Maddox W T, Filoteo J V
Department of Psychology, University of Texas, Austin 78712, USA.
J Int Neuropsychol Soc. 2001 Sep;7(6):710-27. doi: 10.1017/s1355617701766076.
The contribution of the striatum to category learning was examined by having patients with Parkinson's disease (PD) and matched controls solve categorization problems in which the optimal rule was linear or nonlinear using the perceptual categorization task. Traditional accuracy-based analyses, as well as quantitative model-based analyses were performed. Unlike accuracy-based analyses, the model-based analyses allow one to quantify and separate the effects of categorization rule learning from variability in the trial-by-trial application of the participant's rule. When the categorization rule was linear, PD patients showed no accuracy, categorization rule learning, or rule application variability deficits. Categorization accuracy for the PD patients was associated with their performance on a test believed to be sensitive to frontal lobe functioning. In contrast, when the categorization rule was nonlinear, the PD patients showed accuracy, categorization rule learning, and rule application variability deficits. Furthermore, categorization accuracy was not associated with performance on the test of frontal lobe functioning. Implications for neuropsychological theories of categorization learning are discussed.
通过让帕金森病（PD）患者和匹配的对照组使用感知分类任务解决分类问题，其中最优规则为线性或非线性，研究了纹状体对类别学习的贡献。进行了传统的基于准确性的分析以及基于定量模型的分析。与基于准确性的分析不同，基于模型的分析允许人们量化并区分分类规则学习的影响与参与者规则在逐次试验应用中的变异性。当分类规则为线性时，PD患者在准确性、分类规则学习或规则应用变异性方面没有缺陷。PD患者的分类准确性与他们在一项被认为对额叶功能敏感的测试中的表现相关。相比之下，当分类规则为非线性时，PD患者在准确性、分类规则学习和规则应用变异性方面存在缺陷。此外，分类准确性与额叶功能测试的表现无关。讨论了对类别学习神经心理学理论的启示。
