Estimating coupling strength between multivariate neural series with multivariate permutation conditional mutual information-Reference-Cited by-同舟云学术

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Estimating coupling strength between multivariate neural series with multivariate permutation conditional mutual information

Published:2019-02 Issue: Volume:110 Page:159-169
ISSN:0893-6080
Container-title:Neural Networks
language:en
Short-container-title:Neural Networks

Author:

Wen Dong,Jia Peilei,Hsu Sheng-Hsiou,Zhou Yanhong,Lan Xifa,Cui Dong,Li Guolin,Yin Shimin,Wang Lei

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Natural Science Foundation of Hebei Province

Doctorial Foundation of Yanshan University in China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference50 articles.

1. Characterizing unidirectional couplings between point processes and flows;Andrzejak;EPL (Europhysics Letters),2011

2. White matter vascular lesions are related to parietal-to-frontal coupling of EEG rhythms in mild cognitive impairment;Babiloni;Human Brain Mapping,2008

3. Brain neural synchronization and functional coupling in alzheimer’s disease as revealed by resting state eeg rhythms;Babiloni;International Journal of Psychophysiology,2016

4. The MVGC multivariate Granger causality toolbox: a new approach to Granger-causal inference;Barnett;Journal of Neuroscience Methods,2014

5. Supervised estimation of granger-based causality between time series;Benozzo;Frontiers in Neuroinformatics,2017

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