Memory search: When does semantic analysis occur?

This study was addressed to the determination of the stage at which semantic analysis occurs during a STM recognition task. A list of exemplars (memory set), drawn from 13 different categories, was presented at a rate of 11/2 sec/item, followed by a category name probe. Ss then indicated whether any of the exemplars in the memory set belonged to that category. List length was varied from 5 to 7, with each memory set containing items from either two or three categories. It was found that RT was independent of list length, but did increase by 60 msec as the number of categories represented in the list increased from two to three. From this, it was concluded that activation of a superordinate category representation occurred upon presentation of each memory-set item, and that the memory scan was done on these superordinate categories.     

6岁儿童的类别学习能力:类别表征、注意和分类策略

探讨了6岁儿童的类别学习能力、类别表征和分类策略。62名儿童参加了实验,实验1采用了"5/4模型"类别结构,实验2采用了"3/3类别结构"。结果发现:6岁儿童已经具备了一定的类别学习能力;相对于原型表征,6岁儿童更倾向于进行样例表征;6岁儿童在注意上具有定位在高典型性特征维度上的能力,但不具备定位在区分性特征维度上的能力;在类别学习策略上主要采用单维度分类策略和规则加例外的分类策略。     

知道与不知道要学多少：类别学习中样例量的预期作用

采用“5/4模型”类别结构探讨了类别学习中样例量的预期作用。设置了两种学习条件(“知道样例量”和“不知道样例量”), 分别探讨两种学习条件下的学习效率、学习策略以及所形成的类别表征。106名大学生参加了实验, 结果表明：在类别学习中, 样例量的预期作用显著, 知道样例量组的学习效率高于不知道样例量组; 样例量的预期作用对类别学习效率的影响是通过影响学习过程中使用的策略来实现的; 样例量的预期作用不影响两种学习条件的学习后形成的类别表征, 且两种学习条件的被试自始至终表现出样例学习的表征模式。     

Comparison and representation failures both cause real-world change blindness

Change blindness (CB) occurs when people miss changes across views. Hypothetically, CB would occur if observers failed to represent information about the changing object, but CB would also occur if observers represented and failed to compare information across views, or represented only the pre- or post-change object. For a variety of reasons, previous studies have been unable to determine which of these alternatives contribute to CB in an incidental real-world setting. To address these ambiguities, we conducted two real-world experiments using stimuli that changed on only one feature and tested recognition memory for both the changing feature and a non-changing feature. Participants also provided confidence ratings on recognition responses, allowing us to test whether CB has multiple causes within a single task setting. The results suggest that, in a single real-world setting, CB can be caused by both a failure to represent and a failure to compare information across views.     

Categorization as causal reasoning⋆

A theory of categorization is presented in which knowledge of causal relationships between category features is represented in terms of asymmetric and probabilistic causal mechanisms. According to causal‐model theory, objects are classified as category members to the extent they are likely to have been generated or produced by those mechanisms. The empirical results confirmed that participants rated exemplars good category members to the extent their features manifested the expectations that causal knowledge induces, such as correlations between feature pairs that are directly connected by causal relationships. These expectations also included sensitivity to higher‐order feature interactions that emerge from the asymmetries inherent in causal relationships. Quantitative fits of causal‐model theory were superior to those obtained with extensions to traditional similarity‐based models that represent causal knowledge either as higher‐order relational features or “prior exemplars” stored in memory.     

Decision processes in verifying category membership statements: Implications for models of semantic memory

Current models of semantic memory assume that natural categories are well-defined. Specific predictions of two such models, the Smith, Shoben, and Rips (1974a) two-stage feature comparison model and the Glass and Holyoak (1974/75) ordered search model, were tested and disconfirmed in Experiment I. We propose an alternative model postulating fuzzy categories represented as sets of characteristic properties. This model, combined with a Bayesian decision process, accounts for the results of three additional experiments, as well as for the major findings in the semantic memory literature. We argue that people verify category membership statements by assessing similarity relations between concepts rather than by using information which logically specifies the truth value of the sentence. Our data also imply that natural categories are fuzzy rather than well-defined.     

Evidence for an age-independent process in category learning

After learning to categorize a set of alien-like stimuli in the context of a story, a group of 5-year-old children and adults judged pairs of stimuli from different categories to be less similar than did groups not learning the category distinction. In a same-different task, the learning group made more errors on pairs of non-identical stimuli from the same category than did the other groups, suggesting increased within-category item similarity, or compression. These expansion and compression effects add further support to the view that concept formation involves systematic changes in the metric of similarity space within which objects are represented. They also suggest that these processes do not vary with age, which is at least consistent with the hypothesis that they are fundamental to the mechanisms underlying concept formation.     

