Murdock Bennet
Department of Psychology, University of Toronto, Toronto, Ontario M5S 3G3, Canada.
Psychol Rev. 2006 Jul;113(3):648-56. doi: 10.1037/0033-295X.113.3.648.
The sum-difference theory of remembering and knowing (STREAK) provides a sophisticated account of many interactions in the remember-know (R-K) area (C. M. Rotello, N. A. Macmillan, & J. A. Reeder, 2004). It assumes 2 orthogonal strength dimensions and oblique criterion planes. Another dual-process model (J. T. Wixted & V. Stretch, 2004) with one decision axis has also been applied to R-K judgments with considerable success and provides new insights into the processes involved. An analysis of the 4 major R-K interactions can also be explained by a simpler one-dimensional signal detection theory (J. C. Dunn, 2004a). However these models do not make contact with standard work on recognition memory, so their scope is limited. To bridge this gap, a global-matching model (a theory of distributed associative memory [TODAM]) for R-K judgments is proposed. This model can produce good fits to the data, and there are established experimental manipulations with which to test it. It provides further support for the idea that R judgments are based on associative information, whereas K judgments are based on item information.
记忆与知晓的和差理论（STREAK）对记忆-知晓（R-K）领域中的诸多相互作用给出了一种复杂的解释（C.M. 罗泰洛、N.A. 麦克米伦和J.A. 里德，2004年）。该理论假定存在两个正交的强度维度和倾斜的标准平面。另一个具有单一决策轴的双加工模型（J.T. 威克斯泰德和V. 斯特雷奇，2004年）也已被应用于R-K判断，并取得了相当大的成功，且为其中涉及的过程提供了新的见解。对四种主要的R-K相互作用的分析也可以用一种更简单的一维信号检测理论来解释（J.C. 邓恩，2004a）。然而，这些模型并未与识别记忆的标准研究相联系，因此其范围有限。为弥合这一差距，本文提出了一种用于R-K判断的全局匹配模型（一种分布式联想记忆理论[TODAM]）。该模型能够很好地拟合数据，并且有既定的实验操作来对其进行检验。它进一步支持了这样一种观点，即R判断基于联想信息，而K判断基于项目信息。
