Titre
Transmission of Distributed Deterministic Temporal Information through a Diverging/Converging Three-Layers Neural Network
Type
article de conférence/colloque
Institution
UNIL/CHUV/Unisanté + institutions partenaires
Auteur(s)
Asai, Y.
Auteure/Auteur
Villa, A.E.P.
Auteure/Auteur
Liens vers les personnes
Liens vers les unités
Maison d’édition
Springer Berlin Heidelberg
Titre du livre ou conférence/colloque
Artificial Neural Networks – ICANN 2010
Adresse
Bonn, Germany
ISBN
978-3-642-15818-6
Statut éditorial
Publié
Date de publication
2010
Volume
6352
Première page
145
Dernière page/numéro d’article
154
Peer-reviewed
Oui
Langue
anglais
Résumé
This study investigates the ability of a diverging/converging neural network to transmit and integrate a complex temporally organized activity embedded in afferent spike trains. The temporal information is originally generated by a deterministic nonlinear dynamical system whose parameters determine a chaotic attractor. We present the simulations obtained with a network formed by simple spiking neurons (SSN) and a network formed by a multiple-timescale adaptive threshold neurons (MAT). The assessment of the temporal structure embedded in the spike trains is carried out by sorting the preferred firing sequences detected by the pattern grouping algorithm (PGA). The results suggest that adaptive threshold neurons are much more efficient in maintaining a specific temporal structure distributed across multiple spike trains throughout the layers of a feed-forward network.
PID Serval
serval:BIB_DA1AE8AC9AA7
Date de création
2017-08-04T09:02:31.682Z
Date de création dans IRIS
2025-05-21T05:08:06Z