Global Dominance Outside the Focus of Attention

Identification of the local aspect of a relevant compound stimulus has been found to be delayed by the presence of target-set members at the global aspect of an irrelevant compound stimulus, whereas identification of the global aspect is unaffected by the presence of local target-set members within the irrelevant object (Paquet & Merikle, 1988). This effect has been termed the global category effect , and it suggests that global dominance occurs for objects located outside the attentional focus, as well as within an attended hierarchical object. In the present experiments, attention was directed to the relevant one of two compound stimuli by using either shape information (Experiments 1 and 2) or a 100-msec peripheral rapid onset precue (Experiment 3). Results revealed a global category effect even when the physical features of the displays containing global target-set members within the irrelevant object were closely matched with those of the control displays. Critically, the magnitude of the global category effect was affected by how well attention could be focused on the relevant compound stimulus. These findings suggest (a) that the analysis of global information for irrelevant objects is more elaborate than the simple detection of features; and (b) that both perceptual and attentional mechanisms are involved in global dominance.     

Category learning with minimal prior knowledge

In 6 experiments, the authors examined the use of prior knowledge in category learning. Previous studies of the effects of knowledge on category learning have used categories in which knowledge was related to all of the category's features. However, people's knowledge of real-world categories often consists of many "rote" features that are not related to their prior knowledge. Five experiments found that even minimal prior knowledge (1 knowledge-relevant feature and 5 rote features per exemplar) can facilitate category learning. Posttests revealed that although the knowledge aided learning, subjects also acquired the rote features that were not related to knowledge, contradicting predictions of an attentional explanation of the knowledge effect. The results of Experiment 6 suggested that subjects attempt to link even rote features to their knowledge.     

特征概率影响多维和少维类别的分类学习和特征学习

探讨了特征概率对多维和少维类别的分类学习和特征学习的效果及策略的影响。结果表明高特征概率条件下,多维比少维类别的分类学习更容易,而且学到更多的特征知识,多维条件下人们更倾向于整体性加工策略,而少维条件下人们倾向于分析性加工策略。低特征概率条件下,多维比少维类别的分类学习和特征学习都困难,且两种条件下人们都倾向于采取分析性加工策略。     

类别成员跨维度特征关系对类别学习的影响

探讨类别成员具有多维度相同特征与多维度匹配特征条件下对人们类别学习的影响。被试来自华南师范大学一年级本科生,要求他们学习不同特征结构的类别材料,然后进行测试,以学习阶段的单元数与错误率、测试阶段的反应时与错误率为指标。共包括3个实验,实验1探讨了类别成员具有双维度相同特征、双维度匹配特征与非匹配特征条件下进行类别学习的成绩。实验2探讨类别成员在空间位置分离的两个维度上具有相同特征对类别学习的影响。实验3进一步探讨类别间成员具有双维度相同特征对类别学习的影响。结果表明：（1）类别成员具有双维度相同特征时,人们在归类学习中会将这两个维度看成是一个维度,从而促进类别学习;（2）类别成员具有双维度匹配特征,或者在两个不相邻维度具有相同特征时,对于类别学习没有起到这种特定的促进作用;（3）如果类别间成员具有双维度相同特征,则对类别学习产生消极影响。研究结果表明,在类别学习过程中,特征相似性状况对维度的确立也会产生影响。     

Children's category‐based inferences affect classification

Children learn many new categories and make inferences about these categories. Much work has examined how children make inferences on the basis of category knowledge. However, inferences may also affect what is learned about a category. Four experiments examine whether category‐based inferences during category learning influence category knowledge and thereby affect later classifications for 5‐ to 7‐year‐olds. The children learned to classify pictures of new types of creatures on the basis of a salient feature (colour) and then answered a question that required them to make an inference on the basis of other features. At test, children classified pictures that included only some features (without colour). Experiment 1 showed that the features relevant to the inference during learning led to better classification than did features irrelevant to the inference. Experiment 2 replicated this finding even when the relevant features were physically close to the irrelevant features. Experiments 3 and 4 found this effect even when the classification was learned prior to the inference task and even when no mention was made of the categories during inference learning. Taken together, these results show that making inferences during category learning can influence category knowledge and suggest a need to integrate the work on category learning and category‐based inferences.     

