Search

We report the results of a preregistered study that tested the effectiveness of inoculating participants against Islamophobic and radical-Islamist disinformation. Participants in the experimental (inoculation) condition watched a video that explained common rhetorical markers of radical-Islamist and Islamophobic disinformation that had been identified in an analysis of YouTube content. The information was presented in a neutral context not involving Islam and focused on analysis of the misleading argumentation. The control group watched a video about an unrelated topic. Participants were then exposed to target videos with "gateway" content that constituted an entry point to potential Islamist or Islamophobic radicalization. Both videos contained numerous items of disinformation. Participants then answered a variety of questions such as how likely they were to share the video, their level of agreement, and their perceived accuracy of the video. Participants who had received the inoculation displayed less agreement with the video content, perceived the video as less reliable, and were less likely to share it in comparison with participants in the control group. The study provides support for the use of argument-based inoculation in combatting extremist messages.

Algorithms for approximate Bayesian inference, such as those based on sampling (i.e., Monte Carlo methods), provide a natural source of models of how people may deal with uncertainty with limited cognitive resources. Here, we consider the idea that individual differences in working memory capacity (WMC) may be usefully modeled in terms of the number of samples, or "particles," available to perform inference. To test this idea, we focus on two recent experiments that report positive associations between WMC and two distinct aspects of categorization performance: the ability to learn novel categories, and the ability to switch between different categorization strategies ("knowledge restructuring"). In favor of the idea of modeling WMC as a number of particles, we show that a single model can reproduce both experimental results by varying the number of particles--increasing the number of particles leads to both faster category learning and improved strategy-switching. Furthermore, when we fit the model to individual participants, we found a positive association between WMC and best-fit number of particles for strategy switching. However, no association between WMC and best-fit number of particles was found for category learning. These results are discussed in the context of the general challenge of disentangling the contributions of different potential sources of behavioral variability.

People frequently continue to use inaccurate information in their reasoning even after a credible retraction has been presented. This phenomenon is often referred to as the continued influence effect of misinformation. The repetition of the original misconception within a retraction could contribute to this phenomenon, as it could inadvertently make the "myth" more familiar--and familiar information is more likely to be accepted as true. From a dual-process perspective, familiarity-based acceptance of myths is most likely to occur in the absence of strategic memory processes. Thus, we examined factors known to affect whether strategic memory processes can be utilized: age, detail, and time. Participants rated their belief in various statements of unclear veracity, and facts were subsequently affirmed and myths were retracted. Participants then rerated their belief either immediately or after a delay. We compared groups of young and older participants, and we manipulated the amount of detail presented in the affirmative or corrective explanations, as well as the retention interval between encoding and a retrieval attempt. We found that (a) older adults over the age of 65 were worse at sustaining their postcorrection belief that myths were inaccurate, (b) a greater level of explanatory detail promoted more sustained belief change, and (c) fact affirmations promoted more sustained belief change in comparison with myth retractions over the course of 1 week (but not over 3 weeks), This supports the notion that familiarity is indeed a driver of continued influence effects.

Is consolidation needed to account for retroactive interference in free recall? Interfering mental activity during the retention interval of a memory task impairs performance, in particular if the interference occurs in temporal proximity to the encoding of the to-be-remembered (TBR) information. There are at least two rival theoretical accounts of this temporal gradient of retroactive interference. The cognitive neuroscience literature has suggested neural consolidation is a pivotal factor determining item recall. According to this account, interfering activity interrupts consolidation processes that would otherwise stabilize the memory representations of TBR items post-encoding. Temporal distinctiveness theory, by contrast, proposes that the retrievability of items depends on their isolation in psychological time. According to this theory, information processed after the encoding of TBR material will reduce the temporal distinctiveness of the TBR information. To test between these accounts, implementations of consolidation were added to the SIMPLE model of memory and learning. We report data from two experiments utilizing a two-list free recall paradigm. Modeling results imply that SIMPLE was able to model the data and did not benefit from the addition of consolidation. It is concluded that the temporal gradient of retroactive interference cannot be taken as evidence for memory consolidation.

