Improving spatiotemporal characterization of cognitive processes with data-driven EEG-fMRI analysis

To fully understand the cognitive processes occurring in the human brain, high resolution in both spatial and temporal information is needed. Most neuroimaging approaches, however, only possess high accuracy in one of these two domains. Therefore, the multimodal analysis of brain activity is becoming more and more popular among the research community. One of these approaches concerns the integration of simultaneously acquired electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) data. This combination poses a series of challenges, ranging from recovering data quality to the fusion of two types of data of a completely different nature. In this work, several of these challenges will be addressed, and an overview of different integration approaches is provided.