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Miller and Shettleworth (2007) used an associative model of instrumental choice to explain a confusing pattern of results in the geometry learning literature. Dupuis and Dawson (in press) identified a structural flaw in the Miller-Shettleworth (MS) model and suggested replacing it with an operant perceptron model which can correctly reproduce some experimental results that the MS model does not. Here we demonstrate that the error in the MS model can be easily corrected without altering any of the model's predictions by making it stochastic rather than deterministic. In addition, we show that the raw outputs of the perceptron model cannot be interpreted as discriminative choices in an instrumental task without first being normalized. We show that this additional step renders the results of the perceptron model identical to those of the MS model in exactly those cases in which it has been claimed to correctly predict results that the latter cannot.

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We cannot test animals for insight's distinctive phenomenology, the "aha" experience, but we can study the processes underlying insightful behaviour, classically described by Köhler as sudden solution of a problem after an impasse. The central question in the study of insightful behaviour in any species is whether it is the product of a distinctive cognitive process, insight. Although some claims for insight in animals confuse it with other problem-solving processes, contemporary research on string pulling and other physical problems, primarily with birds, has uncovered new examples of insightful behaviour and shed light on the role of experience in producing it. New research suggests insightful behaviour can be captured in common laboratory tasks while brain activity is monitored, opening the way to better integration of research on animals with the cognitive neuroscience of human insight.

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Darwin's claim 'that the difference in mind between man and the higher animals … is certainly one of degree and not of kind' is at the core of the comparative study of cognition. Recent research provides unprecedented support for Darwin's claim as well as new reasons to question it, stimulating new theories of human cognitive uniqueness. This article compares and evaluates approaches to such theories. Some prominent theories propose sweeping domain-general characterizations of the difference in cognitive capabilities and/or mechanisms between adult humans and other animals. Dual-process theories for some cognitive domains propose that adult human cognition shares simple basic processes with that of other animals while additionally including slower-developing and more explicit uniquely human processes. These theories are consistent with a modular account of cognition and the 'core knowledge' account of children's cognitive development. A complementary proposal is that human infants have unique social and/or cognitive adaptations for uniquely human learning. A view of human cognitive architecture as a mosaic of unique and species-general modular and domain-general processes together with a focus on uniquely human developmental mechanisms is consistent with modern evolutionary-developmental biology and suggests new questions for comparative research.

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From the process of organic evolution to the analysis of insect societies as self-organizing systems, biology is full of awe-inspiring examples of complexity arising from simplicity. Yet in the contemporary study of animal cognition, demonstrations that complex human-like behavior arises from simple mechanisms rather than from 'higher' processes, such as insight or theory of mind, are often seen as uninteresting and 'killjoy', almost a denial of mental continuity between other species and humans. At the same time, however, research elsewhere in psychology increasingly reveals an unexpected role in human behavior for simple, unconscious and sometimes irrational processes shared by other animals. Greater appreciation of such mechanisms in nonhuman species would contribute to a deeper, more truly comparative psychology.

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A new study of how experience contributes to apparently insightful problem-solving by tool-using crows has shown that operating an apparatus with the beak or a stick promotes novel use of stones on the same apparatus.

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In "The Snark is a Boojum", Beach [Beach, F.A., 1950. The snark was a boojum. American Psychologist. 5, 115-124] famously asserted that animal psychology embraced too few species and too few problems to deserve the name comparative. Later in the 20th century, others [e.g. Kamil, A.C., 1988. A synthetic approach to the study of animal intelligence. In: Leger, D.W. (Ed.), Comparative Perspectives in Modern Psychology. Nebraska Symposium on Motivation, vol. 35. University of Nebraska Press, Lincoln, NE, pp. 230-257; Shettleworth, S.J., 1993. Where is the comparison in comparative cognition? Alternative research programs. Psychological Science. 4, 179-184] expressed similar concerns about the new subfield of comparative cognition, suggesting that a more biological approach to choice of species and problems was needed to balance a dominant anthropocentrism. The last 10-15 years have seen many new developments, and a recent survey like Beach's reveals a very different picture. Not only are many more species being studied, contributions by researchers from different backgrounds are increasing, and research on comparative cognition is better connected with developmental psychology, behavioral neuroscience, primatology, behavioral ecology, and other fields. Contemporary research addresses three major aspects of cognition about equally: basic processes, physical cognition, and social cognition. This article describes a selected research program from each area, chosen to exemplify current trends and challenges for the field.

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In a recent article, the authors (Miller & Shettleworth, 2007) showed how the apparently exceptional features of behavior in geometry learning ("reorientation") experiments can be modeled by assuming that geometric and other features at given locations in an arena are learned competitively as in the Rescorla-Wagner model and that the probability of visiting a location is proportional to the total associative strength of cues at that location relative to that of all relevant locations. Reinforced or unreinforced visits to locations drive changes in associative strengths. Dawson, Kelly, Spetch, and Dupuis (2008) have correctly pointed out that at parameter values outside the ranges the authors used to simulate a body of real experiments, our equation for choice probabilities can give impossible and/or wildly fluctuating results. Here, the authors show that a simple modification of the choice rule eliminates this problem while retaining the transparent way in which the model relates spatial choice to competitive associative learning of cue values.

