Biochemically plausible models of habituation for single-cell learning
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.
Authors
- Ziyuan Zhao (ORCID: https://orcid.org/0009-0003-2019-1406)
- Lina Eckert (ORCID: https://orcid.org/0000-0001-5827-3018)
- Rosa Martinez-Corral (ORCID: https://orcid.org/0000-0003-3600-3601)
- Jordi García‐Ojalvo (ORCID: https://orcid.org/0000-0002-3716-7520)
- Jeremy Gunawardena (ORCID: https://orcid.org/0000-0002-7280-1152)
- María Sol Vidal-Saez
Institutions
- Harvard University (US)
- Universitat Pompeu Fabra (ES)
- Centre for Genomic Regulation (ES)
- Max Planck Institute of Neurobiology (DE)
- Center for Systems Biology (US)
Publication Details
- Journal
- Current Biology
- Published
- 2024-11-19
- DOI
- https://doi.org/10.1016/j.cub.2024.10.041
- Citations
- 21
- Primary Topic
- Gene Regulatory Network Analysis
- Type
- article
- Field-Weighted Citation Impact
- 4.91
Funders
- Harvard University
- Centres de Recerca de Catalunya
- European Commission
- Generalitat de Catalunya
- Institució Catalana de Recerca i Estudis Avançats
- Ministerio de Ciencia e Innovación
- Agència de Gestió d'Ajuts Universitaris i de Recerca
- Agencia Estatal de Investigación
- Air Force Office of Scientific Research