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

Publikation: Bidrag til bog/antologi/rapportKonferencebidragForskningpeer review

Abstrakt

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.

OriginalsprogEngelsk
Titel2015 International Joint Conference on Neural Networks, IJCNN 2015
ForlagInstitute of Electrical and Electronics Engineers Inc.
ISBN (Elektronisk)9781479919604, 9781479919604, 9781479919604, 9781479919604
DOI
StatusUdgivet - 28 sep. 2015
BegivenhedInternational Joint Conference on Neural Networks, IJCNN 2015 - Killarney, Irland
Varighed: 12 jul. 201517 jul. 2015

Publikationsserier

NavnProceedings of the International Joint Conference on Neural Networks
Vol/bind2015-September

Konference

KonferenceInternational Joint Conference on Neural Networks, IJCNN 2015
Land/OmrådeIrland
ByKillarney
Periode12/07/1517/07/15

Fingeraftryk

Udforsk hvilke forskningsemner 'Modelling Absence Epilepsy seizure data in the NeuCube evolving spiking neural network architecture' indeholder.

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