Source reconstruction via the spatiotemporal Kalman filter and LORETA from EEG time series with 32 or fewer electrodes. - Université de Rennes Accéder directement au contenu
Article Dans Une Revue Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference Année : 2017

Source reconstruction via the spatiotemporal Kalman filter and LORETA from EEG time series with 32 or fewer electrodes.

Laith Hamid
  • Fonction : Auteur
Ali Al Farawn
  • Fonction : Auteur
Natia Japaridze
  • Fonction : Auteur
Ulrich Heute
  • Fonction : Auteur
Ulrich Stephani
  • Fonction : Auteur
Andreas Galka
  • Fonction : Auteur

Résumé

The clinical routine of non-invasive electroencephalography (EEG) is usually performed with 8-40 electrodes, especially in long-term monitoring, infants or emergency care. There is a need in clinical and scientific brain imaging to develop inverse solution methods that can reconstruct brain sources from these low-density EEG recordings. In this proof-of-principle paper we investigate the performance of the spatiotemporal Kalman filter (STKF) in EEG source reconstruction with 9-, 19- and 32- electrodes. We used simulated EEG data of epileptic spikes generated from lateral frontal and lateral temporal brain sources using state-of-the-art neuronal population models. For validation of source reconstruction, we compared STKF results to the location of the simulated source and to the results of low-resolution brain electromagnetic tomography (LORETA) standard inverse solution. STKF consistently showed less localization bias compared to LORETA, especially when the number of electrodes was decreased. The results encourage further research into the application of the STKF in source reconstruction of brain activity from low-density EEG recordings.
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Dates et versions

hal-01624619 , version 1 (26-10-2017)

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Laith Hamid, Ali Al Farawn, Isabelle Merlet, Natia Japaridze, Ulrich Heute, et al.. Source reconstruction via the spatiotemporal Kalman filter and LORETA from EEG time series with 32 or fewer electrodes.. Conference proceedings : .. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2017, pp.2218-2222. ⟨10.1109/EMBC.2017.8037295⟩. ⟨hal-01624619⟩
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