How neural are neural networks? A comparison of information processing and storage in artificial and real neural systems

DOI10.1016/0378-3758(92)90093-8zbMath0752.92005OpenAlexW2063375624MaRDI QIDQ1200644

Gregory A. Clark, Robert D. Hawkins, William N. Frost

Publication date: 16 January 1993

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(92)90093-8

zbMATH Keywords

learningartificial neural networksmemoryneuronal excitabilitylong-term potentiationsignal-to-noise ratiosneurotransmitterneuron numberAplysiabiological neuronschanges in connection strengthscomparison of information processingneuronal plasticityreal nervous systemssynaptic transmission

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Neural biology (92C20) Neural networks for/in biological studies, artificial life and related topics (92B20)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Content-addressable memories. 2nd ed
• Collective Computation With Continuous Variables
• Learning representations by back-propagating errors

This page was built for publication: How neural are neural networks? A comparison of information processing and storage in artificial and real neural systems