Learning about the world is critical to survival and success. In social animals, learning about others is a necessary component of navigating the social world, ultimately contributing to increasing evolutionary fitness. How humans and nonhuman animals represent the internal states and experiences of others has long been a subject of intense interest in the developmental psychology tradition, and, more recently, in studies of learning and decision making involving self and other. In this review, we explore how psychology conceptualizes the process of representing others, and how neuroscience has uncovered correlates of reinforcement learning signals to explore the neural mechanisms underlying social learning from the perspective of representing reward-related information about self and other. In particular, we discuss self-referenced and other-referenced types of reward prediction errors across multiple brain structures that effectively allow reinforcement learning algorithms to mediate social learning. Predictionbased computational principles in the brain may be strikingly conserved between self-referenced and other-referenced information.npj Science of Learning (2017) 2:8 ; doi:10.1038/s41539-017-0009-2 HISTORICAL PERSPECTIVES ON REPRESENTING OTHERLearning about the world and making adaptive decisions is a critical feature of cognition. This important link allows human and nonhuman animals to manipulate their environment and survive. Decision-making takes on more complex dynamics when an animal is not solitary, but lives in a community with other members of its own species. We know much about how human and nonhuman animals learn from their own actions and outcomes, and where such self-referenced information is represented in the brain. However, much less is known about the computations underlying how we learn about others. In this review, we examine the presence of other-referenced prediction errors in the brain that represent other's actions and reward outcomes.One of the first academic disciplines to attempt to understand how we develop a concept of others is developmental psychology, in which researchers often explore how babies come to understand the world.

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Optimality principles guide how animals adapt to changing environments. During foraging for nonsocial resources such as food and water, species across taxa obey a strategy that maximizes resource harvest rate. However, it remains unknown whether foraging for social resources also obeys such a strategic principle. We investigated how primates forage for social information conveyed by conspecific facial expressions using the framework of optimal foraging theory. We found that the canonical principle of Marginal Value Theorem (MVT) also applies to social resources. Consistent with MVT, rhesus macaques (Macaca mulatta) spent more time foraging for social information when alternative sources of information were farther away compared to when they were closer by. A comparison of four models of patch-leaving behavior confirmed that the MVT framework provided the best fit to the observed foraging behavior. This analysis further demonstrated that patch-leaving decisions were not driven simply by the declining value of the images in the patch, but instead were dependent upon both the instantaneous social value intake rate and current time in the patch.Optimal foraging theory describes the behavior of animals seeking out resources in a patchy environment according to an energy-maximizing strategy. As animals use the supply of resources within a patch, patch value naturally declines and animals must decide when to leave the current patch in search of a new one. The Marginal Value Theorem (MVT) is a broadly applied optimality model that predicts foraging behavior in a variety of taxa [1][2][3] . MVT predicts that animals should leave the current patch when the energy intake rate within the patch diminishes to the average energy-harvesting rate in the environment 4,5 . Thus, the time that animals spend within a patch (i.e., patch-residence time) depends upon a variety of factors, including the value of the current patch (in terms of the resource being consumed), the value of other patches in the environment, and the time it would take to travel to the next closest patch (i.e., travel time).The optimality of the strategies animals use to forage for primary resources such as food and water has been studied broadly. Across taxa, animals seek out primary resources in accordance with MVT, spending relatively more time in high quality patches that are farther from other patches in the environment and less time in patches that are low quality and nearer to other patches 1,3,[6][7][8] . This optimal foraging model has also been applied to describe foraging for nonsocial information. Human subjects foraged for scholarly publications 9 ; written content in online web searches (e.g., ref. 10 ); and even their own memories 11 . These studies used a patch foraging framework to model humans' strategic decision processes focused on exploiting nonsocial information. Although information is inherently difficult to quantify relative to primary resources, individuals' nonsocial information-foraging decisions could be described using an optimal f...

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We assessed diurnal activity patterns associated with communal roosts (n ¼ 26) by tracking nonbreeding bald eagles (Haliaeetus leucocephalus; n ¼ 58) within the upper Chesapeake Bay, USA, 2008-2013. We used daytime locations (n ¼ 54,165) to map activity shadows (using home range analytics, 90% kernel) around communal roosts, to evaluate the spatial structure and to delineate diurnal activity centers. We overlaid a range (100-3,200 m) of buffers around the perimeter of each roost to estimate the benefits of management scenarios in extending protection to daytime activities. Activity shadows around roosts varied from 1.5 km 2 to 116 km 2 ( x ¼ 30.3 AE 5.48 [SE]), reflecting landscape context. Roosts with small (<10 km 2 ) activity shadows tended to have simple shapes with roosts centrally located and positioned along primary shorelines. Roosts supporting large (>50 km 2 ) activity shadows tended to have complex shapes with roosts not centrally located and set back from primary shorelines. Daytime locations were highly concentrated in areas near communal roosts (76% of locations within 2 km of roost perimeters). Diurnal activity centers (n ¼ 38) included areas surrounding roosts and secondary activity centers that were primarily located along prominent shorelines. Communal roosts play a more significant and multi-faceted role in the eagle life cycle than we previously understood. Many of the roosts positioned along the shoreline provided resting places during the night and day, served as social gathering places during the day, and functioned as feeding locations. Evaluation of management buffers supports current management guidelines that recommend the establishment of 800-m buffers. Establishment of 800-m buffers within the study area would enclose 54% of all daytime locations, 66.7% of the area enclosed within activity centers associated with roosts, and 12.1% of the area enclosed in secondary activity centers. Ó 2017 The Wildlife Society.