Tuning positive feedback for signal detection in noisy dynamic environments
2012 (English)In: Journal of Theoretical Biology, ISSN 0022-5193, E-ISSN 1095-8541, Vol. 309, 88-95 p.Article in journal (Refereed) Published
Learning from previous actions is a key feature of decision-making. Diverse biological systems, from neuronal assemblies to insect societies, use a combination of positive feedback and forgetting of stored memories to process and respond to input signals. Here we look how these systems deal with a dynamic two-armed bandit problem of detecting a very weak signal in the presence of a high degree of noise. We show that by tuning the form of positive feedback and the decay rate to appropriate values, a single tracking variable can effectively detect dynamic inputs even in the presence of a large degree of noise. In particular, we show that when tuned appropriately a simple positive feedback algorithm is Fisher efficient, in that it can track changes in a signal on a time of order L(h)= (vertical bar h vertical bar/sigma)(-2), where vertical bar h vertical bar is the magnitude of the signal and sigma the magnitude of the noise.
Place, publisher, year, edition, pages
2012. Vol. 309, 88-95 p.
Self-organisation, Ant foraging, Bandit problems, Biochemical systems
IdentifiersURN: urn:nbn:se:uu:diva-181389DOI: 10.1016/j.jtbi.2012.05.023ISI: 000307526200010OAI: oai:DiVA.org:uu-181389DiVA: diva2:557701