On the heritability of inspection time and its covariance with IQ: a twin study

Using the classical twin design, this study investigates the influence of genetic factors on the large phenotypic variance in inspection time (IT), and whether the well established IT–IQ association can be explained by a common genetic factor. Three hundred ninety pairs of twins (184 monozygotic, MZ; 206 dizygotic, DZ) with a mean age of 16 years participated, and 49 pairs returned approximately 3 months later for retesting. As in many IT studies, the pi figure stimulus was used and IT was estimated from the cumulative normal ogive. IT ranged from 39.4 to 774.1 ms (159±110.1 ms) with faster ITs (by an average of 26.9 ms) found in the retest session from which a reliability of .69 was estimated. Full-scale IQ (FIQ) was assessed by the Multidimensional Aptitude Battery (MAB) and ranged from 79 to 145 (111±13). The phenotypic association between IT and FIQ was confirmed (−.35) and bivariate results showed that a common genetic factor accounted for 36% of the variance in IT and 32% of the variance in FIQ. The maximum likelihood estimate of the genetic correlation was −.63. When performance and verbal IQ (PIQ & VIQ) were analysed with IT, a stronger phenotypic and genetic relationship was found between PIQ and IT than with VIQ. A large part of the IT variance (64%) was accounted for by a unique environmental factor. Further genetic factors were needed to explain the remaining variance in IQ with a small component of unique environmental variance present. The separability of a shared genetic factor influencing IT and IQ from the total genetic variance in IQ suggests that IT affects a specific subcomponent of intelligence rather than a generalised efficiency.     

Genetic and environmental influences on executive functions and intelligence in middle childhood

Executive functions (EFs) and intelligence (IQ) are phenotypically correlated. In twin studies, latent variables for EFs and IQ display moderate to high heritability estimates; however, they show variable genetic correlations in twin studies spanning childhood to middle age. We analyzed data from over 11,000 children (9- to 10-year-olds, including 749 twin pairs) in the Adolescent Brain Cognitive Development (ABCD) Study to examine the phenotypic and genetic relations between EFs and IQ in childhood. We identified two EF factors—Common EF and Updating-Specific—which were both related to IQ (rs = 0.64–0.81). Common EF and IQ were heritable (53%–67%), and their genetic correlation (rG = 0.86) was not significantly different than 1. These results suggest that EFs and IQ are phenotypically but not genetically separable in middle childhood, meaning that this phenotypic separability may be influenced by environmental factors.     

Eliminating the IQ-RT correlation by eliminating an experimental confound

Three experiments investigated the relation between visual scanning demands, reaction time (RT), and psychometrically defined intelligence (IQ). Prior studies have shown reliable correlations between RT and IQ in the range of −.20 to −.80. However, these studies have confounded the number of possible stimuli (stimulus uncertainty) with the size of the area in which the stimuli may appear (visual angle). Experiment 1 replicated these studies retaining this confound. As the number of stimuli increased from one to eight, the visual angle was permitted to increase as well (from 0° to 30°). The results showed that RT varied in accord with Hick's (1952) law, and a median correlation between IQ and six RT parameters (subjects' mean RTs and standard deviations at three levels of stimulus uncertainty) of −.47 was observed. Experiment 2 removed the confound, varying only stimulus uncertainty, and the median IQ-RT correlation declined to −.02. Experiment 3 held stimulus uncertainty constant at 1 bit (two stimuli) and varied visual angle; a median correlation of −.19 was observed. It was concluded that many of the previously reported correlations may not have hinged on speed of information processing alone, but at least in part on subjects' abilities to scan the display across which the stimuli appeared.     

