不同类别学习方式的对比研究

55名被试被随机分配到两个组,分别通过分类学习与推理学习来学习两个类别,之后,两组被试对新的测试项目进行典型性评定,考察类别学习方式对类别表征的影响。研究结果表明,分类学习者仅仅依据项目的诊断性程度来评定,而推理学习者主要依据项目的典型性程度来评定。所以,诊断性信息在分类学习者的类别表征中占有重要位置,典型性信息在推理学习者的类别表征中占有重要位置,即分类学习与推理学习导致的类别表征不同。     

义符促进类别归纳推理的ERP证据

为了明确义符对归纳推理影响,本研究使用有义符和无义符汉字为材料,使用ERP技术考查义符对不同层级类别概念归纳推理的影响。行为结果显示,有义符条件下反应速度更快,肯定判断率更高。脑电指标上,P3阶段义符主效应显著,有义符条件下P3波幅更大;N1、N400和P600阶段义符与层级交互作用显著,组内简单效应分析显示,层级主效应仅在无义符条件下显著;组间简单效应分析显示,义符主效在N400和P600阶段仅在下-上推理条件下显著,无义符条件下,下-上推理引发更大的N400和P600波幅。这些结果表明,义符促进了归纳推理过程,这种促进主要表现在对下-上推理的促进。     

语言表征在颜色类别知觉中的作用

采用同时和继时实验任务,探讨语言表征在颜色类别知觉中的作用.实验一刺激同时呈现,被试表现出类别知觉效应,但效应不受语言干扰影响.实验二刺激间隔呈现,被试表现出类别知觉效应,效应在语言干扰时消失.实验三采用继时任务,没有语言干扰,在刺激呈现间隔(SOA)小于300ms时效应不显著,大于等于300ms时效应显著.研究提示类别知觉效应的机制取决于任务要求和被试无意识的认知策略.在同时任务中效应来自知觉过程本身,在继时任务中效应来自语言编码.继时任务中效应量随SOA变化,说明语言表征由上至下地影响知觉加工,类别知觉是一个动态过程.     

工作记忆对知觉类别学习的影响:问题与构想

人们学习将感知到的客体按照不同的标准或规则分类存储,即类别学习。而工作记忆作为多种认知加工的基础,对类别学习具有重要作用。基于已有研究,分别梳理了言语工作记忆和视空工作记忆对基于规则和信息整合类别结构的影响。目前,执行功能是否影响内隐类别学习系统、工作记忆负荷对内隐外显类别学习系统的影响是否一致还存在争议。此外,工作记忆影响知觉类别学习的认知加工阶段尚不清晰。未来的研究还需明确工作记忆负荷对内隐和外显类别学习的影响,进一步验证工作记忆影响类别学习的认知加工阶段假设的合理性。     

酝酿期有效提示和无效提示的比较

采用中国汉字谜,通过模拟wallas(1926)关于顿悟问题解决的四个阶段,探讨了酝酿期有效提示和无效提示对猜字谜的影响。结果发现：有效提示组被试比无效提示组猜对了更多的靶字谜,反应时也更短;在脑电水平上,酝酿期的有效提示谜比无效提示谜在左前额叶分别于300ms-400ms,400ms-600ms,600ms-800ms内引发了更大的P300-400成分、P400-600成分、P600-800成分。表明有效提示谜比无效提示谜对靶字谜问题的解决有更大促进作用。     

样例呈现方式对概念训练类别表征的影响

以往研究发现训练形式会影响类别学习的表征方式。实验采用学习-迁移范式,探究概念训练中样例的呈现方式对类别表征的影响。实验中被试通过不同呈现方式来学习类别知识,在学习3个block之后对其进行测验。实验结果表明:(1)学习单样例和同一类别比较学习的被试在测验阶段的成绩与学习阶段之间没有差异;(2)学习不同类别比较学习的被试在测验阶段的成绩大幅度下降。因此得出结论,在概念训练中,不同类别比较学习导致被试形成类别间信息的表征。     

类别标签与典型性程度对类别特征推理的影响

本研究采用学习-测试二阶段实验范式,探讨了类别标签及典型性程度对类别特征推理任务的共同影响,结果表明,类别标签及典型性程度都会影响类别特征推理任务,而且,类别标签及典型性程度之间存在交互作用,典型性程度为高条件下类别标签对类别特征推理任务的影响要高于典型性程度为低条件,类别标签匹配条件下,典型性程度对类别特征推理任务的影响要高于类别标签不匹配条件。     

