The dimensionality of perceptual category learning: A state-trace analysis

State-trace analysis was used to investigate the effect of concurrent working memory load on perceptual category learning. Initial reanalysis of Zeithamova and Maddox (2006, Experiment 1) revealed an apparently two-dimensional state-trace plot consistent with a dual-system interpretation of category learning. However, three modified replications of the original experiment found evidence of a single resource underlying the learning of both rule-based and information integration category structures. Follow-up analyses of the Zeithamova and Maddox data, restricted to only those participants who had learned the category task and performed the concurrent working memory task adequately, revealed a one-dimensional plot consistent with a single-resource interpretation and the results of the three new experiments. The results highlight the potential of state-trace analysis in furthering our understanding of the mechanisms underlying category learning.     

The role of visuospatial and verbal working memory in perceptual category learning

The role of verbal and visuospatial working memory in rule-based and information-integration category learning was examined. Previously, Maddox, Ashby, Ing, and Pickering found that a sequentially presented verbal working memory task did not affect information-integration learning, but disrupted rule-based learning when the rule was on the spatial frequency of a Gabor stimulus. This pattern was replicated in Experiment 1, in which the same category structures were used, but in which the verbal working memory task was replaced with a visuospatial analog. Experiment 2A examined rule-based learning on an oblique orientation and also found both verbal and visuospatial working memory tasks disrupting learning. Experiment 2B examined rule-based learning on a cardinal orientation and found a minimal effect of the verbal working memory task, but a large effect of the visuospatial working memory task. The conceptual significance of cardinal orientations and the role of visuospatial and verbal working memory in category learning are discussed.     

Automaticity in rule-based and information-integration categorization

Three experiments studied the effects of category structure on the development of categorization automaticity. In Experiment 1, participants were each trained for over 10,000 trials in a simple categorization task with one of three category structures. Results showed that after the first few sessions, there were no significant behavioral differences between participants who learned rule-based versus information-integration category structures. Experiment 2 showed that switching the locations of the response keys after automaticity had developed caused a similar highly significant interference, regardless of category structure. In Experiment 3, a simultaneous dual task that engaged executive functions did not interfere with either rule-based or information-integration categorization. These novel results are consistent with a theory assuming separate processing pathways for initial rule-based and information-integration category learning but a common processing pathway after the development of automaticity.     

嵌套范式下视空工作记忆对基于规则类别学习

基于COVIS模型与认知加工阶段假设,通过2个实验探讨嵌套范式下, 视空工作记忆对基于规则类别学习的影响。实验1采用类别学习中嵌套视空工作记忆的范式,结果发现视空工作记忆削弱基于规则类别学习成绩,与COVIS模型预测相一致。实验2则采用视空工作记忆中嵌套类别学习任务的范式,结果却发现视空工作记忆对基于规则类别学习的影响消失。实验结果表明嵌套范式下视空工作记忆的位置影响基于规则类别学习,初步验证了类别学习存在多个认知加工阶段的假设,视空工作记忆主要影响基于规则类别学习中规则的发现和检验阶段。     

Cognitive changes in conjunctive rule-based category learning: An ERP approach

When learning rule-based categories, sufficient cognitive resources are needed to test hypotheses, maintain the currently active rule in working memory, update rules after feedback, and to select a new rule if necessary. Prior research has demonstrated that conjunctive rules are more complex than unidimensional rules and place greater demands on executive functions like working memory. In our study, event-related potentials (ERPs) were recorded while participants performed a conjunctive rule-based category learning task with trial-by-trial feedback. In line with prior research, correct categorization responses resulted in a larger stimulus-locked late positive complex compared to incorrect responses, possibly indexing the updating of rule information in memory. Incorrect trials elicited a pronounced feedback-locked P300 elicited which suggested a disconnect between perception, and the rule-based strategy. We also examined the differential processing of stimuli that were able to be correctly classified by the suboptimal single-dimensional rule (“easy” stimuli) versus those that could only be correctly classified by the optimal, conjunctive rule (“difficult” stimuli). Among strong learners, a larger, late positive slow wave emerged for difficult compared with easy stimuli, suggesting differential processing of category items even though strong learners performed well on the conjunctive category set. Overall, the findings suggest that ERP combined with computational modelling can be used to better understand the cognitive processes involved in rule-based category learning.     

