Mutual influence of implicit and explicit attitudes

Research and theory distinguish two types of attitude: automatic evaluative reactions and deliberate evaluative judgments, referred to as implicit and explicit attitudes, respectively. Although these attitudes are distinct, they may influence each other. Four studies tested whether implicit and explicit attitudes are both influenced by propositional and associative learning. We also tested whether changes in one kind of attitude mediate changes in the other. Study 1 found that propositional learning about novel individuals directly influenced explicit attitudes and indirectly influenced implicit attitudes through changes in explicit attitudes. Studies 2 and 3 replicated this finding and extended it by simultaneously demonstrating that associative learning through Evaluative Conditioning directly influences implicit attitudes and indirectly influences explicit attitudes through changes in implicit attitudes. Study 4 replicated these effects for attitudes toward familiar, rather than novel, targets. These results suggest that implicit and explicit attitudes can share common antecedents and influence each other.     

Intact implicit learning in autism spectrum conditions

Individuals with autism spectrum condition (ASC) have diagnostic impairments in skills that are associated with an implicit acquisition; however, it is not clear whether ASC individuals show specific implicit learning deficits. We compared ASC and typically developing (TD) individuals matched for IQ on five learning tasks: four implicit learning tasks—contextual cueing, serial reaction time, artificial grammar learning, and probabilistic classification learning tasks—that used procedures expressly designed to minimize the use of explicit strategies, and one comparison explicit learning task, paired associates learning. We found implicit learning to be intact in ASC. Beyond no evidence of differences, there was evidence of statistical equivalence between the groups on all the implicit learning tasks. This was not a consequence of compensation by explicit learning ability or IQ. Furthermore, there was no evidence to relate implicit learning to ASC symptomatology. We conclude that implicit mechanisms are preserved in ASC and propose that it is disruption by other atypical processes that impact negatively on the development of skills associated with an implicit acquisition.     

Gender moderates the relation between implicit and explicit self-esteem

Relative to men, women are more strongly socialized to trust their feelings and intuitions. We thus expected that the association between implicit and explicit self-esteem would be stronger for women than for men. That is, if implicit self-esteem contains a large intuitive, experiential or affective component, then people who are in touch with their feelings and intuitions should be more likely to report explicit self-esteem scores that are congruent with their implicit self-esteem scores. Six studies supported this idea by showing that the association between implicit and explicit self-esteem is indeed stronger for women than for men. This finding held in three different cultures and for two different measures of implicit self-esteem. We discuss the implications of this finding for debates regarding the nature and validity of implicit self-esteem.     

A note on DeCaro, Thomas, and Beilock (2008): Further data demonstrate complexities in the assessment of information-integration category learning

DeCaro et al. [DeCaro, M. S., Thomas, R. D., & Beilock, S. L. (2008). Individual differences in category learning: Sometimes less working memory capacity is better than more. Cognition, 107(1), 284-294] explored how individual differences in working memory capacity differentially mediate the learning of distinct category structures. Specifically, their results showed that greater working memory capacity facilitates the learning of novel category structures that are verbalisable and discoverable through logical reasoning processes. Conversely, however, greater working memory was shown to impede the learning of novel category structures thought to be non-verbalisable, inaccessible to conscious reasoning and discoverable only through implicit (procedural) learning of appropriate stimulus-category responses. The present paper calls into question the specific nature of the category learning tasks used, in particular their ability to discriminate between different modes of category learning.     

Gender differences in implicit and explicit memory for affective passages

Thirty-two participants were administered 4 verbal tasks, an Implicit Affective Task, an Implicit Neutral Task, an Explicit Affective Task, and an Explicit Neutral Task. For the Implicit Tasks, participants were timed while reading passages aloud as quickly as possible, but not so quickly that they did not understand. A target verbal passage was repeated three times, and alternated with other previously unread passages. The Implicit Affective and Neutral passages had strong affective or neutral content, respectively. The Explicit Tasks were administered at the end of testing, and consisted of multiple choice questions regarding the passages. Priming effects in terms of more rapid reading speed for the target compared to non-target passages were seen for both the Implicit Affective Task and the Implicit Neutral Task. Overall reading speed was faster for the passages with neutral compared to affective content, consistent with studies of the emotional Stroop effect. For the Explicit memory tasks, overall performance was better on the items from the repeated passage, and on the Affective compared to Neutral Task. The male subjects showed greater priming for affective material than female subjects, and a greater gain than female subjects in explicit memory for affective compared to neutral material.     