Skull size and intelligence, and King Robert Bruce's IQ

An estimate of someone's IQ is a potentially informative personal datum. This study examines the association between external skull measurements and IQ scores, and uses the resulting regression equation to provide an estimate of the IQ of King Robert I of Scotland (Robert Bruce, 1274–1329). Participants were 48 relatively healthy Caucasian men (age 71–76 years) resident in Scotland. Using magnetic resonance imaging data, intracranial volume estimated from external skull length and width correlated greater than .5 (p < .001) with measured intracranial area, which correlates very highly with brain volume. IQ scores estimated from the National Adult Reading Test (NART) correlated .56 (p < .001) with measured intracranial area, and .49 (p < .01) with estimated intracranial volume based on external skull width and length. The partial correlation coefficient of this latter association was .25 (p = .09) after adjustment for measured intracranial area. Thus, actual intracranial area accounts for about 74% of the variance shared by NART and estimated intracranial volume. A cast of the skull of Robert Bruce was measured and its intracranial volume estimated. A regression equation between IQ and estimated intracranial volume, based on data from the 48 subjects, estimated the IQ of Robert Bruce at about 128 (95% confidence interval 106 to  130), i.e. almost two standard deviations above the mean. NART scores show a ceiling effect, so this estimated IQ might be an underestimate. Robert Bruce's estimated high IQ is congruent with his military, political and other intellectual achievements.     

Individual differences in working memory capacity and divided attention in dichotic listening

The controlled attention theory of working memory suggests that individuals with greater working memory capacity (WMC) are better able to control or focus their attention than individuals with lesser WMC. This relationship has been observed in a number of selective attention paradigms including a dichotic listening task (Conway, Cowan, & Bunting, 2001) in which participants were required to shadow words presented to one ear and ignore words presented to the other ear. Conway et al. found that when the participant’s name was presented to the ignored ear, 65% of participants with low WMC reported hearing their name, compared to only 20% of participants with high WMC, suggesting greater selective attention on the part of high WMC participants. In the present study, individual differences in divided attention were examined in a dichotic listening task, in which participants shadowed one message and listened for their own name in the other message. Here we find that 66.7% of high WMC and 34.5% of low WMC participants detected their name. These results suggest that as WMC capacity increases, so does the ability to control the focus of attention, with high WMC participants being able to flexibly “zoom in” or “zoom out” depending on task demands.     

Whichever way you choose to categorize,working memory helps you learn

There has been growing interest in the relationship between the capacity of a person's working memory and their ability to learn to categorize stimuli. While there is evidence that working memory capacity (WMC) is related to the speed of category learning, it is unknown whether WMC predicts which strategies people use when there are multiple possible solutions to a categorization problem. To explore the relationship between WMC, category learning, and categorization strategy use, 173 participants completed two categorization tasks and a battery of WMC tasks. WMC predicted the speed of category learning, but it did not predict which strategies participants chose to perform categorization. Thus, WMC does not predict which categorization strategies people use but it predicts how well they will use the strategy they select.     

Working memory capacity and fluid intelligence are strongly related constructs: comment on Ackerman, Beier, and Boyle (2005)

The authors agree with P. L. Ackerman, M. E. Beier, and M. O. Boyle (2005; see record 2004-22408-002) that working memory capacity (WMC) is not isomorphic with general fluid intelligence (Gf) or reasoning ability. However, the WMC and Gf/reasoning constructs are more strongly associated than Ackerman et al. (2005) indicate, particularly when considering the outcomes of latent-variable studies. The authors' reanalysis of 14 such data sets from 10 published studies, representing more than 3,100 young-adult subjects, suggests a strong correlation between WMC and Gf/reasoning factors (median r=.72), indicating that the WMC and Gf constructs share approximately 50% of their variance. This comment also clarifies the authors' "executive attention" view of WMC, it demonstrates that WMC has greater discriminant validity than Ackerman et al. (2005) implied, and it suggests some future directions and challenges for the scientific study of the convergence of WMC, attention control, and intelligence.     

