Spatial Resolution of EEG Source Reconstruction in Assessing Brain Connectivity Analysis

  • Jorge Ivan Padilla-BuriticáEmail author
  • J. D. Martínez-Vargas
  • A. Suárez-Ruiz
  • J. M. Ferrandez
  • G. Castellanos-Dominguez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10338)


Brain connectivity analysis has emerged as a tool to associate activity generated in diverse brain areas, making possible the integration of functionally specialized brain regions in networks. However, estimation of the areas with relevant activity is well influenced by the applied brain mapping methods. This paper carries out the comparison of three reconstruction principles that differ in the way the prior covariance is adjusted, including its generalization through multiple and sparse spatial priors. To cluster the locations with significant brain activity (regions of interest), we select the most powerful areas, for which the functional connectivity is measured by the coherence and Kullback-Liebler divergence. From the obtained results on simulated and real-world EEG data, both measures show that the mapping method that includes Multiple Sparse Priors allows improving the connectivity accuracy regardless the used measure for all tested values of added noise.


Connectivity Analysis Connectivity Measure Source Covariance Active Dipole Lead Field Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by the research project 11974454838 founded by COLCIENCIAS. J.I. Padilla-Buriticá is founded by Programa nacional de becas de doctorado, convocatoria 647 (2014).


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Jorge Ivan Padilla-Buriticá
    • 1
    • 2
    Email author
  • J. D. Martínez-Vargas
    • 1
  • A. Suárez-Ruiz
    • 1
  • J. M. Ferrandez
    • 2
  • G. Castellanos-Dominguez
    • 1
  1. 1.Universidad Nacional de ColombiaManizalesColombia
  2. 2.Universidad Politécnica de CartagenaCartagenaSpain

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