Welcome
I am a cognitive neuroscientist in the lab of Christian Ruff at the Zurich Center for Neuroeconomics (ZNE), University of Zurich (UZH).
I want to understand how the brain represents the world, and how the limits of those representations shape what we perceive and decide. Neural populations encode visual space, numbers and value with limited precision, and much of our behaviour, including choices that look irrational, follows from how the brain makes the most of these noisy codes. I measure such codes in individual human brains with ultra-high-field (7T) fMRI and encoding models, relate them to behaviour with computational models, and test their role with causal manipulations such as brain stimulation.
- Risk attitudes start in perception. People whose parietal cortex encodes payoff magnitudes more precisely are less risk averse (Nature Human Behaviour, 2023), disrupting these representations with TMS makes them more risk seeking (preprint, 2025), and noisier payoffs held in memory shift risk attitudes from one choice to the next (Nature Communications, 2026).
- Neural codes adapt to context. Number tuning in parietal cortex shifts and rescales with the range of numbers, and the change in neural precision predicts the change in behavioural precision (Nature Communications, 2026).
- Value has a population code too. Orbitofrontal cortex carries a probabilistic population code for value, and its decoded uncertainty predicts how stable people’s preferences are (preprint, 2026).
- Vision at the scale of columns and layers. At 0.7 mm resolution, fMRI separates feedforward input from attentional feedback across the layers of ocular dominance columns (NeuroImage, 2021), and visual cortex represents space in retinotopic coordinates (eLife, 2026).
Next, I want to find out whether the brain uses one shared architecture for all the scales it builds, for numbers, time, rank and value, and whether the shape of each neural scale explains where our judgements are precise and where they are biased.
All of this runs on two open-source Python packages that I wrote and maintain:
Selected papers
Updates
2026
- Nov Out in Nature Communications, with Arthur Prat-Carrabin and Sam Gershman: numerical receptive fields in parietal cortex shift and rescale to the range of numbers. Explore them in our 3D brain viewers.
- Nov Interactive 3D brain maps of ocular dominance columns from our 2021 NeuroImage paper, on each participant’s own cortical surface.
- Oct New preprint led by Maike Renkert, with Karin Kucian and Sofie Valk: dyscalculia reflects less precise numerical representations in parietal cortex and an altered allocation of this cortex to functional networks.
- Sep Out in Nature Communications: rapid changes in risk attitudes originate from Bayesian inference on noisy parietal magnitude representations.
- Jun New preprint: separable efficient codes shape both perception and value along the pathway from sensation to action.
- Jun Our cognitive-modelling package bauer now supports DDM and race-diffusion likelihoods.
- Apr New preprint: the OFC/vmPFC implements a probabilistic population code for value.
2025
- Nov New preprint on the effect of stress on risky decision-making and numerical representations.
- Sep Material from my workshop on Computational Methods for Neuroeconomics in Soglio, Switzerland.
Explore in 3D
These viewers download a full brain surface, so they may take a minute or more to load.