The dissemination and control of information are indispensable ingredients of violent conflict, with all parties involved in a conflict or at war seeking to frame the discussion on their own terms. Those attempts at information control often involve the dissemination of misinformation or disinformation (i.e., information that is incorrect by accident or intent, respectively). We review the way in which misinformation can facilitate violent conflicts and, conversely, how the successful refutation of misinformation can contribute to peace. We illustrate the relevant cognitive principles by examining two case studies. The first, a retrospective case, involves the Iraq War of 2003 and the "War on Terror." The second, a prospective case, points to likely future sources of conflict arising from climate change and its likely consequences.

Information changes as it is passed from person to person, with this process of cultural transmission allowing the minds of individuals to shape the information that they transmit. We present mathematical models of cultural transmission which predict that the amount of information passed from person to person should affect the rate at which that information changes. We tested this prediction using a function-learning task, in which people learn a functional relationship between two variables by observing the values of those variables. We varied the total number of observations and the number of those observations that take unique values. We found an effect of the number of observations, with functions transmitted using fewer observations changing form more quickly. We did not find an effect of the number of unique observations, suggesting that noise in perception or memory may have affected learning. (Contains 4 notes and 3 figures.)

The article tests the assumption that forgetting in working memory for verbal materials is caused by time-based decay, using the complex-span paradigm. Participants encoded 6 letters for serial recall; each letter was preceded and followed by a processing period comprising 4 trials of difficult visual search. Processing duration, during which memory could decay, was manipulated via search set size. This manipulation increased retention interval by up to 100% without having any effect on recall accuracy. This result held with and without articulatory suppression. Two experiments using a dual-task paradigm showed that the visual search process required central attention. Thus, even when memory maintenance by central attention and by articulatory rehearsal was prevented, a large delay had no effect on memory performance, contrary to the decay notion. Most previous experiments that manipulated the retention interval and the opportunity for maintenance processes in complex span have confounded these variables with time pressure during processing periods. Three further experiments identified time pressure as the variable that affected recall. We conclude that time-based decay does not contribute to the capacity limit of verbal working memory. (Contains 12 tables, 15 figures and 5 footnotes.)

The concept of attention is central to theorizing in learning as well as in working memory. However, research to date has yet to establish how attention as construed in one domain maps onto the other. We investigate two manifestations of attention in category- and cue-learning to examine whether they might provide common ground between learning and working memory. Experiment 1 examined blocking and highlighting effects in an associative learning paradigm, which are widely thought to be attentionally mediated. No relationship between attentional performance indicators and working memory capacity (WMC) was observed, despite the fact that WMC was strongly associated with overall learning performance. Experiment 2 used a knowledge restructuring paradigm, which is known to require recoordination of partial category knowledge using representational attention. We found that the extent to which people successfully recoordinated their knowledge was related to WMC. The results illustrate a link between WMC and representational--but not dimensional--attention in category learning. (Contains 9 figures, 11 tables and 8 footnotes.)

Working memory is crucial for many higher level cognitive functions, ranging from mental arithmetic to reasoning and problem solving. Likewise, the ability to learn and categorize novel concepts forms an indispensable part of human cognition. However, very little is known about the relationship between working memory and categorization. This article reports 2 studies that related people's working memory capacity (WMC) to their learning performance on multiple rule-based and information-integration perceptual categorization tasks. In both studies, structural equation modeling revealed a strong relationship between WMC and category learning irrespective of the requirement to integrate information across multiple perceptual dimensions. WMC was also uniformly related to people's ability to focus on the most task-appropriate strategy, regardless of whether or not that strategy involved information integration. Contrary to the predictions of the multiple systems view of categorization, working memory thus appears to underpin performance in both major classes of perceptual category-learning tasks. (Contains 8 tables, 12 figures and 3 footnotes.)

