Soft-wired long-term memory in a natural recurrent neuronal network

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  • dc.contributor.author Casal Santiago, Miguel Ángel
  • dc.contributor.author Galella Toledo, Santiago
  • dc.contributor.author Vilarroya, Óscar
  • dc.contributor.author García Ojalvo, Jordi
  • dc.date.accessioned 2022-01-26T07:34:06Z
  • dc.date.available 2022-01-26T07:34:06Z
  • dc.date.issued 2020
  • dc.description.abstract Recurrent neuronal networks are known to be endowed with fading (short-term) memory, whereas long-term memory is usually considered to be hard-wired in the network connectivity via Hebbian learning, for instance. Here, we use the neuronal network of the roundworm C. elegans to show that recurrent architectures in living organisms can exhibit long-term memory without relying on specific hard-wired modules. We applied a genetic algorithm, using a binary genome that encodes for inhibitory-excitatory connectivity, to solve the unconstrained optimization problem of fitting the experimentally observed dynamics of the worm's neuronal network. Our results show that the network operates in a complex chaotic regime, as measured by the permutation entropy. In that complex regime, the response of the system to repeated presentations of a time-varying stimulus reveals a consistent behavior that can be interpreted as long-term memory. This memory is soft-wired, since it does not require structural changes in the network connectivity, but relies only on the system dynamics for encoding.
  • dc.description.sponsorship This work was supported by the Spanish Ministry of Science, Innovation and Universities and FEDER (Project Nos. FIS2017-92551-EXP and PGC2018-101251-B-I00), the “Maria de Maeztu” Programme for Units of Excellence in R&D (Grant No. CEX2018-000792-M), and the Generalitat de Catalunya (ICREA Academia programme). M.A.C. is currently supported by the EU Marie Skłodowska-Curie Training Network “NeuTouch” (Contract No. 813713, call H2020-MSCA-ITN-2018).
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Casal MA, Galella S, Vilarroya O, Garcia-Ojalvo J. Soft-wired long-term memory in a natural recurrent neuronal network. Chaos. 2020; 30(6):061101. DOI: 10.1063/5.0009709
  • dc.identifier.doi http://dx.doi.org/10.1063/5.0009709
  • dc.identifier.issn 1054-1500
  • dc.identifier.uri http://hdl.handle.net/10230/52325
  • dc.language.iso eng
  • dc.publisher American Institute of Physics (AIP)
  • dc.relation.ispartof Chaos. 2020; 30(6):061101
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/FIS2017-92551-EXP
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PGC2018-101251-B-I00
  • dc.rights © American Institute of Physics. The following article appeared in Casal MA, Galella S, Vilarroya O, Garcia-Ojalvo J. Soft-wired long-term memory in a natural recurrent neuronal network. Chaos. 2020; 30(6):061101. DOI: 10.1063/5.0009709 and may be found at https://doi.org/10.1063/5.0009709
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.title Soft-wired long-term memory in a natural recurrent neuronal network
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/acceptedVersion

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