The Genetic Association Between ADHD Symptoms and Reading Difficulties: The Role of Inattentiveness and IQ

Previous studies have documented the primarily genetic aetiology for the stronger phenotypic covariance between reading disability and ADHD inattention symptoms, compared to hyperactivity-impulsivity symptoms. In this study, we examined to what extent this covariation could be attributed to “generalist genes” shared with general cognitive ability or to “specialist” genes which may specifically underlie processes linking inattention symptoms and reading difficulties. We used multivariate structural equation modeling on IQ, parent and teacher ADHD ratings and parent ratings on reading difficulties from a general population sample of 1312 twins aged 7.9–10.9 years. The covariance between reading difficulties and ADHD inattention symptoms was largely driven by genetic (45%) and child-specific environment (21%) factors not shared with IQ and hyperactivity-impulsivity; only 11% of the covariance was due to genetic effects common with IQ. Aetiological influences shared among all phenotypes explained 47% of the variance in reading difficulties. The current study, using a general population sample, extends previous findings by showing, first, that the shared genetic variability between reading difficulties and ADHD inattention symptoms is largely independent from genes contributing to general cognitive ability and, second, that child-specific environment factors, independent from IQ, also contribute to the covariation between reading difficulties and inattention symptoms.     

Whichever way you choose to categorize, working memory helps you learn

There has been growing interest in the relationship between the capacity of a person's working memory and their ability to learn to categorize stimuli. While there is evidence that working memory capacity (WMC) is related to the speed of category learning, it is unknown whether WMC predicts which strategies people use when there are multiple possible solutions to a categorization problem. To explore the relationship between WMC, category learning, and categorization strategy use, 173 participants completed two categorization tasks and a battery of WMC tasks. WMC predicted the speed of category learning, but it did not predict which strategies participants chose to perform categorization. Thus, WMC does not predict which categorization strategies people use but it predicts how well they will use the strategy they select.     

Working memory capacity and retrieval from long-term memory: the role of controlled search

In two experiments, the role of working memory capacity (WMC) in the controlled search of long-term memory was examined. Participants performed a prolonged category fluency task that required them to retrieve as many animals as possible in 5 min. The results suggested that WMC differences arose in the numbers of animals retrieved, the numbers of clusters retrieved, and the rates of the retrieval (Exp. 1). However, no differences were found in terms of how participants initiated retrieval or in the nature of the clusters generated. Furthermore, an examination of differences in retrieval strategies suggested that high-WMC individuals were more strategic than low-WMC individuals and that these differences in retrieval strategies accounted for the overall differences in the numbers of animals retrieved. Additionally, presenting participants with retrieval cues eliminated WMC differences in the numbers of animals retrieved (Exp. 2). These results suggest that low-WMC individuals are less able than high-WMC individuals to select and utilize appropriate retrieval strategies to self-generate cues to access information in long-term memory. Collectively, the results are consistent with research suggesting that WMC is important for controlled search from long-term memory.     

Individual differences in working memory capacity predict sleep-dependent memory consolidation

Decades of research have established that "online" cognitive processes, which operate during conscious encoding and retrieval of information, contribute substantially to individual differences in memory. Furthermore, it is widely accepted that "offline" processes during sleep also contribute to memory performance. However, the question of whether individual differences in these two types of processes are related to one another remains unanswered. We investigated whether working memory capacity (WMC), a factor believed to contribute substantially to individual differences in online processing, was related to sleep-dependent declarative memory consolidation. Consistent with previous studies, memory for word pairs reliably improved after a period of sleep, whereas performance did not improve after an equal interval of wakefulness. More important, there was a significant, positive correlation between WMC and increase in memory performance after sleep but not after a period of wakefulness. The correlation between WMC and performance during initial test was not significant, suggesting that the relationship is specific to change in memory due to sleep. This suggests a fundamental underlying ability that may distinguish individuals with high memory capacity.     

Working memory supports inference learning just like classification learning

Recent research has found a positive relationship between people's working memory capacity (WMC) and their speed of category learning. To date, only classification-learning tasks have been considered, in which people learn to assign category labels to objects. It is unknown whether learning to make inferences about category features might also be related to WMC. We report data from a study in which 119 participants undertook classification learning and inference learning, and completed a series of WMC tasks. Working memory capacity was positively related to people's classification and inference learning performance.     

