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 might construct 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.

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 PDF:

final_PDF_camera_ready_efficient_bounds.pdf

---------------------------------------------------------------------------------------------------------------------------------------------------------------

Efficient coding in biophysically realistic excitatory-inhibitory spiking networks

Authors: Veronika Koren, Simone Blanco Malerba, Tilo Schwalger, Stefano Panzeri

to eLife paper | YouTube link to presentation at SNUFA conference | 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

A: Shema od two recurrently connected spiking networks to capture thalamus and primary somatosensory cortex (S1). S1 network has two types of inhibitory neurons, parvalbumin-positive (PV) and somatostatin-positive (SST). B: The model reproduces non-linear effects of the knock-out of slowly adapting and rapidly adapting low-threshold mechanoreceptors (SA-LTMRs and RA-LTMRs) in the primary somatosensory cortex. C: Weak perturbation on the level of receptor neurons is amplified in the thalamus and in S1.

COSYNE 2025 Abstract, Poster and Video | Biorxiv pre-print | YouTube link to the presentation at SNUFA conference

COSYNE25_poster_download_as_PDF.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

to Biorxiv | READ MORE

Computational methods to study information processing in neural circuits (review)

Authors: Veronika Koren, Giulio Bondanelli, Stefano Panzeri

to the paper in CSBJ | READ MORE

Biologically plausible solutions for spiking networks with efficient coding

Authors: Veronika Koren, Stefano Panzeri

to NeurIPS paper | READ MORE

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

Author: Veronika Koren

to STAR Protocols | READ MORE

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

Computational Account of Spontaneous Activity as a Signature of Predictive Coding

Authors: Veronika Koren, Sophie Deneve

to paper in PLOS Comp Bio | READ MORE