EEG Based Brain Mapping by Using Frequency-Spatio-Temporal Constraints

  • Pablo Andrés Muñoz-GutiérrezEmail author
  • Juan David Martinez-Vargas
  • Sergio Garcia-Vega
  • Eduardo Giraldo
  • German Castellanos-Dominguez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11309)


In this paper an improvement of the dynamic inverse problem solution is proposed by using constraints in the space-time-frequency domain. The method is based on multi-rate filter banks for frequency selection of the EEG signals and a cost function that includes spatial and temporal constraints. As a result, an iterative method which includes Frequency-Spatio-temporal constraints is proposed. The performance of the proposed method is evaluated by using simulated and real EEG signals. It can be concluded that the enhanced IRA-L1 method with the frequency-spatio-temporal stage improves the quality of the brain reconstruction performance in terms of the Wasserstein metric, in comparison with the other methods, for both simulated and real EEG signals.


Dynamic inverse problem Frequency-Spatio-temporal constraints 



This work was carried out under the funding of the Departamento Administrativo Nacional de Ciencia, Tecnología e Innovación (Colciencias). Research project: 111077757982 “Sistema de identificación de fuentes epileptogénicas basado en medidas de conectividad funcional usando registros electroencefalográficos e imágenes de resonancia magnética en pacientes con epilepsia refractaria: apoyo a la cirugía resectiva”.

This work is also part of the research project “Solución del problema inverso dinámico considerando restricciones espacio-temporales no homogéneas aplicado a la reconstrucción de la actividad cerebral” funded by the Universidad Tecnológica de Pereira under the code E6-17-2.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Pablo Andrés Muñoz-Gutiérrez
    • 1
    Email author
  • Juan David Martinez-Vargas
    • 2
  • Sergio Garcia-Vega
    • 4
  • Eduardo Giraldo
    • 3
  • German Castellanos-Dominguez
    • 4
  1. 1.Universidad del QuindíoArmeniaColombia
  2. 2.Instituto Tecnológico MetropolitanoMedellínColombia
  3. 3.Universidad Tecnológica de PereiraPereiraColombia
  4. 4.Signal Processing and Recognition GroupUniversidad Nacional de Colombia, sede ManizalesManizalesColombia

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