Liking for positive words and icons moderates the association between implicit and explicit self-esteem

Whereas explicit self-esteem (ESE) refers to a conscious self-evaluation, implicit self-esteem (ISE) refers to non-conscious self-evaluation. Presumably, ISE and ESE are based on different mental processes — the experiential system and the rational system, respectively (Epstein, 1994) as well as different experiences (DeHart, Pelham, & Tennen, 2006). Two studies showed that participants who more strongly preferred positive icons and positive words showed a stronger association between ISE and ESE, presumably because they are highly willing to trust their intuitions. Because the major motive of the experiential system is the hedonic principle — pursuing positive affect and avoiding negative affect (Epstein, 2010), we argue that people's reactions to unambiguously positive stimuli should reflect their reliance on their intuition. In addition, we suggest that a better understanding of intuitiveness may yield important insights into the nature of ISE and ESE.     

Changing explicit and implicit attitudes: The case of self-esteem

Three experiments investigated predictions concerning asymmetrical patterns of implicit and explicit self-esteem change. Specifically, we investigated the influence of knowledge about the own self that is momentarily salient as well as the influence of affective valence associated with the self in memory on implicit and explicit self-esteem. The latter was induced by evaluative conditioning, the former by directed thinking about oneself. We found that while evaluative conditioning changed implicit but not explicit self-esteem (Experiment 1), thinking about the own self altered explicit but not implicit self-esteem (Experiment 2). Moreover, in a third experiment, it could be shown that the effect of evaluative conditioning can spill over to the explicit level when participants are asked to focus on their feelings prior to making their self-report judgements (Experiment 3). Implications of our results are discussed in terms of recent controversies regarding dual-process models of attitudes and associative versus propositional modes of information processing.     

Analyzing the RULEX model of category learning

Recent approaches to human category learning have often (re)invoked the notion of systematic search for good rules. The RULEX model of category learning is emblematic of this renewed interest in rule-based categorization, and is able to account for crucial findings previously thought to provide evidence in favor of prototype or exemplar models. However, a major difficulty in comparing RULEX to other models is that RULEX is framed in terms of a stochastic search process, with no analytic expressions available for its predictions. The result is that RULEX predictions can only be found through time consuming simulations, making model-fitting very difficult, and all but prohibiting more detailed investigations of the model. To remedy this problem, this paper describes an algorithmic method of calculating RULEX predictions that does not rely on numerical simulation, and yields some insight into the behavior of the model itself.     

The intergenerational transmission of implicit and explicit attitudes toward smoking: Predicting adolescent smoking initiation

This study examined the intergenerational transmission of implicit and explicit attitudes toward smoking, as well as the role of these attitudes in adolescents’ smoking initiation. There was evidence of intergenerational transmission of implicit attitudes. Mothers who had more positive implicit attitudes had children with more positive implicit attitudes. In turn, these positive implicit attitudes of adolescents predicted their smoking initiation 18-months later. Moreover, these effects were obtained above and beyond the effects of explicit attitudes. These findings provide the first evidence that the intergenerational transmission of implicit cognition may play a role in the intergenerational transmission of an addictive behavior.     

Eyetracking and selective attention in category learning

An eyetracking version of the classic Shepard, Hovland, and Jenkins (1961) experiment was conducted. Forty years of research has assumed that category learning often involves learning to selectively attend to only those stimulus dimensions useful for classification. We confirmed that participants learned to allocate their attention optimally. We also found that learners tend to fixate all stimulus dimensions early in learning. This result obtained despite evidence that participants were also testing one-dimensional rules during this period. Finally, the restriction of eye movements to only relevant dimensions tended to occur only after errors were largely (or completely) eliminated. We interpret these findings as consistent with multiple-systems theories of learning which maximize information input in order to maximize the number of learning modules involved, and which focus solely on relevant information only after one module has solved the learning problem.     

