Dynamics of pruning in simulated large-scale spiking neural networks

Détails

ID Serval
serval:BIB_8D1986E916D8
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Dynamics of pruning in simulated large-scale spiking neural networks
Périodique
Biosystems
Auteur⸱e⸱s
Iglesias J., Eriksson J., Grize F., Tomassini M., Villa A.
ISSN
0303-2647
Statut éditorial
Publié
Date de publication
2005
Peer-reviewed
Oui
Volume
79
Numéro
1-3
Pages
11 - 20
Langue
anglais
Résumé
Massive synaptic pruning following over-growth is a general feature of mammalian brain maturation. This article studies the synaptic pruning that occurs in large networks of simulated spiking neurons in the absence of specific input patterns of activity. The evolution of connections between neurons were governed by an original bioinspired spike-timing-dependent synaptic plasticity (STDP) modification rule which included a slow decay term. The network reached a steady state with a bimodal distribution of the synaptic weights that were either incremented to the maximum value or decremented to the lowest value. After 1 X 10(6) time steps the final number of synapses that remained active was below 10% of the number of initially active synapses independently of network size. The synaptic modification rule did not introduce spurious biases in the geometrical distribution of the remaining active projections. The results show that, under certain conditions, the model is capable of generating spontaneously emergent cell assemblies.
Mots-clé
Locally connected random network, Spike-timing-dependent synaptic plasticity, Spiking neural network, Large-scale simulation
Web of science
Création de la notice
10/10/2008 14:45
Dernière modification de la notice
20/08/2019 14:51
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