Abstract

Interaction between different brain regions has received wide attention recently. Granger causality (GC) is one of the most popular methods to explore causality relationship between different brain regions. In 2011, Hu et. al [1] pointed out shortcomings and/or limitations of GC by using a large of number of illustrative examples and showed that GC is only a causality definition in the sense of Granger and does not reflect real causality at all, and meanwhile proposed a new causality (NC) which is shown to be more reasonable and understandable than GC by those examples. Motor imagery (MI) is an important mental process in cognitive neuroscience and cognitive psychology and has received growing attention for a long time. However, there is few work about causality flow so far during MI based on scalp EEG. In this paper, we use scalp EEG to study causality flow during MI. The scalp EEGs are from 9 subjects in BCI competition IV held in 2008 [2] and provided by Graz University of Technology. We are interested in three regions: Cz (the centre of cerebral cortex), C3 (the left of cerebral cortex) and C4 (the right of cerebral cortex) which are considered to be optimal locations for recognizing MI states in literature. We apply GC and NC to scalp EEG and find that i) there is strong directional connectivity from Cz to C3/C4 during left hand and right hand MI based on GC and NC. ii) During left hand MI, there is directional connectivity from C4 to C3 based on GC and NC. iii) During right hand MI, there is strong directional connectivity from C3 to C4 which is much clearly revealed by NC method than by GC method. iv) Our results suggest that NC method in time and frequency domains is demonstrated to be much better to reveal causal influence between different brain regions than GC method. Thus, we deeply believe that NC method will shed new light on causality analysis in economics and neuroscience.

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