Research

I am interested in two main directions:

• The first one is related to analysis and classification of biological signals from voice recognition to analysis of neuronal recordings. The main topics include: the classification of human EEG recording during anesthesia, study of dimensionality of local field potential recorded from the visual cortex of anesthetized cats and the modeling spike trains with realistic statistical properties. Future work will include the analysis of human EEG during visual perception and cognition tasks.
  
• The second direction is related to the analysis of neural networks. In his previous work the artificial neural networks were used as simple classifiers, and recently its interest shifted towards the dynamics of activity in spiking artifficial neural networks. Later I become interested also in structural and topological reorganization of biological networks during learning, as a source of inspiration for new models of learning in artificial spiking neural networks. Currently my focus is on understanding how membrane resonant properties of individual neurons affect the oscillatory dynamics of the networks.

Current projects

To be continued...

Past projects

Robust quantification of neural oscillations