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Cheng, K. (2004). K.J. Jeffery (ed) The neurobiology of spatial behaviour. Anim. Cogn., 7(3), 199–200.
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Gould, J. L. (2004). Thinking about thinking: how Donald R. Griffin (1915-2003) remade animal behavior. Anim. Cogn., 7(1), 1–4.
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Chappell J, & Kacelnik A. (2004). Selection of tool diameter by New Caledonian crows. Anim. Cogn., 7, 121.
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Call J. (2004). Inferences about the location of food in the great apes (Pan paniscus, Pan troglodytes, Gorilla gorilla, and Pongo pygmaeus). J. Comp. Psychol., 118(2), 232.
Abstract: Bonobos (Pan paniscus; n = 4), chimpanzees (Pan troglodytes; n = 12), gorillas (Gorilla gorilla; n = 8), and orangutans (Pongo pygmaeus; n = 6) were presented with 2 cups (1 baited) and given visual or auditory information about their contents. Visual information consisted of letting subjects look inside the cups. Auditory information consisted of shaking the cup so that the baited cup produced a rattling sound. Subjects correctly selected the baited cup both when they saw or heard the food. Nine individuals were above chance in both visual and auditory conditions. More important, subjects as a group selected the baited cup when only the empty cup was either shown or shaken, which means that subjects chose correctly without having seen or heard the food (i.e., inference by exclusion). Control tests showed that subjects were not more attracted to noisy cups, avoided shaken noiseless cups, or learned to use auditory information as a cue during the study. It is concluded that subjects understood that the food caused the noise, not simply that the noise was associated with the food. (PsycINFO Database Record (c) 2010 APA, all rights reserved)
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Dukas, R. (2004). Evolutionary Biology Of Animal Cognition. Annual Review of Ecology, Evolution, and Systematics, 35(1), 347–374.
Abstract: This review focuses on five key evolutionary issues pertaining to animal cognition, defined as the neuronal processes concerned with the acquisition, retention, and use of information. Whereas the use of information, or decision making, has been relatively well examined by students of behavior, evolutionary aspects of other cognitive traits that affect behavior, including perception, learning, memory, and attention, are less well understood. First, there is ample evidence for genetically based individual variation in cognitive traits, although much of the information for some traits comes from humans. Second, several studies documented positive association between cognitive abilities and performance measures linked to fitness. Third, information on the evolution of cognitive traits is available primarily for color vision and decision making. Fourth, much of the data on plasticity of cognitive traits appears to reflect nonadaptive phenotypic plasticity, perhaps because few evolutionary analyses of cognitive plasticity have been carried out. Nonetheless, several studies suggest that cognitive traits show adaptive plasticity, and at least one study documented genetically based individual variation in plasticity. Fifth, whereas assertions that cognition has played a central role in animal evolution are not supported by currently available data, theoretical considerations indicate that cognition may either increase or decrease the rate of evolutionary change.
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Kanazawa, S. (2004). Social sciences are branches of biology. Socioecon. Rev., 2(3), 371–390.
Abstract: Since biology is the study of living organisms, their behaviour and social systems, and since humans are living organisms, it is possible to suggest that social sciences (the study of human behaviour and social systems) are branches of biology and all social scientific theories should be consistent with known biological principles. To claim otherwise and to establish a separate science only for humans might be analogous to the establishment of hydrogenology, the study of hydrogen separate from and inconsistent with the rest of physics. Evolutionary psychology is the application of evolutionary biology to humans, and provides the most general (panspecific) explanations of human behaviour, cognitions, emotions and human social systems. Evolutionary psychology's recognition that humans are animals can explain some otherwise perplexing empirical puzzles in social sciences, such as why there is a wage penalty for motherhood but a wage reward for fatherhood, and why boys produce a greater wage reward for fathers than do girls. The General Social Survey data illustrate the evolutionary psychological argument that reproductive success is important for both men's and women's happiness, but money is only important for men's.
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Gentner, T. Q. (2004). Neural Systems for Individual Song Recognition in Adult Birds. Ann. N.Y. Acad. Sci., 1016(1), 282–302.
Abstract: The songbird auditory system is an excellent model for neuroethological studies of the mechanisms that govern the perception and cognition of natural stimuli (i.e., song), and the translation of corresponding representations into natural behaviors. One common songbird behavior is the learned recognition of individual conspecific songs. This chapter summarizes the research effort to identify the brain regions and mechanisms mediating individual song recognition in European starlings, a species of songbird. The results of laboratory behavioral studies are reviewed, which show that when adult starlings learn to recognize other individual's songs, they do so by memorizing large sets of song elements, called motifs. Recent data from single neurons in the caudal medial portion of the mesopallium are then reviewed, showing that song recognition learning leads to explicit representation of acoustic features that correspond closely to specific motifs, but only to motifs in the songs that birds have learned to recognize. This suggests that the strength and tuning of high-level auditory object representations, of the sort that presumably underlie many forms of vocal communication, are shaped by each animal's unique experience.
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Emery, N. J., & Clayton, N. S. (2004). The Mentality of Crows: Convergent Evolution of Intelligence in Corvids and Apes. Science, 306(5703), 1903–1907.
Abstract: 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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Clayton, N. S. (2004). COGNITION: An Open Sandwich or an Open Question? Science, 305(5682), 344–.
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Verguts, T., & Fias, W. (2004). Representation of Number in Animals and Humans: A Neural Model. J. Cogn. Neurosci., 16(9), 1493–1504.
Abstract: This article addresses the representation of numerical information conveyed by nonsymbolic and symbolic stimuli. In a first simulation study, we show how number-selective neurons develop when an initially uncommitted neural network is given nonsymbolic stimuli as input (e.g., collections of dots) under unsupervised learning. The resultant network is able to account for the distance and size effects, two ubiquitous effects in numerical cognition. Furthermore, the properties of the network units conform in detail to the characteristics of recently discovered number-selective neurons. In a second study, we simulate symbol learning by presenting symbolic and nonsymbolic input simultaneously. The same number-selective neurons learn to represent the numerical meaning of symbols. In doing so, they show properties reminiscent of the originally available number-selective neurons, but at the same time, the representational efficiency of the neurons is increased when presented with symbolic input. This finding presents a concrete proposal on the linkage between higher order numerical cognition and more primitive numerical abilities and generates specific predictions on the neural substrate of number processing. N1 -
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