Disrupting feedback processing interferes with rule-based but not information-integration category learning

The effect of a sequentially presented memory scanning task on rule-based and information-integration category learning was investigated. On each trial in the short feedback-processing time condition, memory scanning immediately followed categorization. On each trial in the long feedback-processing time condition, categorization was followed by a 2.5-sec delay and then memory scanning. In the control condition, no memory scanning was required. Rule-based category learning was significantly worse in the short feedback-processing time condition than in the long feedback-processing time condition or control condition, whereas information-integration category learning was equivalent across conditions. In the rule-based condition, a smaller proportion of observers learned the task in the short feedback-processing time condition, and those who learned took longer to reach the performance criterion than did those in the long feedback-processing time or control condition. No differences were observed in the information integration task. These results provide support for a multiple-systems approach to category learning and argue against the validity of single-system approaches.     

Stimulus modality interacts with category structure in perceptual category learning

Two experiments were conducted that examined information integration and rule-based category learning, using stimuli that contained auditory and visual information. The results suggest that it is easier to perceptually integrate information within these sensory modalities than across modalities. Conversely, it is easier to perform a disjunctive rule-based task when information comes from different sensory modalities, rather than from the same modality. Quantitative model-based analyses suggested that the information integration deficit for across-modality stimulus dimensions was due to an increase in the use of hypothesis-testing strategies to solve the task and to an increase in random responding. The modeling also suggested that the across-modality advantage for disjunctive, rule-based category learning was due to a greater reliance on disjunctive hypothesis-testing strategies, as opposed to unidimensional hypothesis-testing strategies and random responding.     

Pigeons' categorization may be exclusively nonanalytic

Recent theoretical and empirical developments in human category learning have differentiated an analytic, rule-based system of category learning from a nonanalytic system that integrates information across stimulus dimensions. In the present study, the researchers applied this theoretical distinction to pigeons' category learning. Pigeons learned to categorize stimuli varying in the tilt and width of their internal striping. The matched category problems had either a unidimensional (rule-based) or multidimensional (information-integration) solution. Whereas humans and nonhuman primates strongly dimensionalize these stimuli and learn rule-based tasks far more quickly than information-integration tasks, pigeons learned the two tasks equally quickly to the same accuracy level. Pigeons may represent a cognitive system in which the commitment to dimensional analysis and category rules was not strongly made. Their performance could suggest the character of the ancestral vertebrate categorization system from which that of primates emerged.     

A quantitative model-based approach to examining aging effects on information-integration category learning

Information-integration category learning was examined in older and younger adults. Accuracy results indicated that older participants learned less well than younger participants in both linear and nonlinear conditions. Model-based analyses indicated that both groups in the linear condition tended to use information integration but that later in training younger participants were more likely to do so. In contrast, the 2 groups in the nonlinear condition were equally likely to use information integration. Further analysis indicated that younger adults were more accurate than older adults when an information-integration approach was adopted, whereas fewer age-related differences were observed when a rule-based approach was used, suggesting that age can have a negative impact on information-integration category learning processes but less impact on rule-based learning.     

空间工作记忆负载对真实场景情境提示效应的影响

重复的画面布局能够促进观察者对目标项的搜索 (情境提示效应)。本研究采用双任务范式,分别在视觉搜索任务的学习阶段 (实验2a) 和测验阶段 (实验2b) 加入空间工作记忆任务, 并与单任务基线 (实验1)进行比较, 考察空间工作记忆负载对真实场景搜索中情境线索学习和情境提示效应表达的影响。结果发现: 空间负载会增大学习阶段的情境提示效应量, 同时削弱测验阶段的情境提示效应量, 而不影响情境线索的外显提取。由此可见, 真实场景中情境线索的学习和提示效应的表达均会受到有限的工作记忆资源的影响, 但情境线索提取的外显性不变。     

The effects of category overlap on information-integration and rule-based category learning