Working memory is crucial for many higher-level cognitive functions, ranging from mental arithmetic to reasoning and problem solving. Likewise, the ability to learn and categorize novel concepts forms an indispensable part of human cognition. However, very little is known about the relationship between working memory and categorization, and modeling in category learning has thus far been largely uninformed by knowledge about people's memory processes. This article reports a large study (N = 113) that related people's working memory capacity (WMC) to their category-learning performance using the 6 problem types of Shepard, Hovland, and Jenkins (1961). Structural equation modeling revealed a strong relationship between WMC and category learning, with a single latent variable accommodating performance on all 6 problems. A model of categorization (the Attention Learning COVEring map, ALCOVE; Kruschke, 1992) was fit to the individual data and a single latent variable was sufficient to capture the variation among associative learning parameters across all problems. The data and modeling suggest that working memory mediates category learning across a broad range of tasks. (Contains 7 figures, 5 tables and 8 footnotes.)

The assumption in some current theories of probabilistic categorization is that people gradually attenuate their learning in response to unavoidable error. However, existing evidence for this error discounting is sparse and open to alternative interpretations. We report 2 probabilistic-categorization experiments in which we investigated error discounting by shifting feedback probabilities to new values after different amounts of training. In both experiments, responding gradually became less responsive to errors, and learning was slowed for some time after the feedback shift. Both results were indicative of error discounting. Quantitative modeling of the data revealed that adding a mechanism for error discounting significantly improved the fits of an exemplar-based and a rule-based associative learning model, as well as of a recency-based model of categorization. We conclude that error discounting is an important component of probabilistic learning. (Contains 5 figures and 2 tables.)

Knowledge restructuring refers to changes in the strategy with which people solve a given problem. Two types of knowledge restructuring are supported by existing category learning models. The first is a relearning process, which involves incremental updating of knowledge as learning progresses. The second is a recoordination process, which involves novel changes in the way existing knowledge is applied to the task. Whereas relearning is supported by both single- and multiple-module models of category learning, only multiple-module models support recoordination. To date, only relearning has been directly supported empirically. We report two category learning experiments that provide direct evidence of recoordination. People can fluidly alternate between different categorization strategies, and moreover, can reinstate an old strategy even after prolonged use of an alternative. The knowledge restructuring data are not well fit by a single-module model (ALCOVE). By contrast, a multiple-module model (ATRIUM) quantitatively accounts for recoordination. Low-level changes in the distribution of dimensional attention are shown to subsequently affect how ATRIUM coordinates its modular knowledge. We argue that learning about complex tasks occurs at the level of the partial knowledge elements used to generate a response strategy. (Contains 12 tables and 16 figures.)

We investigated the effects of the duration and type of to-be-articulated distractors during encoding of a verbal list into short-term memory (STM). Distractors and to-be-remembered items alternated during list presentation, as in the complex-span task that underlies much of working-memory research. According to an interference model of STM, known as serial order in a box (SOB; Farrell & Lewandowsky, 2002), additional repeated articulations of the same word between list items should cause minimal further disruption of encoding into STM even though the retention interval for early list items is increased. SOB also predicts that the articulation of several different distractor items should lead to much enhanced disruption if the distractor interval is increased. Those predictions were qualitatively confirmed in 4 experiments that found that it is the type of distractors, not their total duration, that determines the success of encoding a list into STM. The results pose a challenge to temporal models of complex-span performance, such as the time-based resource sharing model (Barrouillet, Bernardin, & Camos, 2004). The results add to a growing body of evidence that memory for the short term is not exclusively governed by purely temporal processes. (Contains 6 footnotes, 3 tables, and 10 figures.)

