Investigating Causality Between Interacting Brain Areas with Multivariate Autoregressive Models of MEG Sensor Data
In this work we investigate the feasibility of building a MAR model directly on MEG sensor measurements and projecting the model in brain locations where causality is calculated through Partial Directed Coherence (PDC). This method overcomes the problems of model non-robustness and large computation times encountered during causality analysis by existing methods, which first project entire MEG sensor time-series into a large number of brain locations and then the MAR model is built on this large number of time-series.
George Michalareas Jan Mathijs Schoffelen Joachim Gross
Centre for Cognitive Neuroimaging, University of Glasgow, Glasgow, UK
国际会议
The Second International Conference on Cognitive Neurodynamics--2009(第二届国际认知神经动力学会议)
杭州
英文
361-370
2009-11-15（万方平台首次上网日期，不代表论文的发表时间）