Monday, August 15, 2022

Intelligence Correlates with the Temporal Variability of Brain Networks - ScienceDirect

 Intelligence Correlates with the Temporal Variability of Brain Networks - ScienceDirect 
https://www.sciencedirect.com/science/article/abs/pii/S0306452222004043?via%3Dihub

Abstract
Intelligence is the ability to recognize and understand objective things, and use knowledge and experience to solve problems. Highly intelligent people show the ability to switch between different thought patterns and shift their mental focus. This suggests a link between intelligence and the dynamic interaction of brain networks. Thus, we investigated the relationships between resting-state dynamic brain network remodeling (temporal variability) and scores on the Wechsler Adult Intelligent Scale using a large dataset comprising 606 individuals. We found that performance intelligence was associated with greater temporal variability in the functional connectivity patterns of the dorsal attention network. High variability in these areas indicates flexible connectivity patterns, which may contribute to cognitive processes such as attention selection. In addition, performance intelligence was related to greater temporal variability in the functional connectivity patterns of the salience network. Thus, this study revealed a close relationship between performance intelligence and high variability in brain networks involved in attentional choice, spatial orientation, and cognitive control.

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Saturday, August 06, 2022

J. Intell. | Free Full-Text | Intelligence IS Cognitive Flexibility: Why Multilevel Models of Within-Individual Processes Are Needed to Realise This

 J. Intell. | Free Full-Text | Intelligence IS Cognitive Flexibility: Why Multilevel Models of Within-Individual Processes Are Needed to Realise This 
https://www.mdpi.com/2079-3200/10/3/49

Abstract
Despite substantial evidence for the link between an individual's intelligence and successful life outcomes, questions about what defines intelligence have remained the focus of heated dispute. The most common approach to understanding intelligence has been to investigate what performance on tests of intellect is and is not associated with. This psychometric approach, based on correlations and factor analysis is deficient. In this review, we aim to substantiate why classic psychometrics which focus on between-person accounts will necessarily provide a limited account of intelligence until theoretical considerations of within-person accounts are incorporated. First, we consider the impact of entrenched psychometric presumptions that support the status quo and impede alternative views. Second, we review the importance of process-theories, which are critical for any serious attempt to build a within-person account of intelligence. Third, features of dynamic tasks are reviewed, and we outline how static tasks can be modified to target within-person processes. Finally, we explain how multilevel models are conceptually and psychometrically well-suited to building and testing within-individual notions of intelligence, which at its core, we argue is cognitive flexibility. We conclude by describing an application of these ideas in the context of microworlds as a case study. View Full-Text
Keywords: cognitive flexibilityergodic assumptionformative modelsmultilevel modelscomplex problem-solving

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Friday, August 05, 2022

Reassessment of innovative methods to determine the number of factors: A simulation-based comparison of exploratory graph analysis and next eigenvalue sufficiency test. - PsycNET

 Reassessment of innovative methods to determine the number of factors: A simulation-based comparison of exploratory graph analysis and next eigenvalue sufficiency test. - PsycNET 
https://psycnet.apa.org/doiLanding?doi=10.1037%2Fmet0000527

Brandenburg, N., & Papenberg, M. (2022). Reassessment of innovative methods to determine the number of factors: A simulation-based comparison of exploratory graph analysis and next eigenvalue sufficiency test. Psychological Methods. Advance online publication. https://doi.org/10.1037/met0000527

