Understanding how the human brain works is becoming more and more important due to increasing complexity of technology and its multimodal interaction with humans. One of the reasons for this is the fact, that brain is the ultimate frontier of communication between human and its environment (e.g. other humans). Understanding the mechanics of the brain may allow for creating novel channels of human interaction, omitting present “interfaces”, like eyes, ears or hands. Moreover, it may allow for enhancing the way brain works or even allow for its integration with sophisticated computing devices. It is also probable, that unraveling the very basics of human brain’s functioning would make a step towards the creation of Strong Artificial Intelligence. As is well known, human brain is the most complex and dynamic system in known Universe. As such, it is obvious that it must be analyze in rigorous way with advanced statistical methods.
Main fields of research of MK CCSR Cognitive Lab include several topics in Cognitive Science, like the problems of thinking, imagination, memory, creativity, speech and emotions. Important research subjects are: Brain-Computer Interface (BCI), Human-Computer Interaction (HCI), intriguing situations of inter-human interaction and its qualitative impact on brain functioning (like two operators and operator-AI cooperation), multimodal whole-body signal processing and integrated modeling. We are interested in novel applications of MK CSRC Signal Analysis Methods to highly-dimensional human brain data. Neural information poses a great challenge for the science and we attack this problem to investigate in a systematic way the nature of the data. We do this by applying methods of modern theoretical physics designed to solve some of the greatest mysteries of fundamental science and now believe, that these methods can be used in the program of adaptive BCI creation. These include Free Random Variables, Noise Classification and Reduction, Spatial and Temporal Correlations in highly nonlinear, highly-dimensional signals of multimodal nature, in combination of well established methods like Independent Components Analysis, Principal Component Analysis, Data Mining and general Statistical Learning techniques. To support the program we also focus on Artificial Intelligence. In this way we supplement the approach by including Massive Machine Learning Algorithms, like Massive Neural Networks of different types and other Random Nets developed in collaboration with MK NetLab , uncertainty reasoning and statistical learning/inference. For the purposes of modeling and simulation we utilize efficient, parallel, multiprocessor techniques provided by experienced staff and our supercomputer. Finally we are strongly interested in Computational Brain Models that can be used to model its behavior and even allow for emergence of a “Thermodynamics of the Brain”.
In the field of experimental neurology Mark Kac Centre is in strong collaboration with Neuroergonomics group from Jagiellonian University. Within this cooperation we have access to experienced staff and advanced laboratory operating Dense Electroencephalograph (256 channel EGI 300 dEEG) and Electrooculograph (Facelab5), as well as broad range of physiological sensors for measuring wide spectrum of whole-body, multimodal signals, which we believe are all important for the explanation of human brain functioning.
Some of main research environments and test beds are provided by serious games, that we create in collaboration with European Academy of Games. That allows for creation of complex scenarios people face in reality, like critical machine operation (various military as well as civilian simulators), Virtual and Augmented Reality, and others. On the top of that, we are interested in transfer of ideas from fundamental research towards visionary technologies.
- Prof. dr hab. Grzegorz Nalepa (lab leader)
- Dr Piotr Czarnik
- Dr Jacek Grela
- Prof. dr hab. Maciej A. Nowak
- Dr Jeremi Ochab
- Dr hab. Paweł Węgrzyn
- Dr Przemek Witaszczyk