The reward probability index: design and validation of a scale measuring access to environmental reward

Behavioral models of depression implicate decreased response-contingent positive reinforcement (RCPR) as critical toward the development and maintenance of depression (Lewinsohn, 1974). Given the absence of a psychometrically sound self-report measure of RCPR, the Reward Probability Index (RPI) was developed to measure access to environmental reward and to approximate actual RCPR. In Study 1 (n = 269), exploratory factor analysis supported a 20-item two-factor model (Reward Probability, Environmental Suppressors) with strong internal consistency (α = .90). In Study 2 (n = 281), confirmatory factor analysis supported this two-factor structure and convergent validity was established through strong correlations between the RPI and measures of activity, avoidance, reinforcement, and depression (r = .65 to .81). Discriminant validity was supported via smaller correlations between the RPI and measures of social support and somatic anxiety (r = – .29 to – .40). Two-week test–retest reliability was strong (r = .69). In Study 3 (n = 33), controlling for depression symptoms, hierarchical regression supported the incremental validity of the RPI in predicting daily diary reports of environmental reward. The RPI represents a parsimonious, reliable, and valid measure that may facilitate understanding of the etiology of depression and its relationship to overt behaviors.     

Working memory and the attentional blink: Blink size is predicted by individual differences in operation span

The attentional blink (AB) is often attributed to resource limitations, but the nature of these resources is commonly underspecified. Recent observations rule out access to short-term memory or storage capacity as limiting factors, but operation bottlenecks are still an option. We considered the operation span of working memory (WM) as a possible factor and investigated the relationship between individual WM operation span (as measured by OSPAN), fluid intelligence (as measures by Raven’s SPM), and the size of the AB. WM operation span was negatively correlated with the AB, whereas fluid intelligence was associated with higher overall accuracy but not with AB magnitude. These results support the idea that individual processing limitations (with regard to either attentional allocation policies or the speed of global cortical integration processes) play a key role in the AB.     

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.     

Sensory Discrimination,Working Memory and Intelligence in 9‐Year‐Old and 11‐Year‐Old Children

More than a century ago, Galton and Spearman suggested that there was a functional relationship between sensory discrimination ability and intelligence. Studies have since been able to confirm a close relationship between general discrimination ability (GDA) and IQ. The aim of the present study was to assess whether this strong relationship between GDA and IQ could be due to working memory (WM) demands of GDA tasks. A sample of 140 children (seventy 9‐year‐olds and seventy 11‐year‐olds) was studied. Results showed that there was a significant overlap between WM, GDA and fluid intelligence. Furthermore, results also revealed that WM could not explain the relationship between GDA and fluid intelligence as such, but that it acted as a bottleneck of information processing, limiting the influence of GDA on the prediction of fluid intelligence. Specifically, GDA's influence on the prediction of intelligence was only visible when WM capacity was above a certain level. Copyright © 2013 John Wiley & Sons, Ltd.     

High intelligence prevents the negative impact of anxiety on working memory

Using a large sample and the confirmatory factor analysis, the study investigated the relationships between anxiety, working memory (WM) and (fluid) intelligence. The study showed that the negative impact of anxiety on WM functioning diminishes with increasing intelligence, and that anxiety can significantly affect WM only in people below average intelligence. This effect could not be fully explained by the sheer differences in WM capacity (WMC), suggesting the importance of higher-level cognition in coping with anxiety. Although intelligence moderated the impact of anxiety on WM, it was only weakly related to anxiety. In contrast to previous studies, anxiety explained the substantial amount of WMC variance (17.8%) in less intelligent participants, but none of the variance in more intelligent ones. These results can be explained in terms of either increased motivation of intelligent but anxious people to cope with a WM task, or their ability to compensate decrements in WM.     

An automated version of the operation span task

We present an easy-to-administer and automated version of a popular working memory (WM) capacity task (operation span; Ospan) that is mouse driven, scores itself, and requires little intervention on the part of the experimenter. It is shown that this version of Ospan correlates well with other measures of WM capacity and has both good internal consistency (alpha=.78) and test-retest reliability (.83). In addition, the automated version of Ospan (Aospan) was shown to load on the same factor as two other WM measures. This WM capacity factor correlated with a factor composed of fluid abilities measures. The utility of the Aospan was further demonstrated by analyzing response times (RTs) that indicated that RT measures obtained in the task accounted for additional variance in predicting fluid abilities. Our results suggest that Aospan is a reliable and valid indicator of WM capacity that can be applied to a wide array of research domains.     