A Dissociation Between Attention and Selection

It is widely assumed that the allocation of spatial attention results in the "selection" of attended objects or regions of space. That is, once a stimulus is attended, all its feature dimensions are processed irrespective of their relevance to behavioral goals. This assumption is based in part on experiments showing significant interference for attended stimuli when the response to an irrelevant dimension conflicts with the response to the relevant dimension (e.g., the Stroop effect). Here we show that such interference is not due to attending per se. In two spatial cuing experiments, we found that it was possible to restrict processing of attended stimuli to task-relevant dimensions. This new evidence supports two novel conclusions: (a) Selection involves more than the focusing of attention per se; and (b) task expectations play a key role in determining the depth of processing of the elementary feature dimensions of attended stimuli.     

Prior knowledge and correlational structure in unsupervised learning.

Prior knowledge has been shown to facilitate both supervised and unsupervised category learning, but questions remain about how this facilitation occurs. This article describes two experiments that investigate the effects of prior knowledge on unsupervised learning, using the exemplar-memory task of Clapper and Bower (2002). Experiment 1 demonstrates that prior knowledge facilitates learning in this task, as expected, and that this facilitation extends to both knowledge-relevant and knowledge-irrelevant features of the new categories. Experiment 2 shows that knowledge facilitates learning not only by increasing the probability that people will discover separate categories, but also by making the features of different categories seem less interchangeable, thereby reducing interference and confusion among them. Taken together, these experiments demonstrate that prior knowledge has multiple effects on unsupervised learning and suggests that the exemplar-memory task may provide a useful procedure for disentangling and investigating these effects.     

On the Interaction of Prior Knowledge and Stimulus Structure in Category Learning

Contemporary theories of categorization propose that concepts are coherent in virtue of being embedded in a network of theories about the world. Those theories function to pick out some of the many possible features of a set of objects as most salient for purposes of classification, a process that is complex and still poorly understood (Murphy & Medin, 1985). Part of what makes this account incomplete is a lack of information as to (1) what makes a feature salient on a given occasion and (2) how feature salience interacts with category structure to determine the course of learning. We report on the results of three studies of category learning using complex schematic drawings to show that (1) the contrast set defined by one's initial encounters with category exemplars can be a source of individual differences in feature salience assignments; (2) such effects are short-lived in the face of clear evidence about actual feature diagnosticity; and (3) more robust prior hypotheses interact with category structure to either enhance learning or impede it. The enhancement occurs when the hypothesis emphasizes category-relevant features, even if the hypothesis is in fact incorrect. A hypothesis that assigns high salience to irrelevant features impedes learning. Learning does occur as feedback concerning category structure leads to enhanced salience for relevant features. Salience of irrelevant features remains high, however, suggesting that such learning as occurs involves augmentation and not total revision of the (incorrect) prior hypothesis.     

Diagnosticity and prototypicality in category learning: a comparison of inference learning and classification learning

Category knowledge allows for both the determination of category membership and an understanding of what the members of a category are like. Diagnostic information is used to determine category membership; prototypical information reflects the most likely features given category membership. Two experiments examined 2 means of category learning, classification and inference learning, in terms of sensitivity to diagnostic and prototypical information. Classification learners were highly sensitive to diagnostic features but not sensitive to nondiagnostic, but prototypical, features. Inference learners were less sensitive to the diagnostic features than were classification learners and were also sensitive to the nondiagnostic, prototypical, features. Discussion focuses on aspects of the 2 learning tasks that might lead to this differential sensitivity and the implications for learning real-world categories.     

