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Research Title:
Research on Evolutionary Models of Human Learning Abilities
Research Organization:
Team Leader
- Kenichi Aoki, Emeritus Professor,
Theological Biology, The University of Tokyo
Co-investigators
- Joe Yuichiro Wakano, Associate Professor,
Mathematical Biology, Institute for Advanced Study of Mathematical Sciences, Meiji University
- Ryosuke Kimura, Associate Professor,
Molecular Anthropology, Graduate School of Medicine, University of the Ryukyus
- Yutaka Kobayashi, Associate Professor,
Mathematical Biology, Department of Management, Kochi University of Technology
- Kyoko Yamaguchi, Full-Time Lecturer,
Molecular Anthropology, Liverpool John Moores University, UK
- Ryo Oizumi, Research Officer of Demographic Affairs,
Mathematical Biology, Mathematical Demography, DG Bureau for Policy Planning and Evaluation, Ministry of Health, Labour and Welfare
Overseas Collaborators
- Marcus W. Feldman, Professor,
Population Biology, Department of Biology, Stanford University, USA
- Laurent Lehmann, Associate Professor,
Mathematical Biology, Department of Ecology and Evolution, University of Lausanne, Switzerland
Invited Researchers
- Mayuko Nakamaru, Associate Professor,
Graduate School of Decision Science and Technology, Tokyo Institute of Technology
- Shiro Horiuchi, Associate Professor,
COC Promotion Office, Yamagata University
- Toshiyuki Hayakawa, Associate Professor,
Faculty of Arts and Science, Kyusyu University
Research Objectives
We will provide theoretical support for the “learning hypothesis” that the replacement of Neanderthals (Homo neanderthalensis) by humans (H. sapiens) is attributable to innate differences in learning abilities between the two hominid species. Towards this goal, we will use evolutionary models to deduce the conditions under which abilities supportive of social learning (e.g. learning from others by imitation, teaching) and/or individual learning (e.g. learning by oneself by trial-and-error, “creativity”) evolve as adaptations to a changing environment. With reference to data on climate change and other environmental variables supplied by B02, we will then attempt to explain why these abilities evolved to a high level in humans but presumably did not in Neanderthals. Furthermore, with the expectation that differences in learning abilities should be most directly reflected in differences in cultural evolutionary rate, we will examine whether such a causal relation can be discerned in the archaeological record provided by A01. A complementary goal is to identify the genes contributing to the highly-developed learning abilities of humans, based on statistical analyses of molecular population genetic data, and to locate possible region(s) of the brain where these genes are expressed, with reference to the functional map for present-day humans provided by C02. In addition, we will use both evolutionary models and molecular population genetic data to investigate the pattern, speed, and routes of range expansion of humans within and outside of Africa.
Research Methods
We will describe and analyze mathematical models dealing with the effects of environmental change on the evolution of social learning and individual learning abilities. In particular, we will study stepping-stone models (habitats are arranged like beads on a necklace, see for example Aoki & Nakahashi 2008, Theoretical Population Biology 74, 356-368) and reaction-diffusion models (habitats are distributed continuously, Shigesada & Kawasaki 1997 Biological Invasions, Oxford University Press) incorporating spatial environmental heterogeneity, and will derive the conditions for the evolution of learning abilities (especially individual learning abilities) during range expansion into an environmentally heterogeneous world. Moreover, we will review the special features of range expansion of humans relative to that of other biological species including Neanderthals and H. erectus, in order to add precision to the above evolutionary models. This we will do from the standpoints of mathematical ecology and molecular population genetics, focusing on such factors as aggregation toward favorable environments or invasion of inhospitable environments, density-dependent migration, and changes in migration rate per se.
By juxtaposing the results obtained from the above theoretical studies with quantitative data on environmental variability (e.g., between habitats) provided by B02, we will suggest reasons why learning abilities only evolved to a high level in humans.
Using gene-culture coevolutionary models that incorporate both the evolution of learning abilities and cultural transmission, we will clarify the process by which novel technology created by individual learning may spread culturally through social learning. This will permit us to predict and interpret the spatio-temporal distribution of modern behavior (Upper Paleolithic tools, ornaments, art). Furthermore, we will study the relationship between learning abilities and cultural evolutionary rates. For example, we will evaluate the claim made by some archaeologists that one-to-many transmission, such as may occur when lithic technology is taught by one expert to many novices, accelerates cultural evolution (Aoki et al., in preparation).
We will conduct statistical analyses of genome diversity in present-day humans to estimate changes in population size as well as the pattern and routes of range expansion in H. sapiens. In addition, we will use genome data from the chimpanzee, the Neanderthals (a draft sequence has recently become available), and present-day humans to statistically identify (by observing selective sweep and ratio of synonymous/non-synonymous substitutions) the genes subject to natural selection in the human lineage, and to obtain estimates of the time, place and magnitude of these selective events. In particular, by investigating the signature of natural selection on genes that are expressed in the brain and the nervous system, we will identify the genes contributing to advanced individual learning ability in humans, the existence of which is both a premise for and a prediction of the evolutionary models.
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