A comparison of laboratory and clinical working memory tests and their prediction of fluid intelligence

The working memory (WM) construct is conceptualized similarly across domains of psychology, yet the methods used to measure WM function vary widely. The present study examined the relationship between WM measures used in the laboratory and those used in applied settings. A large sample of undergraduates completed three laboratory-based WM measures (operation span, listening span, and n-back), as well as the WM subtests from the Wechsler Adult Intelligence Scale-III and the Wechsler Memory Scale-III. Performance on all of the WM subtests of the clinical batteries shared positive correlations with the lab measures; however, the Arithmetic and Spatial Span subtests shared lower correlations than the other WM tests. Factor analyses revealed that a factor comprising scores from the three lab WM measures and the clinical subtest, Letter-Number Sequencing (LNS), provided the best measurement of WM. Additionally, a latent variable approach was taken using fluid intelligence as a criterion construct to further discriminate between the WM tests. The results revealed that the lab measures, along with the LNS task, were the best predictors of fluid abilities.     

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.     

The generality of working memory capacity: a latent-variable approach to verbal and visuospatial memory span and reasoning

A latent-variable study examined whether verbal and visuospatial working memory (WM) capacity measures reflect a primarily domain-general construct by testing 236 participants in 3 span tests each of verbal WM. visuospatial WM, verbal short-term memory (STM), and visuospatial STM. as well as in tests of verbal and spatial reasoning and general fluid intelligence (Gf). Confirmatory' factor analyses and structural equation models indicated that the WM tasks largely reflected a domain-general factor, whereas STM tasks, based on the same stimuli as the WM tasks, were much more domain specific. The WM construct was a strong predictor of Gf and a weaker predictor of domain-specific reasoning, and the reverse was true for the STM construct. The findings support a domain-general view of WM capacity, in which executive-attention processes drive the broad predictive utility of WM span measures, and domain-specific storage and rehearsal processes relate more strongly to domain-specific aspects of complex cognition.     

The Predictive Utility of a Working Memory Span Task Depends on Processing Demand and the Cognitive Task

The relationship between performance in working memory (WM) span tasks, scholastic skills and fluid intelligence was investigated to determine how WM span is related to higher order cognition. The predictive utility of two WM span tasks differing in the demand of the processing task was studied with controlled presentation times and a broad set of academic criterion tasks. Sixty‐eight adolescents (mean age 16 years) completed two WM span tasks, Raven's Progressive Matrices and several scholastic performance measures. The results showed that the more demanding WM span task predicted fluid intelligence, but did not contribute uniquely in explaining scholastic performance. In contrast, the less demanding WM task predicted scholastic performance. The results suggest that the strength of the relation between WM performance and higher order cognition varies in conjunction with both the demand of the WM span task and the type of higher order cognition measure.Copyright © 2016 John Wiley & Sons, Ltd.     

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.     

Confirmatory analysis of simultaneous,sequential, and achievement factors on the K-ABC at 11 age levels ranging from 212 to 1212 years

The K-ABC is a recently published measure of children's intelligence based on a theoretical model of information processing. Exploratory factor analyses conducted during the scale's development supported the underlying theoretical model of sequential, simultaneous, and achievement factors. Confirmatory analysis using a Jöreskog method was carried out in the present investigation and completely supported the two-factor processing model. When the achievement measures were included, the two mental processing factors again clearly emerged, along with a third factor defined by the achievement scale subtests, but they did not fit an independent three-factor model.     

Working memory and phonological processing as predictors of children’s mathematical problem solving at different ages

The study explored the contribution of working memory (WM) to mathematical problem solving in younger (8-year-old) and older (11-year-old) children. The results showed that (1) significant age-related differences in WM performance were maintained when measures of phonological processing (i.e., digit naming speed, short-term memory, phonological deletion) were partialed from the analysis; (2) WM predicted solution accuracy of word problems independently of measures of problem representation, knowledge of operations and algorithms, phonological processing, fluid intelligence, reading, and math skill; and (3) a second-order WM factor was correlated with problem solving, suggesting that a general or executive system underlies age-related performance. The results were interpreted as support for the notion that the executive system was an important predictor of age-related changes in problem solving beyond the contribution of math and reading skills, and this system operates independently of the phonological system and domain-specific knowledge in predicting solution accuracy.     

The influence of temporal resolution power and working memory capacity on psychometric intelligence

According to the temporal resolution power (TRP) hypothesis, higher TRP as reflected by better performance on psychophysical timing tasks accounts for faster speed of information processing and increased efficiency of information processing leading to better performance on tests of psychometric intelligence. An alternative explanation of individual differences in psychometric intelligence highlights individual differences in working memory (WM) capacity which has been found to be closely associated with psychometric intelligence. A latent variable approach was applied on the data of 200 participants ranging in age from 18 to 30 years and spanning a large range of levels of psychometric intelligence. Functional relationships were examined among TRP, WM capacity, as well as reasoning and speed of processing as two important aspects of psychometric intelligence. As predicted by the TRP hypothesis, the relation between TRP and psychometric intelligence was mediated by WM capacity supporting the view that higher TRP leads to better coordinated mental operations which, in turn, result in higher psychometric intelligence. The results are discussed against the background that WM capacity and psychometric reasoning are hardly dissociable from each other and that the specific factors limiting WM capacity and accounting for the mediation effect need to be identified in future research.     