Prior knowledge enhances the category dimensionality effect

A study of the combined influence of prior knowledge and stimulus dimensionality on category learning was conducted. Subjects learned category structures with the same number of necessary dimensions but with more or fewer additional, redundant dimensions and with either knowledge-related or knowledge-unrelated features. Minimal-learning models predict that all subjects, regardless of condition, either should learn the same number of dimensions or should respond more slowly to each dimension. Despite similar learning rates and response times, subjects learned more features in the high-dimensional than in the low-dimensional condition. Furthermore, prior knowledge interacted with dimensionality, increasing what was learned, especially in the high-dimensional case. A second experiment confirmed that the participants did, in fact, learn more features during the training phase, rather than simply inferring them at test. These effects can be explained by direct associations among features (representing prior knowledge), combined with feedback between features and the category label, as was shown by simulations of the knowledge resonance, or KRES, model of category learning.     

Learning about the internal structure of categories through classification and feature inference

Previous research on category learning has found that classification tasks produce representations that are skewed toward diagnostic feature dimensions, whereas feature inference tasks lead to richer representations of within-category structure. Yet, prior studies often measure category knowledge through tasks that involve identifying only the typical features of a category. This neglects an important aspect of a category's internal structure: how typical and atypical features are distributed within a category. The present experiments tested the hypothesis that inference learning results in richer knowledge of internal category structure than classification learning. We introduced several new measures to probe learners' representations of within-category structure. Experiment 1 found that participants in the inference condition learned and used a wider range of feature dimensions than classification learners. Classification learners, however, were more sensitive to the presence of atypical features within categories. Experiment 2 provided converging evidence that classification learners were more likely to incorporate atypical features into their representations. Inference learners were less likely to encode atypical category features, even in a “partial inference” condition that focused learners' attention on the feature dimensions relevant to classification. Overall, these results are contrary to the hypothesis that inference learning produces superior knowledge of within-category structure. Although inference learning promoted representations that included a broad range of category-typical features, classification learning promoted greater sensitivity to the distribution of typical and atypical features within categories.     

Errors, efficiency, and the interplay between attention and category learning

Learning to identify objects as members of categories is an essential cognitive skill and learning to deploy attention effectively is a core component of that process. The present study investigated an assumption imbedded in formal models of categorization: error is necessary for attentional learning. Eye-trackers were used to record participants’ allocation of attention to task relevant and irrelevant features while learning a complex categorization task. It was found that participants optimized their fixation patterns in the absence of both performance errors and corrective external feedback. Optimization began immediately after each category was mastered and continued for many trials. These results demonstrate that error is neither necessary nor sufficient for all forms of attentional learning.     

工作记忆容量与内容相关性对类别学习的影响

类别学习是通过不断地分类练习,学会如何将类别刺激进行归类的过程。采用2(工作记忆容量:高、低)×4(内容相关性:方向、宽度、亮度、控制组)被试间实验设计,通过两个实验探讨工作记忆容量与内容相关性对基于规则类别学习和信息整合类别学习的影响。结果显示:(1)对基于规则类别学习来说,在高工作记忆容量条件下,当关注相关维度时,类别学习的成绩更好;(2)对基于信息整合类别学习来说,不管工作记忆容量如何,只要关注相关维度类别学习的成绩更好。     

特征的呈现方式对类别学习中规则和相似性知识获得的影响

采用原型变异任务,通过操纵规则和相似性特征的呈现通道,探讨特征的呈现方式对类别学习中规则和相似性知识获得的影响。结果发现,在听觉-视觉条件下习得规则的人数显著多于习得相似性的人数,而在视觉-听觉和视觉-视觉条件下则不存在显著差异;并且,三种条件下习得规则的正确率都高于习得相似性的正确率。这说明特征的呈现方式影响对规则和相似性特征的习得,在听觉通道呈现规则时被试更倾向基于规则分类。     

An inverse base rate effect with continuously valued stimuli

It is well known that people do not always make normative use of information about relative frequencies of categories when making categorical judgments. The "inverse base rate" effect (Medin & Edelson, 1988) is a typical example of this: Subjects violate normative reasoning principles by assigning certain ambiguous stimuli as belonging to the less frequent of two categories, rather than to the more common category. This effect has been explained as being due to the shifting of attention from shared stimulus features to distinctive features during learning. When stimuli are defined by values along continuous dimensions, rather than by the presence and absence of features, then attention could shift between dimensions or between values, or both. In three experiments, base rate differences were used to determine the way in which attention is shifted during learning about stimuli with continuously valued dimensions. Simulation modeling shows that the results are consistent with the movement of attention both between and within stimulus dimensions.     

