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  Stochastic hybrid 3D matrix: learning and adaptation of electrical properties

Erokhin, V., Berzina, T., Gorshkov, K., Camorani, P., Ricci, A., Ricci, L., et al. (2012). Stochastic hybrid 3D matrix: learning and adaptation of electrical properties. Journal of Materials Chemistry, 22(43), 22881-22887. doi:10.1039/C2JM35064E.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-B62C-7 Version Permalink: http://hdl.handle.net/21.11116/0000-0001-8505-3
Genre: Journal Article

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Erokhin, V, Author
Berzina, T, Author
Gorshkov, K, Author
Camorani, P, Author
Ricci, A, Author
Ricci, L, Author
Ruggeri , G, Author
Sigala, R1, 2, Author              
Schüz, A1, 2, Author              
Affiliations:
1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Memristive devices are electronic elements with memory properties. This feature marks them out as possible candidates for mimicking synapse properties. Development of systems capable of performing simple brain operations demands a high level of integration of elements and their 3D organization into networks. Here, we demonstrate the formation and electrical properties of stochastic polymeric matrices. Several features of the network revealed similarities with those of the nervous system. In particular, applying different training protocols, we obtained two kinds of learning comparable to the “baby” and “adult” learning in animals and humans. To mimic “adult” learning, multi-task training was applied simultaneously resulting in the formation of few parallel pathways for a given task, modifiable by successive training. To mimic “baby” learning (imprinting), single task training was applied at one time, resulting in the formation of multiple parallel signal pathways, scarcely influenced by successive training.

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 Dates: 2012-09
 Publication Status: Published in print
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 Rev. Method: -
 Identifiers: DOI: 10.1039/C2JM35064E
BibTex Citekey: ErokhinBGCPRRSS2012
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Title: Journal of Materials Chemistry
Source Genre: Journal
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Pages: - Volume / Issue: 22 (43) Sequence Number: - Start / End Page: 22881 - 22887 Identifier: -