about Göttingen and equal opportunities
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Ingmar de Vries @ingmardevries.bsky.social · 03/08/2026
🔭JOB ALERT🔬 Fully-funded PhD (+ soon postdoc) openings in my lab @cimecunitrento.bsky.social in Italy, as part of an Italian FIS3 starting grant. TOPIC: Investigating predictive neural representations in naturalistic settings using MEG-based dynamic RSA
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Dota Tianai Dong @dotadotadota.bsky.social · 21/07/2026
1/5 Over a decade of comparing deep neural networks to the human brain—but what have we actually learned? Our new @cp-trendscognsci.bsky.social Feature Review synthesizes a decade of brain–DNN comparisons, asking what they reveal about brain function across vision and language.
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micha heilbron @mheilbron.bsky.social · 16/07/2026
What makes some stimuli more memorable than others? In a new paper w/ @davogelsang.bsky.social, we show that the magnitude of a stimulus's ANN representation predicts both image and word memorability Stimuli that activate more features, more strongly, leave a stronger memory trace Out now in JML⬇️
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Tim Kietzmann @timkietzmann.bsky.social · 11/05/2026
A huge effort and a new take on what constitutes the "feedforward pass" across the visual system. Make sure to check out our new preprint:
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Mind, Brain and Behavior Research Center - CIMCYC @cimcyc.bsky.social · 29/04/2026
Spend your July doing research in Granada! The CIMCYC is calling for talented undergraduate students (non-UGR) to join our Summer Research Stays 2026. 📍 9 Placements available 💶 €1,600 scholarship 🔬 8 specialized Research Groups (see next post!) 🏡 Housing support included Apply by May 11
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ines-schoenmann.bsky.social @ines-schoenmann.bsky.social · 27/04/2026
New peer-reviewed paper w/ @mheilbron.bsky.social, @predictivebrain.bsky.social & Jakub Szewczyk! Pre-onset brain encoding has been taken as evidence that brains–like LLMs–predict upcoming words. We show that the same signatures arise in systems that cannot predict. (elifesciences.org) (1/8)
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bachlab @bachlab.bsky.social · 29/04/2026
📢Publication Alert: New Paper on Human Pavlovian Fear Conditioning! It has been speculated that psychophysiological responses to an outcome during learning could express prediction errors. ➡️ onlinelibrary.wiley.com/doi/10.1111/... #associativelearning #psychophysiology #PavlovianFearConditioning
onlinelibrary.wiley.com
<em>Psychophysiology</em> | SPR Journal | Wiley Online Library
Pavlovian reward learning is driven by prediction errors (PE), but it remains unclear whether this is also the case for aversive learning, and to what extent PE are expressed in physiological indices...
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David Richter @davidrichter.bsky.social · 28/04/2026
Looking forward to it! Hope to see some of you there!
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andrea e. martin @andreaeyleen.eurosky.social · 13/04/2026
OPEN POSTDOC position (part of @erc.europa.eu Consolidator DYNALANG) We build math&comp models of neural dynamics using insights from formal linguistics + ML Seeking theory-driven researchers w/ interests in language, neural dynamics, & math/comp neuroscience. Apply here: tinyurl.com/55exdpse
tinyurl.com
Postdoctoral Position in the Cognitive Computational Neuroscience of Language | Max Planck Institute
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Ingmar de Vries @ingmardevries.bsky.social · 04/04/2026
JOB ALERT: PhD opening in my lab! @cimecunitrento.bsky.social in Italy, as part of an Italian FIS3 starting grant. The project will use advanced analysis methods of MEG data to investigate how our world's naturalistic hierarchical structure facilitates predictive neural processing.
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Ingmar de Vries @ingmardevries.bsky.social · 30/03/2026
I recently had the pleasure to visit the great Neurospin institute in Paris where I presented my work on the neural prediction of naturalistic dynamic input: www.youtube.com/watch?v=Ywxt... Some data from the talk is published at: doi.org/10.1038/s414... and doi.org/10.1101/2025...
youtube.com
Hierarchical priors and stimulus familiarity facilitate neural prediction of naturalistic...