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Metamemory, the ability to report on memory strength, is clearly established in rhesus macaques (Macaca mulatta) by converging evidence from several paradigms. In contrast, A. Inman and S. J. Shettleworth (1999) found no conclusive evidence of metamemory in pigeons. The authors studied pigeons further in 3 paradigms, with multiple tests of metamemory in each. Pigeons encountered a safe alternative to a matching-to-sample test either before (Experiment 2) or concurrently with (Experiment 3) the matching test. Choices of the safe option did not vary consistently with matching accuracy or change in trials with omitted samples in the way predicted for an animal with metamemory. In Experiment 4, confidence ratings following completion of the matching test also did not vary consistently as predicted by metamemory.

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K. Cheng (1986) suggested that learning the geometry of enclosing surfaces takes place in a geometric module blind to other spatial information. Failures to find blocking or overshadowing of geometry learning by features near a goal seem consistent with this view. The authors present an operant model in which learning spatial features competes with geometry learning, as in the Rescorla-Wagner model. Relative total associative strength of cues at a location determines choice of that location and thus the frequencies of reward paired with each cue. The model shows how competitive learning of local features and geometry can appear to result in potentiation, blocking, or independence, depending on enclosure shape and kind of features. The model reproduces numerous findings from dry arenas and water mazes.

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Spatial judgments and actions are often based on multiple cues. The authors review a multitude of phenomena on the integration of spatial cues in diverse species to consider how nearly optimally animals combine the cues. Under the banner of Bayesian perception, cues are sometimes combined and weighted in a near optimal fashion. In other instances when cues are combined, how optimal the integration is might be unclear. Only 1 cue may be relied on, or cues may seem to compete with one another. The authors attempt to bring some order to the diversity by taking into account the subjective discrepancy in the dictates of multiple cues. When cues are too discrepant, it may be best to rely on 1 cue source. When cues are not too discrepant, it may be advantageous to combine cues. Such a dual principle provides an extended Bayesian framework for understanding the functional reasons for the integration of spatial cues.

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The authors report a novel approach to testing episodic-like memory for single events. Pigeons were trained in separate sessions to match the identity of a sample on a touch screen, to match its location, and to report on the length of the retention interval. When these 3 tasks were mixed randomly within sessions, birds were more than 80% correct on each task. However, performance on 2 different tests in succession after each sample was not consistent with an integrated memory for sample location, time, and identity. Experiment 2 tested binding of location and identity memories in 2 different ways. The results were again consistent with independent feature memories. Implications for tests of episodic-like memory are discussed.

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We investigated the potential relationships between foraging strategies and relative brain and brain region volumes in predatory (animal-eating) echolocating bats. The species we considered represent the ancestral state for the order and approximately 70% of living bat species. The two dominant foraging strategies used by echolocating predatory bats are substrate-gleaning (taking prey from surfaces) and aerial hawking (taking airborne prey). We used species-specific behavioral, morphological, and ecological data to classify each of 59 predatory species as one of the following: (1) ground gleaning, (2) behaviorally flexible (i.e., known to both glean and hawk prey), (3) clutter tolerant aerial hawking, or (4) open-space aerial hawking. In analyses using both species level data and phylogenetically independent contrasts, relative brain size was larger in behaviorally flexible species. Further, relative neocortex volume was significantly reduced in bats that aerially hawk prey primarily in open spaces. Conversely, our foraging behavior index did not account for variability in hippocampus and inferior colliculus volume and we discuss these results in the context of past research.

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The relative importance of an internal sense of direction based on inertial cues and landmark piloting for small-scale navigation by White King pigeons (Columba livia) was investigated in an arena search task. Two groups of pigeons differed in whether they had access to visual cues outside the arena. In Experiment 1, pigeons were given experience with 2 different entrances and all pigeons transferred accurate searching to novel entrances. Explicit disorientation before entering did not affect accuracy. In Experiments 2-4, landmarks and inertial cues were put in conflict or tested 1 at a time. Pigeons tended to follow the landmarks in a conflict situation but could use an internal sense of direction to search when landmarks were unavailable.

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Rats homed with food in a large lighted arena. Without visual cues, they used dead reckoning. When a beacon indicated the home, rats could also use the beacon. Homing did not differ in 2 groups of rats, 1 provided with the beacon and 1 without it; tests without the beacon gave no evidence that beacon learning overshadowed dead reckoning (Experiment 1). When the beacon was at the home for 1 group and in random locations for another, there was again no evidence of cue competition (Experiment 2). Dead reckoning experience did not block acquisition of beacon homing (Experiment 3). Beacon learning and dead reckoning do not compete for predictive value but acquire information in parallel and are used hierarchically.

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Six experiments using habituation of exploratory behavior tested whether disoriented rats foraging in a large arena encode the shapes of arrays of objects. Rats did not respond to changes in position of a single object, but they responded to a change in object color and to a change in position of 1 object in a square array, as in previous research (e.g., C. Thinus-Blanc et al., 1987). Rats also responded to an expansion of a square array, suggesting that they encoded sets of interobject distances rather than overall shape. In Experiments 4-6, rats did not respond to changes in sense of a triangular array that maintained interobject distances and angles. Shapes of object arrays are encoded differently from shapes of enclosures.

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Neurobiological and behavioral research indicates that place learning and response learning occur simultaneously, in parallel. Such findings seem to conflict with theories of associative learning in which different cues compete for learning. The authors conducted place+response training on a radial maze and then tested place learning and response learning separately by reconfiguring the maze in various ways. Consistent with the effects of manipulating place and response systems in the brain (M. G. Packard & J. L. McGaugh, 1996), well-trained rats showed strong place learning and strong response learning. Three experiments using associative blocking paradigms indicated that prior response learning interferes with place learning. Blocking and related tests can be used to better understand how memory systems interact during learning.

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