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Hamilton, W. D. (1970). Selfish and Spiteful Behaviour in an Evolutionary Model. Nature, 228, 1218–1220.
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Reeve, H. K. (1992). Queen activation of lazy workers in colonies of the eusocial naked mole-rat. Nature, 358, 147–149.
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Foster, K. R., & Ratnieks, F. L. W. (2000). Social insects: Facultative worker policing in a wasp. Nature, 407(6805), 692–693.
Abstract: Kin-selection theory predicts that in social-insect colonies where the queen has mated multiple times, the workers will enforce cooperation by policing each other's reproduction1, 2, 3, 4. We have discovered a species, the wasp Dolichovespula saxonica, in which some queens mate once and others mate many times, and in which workers frequently attempt reproduction, allowing this prediction to be tested directly. We find that multiple mating by the queen leads to mutual policing by workers, whereas single mating does not.
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Harrison, S. A., & Tong, F. (2009). Decoding reveals the contents of visual working memory in early visual areas. Nature, 458(7238), 632–635.
Abstract: Visual working memory provides an essential link between perception and higher cognitive functions, allowing for the active maintenance of information about stimuli no longer in view1, 2. Research suggests that sustained activity in higher-order prefrontal, parietal, inferotemporal and lateral occipital areas supports visual maintenance3, 4, 5, 6, 7, 8, 9, 10, 11, and may account for the limited capacity of working memory to hold up to 3–4 items9, 10, 11. Because higher-order areas lack the visual selectivity of early sensory areas, it has remained unclear how observers can remember specific visual features, such as the precise orientation of a grating, with minimal decay in performance over delays of many seconds12. One proposal is that sensory areas serve to maintain fine-tuned feature information13, but early visual areas show little to no sustained activity over prolonged delays14, 15, 16. Here we show that orientations held in working memory can be decoded from activity patterns in the human visual cortex, even when overall levels of activity are low. Using functional magnetic resonance imaging and pattern classification methods, we found that activity patterns in visual areas V1–V4 could predict which of two oriented gratings was held in memory with mean accuracy levels upwards of 80%, even in participants whose activity fell to baseline levels after a prolonged delay. These orientation-selective activity patterns were sustained throughout the delay period, evident in individual visual areas, and similar to the responses evoked by unattended, task-irrelevant gratings. Our results demonstrate that early visual areas can retain specific information about visual features held in working memory, over periods of many seconds when no physical stimulus is present.
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Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of /`small-world/' networks. Nature, 393(6684), 440–442.
Abstract: Networks of coupled dynamical systems have been used to model biological oscillators Josephson junction arrays excitable media, neural networks spatial games11, genetic control networks12 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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Prather, J. F., Peters, S., Nowicki, S., & Mooney, R. (2008). Precise auditory-vocal mirroring in neurons for learned vocal communication. Nature, 451(7176), 305–310.
Abstract: Brain mechanisms for communication must establish a correspondence between sensory and motor codes used to represent
the signal. One idea is that this correspondence is established at the level of single neurons that are active when the
individual performs a particular gesture or observes a similar gesture performed by another individual. Although neurons
that display a precise auditory–vocal correspondence could facilitate vocal communication, they have yet to be identified.
Here we report that a certain class of neurons in the swamp sparrow forebrain displays a precise auditory–vocal
correspondence. We show that these neurons respond in a temporally precise fashion to auditory presentation of certain
note sequences in this songbird’s repertoire and to similar note sequences in other birds’ songs. These neurons display
nearly identical patterns of activity when the bird sings the same sequence, and disrupting auditory feedback does not alter
this singing-related activity, indicating it is motor in nature. Furthermore, these neurons innervate striatal structures
important for song learning, raising the possibility that singing-related activity in these cells is compared to auditory
feedback to guide vocal learning.
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Nagy, M., Akos, Z., Biro, D., & Vicsek, T. (2010). Hierarchical group dynamics in pigeon flocks. Nature, 464(7290), 890–893.
