Reposted by David RichterAlireza Modirshanechi @modirshanechi.bsky.social · 15/08/2026Excited 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! 🙏 1217059
Reposted by David RichterIngmar 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 11917
Reposted by David RichterDota Tianai Dong @dotadotadota.bsky.social · 21/07/20261/5 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. 14421
Reposted by David Richtermicha heilbron @mheilbron.bsky.social · 16/07/2026What 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⬇️ 34411
Reposted by David RichterTim Kietzmann @timkietzmann.bsky.social · 11/05/2026A huge effort and a new take on what constitutes the "feedforward pass" across the visual system. Make sure to check out our new preprint: 0427
Reposted by David RichterMind, Brain and Behavior Research Center - CIMCYC @cimcyc.bsky.social · 29/04/2026Spend 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 11118
Reposted by David Richterines-schoenmann.bsky.social @ines-schoenmann.bsky.social · 27/04/2026New 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) 312050
Reposted by David Richterbachlab @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 #PavlovianFearConditioningonlinelibrary.wiley.com<em>Psychophysiology</em> | SPR Journal | Wiley Online LibraryPavlovian 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... 152
David Richter @davidrichter.bsky.social · 28/04/2026Looking forward to it! Hope to see some of you there! 071
Reposted by David Richterandrea e. martin @andreaeyleen.eurosky.social · 13/04/2026OPEN 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/55exdpsetinyurl.comPostdoctoral Position in the Cognitive Computational Neuroscience of Language | Max Planck Institute 24141
Reposted by David RichterIngmar de Vries @ingmardevries.bsky.social · 04/04/2026JOB 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. 23526
Reposted by David RichterIngmar de Vries @ingmardevries.bsky.social · 30/03/2026I 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.comHierarchical priors and stimulus familiarity facilitate neural prediction of naturalistic...YouTube video by Cognitive Neuroscience & Brain Imaging conferences 1113
Reposted by David RichterDock H Duncan @docdocdunk.bsky.social · 31/03/2026Check out our new paper out in communications psychology! @commspsychol.nature.com 1112
Reposted by David RichterJuan Linde-Domingo @lindedomingo.bsky.social · 18/03/2026New 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... 15726
Reposted by David RichterClare Press @clarepress.bsky.social · 09/03/2026Temporally-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.comFixed and flexible perceptual rhythmsOur 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... 03815
Reposted by David Richtermicha 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 12935
Reposted by David Richtermicha 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 25239
Reposted by David RichterHeleen Slagter @haslagter.bsky.social · 29/01/2026What 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... 210039
David Richter @davidrichter.bsky.social · 08/01/2026It’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.eduFeature-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.... 000
David Richter @davidrichter.bsky.social · 08/01/2026In 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. 110
David Richter @davidrichter.bsky.social · 08/01/2026Rather 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. 110
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. 🧵👇 1205
David Richter @davidrichter.bsky.social · 11/12/2025Congratulations Peter! Amazing news and well deserved! 110
David Richter @davidrichter.bsky.social · 05/12/2025If you’re interested in more details, check out the full paper: doi.org/10.1016/j.is...doi.orgRedirecting 020
David Richter @davidrichter.bsky.social · 05/12/2025Taken 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. 130
David Richter @davidrichter.bsky.social · 05/12/2025We 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. 110
David Richter @davidrichter.bsky.social · 05/12/2025Then 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! 110
David Richter @davidrichter.bsky.social · 05/12/2025As 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. 110
David Richter @davidrichter.bsky.social · 05/12/2025We 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. 110
David Richter @davidrichter.bsky.social · 05/12/2025Predictive 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? 100
David Richter @davidrichter.bsky.social · 05/12/2025High-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.comRapid computation of high-level visual surpriseHealth sciences 23417
Reposted by David RichterEelke 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.eduRegularization, Action, and Attractors in the Dynamical “Bayesian” BrainAbstract. 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... 22912
Reposted by David RichterPeter 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.orgContents of visual predictions oscillate at alpha frequenciesPredictions 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... 711243
David Richter @davidrichter.bsky.social · 11/08/2025If 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. 0172
Reposted by David RichterTim Kietzmann @timkietzmann.bsky.social · 09/08/2025Hi, 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! 05931
Reposted by David RichterPeter Kok @peterkok.bsky.social · 08/08/2025We 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.ukUCL – University College LondonUCL 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). 05869
Reposted by David RichterLiad Mudrik @liadmudrik.bsky.social · 21/07/2025If you are interested in pursuing a PhD in cognitive neuroscience, specially targeting conscious vs. unconscious processing, contact me. We are recruiting 🙏🧠 please RT 03829
Reposted by David RichterCarlos 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.ioPostdoc Position – FLARE Project 12222
Reposted by David RichterTim Kietzmann @timkietzmann.bsky.social · 08/07/2025Exciting 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/2507.03168arxiv.org 313858
David Richter @davidrichter.bsky.social · 26/06/2025If you are interested in more details check out the preprint here: www.biorxiv.org/content/10.1...biorxiv.orgRapid Computation of High-Level Visual SurprisePredictive processing theories propose that the brain continuously generates expectations about incoming sensory information. Discrepancies between these predictions and actual inputs, sensory predict... 000
David Richter @davidrichter.bsky.social · 26/06/2025Taken 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. 110
David Richter @davidrichter.bsky.social · 26/06/2025We 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. 100
David Richter @davidrichter.bsky.social · 26/06/2025Next, 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. 100
David Richter @davidrichter.bsky.social · 26/06/2025First, 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. 100
David Richter @davidrichter.bsky.social · 26/06/2025We 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. 100
David Richter @davidrichter.bsky.social · 26/06/2025Predictive 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? 100
David Richter @davidrichter.bsky.social · 26/06/2025The 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 1239
Reposted by David RichterClare Press @clarepress.bsky.social · 19/06/2025Out 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] 36931