YouTube video by Cognitive Neuroscience & Brain Imaging conferences
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Dock H Duncan @docdocdunk.bsky.social · 31/03/2026
Check out our new paper out in communications psychology! @commspsychol.nature.com
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Juan Linde-Domingo @lindedomingo.bsky.social · 18/03/2026
New paper! 🚨 ~1.8K Mooney images from THINGS + ~1K participants to study visual ambiguity resolution. Results suggest the visual system shifts from a top-down guess to bottom-up matching after disambiguation, and a U-shaped link between info gain and identification. www.nature.com/articles/s44...
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Clare Press @clarepress.bsky.social · 09/03/2026
Temporally-precise sensory encoding of predicted content, entraining motor oscillations to derive time. @akalt.bsky.social's first study out @currentbiology.bsky.social, testing parts of this idea (tinyurl.com/TiCSKaltenma...). Huge thanks @leverhulme.ac.uk ac.uk @erc.europa.eu, great work Aaron!
tinyurl.com
Fixed and flexible perceptual rhythms
Our sensory inputs are never identical across time and contain temporal structure. Cognitive scientists have recently been fascinated by how these sensory rhythms interact with neural oscillatory rhyt...
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micha heilbron @mheilbron.bsky.social · 10/03/2026
📢 PhD position in Developmental Language Modelling (PLZ RT) What can human language acquisition teach us about training language models? Join us as a PhD! mpi.nl/career-education/vacancies/vacancy/fully-funded-4-year-phd-position-developmental-language @carorowland.bsky.social @mpi-nl.bsky.social
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micha heilbron @mheilbron.bsky.social · 05/03/2026
📢 PhD position in the NeuroAI of Language Why can LLMs predict brain activity so well? We're hiring a PhD student to find out -- AI interpretability meets neuroimaging Deadline March 20 Please RT 🙏 👇 mpi.nl/career-education/vacancies/vacancy/fully-funded-4-year-phd-position-neuroai-language
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Heleen Slagter @haslagter.bsky.social · 29/01/2026
What is the brain for? Active inference is widely discussed as a unifying framework for understanding brain function, yet its empirical status remains debated. Our review identifies core predictions across the action-perception cycle and evaluates their empirical support: osf.io/preprints/ps...
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David Richter @davidrichter.bsky.social · 08/01/2026
It’s a short read, highlighting open questions about where and how feature-specific prediction errors are computed and relayed across the visual hierarchy. Take a look! direct.mit.edu/imag/article...
direct.mit.edu
Feature-specific predictive processing: What’s in a prediction error?
Abstract. Despite numerous studies reporting sensory prediction errors—a key component of predictive processing theories—the nature of the surprise represented in these errors remains largely unknown....
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David Richter @davidrichter.bsky.social · 08/01/2026
In our article, we discuss whether and how four accounts might explain these results: (1) hierarchical predictive coding, (2) feedback propagation of error signals, (3) V1 as a comparator circuit for higher-level features, (4) dendritic HPC.
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David Richter @davidrichter.bsky.social · 08/01/2026
Rather than focusing only on the magnitude of surprise, studies have begun to probe the content of prediction errors, showing that even early visual responses may primarily scale with high-level, rather than low-level, visual surprise.
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David Richter @davidrichter.bsky.social · 08/01/2026
🧠 Feature-specific predictive processing: What’s in a prediction error? 🧠 Perspective article w/ Cem Uran, @martinavinck.bsky.social & @predictivebrain.bsky.social now in @imagingneurosci.bsky.social, highlighting recent work on the nature of surprise reflected in visual prediction errors. 🧵👇
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David Richter @davidrichter.bsky.social · 11/12/2025
Congratulations Peter! Amazing news and well deserved!
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David Richter @davidrichter.bsky.social · 09/12/2025
Thanks Juan!
