title: BrainNetVis: an open-access tool to effectively quantify and visualize brain networks.
abstract: This paper presents BrainNetVis, a tool which serves brain network modelling and visualization, by providing both quantitative and qualitative network measures of brain interconnectivity. It emphasizes the needs that led to the creation of this tool by presenting similar works in the field and by describing how our tool contributes to the existing scenery. It also describes the methods used for the calculation of the graph metrics (global network metrics and vertex metrics), which carry the brain network information. To make the methods clear and understandable, we use an exemplar dataset throughout the paper, on which the calculations and the visualizations are performed. This dataset consists of an alcoholic and a control group of subjects.
authors: Institute of Computer Science, Foundation for Research and Technology-Hellas, FORTH, Heraklion, Greece. echristo@ics.forth.gr
authors: Eleni G
authors: EG
authors: Christodoulou
authors: Vangelis
authors: V
authors: Sakkalis
authors: Vassilis
authors: V
authors: Tsiaras
authors: Ioannis G
authors: IG
authors: Tollis
mesh_terms: D020268:Alcohol-Induced Disorders, Nervous System / Q000175:diagnosis / Q000503:physiopathology; D057229:Alcoholics / Q000523:psychology; D000465:Algorithms; D001931:Brain Mapping / Q000379:methods*; D002540:Cerebral Cortex / Q000033:anatomy & histology / Q000187:drug effects / Q000502:physiology; D003344:Cortical Synchronization / Q000502:physiology; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D015225:Magnetoencephalography / Q000379:methods; D009415:Nerve Net / Q000033:anatomy & histology / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods* / Q000592:standards; D012815:Signal Processing, Computer-Assisted; D012984:Software / Q000592:standards*; D012985:Software Design