Department of Psychological and Brain Sciences, University of Massachusetts, Amherst, MA 01003, U.S.A.
Neural Comput. 2021 Nov 12;33(12):3351-3360. doi: 10.1162/neco_a_01444.
Rizzuto and Kahana (2001) applied an autoassociative Hopfield network to a paired-associate word learning experiment in which (1) participants studied word pairs (e.g., ABSENCE-HOLLOW), (2) were tested in one direction (ABSENCE-?) on a first test, and (3) were tested in the same direction again or in the reverse direction (?-HOLLOW) on a second test. The model contained a correlation parameter to capture the dependence between forward versus backward learning between the two words of a word pair, revealing correlation values close to 1.0 for all participants, consistent with neural network models that use the same weight for communication in both directions between nodes. We addressed several limitations of the model simulations and proposed two new models incorporating retrieval practice learning (e.g., the effect of the first test on the second) that fit the accuracy data more effectively, revealing substantially lower correlation values (average of .45 across participants, with zero correlation for some participants). In addition, we analyzed recall latencies, finding that second test recall was faster in the same direction after a correct first test. Only a model with stochastic retrieval practice learning predicted this effect. In conclusion, recall accuracy and recall latency suggest asymmetric learning, particularly in light of retrieval practice effects.
里祖托和卡哈纳（2001）将自联想霍普菲尔德网络应用于成对联想词学习实验中，其中（1）参与者学习单词对（例如，ABSENCE-HOLLOW），（2）在第一次测试中以一个方向（ABSENCE-？）进行测试，（3）在第二次测试中以相同的方向或相反的方向（？-HOLLOW）进行测试。该模型包含一个相关参数，以捕捉单词对中两个单词之间正向与反向学习之间的依赖关系，所有参与者的相关值接近 1.0，与使用相同权重在节点之间双向进行通信的神经网络模型一致。我们解决了模型模拟的几个限制，并提出了两个新的模型，纳入了检索练习学习（例如，第一次测试对第二次测试的影响），更有效地拟合了准确性数据，显示出显著较低的相关值（参与者平均为.45，有些参与者的相关值为零）。此外，我们分析了回忆潜伏期，发现正确的第一次测试后，在相同的方向上第二次测试的回忆更快。只有具有随机检索实践学习的模型才能预测这种效果。总之，回忆准确性和回忆潜伏期表明存在不对称学习，尤其是在考虑检索实践效果的情况下。