Working memory updating (WMU) has been identified as a cognitive function of prime importance for everyday tasks and has also been found to be a significant predictor of higher mental abilities. Yet, little is known about the constituent processes of WMU. We suggest that operations required in a typical WMU task can be decomposed into 3 major component processes: retrieval, transformation, and substitution. We report a large-scale experiment that instantiated all possible combinations of those 3 component processes. Results show that the 3 components make independent contributions to updating performance. We additionally present structural equation models that link WMU task performance and working memory capacity (WMC) measures. These feature the methodological advancement of estimating interindividual covariation and experimental effects on mean updating measures simultaneously. The modeling results imply that WMC is a strong predictor of WMU skills in general, although some component processes--in particular, substitution skills--were independent of WMC. Hence, the reported predictive power of WMU measures may rely largely on common WM functions also measured in typical WMC tasks, although substitution skills may make an independent contribution to predicting higher mental abilities. (Contains 12 footnotes, 8 tables and 3 figures.)

What drives forgetting in working memory? Recent evidence suggests that in a complex-span task in which an irrelevant processing task alternates with presentation of the memoranda, recall declines when the time taken to complete the processing task is extended while holding the time for rehearsal in between processing steps constant (Portrat, Barrouillet, & Camos, 2008). This time-based forgetting was interpreted in support for the role of time-based decay in working memory. In this article, we argue the contrary position by (a) showing in an experiment that the processing task in Portrat et al.'s (2008) study gave rise to uncontrolled post-error processes that occupied the attentional bottleneck, thus preventing restorative rehearsal, and (b) showing that when those post-error processes are statistically controlled, there is no evidence for temporal decay in Portrat et al.'s study. We conclude that currently there exists no direct evidence for temporal decay in the complex-span paradigm. (Contains 2 tables, 1 figure and 1 footnote.)

In probabilistic categorization, also known as multiple cue probability learning (MCPL), people learn to predict a discrete outcome on the basis of imperfectly valid cues. In MCPL, normatively irrelevant cues are usually ignored, which stands in apparent conflict with recent research in deterministic categorization that has shown that people sometimes use irrelevant cues to gate access to partial knowledge encapsulated in independent partitions. The authors report 2 experiments that sought support for the existence of such knowledge partitioning in probabilistic categorization. The results indicate that, as in other areas of concept acquisition (such as function learning and deterministic categorization), a significant proportion of participants partitioned their knowledge on the basis of an irrelevant cue. The authors show by computational modeling that knowledge partitioning cannot be accommodated by 2 exemplar models (Generalized Context Model and Rapid Attention Shifts 'N Learning), whereas a rule-based model (General Recognition Theory) can capture partitioned performance. The authors conclude by pointing to the necessity of a mixture-of-experts approach to capture performance in MCPL and by identifying reduction of complexity as a possible explanation for partitioning. (Contains 7 footnotes, 4 tables, and 7 figures.)

Despite the fact that categories are often composed of correlated features, the evidence that people detect and use these correlations during intentional category learning has been overwhelmingly negative to date. Nonetheless, on other categorization tasks, such as feature prediction, people show evidence of correlational sensitivity. A conventional explanation holds that category learning tasks promote rule use, which discards the correlated-feature information, whereas other types of category learning tasks promote exemplar storage, which preserves correlated-feature information. Contrary to that common belief, the authors report 2 experiments that demonstrate that using probabilistic feedback in an intentional categorization task leads to sensitivity to correlations among nondiagnostic cues. Deterministic feedback eliminates correlational sensitivity by focusing attention on relevant cues. Computational modeling reveals that exemplar storage coupled with selective attention is necessary to explain this effect. (Contains 6 tables, 14 figures and 5 footnotes.)

This article presents four experiments that tested predictions of SOB (Serial Order in a Box), an interference-based theory of short-term memory. Central to SOB is the concept of novelty-sensitive encoding, which holds that items are encoded to the extent that they differ from already-encoded information. On the additional assumption that distractors are encoded into memory in the same manner as list items, the theory predicts differential effects of interfering activity based on the similarity structure of distractors. Consistent with predictions, three experiments showed that overt articulation of distractors in between recalls of list items did not affect forgetting when the same distractor was repeated multiple times, whereas forgetting was observed if several different distractors were articulated within the same time span. A fourth experiment showed that the absence of forgetting with repeated articulations of the same item was not due to compensatory attentional refreshing of memory traces. The data support the notion that forgetting from short-term memory arises from interference and are difficult to reconcile with temporal decay. (Contains 8 figures and 3 tables.)

