• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

关于格兰杰因果连接性估计器的统计性能

On the statistical performance of Granger-causal connectivity estimators.

作者信息

Sameshima Koichi, Takahashi Daniel Y, Baccalá Luiz A

机构信息

Radiology & Oncology Department, Faculdade de Medicina, University of São Paulo, São Paulo, SP, 01246-903, Brazil.

Psychology Department, Neuroscience Institute, Princeton University, Princeton, NJ, USA.

出版信息

Brain Inform. 2015 Jun;2(2):119-133. doi: 10.1007/s40708-015-0015-1. Epub 2015 Apr 22.

DOI:10.1007/s40708-015-0015-1
PMID:27747486
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4883150/
Abstract

In this article, we extend the statistical detection performance evaluation of linear connectivity from Sameshima et al. (in: Slezak et al. (eds.) Lecture Notes in Computer Science, 2014) via brand new Monte Carlo simulations of three widely used toy models under different data record lengths for a classic time domain multivariate Granger causality test, information partial directed coherence, information directed transfer function, and include conditional multivariate Granger causality whose behaviour was found to be anomalous.

摘要

在本文中,我们通过对三个广泛使用的玩具模型进行全新的蒙特卡罗模拟,扩展了Sameshima等人(见:Slezak等人(编)《计算机科学讲义》,2014年)对线性连通性的统计检测性能评估。这些模拟针对经典时域多变量格兰杰因果检验、信息偏直接相干性、信息直接传递函数,在不同数据记录长度下进行,并且包括条件多变量格兰杰因果关系,其行为被发现是异常的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/463b2ac36953/40708_2015_15_Fig20_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/5a4ee85014be/40708_2015_15_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/6288f69c11b1/40708_2015_15_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/d49a8200da90/40708_2015_15_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/ad03b6c2f1aa/40708_2015_15_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/3344dafeb2cb/40708_2015_15_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/cc3926fab31c/40708_2015_15_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/cdc53d1b2cd3/40708_2015_15_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/54468af0a33e/40708_2015_15_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/7177e9d2e750/40708_2015_15_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/8919d7a9fc05/40708_2015_15_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/e9cf24022bfd/40708_2015_15_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/ddb98da74f5d/40708_2015_15_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/ca2bef65729f/40708_2015_15_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/d62a41719d4a/40708_2015_15_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/1a126fe847ab/40708_2015_15_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/721a42873070/40708_2015_15_Fig16_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/29428e638225/40708_2015_15_Fig17_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/8bb1cc3ff799/40708_2015_15_Fig18_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/0f044bec9dd5/40708_2015_15_Fig19_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/463b2ac36953/40708_2015_15_Fig20_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/5a4ee85014be/40708_2015_15_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/6288f69c11b1/40708_2015_15_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/d49a8200da90/40708_2015_15_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/ad03b6c2f1aa/40708_2015_15_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/3344dafeb2cb/40708_2015_15_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/cc3926fab31c/40708_2015_15_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/cdc53d1b2cd3/40708_2015_15_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/54468af0a33e/40708_2015_15_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/7177e9d2e750/40708_2015_15_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/8919d7a9fc05/40708_2015_15_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/e9cf24022bfd/40708_2015_15_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/ddb98da74f5d/40708_2015_15_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/ca2bef65729f/40708_2015_15_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/d62a41719d4a/40708_2015_15_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/1a126fe847ab/40708_2015_15_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/721a42873070/40708_2015_15_Fig16_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/29428e638225/40708_2015_15_Fig17_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/8bb1cc3ff799/40708_2015_15_Fig18_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/0f044bec9dd5/40708_2015_15_Fig19_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b894/4883150/463b2ac36953/40708_2015_15_Fig20_HTML.jpg

相似文献

1
On the statistical performance of Granger-causal connectivity estimators.关于格兰杰因果连接性估计器的统计性能
Brain Inform. 2015 Jun;2(2):119-133. doi: 10.1007/s40708-015-0015-1. Epub 2015 Apr 22.
2
On the spectral formulation of Granger causality.关于格兰杰因果关系的频谱公式。
Biol Cybern. 2011 Dec;105(5-6):331-47. doi: 10.1007/s00422-011-0469-z. Epub 2012 Jan 17.
3
Frequency Domain Repercussions of Instantaneous Granger Causality.瞬时格兰杰因果关系的频域影响
Entropy (Basel). 2021 Aug 12;23(8):1037. doi: 10.3390/e23081037.
4
Evaluation of Directed Causality Measures and Lag Estimations in Multivariate Time-Series.多元时间序列中直接因果关系度量和滞后估计的评估
Front Syst Neurosci. 2021 Oct 22;15:620338. doi: 10.3389/fnsys.2021.620338. eCollection 2021.
5
A copula approach to assessing Granger causality.一种用于评估格兰杰因果关系的Copula方法。
Neuroimage. 2014 Oct 15;100:125-34. doi: 10.1016/j.neuroimage.2014.06.013. Epub 2014 Jun 17.
6
Time, frequency, and time-varying Granger-causality measures in neuroscience.时间、频率及时变格兰杰因果关系度量在神经科学中的应用
Stat Med. 2018 May 20;37(11):1910-1931. doi: 10.1002/sim.7621. Epub 2018 Mar 15.
7
Temporal Information of Directed Causal Connectivity in Multi-Trial ERP Data using Partial Granger Causality.使用部分格兰杰因果关系分析多试验ERP数据中定向因果连接的时间信息
Neuroinformatics. 2016 Jan;14(1):99-120. doi: 10.1007/s12021-015-9281-6.
8
Granger causality for state-space models.状态空间模型的格兰杰因果关系。
Phys Rev E Stat Nonlin Soft Matter Phys. 2015 Apr;91(4):040101. doi: 10.1103/PhysRevE.91.040101. Epub 2015 Apr 23.
9
Nonlinear effective connectivity measure based on adaptive Neuro Fuzzy Inference System and Granger Causality.基于自适应神经模糊推理系统和格兰杰因果关系的非线性有效连接度量。
Neuroimage. 2018 Nov 1;181:382-394. doi: 10.1016/j.neuroimage.2018.07.024. Epub 2018 Jul 19.
10
Does partial Granger causality really eliminate the influence of exogenous inputs and latent variables?部分格兰杰因果关系真的能消除外生输入和潜在变量的影响吗?
J Neurosci Methods. 2012 Apr 30;206(1):73-7. doi: 10.1016/j.jneumeth.2012.01.010. Epub 2012 Feb 11.

