Electroencephalography (EEG) enables the recording and analysis of fast physiological processes in the cerebral cortex, which is currently virtually impossible for the majority of methods of functional brain examination. However, there is a certain stagnation in the EEG technology that requires some improvement in both methodological and technical approaches to EEG. Objective: to analyze the capacities of EEG and its role in current medical diagnostics. The majority of EEG machines have 8 to 32 recording channels and use the 10–20 electrode placement system. This results in loosing a substantial amount of information due to limited registration of some bioelectric activity and prevents using EEG data together with high-resolution neuroimaging. This issue can be addressed by EEG machines with high-density recording and multiple primary electroencephalographic sensors (at least 128), which ensures minimal loss of information at the first stage. However, such systems require an absolutely different approach to the analysis of EEG recordings. Larger amount of information (compared to conventional EEG) necessitates the implementation of various mathematical methods to analyze the recorded signals, as well as more extensive use of techniques for combining this data with findings of other diagnostic methods, primarily magnetic resonance imaging and functional magnetic resonance imaging. This will open new horizons for the investigation of bioelectric activity of the human brain.