Basics and applications of graph theory on EEG and MEG studies

In electroencephalography(EEG) or magnetoencephalography (MEG) studies, the brain can be considered as a network of discrete brain regions in which those regions are mutually interacting over the course of time. One way to study functions of the brain is to look at functions of each spatially distinct brain region. Some researchers are looking at interactions (i.e., connectivity) between a pair of brain regions. Importantly, however, the interactions between pairs of brain regions combine to make a single, large network. To describe the properties of these complex networks, the field of neuroscience has provided “graph theory”. It gives us a new perspective, some findings from which are deeply interesting. For example, networks of healthy human brains have an optimal balance of functional integration and segregation, but the balance reportedly deviates from the optimal in some brain disorders such as depression, dementia, and schizophrenia.

Despite its potential usefulness, some issues of graph theory combined with EEG or MEG have not been well-addressed. For example, evidence about some very basic properties of brain network is relatively scarce. We need more data about the effect of demographic variables (e.g., aging, sex, history of education, and so on) on the brain networks or changes in brain networks between eyes-open/closed conditions. Second, despite some promising evidence in terms of measures of functional integration and segregation (as mentioned above), other properties of brain networks remain to be further investigated. In this context, well-designed studies using newer network measures would be needed. Third, graph theory combined with EEG or MEG is rarely used to investigate the effect of pharmacological or non-pharmacological interventions for psychiatric disorders. Given that those interventions affect neurons in large areas of cortex and thus its effect would be reflected as an alteration on a network level, it would be promising to explore the effect on the network using graph theory.

This research topic includes three themes.

· Very basic knowledge of networks of the brain. For example, studies about the effect of demographic variables on the brain networks, changes in network properties between eye-open and eye-closed conditions, changes induced by photic stimulation, and effect of drowsiness on network properties are of interest.

· Possible application of newer network measures to describe etiology of psychiatric diseases including dementia, mood disorder, schizophrenia, and developmental disorders.

· How graph theory describes changes in network of the brain before and after pharmacological or non-pharmacological interventions.

We welcome manuscripts with a conceptual or methodological focus and papers reporting original data.