Abstract
In the frame of a collaboration between Department of Information technology of the University of Milan and Stem Cells Research Institute of the DIBIT- San Raffaele, Milan, learning methods are under study following known models of the Artificial Neural Networks on human neural stem cells cultured on MEA (Multielectrode Arrays) support. The MEAs are constituted by a glass support where a set of tungsten electrodes are inserted to form a lattice structured by our group following the artificial Hopfield and Kohonen models. In such a way it is possible to electrically stimulate the neurons and to record their reaction, opening the possibility to verify in vivo learning models of the Artificial neural Networks. Neurons are stimulated with digital patterns constituted by bursts of different voltages at the input electrodes, and the electrical output generated by the neurons is analyzed with advanced methods in order to highlight organized answers by the natural neural network. The experiments performed up to now show how neurons react selectively to different patterns and show similar reactions in front of the presentation of identical or similar patterns. These results suggest the possibility of using the learning capabilities of these hybrid networks in different application fields, in particular in bionic applications.
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Pizzi1, R., Fantasia, A., Rossetti, D., Cino, G., Gelain, F., Vescovi, A. (2005). The Hopfield and Kohonen Networks: an in Vivo Test. In: Apolloni, B., Marinaro, M., Tagliaferri, R. (eds) Biological and Artificial Intelligence Environments. Springer, Dordrecht. https://doi.org/10.1007/1-4020-3432-6_24
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DOI: https://doi.org/10.1007/1-4020-3432-6_24
Publisher Name: Springer, Dordrecht
Print ISBN: 978-1-4020-3431-2
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