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David Richter @davidrichter.bsky.social · 05/12/2025
If you’re interested in more details, check out the full paper: doi.org/10.1016/j.is...
doi.org
Redirecting
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David Richter @davidrichter.bsky.social · 05/12/2025
Taken together, our findings show that high-level visual predictions are rapidly integrated during perceptual inference, suggesting that the brain's predictive machinery is finely tuned to utilize expectations abstracted away from low-level sensory details to facilitate perception.
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David Richter @davidrichter.bsky.social · 05/12/2025
We also found a small decrease in neural responses by semantic (word-based) surprise. Notably, low-level visual surprise had no detectable effect, even though stimuli were predictable all the way down to the pixel level.
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David Richter @davidrichter.bsky.social · 05/12/2025
Then we turned to the key questions: When and what kind of surprise drives visually evoked responses? Neural responses ~190 ms post-stimulus onset over parieto-occipital electrodes were selectively increased by high-level visual surprise!
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David Richter @davidrichter.bsky.social · 05/12/2025
As a sanity check, we first used RSA to show that the CNN and other models of interest (semantic and task models) robustly explained the EEG responses independent of surprise.
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David Richter @davidrichter.bsky.social · 05/12/2025
We investigated these questions using EEG and a visual CNN. Participants viewed object images that were probabilistically predicted by preceding cues. We then quantified surprise trial-by-trial at low-levels (early CNN layers) and high-levels (late CNN layers) of visual feature abstraction.
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David Richter @davidrichter.bsky.social · 05/12/2025
Predictive processing theories propose that the brain continuously generates predictions about incoming sensory input. But what exactly does the brain predict? Low-level (edges, contrasts) and/or high-level visual features (textures, objects)? And when do these predictions shape neural responses?
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David Richter @davidrichter.bsky.social · 05/12/2025
High-level visual surprise is rapidly integrated during perceptual inference! 🚨 New paper 🚨 out now in @cp-iscience.bsky.social with @paulapena.bsky.social and @mruz.bsky.social www.cell.com/iscience/ful... Summary 🧵 below 👇
cell.com
Rapid computation of high-level visual surprise
Health sciences
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Eelke Spaak @eelkespaak.bsky.social · 22/10/2025
🧠 Regularization, Action, and Attractors in the Dynamical “Bayesian” Brain direct.mit.edu/jocn/article... (still uncorrected proofs, but they should post the corrected one soon--also OA is forthcoming, for now PDF at brainandexperience.org/pdf/10.1162-...)
direct.mit.edu
Regularization, Action, and Attractors in the Dynamical “Bayesian” Brain
Abstract. The idea that the brain is a probabilistic (Bayesian) inference machine, continuously trying to figure out the hidden causes of its inputs, has become very influential in cognitive (neuro)sc...
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Peter Kok @peterkok.bsky.social · 21/10/2025
@dotproduct.bsky.social's first first author paper is finally out in @sfnjournals.bsky.social! Her findings show that content-specific predictions fluctuate with alpha frequencies, suggesting a more specific role for alpha oscillations than we may have thought. With @jhaarsma.bsky.social. 🧠🟦 🧠🤖
jneurosci.org
Contents of visual predictions oscillate at alpha frequencies
Predictions of future events have a major impact on how we process sensory signals. However, it remains unclear how the brain keeps predictions online in anticipation of future inputs. Here, we combin...
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David Richter @davidrichter.bsky.social · 11/08/2025
If you’re into predictive processing and curious about the ‘what & when of visual surprise’, come see me at #CCN2025 in Amsterdam! Poster B23 · Wednesday at 1:00 pm · de Brug.
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Tim Kietzmann @timkietzmann.bsky.social · 09/08/2025
Hi, we will have three NeuroAI postdoc openings (3 years each, fully funded) to work with Sebastian Musslick (@musslick.bsky.social), Pascal Nieters and myself on task-switching, replay, and visual information routing. Reach out if you are interested in any of the above, I'll be at CCN next week!
