As one of the most successful approaches to uncover complex network structures from experimental data, Granger causality has been widely applied to various reverse engineering problems. This chapter first reviews some current developments of Granger causality and then presents the graphical user interface (GUI) to facilitate the application. To make Granger causality more computationally feasib...

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 understandin...

Granger causality analysis of functional magnetic resonance imaging (fMRI) blood-oxygen-level-dependent signal data allows one to infer the direction and magnitude of influence that brain regions exert on one another. We employed a method for upsampling the time resolution of fMRI data that does not require additional interpolation beyond the interpolation that is regularly used for slice-timin...

Over the last decades several techniques have been developed to analyze interactions in multivariate dynamic systems. These analysis techniques have been applied to empirical data recorded in various branches of research, ranging from economics to biomedical sciences. Investigations of interactions between different brain structures are of strong interest in neuroscience. The information contai...

the relationship between economic growth and developments in the ‎financial sector has been one of the most discussed areas in economics ‎for a long time; and the direction of causality – whether financial ‎development causes economic growth or vice versa – is by no means a ‎settled issue.‎this paper investigates the short- run and long-run granger causality ‎between financial development and e...

Detecting changes of spatially high-resolution functional connectivity patterns in the brain is crucial for improving the fundamental understanding of brain function in both health and disease, yet still poses one of the biggest challenges in computational neuroscience. Currently, classical multivariate Granger Causality analyses of directed interactions between single process components in cou...

Establishing the relationship between stock prices and macroeconomic variables is very important for formulating current economic stabilisation policies. This paper investigates the causal relationship between four macroeconomic variables and Dhaka Stock Exchange (DSE) stock prices using cointegration and Granger causality test. The results suggest that cointegration exists between stock prices...

The paper focuses on establishing causation in regression analysis in observational settings. Simple static regression analysis cannot establish causality in the absence of a priori theory on possible causal mechanisms or controlled and randomized experiments. However, two regression based econometric techniques – instrumental variables and Granger causality can be used to test for causality gi...