Biochemically plausible models of habituation for single-cell learning

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  • dc.contributor.author Eckert, Lina
  • dc.contributor.author Vidal-Saez, María Sol
  • dc.contributor.author Zhao, Ziyuan
  • dc.contributor.author García Ojalvo, Jordi
  • dc.contributor.author Martínez Corral, Rosa, 1991-
  • dc.contributor.author Gunawardena, Jeremy
  • dc.date.accessioned 2025-02-04T07:46:06Z
  • dc.date.available 2025-02-04T07:46:06Z
  • dc.date.issued 2024
  • dc.description.abstract The ability to learn is typically attributed to animals with brains. However, the apparently simplest form of learning, habituation, in which a steadily decreasing response is exhibited to a repeated stimulus, is found not only in animals but also in single-cell organisms and individual mammalian cells. Habituation has been codified from studies in both invertebrate and vertebrate animals as having ten characteristic hallmarks, seven of which involve a single stimulus. Here, we show by mathematical modeling that simple molecular networks, based on plausible biochemistry with common motifs of negative feedback and incoherent feedforward, can robustly exhibit all single-stimulus hallmarks. The models reveal how the hallmarks arise from underlying properties of timescale separation and reversal behavior of memory variables, and they reconcile opposing views of frequency and intensity sensitivity expressed within the neuroscience and cognitive science traditions. Our results suggest that individual cells may exhibit habituation behavior as rich as that which has been codified in multi-cellular animals with central nervous systems and that the relative simplicity of the biomolecular level may enhance our understanding of the mechanisms of learning.
  • dc.description.sponsorship We thank Arjun Raj and two anonymous reviewers for their thoughtful and constructive comments. M.S.V.-S. was supported by PhD Fellowship 2021-FI-B-00408 from the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) from the Generalitat de Catalunya. Z.Z. was supported by a Harvard University Program for Research in Science and Engineering (PRISE) Award. J.G.-O. was supported by the Spanish State Research Agency and FEDER Project PID2021-127311NB-I00, the Spanish Ministry of Science and Innovation, and the Generalitat de Catalunya (ICREA programme). R.M.-C. was supported by EMBO fellowship ALTF683–2019, RYC2021-033860-I funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGeneration EU/PRTR; R.M.-C. also acknowledges the support of the Spanish Ministry of Science and Innovation through the Centro de Excelencia Severo Ochoa (CEX2020-001049-S, MCIN/AEI /10.13039/ 501100011033) and the Generalitat de Catalunya through the CERCA programme. J.G. was supported by AFOSR grant FA9550-22-1-0345. The work of M.S.V.-S., J.G.-O., and R.M.-C. was partially carried out at the Barcelona Collaboratorium for Modelling and Predictive Biology.
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Eckert L, Vidal-Saez MS, Zhao Z, Garcia-Ojalvo J, Martinez-Corral R, Gunawardena J. Biochemically plausible models of habituation for single-cell learning. Curr Biol. 2024 Dec 16;34(24):5646-58.e3. DOI: 10.1016/j.cub.2024.10.041
  • dc.identifier.doi http://dx.doi.org/10.1016/j.cub.2024.10.041
  • dc.identifier.issn 0960-9822
  • dc.identifier.uri http://hdl.handle.net/10230/69475
  • dc.language.iso eng
  • dc.publisher Elsevier
  • dc.relation.ispartof Curr Biol. 2024 Dec 16;34(24):5646-58.e3
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/3PE/PID2021-127311NB-I00
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/3PE/RYC2021-033860-I
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/CEX2020-001049-S
  • dc.rights © 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
  • dc.subject.keyword Cellular information processing
  • dc.subject.keyword Hallmarks of habituation
  • dc.subject.keyword Incoherent feedforward
  • dc.subject.keyword Modification-demodification cycle
  • dc.subject.keyword Negative feedback
  • dc.subject.keyword Timescale separation
  • dc.title Biochemically plausible models of habituation for single-cell learning
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/publishedVersion

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