Visual working memory represents a fixed number of items regardless of complexity

Does visual working memory represent a fixed number of objects, or is capacity reduced as object complexity increases? We measured accuracy in detecting changes between sample and test displays and found that capacity estimates dropped as complexity increased. However, these apparent capacity reductions were strongly correlated with increases in sample-test similarity (r= .97), raising the possibility that change detection was limited by errors in comparing the sample and test, rather than by the number of items that were maintained in working memory. Accordingly, when sample-test similarity was low, capacity estimates for even the most complex objects were equivalent to the estimate for the simplest objects (r= .88), suggesting that visual working memory represents a fixed number of items regardless of complexity. Finally, a correlational analysis suggested a two-factor model of working memory ability, in which the number and resolution of representations in working memory correspond to distinct dimensions of memory ability.     

Memory span and general intelligence: A latent-variable approach

There are several studies showing that working memory and intelligence are strongly related. However, working memory tasks require simultaneous processing and storage, so the causes of their relationship with intelligence are currently a matter of discussion. The present study examined the simultaneous relationships among short-term memory (STM), working memory (WM), and general intelligence (g). Two hundred and eight participants performed six verbal, quantitative, and spatial STM tasks, six verbal, quantitative, and spatial WM tasks, and eight tests measuring fluid, crystallized, spatial, and quantitative intelligence. Especial care is taken to avoid misrepresenting the relations among the constructs being studied because of specific task variance. Structural equation modelling (SEM) results revealed that (a) WM and g are (almost) isomorphic constructs, (b) the isomorphism vanishes when the storage component of WM is partialed out, and (c) STM and WM (with its storage component partialed out) predict g.     

Working memory training in older adults: evidence of transfer and maintenance effects

Few studies have examined working memory (WM) training-related gains and their transfer and maintenance effects in older adults. This present research investigates the efficacy of a verbal WM training program in adults aged 65-75 years, considering specific training gains on a verbal WM (criterion) task as well as transfer effects on measures of visuospatial WM, short-term memory, inhibition, processing speed, and fluid intelligence. Maintenance of training benefits was evaluated at 8-month follow-up. Trained older adults showed higher performance than did controls on the criterion task and maintained this benefit after 8 months. Substantial general transfer effects were found for the trained group, but not for the control one. Transfer maintenance gains were found at follow-up, but only for fluid intelligence and processing speed tasks. The results are discussed in terms of cognitive plasticity in older adults.     

Working Memory Capacity as Executive Attention

Performance on measures of working memory (WM) capacity predicts performance on a wide range of real-world cognitive tasks. I review the idea that WM capacity (a) is separable from short-term memory, (b) is an important component of general fluid intelligence, and (c) represents a domain-free limitation in ability to control attention. Studies show that individual differences in WM capacity are reflected in performance on antisaccade, Stroop, and dichotic-listening tasks. WM capacity, or executive attention, is most important under conditions in which interference leads to retrieval of response tendencies that conflict with the current task.     

Personality and Intelligence in Business People: A Study of Two Personality and Two Intelligence Measures

This study examined the overlap and correlations among two well-known personality measures (NEO-PI–R; Myers-Briggs Type Indicator, MBTI) and two widely used intelligence tests (the Graduate Management Assessment (GMA), Watson-Glaser Critical Thinking Appraisal (WGCTA)). The GMA measures both fluid intelligence (Gf) and crystallized intelligence (Gc), whereas WGCTA mainly assess Gc. A total of over 3,500 participants completed the four measures in a middle management assessment event. Correlational analysis showed that Extraversion on the MBTI tended to be associated with Openness and Stability on the NEO. Intuition was associated with Openness and Introversion. Feeling types tended to be both Agreeable and Neurotic while perceiving types were high on Openness but low on Agreeableness. The NEO Big Five factor of Openness was most consistently and significantly associated with both measures of intelligence (r = .09 to r =.12). Results from the MBTI showed that Intuition and Perceiving scores were positively and significantly associated with both intelligence test scores which were intercorrelated (r = .38). Regressional analysis showed that personality traits are logically and coherently related to intelligence test scores. Implications for selection and assessment are considered.     

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.