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      Cognitive ornithology: the evolution of avian intelligence

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      Philosophical Transactions of the Royal Society B: Biological Sciences
      The Royal Society

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          Abstract

          Comparative psychologists interested in the evolution of intelligence have focused their attention on social primates, whereas birds tend to be used as models of associative learning. However, corvids and parrots, which have forebrains relatively the same size as apes, live in complex social groups and have a long developmental period before becoming independent, have demonstrated ape-like intelligence. Although, ornithologists have documented thousands of hours observing birds in their natural habitat, they have focused their attention on avian behaviour and ecology, rather than intelligence. This review discusses recent studies of avian cognition contrasting two different approaches; the anthropocentric approach and the adaptive specialization approach. It is argued that the most productive method is to combine the two approaches. This is discussed with respects to recent investigations of two supposedly unique aspects of human cognition; episodic memory and theory of mind. In reviewing the evidence for avian intelligence, corvids and parrots appear to be cognitively superior to other birds and in many cases even apes. This suggests that complex cognition has evolved in species with very different brains through a process of convergent evolution rather than shared ancestry, although the notion that birds and mammals may share common neural connectivity patterns is discussed.

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          Collective dynamics of 'small-world' networks.

          Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks 'rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them 'small-world' networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation. The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.
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            Neocortex size as a constraint on group size in primates

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              The mentality of crows: convergent evolution of intelligence in corvids and apes.

              Discussions of the evolution of intelligence have focused on monkeys and apes because of their close evolutionary relationship to humans. Other large-brained social animals, such as corvids, also understand their physical and social worlds. Here we review recent studies of tool manufacture, mental time travel, and social cognition in corvids, and suggest that complex cognition depends on a "tool kit" consisting of causal reasoning, flexibility, imagination, and prospection. Because corvids and apes share these cognitive tools, we argue that complex cognitive abilities evolved multiple times in distantly related species with vastly different brain structures in order to solve similar socioecological problems.
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                Author and article information

                Journal
                Philosophical Transactions of the Royal Society B: Biological Sciences
                Phil. Trans. R. Soc. B
                The Royal Society
                0962-8436
                1471-2970
                January 29 2006
                December 07 2005
                January 29 2006
                : 361
                : 1465
                : 23-43
                Affiliations
                [1 ]Sub-department of Animal Behaviour, University of CambridgeMadingley, Cambridge CB3 8AA, UK
                Article
                10.1098/rstb.2005.1736
                1626540
                16553307
                33becc81-bcb1-4fb5-a070-9ada16773872
                © 2006

                https://royalsociety.org/journals/ethics-policies/data-sharing-mining/

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