Modelling Absence Epilepsy seizure data in the NeuCube evolving spiking neural network architecture

Elisa Capecci, Josafath I. Espinosa-Ramos, Nadia Mammone, Nikola Kasabov, Jonas Duun-Henriksen, Troels Wesenberg Kjaer, Maurizio Campolo, Fabio La Foresta, Francesco C. Morabito

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Epilepsy is the most diffuse brain disorder that can affect people's lives even on its early stage. In this paper, we used for the first time the spiking neural networks (SNN) framework called NeuCube for the analysis of electroencephalography (EEG) data recorded from a person affected by Absence Epileptic (AE), using permutation entropy (PE) features. Our results demonstrated that the methodology constitutes a valuable tool for the analysis and understanding of functional changes in the brain in term of its spiking activity and connectivity. Future applications of the model aim at personalised modelling of epileptic data for the analysis and the event prediction.

Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781479919604, 9781479919604, 9781479919604, 9781479919604
Publication statusPublished - Sep 28 2015
EventInternational Joint Conference on Neural Networks, IJCNN 2015 - Killarney, Ireland
Duration: Jul 12 2015Jul 17 2015


OtherInternational Joint Conference on Neural Networks, IJCNN 2015


  • Childhood Absence Seizures
  • EEG
  • Epilepsy
  • NeuCube
  • Spiking Neural Networks

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence


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