VI.a CON: Cognitive neuroscience

Head of the group
Name: Lenka Lhotská
Phone: +(420) 224 353 933
Email: lenka.lhotska(at)

The CON research group is focused on application of the latest methods of EEG signal processing during analysis of normal and pathological recordings. Modern algorithms allow more precise analysis of brain activity during recording and allow monitoring not only surface activity but also localization of sources in deeper brain structures. Our activity starts from current knowledge of methods for 3D signal reconstruction based on DIPFIT methods. We plan to extend them by advanced methods, as for example SIFT or NFT. Application of these methods represents a competition advantage in comparison to application of standard methods. Thus the results can be published in more prestigious journals and will contribute to cooperation with institutions that do not have these methods at their disposal but are interested in their utilization in joint projects. The outputs will be new and improved algorithms integrated into the system being developed for EEG analysis and also experimental measurement in the area of cognitive process and emotional reaction analysis. Another important topic will be research in cognitive modelling of spatial perception at human and experimental animals. This task will be solved jointly with collaborating institutes of the Academy of Sciences and neurological clinics. Combination of long-term monitoring and signal processing (our own methodology imitating work of a neurologist during visual EEG evaluation) together with advanced methods of detailed EEG analysis for detection of short graphoelements, including spatio-temporal analysis will bring new information about brain activity. The aim of proposed work is extension of the methodology and theory of long-term and detailed analysis of EEG signal. There will be developed methods of computer-aided analysis of human brain functioning and acquired data for improvement of diagnosis and therapy of brain activity disorders. The methods will be based on automatized processing and evaluation of EEG recordings. Based on our previous pilot studies we intend to research possibilities of application of modern methods of spatio-temporal signal analysis and further non-traditional new methods, including cordance for analysis of perfusion in the brain and artificial intelligence, adaptive algorithms and neural networks for automatic extraction of significant information from long-term EEG recordings. Acquired data will contribute to improvement of diagnosis and therapy of brain activity disorders.

The above described topics are significant both for diagnostics of neurological and neurodegenerative disorders, and for evaluation of therapy efficiency.

Responsible: Lenka Lhotská