Three hypotheses of forgetting from immediate memory were tested: time-based decay, decreasing temporal distinctiveness, and interference. The hypotheses were represented by 3 models of serial recall: the primacy model, the SIMPLE (scale-independent memory, perception, and learning) model, and the SOB (serial order in a box) model, respectively. The models were fit to 2 experiments investigating the effect of filled delays between items at encoding or at recall. Short delays between items, filled with articulatory suppression, led to massive impairment of memory relative to a no-delay baseline. Extending the delays had little additional effect, suggesting that the passage of time alone does not cause forgetting. Adding a choice reaction task in the delay periods to block attention-based rehearsal did not change these results. The interference-based SOB fit the data best; the primacy model overpredicted the effect of lengthening delays, and SIMPLE was unable to explain the effect of delays at encoding. The authors conclude that purely temporal views of forgetting are inadequate.

According to temporal distinctiveness models, items that are temporally isolated from their neighbors during list presentation are more distinct and thus should be recalled better. Contrary to that expectation of distinctiveness views, much recent evidence has shown that forward short-term serial recall is unaffected by temporal isolation. We report two experiments using reconstruction of order tasks that confirmed that when report order is strictly forward, temporal isolation does not benefit performance. However, both experiments also showed that when report order is unconstrained, temporal isolation does benefit performance. The differences between forward and unconstrained report were found to be independent of whether or not people can anticipate the type of test at encoding. The presence and absence of isolation effects under two different conditions, both requiring memory for order, challenges many existing theories of memory but is compatible with the idea that multiple differentially weighted types of information contribute to memory retrieval.

In short-term serial recall, similar-sounding items are remembered more poorly than items that do not sound alike. When lists mix similar and dissimilar items, performance on the dissimilar items is of considerable theoretical interest. Farrell and Lewandowsky [Farrell, S., & Lewandowsky, S. (2003). Dissimilar items benefit from phonological similarity in serial recall. "Journal of Experimental Psychology: Learning, Memory, and Cognition," 29, 838-849.] recently showed that if guessing strategies are controlled, dissimilar items on mixed lists are recalled more accurately than on pure dissimilar lists, a finding that challenges several current theories of serial recall. This article presents two experiments that extend the generality of the mixed-list advantage for dissimilar items and then applies three theories of memory--the primacy model, SIMPLE, and SOB--to the data. The simulations show that the data are best explained by the SOB theory [Farrell, S. (2006). Mixed-list phonological similarity effects in delayed serial recall. "Journal of Memory and Language," 55, 587-600; Farrell, S., & Lewandowsky, S. (2002). An endogenous distributed model of ordering in serial recall. "Psychonomic Bulletin & Review," 9, 59-79.] which, unlike most other current theories, posits that similarity has an effect at the time of encoding.

According to temporal distinctiveness models, items that are temporally isolated from their neighbors during list presentation are more distinct and thus should be recalled better. Event-based theories, by contrast, deny that time plays a role at encoding and predict no beneficial effect of temporal isolation, although they acknowledge that a pause after item presentation may afford extra opportunity for a consolidation process such as rehearsal or grouping. We report two experiments aimed at differentiating between the two classes of theories. The results show that neither serial recall nor probed recall benefit from temporal isolation, unless participants use pauses to group a list. Simulations of the SIMPLE model provide convergent evidence that short-term memory for serial order need not involve temporal representations.

