Keiriz Johnson J G, Zhan Liang, Ajilore Olusola, Leow Alex D, Forbes Angus G
Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA.
Department of Engineering and Technology, University of Wisconsin-Stout Menomonie, WI, USA.
Netw Neurosci. 2018 Sep 1;2(3):344-361. doi: 10.1162/netn_a_00044. eCollection 2018.
We introduce NeuroCave, a novel immersive visualization system that facilitates the visual inspection of structural and functional connectome datasets. The representation of the human connectome as a graph enables neuroscientists to apply network-theoretic approaches in order to explore its complex characteristics. With NeuroCave, brain researchers can interact with the connectome-either in a standard desktop environment or while wearing portable virtual reality headsets (such as Oculus Rift, Samsung Gear, or Google Daydream VR platforms)-in any coordinate system or topological space, as well as cluster brain regions into different modules on-demand. Furthermore, a default side-by-side layout enables simultaneous, synchronized manipulation in 3D, utilizing modern GPU hardware architecture, and facilitates comparison tasks across different subjects or diagnostic groups or longitudinally within the same subject. Visual clutter is mitigated using a state-of-the-art edge bundling technique and through an interactive layout strategy, while modular structure is optimally positioned in 3D exploiting mathematical properties of platonic solids. NeuroCave provides new functionality to support a range of analysis tasks not available in other visualization software platforms.
我们介绍了NeuroCave，这是一种新型沉浸式可视化系统，有助于对结构和功能连接组数据集进行视觉检查。将人类连接组表示为图形，使神经科学家能够应用网络理论方法来探索其复杂特征。借助NeuroCave，大脑研究人员可以在标准桌面环境中，或者在佩戴便携式虚拟现实头显（如Oculus Rift、三星Gear或谷歌Daydream VR平台）时，在任何坐标系或拓扑空间中与连接组进行交互，还能按需将脑区聚类为不同模块。此外，默认的并排布局利用现代GPU硬件架构实现3D同步操作，便于跨不同受试者或诊断组进行比较任务，或在同一受试者内进行纵向比较。使用先进的边捆绑技术和交互式布局策略可减轻视觉混乱，同时利用柏拉图立体的数学特性在3D中优化模块结构的定位。NeuroCave提供了新功能，以支持其他可视化软件平台中无法实现的一系列分析任务。
