Elucidating the Functional Relationship Between Working Memory Capacity and Psychometric Intelligence: A Fixed-Links Modeling Approach for Experimental Repeated-Measures Designs

Numerous studies reported a strong link between working memory capacity (WMC) and fluid intelligence (Gf), although views differ in respect to how close these two constructs are related to each other. In the present study, we used a WMC task with five levels of task demands to assess the relationship between WMC and Gf by means of a new methodological approach referred to as fixed-links modeling. Fixed-links models belong to the family of confirmatory factor analysis (CFA) and are of particular interest for experimental, repeated-measures designs. With this technique, processes systematically varying across task conditions can be disentangled from processes unaffected by the experimental manipulation. Proceeding from the assumption that experimental manipulation in a WMC task leads to increasing demands on WMC, the processes systematically varying across task conditions can be assumed to be WMC-specific. Processes not varying across task conditions, on the other hand, are probably independent of WMC. Fixed-links models allow for representing these two kinds of processes by two independent latent variables. In contrast to traditional CFA where a common latent variable is derived from the different task conditions, fixed-links models facilitate a more precise or purified representation of the WMC-related processes of interest. By using fixed-links modeling to analyze data of 200 participants, we identified a non-experimental latent variable, representing processes that remained constant irrespective of the WMC task conditions, and an experimental latent variable which reflected processes that varied as a function of experimental manipulation. This latter variable represents the increasing demands on WMC and, hence, was considered a purified measure of WMC controlled for the constant processes. Fixed-links modeling showed that both the purified measure of WMC (β = .48) as well as the constant processes involved in the task (β = .45) were related to Gf. Taken together, these two latent variables explained the same portion of variance of Gf as a single latent variable obtained by traditional CFA (β = .65) indicating that traditional CFA causes an overestimation of the effective relationship between WMC and Gf. Thus, fixed-links modeling provides a feasible method for a more valid investigation of the functional relationship between specific constructs.     

An account of the relationship between fluid intelligence and complex learning in considering storage capacity and executive attention

Although fluid intelligence and complex learning are conceptualized differently and assessed by apparently different measures, both theoretical accounts and empirical evidence suggest a relationship between the two constructs. In this study, major working memory aspects including the storage capacity and executive attention were proposed to account for the relationship between fluid intelligence and complex learning. A sample of 184 participants completed fluid intelligence and complex learning scales, as well as working memory measures that each included two or three treatment levels differing in the demands on capacity or executive control. The differences among the treatment levels provided a favorable precondition for employing fixed-links models to separate the core processes of storage capacity or executive attention from the auxiliary processes. Results indicated that both storage capacity and executive attention contributed significantly to fluid intelligence and complex learning. A further analysis showed that the two working memory aspects, particularly the storage capacity, accounted for most of the shared variance between fluid intelligence and complex learning.     

There’s more to the working memory capacity—fluid intelligence relationship than just secondary memory

The present study examined the claim that secondary memory processes account for the correlation between working memory capacity and fluid intelligence via a latent variable analysis. In the present study, participants performed multiple measures of secondary memory, working memory capacity, and fluid intelligence. Structural equation modeling suggested that both secondary memory and working memory capacity account for unique variance in fluid intelligence. These results are inconsistent with recent claims that working memory capacity does not account for variance in fluid intelligence over and above what is accounted for by secondary memory. Rather, the results are consistent with models of working memory capacity that suggest that both maintenance and retrieval processes are needed to account for the substantial relation between working memory capacity and fluid intelligence.     

The unique contributions of the facilitation of procedural memory and working memory to individual differences in intelligence

Individual differences in working memory account for a substantial portion of individual differences in complex cognitive processes (e.g., comprehension) and fluid intelligence. However, a large portion of the variance in fluid intelligence and comprehension is unexplained. The current investigation was conducted to evaluate whether individual differences in the facilitation of procedural memory accounts for unique variance in intelligence not accounted for by working memory. To measure variability in the facilitation of procedural memory, we used a task that required participants to first classify exemplars of two categories; facilitation was then operationalized by subsequent improvements in the speed of classifying new exemplars from those categories (i.e., an operation-specific memory procedure). Three measures of each focal construct (facilitation in procedural memory, working memory, comprehension and fluid intelligence) were administered to 256 participants. We used structural equation modeling to examine the relationships among these latent variables. Working memory did account for variance in fluid intelligence and comprehension, but most important, individual differences in facilitation of procedural memory accounted for unique variance in fluid intelligence and comprehension.     

