Sparse Granger Causality Analysis Model Based on Sensors Correlation for Emotion Recognition Classification in Electroencephalography. [PDF]
Front Comput Neurosci, 2021 In recent years, affective computing based on electroencephalogram (EEG) data has attracted increased attention. As a classic EEG feature extraction model, Granger causality analysis has been widely used in emotion classification models, which construct ...
Chen D, Miao R, Deng Z, Han N, Deng C.
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New Insights into Signed Path Coefficient Granger Causality Analysis. [PDF]
Front Neuroinform, 2016 Granger causality analysis, as a time series analysis technique derived from econometrics, has been applied in an ever-increasing number of publications in the field of neuroscience, including fMRI, EEG/MEG, and fNIRS. The present study mainly focuses on
Zhang J, Li C, Jiang T.
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Multivariate Timing and Granger Causality Analysis of Spontaneous Facial Mimicry in Response to Android Dynamic Facial Expressions. [PDF]
Sensors (Basel)Although evidence exists for android-induced spontaneous facial mimicry, the timing and temporal precedence (Granger causality) of this effect remain uncertain.
Hsu CT +4 more
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Robust unified Granger causality analysis: a normalized maximum likelihood form. [PDF]
Brain Inform, 2021 Unified Granger causality analysis (uGCA) alters conventional two-stage Granger causality analysis into a unified code-length guided framework. We have presented several forms of uGCA methods to investigate causal connectivities, and different forms of ...
Hu Z +5 more
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Description length guided nonlinear unified Granger causality analysis. [PDF]
Netw Neurosci, 2023 Li F, Lin Q, Zhao X, Hu Z.
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A study of problems encountered in Granger causality analysis from a neuroscience perspective. [PDF]
Proc Natl Acad Sci U S A, 2017 Stokes PA, Purdon PL.
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Bibliometric Analysis of Granger Causality Studies
Entropy, 2023 Granger causality provides a framework that uses predictability to identify causation between time series variables. This is important to policymakers for effective policy management and recommendations.
Weng Siew Lam +3 more
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Description Length Guided Unified Granger Causality Analysis
IEEE Access, 2021 In this article, we propose a description length guided unified Granger causality analysis (uGCA) framework for sequential medical imaging. While existing efforts of GCA focused on causal relation design and statistical methods for their improvement, our
Zhenghui Hu +3 more
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Depressed MEG causality analysis based on polynomial kernel Granger causality
AIP Advances, 2023 In this study, we employ the Granger causality of a polynomial kernel to identify the coupling causality of depressed magnetoencephalography (MEG). We collect MEG under positive, neutral, and negative emotional stimuli and focus on the β-band activities.
Jing Qian +7 more
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Heliyon, 2023 This study investigates the nexus between economic growth (GDP), trade openness, remittances, exchange rate, and agricultural output in E7 (Russia, Indonesia, Mexico, China, India, Brazil, and Turkey) economies, covering the data from 1990 to 2020.
Khalid Usman
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