Next Eigenvalue Sufficiency Test (NEST; Achim, 2017) is a recently proposed method to determine the number of factors in exploratory factor analysis (EFA). NEST sequentially tests the null-hypothesis that k factors are sufficient to model correlations among observed variables. Another recent approach to detect factors is exploratory graph analysis (EGA; Golino & Epskamp, 2017), which rules the number of factors equal to the number of nonoverlapping communities in a graphical network model of observed correlations. We applied NEST and EGA to data sets under simulated factor models with known numbers of factors and scored their accuracy in retrieving this number. Specifically, we aimed to investigate the effects of cross-loadings on the performance of NEST and EGA. In the first study, we show that NEST and EGA performed less accurately in the presence of cross-loadings on two factors compared with factor models without cross-loadings: We observed that EGA was more sensitive to cross-loadings than NEST. In the second study, we compared NEST and EGA under simulated circumplex models in which variables showed cross-loadings on two factors. Study 2 magnified the differences between NEST and EGA in that NEST was generally able to detect factors in circumplex models while EGA preferred solutions that did not match the factors in circumplex models. In total, our studies indicate that the assumed correspondence between factors and nonoverlapping communities does not hold in the presence of substantial cross-loadings. We conclude that NEST is more in line with the concept of factors in factor models than EGA. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Impact Statement
Exploratory factor analysis (EFA) is a method to develop hypotheses concerning common factors governing correlations among variables. This makes EFA a valuable instrument in various fields of psychology (such as test development). A key problem in EFA is to determine the optimal number of factors that fits observed correlations and keeps resulting models parsimonious. Contemporary research on this problem does not provide consensus on the optimal solution. Next Eigenvalue Sufficiency Test (NEST; Achim, 2017) and exploratory graph analysis (EGA; Golino & Epskamp, 2017) are recently proposed methods to approach this problem. Both were shown to determine accurately the number of factors in simulated factor models in which variables indicated one factor each. In our report, we compare NEST and EGA with simulated factor models in which each variable indicated multiple factors to varying degrees. These conditions suit validation of methods to detect factors because the premise of an unknown number of factors implies that one may not assume how many factors link to individual variables. We conducted two simulation studies: In Study 1, we show that methods detect factors less accurately when variables indicated multiple factors each and highlight that EGA suffered stronger than NEST. In Study 2, we simulated circumplex models—a particular class of factor models—and show that NEST achieved high accuracy while EGA was strikingly inaccurate. We discuss reasons for the methods' performances and argue that the signal that EGA detects is incongruent on a statistical level with the understanding of factors in factor analysis. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Tuesday, August 02, 2022

Wayfinding in Children: A Descriptive Literature Review of Research Methods: The Journal of Genetic Psychology: Vol 0, No 0

 Large scale spatial navigation is part of Gv domain.

Wayfinding in Children: A Descriptive Literature Review of Research Methods: The Journal of Genetic Psychology: Vol 0, No 0 
https://www.tandfonline.com/doi/abs/10.1080/00221325.2022.2103789

Abstract
Wayfinding refers to the process of locating unseen destinations in the spatial environment and is an important spatial skill for children. Despite a growing interest in wayfinding development in children, less attention has been focused on documenting the vast methodological heterogeneity of the existing research body, which impacts the ability to synthesize results across different studies. This review aims to systematically catalog and examine the research methods of the wayfinding development literature. We identified a total of 96 studies that examined 4- to 16- year-old children's wayfinding of unfamiliar, large-scale environments and were published between 1965 and 2020. Based on the environments, we grouped these studies into virtual reality (VR) vs. real-life and indoor vs. outdoor. The review revealed a vast diversity in research methods regarding participants, environments, independent variables (IVs), environmental exposure, dependent variables (DVs), and cognitive/behavioral correlates. The field has seen growing research interests in VR environments and atypical development. The most common IVs focused on the environmental features of landmarks and turn information. Relatively less research considered how different cognitive processes such as attention, memory, and learning contribute to wayfinding. Various outcome measures have been used to investigate landmark, route, and survey knowledge regarding DVs. This review showed an imbalance of topic areas in the field, systematic differences between different types of studies, and the need for greater attention on a number of important topics. Finally, we provided targeted, detailed recommendations for future research.

