Tuning Transduction from Hidden Observables to Optimize Information Harvesting
Biological and living organisms sense and process information from their surroundings, typically having access only to a subset of external observables for a limited amount of time. In this Letter, we uncover how biological systems can exploit these accessible degrees of freedom to transduce information from the inaccessible ones with a limited energy budget. We find that optimal transduction strategies may boost information harvesting over the ideal case in which all degrees of freedom are known, even when only finite-time trajectories are observed, at the price of higher dissipation. We apply our results to red blood cells, inferring the implemented transduction strategy from membrane flickering data and shedding light on the connection between mechanical stress and transduction efficiency. Our framework offers novel insights into the adaptive strategies of biological systems under nonequilibrium conditions.
Authors
- Daniel Maria Busiello (ORCID: https://orcid.org/0000-0002-6754-5019)
- Giorgio Nicoletti (ORCID: https://orcid.org/0000-0002-7682-0596)
Institutions
- Max Planck Institute for the Physics of Complex Systems (DE)
- École Polytechnique Fédérale de Lausanne (CH)
Publication Details
- Journal
- Physical Review Letters
- Published
- 2024-10-07
- DOI
- https://doi.org/10.1103/physrevlett.133.158401
- Citations
- 16
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 3.34
Funders
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
- Max-Planck-Institut für Physik Komplexer Systeme