Por favor, use este identificador para citar o enlazar a este item:
http://hdl.handle.net/10261/59605
COMPARTIR / EXPORTAR:
SHARE CORE BASE | |
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE | |
Título: | Artificial astrocytes improve neural network performance |
Autor: | Porto Pazos, Ana Belén CSIC; Veiguela, Noha; Mesejo, Pablo; Navarrete, Marta CSIC ORCID ; Alvarellos, A.; Ibáñez, Óscar; Pazos Sierra, Alejandro; Araque, Alfonso CSIC ORCID | Fecha de publicación: | 2011 | Editor: | Public Library of Science | Citación: | PLoS ONE 6 (2011) | Resumen: | Compelling evidence indicates the existence of bidirectional communication between astrocytes and neurons. Astrocytes, a type of glial cells classically considered to be passive supportive cells, have been recently demonstrated to be actively involved in the processing and regulation of synaptic information, suggesting that brain function arises from the activity of neuron-glia networks. However, the actual impact of astrocytes in neural network function is largely unknown and its application in artificial intelligence remains untested. We have investigated the consequences of including artificial astrocytes, which present the biologically defined properties involved in astrocyte-neuron communication, on artificial neural network performance. Using connectionist systems and evolutionary algorithms, we have compared the performance of artificial neural networks (NN) and artificial neuron-glia networks (NGN) to solve classification problems. We show that the degree of success of NGN is superior to NN. Analysis of performances of NN with different number of neurons or different architectures indicate that the effects of NGN cannot be accounted for an increased number of network elements, but rather they are specifically due to astrocytes. Furthermore, the relative efficacy of NGN vs. NN increases as the complexity of the network increases. These results indicate that artificial astrocytes improve neural network performance, and established the concept of Artificial Neuron-Glia Networks, which represents a novel concept in Artificial Intelligence with implications in computational science as well as in the understanding of brain function. © 2011 Porto-Pazos et al. | URI: | http://hdl.handle.net/10261/59605 | DOI: | 10.1371/journal.pone.0019109 | Identificadores: | doi: 10.1371/journal.pone.0019109 issn: 1932-6203 |
Aparece en las colecciones: | (IC) Artículos |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
---|---|---|---|---|
journal.pone.0019109.pdf | 1,18 MB | Adobe PDF | Visualizar/Abrir |
CORE Recommender
PubMed Central
Citations
20
checked on 14-abr-2024
SCOPUSTM
Citations
62
checked on 13-abr-2024
WEB OF SCIENCETM
Citations
58
checked on 28-feb-2024
Page view(s)
326
checked on 18-abr-2024
Download(s)
250
checked on 18-abr-2024
Google ScholarTM
Check
Altmetric
Altmetric
Artículos relacionados:
NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.