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Terrace, H. S. (1987). Chunking by a pigeon in a serial learning task. Nature, 325(7000), 149–151.
Abstract: A basic principle of human memory is that lists that can be organized into memorable 'chunks' are easier to remember. Memory span is limited to a roughly constant number of chunks and is to a large extent independent of the amount of informaton contained in each chunk. Depending on the ingenuity of the code used to integrate discrete items into chunks, one can substantially increase the number of items that can be recalled correctly. Newly developed paradigms for studying memory in non-verbal organisms allow comparison of the abilities of human and non-human subjects to memorize lists. Here I present two types of evidence that pigeons 'chunk' 5-element lists whose components (colours and achromatic geometric forms) are clustered into distinct groups. Those lists were learned twice as rapidly as a homogeneous list of colours or heterogeneous lists in which the elements are not clustered. The pigeons were also tested for knowledge of the order of two elements drawn from the 5-element lists. They responded in the correct order only to those subsets that contained a chunk boundary. Thus chunking can be studied profitably in animal subjects; the cognitive processes that allow an organism to form chunks do no presuppose linguistic competence.
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Crook, J. H. (1983). On attributing consciousness to animals. Nature, 303(5912), 11–14.
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Franks, N. R., & Richardson, T. (2006). Teaching in tandem-running ants. Nature, 439(7073), 153.
Abstract: The ant Temnothorax albipennis uses a technique known as tandem running to lead another ant from the nest to food--with signals between the two ants controlling both the speed and course of the run. Here we analyse the results of this communication and show that tandem running is an example of teaching, to our knowledge the first in a non-human animal, that involves bidirectional feedback between teacher and pupil. This behaviour indicates that it could be the value of information, rather than the constraint of brain size, that has influenced the evolution of teaching.
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Nicol, C. J. (2004). Development, direction, and damage limitation: social learning in domestic fowl. Learn Behav, 32(1), 72–81.
Abstract: This review highlights two areas of particular interest in the study of social learning in fowl. First, the role of social learning in the development of feeding and foraging behavior in young chicks and older birds is described. The role of the hen as a demonstrator and possible teacher is considered, and the subsequent social influence of brood mates and other companions on food avoidance and food preference learning is discussed. Second, the way in which work on domestic fowl has contributed to an understanding of the importance of directed social learning is examined. The well-characterized hierarchical social organization of small chicken flocks has been used to design studies which demonstrate that the probability of social transmission is strongly influenced by social relationships between birds. The practical implications of understanding the role of social learning in the spread of injurious behaviors in this economically important species are briefly considered.
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Zentall, T. R. (2004). Action imitation in birds. Learn Behav, 32(1), 15–23.
Abstract: Action imitation, once thought to be a behavior almost exclusively limited to humans and the great apes, surprisingly also has been found in a number of bird species. Because imitation has been viewed by some psychologists as a form of intelligent behavior, there has been interest in how it is distributed among animal species. Although the mechanisms responsible for action imitation are not clear, we are now at least beginning to understand the conditions under which it occurs. In this article, I try to identify and differentiate the various forms of socially influenced behavior (species-typical social reactions, social effects on motivation, social effects on perception, socially influenced learning, and action imitation) and explain why it is important to differentiate imitation from other forms of social influence. I also examine some of the variables that appear to be involved in the occurrence of imitation. Finally, I speculate about why a number of bird species, but few mammal species, appear to imitate.
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Gibson, B. M., & Shettleworth, S. J. (2003). Competition among spatial cues in a naturalistic food-carrying task. Learn Behav, 31(2), 143–159.
Abstract: Rats collected nuts from a container in a large arena in four experiments testing how learning about a beacon or cue at a goal interacts with learning about other spatial cues (place learning). Place learning was quick, with little evidence of competition from the beacon (Experiments 1 and 2). Rats trained to approach a beacon regardless of its location were subsequently impaired when the well-learned beacon was removed and other spatial cues identified the location of the goal (Experiment 3). The competition between beacon and place cues reflected learned irrelevance for place cues (Experiment 4). The findings differ from those of some studies of associative interactions between cue and place learning in other paradigms.
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Fragaszy, D., & Visalberghi, E. (2004). Socially biased learning in monkeys. Learn Behav, 32(1), 24–35.
