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A model for brain life history evolution

González-Forero, Mauricio; Faulwasser, Timm; Lehmann, Laurent

Abstract:
Complex cognition and relatively large brains are distributed across various taxa, and many primarily verbal hypotheses exist to explain such diversity. Yet, mathematical approaches formalizing verbal hypotheses would help deepen the understanding of brain and cognition evolution. With this aim, we combine elements of life history and metabolic theories to formulate a metabolically explicit mathematical model for brain life history evolution. We assume that some of the brain’s energetic expense is due to production (learning) and maintenance (memory) of energy-extraction skills (or cognitive abilities, knowledge, information, etc.). We also assume that individuals use such skills to extract energy from the environment, and can allocate this energy to grow and maintain the body, including brain and reproductive tissues. The model can be used to ask what fraction of growth energy should be allocated at each age, given natural selection, to growing brain and other tissues under various biological settings. We apply the model to find uninvadable allocation strategies under a baseline setting (“me vs nature”), namely when energy-extracti ... mehr


Zugehörige Institution(en) am KIT Institut für Angewandte Informatik (IAI)
Publikationstyp Zeitschriftenaufsatz
Jahr 2017
Sprache Englisch
Identifikator DOI: 10.1371/journal.pcbi.1005380
ISSN: 1553-7358, 1553-734X
KITopen ID: 1000068018
HGF-Programm 37.06.01; LK 01
Erschienen in PLoS Computational Biology
Band 13
Heft 3
Seiten e1005380
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