The brain is one of the most important organs of the human body, yet it remains poorly understood. The anatomical connections between different brain regions facilitate the transmission of electrical signals across the brain, forming the basis of higher functionalities such as speech, vision, comprehension, and sensory perception. During brain tumor surgery, it is critical to preserve vital connections within the brain while resecting as much of the tumor as possible. Therefore, accurately locating and mapping functional tracts within the brain is crucial for optimal patient outcomes. This thesis focuses on the exploration and application of electrocorticography (ECoG) and Cortico-Cortical Evoked Potentials (CCEP) to enhance our understanding of brain connectivity to ultimately aid in the improvement of tumor resection.

The Background chapter provides all necessary information on the electrophysiological brain, intraoperative neuromonitoring, ECoG, and CCEP. By explaining the fundamental concepts and technological aspects, the chapter sets the stage for understanding how ECoG and CCEP can be utilized to study brain connectivity and improve surgical outcomes.

Chapter 1 establishes the foundation of the research. It uses data from a study on brain transmission speeds involving 74 patients who underwent epilepsy surgery. The chapter explains the composition and structure of the raw data, explaining the processes of data loading and preprocessing, including the construction of epochs and evoked objects from the raw data. The peak detection algorithm, the primary analysis method used to extract amplitude and latency parameters from registered CCEP N1 peaks, is illustrated. These results, a combination of the CCEP connections between electrodes and their corresponding amplitude and latency, form the basis for further chapters.

In Chapter 2, the research primarily addresses the analysis of CCEP responses measured with ECoG across a population. The analysis made a construction of brain connectivity graphs based on Destrieux labels and individual electrodes. The peak detection algorithm identified various CCEP responses and highlighted connections between stimulating and recording electrodes. Notably, connections between temporal and parietal brain regions, and between parietal and frontal regions, were found. These findings corresponded with known white matter tracts, demonstrating the capability of CCEP measurements to reflect connectivity, comparable to standard DTI measurements.

Chapter 3 shifts focus to the visualization of these CCEP responses at an individual patient level for clinical translation. Stimulation of electrodes in the parietal region revealed both local responses and distant connections in the frontal and temporal regions of an exemplary patient. These visualizations provide intuitive insights into the brain's connectivity. An animation illustrating the temporal progression of signal propagation offers a basis for personalized visualizations of connectivity based on CCEP measurements.

In summary, this work contributes to the field of neuroscience by providing robust methods for visualizing and analyzing brain connectivity, ultimately enhancing our ability to translate these findings into practical clinical applications.