Экспериментальные методики и алгоритмы обработки электрофизиологических измерений активности мозга в когнитивных парадигмах реального времениExperimental paradigms and data processing algorithms design in real time cognitive neuroimaging

Systems that process electrophysiological measurements of brain activity in real time, in particular, brain-computer interfaces (BCIs), are used in a number of fields for various research and practical purposes. Most often, such systems use non-invasive recording methods, which are safe and available but introduce limitations in signal quality and throughput that bound the complexity of BCIs that can be implemented with this technology. Invasive recording techniques, on the other hand, give access to more informative signal but pose their own risks and limitations related to the required medical procedures. A currently emerging trend in BCI development is using electrocorticogram (ECoG), an invasive method that is considered to be safer than microelectrode implantation and is routinely used in clinical practice. ECoG yields high spatial resolution, low noise levels, near absence of oculographic and myographic artifacts, proximity to the signal sources and possibility to conduct cortical stimulation through the electrodes, all of which are desirable characteristics for implementation of a complex BCI. In our work, firstly, we propose methods utilizing additional information to improve decoding in non-invasive interfaces, and, secondly, develop experimental paradigms and signal processing methods for ECoG, allowing to perform real-time finger movement decoding, passive cortical mapping, and explore the artificial haptic feedback that could be carried out through ECoG stimulation.