He graduated at the Eötvös Lorand University (ELTE) in Budapest as Biologist (specialized in neurobiology) in 2005. During his university years, Balázs developed an interest in computational neuroscience and worked as an undergraduate in Péter Érdi’s group, where he started to build models of the septo-hippocampal system. He attended the neuroscience PhD program at the Eötvös Lorand University (ELTE) and received his PhD in Neuroscience in 2010. During his PhD years he was working on computational models of hippocampal place cells and their role in error correction during navigation. He moved to the University of Cambridge in 2011 to learn Bayesian approches to neuronal computations and to work with Máté Lengyel on normative theories of nonlinear dendritic integration. In 2014 he joined the laboratory of Tiago Branco at the MRC LMB where he was developping simplified models of dendritic integration. He returned to Hungary in 2015 as an MTA postdoc with Judit Makara where he is using computational techniques to understand how specific biophysical properties of neurons contribute to the computation performed by the local circuit and, ultimately, to the behavior.
BB Ujfalussy, JK Makara: Impact of functional synapse clusters on neuronal response selectivity. Nature Comm. 11 (1), 1-14, 2020;
L Vágó, BB Ujfalussy: Robust and efficient coding with grid cells. PLoS Computational Biology 14 (1), e1005922, 2018;
BB Ujfalussy, JK Makara, M Lengyel, T Branco: Global and multiplexed dendritic com- putations under in vivo-like conditions. Neuron 100 (3), 579-592. e5, 2018;
BB Ujfalussy, T Branco, JK Makara and M Lengyel: Dendritic nonlinearities are tuned for efficient spike-based computations in cortical circuits. eLife 2015;4:e10056. 2015.