Intelligence, reaction times, and peripheral nerve conduction velocity

Two studies (with sample sizes of 85 and 88) are reported that investigated relationships among measures of intelligence, speed of information processing, and peripheral nerve conduction velocity (NCV). In both studies, NCV was significantly correlated with IQ scores (rs = .42 and .48) and with reaction times (RTs; rs = −.28 and −.18): Thus, faster NCV was associated with higher IQ scores and faster speed of processing. In both studies, NCV and RTs contributed significantly, in combination, to the prediction of fullscale IQ (shrunken multiple Rs = .53 and .57), but the expected pattern of causal relationships between the variables was not borne out. The results are interpreted in terms of a “neural efficiency” model of intelligence, which has recieved support from other studies of physiological correlates of human intelligence.     

Working memory and intelligence--their correlation and their relation: comment on Ackerman, Beier, and Boyle (2005)

On the basis of a meta-analysis of pairwise correlations between working memory tasks and cognitive ability measures, P. L. Ackerman, M. E. Beier, and M. O. Boyle (2005; see record 2004-22408-002) claimed that working memory capacity (WMC) shares less than 25% of its variance with general intelligence (g) and with reasoning ability. In this comment, the authors argue that this is an underestimation because of several methodological shortcomings and biases. A reanalysis of the data reported in Ackerman et al. using the correct statistical procedures demonstrates that g and WMC are very highly correlated. On a conceptual level, the authors point out that WMC should be regarded as an explanatory construct for intellectual abilities. Theories of working memory do not claim that WMC is isomorphic with intelligence factors but that it is a very strong predictor of reasoning ability and also predicts general fluid intelligence and g.     

Herrnstein''s syllogism: genetic and shared environmental influences on IQ, education, and income

Genotypes may influence the phenotypic associations among IQ, education, and income. To investigate this hypothesis, we believe that the appropriate methodology requires estimation of genetic and environmental influences using data able to separate these influences. The National Longitudinal Survey of Youth (NLSY) is a nationally representative sample that contains genetically-informative full- and half-siblings (28–35 years old in 1992; Ns=1943 full-siblings, 129 half-siblings). A biometric genetic model was fit that estimated the shared environmental and genetic variance components of IQ, years of education, and hourly income. The total heritabilities were 0.64 for IQ, 0.68 for education, and 0.42 for income. Heritabilities due to a common genetic factor were 0.35 for IQ, 0.52 for education, and 0.12 for income. Environmental influences due to a common shared environmental factor were 0.23 for IQ, 0.18 for education, and 0.08 for income. The model predicted a correlation of 0.63 between IQ and education and 0.34 between IQ and income. Sixty-eight percent of the former and 59% of the latter was genetically mediated; the remainder was mediated by common shared environment. These findings suggest that social inequality in the United States has its origin in both genetically-based traits and in different environmental backgrounds.     

Intelligence: new findings and theoretical developments

We review new findings and new theoretical developments in the field of intelligence. New findings include the following: (a) Heritability of IQ varies significantly by social class. (b) Almost no genetic polymorphisms have been discovered that are consistently associated with variation in IQ in the normal range. (c) Much has been learned about the biological underpinnings of intelligence. (d) "Crystallized" and "fluid" IQ are quite different aspects of intelligence at both the behavioral and biological levels. (e) The importance of the environment for IQ is established by the 12-point to 18-point increase in IQ when children are adopted from working-class to middle-class homes. (f) Even when improvements in IQ produced by the most effective early childhood interventions fail to persist, there can be very marked effects on academic achievement and life outcomes. (g) In most developed countries studied, gains on IQ tests have continued, and they are beginning in the developing world. (h) Sex differences in aspects of intelligence are due partly to identifiable biological factors and partly to socialization factors. (i) The IQ gap between Blacks and Whites has been reduced by 0.33 SD in recent years. We report theorizing concerning (a) the relationship between working memory and intelligence, (b) the apparent contradiction between strong heritability effects on IQ and strong secular effects on IQ, (c) whether a general intelligence factor could arise from initially largely independent cognitive skills, (d) the relation between self-regulation and cognitive skills, and (e) the effects of stress on intelligence.     