Non-abstractive global-matching models: A framework for investigating the distinctiveness effect on explicit and implicit memory

One very well-known memory phenomenon is the observation that if a specific item seems to be different or rare in any way from other items present in the same encoding context, this item is likely to be remembered more accurately. This phenomenon, named the von Restorff effect or the isolation effect, has been known since 1933 and been considered today as one of the possible ways to create distinctiveness. The aim of this article is to report that the current debate concerning its non-emergence in implicit memory tasks is directly due to a theoretical disagreement about the nature of human memory. In this paper, we conclude that non-abstractive global-matching models can provide an effective theoretical framework for the study of the distinctiveness effect with isolation both in implicit and explicit memory tasks.     

Unsupervised category learning with integral-dimension stimuli

Despite the recent surge in research on unsupervised category learning, the majority of studies have focused on unconstrained tasks in which no instructions are provided about the underlying category structure. Relatively little research has focused on constrained tasks in which the goal is to learn predefined stimulus clusters in the absence of feedback. The few studies that have addressed this issue have focused almost exclusively on stimuli for which it is relatively easy to attend selectively to the component dimensions (i.e., separable dimensions). In the present study, we investigated the ability of participants to learn categories constructed from stimuli for which it is difficult, if not impossible, to attend selectively to the component dimensions (i.e., integral dimensions). The experiments demonstrate that individuals are capable of learning categories constructed from the integral dimensions of brightness and saturation, but this ability is generally limited to category structures requiring selective attention to brightness. As might be expected with integral dimensions, participants were often able to integrate brightness and saturation information in the absence of feedback—an ability not observed in previous studies with separable dimensions. Even so, there was a bias to weight brightness more heavily than saturation in the categorization process, suggesting a weak form of selective attention to brightness. These data present an important challenge for the development of models of unsupervised category learning.     

Creating distinct implicit and explicit attitudes with an illusory correlation paradigm

Two studies used an illusory correlation procedure to test whether distinct implicit and explicit evaluations can result from the same learning episode. All participants learned twice as much about the qualities of one group (majority) than another (minority). In one condition, the ratio of positive to negative information was equal between groups. In other conditions, the majority group showed proportionally more positive qualities than the minority group, or vice versa. Participants in the pro-majority and pro-minority conditions formed both implicit and explicit attitudes consistent with the attitude induction. Participants in the illusory correlation condition showed the expected preference for the majority group (the illusory bias), but showed no implicit preference, suggesting distinct influences on implicit and explicit attitude formation. The effects are consistent with dual-process models in which implicit attitudes reflect accounting of covariation and explicit attitudes reflect interpretative judgments of that covariation.     

Compensatory processing during rule-based category learning in older adults

Healthy older adults typically perform worse than younger adults at rule-based category learning, but better than patients with Alzheimer’s or Parkinson’s disease. To further investigate aging’s effect on rule-based category learning, we monitored event-related potentials (ERPs) while younger and neuropsychologically typical older adults performed a visual category-learning task with a rule-based category structure and trial-by-trial feedback. Using these procedures, we previously identified ERPs sensitive to categorization strategy and accuracy in young participants. In addition, previous studies have demonstrated the importance of neural processing in the prefrontal cortex and the medial temporal lobe for this task. In this study, older adults showed lower accuracy and longer response times than younger adults, but there were two distinct subgroups of older adults. One subgroup showed near-chance performance throughout the procedure, never categorizing accurately. The other subgroup reached asymptotic accuracy that was equivalent to that in younger adults, although they categorized more slowly. These two subgroups were further distinguished via ERPs. Consistent with the compensation theory of cognitive aging, older adults who successfully learned showed larger frontal ERPs when compared with younger adults. Recruitment of prefrontal resources may have improved performance while slowing response times. Additionally, correlations of feedback-locked P300 amplitudes with category-learning accuracy differentiated successful younger and older adults. Overall, the results suggest that the ability to adapt one’s behavior in response to feedback during learning varies across older individuals, and that the failure of some to adapt their behavior may reflect inadequate engagement of prefrontal cortex.     