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Peter Kok @peterkok.bsky.social · 08/08/2025
We are recruiting a new PI at the FIL @imagingneuroucl.bsky.social, Associate or Full Professor. This is an amazing place to do cognitive neuroscience, in the heart of London. If you or someone you know might be interested, please pass it on. #neuroskyence www.ucl.ac.uk/work-at-ucl/...
ucl.ac.uk
UCL – University College London
UCL is consistently ranked as one of the top ten universities in the world (QS World University Rankings 2010-2022) and is No.2 in the UK for research power (Research Excellence Framework 2021).
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Liad Mudrik @liadmudrik.bsky.social · 21/07/2025
If you are interested in pursuing a PhD in cognitive neuroscience, specially targeting conscious vs. unconscious processing, contact me. We are recruiting 🙏🧠 please RT
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Carlos González-García @gonzalezgarcia.bsky.social · 18/07/2025
🚨 We’re hiring a postdoc! Join the FLARE project @cimcyc.bsky.social to study sudden perceptual learning using fMRI, RSA, and DNNs. 🧠 2 years, fully funded, flexible start More info 👉 gonzalezgarcia.github.io/postdoc/ DMs or emails welcome! Please share!
gonzalezgarcia.github.io
Postdoc Position – FLARE Project
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Tim Kietzmann @timkietzmann.bsky.social · 08/07/2025
Exciting new preprint from the lab: “Adopting a human developmental visual diet yields robust, shape-based AI vision”. A most wonderful case where brain inspiration massively improved AI solutions. Work with @zejinlu.bsky.social @sushrutthorat.bsky.social and Radek Cichy arxiv.org/abs/2507.03168
arxiv.org
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David Richter @davidrichter.bsky.social · 26/06/2025
If you are interested in more details check out the preprint here: www.biorxiv.org/content/10.1...
biorxiv.org
Rapid Computation of High-Level Visual Surprise
Predictive processing theories propose that the brain continuously generates expectations about incoming sensory information. Discrepancies between these predictions and actual inputs, sensory predict...
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David Richter @davidrichter.bsky.social · 26/06/2025
Taken together, our findings demonstrate that high-level visual predictions are rapidly integrated during perceptual inference. This suggests that the brain's predictive machinery is finely tuned to utilize expectations abstracted away from low-level sensory details, likely to facilitate perception.
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David Richter @davidrichter.bsky.social · 26/06/2025
We also found a curious decrease in ERP amplitude by semantic (word-based) surprise. Critically, we found no modulation by low-level visual surprise, even though stimuli were predictable all the way down to the pixel level.
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David Richter @davidrichter.bsky.social · 26/06/2025
Next, we turned to the key questions – when and what kind of surprise drive visually evoked responses? Results showed that neural responses around 200ms post-stimulus onset over parieto-occipital electrodes were selectively enhanced by high-level visual surprise.
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David Richter @davidrichter.bsky.social · 26/06/2025
First, as a sanity check, we used RSA to show that the DNN and other models of interest (a semantic word-based and a task model) well explained the EEG response irrespective of surprise.
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David Richter @davidrichter.bsky.social · 26/06/2025
We investigated these questions using EEG and a visual DNN. Participants viewed object images that were probabilistically predicted by preceding cues. We then quantified trial-by-trial surprise at low-levels (early DNN layers) and high-levels (late DNN layers) of visual feature abstraction.
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David Richter @davidrichter.bsky.social · 26/06/2025
Predictive processing holds that the brain continuously generates predictions about incoming sensory information. But at what level of abstraction does the brain predict – edges & contrasts or high-level textures & objects? And which stages of visual processing do such predictions modulate?
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David Richter @davidrichter.bsky.social · 26/06/2025
The what and when of visual surprise: EEG shows that high-level visual surprise emerges rapidly and modulates neural responses ~200ms after stimulus onset. New preprint with @paulapena.bsky.social and @mruz.bsky.social available here: doi.org/10.1101/2025... Summary 🧵 below
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Clare Press @clarepress.bsky.social · 19/06/2025
Out now @cp-trendscognsci.bsky.social, w/ @akalt.bsky.social & @drmattdavis.bsky.social. Are sensory sampling rhythms fixed by intrinsically-determined processes, or do they couple to external structure? Here we highlight the incompatibility between these accounts and propose a resolution [1/6]
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