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Blaisdell, A. P., Sawa, K., Leising, K. J., & Waldmann, M. R. (2006). Causal reasoning in rats. Science, 311(5763), 1020–1022.
Abstract: Empirical research with nonhuman primates appears to support the view that causal reasoning is a key cognitive faculty that divides humans from animals. The claim is that animals approximate causal learning using associative processes. The present results cast doubt on that conclusion. Rats made causal inferences in a basic task that taps into core features of causal reasoning without requiring complex physical knowledge. They derived predictions of the outcomes of interventions after passive observational learning of different kinds of causal models. These competencies cannot be explained by current associative theories but are consistent with causal Bayes net theories.
Keywords: Animals; *Association Learning; Bayes Theorem; *Cognition; Comprehension; Forecasting; Male; Rats; Rats, Long-Evans
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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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Pickens, C. L., & Holland, P. C. (2004). Conditioning and cognition. Neurosci Biobehav Rev, 28(7), 651–661.
Abstract: Animals' abilities to use internal representations of absent objects to guide adaptive behavior and acquire new information, and to represent multiple spatial, temporal, and object properties of complex events and event sequences, may underlie many aspects of human perception, memory, and symbolic thought. In this review, two classes of simple associative learning tasks that address these core cognitive capacities are discussed. The first set, including reinforcer revaluation and mediated learning procedures, address the power of Pavlovian conditioned stimuli to gain access, through learning, to representations of upcoming events. The second set of investigations concern the construction of complex stimulus representations, as illustrated in studies of contextual learning, the conjunction of explicit stimulus elements in configural learning procedures, and recent studies of episodic-like memory. The importance of identifying both cognitive process and brain system bases of performance in animal models is emphasized.
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Moses, S. N., Villate, C., & Ryan, J. D. (2006). An investigation of learning strategy supporting transitive inference performance in humans compared to other species. Neuropsychologia, 44(8), 1370–1387.
Abstract: Generalizations about neural function are often drawn from non-human animal models to human cognition, however, the assumption of cross-species conservation may sometimes be invalid. Humans may use different strategies mediated by alternative structures, or similar structures may operate differently within the context of the human brain. The transitive inference problem, considered a hallmark of logical reasoning, can be solved by non-human species via associative learning rather than logic. We tested whether humans use similar strategies to other species for transitive inference. Results are crucial for evaluating the validity of widely accepted assumptions of similar neural substrates underlying performance in humans and other animals. Here we show that successful transitive inference in humans is unrelated to use of associative learning strategies and is associated with ability to report the hierarchical relationship among stimuli. Our work stipulates that cross-species generalizations must be interpreted cautiously, since performance on the same task may be mediated by different strategies and/or neural systems.
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