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Process-oriented intelligence research: A review from the cognitive perspective - ScienceDirect

 Process-oriented intelligence research: A review from the cognitive perspective - ScienceDirect 
https://www.sciencedirect.com/science/article/pii/S0160289622000629?via%3Dihub

Abstract
Despite over a century of research on intelligence, the cognitive processes underlying intelligent behavior are still unclear. In this review, we summarize empirical results investigating the contribution of cognitive processes associated with working memory capacity, processing speed, and executive processes to intelligence differences. Specifically, we (a) evaluate how cognitive processes associated with the three different cognitive domains have been measured, and (b) how these processes are related to individual differences in intelligence. Consistently, this review illustrates that isolating single cognitive processes using average performance in cognitive tasks is hardly possible. Instead, formal models that implement theories of cognitive processes underlying performance in different cognitive tasks may provide more adequate indicators of single cognitive processes. Therefore, we outlined which models for working memory capacity, processing speed, and executive processes may provide more specific insights into cognitive processes associated with individual differences in intelligence. Finally, we discuss implications of a process-oriented intelligence research using cognitive measurement models for psychometric theories of intelligence and argue that a model-based approach might overcome validity problems of traditional intelligence theories.

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Saturday, July 02, 2022

Can a Neandertal meditate? An evolutionary view of attention as a core component of general intelligence - ScienceDirect

 Can a Neandertal meditate? An evolutionary view of attention as a core component of general intelligence - ScienceDirect 
https://www.sciencedirect.com/science/article/abs/pii/S0160289622000496

Interesting speculations, particularly (IMHO) the role of attention in intelligence, which is related to contemporary research that has suggested that attentional control (Gwm-AC) may be one of the most central causal mechanisms of intelligence.

Attention might be considered a key component of intelligence, and its cognitive and neurobiological mechanisms probably underwent profound changes in the course of human evolution. Attention can be conceived as a "limiting factor" for general intelligence (g), as the ability to maintain a selective coordination of specific cognitive processes through time regardless of conflicting stimuli. In this perspective review, we consider the paleontological and archaeological evidence that may supply information on the evolution of the attention system in the human genus. In terms of anatomy, the paleoneurological record suggests that the parietal cortex experienced a relative enlargement in Neandertals and, most prominently, in modern humans. These anatomical variations match cultural changes associated with technological and social complexity. Inferences in cognitive archaeology indicate that Homo sapiens is also specialized for working memory and visuospatial integration, when compared with extinct human taxa. These features are likely associated with changes in the attention system, and in cognitive processes dealing with meta-awareness, conscious control of mind wandering, resistance to distractors, and management of emotional clues. Although these inferences are inevitably speculative, they might stimulate a comprehensive interpretation of the technological and social behaviours associated with the evolution of the human genus, bridging together psychology and evolutionary anthropology.

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Friday, July 01, 2022

Numerosity sense correlates with fluent mathematical abilities - ScienceDirect

 Numerosity sense correlates with fluent mathematical abilities - ScienceDirect 
https://www.sciencedirect.com/science/article/pii/S0001691822001706?via%3Dihub

Abstract
Although a great deal of research has shown a relationship between numerosity sense and mathematical ability, some studies have failed to do so. The main source of this inconsistency could be the varied ways of measuring mathematical abilities. The current investigation explored several types of mathematical ability, from basic number processing and arithmetic computation to numerical reasoning and arithmetic learning. We hypothesized that the correlation between numerosity sense and mathematical ability depends on mathematical fluency. A total of 415 college students (178 males and 237 females, mean age = 20.42 years, range = 18.58–22.92 years) were recruited to complete seven mathematical tasks and two numerosity tasks, as well as other tasks that measured cognitive covariates. The results showed that after controlling for age, gender, and related general cognitive factors, numerosity sense still predicted substantial variation in parity judgment, visual digit comparison, and computation, but it did not predict variation in numerosity estimation, auditory digit comparison, number series completion, or digit associate learning. The results suggest that numerosity sense correlates with mathematical abilities that accompany fluency.

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Monday, June 27, 2022

Examination of differential effects of cognitive abilities on reading and mathematics achievement across race and ethnicity: Evidence with the WJ IV - ScienceDirect

COI…I have a financial interest in the WJ IV as one of its authors. 

