Laboratory of Computational Neuroscience, Institute of Scientific Instruments, CAS
Research objectives:
Development of methods for automatic processing:
– Development of automatic and semi-automatic tools for data quality assessment and pre-processing of extensive EEG recordings.
– Development of a multicentric database with prolonged recordings, which should allow for testing on bigger samples across different institutions.
Research and development of analytical methods:
– Methods for broadband EEG signal processing – analysis of interictal epileptic discharges and high frequency oscillations (HFO).
– Connectivity and mutual interactions between anatomical structures of the human brain, analysis of the epileptogenic zone functional connectivity.
Application of developed methods in neurology
– The basic research of motor and cognitive processes.
– Analysis of the epileptogenic zone function, dynamics of epileptic seizures.
– Effectivity of deep brain stimulation (DBS).
– Machine learning models: localization of the epileptogenic zone; prediction of surgical outcome in epilepsy surgery; seizure forecasting and seizure prediction; prediction of the effect of vagal nerve stimulation (non-invasive scalp EEG study).
– Implementation of the developed tools into clinical practise.
– Therapy: aimed estimation, selective micro ablations.