引用本文的文献

1
Hippocampus-retrosplenial cortex interaction is increased during phasic REM and contributes to memory consolidation.海马-后扣带回皮层的相互作用在 REM 相位增加,并有助于记忆巩固。
Sci Rep. 2021 Jun 22;11(1):13078. doi: 10.1038/s41598-021-91659-5.
2
SEED-G: Simulated EEG Data Generator for Testing Connectivity Algorithms.SEED-G:用于测试连通性算法的模拟 EEG 数据生成器。
Sensors (Basel). 2021 May 23;21(11):3632. doi: 10.3390/s21113632.
3
Multiple-Brain Connectivity During Third Party Punishment: an EEG Hyperscanning Study.第三方惩罚过程中的大脑多连通性:一项 EEG 超扫描研究。

本文引用的文献

1
The MVGC multivariate Granger causality toolbox: a new approach to Granger-causal inference.MVGC 多元 Granger 因果关系工具箱:Granger 因果推断的新方法。
J Neurosci Methods. 2014 Feb 15;223:50-68. doi: 10.1016/j.jneumeth.2013.10.018. Epub 2013 Nov 5.
2
Unified asymptotic theory for all partial directed coherence forms.所有偏定向相干形式的一致渐近理论。
Philos Trans A Math Phys Eng Sci. 2013 Jul 15;371(1997):20120158. doi: 10.1098/rsta.2012.0158. Print 2013 Aug 28.
3
Comparative performance evaluation of data-driven causality measures applied to brain networks.
Sci Rep. 2018 May 1;8(1):6822. doi: 10.1038/s41598-018-24416-w.
4
A Time-Varying Connectivity Analysis from Distributed EEG Sources: A Simulation Study.来自分布式脑电图源的时变连通性分析:一项模拟研究。
Brain Topogr. 2018 Sep;31(5):721-737. doi: 10.1007/s10548-018-0621-3. Epub 2018 Jan 27.
基于数据驱动的因果度量方法在脑网络中的比较性能评估。
J Neurosci Methods. 2013 May 15;215(2):170-89. doi: 10.1016/j.jneumeth.2013.02.021. Epub 2013 Mar 26.
4
A critical assessment of connectivity measures for EEG data: a simulation study.对 EEG 数据连通性测量的批判性评估:一项模拟研究。
Neuroimage. 2013 Jan 1;64:120-33. doi: 10.1016/j.neuroimage.2012.09.036. Epub 2012 Sep 21.
5
A comparison of multivariate causality based measures of effective connectivity.基于多元因果关系的有效连接度测度的比较。
Comput Biol Med. 2011 Dec;41(12):1132-41. doi: 10.1016/j.compbiomed.2011.06.007. Epub 2011 Jul 13.
6
Reliability of multivariate causality measures for neural data.多变量因果度量在神经数据中的可靠性。
J Neurosci Methods. 2011 Jun 15;198(2):344-58. doi: 10.1016/j.jneumeth.2011.04.005. Epub 2011 Apr 12.
7
Information theoretic interpretation of frequency domain connectivity measures.频域连通性测度的信息论解释
Biol Cybern. 2010 Dec;103(6):463-9. doi: 10.1007/s00422-010-0410-x. Epub 2010 Dec 14.
8
Uncovering interactions in the frequency domain.揭示频域中的相互作用。
PLoS Comput Biol. 2008 May 30;4(5):e1000087. doi: 10.1371/journal.pcbi.1000087.
9
Comparison of different cortical connectivity estimators for high-resolution EEG recordings.高分辨率脑电图记录中不同皮质连接性估计器的比较
Hum Brain Mapp. 2007 Feb;28(2):143-57. doi: 10.1002/hbm.20263.
10
Overcoming the limitations of correlation analysis for many simultaneously processed neural structures.克服对许多同时处理的神经结构进行相关性分析的局限性。
Prog Brain Res. 2001;130:33-47. doi: 10.1016/s0079-6123(01)30004-3.