Examination of differential effects of cognitive abilities on reading and mathematics achievement across race and ethnicity: Evidence with the WJ IV - ScienceDirect 
https://www.sciencedirect.com/science/article/pii/S0022440522000462

There has been little research investigating the predictive validity of modern intelligence tests for racially and ethnically diverse students. The validity of test score interpretation within educational and psychological assessment assumes that test scores predict educationally relevant phenomena equally well for individuals, regardless of group membership (American Educational Research Association et al., 2014; Messick, 1995; Warne et al., 2014). We used multiple group latent variable structural equation modeling (SEM) to investigate Cattell-Horn-Carroll general (g) and broad cognitive abilities on reading and mathematics achievement and whether these differed between racial (African American, Asian, and Caucasian) and ethnic (Hispanic, non-Hispanic) children and adolescents within the Woodcock-Johnson IV norming sample (N = 3127). After establishing construct equivalence across racial and ethnic groups, supporting the consistent calculation of composite scores regardless of group membership, we then examined the predictive validity of intelligence on achievement. After controlling for parent education, findings suggested two instances of differential predictive relations: (a) general intelligence had larger influences on basic reading skills for Caucasians when compared to Asian peers, and (b) comprehension-knowledge had larger influences on basic reading skills for Asians when compared to Caucasian peers. The overall pattern of findings suggests there is little to no predictive bias with the WJ IV. However, the findings indicate that when latent mean differences exist (after establishing strong factorial invariance), then bias will be introduced into the estimation of regression parameters used to identify differential predictive validity. Thus, even when measurement invariance is supported, differential prediction bias is inevitable when there are mean differences in the scores used as predictors. Future test bias research should consider latent ability differences and how that may impact findings of bias, and possibly, socioeconomic status-related indicators when assessing for measurement or prediction bias in intelligence and achievement tests.

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
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Tuesday, June 07, 2022

Structure of working memory in children from 3 to 8 years old. - PsycNET

 Structure of working memory in children from 3 to 8 years old. - PsycNET 
https://psycnet.apa.org/record/2022-66912-001

Abstract
Several models of working memory (WM) have been proposed in the literature. Most of the research on the architecture of WM is based on adults or older children, but less is known about younger children. In this study, we tested various models of WM on a sample of 739 Italian children, ranging in age from 3 to 8 years, primarily of European heritage and from medium to medium–high socioeconomic background. Participants were assessed with 12 WM tasks, systematically varying the modality and level of executive control required (based on the number of activities to be performed at once: retention alone, ignoring distractors, and dealing with dual tasks). We examined younger children (n = 501, Mage = 56.8 months, SD = 6.4, 48% boys) and older children (n = 238, Mage = 80.0 months, SD = 9.0, 58% boys) separately using multigroup confirmatory factor analyses. A Bayesian analytical approach was adopted. Our results suggested that a four-factor model distinguishing between verbal, visual, spatial–simultaneous, and spatial–sequential components of WM achieved the best fit. Overall, the WM structure was very similar in the two groups. We further explored this result with an additional model with a central executive factor loaded on high-control tasks only and found evidence for the presence of an executive control component. The contribution of this factor in terms of explained variance was only modest, however. Our findings demonstrate that it is important to distinguish between WM components in young children. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
******************************************

Friday, May 20, 2022

Intelligence and wisdom: Age-related differences and nonlinear relationships. - PsycNET

 Intelligence and wisdom: Age-related differences and nonlinear relationships. - PsycNET 
https://psycnet.apa.org/doiLanding?doi=10.1037%2Fpag0000692

