Zuckerman Mind Brain Behavior Institute.
Department of Psychology.
J Exp Psychol Anim Learn Cogn. 2021 Oct;47(4):464-475. doi: 10.1037/xan0000298.
Rhesus macaques, when trained for several hundred trials on adjacent items in an ordered list (e.g., A > B, B > C, C > D), are able to make accurate transitive inferences (TI) about previously untrained pairs (e.g., A > C, B > D). How that learning unfolds during training, however, is not well understood. We sought to measure the relationship between the amount of TI training and the resulting response accuracy in 4 rhesus macaques using seven-item lists. The training conditions included the absolute minimal case of presenting each of the six adjacent pairs only once prior to testing. We also tested transfer to nonadjacent pairs with 24 and 114 training trials. Because performance during and after small amounts of training is expected to be near chance levels, we developed a descriptive statistical model to estimate potentially subtle learning effects in the presence of much larger random response variability and systematic bias. These results suggest that subjects learned serial order in an incremental fashion. Thus, rather than performing transitive inference by a logical process, serial learning in rhesus macaques proceeds in a manner more akin to a statistical inference, with an initial uncertainty about list position that gradually becomes more accurate as evidence accumulates. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
恒河猴在经过数百次针对有序列表中相邻项目的训练后(例如,A>B,B>C,C>D),能够对之前未经训练的项目进行准确的传递性推理(TI)(例如,A>C,B>D)。然而,这种学习是如何展开的还不太清楚。我们使用七项列表,试图在四只恒河猴身上测量 TI 训练量与由此产生的反应准确率之间的关系。训练条件包括在测试前仅对每个相邻的六个项目各呈现一次的绝对最小案例。我们还测试了有 24 次和 114 次训练的非相邻对的转移。因为在训练量较少的情况下的表现预计接近随机水平,所以我们开发了一个描述性统计模型来估计在存在更大的随机反应变异性和系统偏差的情况下可能存在的微妙学习效果。这些结果表明,被试以增量的方式学习了序列顺序。因此,恒河猴的序列学习不是通过逻辑过程进行传递性推理,而是更类似于统计推理,最初对列表位置的不确定性随着证据的积累而逐渐变得更加准确。