🏰 New preprint! 🏰

(w/ the excellent @neuronomist.bsky.social & Prof. Jason Mattingley)

For my PhD I've been using EEG, psychophysics and modelling to explore how the brain uses uncertainty to balance sensory information against expectations about what's out there.

🧵1/n

My first foray into explicitly trying to bridge Marr’s levels, with @bealebrains.bsky.social. Inspired by Hahn and Wei’s models (pubmed.ncbi.nlm.nih.gov/38360947/), we wondered how the brain could instantiate sensory inference with efficient /decoding/ properties.

1/

Will the ads also be AI-generated?? 👀

Using time-resolved EEG/MEG decoding?🧠 Here’s a new approach!
No feature engineering (decode from raw signals), but capturing info that standard decoding often misses (oscillatory/aperiodic activity, connectivity).
Lightweight, INTERPRETABLE, and easy to use. (1/6)
www.biorxiv.org/content/10.6...

This is great work, Runhao! Really impressive improvement in decoding. Would the interpreted features vary much with different instantiations of the untrained channel projection weights/time constants?

"The Analytical Engine has no pretensions whatever to originate any thing. It can do whatever we know how to order it to perform. It [cannot] anticipat[e] any analytical relations or truths. Its province is to assist us in making available what we are already acquainted with."

— Ada Lovelace, 1843

Clarifying the conceptual dimensions of representation in neuroscience Nature Reviews Neuroscience - Appeals to representation are widespread, despite neuroscientists’ uncertainty about what kind of findings count as evidence for such claims. In this...

www.nature.com/articles/s41...

Our paper on double decisions in working memory tasks is now published in Computational Brain and Behaviour!

When you give people a second chance, it reveals a lot about the contents of their memory.

Led by @paulmgarrett.bsky.social
@psychunimelb.bsky.social

rdcu.be/e8SLX

Screenshot of job ad: How do Bayesian brains acquire priors? APPLICATIONS CLOSE 20/4/2026 11:55 PM Summary of the Project This project explores how the brain constructs perceptual experience from visual input, focusing on the role of Bayesian models in perception. A key challenge in vision science is understanding how humans interpret complex scenes from the limited information available in retinal images. Modern theories suggest that perception involves probabilistic inference, where the brain integrates sensory signals with prior expectations to make sense of the world. However, the origins and nature of these expectations remain poorly understood. This research aims to advance our understanding of perceptual experience by examining how structured patterns in visual input can inform models of perception. The work spans computational modelling and experimental approaches to uncover principles that explain how visual systems interpret properties such as shape, material, and lighting from images. By addressing fundamental questions about perception, this project will contribute to psychology, neuroscience, and artificial intelligence, offering insights into how biological and artificial systems can learn to interpret complex environments.

I'm looking for a skilled PhD student who doesn't want to work too hard but still do great science:
unisc-cp.enquire.cloud/round/RND-00...

To add to this: now is the time we need human to human training and transfer of verifiable research and scholarship skills.

As much as tech bros want to replace your jobs, legitimate scientists are now more important than ever.

Excited to share our new paper in @pnas.org with @bnmorillon.bsky.social &
@valentinwyart.bsky.social www.pnas.org/doi/10.1073/...
We study three core inference systems, and how their interaction shapes human learning and decision-making.

𝗪𝗵𝗮𝘁 𝗶𝘀 𝗰𝗼𝗺𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻 𝗶𝗻 𝗱𝘆𝗻𝗮𝗺𝗶𝗰𝗮𝗹 𝘀𝘆𝘀𝘁𝗲𝗺𝘀?
Interesting paper tackling this difficult question.
Answer (in part): it's complicated!
The same fixed system can be interpreted as implementing many (even infinitely many) computations depending on the chosen decoding map.
doi.org/10.1088/2632...

Why do children struggle to recognise objects in cluttered scenes more than adults? Our new paper looks at the development of visual acuity and crowding across childhood, and the way the visual system fine tunes our ability to see detail: www.nature.com/articles/s41...

from a published academic paper by highly influential authors: pmc.ncbi.nlm.nih.gov/articles/PMC...

Visual language models show widespread visual deficits on neuropsychological tests - Nature Machine Intelligence Tangtartharakul and Storrs use standardized neuropsychological tests to compare human visual abilities with those of visual language models (VLMs). They report that while VLMs excel in high-level obje...

Our latest paper, “Visual language models show widespread visual deficits on neuropsychological tests”, is now out in Nature Machine Intelligence: www.nature.com/articles/s42...

Non-paywalled version:
arxiv.org/abs/2504.10786

Tweet thread below from first author @genetang.bsky.social...