In three experiments, we investigated whether the amount of category overlap constrains the decision strategies used in category learning, and whether such constraints depend on the type of category structures used. Experiments 1 and 2 used a category-learning task requiring perceptual integration of information from multiple dimensions (an information-integration task) and Experiment 3 used a task requiring the application of an explicit strategy (a rule-based task). In the information-integration task, participants used perceptual-integration strategies at moderate levels of category overlap, but explicit strategies at extreme levels of overlap--even when such strategies were suboptimal. In contrast, in the rule-based task, participants used explicit strategies, regardless of the level of category overlap. These data are consistent with a multiple systems view of category learning, and suggest that categorization strategy depends on the type of task that is used, and on the degree to which each stimulus is probabilistically associated with the contrasting categories.     

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。     

相关维度数量对两种结构类别学习的影响

在多重系统理论研究基础上,运用即时反馈训练范式,以大学生为被试,考查相关维度数量对基于规则和信息整合两种结构的类别学习的影响.结果表明:(1)相关维度数量是影响类别学习的重要因素,基于规则单维度结构的学习显著优于信息整合结构和基于规则双维度结构的学习,基于规则双维度结构的学习与信息整合结构的学习没有显著差异.(2)反应策略受到规则复杂性的影响,当类别结构中隐含的规则比较简单时,学习者使用规则策略;当类别结构中隐含的规则比较复杂时,学习者难以掌握规则,就会使用相似性策略.研究结果支持"难度观",而不支持多重系统理论.     

Critrial noise effects on rule-based category learning: The impact of delayed feedback

Variability in the representation of the decision criterion is assumed in many category-learning models, yet few studies have directly examined its impact. On each trial, criterial noise should result in drift in the criterion and will negatively impact categorization accuracy, particularly in rule-based categorization tasks, where learning depends on the maintenance and manipulation of decision criteria. In three experiments, we tested this hypothesis and examined the impact of working memory on slowing the drift rate. In Experiment 1, we examined the effect of drift by inserting a 5-sec delay between the categorization response and the delivery of corrective feedback, and working memory demand was manipulated by varying the number of decision criteria to be learned. Delayed feedback adversely affected performance, but only when working memory demand was high. In Experiment 2, we built on a classic finding in the absolute identification literature and demonstrated that distributing the criteria across multiple dimensions decreases the impact of drift during the delay. In Experiment 3, we confirmed that the effect of drift during the delay is moderated by working memory. These results provide important insights into the interplay between criterial noise and working memory, as well as providing important constraints for models of rule-based category learning.     

The effects of concurrent verbal and visual tasks on category learning

Current theories of category learning posit separate verbal and nonverbal learning systems. Past research suggests that the verbal system relies on verbal working memory and executive functioning and learns rule-defined categories; the nonverbal system does not rely on verbal working memory and learns non-rule-defined categories (E. M. Waldron & F. G. Ashby, 2001; D. Zeithamova & W. T. Maddox, 2006). However, relatively little research has explored the importance of visual working memory or visual processing for either system. The authors investigated the role of working memory (Experiment 1a and 1b), visual processing (Experiment 2), and executive functioning for each system, using a concurrent task methodology. It was found that visual tasks with high executive functioning demands and verbal tasks with high or low executive demands disrupted rule-defined learning, whereas any visual task, regardless of executive functioning demand, disrupted non-rule-defined learning. Taken together, these results confirm the importance of verbal working memory and executive functioning for the verbal system and provide new evidence for the importance of visual processing for the nonverbal system. These results help to clarify understanding of the nonverbal system and have implications for multiple systems theories of category learning (F. G. Ashby, L. A. Alfonso-Reese, A. U. Turken, & E. M. Waldron, 1998).     

Category number impacts rule-based but not information-integration category learning: further evidence for dissociable category-learning systems

Category number effects on rule-based and information-integration category learning were investigated. Category number affected accuracy and the distribution of best-fitting models in the rule-based task but had no effect on accuracy and little effect on the distribution of best-fining models in the information-integration task. In the 2 category conditions, rule-based learning was better than information-integration learning, whereas in the 4 category conditions, unidimensional and conjunctive rule-based learning was worse than information-integration learning. Rule-based strategies were used in the 2-category/rule-based condition, but about half of the observers used rule-based strategies in the 4-category unidimensional and conjunctive rule-based conditions. Information-integration strategies were used in the 4-category/ information-integration condition and by the end of training were used in the 2-category/information-integration condition.     

