Lingawi Nura W, Andrew Elpiniki, Laurent Vincent, Killcross Simon, Westbrook R Frederick, Holmes Nathan M
School of Psychology, University of New South Wales, Sydney, NSW 2052, Australia.
Neurobiol Learn Mem. 2018 Dec;156:53-59. doi: 10.1016/j.nlm.2018.10.009. Epub 2018 Oct 22.
People and animals sometimes associate events that never occurred together. These false memories can have disastrous consequences, yet little is known about the conditions under which they form. In four experiments, we investigated how rats learn to fear a context in which they have never experienced danger (i.e., how they form a false context fear memory). In each experiment, rats were pre-exposed to a context on day 1, shocked in a similar-but-different context on day 2, and tested in the pre-exposed or explicitly-conditioned context on day 3. The results revealed that: (1) the true memory of the explicitly-conditioned context and false memory of the pre-exposed context develop simultaneously and independently; and (2) the conditions of pre-exposure on day 1 and time of shock exposure on day 2 interact to determine the strength of the false memory. These findings are anticipated by a recent computational model, the Bayesian Context Fear Algorithm/Automaton (BACON; Krasne, Cushman, & Fanselow, 2015). They are discussed in relation to this model and more general theories of context learning.
人和动物有时会将从未同时发生过的事件联系起来。这些错误记忆可能会带来灾难性后果,但对于它们形成的条件却知之甚少。在四项实验中,我们研究了大鼠如何学会害怕一个它们从未经历过危险的环境(即它们如何形成错误的环境恐惧记忆)。在每项实验中,大鼠在第1天被预先暴露于一个环境中,在第2天在一个相似但不同的环境中受到电击,并在第3天在预先暴露或明确条件化的环境中进行测试。结果显示:(1)明确条件化环境的真实记忆和预先暴露环境的错误记忆同时且独立地发展;(2)第1天的预先暴露条件和第2天的电击暴露时间相互作用,以确定错误记忆的强度。最近的一个计算模型,即贝叶斯环境恐惧算法/自动机(BACON;Krasne、Cushman和Fanselow,2015)预测了这些发现。我们将结合这个模型以及更一般的环境学习理论来讨论这些发现。