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Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., & Alon, U. (2002). Network Motifs: Simple Building Blocks of Complex Networks. Science, 298(5594), 824–827.
Abstract: Complex networks are studied across many fields of science. To uncover their structural design principles, we defined “network motifs,” patterns of interconnections occurring in complex networks at numbers that are significantly higher than those in randomized networks. We found such motifs in networks from biochemistry, neurobiology, ecology, and engineering. The motifs shared by ecological food webs were distinct from the motifs shared by the genetic networks of Escherichia coli and Saccharomyces cerevisiae or from those found in the World Wide Web. Similar motifs were found in networks that perform information processing, even though they describe elements as different as biomolecules within a cell and synaptic connections between neurons in Caenorhabditis elegans. Motifs may thus define universal classes of networks. This approach may uncover the basic building blocks of most networks.
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Seyfarth, R. M., Cheney, D. L., & Marler, P. (1980). Monkey responses to three different alarm calls: evidence of predator classification and semantic communication. Science, 210(4471), 801–803.
Abstract: Vervet monkeys give different alarm calls to different predators. Recordings of the alarms played back when predators were absent caused the monkeys to run into trees for leopard alarms, look up for eagle alarms, and look down for snake alarms. Adults call primarily to leopards, martial eagles, and pythons, but infants give leopard alarms to various mammals, eagle alarms to many birds, and snake alarms to various snakelike objects. Predator classification improves with age and experience.
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Brannon, E. M., & Terrace, H. S. (1998). Ordering of the numerosities 1 to 9 by monkeys. Science, 282(5389), 746–749.
Abstract: A fundamental question in cognitive science is whether animals can represent numerosity (a property of a stimulus that is defined by the number of discriminable elements it contains) and use numerical representations computationally. Here, it was shown that rhesus monkeys represent the numerosity of visual stimuli and detect their ordinal disparity. Two monkeys were first trained to respond to exemplars of the numerosities 1 to 4 in an ascending numerical order (1 --> 2 --> 3 --> 4). As a control for non-numerical cues, exemplars were varied with respect to size, shape, and color. The monkeys were later tested, without reward, on their ability to order stimulus pairs composed of the novel numerosities 5 to 9. Both monkeys responded in an ascending order to the novel numerosities. These results show that rhesus monkeys represent the numerosities 1 to 9 on an ordinal scale.
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Singh, M., Singh, M., Sharma, A. K., & Krishna B. A. (2003). Methodological considerations in measurement of dominance in primates. CURRENT SCIENCE, 84(5), 709–713.
Abstract: The strength of dominance hierarchy in a group of
animals needs to be quantitatively measured since it
influences many other aspects of social interactions.
This article discusses three attempts made by previous
researchers to measure the strength of hierarchy. We
propose a method which attempts to rectify the lacunae
in the previous attempts. Data are used from a
group of Japanese macaques housed in a colony. A
method to calculate strength of hierarchy has been
illustrated and a procedure has been suggested to
normalize the dominance scores in order to place the
ranks of individuals on an interval scale.
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Rosati, A. G. (2017). Foraging Cognition: Reviving the Ecological Intelligence Hypothesis. Trends in Cognitive Sciences, 21(9), 691–702.
Abstract: What are the origins of intelligent behavior? The demands associated with living in complex social groups have been the favored explanation for the evolution of primate cognition in general and human cognition in particular. However, recent comparative research indicates that ecological variation can also shape cognitive abilities. I synthesize the emerging evidence that ?foraging cognition? ? skills used to exploit food resources, including spatial memory, decision-making, and inhibitory control ? varies adaptively across primates. These findings provide a new framework for the evolution of human cognition, given our species? dependence on costly, high-value food resources. Understanding the origins of the human mind will require an integrative theory accounting for how humans are unique in both our sociality and our ecology.
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Straub, A. (2007). An intelligent crow beats a lab. Science, 316(5825), 688.
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Legare, C. H., & Nielsen, M. (). Imitation and Innovation: The Dual Engines of Cultural Learning. Trends in Cognitive Sciences, 19(11), 688–699.
Abstract: Imitation and innovation work in tandem to support cultural learning in children and facilitate our capacity for cumulative culture. Here we propose an integrated theoretical account of how the unique demands of acquiring instrumental skills and cultural conventions provide insight into when children imitate, when they innovate, and to what degree. For instrumental learning, with an increase in experience, high fidelity imitation decreases and innovation increases. By contrast, for conventional learning, imitative fidelity stays high, regardless of experience, and innovation stays low. We synthesize cutting edge research on the development of imitative flexibility and innovation to provide insight into the social learning mechanisms underpinning the uniquely human mind.
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Peham, C., Licka, T., Schobesberger, H., & Meschan, E. (2004). Influence of the rider on the variability of the equine gait. European Workshop on Movement Science, 23(5), 663–671.
Abstract: The aim of this study was to show that the motion pattern of a well-ridden horse varies less than the motion pattern of an unridden horse. In order to do so, we recorded the motion of two markers, one attached to the dorsal spinous processus of lumbar vertebra L4, the other to the right fore hoof. In total, we measured 21 horses in trot, ridden and unridden, with a fitting and with a non-fitting saddle. After breaking down the entire time series of the three-dimensional motion of the markers into their respective motion cycles, we computed a measure of motion pattern variability for the motion as well as for the derivatives (velocity and acceleration) along each of the three principal dimensions. Two of six variables (velocity and acceleration in the forward direction) displayed a significant discrimination between the ridden and the unridden case, and demonstrated the beneficial effect of a rider on the horse's motion pattern variability. Saddle fit was shown to have also an influence on motion variability: variability of two variables (velocity and of acceleration in forward direction) was significantly lower with a fitting saddle compared to a non-fitting saddle, a third variable (acceleration in the transversal direction) showed a significant difference also. This new method offers an objective evaluation of saddle fit, and a sensitive assessment of the quality of the rider in the moving horse.
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de Waal, F. B. (2000). Primates--A natural heritage of conflict resolution. Science, 289(5479), 586–590.
Abstract: The traditional notion of aggression as an antisocial instinct is being replaced by a framework that considers it a tool of competition and negotiation. When survival depends on mutual assistance, the expression of aggression is constrained by the need to maintain beneficial relationships. Moreover, evolution has produced ways of countering its disruptive consequences. For example, chimpanzees kiss and embrace after fights, and other nonhuman primates engage in similar “reconciliations.” Theoretical developments in this field carry implications for human aggression research. From families to high schools, aggressive conflict is subject to the same constraints known of cooperative animal societies. It is only when social relationships are valued that one can expect the full complement of natural checks and balances.
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Premack D, & Woodruff G. (1978). Chimpanzee problem-solving: a test for comprehension. Science, 202(3), 532.
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