不同类别学习任务的差异

The Difference of Category-Learning Tasks

多重类别学习系统观点的提出和认知神经科学的研究进展使分类研究在过去十年中有了根本性的改变，文章运用多重类别学习系统的观点和认知神经科学的相关研究结果，从构造方式、理论解释和神经心理基础几个方面对类别学习研究中通常采用的四种类别学习任务——基于规则的任务、信息整合任务、原型变式任务和天气预报任务的差异进行了梳理和区分。基于规则的任务依赖于前扣带回，需要工作记忆和执行注意的参与；信息整合任务学习实质上是一种内隐程序学习；“A，非A”原型变式任务诱发视皮层的知觉学习；天气预报任务存在各种不同的接近最佳反应的学习策略。

The past decade has seen two fundamental changes in categorization research. The article link this two aspect—multiple category learning systems and cognitive neuroscience， introduce and analysis four different kinds of category-learning tasks: rule-based tasks， information-integration tasks， prototype distortion tasks， and the weather prediction task， that are currently popular in the study of human perceptual categories learning. The article suggests that when interpreting a category-learning result， it is critical to consider carefully the specific task has been used in the research， this would help us comprehending those apparently contradictory results.