A model for brain life history evolution.

Détails

Ressource 1Télécharger: journal.pcbi.1005380.pdf (2252.98 [Ko])
Etat: Public
Version: Final published version
ID Serval
serval:BIB_02A68845CE6E
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
A model for brain life history evolution.
Périodique
PLoS Computational Biology
Auteur(s)
González-Forero M., Faulwasser T., Lehmann L.
ISSN
1553-7358 (Electronic)
ISSN-L
1553-734X
Statut éditorial
Publié
Date de publication
2017
Peer-reviewed
Oui
Volume
13
Numéro
3
Pages
e1005380
Langue
anglais
Résumé
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-extraction challenges are environmentally determined and are overcome individually but possibly with maternal help, and use modern-human data to estimate model's parameter values. The resulting uninvadable strategies yield predictions for brain and body mass throughout ontogeny and for the ages at maturity, adulthood, and brain growth arrest. We find that: (1) a me-vs-nature setting is enough to generate adult brain and body mass of ancient human scale and a sequence of childhood, adolescence, and adulthood stages; (2) large brains are favored by intermediately challenging environments, moderately effective skills, and metabolically expensive memory; and (3) adult skill is proportional to brain mass when metabolic costs of memory saturate the brain metabolic rate allocated to skills.

Pubmed
Web of science
Open Access
Oui
Création de la notice
01/02/2017 20:55
Dernière modification de la notice
20/08/2019 12:24
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