The role of working memory capacity and interference resolution mechanisms in task switching

Theories of task switching have emphasized a number of control mechanisms that may support the ability to flexibly switch between tasks. The present study examined the extent to which individual differences in working memory (WM) capacity and two measures of interference resolution, response–distractor inhibition and resistance to proactive interference (PI), account for variability in task switching, including global costs, local costs, and N-2 repetition costs. A total of 102 young and 60 older adults were tested on a battery of tasks. Composite scores were created for WM capacity, response–distractor inhibition, and resistance to PI; shifting was indexed by rate residual scores, which combine response time and accuracy and account for individual differences in processing speed. Composite scores served as predictors of task switching. WM was significantly related to global switch costs. While resistance to PI and WM explained some variance in local costs, these effects did not reach significance. In contrast, none of the control measures explained variance in N-2 repetition costs. Furthermore, age effects were only evident for N-2 repetition costs, with older adults demonstrating larger costs than young adults. Results are discussed within the context of theoretical models of task switching.     

Happiness increases verbal and spatial working memory capacity where sadness does not: Emotion,working memory and executive control

The effects of emotion on working memory and executive control are often studied in isolation. Positive mood enhances verbal and impairs spatial working memory, whereas negative mood enhances spatial and impairs verbal working memory. Moreover, positive mood enhances executive control, whereas negative mood has little influence. We examined how emotion influences verbal and spatial working memory capacity, which requires executive control to coordinate between holding information in working memory and completing a secondary task. We predicted that positive mood would improve both verbal and spatial working memory capacity because of its influence on executive control. Positive, negative and neutral moods were induced followed by completing a verbal (Experiment 1) or spatial (Experiment 2) working memory operation span task to assess working memory capacity. Positive mood enhanced working memory capacity irrespective of the working memory domain, whereas negative mood had no influence on performance. Thus, positive mood was more successful holding information in working memory while processing task-irrelevant information, suggesting that the influence mood has on executive control supersedes the independent effects mood has on domain-specific working memory.     

Performance on auditory and visual temporal information processing is related to psychometric intelligence

The present study investigated the relationship between psychometric intelligence and temporal resolution power (TRP) as simultaneously assessed by auditory and visual psychophysical timing tasks. In addition, three different theoretical models of the functional relationship between TRP and psychometric intelligence as assessed by means of the Adaptive Matrices Test (AMT) were developed. To test the validity of these models, structural equation modeling was applied. Empirical data supported a hierarchical model that assumed auditory and visual modality-specific temporal processing at a first level and amodal temporal processing at a second level. This second-order latent variable was substantially correlated with psychometric intelligence. Therefore, the relationship between psychometric intelligence and psychophysical timing performance can be explained best by a hierarchical model of temporal information processing.     

The broad factor of working memory is virtually isomorphic to fluid intelligence tested under time pressure

How much overall variance in fluid intelligence (Gf) can be predicted by four working memory (WM) functions: storage capacity, attention control, relational integration, and updating was investigated under time pressured Gf testing. Confirmatory factor analysis indicated that the broad WM factor, which was subsumed by these four WM functions, shared 83.4% of variance with Gf tested under pressure, whereas a reanalysis of previous data with the same model showed that only 58.2% variance was shared with virtually untimed Gf tests. Moreover, in timed Gf tests, only the easiest, early items contributed to the WM-Gf correlation, whereas in untimed tests also the hardest, late items were linked with Gf. These results suggest that the measurement of “fast” intelligence primarily taps the functions of WM, whereas “slow(er)” intelligence depends also on some other cognitive processes beyond WM.     

视觉工作记忆负载类型对注意选择的影响

通过操纵Flanker任务相对于视觉工作记忆任务的呈现位置, 探讨在视觉工作记忆编码和保持阶段, 精度负载和容量负载对注意选择的影响。行为结果发现, Flanker任务呈现位置和视觉工作记忆负载类型影响注意选择; ERP结果发现, 在保持阶段, 当搜索目标和干扰项不一致时, 负载类型影响N2成分。研究表明, 在编码阶段, 视觉工作记忆负载主要通过占用更多知觉资源降低干扰效应, 支持知觉负载理论; 而在保持阶段, 当Flanker任务位于记忆项内部时, 两类负载在工作记忆表征过程中不同的神经活动导致投入到注意选择的认知控制资源不同, 可能是两类负载影响保持阶段注意选择的机制。     

