I study how networks of neurons in the brain construct, process and transmit signals that are relevant to perception and behaviour. I work with theoretical approaches, computer simulations and analyse experimental data.
I made a Master in cognitive science at Ecole Normale Superieure in Paris and a Ph.D. in computational neuroscience at the Berlin Institute of Technology (Technische Universitaet Berlin), with a fellowship of the Bernstein Center for Computational Neuroscience Berlin. In my Ph.D. thesis titled Coding of low-dimensional variables with spiking neural networks I studied how the brain constructs behaviourally relevant neural signals with spiking networks. After Ph.D., I made a short postdoc at the Institute for Mathematics of the Berlin Institute of Technology. Since 2022, I work as a postdoctoral researcher at the Institute for Neural Information Processing (Panzeri lab) at the University Medical Center Hamburg-Eppendorf.
Efficient coding in biophysically realistic excitatory-inhibitory spiking networks
Authors: Veronika Koren, Simone Blanco Malerba, Tilo Schwalger, Stefano Panzeri
to eLife paper | eLife Interview | YouTube link to presentation at SNUFA conference | READ MORE
Biologically plausible solutions for spiking networks with efficient coding
Authors: Veronika Koren, Stefano Panzeri
Pairwise Synchrony and Correlations Depend on the Structure of the Population Code in Visual Cortex
Authors: Veronika Koren, Ariana R. Andrei, Ming Hu, Valentin Dragoi, Klaus Obermayer
to paper in Cell reports | READ MORE
Computational Account of Spontaneous Activity as a Signature of Predictive Coding
Authors: Veronika Koren, Sophie Deneve
to paper in PLOS Comp Bio | READ MORE
Firing rates and representational error in efficient spiking networks are bounded by design
Authors: Matin Urdu, Gabriel Matías Lorenz, Ching-Peng Huang, Stefano Panzeri, Veronika Koren
Accepted at the International Conference on Artificial Neural Networks 2025 (ICANN 2025)
Disclaimer: This version of the contribution has been accepted for publication, after peer review but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record will be available online at: https://link.springer.com/conference/icann. Use of this Accepted Version is subject to the publisher’s Accepted Manuscript terms of use https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms
Download paper PDF: Urdu_Efficient.pdf
Computational methods to study information processing in neural circuits (review)
Authors: Veronika Koren, Giulio Bondanelli, Stefano Panzeri
Uncovering structured responses of neural populations recorded from macaque monkeys with linear support vector machines (protocol)
Author: Veronika Koren
Reading-out task variables as a low-dimensional reconstruction of neural spike trains in single trials
Authors: Veronika Koren, Ariana R. Andrei, Ming Hu, Valentin Dragoi, Klaus Obermayer
to paper in PLOS ONE | READ MORE
Efficient encoding, transmission and transformation of sensory features in a multilayer spiking neural network
(work in progress)
Authors: Veronika Koren, Alan J. Emanuel, Stefano Panzeri
COSYNE 2025 Abstract, Poster and Video | Biorxiv pre-print | YouTube link to the presentation at SNUFA conference
Download poster: COSYNE25.pdf
Learning from invariants predicts upcoming behavioral choice from spiking activity in monkey V1
(work in progress)
Authors: Veronika Koren, Ariana R. Andrei, Ming Hu, Valentin Dragoi, Klaus Obermeyer