Abstract
AbstractElectroencephalography (EEG) coherence networks represent functional brain connectivity, and are constructed by calculating the coherence between pairs of electrode signals as a function of frequency. Visualization of such networks can provide insight into unexpected patterns of cognitive processing and help neuroscientists to understand brain mechanisms. However, visualizing dynamic EEG coherence networks is a challenge for the analysis of brain connectivity, especially when the spatial structure of the network needs to be taken into account. In this paper, we present a design and implementation of a visualization framework for such dynamic networks. First, requirements for supporting typical tasks in the context of dynamic functional connectivity network analysis were collected from neuroscience researchers. In our design, we consider groups of network nodes and their corresponding spatial location for visualizing the evolution of the dynamic coherence network. We introduce an augmented timeline‐based representation to provide an overview of the evolution of functional units (FUs) and their spatial location over time. This representation can help the viewer to identify relations between functional connectivity and brain regions, as well as to identify persistent or transient functional connectivity patterns across the whole time window. In addition, we introduce the time‐annotated FU map representation to facilitate comparison of the behaviour of nodes between consecutive FU maps. A colour coding is designed that helps to distinguish distinct dynamic FUs. Our implementation also supports interactive exploration. The usefulness of our visualization design was evaluated by an informal user study. The feedback we received shows that our design supports exploratory analysis tasks well. The method can serve as a first step before a complete analysis of dynamic EEG coherence networks.
Highlights
A functional brain network is a graph representation of brain organization, in which the nodes usually represent signals recorded from spatially distinct brain regions and edges represent significant statistical correlations between pairs of signals
Properties of brain connectivity networks that neuroscientists are interested in include the significant connections, as usually expressed in connectivity values above a threshold between brain activities recorded at distinct brain locations, the relation between functional connectivity and brain spatial structures, and how these relations change over time
Regarding the change in brain connectivity over time, one participant said that she can find the change in functional units (FUs) over time from the transition of lines in the timeline representation and she can analyse brain connectivity at a specific time step (Tasks 2 and 4)
Summary
A functional brain network is a graph representation of brain organization, in which the nodes usually represent signals recorded from spatially distinct brain regions and edges represent significant statistical correlations between pairs of signals. A sub-group is defined as an intermediate entity between the entire network and individual nodes, such as a community or module which is composed of a set of densely connected nodes (Ahn et al [APS14]). Data-driven visualization of functional brain networks plays an important role as a pre-processing step in the exploration of brain connectivity, where no a priori assumptions or hypotheses about brain activity in specific regions are made. This type of visualization can provide insight into unexpected patterns of brain function and help neuroscientists to understand how the brain works.
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