预设路径模型及其在认知心理学研究中的应用

预设路径模型(Fixed-links modeling)是在结构方程模型框架下发展出的用于分析心理学实验数据的统计模型。该类模型的主要特征是根据前期理论基础和实验设计,通过预先设定模型中显变量与潜变量之间的因素载荷矩阵实现对显变量方差的拆分。因素载荷矩阵的设定主要基于实验水平与所表征的心理过程之间的关系,选取相应函数来表征不同实验水平之间的变化趋势。该模型在表征工作记忆、注意和学习的内部加工过程及揭示不同认知过程的具体联系中发挥了重要作用。     

Similarities and differences between mind-wandering and external distraction: A latent variable analysis of lapses of attention and their relation to cognitive abilities

The current study examined the extent to which task-unrelated thoughts represent both vulnerability to mind-wandering and susceptibility to external distraction from an individual difference perspective. Participants performed multiple measures of attention control, working memory capacity, and fluid intelligence. Task-unrelated thoughts were assessed using thought probes during the attention control tasks. Using latent variable techniques, the results suggested that mind-wandering and external distraction reflect distinct, yet correlated constructs, both of which are related to working memory capacity and fluid intelligence. Furthermore, the results suggest that the common variance shared by mind-wandering, external distraction, and attention control is what primarily accounts for their relation with working memory capacity and fluid intelligence. These results support the notion that lapses of attention are strongly related to cognitive abilities.     

Fluid intelligence, memory span, and temperament difficulties predict academic performance of young adolescents

There are several candidate measures when asking which psychological construct significantly predicts academic performance. Hundreds of studies have addressed this issue by measuring intelligence, basic cognitive processes, or personality. However, the simultaneous consideration of a broad and varied array of measures is much less common. Here we consider several cognitive and personality measures concurrently to define latent factors representing six constructs of presumed interest: fluid intelligence, short-term memory, working memory, processing speed, controlled attention, and temperament difficulties. One hundred and thirty-five secondary school students were tested. Their academic performance was measured by average grades in the nine scholastic areas of their curriculum. The main finding shows that a latent factor defined by fluid intelligence and memory span along with a latent factor defined by impulsiveness, sensation seeking, and lack of fear account for an impressive figure of 60% of the variance in academic performance.     

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.     

A dissociation between the sense of familiarity and access to semantic information concerning familiar people

In the current study we examined the relationship between working memory capacity, inhibition/susceptibility to interference and fluid intelligence, measured by the Raven's Progressive Matrices (PM38), comparing groups of young (aged 18–35), young-old (aged 65–74), and old-old (aged 75–86) participants. Groups were administered two working memory tasks tapping into different mechanisms involved in working memory. The ability to control for irrelevant information was measured both considering memory errors (intrusion errors) in a working memory task and an index of susceptibility to interference obtained with a variant of the Brown-Peterson task. Regression analyses showed that the classical working memory measure was the most potent predictors of the Raven's score. Susceptibility to interference and intrusions errors contributed, but to a lower extent, to the Raven explained variance. These results confirm that working memory shares cognitive aspects with the fluid intelligence measure considered, whereas the role of inhibition to Raven scores is still in need of better evidence.     

Working memory, inhibition, and fluid intelligence as predictors of performance on Tower of Hanoi and London tasks

The contributions of working memory, inhibition, and fluid intelligence to performance on the Tower of Hanoi (TOH) and Tower of London (TOL) were examined in 85 undergraduate participants. All three factors accounted for significant variance on the TOH, but only fluid intelligence accounted for significant variance on the TOL. When the contribution of fluid intelligence was accounted for, working memory and inhibition continued to account for significant variance on the TOH. These findings support argument that fluid intelligence contributes to executive functioning, but also show that the executive processes elicited by tasks vary according to task structure.     

Item-Position Effect in Raven’s Matrices: A Developmental Perspective

ABSTRACT

This study examined whether there is a developmental difference in the emergence of an item-position effect in intelligence testing. The item-position effect describes the dependency of the item’s characteristics on the positions of the items and is explained by learning. Data on fluid intelligence measured by Raven’s Standard Progressive Matrices (SPM) and data on working memory tasks were collected from both primary school age children (7–8 years old) and secondary school age adolescents (12–13 years old). The item-position effect of SPM was represented and separated from the ability component by the fixed-links model. The results indicated a clear age difference: whereas the item-position effect was observed in the adolescents, it was not found in the primary school children. In addition, separating the item-position effect detected in the adolescents from the ability component led to a larger correlation with working memory than otherwise. These results suggest that age differences in intelligence test performance may not only reflect differences in the general ability but also in the sources of the item-position effect.     

Using the process dissociation procedure to estimate recollection and familiarity in working memory: An experimental and individual differences investigation

Numerous studies have found that working memory capacity and perceptual speed predict variation in fluid intelligence. Within the cognitive ageing literature, perceptual speed accounts for substantial ageing variance in working memory capacity and fluid intelligence. However, within young adults, the interrelationships among these three abilities are less clear. The current work investigated these relationships via confirmatory factor analyses and structural equation modelling using tasks with verbal, spatial, and numerical content. The results indicate that working memory capacity and perceptual speed were not related in a large, cognitively diverse sample of young adults. However, both working memory capacity and perceptual speed accounted for unique variance in fluid intelligence. The results are discussed in relation to previous research with young and older adults.     