Abstract: We review socially biased learning about food and problem solving in monkeys, relying especially on studies with tufted capuchin monkeys (Cebus apella) and callitrichid monkeys. Capuchin monkeys most effectively learn to solve a new problem when they can act jointly with an experienced partner in a socially tolerant setting and when the problem can be solved by direct action on an object or substrate, but they do not learn by imitation. Capuchin monkeys are motivated to eat foods, whether familiar or novel, when they are with others that are eating, regardless of what the others are eating. Thus, social bias in learning about foods is indirect and mediated by facilitation of feeding. In most respects, social biases in learning are similar in capuchins and callitrichids, except that callitrichids provide more specific behavioral cues to others about the availability and palatability of foods. Callitrichids generally are more tolerant toward group members and coordinate their activity in space and time more closely than capuchins do. These characteristics support stronger social biases in learning in callitrichids than in capuchins in some situations. On the other hand, callitrichids' more limited range of manipulative behaviors, greater neophobia, and greater sensitivity to the risk of predation restricts what these monkeys learn in comparison with capuchins. We suggest that socially biased learning is always the collective outcome of interacting physical, social, and individual factors, and that differences across populations and species in social bias in learning reflect variations in all these dimensions. Progress in understanding socially biased learning in nonhuman species will be aided by the development of appropriately detailed models of the richly interconnected processes affecting learning.
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Whiten, A., Horner, V., Litchfield, C. A., & Marshall-Pescini, S. (2004). How do apes ape? Learn. Behav., 32(1), 36–52.
Abstract: In the wake of telling critiques of the foundations on which earlier conclusions were based, the last 15 years have witnessed a renaissance in the study of social learning in apes. As a result, we are able to review 31 experimental studies from this period in which social learning in chimpanzees, gorillas, and orangutans has been investigated. The principal question framed at the beginning of this era, Do apes ape? has been answered in the affirmative, at least in certain conditions. The more interesting question now is, thus, How do apes ape? Answering this question has engendered richer taxonomies of the range of social-learning processes at work and new methodologies to uncover them. Together, these studies suggest that apes ape by employing a portfolio of alternative social-learning processes in flexibly adaptive ways, in conjunction with nonsocial learning. We conclude by sketching the kind of decision tree that appears to underlie the deployment of these alternatives.
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Leadbeater, E. (2015). What evolves in the evolution of social learning? J Zool, 295(1), 4–11.
Abstract: Social learning is fundamental to social life across the animal kingdom, but we still know little about how natural selection has shaped social learning abilities on a proximate level. Sometimes, complex social learning phenomena can be entirely explained by Pavlovian processes that have little to do with the evolution of sociality. This implies that the ability to learn socially could be an exaptation, not an adaptation, to social life but not that social learning abilities have been left untouched by natural selection. I discuss new empirical evidence for associative learning in social information use, explain how natural selection might facilitate the associative learning process and discuss why such studies are changing the way that we think about social learning.
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McGreevy, P. D., & McLean, A. N. (2007). Roles of learning theory and ethology in equitation. Journal of Veterinary Behavior: Clinical Applications and Research, 2(4), 108–118.
Abstract: By definition, ethology is primarily the scientific study of animal behavior, especially as it occurs in a natural environment; applied ethology being the study of animal behavior in the human domain. The terms equine ethology and ethological training are becoming commonplace in the equestrian domain, yet they seem to be used with a conspicuous lack of clarity and with no mention of learning theory. Most of what we do to train horses runs counter to their innate preferences. This article summarizes the ethological challenges encountered by working horses and considers the merits and limitations of ethological solutions. It also questions the use of terms such as “alpha” and “leader” and examines aspects of learning theory, equine cognition, and ethology as applied to horse training and clinical behavior modification. We propose 7 training principles that optimally account for the horse's ethological and learning abilities and maintain maximal responsivity in the trained horse. These principles can be summarized as: (1) use learning theory appropriately; (2) train easy-to-discriminate signals; (3) train and subsequently elicit responses singularly; (4) train only one response per signal; (5) train all responses to be initiated and subsequently completed within a consistent structure; (6) train persistence of current operantly conditioned responses; and (7) avoid and disassociate flight responses. Adherence to these principles and incorporating them into all horse training methodologies should accelerate training success, reduce behavioral wastage of horses, and improve safety for both humans and horses.
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