Using data from two studies, we tested three predictions about the relationship between intelligence and wisdom: (a) Relationships between intelligence and wisdom are "triangular" rather than linear, that is, intelligence is a necessary but not sufficient condition for wisdom; (b) intelligence is primarily related to cognition-focused measures and performance measures of wisdom; (c) the relationship between wisdom and intelligence varies by intelligence domain and age-group. In Study 1, 318 participants from three age-groups (adolescents: 15–20 years; younger adults: 30–40 years; older adults: 60–70 years) completed measures of fluid and crystallized intelligence and the Berlin wisdom paradigm (BWP). Necessary-condition analyses showed "triangular" relationships between intelligence and wisdom. Crystallized intelligence was a necessary condition for wisdom in all age-groups; fluid intelligence was a necessary condition for wisdom in adolescents and young adults below a certain intelligence threshold. In Study 2, a life span sample of 155 participants (Age-group 1: 23–57 years, M = 45.0; Age-group 2: 58–90 years, M = 68.1) completed four measures of wisdom and measures of fluid and crystallized intelligence. Crystallized intelligence was a necessary but not sufficient condition for wisdom as measured by performance measures; fluid intelligence may also be a necessary condition for wisdom in advanced old age. Relationships with self-report measures of wisdom were zero for fluid and moderate and linear for crystallized intelligence. In other words, the role of intelligence for wisdom varies across conceptualizations of wisdom and across life phases. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
******************************************

Is Early Bilingual Experience Associated with Greater Fluid Intelligence in Adults?

Is Early Bilingual Experience Associated with Greater Fluid Intelligence in Adults? 
https://www.mdpi.com/2226-471X/7/2/100

Emerging evidence suggests that early bilingual experience constrains the development of attentional processes in infants, and that some of these early bilingual adaptations could last into adulthood. However, it is not known whether the early adaptations in the attentional domain alter more general cognitive abilities. If they do, then we would expect that bilingual adults who learned their second language early in life would score more highly across cognitive tasks than bilingual adults who learned their second language later in life. To test this hypothesis, 170 adult participants were administered a well-established (non-verbal) measure of fluid intelligence: Raven's Advanced Progressive Matrices (RAPM). Fluid intelligence (the ability to solve novel reasoning problems, independent of acquired knowledge) is highly correlated with numerous cognitive abilities across development. Performance on the RAPM was greater in bilinguals than monolinguals, and greater in 'early bilinguals' (adults who learned their second language between 0–6 years) than 'late bilinguals' (adults who learned their second language after age 6 years). The groups did not significantly differ on a proxy of socioeconomic status. These results suggest that the difference in fluid intelligence between bilinguals and monolinguals is not a consequence of bilingualism per se, but of earlyadaptive processes. However, the finding may depend on how bilingualism is operationalized, and thus needs to be replicated with a larger sample and more detailed measures. View Full-Text
Keywords: bilingual advantagebilingualismchild developmentearly bilingualfluid reasoningmultiple-demand (MD) systemRaven's Progressive Matrices

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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
******************************************

Sunday, May 15, 2022

J. Intell. | Free Full-Text | Bridging Brain and Cognition: A Multilayer Network Analysis of Brain Structural Covariance and General Intelligence in a Developmental Sample of Struggling Learners

 J. Intell. | Free Full-Text | Bridging Brain and Cognition: A Multilayer Network Analysis of Brain Structural Covariance and General Intelligence in a Developmental Sample of Struggling Learners 
https://www.mdpi.com/2079-3200/9/2/32

Abstract: Network analytic methods that are ubiquitous in other areas, such as systems neuroscience,

have recently been used to test network theories in psychology, including intelligence research.

The network or mutualism theory of intelligence proposes that the statistical associations among

cognitive abilities (e.g., specific abilities such as vocabulary or memory) stem from causal relations

among them throughout development. In this study, we used network models (specifically LASSO)

of cognitive abilities and brain structural covariance (grey and white matter) to simultaneously model

brain–behavior relationships essential for general intelligence in a large (behavioral, N = 805; cortical

volume, N = 246; fractional anisotropy, N = 165) developmental (ages 5–18) cohort of struggling

learners (CALM). We found that mostly positive, small partial correlations pervade our cognitive,

neural, and multilayer networks. Moreover, using community detection (Walktrap algorithm) and

calculating node centrality (absolute strength and bridge strength), we found convergent evidence

that subsets of both cognitive and neural nodes play an intermediary role 'between' brain and

behavior. We discuss implications and possible avenues for future studies.

Keywords: general intelligence; cortical volume; fractional anisotropy; brain structural covariance;

cognitive network neuroscience; multilayer network analysis

******************************************
Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
https://www.themindhub.com
******************************************