David Richter

If you’re interested in more details, check out the full paper:
doi.org/10.1016/j.is...

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.

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.

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!

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.

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.

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?

Rapid computation of high-level visual surprise Health sciences

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 👇

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...

🧠 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-...)

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...

@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. 🧠🟦 🧠🤖

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.

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!

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).

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/...

If you are interested in pursuing a PhD in cognitive neuroscience, specially targeting conscious vs. unconscious processing, contact me. We are recruiting 🙏🧠 please RT

🚨 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!

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

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...

If you are interested in more details check out the preprint here:
www.biorxiv.org/content/10.1...

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.

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.

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.

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.

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.

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?

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

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]

Shared and diverging neural dynamics underlying false and veridical perception We often mistake visual noise for meaningful images, which sometimes appear as convincing as veridical percepts. This suggests considerable overlap between the mechanisms that underlie false and verid...

New MEG paper by @jhaarsma.bsky.social and @dotproduct.bsky.social‬! Same design and behavioural results as our 7T layer fMRI study (www.jneurosci.org/content/43/4...), but now shedding light on the temporal dynamics of the sensory signals underlying false percepts. #neuroskyence

PhD Studentship: Public Communication and Private Confidence at Birkbeck, University of London Find a PhD Studentship: Public Communication and Private Confidence on jobs.ac.uk, the top job board in higher education. Click to view more!

Looking for a PhD in #psychology or #cogneuro ? I’m recruiting a fully-funded @leverhulme.ac.uk PhD student to join my lab at @birkbeckpsychology.bsky.social. If you’re interested in metacognition, learning, social cognition and culture I’d love you to apply 🧠👇

www.jobs.ac.uk/job/DNJ330/p...

I am so excited to share that our paper 'A neural basis for distinguishing imagination from reality' is now published in @cp-neuron.bsky.social! 🧠✨ See thread below! doi.org/10.1016/j.ne...

Introducing All-TNNs: Topographic deep neural networks that exhibit ventral-stream-like feature tuning and a better match to human behaviour than the gold standard. Now out in Nature Human Behaviour. 👇

PhD position alert!!!
Together with @predictivebrain.bsky.social and Sonja Kotz we are looking for a PhD candidate to join a great project on the biological foundations of perceptual decisions vacancies.maastrichtuniversity.nl/job/Maastric...

Happy to answer any question you may have!