Abstract: Animals that travel together in groups display a variety of fascinating motion patterns thought to be the result of delicate local interactions among group members1, 2, 3. Although the most informative way of investigating and interpreting collective movement phenomena would be afforded by the collection of high-resolution spatiotemporal data from moving individuals, such data are scarce4, 5, 6, 7 and are virtually non-existent for long-distance group motion within a natural setting because of the associated technological difficulties8. Here we present results of experiments in which track logs of homing pigeons flying in flocks of up to 10 individuals have been obtained by high-resolution lightweight GPS devices and analysed using a variety of correlation functions inspired by approaches common in statistical physics. We find a well-defined hierarchy among flock members from data concerning leading roles in pairwise interactions, defined on the basis of characteristic delay times between birds’ directional choices. The average spatial position of a pigeon within the flock strongly correlates with its place in the hierarchy, and birds respond more quickly to conspecifics perceived primarily through the left eye—both results revealing differential roles for birds that assume different positions with respect to flock-mates. From an evolutionary perspective, our results suggest that hierarchical organization of group flight may be more efficient than an egalitarian one, at least for those flock sizes that permit regular pairwise interactions among group members, during which leader–follower relationships are consistently manifested.
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Tricomi, E., Rangel, A., Camerer, C. F., & O/'Doherty, J. P. (2010). Neural evidence for inequality-averse social preferences. Nature, 463(7284), 1089–1091.
Abstract: A popular hypothesis in the social sciences is that humans have social preferences to reduce inequality in outcome distributions because it has a negative impact on their experienced reward1, 2, 3. Although there is a large body of behavioural and anthropological evidence consistent with the predictions of these theories1, 4, 5, 6, there is no direct neural evidence for the existence of inequality-averse preferences. Such evidence would be especially useful because some behaviours that are consistent with a dislike for unequal outcomes could also be explained by concerns for social image7 or reciprocity8, 9, which do not require a direct aversion towards inequality. Here we use functional MRI to test directly for the existence of inequality-averse social preferences in the human brain. Inequality was created by recruiting pairs of subjects and giving one of them a large monetary endowment. While both subjects evaluated further monetary transfers from the experimenter to themselves and to the other participant, we measured neural responses in the ventral striatum and ventromedial prefrontal cortex, two areas that have been shown to be involved in the valuation of monetary and primary rewards in both social and non-social contexts10, 11, 12, 13, 14. Consistent with inequality-averse models of social preferences, we find that activity in these areas was more responsive to transfers to others than to self in the ‘high-pay’ subject, whereas the activity of the ‘low-pay’ subject showed the opposite pattern. These results provide direct evidence for the validity of this class of models, and also show that the brain’s reward circuitry is sensitive to both advantageous and disadvantageous inequality.
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Clutton-Brock, T. (2009). Cooperation between non-kin in animal societies. Nature, 462(7269), 51–57.
Abstract: Explanations of cooperation between non-kin in animal societies often suggest that individuals exchange resources or services and that cooperation is maintained by reciprocity. But do cooperative interactions between unrelated individuals in non-human animals really resemble exchanges or are they a consequence of simpler mechanisms? Firm evidence of reciprocity in animal societies is rare and many examples of cooperation between non-kin probably represent cases of intra-specific mutualism or manipulation.
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Weissing, F. J. (2011). Animal behaviour: Born leaders. Nature, 474(7351), 288–289.
Abstract: Social animals face a dilemma. To reap the benefits of group living, they have to stay together. However, individuals differ in their preferences as to where to go and what to do next. If all individuals follow their own preferences, group coherence is undermined, resulting in an outcome that is unfavourable for everyone. Neglecting one's own preferences and following a leader is one way to resolve this coordination problem. But what attributes make an individual a 'leader'? A modelling study by Johnstone and Manica1 illuminates this question.
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