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Nedungadi, A.G., Rangarajan, G., Jain, N. and Ding, M. Z. (2009) Analyzing multiple spike trains with nonparametric granger causality. Journal of Computational Neu- roscience, 27(1), 55-64.

has been cited by the following article:

• TITLE: Using granger-geweke causality model to evaluate the effective connectivity of primary motor cortex, supplementary motor area and cerebellum

  AUTHORS: Le Zhang, Guangjin Zhong, Yukun Wu, Mark G. Vangel, Beini Jiang, Jian Kong

  KEYWORDS: Granger-Geweke Causality Model; Time Series; Computational Neuroscience; fMRI; Finger-tapping; Hand Movement; Math Modeling

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.3 No.9, September 29, 2010

  ABSTRACT: Currently, Granger-Geweke causality models have been widely applied to investigate the dynamic direction relationships among brain regions. In a previous study, we have found that the right hand finger-tapping task can produce relatively reliable brain response. As an extension of our previous study, we developed an algorithm based on the classical Granger- Geweke causality model to further investigate the effective connectivity of three brain regions (left primary motor cortex (M1), supplementary motor area (SMA) and right cerebellum) that showed the most robust brain activations. Our computational results not only confirm the strong linear feedback among SMA, M1 and right cerebellum, but also demonstrate that M1 is the hub of these three regions indicated by the anatomy research. Moreover, the model predicts the high intermediate node density existing in the area between SMA and M1, which will stimulate the imaging experimentalists to carry out new experiments to validate this postulation.