Here we present a scalable method to compute the structure of causal links over large scale dynamical systems that achieves high efficiency in discovering actual functional connections. The method is based on the Granger causality analysis of multivariate linear models, solved by means of a sparse regression approach, and can deal with autoregressive models of more than 10,000 variables.
Cecchi et al. REF presented a scalable method, based on the Granger causality analysis of multivariate linear models, to compute the structure of causal links over large scale dynamical systems that achieves high efficiency in discovering actual functional connections.
Inferring brain dynamics using granger causality on fMRI data
2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro
2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro
Computer Science