A Graph Theoretic Bridge between fMRI and EEG
The functional organization of the brain is characterized by segregation and integration of information processing. A central paradigm in modern neuroscience is that connections between brain regions are organized in a way such that information processing is near optimal. Graph theory provides powerful mathematical tools for quantitatively investigating the network in general (e.g. social network, biological network, and brain network) and has revealed that the small-world architecture is utilized in a wide variety of network including the brain, providing high efficiency of information transfer. We develop mathematical tools based on the graph theory to understand the human brain network, and will utilize them for future cognitive enhancement systems. For the purpose, we will target on three different but related forms of connectivity, i.e. anatomical connectivity (DTI), functional connectivity (synchronization of neuronal activation, fMRI), and effective connectivity (causal interactions between activated brain areas, EEG/fMRI).
Effective Connectivity and the Mental Workload
Connectivity between brain regions typically presents a balance between the local segregation and global integration of information processing. Such idea stimulates us to investigate the cognitive workload through investigating the connectivity patterns. In our recent studies, electrical recording of brain activities was recorded when subjects were undertaking simple mental arithmetic tasks, a simple psychological task that might happen in our everyday life. When we increase the difficulty level is increasing , different effective connectivity patterns are being revealed, indicating the sensitivity of the connectivity in the classification of cognitive workload.