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Cheng, K., & Wignall, A. E. (2006). Honeybees (Apis mellifera) holding on to memories: response competition causes retroactive interference effects. Anim. Cogn., 9(2), 141–150.
Abstract: Five experiments on honeybees examined how the learning of a second task interferes with what was previously learned. Free flying bees were tested for landmark-based memory in variations on a paradigm of retroactive interference. Bees first learned Task 1, were tested on Task 1 (Test 1), then learned Task 2, and were tested again on Task 1 (Test 2). A 60-min delay (waiting in a box) before Test 2 caused no performance decrements. If the two tasks had conflicting response requirements, (e.g., target right of a green landmark in Task 1 and left of a blue landmark in Task 2), then a strong decrement on Test 2 was found (retroactive interference effect). When response competition was minimised during training or testing, however, the decrement on Test 2 was small or nonexistent. The results implicate response competition as a major contributor to the retroactive interference effect. The honeybee seems to hold on to memories; new memories do not wipe out old ones.
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Cheng, K. (2004). K.J. Jeffery (ed) The neurobiology of spatial behaviourOxford University Press, Oxford, 2003. Anim. Cogn., .
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Cheng, K. (2004). K.J. Jeffery (ed) The neurobiology of spatial behaviour. Anim. Cogn., 7(3), 199–200.
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Cheng, K. (2002). Generalisation: mechanistic and functional explanations. Anim. Cogn., 5(1), 33–40.
Abstract: An overview of mechanistic and functional accounts of stimulus generalisation is given. Mechanistic accounts rely on the process of spreading activation across units representing stimuli. Different models implement the spread in different ways, ranging from diffusion to connectionist networks. A functional account proposed by Shepard analyses the probabilistic structure of the world for invariants. A universal law based on one such invariant claims that under a suitable scaling of the stimulus dimension, generalisation gradients should be approximately exponential in shape. Data from both vertebrates and invertebrates so far uphold Shepard's law. Some data on spatial generalisation in honeybees are presented to illustrate how Shepard's law can be used to determine the metric for combining discrepancies in different stimulus dimensions. The phenomenon of peak shift is discussed. Comments on mechanistic and functional approaches to generalisation are given.
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