DTBIA: An Immersive Visual Analytics System for Brain-Inspired Research

被引：0

作者：

Yao, Jun-Hsiang ^{[1
]}

Li, Mingzheng ^{[1
]}

Liu, Jiayi ^{[1
]}

Li, Yuxiao ^{[2
]}

Feng, Jielin ^{[1
]}

Han, Jun ^{[3
,4
]}

Zheng, Qibao ^{[5
]}

Feng, Jianfeng ^{[5
]}

Chen, Siming ^{[1
]}

机构：

[1] Fudan Univ, Sch Data Sci, Shanghai 200437, Peoples R China

[2] Ohio State Univ, Columbus, OH 43210 USA

[3] Hong Kong Univ Sci & Technol, Clear Water Bay, Hong Kong, Peoples R China

[4] CORE, Clear Water Bay, Hong Kong, Peoples R China

[5] Fudan Univ, Sci & Technol Brain Inspired Intelligence, Shanghai 200437, Peoples R China

来源：

IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS | 2025年 / 31卷 / 06期

关键词：

Data visualization; Spatiotemporal phenomena; Three-dimensional displays; Brain modeling; Artificial intelligence; Neuroscience; Computational modeling; Diffusion tensor imaging; Visual analytics; Solid modeling; Digital twin brain; visual analytics; virtual reality; immersive analytics; VISUALIZATION; CONTEXT;

D O I：

10.1109/TVCG.2025.3567135

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

The Digital Twin Brain (DTB) is an advanced artificial intelligence framework that integrates spiking neurons to simulate complex cognitive functions and collaborative behaviors. For domain experts, visualizing the DTB's simulation outcomes is essential to understanding complex cognitive activities. However, this task poses significant challenges due to DTB data's inherent characteristics, including its high-dimensionality, temporal dynamics, and spatial complexity. To address these challenges, we developed DTBIA, an Immersive Visual Analytics System for Brain-Inspired Research. In collaboration with domain experts, we identified key requirements for effectively visualizing spatiotemporal and topological patterns at multiple levels of detail. DTBIA incorporates a hierarchical workflow - ranging from brain regions to voxels and slice sections - along with immersive navigation and a 3D edge bundling algorithm to enhance clarity and provide deeper insights into both functional (BOLD) and structural (DTI) brain data. The utility and effectiveness of DTBIA are validated through two case studies involving with brain research experts. The results underscore the system's role in enhancing the comprehension of complex neural behaviors and interactions.

引用

页码：3796 / 3808

页数：13

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