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Macphail, E. M. (1996). Cognitive function in mammals: the evolutionary perspective. Brain Res Cogn Brain Res, 3(3-4), 279–290.
Abstract: The work of behavioural pharmacologists has concentrated on small animals, such as rodents and pigeons. The validity of extrapolation of their findings to humans depends upon the existence of parallels in both physiology and psychology between these animals and humans. This paper considers the question whether there are in fact substantial cognitive parallels between, first, different non-human groups of vertebrates and, second, non-humans and humans. Behavioural data from 'simple' tasks, such as habituation and conditioning, do not point to species differences among vertebrates. Using examples that concentrate on the performance of rodents and birds, it is argued that, similarly, data from more complex tasks (learning-set formation, transitive inference, and spatial memory serve as examples) reveal few if any cognitive differences amongst non-human vertebrates. This conclusion supports the notion that association formation may be the critical problem-solving process available to non-human animals; associative mechanisms are assumed to have evolved to detect causal links between events, and would therefore be relevant in all ecological niches. In agreement with this view, recent advances in comparative neurology show striking parallels in functional organisation of mammalian and avian telencephalon. Finally, it is argued that although the peculiarly human capacity for language marks a large cognitive contrast between humans and non-humans, there is good evidence-in particular, from work on implicit learning--that the learning mechanisms available to non--humans are present and do play an important role in human cognition.
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Healy, S., & Braithwaite, V. (2000). Cognitive ecology: a field of substance? Trends. Ecol. Evol, 15(1), 22–26.
Abstract: In 1993, Les Real invented the label 'cognitive ecology'. This label was intended for work that brought cognitive science and behavioural ecology together. Real's article stressed the importance of such an approach to the understanding of behaviour. At the end of a decade in which more interdisciplinary work on behaviour has been seen than for many years, it is time to assess whether cognitive ecology is a label describing an active field.
Keywords: Cognitive ecology; Neuroethology; Cognition; Ecology; Evolution; Orientation mechanisms
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Garamszegi, L. Z., Møller, A. P., & Erritzøe, J. (2002). Coevolving avian eye size and brain size in relation to prey capture and nocturnality. Proc Roy Soc Lond B Biol Sci, 269(1494), 961–967.
Abstract: Behavioural adaptation to ecological conditions can lead to brain size evolution. Structures involved in behavioural visual information processing are expected to coevolve with enlargement of the brain. Because birds are mainly vision–oriented animals, we tested the predictions that adaptation to different foraging constraints can result in eye size evolution, and that species with large eyes have evolved large brains to cope with the increased amount of visual input. Using a comparative approach, we investigated the relationship between eye size and brain size, and the effect of prey capture technique and nocturnality on these traits. After controlling for allometric effects, there was a significant, positive correlation between relative brain size and relative eye size. Variation in relative eye and brain size were significantly and positively related to prey capture technique and nocturnality when a potentially confounding variable, aquatic feeding, was controlled statistically in multiple regression of independent linear contrasts. Applying a less robust, brunching approach, these patterns also emerged, with the exception that relative brain size did not vary with prey capture technique. Our findings suggest that relative eye size and brain size have coevolved in birds in response to nocturnal activity and, at least partly, to capture of mobile prey.
Keywords: adaptation; behaviour; brain size; coevolution; eye size; vision
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Tebbich, S., Bshary, R., & Grutter, A. S. (2002). Cleaner fish Labroides dimidiatus recognise familiar clients. Anim. Cogn., 5(3), 139–145.
