Relationship between Exercise Capacity and Brain Size in Mammals

A great deal of experimental research supports strong associations between exercise, cognition, neurogenesis and neuroprotection in mammals. Much of this work has focused on neurogenesis in individual subjects in a limited number of species. However, no study to date has examined the relationship between exercise and neurobiology across a wide range of mammalian taxa. It is possible that exercise and neurobiology are related across evolutionary time. To test this hypothesis, this study examines the association between exercise and brain size across a wide range of mammals.Controlling for associations with body size, we examined the correlation between brain size and a proxy for exercise frequency and capacity, maximum metabolic rate (MMR; ml O(2) min(-1)). We collected brain sizes and MMRs from the literature and calculated residuals from the least-squares regression line describing the relationship between body mass and each variable of interest. We then analyzed the correlation between residual brain size and residual MMR both before and after controlling for phylogeny using phylogenetic independent contrasts. We found a significant positive correlation between maximum metabolic rate and brain size across a wide range of taxa.These results suggest a novel hypothesis that links brain size to the evolution of locomotor behaviors in a wide variety of mammalian species. In the end, we suggest that some portion of brain size in nonhuman mammals may have evolved in conjunction with increases in exercise capacity rather than solely in response to selection related to cognitive abilities

A Taxonomic Framework for Social Machines

As the Web has developed into a global social platform there has been increasing interest in a particular class of systems known as 'social machines'. Social machines are typically presented as systems that combine some form of social participation with conventional forms of machine-based 'computation'. Beyond this rather general characterization, however, there is little consensus as to what the term 'social machine' actually means. Furthermore, little has been done to explore the core features of social machines and examine differences between them. This limits our understanding of the kinds of social machines that currently exist, and it also limits our ability to imagine the kinds of social machine that could emerge in the future. In this chapter, we introduce a taxonomy for the description and classification of social machines that could be used to frame future scholarly discourse and identify aspects of the social machine research effort that deserve further consideration. As part of this effort, we propose a definition of social machines that puts them in relation to the broader class of socio-technical systems, while distinguishing them from other kinds of technology-mediated social participation system; for example, human computation systems and collective intelligence systems. The taxonomic framework we present serves to extend our understanding of social machines. It includes a total of 33 dimensions and 106 associated characteristics. Together, these specify the space of all (theoretically possible) social machine types