Task and distribution sampling affect auditory category learning

There is substantial evidence that two distinct learning systems are engaged in category learning. One is principally engaged when learning requires selective attention to a single dimension (rule-based), and the other is drawn online by categories requiring integration across two or more dimensions (information-integration). This distinction has largely been drawn from studies of visual categories learned via overt category decisions and explicit feedback. Recent research has extended this model to auditory categories, the nature of which introduces new questions for research. With the present experiment, we addressed the influences of incidental versus overt training and category distribution sampling on learning information-integration and rule-based auditory categories. The results demonstrate that the training task influences category learning, with overt feedback generally outperforming incidental feedback. Additionally, distribution sampling (probabilistic or deterministic) and category type (information-integration or rule-based) both affect how well participants are able to learn. Specifically, rule-based categories are learned equivalently, regardless of distribution sampling, whereas information-integration categories are learned better with deterministic than with probabilistic sampling. The interactions of distribution sampling, category type, and kind of feedback impacted category-learning performance, but these interactions have not yet been integrated into existing category-learning models. These results suggest new dimensions for understanding category learning, inspired by the real-world properties of auditory categories.     

Category label and response location shifts in category learning

The category shift literature suggests that rule-based classification, an important form of explicit learning, is mediated by two separate learned associations: a stimulus-to-label association that associates stimuli and category labels, and a label-to-response association that associates category labels and responses. Three experiments investigate whether information–integration classification, an important form of implicit learning, is also mediated by two separate learned associations. Participants were trained on a rule-based or an information–integration categorization task and then the association between stimulus and category label, or between category label and response location was altered. For rule-based categories, and in line with previous research, breaking the association between stimulus and category label caused more interference than breaking the association between category label and response location. However, no differences in recovery rate emerged. For information–integration categories, breaking the association between stimulus and category label caused more interference and led to greater recovery than breaking the association between category label and response location. These results provide evidence that information–integration category learning is mediated by separate stimulus-to-label and label-to-response associations. Implications for the neurobiological basis of these two learned associations are discussed.     

Learning and transfer of category knowledge in an indirect categorization task

Knowledge representations acquired during category learning experiments are ‘tuned’ to the task goal. A useful paradigm to study category representations is indirect category learning. In the present article, we propose a new indirect categorization task called the “same”–“different” categorization task. The same–different categorization task is a regular same–different task, but the question asked to the participants is about the stimulus category membership instead of stimulus identity. Experiment 1 explores the possibility of indirectly learning rule-based and information-integration category structures using the new paradigm. The results suggest that there is little learning about the category structures resulting from an indirect categorization task unless the categories can be separated by a one-dimensional rule. Experiment 2 explores whether a category representation learned indirectly can be used in a direct classification task (and vice versa). The results suggest that previous categorical knowledge acquired during a direct classification task can be expressed in the same–different categorization task only when the categories can be separated by a rule that is easily verbalized. Implications of these results for categorization research are discussed.     

Feedback interference and dissociations of classification: Evidence against the multiple-learning-systems hypothesis

Researchers have argued that different categorization problems are learned by separate and distinct cognitive systems. They propose that an explicit system is responsible for learning rule-based categories and that a separate implicit system learns information-integration categories. One source of supporting evidence involves experiments in which observers perform a concurrent memory-scanning task that interferes with the processing of feedback. Researchers have reported a dissociation in which this manipulation impairs learning of a rule-based category but not an information-integration category. In the present research, we test the hypothesis that the dissociation was the result of lowered perceptual discriminability in the rule-based structure in comparison with the information-integration one. We demonstrate an example of an alternate rule-based category with easy-to-discriminate stimuli in which performance is unaffected by the interfering memory-scanning task. Furthermore, we demonstrate that learning of an information-integration category with low perceptual discriminability is impaired by the memory-scanning task. These demonstrations of the reverse dissociation challenge the interpretation that rule-based and information-integration category structures are learned by separate cognitive systems.