Intellectual growth in children as a function of domain specific and domain general working memory subgroups

This study examined whether children's growth on measures of fluid (Raven Colored Progressive Matrices) and crystallized (reading and math achievement) intelligence was attributable to domain-specific or domain-general functions of working memory (WM). A sample of 290 elementary school children was tested on measures of intelligence across three testing waves. Two methods, a hierarchical factor model predicting latent growth and a double dissociation design comparing children divided into high and low performers, tested whether general and/or specific components accounted for performance on intelligence measures. A general domain model for the total sample provided the best fit for latent growth on all measures. Further, the lack of a significant WM subgroup × domain interaction suggested that a general WM system underlies the individual differences on measures of fluid and crystallized intelligence. Overall, the findings support a domain-general view of WM capacity on intelligence measures in children, but also suggest that domain specific storage systems may come into play on isolated measures.     

一般流体智力的结构与老化机制--结构方程模型的比较

近年来一般流体智力的认知结构与老化机制已成为认知研究中的一个热点。本研究通过结构方程模型探讨了认知加工速度、工作记忆、注意能力与一般流体智力的联系,结果表明：加工速度、控制性注意是一般流体智力的主要认知成分,工作记忆并非一般流体智力的认知成分,两者之间足共变关系。加入年龄因子的结构方程模型也证实了加工速度和控制性注意是一般流体智力老化的重要中介因子。     

On the division of working memory and long-term memory and their relation to intelligence: A latent variable approach

The present study examined the extent to which working (WM) and long-term memory (LTM) reflect the same, related, or completely different constructs and how they relate to other cognitive ability constructs. Participants performed various WM, recall, recognition, general fluid (gF) and general crystallized intelligence (gC) measures. Confirmatory factor analyses suggested that the memory measures could be grouped into three separate yet correlated factors (WM, recall, and recognition) and that these factors were strongly related to gF, but were related less so with gC. Furthermore, it was found that the common variance from the three memory factors could be accounted for by a higher-order memory factor which was strongly related to gF, but less so with gC. Finally, structural equation modeling suggested that both the variance common to the WM tasks and the variance common to all the memory tasks accounted for a unique variance in gF. These results are interpreted within an embedded process model of memory and suggest that WM and LTM tasks measure both shared and unique processes, which are important for intelligence.     

个体差异对工作记忆训练迁移效果的调节

本研究考察了流体智力基线水平对工作记忆训练迁移效果的影响。采用前后测设计,以视觉和听觉双任务n-back作为工作记忆训练任务,对训练组进行为期一个月的训练;积极对照组采用阅读任务进行训练。结果发现积极控制组的流体智力水平在基线与后测之间无显著变化;而训练组流体智力水平在后测时与基线相比有显著提高,且工作记忆训练提升量越大的个体其流体智力改善越大。说明认知训练有效迁移到了流体智力水平的改善上。我们还发现流体智力基线水平调节了工作记忆训练对流体智力水平的迁移,即工作记忆训练提升量越大,流体智力改善值越大,对于那些流体智力基线水平较高的人来说,工作记忆训练对流体智力改善的效果更大。流体智力基线水平、工作记忆训练提升量及两者的乘积共同影响了流体智力改善值。这一结果表明个体差异如流体智力基线水平可以调节工作记忆训练对流体智力水平的迁移。     

The influence of complex working memory span task administration methods on prediction of higher level cognition and metacognitive control of response times

Participants between the ages of 18 and 80 were tested on a complex working memory span task that was administered either using a typical experimenter-paced method or using a method in which the processing component was presented at a fixed, limited-pace presentation rate. Path analyses revealed that even after controlling for individual differences in general processing speed, the limited-pace task predicted unique variance in episodic memory, executive functioning, and fluid intelligence, whereas the experimenter-paced task did not. For the experimenter-paced task, slower responses on the processing component of the task were associated with better recall, but only when individual differences in processing speed were controlled. These findings suggest that metacognitive control of response times affects recall from working memory span tasks, as well as the relationship between span task recall and high-level cognition. These results support resource-sharing explanations of working memory and suggest that limiting processing times using computer pacing of complex span tasks can be an effective way to efficiently measure working memory capacity.     

Higher Order Factor Structure of the WISC-IV in a Clinical Neuropsychological Sample

A confirmatory factor analysis was conducted examining the higher order factor structure of the WISC-IV scores for 344 children who participated in neuropsychological evaluations at a large children's hospital. The WISC-IV factor structure mirrored that of the standardization sample. The second order general intelligence factor (g) accounted for the largest proportion of variance in the first-order latent factors and in the individual subtests, especially for the working memory index. The first-order processing speed factor exhibited the most unique variance beyond the influence of g. The results suggest that clinicians should not ignore the contribution of g when interpreting the first-order factors.     

Complex working memory span tasks and higher-order cognition: A latent-variable analysis of the relationship between processing and storage

Complex span tasks, assumed by many to measure an individual's working memory capacity, are predictive of several aspects of higher-order cognition. However, the underlying cause of the relationships between “processing-and-storage” tasks and cognitive abilities is still hotly debated nearly 30 years after the tasks were first introduced. The current study utilised latent constructs across verbal, numerical, and spatial content domains to examine a number of questions regarding the predictive power of complex span tasks. In particular, the relations among processing time, processing accuracy, and storage accuracy from the complex span tasks were examined, in combination with their respective relationships with fluid intelligence. The results point to a complicated pattern of unique and shared variance among the constructs. Implications for various theories of working memory are discussed.