Inattentional blindness for ignored words: Comparison of explicit and implicit memory tasks

Inattentional blindness is described as the failure to perceive a supra-threshold stimulus when attention is directed away from that stimulus. Based on performance on an explicit recognition memory test and concurrent functional imaging data Rees, Russell, Frith, and Driver [Rees, G., Russell, C., Frith, C. D., & Driver, J. (1999). Inattentional blindness versus inattentional amnesia for fixated but ignored words. Science, 286, 2504–2507] reported inattentional blindness for word stimuli that were fixated but ignored. The present study examined both explicit and implicit memory for fixated but ignored words using a selective-attention task in which overlapping picture/word stimuli were presented at fixation. No explicit awareness of the unattended words was apparent on a recognition memory test. Analysis of an implicit memory task, however, indicated that unattended words were perceived at a perceptual level. Thus, the selective-attention task did not result in perfect filtering as suggested by Rees et al. While there was no evidence of conscious perception, subjects were not blind to the implicit perceptual properties of fixated but ignored words.     

Prototype-distortion category learning: a two-phase learning process across a distributed network

This paper reviews a body of work conducted in our laboratory that applies functional magnetic resonance imaging (fMRI) to better understand the biological response and change that occurs during prototype-distortion learning. We review results from two experiments (Little, Klein, Shobat, McClure, & Thulborn, 2004; Little & Thulborn, 2005) that provide support for increasing neuronal efficiency by way of a two-stage model that includes an initial period of recruitment of tissue across a distributed network that is followed by a period of increasing specialization with decreasing volume across the same network. Across the two studies, participants learned to classify patterns of random-dot distortions (Posner & Keele, 1968) into categories. At four points across this learning process subjects underwent examination by fMRI using a category-matching task. A large-scale network, altered across the protocol, was identified to include the frontal eye fields, both inferior and superior parietal lobules, and visual cortex. As behavioral performance increased, the volume of activation within these regions first increased and later in the protocol decreased. Based on our review of this work we propose that: (i) category learning is reflected as specialization of the same network initially implicated to complete the novel task, and (ii) this network encompasses regions not previously reported to be affected by prototype-distortion learning.     

Instance memorization and category influence: Challenging the evidence for multiple systems in category learning

A class of dual-system theories of categorization assumes a categorization system based on actively formed prototypes in addition to a separate instance memory system. It has been suggested that, because they have used poorly differentiated category structures (such as the influential “5-4” structure), studies supporting the alternative exemplar theory reveal little about the properties of the categorization system. Dual-system theories assume that the instance memory system only influences categorization behaviour via similarity to single isolated instances, without generalization across instances. However, we present the results of two experiments employing the 5-4 structure to argue against this. Experiment 1 contrasted learning in the standard 5-4 structure with learning in an even more poorly differentiated 5-4 structure. In Experiment 2, participants memorized the 5-4 structure based on a five minute simultaneous presentation of all nine category instances. Both experiments revealed category influences as reflected by differences in instance learnability and generalization, at variance with the dual-system prediction. These results have implications for the exemplars versus prototypes debate and the nature of human categorization mechanisms.     

Differential effects of regulatory fit on category learning

Motivation affects the degree to which people engage in tasks as well as the processes that they bring to bear. We explore the proposal that a fit between a person’s situationally induced self-regulatory focus and the reward structure of the task that they are pursuing supports greater flexibility in processing than does a mismatch between regulatory focus and reward structure. In two experiments, we prime regulatory focus and manipulate task reward structure. Our participants perform a rule-based learning task whose solution requires flexible strategy testing as well as an information-integration task for which flexible strategy use hinders learning. Across two experiments, we predict and obtain a three-way interaction between regulatory focus, reward structure, and task. Relative to a mismatch, a match leads to better rule-based task performance, but worse performance on the information-integration task. We relate these findings to other work on motivation and choking under pressure.     

Distinguishing implicit and explicit learning

I agree with Dienes and Berry’s (1997) and Neal and Hesketh’s (1997) call for investigations of the qualitative differences between implicit and explicit learning and note that such investigations must be guided by a workable definition of what is implicit and by theories that predict what the qualitative differences might be. Following Schacter, Bowers, and Booker’s (1989) retrieval intentionality criterion, I propose using anencoding intentionality criterion to distinguish implicit from explicit learning; we can reasonably infer that implicit learning has occurred when a variable known to influence explicit learning has no effect in a comparable implicit learning condition. I then suggest that implicit learning depends on noncognitive, nonhierarchical associations, whereas explicit learning depends on cognitive, hierarchical associations, and briefly describe an experiment that confirms a qualitative difference between implicit and explicit learning predicted by this hypothesis.