Granger Causality: Basic Theory and Application to Neuroscience

By Mingzhou Ding, Yonghong Chen, Steven L. Bressler. 2006

705 citations recorded by the source corpus.

Multi-electrode neurophysiological recordings produce massive quantities of data. Multivariate time series analysis provides the basic framework for analyzing the patterns of neural interactions in these data. It has long been recognized that neural interactions are directional. Being able to assess the directionality of neuronal interactions is thus a highly desired capability for understanding the cooperative nature of neural computation. Research over the last few years has shown that Granger causality is a key technique to furnish this capability. The main goal of this article is to provide an expository introduction to the concept of Granger causality. Mathematical frameworks for both bivariate Granger causality and conditional Granger causality are developed in detail with particular emphasis on their spectral representations. The technique is demonstrated in numerical examples where the exact answers of causal influences are known. It is then applied to analyze multichannel local field potentials recorded from monkeys performing a visuomotor task. Our results are shown to be physiologically interpretable and yield new insights into the dynamical organization of large-scale oscillatory cortical networks.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/1d09f0c9ddb40b173d5d11703b34e093e3acc24f

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In Cognitive Neuroscience

Citations in the corpus

Analyzing information flow in brain networks with nonparametric Granger causality (2008, methodology): “These graphs are identical to the ones obtained by the parametric techniques reported in (Ding et al., 2006).”
Neurophysiological and Computational Principles of Cortical Rhythms in Cognition (2010, methodology): “Analysis methods have been developed to interrogate the directionality of the flow of signals between two or multiple recorded areas, such as the Granger causality analysis (93, 118, 244, 371, 381, 560) and its frequency-domain representation (38, 244).”
CZECH TECHNICAL UNIVERSITY IN PRAGUE (2005, methodology): “Both problems with indirect connections were solved via multivariate extension, referred to as Conditional Granger causality (CGC) (Ding et al., 2006).”
Analysis of sampling artifacts on the Granger causality analysis for topology extraction of neuronal dynamics (2014, background): “The covariances of residuals possess the following spectral representations [see (Geweke, 1982; Ding et al., 2006) for details]:”
Causality : Objectives and Assessment (2010, background): “, 2000; Kononenko, 2009), epidemiology (Aickin, 2002), climatology (Chu and Glymour, 2008), social and economic sciences (Kaplan, 2000; Demiralp and Hoover, 2003; Moneta, 2005), marketing (CFMDCY, 2006), neuroscience (Ding et al., 2006; Neves et al., 2008), psychology, law enforcement and crime prev”
Stock closing price prediction based on sentiment analysis and LSTM (2019, background): “(8) can guide the stock closing price prediction, this paper conducts a Granger causality test [41] on the causal relationship between the sentiment index BI and the closing price.”
A Tutorial Review of Functional Connectivity Analysis Methods and Their Interpretational Pitfalls (2016, methodology): “Although excellent introductory texts exist that explain the concept of frequency domain Granger causality and their application to neuroscience data (Ding et al., 2006), we briefly review the essential concepts in some detail in the Appendix (Supplementary Material).”
Complex network approaches to nonlinear time series analysis (2019, background): “We do not expand the corresponding discussion here, but refer the interested readers to several review papers on this topic [23,38,39].”
Wiener-Granger Causality: A well established methodology (2011, neutral): “Nonetheless, because the coherence is directly related to the total interdependence (Ding et al., 2006), and the total interdependence is the sum of three measures (the two directional WGCs and the ‘instantaneous feedback’ WGC), coherence peaks are expected to have corresponding peaks in one or…”