Knowledge restructuring occurs when people shift to a new strategy or representation during learning. Although knowledge restructuring can frequently be experimentally encouraged, there are instances in which people resist restructuring and continue to use an expedient but imperfect initial strategy. The authors report 3 category learning experiments that reconciled those conflicting outcomes by postulating that, for restructuring to occur, learners must be dissatisfied with their knowledge and a usable alternative must be available. In line with expectation, restructuring was elicited only when an alternative strategy was pointed out and when people's initial expedient strategy entailed performance error. Neither error nor information about the alternative strategy by itself was sufficient to induce restructuring.

Knowledge partitioning is a theoretical construct holding that knowledge is not always integrated and homogeneous but may be separated into independent parcels containing mutually contradictory information. Knowledge partitioning has been observed in research on expertise, categorization, and function learning. This article presents a theory of function learning (the population of linear experts model--POLE) that assumes people partition their knowledge whenever they are presented with a complex task. The authors show that POLE is a general model of function learning that accommodates both benchmark results and recent data on knowledge partitioning. POLE also makes the counterintuitive prediction that a person's distribution of responses to repeated test stimuli should be multimodal. The authors report 3 experiments that support this prediction.

The authors present 2 experiments that establish the presence of knowledge partitioning in perceptual categorization. Many participants learned to rely on a context cue, which did not predict category membership but identified partial boundaries, to gate independent partial categorization strategies. When participants partitioned their knowledge, a strategy used in 1 context was unaffected by knowledge demonstrably present in other contexts. An exemplar model, attentional learning covering map, was shown to be unable to accommodate knowledge partitioning. Instead, a mixture-of-experts model, attention to rules and instances in a unified model (ATRIUM), could handle the results. The success of ATRIUM resulted from its assumption that people memorize not only exemplars but also the way in which they are to be classified.

Several competing theories of short-term memory can explain serial recall performance at a quantitative level. However, most theories to date have not been applied to the accompanying pattern of response latencies, thus ignoring a rich and highly diagnostic aspect of performance. This article explores and tests the error latency predictions of four alternative mechanisms for the representation of serial order. Data from three experiments show that latency is a negative function of transposition displacement, such that list items that are reported too soon (ahead of their correct serial position) are recalled more slowly than items that are reported too late. We show by simulation that these data rule out three of the four representational mechanisms. The data support the notion that serial order is represented by a primacy gradient that is accompanied by suppression of recalled items.

This article investigated the role of the recognition criterion in the verbal overshadowing effect (VOE). In 3 experiments, people witnessed an event, verbally described a perpetrator, and then attempted identification. The authors found in Experiment 1, which included a "not present" response option and both perpetrator-present (PP) and perpetrator-absent (PA) lineups, an increased reluctance to identify a person from both lineup types after verbalization. Experiment 2 incorporated a forced-choice procedure, and the authors found no effect of verbalization on identification performance. Experiment 3 replicated the essential aspects of these results. Consequently, the VOE may reflect a change in recognition criterion rather than a changed processing style or alteration of the underlying memory trace. This conclusion was confirmed by computational modeling of the data.

The recent hybrid model of categorization, Attention Learning Covering Map (ALCOVE), combines desirable properties of exemplar models with a connectionist architecture and learning rule. An important property is the apparent ability of ALCOVE to account for base-rate neglect. ALCOVE's base-rate neglect predictions are reexamined, and their shortcomings demonstrated. (SLD)

Describes a student project for a class on cognitive psychology in which students learn about the application of psychology principles by designing and producing television commercials. Discusses evaluation by both students and teachers. Explains that the principles used include primacy, rehearsal, repetition, and cue dependence. (DK)

A method for multidimensional scaling that is highly resistant to the effects of outliers is described. Some Monte Carlo simulations illustrate the efficacy of the procedure, which performs well with or without outliers. (SLD)

An extension to Murdock's Theory of Distributed Associative Memory, based on associative chaining between items, is presented. The extended theory is applied to several serial order phenomena, including serial list learning, delayed recall effects, partial report effects, and buildup and release from proactive interference. (TJH)