The phenotypic and genotypic relation between working memory speed and capacity

This study examined the phenotypic and genotypic relationship between working memory speed (WMS) and working memory capacity (WMC) in 12-year-old twins and their siblings (N = 409). To asses WMS all children performed a reaction time task with three memory loads from which a basic mental speed measure and the derived slope were used. WMC was measured with two subtests of the WISC-R, namely Arithmetic and Digit Span. The phenotypic correlations among the WMS and WMC indices were around − 0.30. Heritabilities for all variables ranged from 43% to 56%. Structural equating modelling revealed that a model with two genetic factors, representing WMS and WMC, which were correlated (− 0.54) fitted the data best, indicating that WMS and WMC are partly mediated by the same set of genes and partly by separate sets of genes. When general IQ was simultaneously analysed with the data the correlation between the genetic factors for WMS and WMC decreased (− 0.25), but was still significant. This means that  50% of the genetic correlation between WMS and WMC is explained by IQ.     

Relationship between working memory capacity and contingent involuntary orienting

Individual differences in working memory capacity are related to the ability to control attention; where less working memory capacity is associated with less attentional control. A well-known demonstration of attentional control is contingent involuntary orienting (Folk, Remington, & Johnston, 1992), which is the finding that visuospatial attention is captured by a salient peripheral cue, but only if the cue is featurally similar to the target of search and not if the cue is featurally dissimilar. This control of attention and ability to resist shifting attention towards an irrelevant visual cue is believed to be moderated by attentional settings for target-specific features. This study establishes that working memory capacity is related to contingent involuntary orienting of attention. Lower working memory capacity was associated with larger stimulus-driven cueing effects at short cue-to-target onset asynchronies, than at longer asynchronies, suggesting working memory capacity was associated with the ability to control covert orienting of attention at early processing stages.     

Effects of emotional content on working memory capacity

Emotional events tend to be remembered better than neutral events, but emotional states and stimuli may also interfere with cognitive processes that underlie memory performance. The current study investigated the effects of emotional content on working memory capacity (WMC), which involves both short term storage and executive attention control. We tested competing hypotheses in a preregistered experiment (N?=?297). The emotional enhancement hypothesis predicts that emotional stimuli attract attention and additional processing resources relative to neutral stimuli, thereby making it easier to encode and store emotional information in WMC. The emotional impairment hypothesis, by contrast, predicts that emotional stimuli interfere with attention control and the active maintenance of information in working memory. Participants completed a common measure of WMC (the operation span task; Turner, M. L., &; Engle, R. W. [1989]. Is working memory capacity task dependent? Journal of Memory and Language, 28, 127–154) that included either emotional or neutral words. Results revealed that WMC was reduced for emotional words relative to neutral words, consistent with the emotional impairment hypothesis.     

Children's working memory: Its structure and relationship to fluid intelligence

Working memory (WM) has been predominantly studied in adults. The insights provided by these studies have led to the development of competing theories on the structure of WM and conflicting conclusions on how strongly WM components are related to higher order thinking skills such as fluid intelligence. However, it remains unclear whether and to what extent the theories and findings derived from adult data generalize to children. The purpose of the present study is therefore to investigate children's WM (N = 161), who attended classes at the end of kindergarten in Luxembourg. Specifically, we examine different structural models of WM and how its components, as defined in these models, are related to fluid intelligence. Our results indicate that short-term storage capacity primarily explains the relationship between WM and fluid intelligence. Based on these observations we discuss the theoretical and methodological issues that arise when children's WM is investigated.     

A Bayesian hierarchical model for the measurement of working memory capacity

Working memory is the memory system that allows for conscious storage and manipulation of information. The capacity of working memory is extremely limited. Measurements of this limit, and what affects it, are critical to understanding working memory. Cowan (2001) and Pashler (1988) suggested applying multinomial tree models to data from change detection paradigms in order to estimate working memory capacity. Both Pashler and Cowan suggested simple formulas for estimating capacity with these models. However, in many cases, these simple formulas are inadequate, and may lead to inefficient or biased estimation of working memory capacity. I propose a Bayesian hierarchical alternative to the Pashler and Cowan formulas, and show that the hierarchical model outperforms the traditional formulas. The models are easy to use and appropriate for a wide range of experimental designs. An easy-to-use graphical user interface for fitting the hierarchical model to data is available.     

