DTBVis: An interactive visual comparison system for digital twin brain and human brain

计算机科学 可视化 视觉分析 粒度 相似性(几何) 人工智能 大脑活动与冥想 任务(项目管理) 认知 人机交互 机器学习 脑电图 心理学 图像(数学) 神经科学 操作系统 经济 管理
作者
Yuxiao Li,Xinhong Li,Siqi Shen,Longbin Zeng,Richen Liu,Qibao Zheng,Jianfeng Feng,Siming Chen
出处
期刊:Visual Informatics [Elsevier]
卷期号:7 (2): 41-53 被引量:11
标识
DOI:10.1016/j.visinf.2023.02.002
摘要

The digital twin brain (DTB) computing model from brain-inspired computing research is an emerging artificial intelligence technique, which is realized by a computational modeling approach of hardware and software. It can achieve various cognitive abilities and their synergistic mechanisms in a manner similar to the human brain. Given that the task of the DTB is to simulate the functions of the human brain, comparing the similarities and differences between the two is crucial. However, the visualization study of the DTB is still under-researched. Moreover, the complexity of the datasets (multilevel spatiotemporal granularity and different types of comparison tasks) presents new challenges to the analysis and exploration of visualization. Therefore, in this study, we proposed DTBVis, a visual analytics system that supports comparison tasks for the DTB. DTBVis supports iterative explorations from different levels and at different granularities. Combined with automatic similarity recommendation, and high-dimensional exploration, DTBVis can assist experts to understand the similarities and differences between the DTB and the human brain, thus helping them adjust their model and enhance its functionality. The highest level of DTBVis shows an overview of the datasets from the brain, which is used for comparison and exploration of the function and structure of the DTB and the human brain. The medium level is used for the comparison and exploration of a designated brain region. The low level can analyze a designated brain voxel. We worked closely with experts of brain science and held regular seminars with them. Feedback from the experts indicates that our approach helps them conduct comparative studies of the DTB and human brain and make modeling adjustments of the DTB through intuitive visual comparisons and interactive explorations.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
橙子发布了新的文献求助10
1秒前
卢鑫宇发布了新的文献求助10
1秒前
1秒前
1秒前
1秒前
小启应助害怕的不评采纳,获得30
1秒前
乐空思应助害怕的不评采纳,获得30
1秒前
1秒前
积极问晴完成签到,获得积分10
1秒前
猪猪hero应助小赐采纳,获得10
2秒前
十三完成签到,获得积分10
2秒前
2秒前
3秒前
SciGPT应助ljh采纳,获得10
3秒前
老福贵儿应助ljh采纳,获得10
3秒前
mengyao应助ljh采纳,获得10
3秒前
3秒前
科研通AI2S应助ljh采纳,获得10
3秒前
小蘑菇应助ljh采纳,获得10
3秒前
老福贵儿应助ljh采纳,获得10
4秒前
西陆望岳应助ljh采纳,获得10
4秒前
后来应助ljh采纳,获得80
4秒前
老福贵儿应助ljh采纳,获得10
4秒前
侯总应助ljh采纳,获得10
4秒前
儒雅沛蓝完成签到,获得积分10
4秒前
huhu发布了新的文献求助30
4秒前
joleisalau完成签到,获得积分10
5秒前
5秒前
5秒前
6秒前
6秒前
彭凯发布了新的文献求助10
6秒前
Jessie完成签到,获得积分10
7秒前
袁子晴发布了新的文献求助10
7秒前
7秒前
bajuwei发布了新的文献求助10
7秒前
天天快乐应助ZZ采纳,获得10
8秒前
结王三完成签到,获得积分10
9秒前
ding应助优秀不愁采纳,获得10
9秒前
桃桃不加冰完成签到,获得积分10
9秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
人脑智能与人工智能 1000
花の香りの秘密―遺伝子情報から機能性まで 800
King Tyrant 720
Silicon in Organic, Organometallic, and Polymer Chemistry 500
Principles of Plasma Discharges and Materials Processing, 3rd Edition 400
El poder y la palabra: prensa y poder político en las dictaduras : el régimen de Franco ante la prensa y el periodismo 400
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5605746
求助须知:如何正确求助?哪些是违规求助? 4690350
关于积分的说明 14863110
捐赠科研通 4702499
什么是DOI,文献DOI怎么找? 2542243
邀请新用户注册赠送积分活动 1507853
关于科研通互助平台的介绍 1472142