关系复杂性对关系类别间接性学习中选择性注意的影响

以大学生为被试,使用关系复杂性逐渐变化的实验材料——4特征复杂关系的虚拟外星生物、6特征复杂关系加二阶同功能简单关系的虚拟外星生物和6特征复杂关系加二阶异功能简单关系的虚拟外星生物,采用类别的间接性学习范式——个人功能预测的关系类别的间接性学习条件和参照性交流的关系类别的间接性学习条件,通过三个实验任务（功能预测、自由分类和维度选择）,探讨材料关系复杂性对关系类别间接性学习中选择性注意的影响。结果发现：随着关系复杂性的逐渐增高,被试的选择性注意水平不存在显著差异,但选择性注意的指向性存在极其显著差异,选择性注意的集中性（对无关维度的抑制）不存在显著差异;参照条件下被试选择性注意水平极其显著地高于个人条件,这种差异主要表现在选择性注意的指向性方面,而不表现在选择性注意的集中性（对无关维度的抑制）方面。     

When does visual attention select all features of a distractor?

What happens after visual attention is allocated to an object? Although many theories of attention assume that all of its features are selected and processed, there has been little direct evidence that an irrelevant feature dimension of an attended nontarget is processed. In 5 experiments presented here, the authors used a singleton paradigm to investigate the effect of attention on nontarget objects. Participants made a speeded feature discrimination of a target for which the response was either compatible or incompatible with an irrelevant feature dimension of a distractor. The results show that the irrelevant distractor features were processed to the point that they interfered with the response to the target. The response compatibility effect was observed even when the location of the target or the distractor was invariant, although it was much weaker when both locations were invariant. These results demonstrate that in many circumstances, an attended distractor is completely selected and fully processed, and the complete processing of distractors depends on a number of factors, many of which are related to the strength of attention to the distractor.     

Selective attention and the perception of an attended nontarget object

Although many theories of attention assume that attending to an object results in the processing of all its feature dimensions, there has been no direct evidence that the irrelevant dimensions of an attended nontarget object are encoded. This article explores factors that modulate such processing. In 6 experiments, participants made a speeded response to a probe preceded by a prime that varied in 2 dimensions. Their reaction times to the probe were influenced by the response compatibility between the relevant and irrelevant dimensions of the prime. Furthermore, the effect was observed only when attention was directed to a nonlocation object feature and when participants' reaction times were relatively long. These results suggest that the effect of attention on a nontarget object is more complex than was previously understood.     

参照性交流对关系类别间接性学习的促进作用

以大学生为被试,以4特征虚拟外星生物为实验材料,采用类别的间接性学习范式——个人条件和参照条件,及一个无功能条件,通过三个实验任务（功能预测、自由分类和维度选择）,探讨参照性交流范式下关系类别的间接性学习特点。结果发现：类别的间接性学习条件下,自由分类任务中,被试更倾向于选择关系作为类标准;功能预测的关系类别的间接性学习过程中,参照条件下的功能预测成绩显著高于个人条件,这种差异体现在参照惯例形成的学习过程的中后期;关系类别的间接性学习条件下,参照条件下被试的选择性注意水平显著高于个人条件,这种差异主要表现于选择性注意的指向性方面,而不体现于选择性注意的集中性（对无关维度的抑制）方面。     

Modeling the effects of prior knowledge on learning incongruent features of category members

The authors conducted 3 experiments addressing the issue of how observations and multiple sources of prior knowledge are put together in category learning. In Experiments 1 and 2, learning was faster for critical features, which were predictable on the basis of prior knowledge, than for filler features, and this advantage increased as more observations were made. In addition, learning was fastest for incongruent features that could only be predicted using knowledge from other domains. In Experiment 3, presenting contradictory features that violated prior knowledge led to rote learning rather than use of prior knowledge. The results were simulated with the Baywatch model, which addresses how observations of category members lead to recruitment and selection of sources of prior knowledge.