Sage Jennifer R, Anagnostaras Stephan G, Mitchell Shawn, Bronstein Jeff M, De Salles Antonio, Masterman Donna, Knowlton Barbara J
Department of Psychology, University of California, Los Angeles, California 90095, USA.
Learn Mem. 2003 May-Jun;10(3):226-36. doi: 10.1101/lm.45903.
This study examined the characteristics of probabilistic classification learning, a form of implicit learning previously shown to be impaired in patients with basal ganglia dysfunction (e.g., Parkinson's disease). In this task, subjects learn to predict the weather using associations that are formed gradually across many trials, because of the probabilistic nature of the cue-outcome relationships. Patients with Parkinson's disease, both before and after pallidotomy, and age-matched control subjects, exhibited evidence of probabilistic classification learning across 100 training trials. However, pallidotomy appears to hinder the learning of associations most implicit in nature (i.e., weakly associated cues). Although subjects were most sensitive to single-cue associations when learning the task, there is evidence that cue combinations contribute significantly to probability learning. The utility of multiple dependent measures is discussed.
本研究考察了概率分类学习的特征，概率分类学习是一种内隐学习形式，先前研究表明基底神经节功能障碍患者（如帕金森病患者）在这种学习形式上存在缺陷。在该任务中，由于线索与结果关系的概率性质，受试者通过在多次试验中逐渐形成的关联来学习预测天气。帕金森病患者在苍白球切开术前和术后，以及年龄匹配的对照受试者，在100次训练试验中均表现出概率分类学习的证据。然而，苍白球切开术似乎会阻碍本质上最内隐的关联学习（即弱关联线索）。虽然受试者在学习任务时对单一线索关联最为敏感，但有证据表明线索组合对概率学习有显著贡献。本文还讨论了多种相关测量方法的效用。