The concurrent validity and test–retest reliability of a visuospatial working memory task

To determine whether the visuospatial n-back working memory task is a reliable and valid measure of cognitive processes believed to underlie intelligence, this study compared the reaction times and accuracy of performance of 70 participants, with performance on the Multidimensional Aptitude Battery (MAB). Testing was conducted over two sessions separated by 1 week. Participants completed the MAB during the second test session. Moderate test–retest reliability for percentage accuracy scores was found across the four levels of the n-back task, whilst reaction times were highly reliable. Furthermore, participants' performance on the MAB was negatively correlated with accuracy of performance at the easier levels of the n-back task and positively correlated with accuracy of performance at the harder task levels. These findings confirm previous research examining the cognitive basis of intelligence, and suggest that intelligence is the product of faster speed of information processing, as well as superior working memory capacity.     

Depressive thoughts limit working memory capacity in dysphoria

Dysphoria is associated with persistence of attention on mood-congruent information. Longer time attending to mood-congruent information for dysphoric individuals (DIs) detracts from goal-relevant information processing and should reduce working memory (WM) capacity. Study 1 showed that DIs and non-DIs have similar WM capacities. Study 2 embedded depressive information into a WM task. Compared to non-DIs, DIs showed significantly reduced WM capacity for goal-relevant information in this task. Study 3 replicated results from Studies 1 and 2, and further showed that DIs had a significantly greater association between processing speed and recall on the depressively modified WM task compared to non-DIs. The presence of inter-task depressive information leads to DI-related decreased WM capacity. Results suggest dysphoria-related WM capacity deficits when depressive thoughts are present. WM capacity deficits in the presence of depressive thoughts are a plausible mechanism to explain day-to-day memory and concentration difficulties associated with depressed mood.     

A sub-process view of working memory capacity: Evidence from effects of speech on prose memory

In this article we outline a “sub-process view” of working memory capacity (WMC). This view suggests that any relationship between WMC and another construct (e.g., reading comprehension) is actually a relationship with a specific part of the WMC construct. The parts, called sub-processes, are functionally distinct and can be measured by intrusion errors in WMC tasks. Since the sub-processes are functionally distinct, some sub-process may be related to a certain phenomenon, whereas another sub-process is related to other phenomena. In two experiments we show that a sub-process (measured by immediate/current-list intrusions) is related to the effects of speech on prose memory (semantic auditory distraction), whereas another sub-process (measured by delayed/prior-list intrusions), known for its contribution to reading comprehension, is not. In Experiment 2 we developed a new WMC task called “size-comparison span” and found that the relationship between WMC and semantic auditory distraction is actually a relationship with a sub-process measured by current-list intrusions in our new task.     

The role of working memory capacity in multiple-cue probability learning

Multiple-cue probability learning (MCPL) involves learning to predict a criterion when outcome feedback is provided for multiple cues. A great deal of research suggests that working memory capacity (WMC) is involved in a wide range of tasks that draw on higher level cognitive processes. In three experiments, we examined the role of WMC in MCPL by introducing measures of working memory capacity, as well as other task manipulations. While individual differences in WMC positively predicted performance in some kinds of multiple-cue tasks, performance on other tasks was entirely unrelated to these differences. Performance on tasks that contained negative cues was correlated with working memory capacity, as well as measures of explicit knowledge obtained in the learning process. When the relevant cues predicted positively, however, WMC became irrelevant. The results are discussed in terms of controlled and automatic processes in learning and judgement.     

The structure of working memory and how it relates to intelligence in children

This study explored the structure of working memory, and its relationship with intelligence in 176 typically-developing children in the 4th and 5th grades at school. Different measures of working memory (WM), and intelligence (g) were administered. Confirmatory factor analyses showed that WM involves an attentional control system and storage aspects that rely on domain-specific verbal (STM-V) and visuospatial (STM-VS) resources. The structural equation models showed that WM predicts a large portion (66%) of the variance in g, confirming that the two constructs are separable but closely related in young children. Findings also showed that only WM and STM-VS are significantly related to g, while the contribution of STM-V is moderate. Theoretical implications for the relationship between WM and g are discussed.     

