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Aversive Associative Learning and Memory Formation by Pairing Two Chemicals in Caenorhabditis elegans
Published on: June 23, 2022
Associative Learning Should Go Deep
Esther Mondragón1, Eduardo Alonso1, Niklas Kokkola1
1Research Centre for Systems and Control, University of London, London EC1V 0HB, UK; Computational and Animal Learning Research Centre, St Albans AL1 1RQ, UK.
Abstract:
Conditioning, how animals learn to associate two or more events, is one of the most influential paradigms in learning theory. It is nevertheless unclear how current models of associative learning can accommodate complex phenomena without ad hoc representational assumptions. We propose to embrace deep neural networks to negotiate this problem.
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