Visual confidence accurately tracks increasing internal noise with eccentricity in peripheral vision www.biorxiv.org/content/10.64898/2026.01...

Check out our new paper on Journal of Vision showing that both endogenous and exogenous attention enhance contrast sensitivity uniformly across meridians despite differential adaptation effects!

jov.arvojournals.org/article.aspx...

Using artificial neural networks to reveal the human confidence computation Author summary Human decisions are accompanied by a sense of confidence which reflects the decision accuracy. Conventionally, human confidence has been studied using two-choice tasks with simple stimu...

How do people compute a sense of confidence? This question is usually addressed using very simple images because we don't know how complex stimuli are represented internally. In a new paper, we addressed this question using artificial neural networks (ANNs).

journals.plos.org/ploscompbiol...

With some trepidation, I'm putting this out into the world:
gershmanlab.com/textbook.html
It's a textbook called Computational Foundations of Cognitive Neuroscience, which I wrote for my class.

My hope is that this will be a living document, continuously improved as I get feedback.

How heterogeneity shapes dynamics and computation in the brain No two neurons are the same, yet models often treat neural populations as pools of identical and interchangeable elements. Here, Dahmen et al. highlight recent theoretical advances that reveal the imp...

At the Bernstein Conference 2024, Jeremie Lefebvre and I organized a workshop on the computational consequences of neural heterogeneity. Now, slightly more than a year later, we funneled the emerging discussions into a perspective piece: www.cell.com/neuron/fullt...

Illustration of the hypothesized flows of information between perception, memory and cognitive control in a conceptual model of working memory. Stimuli attributes are processed to varying degrees of abstraction and parts of these representations can be loaded into working memory under the guidance of cognitive control. Familiar stimuli such as the letter B activate visually abstract representations while less familiar stimuli are limited to sensory representations. Information can be shifted both up and down levels of the perceptual hierarchy to build either more or less abstract representations of either perceived or imagined stimuli. Working memories can be shifted into or out of the hierarchy as needed.

We recently published a theoretical review about how compositional and generative mechanisms in working memory provide a flexible engine for creative perception and imagery.

Pre-print:
osf.io/preprints/ps...

Paper: www.sciencedirect.com/science/arti...

A dynamic spatiotemporal normalization model captures perceptual and neural effects of spatial and temporal context The effects of spatial and temporal context on sensory systems have mostly been studied independently of each other. This study shows that the modulation of visual perception and neural activity by th...

Happy to share this new paper from the lab led by Angus Chapman, now out in PLoS Biology! It presents an integrated spatiotemporal normalization model for continuous vision. @afchapman.bsky.social

journals.plos.org/plosbiology/...

🚨 new preprint alert! biorxiv.org/content/10.1...

what is the architecture of an individual working memory?

1/n

Great talk Will!

Tracing the neural trajectories of evidence accumulation and motor preparation processes during voluntary decisions Voluntary decisions have previously been described by where they arise in the brain and how actions corresponding to one's choice are prepared. However, the processes by which these internally guided ...

Interested in how we make preference-driven decisions, and how this is implemented in the brain?

We report that neural correlates of evidence accumulation (CPP, Mu/Beta) are also observed during value-based decisions.

www.biorxiv.org/content/10.1...

Led by @laurencf.bsky.social (Lauren Fong)

1/n

What is the representation underlying cognition? Formal models rely on multidimensional scaling of similarity judgments to derive the representation. In this preprint with @mdlbayes.bsky.social, we take an alternative approach; we build Bayesian generative models for three cognitive tasks. /1

How does our brain excel at complex object recognition, yet get fooled by simple illusory contours? What unifying principle governs all Gestalt laws of perceptual organization?

We may have an answer: integration of learned priors through feedback. New paper with @kenmiller.bsky.social! 🧵

Super happy to share my very first first-author paper out in
@sfnjournals.bsky.social! We show content-specific predictions are represented in an alpha rhythm. It’s been a beautiful, inspiring, yet challenging journey.
Huge thanks to everyone, especially @peterkok.bsky.social @jhaarsma.bsky.social

A Systematic Review of Aperiodic Neural Activity in Clinical Investigations This systematic literature review examines aperiodic neural activity in clinical disorders, summarizing current findings and discussion topics. One-hundred seventy-seven reports from across 38 distin...

📜🎉 I'm happy to share that my review of clinical research investigating aperiodic neural activity is now published!

It examines 177 reports of aperiodic activity in clinical disorders summarizing findings, discussion topics, & making some recommendations!

onlinelibrary.wiley.com/doi/10.1111/...