title: Spatio-temporal Granger causality: a new framework.
abstract: That physiological oscillations of various frequencies are present in fMRI signals is the rule, not the exception. Herein, we propose a novel theoretical framework, spatio-temporal Granger causality, which allows us to more reliably and precisely estimate the Granger causality from experimental datasets possessing time-varying properties caused by physiological oscillations. Within this framework, Granger causality is redefined as a global index measuring the directed information flow between two time series with time-varying properties. Both theoretical analyses and numerical examples demonstrate that Granger causality is a monotonically increasing function of the temporal resolution used in the estimation. This is consistent with the general principle of coarse graining, which causes information loss by smoothing out very fine-scale details in time and space. Our results confirm that the Granger causality at the finer spatio-temporal scales considerably outperforms the traditional approach in terms of an improved consistency between two resting-state scans of the same subject. To optimally estimate the Granger causality, the proposed theoretical framework is implemented through a combination of several approaches, such as dividing the optimal time window and estimating the parameters at the fine temporal and spatial scales. Taken together, our approach provides a novel and robust framework for estimating the Granger causality from fMRI, EEG, and other related data.
authors: Department of Management, School of Information Systems and Management, National University of Defense Technology, Hunan 410073, PR China.
authors: Qiang
authors: Q
authors: Luo
authors: Wenlian
authors: W
authors: Lu
authors: Wei
authors: W
authors: Cheng
authors: Pedro A
authors: PA
authors: Valdes-Sosa
authors: Xiaotong
authors: X
authors: Wen
authors: Mingzhou
authors: M
authors: Ding
authors: Jianfeng
authors: J
authors: Feng
mesh_terms: D001683:Biological Clocks / Q000502:physiology*; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005544:Forecasting; D006801:Humans; D008959:Models, Neurological; D015233:Models, Statistical; D009991:Oscillometry / Q000379:methods*
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