Choking under pressure and working memory capacity: When performance pressure reduces fluid intelligence

Recent findings (Beilock & Carr, 2005) have demonstrated that only individuals with a high working memory capacity (WMC) “choke under pressure” on math problems with high working memory demands. This suggests that performance pressure hinders those who are the most qualified to succeed, because it consumes the WMC they usually rely on to achieve superior performance. This puts into question the use of performance in high-pressure situations as a means of distinguishing individuals with lesser or greater WMC potentials. While addressing several limitations of past research, we offer evidence that such choking (1) occurs only in individuals with high WMC, because of their anxiety-ridden perceptions of high-stakes situations, and (2) is not confined to tasks involving acquired skills and knowledge, but encompasses fluid reasoning abilities or intelligence (Gf). These findings have strong implications for assessments of people’s intellectual capacities in academic, clinical, work, and research settings.     

Split‐Attention and Coherence Principles in Multimedia Instruction Can Rescue Performance for Learners with Lower Working Memory Capacity

This study examined the relation between working memory capacity (WMC) and the principles of Split‐Attention (Experiment 1) and Coherence (Experiment 2) in multimedia learning. Split‐Attention refers to reduced comprehension when learners must divide their attention between images and text, and Coherence refers to reduced comprehension when learners must process irrelevant information. In Experiment 1, those with lower WMC performed worse compared with those with higher WMC when learning from the Split‐Attention condition (audio + on‐screen text + images), but not when learning from the Complementary condition (audio + images). In Experiment 2, those with lower WMC performed worse compared with those with higher WMC when learning from the Incongruent condition (audio + irrelevant images), but not when learning from the Congruent condition (audio + relevant images). Findings reinforce the importance of pedagogically sound instructional design, as it may especially benefit those with lower WMC and equate learning across working memory abilities. Copyright © 2016 John Wiley & Sons, Ltd.     

Working memory capacity in generalized social phobia

Research suggests that understanding complex social cues depends on the availability of cognitive resources (e.g., Phillips, Channon, Tunstall, Hedenstrom, & Lyons, 2008). In spite of evidence suggesting that executive control functioning may impact anxiety (e.g., Eysenck, Derakshan, Santos, & Calvo, 2007), relatively few studies have examined working memory in individuals with generalized social phobia. Moreover, few studies have examined the role of threat-relevant content in working memory performance in clinically anxious populations. To this end, the present study assessed working memory capacity (WMC) in individuals with generalized social phobia and nonanxious controls using an operation span task with threat-relevant and neutral stimuli. Results revealed that nonanxious individuals demonstrated better WMC than individuals with generalized social phobia for neutral words but not for social threat words. Individuals with generalized social phobia demonstrated better WMC performance for threat words relative to neutral words. These results suggest that individuals with generalized social phobia may have relatively enhanced working memory performance for salient, socially relevant information. This enhanced working memory capacity for threat-relevant information may be the result of practice with this information in generalized social phobia.     

Investigating cognitive transfer within the framework of music practice: genetic pleiotropy rather than causality

The idea of far transfer effects in the cognitive sciences has received much attention in recent years. One domain where far transfer effects have frequently been reported is music education, with the prevailing idea that music practice entails an increase in cognitive ability (IQ). While cross‐sectional studies consistently find significant associations between music practice and IQ, randomized controlled trials, however, report mixed results. An alternative to the hypothesis of cognitive transfer effects is that some underlying factors, such as shared genes, influence practice behaviour and IQ causing associations on the phenotypic level. Here we explored the hypothesis of far transfer within the framework of music practice. A co‐twin control design combined with classical twin‐modelling based on a sample of more than 10,500 twins was used to explore causal associations between music practice and IQ as well as underlying genetic and environmental influences. As expected, phenotypic associations were moderate (r = 0.11 and r = 0.10 for males and females, respectively). However, the relationship disappeared when controlling for genetic and shared environmental influences using the co‐twin control method, indicating that a highly practiced twin did not have higher IQ than the untrained co‐twin. In line with that finding, the relationship between practice and IQ was mostly due to shared genetic influences. Findings strongly suggest that associations between music practice and IQ in the general population are non‐causal in nature. The implications of the present findings for research on plasticity, modularity, and transfer are discussed.