After graduating with a Bachelor degree in psychology from the University of Sofia, Bulgaria, I decided to take a more quantitative turn and did a Masters in Cognitive Neuroscience at Radboud University, the Netherlands. There I wrote a thesis on the topic “Topological Properties of Neural Manifolds”, in which I studied the topology generated by the activity of feature selective neurons in neural networks. Now I am hoping to understand how the brain (at least the mouse one) performs visual computation by combining theory, biophysical modeling and machine learning.
Research interests and hobbies
My main research interests are in neural manifolds, neural coding, machine learning and topological data analysis. As for hobbies, I like to play music, read books and hike.
Large-scale network simulations of mouse visual cortex
My project at UiO involves simulating both biophysical (Billeh et al., Neuron, 2020) and artificial (Perich et al., bioRxiv, 2021) neural network models of mouse visual cortex in order to gain a deeper understanding of the visual system. Besides modelling I will also develop machine learning algorithms with which to improve the aforementioned models by making them reproduce population based measurements like the local field potential (LFP). Finally I will use the improved models as an in-silico study case with which to answer questions about neural representation, manifolds and coding.
- Beshkov, K., & Tiesinga, P. (2021) ‘Geodesic-based distance reveals non-linear topological features in neural activity from mouse visual cortex’, bioRxiv. (Accepted for publication in Biological Cybernetics).