Our researchers explore the brain by means of experimentally recorded data from humans (using EEG) and from the visual cortex of mammals (highly parallel recordings) and also through computer simulations of realistic models of cortical microcircuits. In addition, we are developing new, non-conventional techniques of data analysis.
The first important line of investigation is related to the analysis of neuronal data recorded from real brains. We explore both high-density EEG data recorded in humans, as well as paralell recordings from mammalian visual cortex. The second line of research investigates neurocomputational principles in simulations of large scale networks of spiking neurons. This includes studies ranging from new biologically-inspired computational models of vision to general studies related to the dynamics of large-scale neuronal microcircuits and issues regarding their computational simulation. Finally, we are trying to develop new and non-conventional analysis tools for spike-trains, LFP and EEG signals, as well as for the characterization of the complex, non-linear dynamics of neuronal populations.
Computational Neuroscience Laboratory
The laboratory develops and studies learning rules for spiking neural networks.