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Schmoldt, A., Benthe, H. F., & Haberland, G. (1975). Digitoxin metabolism by rat liver microsomes. Biochem Pharmacol, 24(17), 1639–1641.
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Alexander, F., & Davies, M. E. (1969). Studies on vitamin B12 in the horse. Br. Vet. J., 125(4), 169–176.
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Weik, H., & Altmann, J. (1972). The effect of L(+)-lactate on rat and horse adipose tissue in vitro. Zentralbl Veterinarmed A, 19(6), 514–518.
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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.
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Beckers, T., Miller, R. R., De Houwer, J., & Urushihara, K. (2006). Reasoning rats: forward blocking in Pavlovian animal conditioning is sensitive to constraints of causal inference. J Exp Psychol Gen, 135(1), 92–102.
Abstract: Forward blocking is one of the best-documented phenomena in Pavlovian animal conditioning. According to contemporary associative learning theories, forward blocking arises directly from the hardwired basic learning rules that govern the acquisition or expression of associations. Contrary to this view, here the authors demonstrate that blocking in rats is flexible and sensitive to constraints of causal inference, such as violation of additivity and ceiling considerations. This suggests that complex cognitive processes akin to causal inferential reasoning are involved in a well-established Pavlovian animal conditioning phenomenon commonly attributed to the operation of basic associative processes.
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Zentall, T. R. (2006). Mental time travel in animals: a challenging question. Behav. Process., 72(2), 173–183.
Abstract: Humans have the ability to mentally recreate past events (using episodic memory) and imagine future events (by planning). The best evidence for such mental time travel is personal and thus subjective. For this reason, it is particularly difficult to study such behavior in animals. There is some indirect evidence, however, that animals have both episodic memory and the ability to plan for the future. When unexpectedly asked to do so, animals can report about their recent past experiences (episodic memory) and they also appear to be able to use the anticipation of a future event as the basis for a present action (planning). Thus, the ability to imagine past and future events may not be uniquely human.
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Zentall, T. R., & Kaiser, D. H. (2005). Interval timing with gaps: gap ambiguity as an alternative to temporal decay. J Exp Psychol Anim Behav Process, 31(4), 484–486.
Abstract: C. V. Buhusi, D. Perera, and W. H. Meck (2005) proposed a hypothesis of timing in rats to account for the results of experiments that have used the peak procedure with gaps. According to this hypothesis, the introduction of a gap causes the animal's memory for the pregap interval to passively decay (subjectively shorten) in direct proportion to the duration and salience of the gap. Thus, animals should pause with short, nonsalient gaps but should reset their clock with longer, salient gaps. The present authors suggest that the ambiguity of the gap (i.e., the similarity between the gap and the intertrial interval in both appearance and relative duration) causes the animal to actively reset the clock and prevents adequate assessments of the fate of timed intervals prior to the gap. Furthermore, when the intertrial interval is discriminable from the gap, the evidence suggests that timed intervals prior to the gap are not lost but are retained in memory.
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Zentall, T. R., & Riley, D. A. (2000). Selective attention in animal discrimination learning. J Gen Psychol, 127(1), 45–66.
Abstract: The traditional approach to the study of selective attention in animal discrimination learning has been to ask if animals are capable of the central selective processing of stimuli, such that certain aspects of the discriminative stimuli are partially or wholly ignored while their relationships to each other, or other relevant stimuli, are processed. A notable characteristic of this research has been that procedures involve the acquisition of discriminations, and the issue of concern is whether learning is selectively determined by the stimulus dimension defined by the discriminative stimuli. Although there is support for this kind of selective attention, in many cases, simpler nonattentional accounts are sufficient to explain the results. An alternative approach involves procedures more similar to those used in human information-processing research. When selective attention is studied in humans, it generally involves the steady state performance of tasks for which there is limited time allowed for stimulus input and a relatively large amount of relevant information to be processed; thus, attention must be selective or divided. When this approach is applied to animals and alternative accounts have been ruled out, stronger evidence for selective or divided attention in animals has been found. Similar processes are thought to be involved when animals search more natural environments for targets. Finally, an attempt is made to distinguish these top-down attentional processes from more automatic preattentional processes that have been studied in humans and other animals.
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Henning, J. M., & Zentall, T. R. (1981). Imitation, social facilitation, and the effects of ACTH 4-10 on rats' bar-pressing behavior. Am J Psychol, 94(1), 125–134.
Abstract: The effects of ACTH 4-10 on rats' imitation learning was examined during the acquisition and extinction of a bar-press response for water reinforcement. Rats were exposed to either a bar-pressing conspecific (OB), an experimentally naive conspecific (ON), or an empty box (OE) during bar-press acquisition. In a factorial design, each rat was then exposed to one of the same three conditions during extinction. An 80 mcg dose of ACTH 4-10 was administered to half of the rats in each group prior to observation. Performance differences during acquisition were generally small, but significant performance differences during extinction were found. Social facilitation was indicated by the finding that rats extinguished in the presence of a conspecific exhibited significantly greater resistance to extinction than rats extinguished in the presence of an empty box. An imitation effect was also found. Rats that observed a bar-pressing conspecific during both acquisition and extinction (group OB-OB) showed significantly greater resistance top extinction than did groups OB-ON, CB-OE, or OE-OE. There were no significant effects of the hormone, however, relative to saline controls.
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Gibson, B. M., & Shettleworth, S. J. (2005). Place versus response learning revisited: tests of blocking on the radial maze. Behav Neurosci, 119(2), 567–586.
Abstract: 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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