Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity

连接体 人类连接体项目 功能磁共振成像 神经科学 静息状态功能磁共振成像 功能连接 心理学 认知 大脑定位 神经网络 鉴定(生物学) 神经影像学 连接组学 计算机科学 人工智能 生物 植物
作者
Emily S. Finn,Xilin Shen,Dustin Scheinost,Monica D. Rosenberg,Jessica S. Huang,Marvin M. Chun,Xenophon Papademetris,R. Todd Constable
出处
期刊:Nature Neuroscience [Nature Portfolio]
卷期号:18 (11): 1664-1671 被引量:2691
标识
DOI:10.1038/nn.4135
摘要

This study shows that every individual has a unique pattern of functional connections between brain regions. This functional connectivity profile acts as a ‘fingerprint’ that can accurately identify the individual from a large group. Furthermore, an individual's connectivity profile can predict his or her level of fluid intelligence. Functional magnetic resonance imaging (fMRI) studies typically collapse data from many subjects, but brain functional organization varies between individuals. Here we establish that this individual variability is both robust and reliable, using data from the Human Connectome Project to demonstrate that functional connectivity profiles act as a 'fingerprint' that can accurately identify subjects from a large group. Identification was successful across scan sessions and even between task and rest conditions, indicating that an individual's connectivity profile is intrinsic, and can be used to distinguish that individual regardless of how the brain is engaged during imaging. Characteristic connectivity patterns were distributed throughout the brain, but the frontoparietal network emerged as most distinctive. Furthermore, we show that connectivity profiles predict levels of fluid intelligence: the same networks that were most discriminating of individuals were also most predictive of cognitive behavior. Results indicate the potential to draw inferences about single subjects on the basis of functional connectivity fMRI.
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
刚刚
小二郎应助早饭吃蛋饼啦采纳,获得10
2秒前
keen完成签到,获得积分10
2秒前
彭于彦祖应助可靠的凝梦采纳,获得30
2秒前
在水一方应助安伊采纳,获得10
3秒前
yyy0820完成签到,获得积分10
3秒前
焚蕊听水榭完成签到,获得积分10
4秒前
执着发布了新的文献求助10
8秒前
Owen应助健忘英姑采纳,获得10
8秒前
年轻的笙完成签到,获得积分10
9秒前
10秒前
10秒前
10秒前
10秒前
长情半邪完成签到 ,获得积分10
13秒前
dada发布了新的文献求助10
14秒前
14秒前
猫仔发布了新的文献求助10
14秒前
欣喜书易完成签到 ,获得积分10
14秒前
15秒前
eleven完成签到 ,获得积分10
15秒前
MSYMC完成签到 ,获得积分20
15秒前
闹闹发布了新的文献求助10
16秒前
Six_seven完成签到,获得积分10
17秒前
17秒前
19秒前
cnspower完成签到,获得积分0
20秒前
20秒前
传奇3应助胡一刀采纳,获得10
21秒前
wjh完成签到,获得积分10
21秒前
陈俐俐发布了新的文献求助50
22秒前
闹闹完成签到,获得积分10
22秒前
可爱的函函应助dada采纳,获得10
23秒前
Lenora发布了新的文献求助10
24秒前
斑驳发布了新的文献求助10
24秒前
十点差一分完成签到,获得积分10
27秒前
今后应助暴躁的海豚采纳,获得10
29秒前
高震博完成签到 ,获得积分10
30秒前
32秒前
34秒前
高分求助中
【重要!!请各位用户详细阅读此贴】科研通的精品贴汇总(请勿应助) 10000
Genomic signature of non-random mating in human complex traits 2000
Semantics for Latin: An Introduction 1099
醤油醸造の最新の技術と研究 1000
Plutonium Handbook 1000
Three plays : drama 1000
Robot-supported joining of reinforcement textiles with one-sided sewing heads 640
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4109825
求助须知:如何正确求助?哪些是违规求助? 3648164
关于积分的说明 11555880
捐赠科研通 3353853
什么是DOI,文献DOI怎么找? 1842450
邀请新用户注册赠送积分活动 908867
科研通“疑难数据库(出版商)”最低求助积分说明 825770