Publication

Abstract : Mining dynamic and non-trivial patterns of interactions of functional brain networks has gained significance due to the recent advances in the field of computational neuroscience. Sophisticated data search capabilities, advanced signal processing techniques, statistical methods, complex network and graph mining algorithms to unfold and discover hidden patterns in the functional brain network supported with efficient visualization techniques are essential for making potential inferences of the results obtained. Visualization of change in activity during cognitive function is useful to discover and get insights into the hidden, novel and complex neuronal patterns and trends during the normal and cognitive load conditions from the graph/temporal representation of the functional brain network. This paper explores novel methods to detect and track the dynamics and complexity of the brain function. It also uses a new tool called Functional Brain Network Analysis and Visualization (FBNAV) tool to visualize the outcomes of various computational analyses to enable us to identify and study the changing neuronal patterns during various states of the brain activity using augmented/customisedTopoplots andHeadplots. The change detection algorithm tracks and visualizes the cognitive load induced changes across the scalp regions.These techniques may also be helpful to locate and identify patterns in certain abnormal mental states resulting due to some mental disorders such as stress.