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Astrocytes and the Biological Neural Networks

Astrocytes and the Biological Neural Networks

Eduardo D. Martin, Alfonso Araque
Copyright: © 2006 |Pages: 25
ISBN13: 9781591409021|ISBN10: 1591409020|ISBN13 Softcover: 9781591409038|EISBN13: 9781591409045
DOI: 10.4018/978-1-59140-902-1.ch002
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MLA

Martin, Eduardo D., and Alfonso Araque. "Astrocytes and the Biological Neural Networks." Artificial Neural Networks in Real-Life Applications, edited by Juan R. Rabuñal and Julian Dorado, IGI Global, 2006, pp. 22-46. https://doi.org/10.4018/978-1-59140-902-1.ch002

APA

Martin, E. D. & Araque, A. (2006). Astrocytes and the Biological Neural Networks. In J. Rabuñal & J. Dorado (Eds.), Artificial Neural Networks in Real-Life Applications (pp. 22-46). IGI Global. https://doi.org/10.4018/978-1-59140-902-1.ch002

Chicago

Martin, Eduardo D., and Alfonso Araque. "Astrocytes and the Biological Neural Networks." In Artificial Neural Networks in Real-Life Applications, edited by Juan R. Rabuñal and Julian Dorado, 22-46. Hershey, PA: IGI Global, 2006. https://doi.org/10.4018/978-1-59140-902-1.ch002

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Abstract

Artificial neural networks are a neurobiologically inspired paradigm that emulates the functioning of the brain. They are based on neuronal function, because neurons are recognized as the cellular elements responsible for the brain information processing. However, recent studies have demonstrated that astrocytes can signal to other astrocytes and can communicate reciprocally with neurons, which suggests a more active role of astrocytes in the nervous system physiology and fundamental brain functions. This novel vision of the glial role on brain function calls for a reexamination of our current vision of artificial neural networks, which should be expanded to consider artificial neuroglial networks. The neuroglial network concept has not been yet applied to the computational and artificial intelligent sciences. However, the implementation of artificial neuroglial networks by incorporating glial cells as part of artificial neural networks may be as fruitful and successful for artificial networks as they have been for biological networks.

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