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Electronics and Telecommunications Research Institute (한국전자통신연구원)
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Neural source localization using particle filter with optimal proportional set resampling

  • Veeramalla, Santhosh Kumar (Department of Electronics and Communication Engineering, National Institute of Technology) ;
  • Talari, V.K. Hanumantha Rao (Department of Electronics and Communication Engineering, National Institute of Technology)
  • Received : 2019.01.21
  • Accepted : 2019.11.07
  • Published : 2020.12.14
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Abstract

To recover the neural activity from Magnetoencephalography (MEG) and Electroencephalography (EEG) measurements, we need to solve the inverse problem by utilizing the relation between dipole sources and the data generated by dipolar sources. In this study, we propose a new approach based on the implementation of a particle filter (PF) that uses minimum sampling variance resampling methodology to track the neural dipole sources of cerebral activity. We use this approach for the EEG data and demonstrate that it can naturally estimate the sources more precisely than the traditional systematic resampling scheme in PFs.

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References

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