Similarity effects in visual working memory

Perceptual similarity is an important property of multiple stimuli. Its computation supports a wide range of cognitive functions, including reasoning, categorization, and memory recognition. It is important, therefore, to determine why previous research has found conflicting effects of inter-item similarity on visual working memory. Studies reporting a similarity advantage have used simple stimuli whose similarity varied along a featural continuum. Studies reporting a similarity disadvantage have used complex stimuli from either a single or multiple categories. To elucidate stimulus conditions for similarity effects in visual working memory, we tested memory for complex stimuli (faces) whose similarity varied along a morph continuum. Participants encoded 3 morphs generated from a single face identity in the similar condition, or 3 morphs generated from different face identities in the dissimilar condition. After a brief delay, a test face appeared at one of the encoding locations for participants to make a same/different judgment. Two experiments showed that similarity enhanced memory accuracy without changing the response criterion. These findings support previous computational models that incorporate featural variance as a component of working memory load. They delineate limitations of models that emphasize cortical resources or response decisions.     

What's behind different kinds of kinds: effects of statistical density on learning and representation of categories

This research examined how differences in category structure affect category learning and category representation across points of development. The authors specifically focused on category density--or the proportion of category-relevant variance to the total variance. Results of Experiments 1-3 showed a clear dissociation between dense and sparse categories: Whereas dense categories were readily learned without supervision, learning of sparse categories required supervision. There were also developmental differences in how statistical density affected category representation. Although children represented both dense and sparse categories on the basis of the overall similarity (Experiment 4A), adults represented dense categories on the basis of similarity and represented sparse categories on the basis of the inclusion rule (Experiment 4B). The results support the notion that statistical structure interacts with the learning regime in their effects on category learning. In addition, these results elucidate important developmental differences in how categories are represented, which presents interesting challenges for theories of categorization.     

Hybrid search in the temporal domain: Evidence for rapid,serial logarithmic search through memory

In hybrid search, observers memorize a number of possible targets and then search for any of these in visual arrays of items. Wolfe (2012) has previously shown that the response times in hybrid search increase with the log of the memory set size. What enables this logarithmic search of memory? One possibility is a series of steps in which subsets of the memory set are compared to all items in the visual set simultaneously. In the present experiments, we presented single visual items sequentially in a rapid serial visual presentation (RSVP) display, eliminating the possibility of simultaneous testing of all items. We used a staircasing procedure to estimate the time necessary to effectively detect the target in the RSVP stream. Processing time increased in a log–linear fashion with the number of potential targets. This finding eliminates the class of models that require simultaneous comparison of some memory items to all (or many) items in the visual display. Experiment 3 showed that, similar to visual search, memory search efficiency in this paradigm is influenced by the similarity between the target set and the distractors. These results indicate that observers perform separate memory searches on each eligible item in the visual display. Moreover, it appears that memory search for one item can proceed while other items are being categorized as “eligible” or “not eligible.”     

On the nature of the decision axis in signal-detection-based models of recognition memory

Most models of recognition memory involve a signal-detection component in which a criterion is placed along a decision axis. Older models generally assume a familiarity-decision axis, but newer models often assume a likelihood ratio axis instead because it allows for a more natural account of the ubiquitous mirror effect. In 3 experiments reported here, item strength was differentially manipulated to see whether a mirror effect would occur. Within a list, the items from 1 category were strengthened by repetition, but the items from another category were not. On the subsequent recognition test, the hit rate was higher for the strong category, but the false-alarm rates for the weak and strong categories were the same (i.e., no mirror effect was observed). This result suggests that the decision axis represents a familiarity scale and that participants adopt a single decision criterion that they maintain throughout the recognition test.     

Hierarchical encoding in visual working memory: ensemble statistics bias memory for individual items

Influential models of visual working memory treat each item to be stored as an independent unit and assume that there are no interactions between items. However, real-world displays have structure that provides higher-order constraints on the items to be remembered. Even in the case of a display of simple colored circles, observers can compute statistics, such as mean circle size, to obtain an overall summary of the display. We examined the influence of such an ensemble statistic on visual working memory. We report evidence that the remembered size of each individual item in a display is biased toward the mean size of the set of items in the same color and the mean size of all items in the display. This suggests that visual working memory is constructive, encoding displays at multiple levels of abstraction and integrating across these levels, rather than maintaining a veridical representation of each item independently.     

