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Journal Article

Stochastic feeding dynamics arise from the need for information and energy

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Scholz,  Monika       
Max Planck Research Group Neural Information Flow, Center of Advanced European Studies and Research (caesar), Max Planck Society;
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Citation

Scholz, M., Dinner, A. R., Levine, E., & Biron, D. (2017). Stochastic feeding dynamics arise from the need for information and energy. Proceedings of the National Academy of Sciences of the United States of America, 114(35), 9261-9266. doi:10.1073/pnas.1703958114.


Cite as: https://hdl.handle.net/21.11116/0000-000D-B3C7-8
Abstract
Animals regulate their food intake in response to the available level of food. Recent observations of feeding dynamics in small animals showed feeding patterns of bursts and pauses, but their function is unknown. Here, we present a data-driven decision-theoretical model of feeding in Caenorhabditis elegans. Our central assumption is that food intake serves a dual purpose: to gather information about the external food level and to ingest food when the conditions are good. The model recapitulates experimentally observed feeding patterns. It naturally implements trade-offs between speed versus accuracy and exploration versus exploitation in responding to a dynamic environment. We find that the model predicts three distinct regimes in responding to a dynamical environment, with a transition region where animals respond stochastically to periodic signals. This stochastic response accounts for previously unexplained experimental data.