Department of Psychology, George Mason UniversityDepartment of Psychology, Carnegie Mellon University.
Cogn Sci. 2005 Jul 8;29(4):627-54. doi: 10.1207/s15516709cog0000_16.
Four pairs of connectionist simulations are presented in which quasi-regular mappings are computed using localist and distributed representations. In each simulation, a control parameter termed input gain was modulated over the only level of representation that mapped inputs to outputs. Input gain caused both localist and distributed models to shift between regularity-based and item-based modes of processing. Performance on irregular items was selectively impaired in the regularity-based modes, whereas performance on novel items was selectively impaired in the item-based modes. Thus, the models exhibited double dissociations without separable processing components. These results are discussed in the context of analogous dissociations found in language domains such as word reading and inflectional morphology.
本文提出了四对连接主义模拟，其中使用局域和分布式表示来计算准正则映射。在每个模拟中，一个称为输入增益的控制参数在唯一的表示层次上进行调制，该层次将输入映射到输出。输入增益使局域和分布式模型在基于规则和基于项目的处理模式之间转换。在基于规则的模式下，不规则项目的表现受到选择性损害，而在基于项目的模式下，新的项目的表现受到选择性损害。因此，这些模型表现出没有可分离处理成分的双重分离。这些结果在类似的语言领域，如单词阅读和屈折形态学中发现的分离中进行了讨论。
