About

I study how the brain represents the world, and how the limits of those representations shape perception and decisions. Visual space, numbers and values are all encoded by noisy populations of tuned neurons, and people perceive and decide by inferring what is out there from these noisy codes. Prior knowledge and noise then produce systematic biases, such as risk aversion, that are usually explained in very different terms.

My approach combines three things:

• Measuring neural codes in individual brains. With ultra-high-field (7T) fMRI and encoding models borrowed from visual neuroscience, I estimate how precisely each person’s cortex represents a quantity, and decode it back out trial by trial.
• Formal models of behaviour. Bayesian observer and sequential-sampling models estimate the same noise and prior from people’s choices and response times.
• Causal tests. Brain stimulation, stress, working-memory load and changes in context manipulate the code, so we can see whether behaviour changes as predicted.

Next, I want to find out whether the brain builds all of its internal scales, for number, probability, time, rank and value, with one shared architecture, and whether the shape of each neural scale predicts where people’s judgements are precise and where they are biased.

2019 – now: Postdoctoral researcher with Prof. Christian C. Ruff, Zurich Center for Neuroeconomics, University of Zurich

I develop the neuroimaging approach and analyses for the lab's work on how perception shapes economic choice, using numerical and value receptive field models at 7T, Bayesian cognitive models and TMS. I came to Zurich with an NWO Rubicon fellowship.

2017 – 2019: Postdoctoral researcher with Dr. Tomas Knapen, Vrije Universiteit Amsterdam and Spinoza Centre

I mapped ocular dominance columns and retinotopy across cortical depth with 0.7 mm functional MRI, in collaboration with the Chinese Academy of Sciences, Beijing.

2013 – 2018: PhD (cum laude) with Prof. Birte U. Forstmann, University of Amsterdam

I studied the subthalamic nucleus, a small subcortical node of the basal ganglia, with 7 Tesla MRI, histology and computational models such as the drift diffusion model. The thesis received the 2018–2019 Dissertation Award of the Dutch Society for Brain and Cognition.

Download thesis

2010 – 2012: Research Master in Artificial Intelligence, University of Amsterdam

Focus on machine learning and computer vision.

Download academic CV

I co-supervise PhD students in the Ruff lab with Christian Ruff, as their day-to-day supervisor for imaging, analysis and modelling.

• Maike F. Renkert, PhD 2026. Numerical representations in dyscalculia and under stress (dyscalculia preprint, first author).
• Saurabh Bedi, PhD 2026. Efficient coding in perception and value (perception-and-value preprint, first author).
• Alina Davydova, ongoing. Perceptual foundations of loss aversion.
• Gaoyang Huang, ongoing. Neural codes for fractions and proportions.
• Earlier, at the University of Amsterdam: Steven Miletić, PhD (co-supervised).

• 2025: Workshop on computational methods for neuroeconomics, Soglio, Switzerland (course material)
• 2023 – 2024: Programming for data analysis, University of Zurich
• 2012 – 2018: Lectures on model-based neuroimaging, machine learning and fMRI, University of Amsterdam

• 2025: Invited plenary talk, Society for Neuroeconomics annual meeting, Boston
• 2019: Dissertation Award, Dutch Society for Brain and Cognition
• Invited talks: VU Amsterdam (2023, 2026), University of Melbourne and University of Newcastle (2024), University of Basel (2022), Chinese Academy of Sciences, Beijing (2018), Radboud University Nijmegen (2017)

Maintainer

• braincoder - Python package to fit and invert encoding models of neural data
• bauer - Python package to fit Bayesian hierarchical cognitive models of choice
• nideconv - Python package to deconvolve (neural) time series
• pymp2rage - Python package to calculate T1 maps and T1UNI for a MP2RAGE sequence

Contributor

• BIDS
• nilearn
• pycortex
• niworkflows
• nipype

• 2023 – 2024: Organiser of the weekly Zurich Center for Neuroeconomics seminar
• 2020 – 2021: Representative of the Rubicon laureates, which helped secure EUR 20M for researchers on short contracts
• Reviewer for Science Advances, PNAS, PLOS Biology, eLife, Cerebral Cortex, Human Brain Mapping and Journal of Cognitive Neuroscience

Gilles de Hollander

University of Zurich

Department of Economics

Blümlisalpstrasse 10, Room BLU-208

8006 Zurich

gilles.de.hollander@gmail.com

ORCID: 0000-0003-1988-5091