特征呈现方式对类别知觉表征的影响*

两个实验采用阻碍效应范式探讨了特征的呈现方式对类别知觉表征的影响。研究结果发现在阻碍效应范式中,改变特征的呈现方式引发了不同的类别知觉表征方式;当固定样例特征的呈现位置时,引发了基于样例整体相似性的表征;而随机样例特征的呈现位置时,引发了基于样例特征的解析表征。该结果支持了类别学习的多系统理论。     

主题与类属关系的距离对分类和属性推理过程的影响：来自ERP的证据

不同关系类型对归纳推理具有重要的影响,然而主题关系（如,熊猫vs.竹子）与类属关系（如,熊猫vs.羚羊）在归纳推理中的神经机制仍然不清楚。本研究采用事件相关电位（ERP）技术,通过分开呈现属性归纳推理任务中的结论类别和结论属性,探讨两种关系类型及其距离在分类过程和属性推理过程中的ERP特征。结果发现：（1）结论类别呈现阶段,N400（370～500 ms）与LNC（the late negative component）（570～700 ms）时间窗口上,无论是主题关系还是类属关系,远距离比近距离均诱发了更大的负波;前者表明N400与语义整合密切相关,后者说明LNC与语义类别信息违背和假设形成有关。（2）结论属性呈现阶段,主题关系比类属关系诱发了更大的N1;同时,近距离比远距离诱发了更大的N1,反映了类别属性特征的知觉和自动化加工。结果表明：语义类别属性归纳存在距离效应,并且语义关系在属性推理过程中具有不同的加工方式。     

猜谜作业中的ERP效应：基于催化范式的证据

运用ERP技术对个体猜谜任务下的顿悟和无顿悟的情况进行探索。结果发现,在300ms-500ms内,有顿悟比无顿悟引发了更负的N300-500成分,激活了大部分脑区;在600ms-1100ms内,有顿悟比无顿悟引发了更正的P600-1100成分,在中央区显示了最强激活。结果表明,N300-500可能反映了定势破除中的认知冲突,P600-1100可能反映了新异联系的形成。     

Category labels versus feature labels: Category labels polarize inferential predictions

What makes category labels different from feature labels in predictive inference? This study suggests that category labels tend to make inductive reasoning polarized and homogeneous. In two experiments, participants were shown two schematic pictures of insects side by side and predicted the value of a hidden feature of one insect on the basis of the other insect. Arbitrary verbal labels were shown above the two pictures, and the meanings of the labels were manipulated in the instructions. In one condition, the labels represented the category membership of the insects, and in the other conditions, the same labels represented attributes of the insects. When the labels represented category membership, participants’ responses became substantially polarized and homogeneous, indicating that the mere reference to category membership can modify reasoning processes.     

Distributional Models of Category Concepts Based on Names of Category Members

Cognitive scientists have long used distributional semantic representations of categories. The predominant approach uses distributional representations of category-denoting nouns, such as “city” for the category city. We propose a novel scheme that represents categories as prototypes over representations of names of its members, such as “Barcelona,” “Mumbai,” and “Wuhan” for the category city. This name-based representation empirically outperforms the noun-based representation on two experiments (modeling human judgments of category relatedness and predicting category membership) with particular improvements for ambiguous nouns. We discuss the model complexity of both classes of models and argue that the name-based model has superior explanatory potential with regard to concept acquisition.     

Category and feature identification

This paper considers a family of inductive problems where reasoners must identify familiar categories or features on the basis of limited information. Problems of this kind are encountered, for example, when word learners acquire novel labels for pre-existing concepts. We develop a probabilistic model of identification and evaluate it in three experiments. Our first two experiments explore problems where a single category or feature must be identified, and our third experiment explores cases where participants must combine several pieces of information in order to simultaneously identify a category and a feature. Humans readily solve all of these problems, and we show that our model accounts for human inferences better than several alternative approaches.     

Category mistakes and figurative language

Category mistakes are sentences such as ‘The number two is blue’ or ‘Green ideas sleep furiously’. Such sentences are highly infelicitous and thus a prominent view claims that they are meaningless. Category mistakes are also highly prevalent in figurative language. That is to say, it is very common for sentences which are used figuratively to be such that, if taken literally, they would constitute category mistakes. (Consider for example the metaphor ‘The poem is pregnant’, the metonymy ‘The White House decided to change its policy’, or a fictional use of ‘The tree was happy’.) In this paper I argue that the view that category mistakes are meaningless is inconsistent with many central and otherwise plausible theories of figurative language. Thus if the meaninglessness view is correct, the theories in question must each be rejected, and conversely, if any of the theories in question is correct, the meaninglessness view must be wrong. The debates concerning the semantics of figurative language and concerning the semantic status of category mistakes are closely connected.