Category-based grouping in working memory and multiple object tracking

Two prominent cognitive capacity limitations are the maximal number of objects we can place in working memory (WM) and the maximal number of objects we can track in a display. Both are believed to have a numeric value of 3 or 4, which has led to the proposal that we have a general cognitive capacity, and that this capacity is most likely linked to limitations of how many objects we can attend simultaneously. Based on previous results showing that we can memorize more objects if they come from different categories than if they come from the same category (e.g., Feigenson & Halberda, 2008; Wong, Peterson, & Thompson, 2008; Wood, 2008), we compare how category-based grouping affects performance for WM and multiple object tracking (MOT). We present participants with either “pure” displays of either cars or faces, or with “mixed” displays of cars and faces. Overall, the effects of category are weak. In some analyses but not others, we replicate the mixed advantage for WM, albeit with a small effect size. In contrast, we observe a weak pure advantage for MOT tasks, at least in a meta-analysis of five experiments, but not in all experiments. Accordingly, WM and MOT tasks differed significantly in their sensitivity to category membership. We also find that WM is slightly better for faces than for cars, but that no such difference exists for MOT. We tentatively suggest that cognitive capacity limitations in different domains are at least partially due to the limitations of distinct mechanisms.     

The personalisation method applied to a working memory task: Evidence of long-term working memory effects

Ericsson and Kintsch (1995) proposed that, in situations of expertise, individuals can overcome working memory limitations by using long-term working memory. It allows a greater capacity than working memory thanks to long-term memory encoding and retrieving. To test this characteristic, an adaptation of Daneman and Carpenter's (1980) reading span was used. To operationalise expertise, the personalisation method (Guida & Tardieu, 2005) was employed. In Experiment 1, a personalised group, which read reading span sentences that mentioned familiar locations, was compared to a nonpersonalised group, which read sentences with unfamiliar locations. In Experiment 2, a personalised group, which read reading span sentences with neutral locations, was encouraged to mentally personalise these locations by thinking about known locations. This group was compared to a nonpersonalised group, which was encouraged to think about unknown locations. The personalised groups were expected to store and retrieve information in long-term memory via long-term working memory more easily than the nonpersonalised groups, which had to count massively on working memory. The results showed that personalisation enhanced reading span and confirmed one implication of the long-term working memory theory: high- and low-reading-span differences could also be due to long-term memory retrieval. Finally, these results are interpreted in terms of interaction between working memory size and long-term memory knowledge, showing that participants with a lower reading span benefited more from high domain knowledge than participants with a higher reading span.     

Children's use of semantic organizational strategies is mediated by working memory capacity

In adults, the ability to apply semantic grouping strategies has been found to depend on working memory. To investigate this relation in children, two sort-recall tasks (one without and one with a grouping instruction) were administered to 6–12-year-olds. The role of working memory was examined by means of mediation analyses and by assessing whether children who successfully used the semantic grouping strategy had higher working memory capacity than did children who did not show such strategy use. Only children aged 8–12 were able to successfully use semantic grouping strategies (and 8–9-year-olds only after instruction), while strategy use was absent in 6–7-year-olds. Both types of analysis involving working memory suggested that, also in children, working memory (and not short-term memory) mediates the development of successful use of the semantic grouping strategy during both encoding and retrieval.     

Working memory and fluid intelligence in young children

The present study investigates how working memory and fluid intelligence are related in young children and how these links develop over time. The major aim is to determine which aspect of the working memory system—short-term storage or cognitive control—drives the relationship with fluid intelligence. A sample of 119 children was followed from kindergarten to second grade and completed multiple assessments of working memory, short-term memory, and fluid intelligence. The data showed that working memory, short-term memory, and fluid intelligence were highly related but separate constructs in young children. The results further showed that when the common variance between working memory and short-term memory was controlled, the residual working memory factor manifested significant links with fluid intelligence whereas the residual short-term memory factor did not. These findings suggest that in young children cognitive control mechanisms rather than the storage component of working memory span tasks are the source of their link with fluid intelligence.     

Latent profile analysis of working memory capacity and thinking styles in adults and adolescents

This study of adults (n = 269) and adolescents (n = 308) applied latent profile analysis to preference for rational and/or experiential cognition, coupled with working memory capacity (WMC). A 4-profile solution comprising rationally dominant, experientially dominant, dual preference, and disengaged groups was retained for both adult and adolescent samples. Our solution indicated that high WMC was associated with both preference and ability to engage in rational processing. Profile membership significantly discriminated both adults and adolescents on several reasoning tasks and measures of cognitive biases. Overall our results indicate that cognitive processing styles and WMC can be combined to create a typology that distinguishes between four types of thinkers who significantly differ in their performance on reasoning tasks.