Abstract: Individual recognition has been attributed a crucial role in the evolution of complex social systems such as helping behaviour and cooperation. A classical example for interspecific cooperation is the mutualism between the cleaner fish Labroides dimidiatus and its client reef fish species. For stable cooperation to evolve, it is generally assumed that partners interact repeatedly and remember each other's past behaviour. Repeated interactions may be achieved by site fidelity or individual recognition. However, as some cleaner fish have more than 2,300 interactions per day with various individuals per species and various species of clients, basic assumptions of cooperation theory might be violated in this mutualism. We tested the cleaner L. dimidiatus and its herbivorous client, the surgeon fish Ctenochaetus striatus, for their ability to distinguish between a familiar and an unfamiliar partner in a choice experiment. Under natural conditions, cleaners and clients have to build up their relationship, which is probably costly for both. We therefore predicted that both clients and cleaners should prefer the familiar partner in our choice experiment. We found that cleaners spent significantly more time near the familiar than the unfamiliar clients in the first 2 minutes of the experiment. This indicates the ability for individual recognition in cleaners. In contrast, the client C. striatus showed no significant preference. This could be due to a sampling artefact, possibly due to a lack of sufficient motivation. Alternatively, clients may not need to recognise their cleaners but instead remember the defined territories of L. dimidiatus to achieve repeated interactions with the same individual.
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Lefebvre, L., Reader, S. M., & Sol, D. (2004). Brains, Innovations and Evolution in Birds and Primates. Brain. Behav. Evol., 63(4), 233–246.
Abstract: Abstract
Several comparative research programs have focusedon the cognitive, life history and ecological traits thataccount for variation in brain size. We review one ofthese programs, a program that uses the reported frequencyof behavioral innovation as an operational measureof cognition. In both birds and primates, innovationrate is positively correlated with the relative size of associationareas in the brain, the hyperstriatum ventrale andneostriatum in birds and the isocortex and striatum inprimates. Innovation rate is also positively correlatedwith the taxonomic distribution of tool use, as well asinterspecific differences in learning. Some features ofcognition have thus evolved in a remarkably similar wayin primates and at least six phyletically-independent avianlineages. In birds, innovation rate is associated withthe ability of species to deal with seasonal changes in theenvironment and to establish themselves in new regions,and it also appears to be related to the rate atwhich lineages diversify. Innovation rate provides a usefultool to quantify inter-taxon differences in cognitionand to test classic hypotheses regarding the evolution ofthe brain. |
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de Waal, F. B. (1995). Bonobo sex and society. Sci Am, 272(3), 82–88.
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Mulcahy, N. J., & Call, J. (2006). Apes save tools for future use. Science, 312(5776), 1038–1040.
Abstract: Planning for future needs, not just current ones, is one of the most formidable human cognitive achievements. Whether this skill is a uniquely human adaptation is a controversial issue. In a study we conducted, bonobos and orangutans selected, transported, and saved appropriate tools above baseline levels to use them 1 hour later (experiment 1). Experiment 2 extended these results to a 14-hour delay between collecting and using the tools. Experiment 3 showed that seeing the apparatus during tool selection was not necessary to succeed. These findings suggest that the precursor skills for planning for the future evolved in great apes before 14 million years ago, when all extant great ape species shared a common ancestor.
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Watanabe, S., & Huber, L. (2006). Animal logics: decisions in the absence of human language. Anim. Cogn., 9(4), 235–245.
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Pennisi, E. (2006). Animal cognition. Man's best friend(s) reveal the possible roots of social intelligence (Vol. 312).
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Real, L. A. (1991). Animal choice behavior and the evolution of cognitive architecture. Science, 253(5023), 980–986.
Abstract: Animals process sensory information according to specific computational rules and, subsequently, form representations of their environments that form the basis for decisions and choices. The specific computational rules used by organisms will often be evolutionarily adaptive by generating higher probabilities of survival, reproduction, and resource acquisition. Experiments with enclosed colonies of bumblebees constrained to foraging on artificial flowers suggest that the bumblebee's cognitive architecture is designed to efficiently exploit floral resources from spatially structured environments given limits on memory and the neuronal processing of information. A non-linear relationship between the biomechanics of nectar extraction and rates of net energetic gain by individual bees may account for sensitivities to both the arithmetic mean and variance in reward distributions in flowers. Heuristic rules that lead to efficient resource exploitation may also lead to subjective misperception of likelihoods. Subjective probability formation may then be viewed as a problem in pattern recognition subject to specific sampling schemes and memory constraints.
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