When categories collide: accumulation of information about multiple categories in rapid scene perception

Experiments have shown that people can rapidly determine if categories such as "animal" or "beach" are present in scenes that are presented for only a few milliseconds. Typically, observers in these experiments report on one prespecified category. For the first time, we show that observers can rapidly extract information about multiple categories. Moreover, we demonstrate task-dependent interactions between accumulating information about different categories in a scene. This interaction can be constructive or destructive, depending on whether the presence of one category can be taken as evidence for or against the presence of the other.     

Category vs. item learning: Implications for categorization models

A paradigm that required that subjects learn two responses to each of 10 schematic faces was used to study the relative rate of discrimination and generalization learning. One response uniquely identified each face, whereas the second response classified each face as a member of one of two categories. Rapid category learning and slow item learning suggested that category responses were learned on the basis of abstracted information, but item responses depended on the more difficult task of discriminating among patterns. The results are related to categorization models and to task variables that should influence the relative rates of discrimination and generalization learning.     

A probabilistic account of exemplar and category generation

People are capable of imagining and generating new category exemplars and categories. This ability has not been addressed by previous models of categorization, most of which focus on classifying category exemplars rather than generating them. We develop a formal account of exemplar and category generation which proposes that category knowledge is represented by probability distributions over exemplars and categories, and that new exemplars and categories are generated by sampling from these distributions. This sampling account of generation is evaluated in two pairs of behavioral experiments. In the first pair of experiments, participants were asked to generate novel exemplars of a category. In the second pair of experiments, participants were asked to generate a novel category after observing exemplars from several related categories. The results suggest that generation is influenced by both structural and distributional properties of the observed categories, and we argue that our data are better explained by the sampling account than by several alternative approaches.     

Chromatic information processing: Rate depends on stimulus location in the category and psychological complexity

Summary Colors are typically categorized, and color sensations can be conceived to lie on a continuum of psychological complexity from simple, sensations provoked by colors that fall near the centers of color categories and that convey predominately a single percept (like blue), to complex, sensations provoked by colors that fall near boundaries between color categories and that convey two percepts (like blue-green). In three experiments we assessed the effect of the location of colors in a category (their psychological complexity) on the rate at which observers identified and classified them. In Experiment 1, observers named category center colors faster than boundary colors. A subsidiary experiment with range-shifted stimuli showed that observers were not merely bisecting a stimulus continuum. In Experiment 2, observers classified a variety of category centers more rapidly than a variety of boundaries. In Experiment 3, observers who first practiced classifying color centers or boundaries as such later classified category centers faster than boundaries. A subsidiary experiment showed that this differential was not selective to particular response category labels. Neither Experiment 2 nor Experiment 3 showed any differential effect of visual field of presentation. The advantage of category center or simple over boundary or complex sensations in chromatic information processing is discussed in terms of the physiological sensitivity of the visual system to color.     

Contrast effects in typicality judgements: A hierarchical Bayesian approach

We examine the influence of contrast categories on the internal graded membership structure of everyday concepts using computational models proposed in the artificial category learning tradition. In particular, the generalized context model (Nosofsky, 1986), which assumes that only members of a given category contribute to the typicality of a category member, is contrasted to the similarity–dissimilarity generalized context model (SD-GCM; Stewart & Brown, 2005), which assumes that members of other categories are also influential in determining typicality. The models are compared in a hierarchical Bayesian framework in their account of the typicality gradient of five animal categories and six artefact categories. For each target category, we consider all possible relevant contrast categories. Three separate issue are examined: (a) whether contrast effects can be found, (b) which categories are responsible for these effects, and (c) whether more than one category influences the typicality. Results indicate that the internal category structure is codetermined by dissimilarity towards potential contrast categories. In most cases, only a single contrast category contributed to the typicality. The present findings suggest that contrast effects might be more widespread than has previously been assumed. Further, they stress the importance of characteristics particular of everyday concepts, which require careful consideration when applying computational models of representation of the artificial category learning tradition to everyday concepts.     

Cue-dependent effects in recall of categorized lists

Noncued and cued recall of categorized lists are similar in a number of ways: They show the same rate of gain in item recall with increasing category size; they both produce serial position effects within categories; and they both show a “some-or-none” pattern of with-category recall frequency. Cued and noncued recall differ in other respects: There is a great improvement in item and in category recall attendant on the provision of cues, and only noncued recall displays a list position effect. The points of similarity are taken to indicate that both cued and noncued recall measure the same underlying processes. The points of differences suggest the utility of cueing procedures in identifying the origin of characteristics of recall, according to the principle that any feature of noncued recall that is altered by provision of cues must originate in the retrieval process; features resistant to such modification represent encoding or storage effects.