Publications Repository - Gdańsk University of Technology

Electrophysiological activities of the brain are engaged in its various functions and give rise to a wide spectrum of low and high frequency oscillations in the intracranial EEG (iEEG) signals, commonly known as the brain waves. The iEEG spectral activities are distributed across networks of cortical and subcortical areas arranged into hierarchical processing streams. It remains a major challenge to identify these activities in the frequency spectrum, time, and anatomical space, especially during memory and higher-order cognitive functions. Traditionally, this has been done manually by visual inspection of the activities induced in iEEG signals, or semiautomatically by supervised signal detections of computer algorithms. Emerging machine-learning and artificial intelligence tools enable more automated, efficient, objective, and accurate solutions than the traditional expert review. In this chapter, we showcase example applications of features and methods to study cognitive functions and to identify brain areas for therapeutic interventions, including electrical stimulation. These resulted in unexpected findings about the spatiotemporal organization of memory processing and the effects of stimulating the brain. Thus identified iEEG activities offer electrophysiological biomarkers for mapping not only cognitive but also other sensorimotor functions, and are ideally suited for new brain-computer interface approaches to intelligently modulate specific neural processes.

Authors

• dr Michał Kucewicz link open in new tab ,
• Gregory A. Worrell,
• Krishnakant Saboo