Bridging Brain and Cognition: A Multilayer Network Analysis of Brain Structural Covariance and General Intelligence in a Developmental Sample of Struggling Learners

Simpson-Kent, Ivan L.; Fried, Eiko I.; Akarca, Danyal; Mareva, Silvana; Bullmore, Edward T.; Kievit, Rogier A.

doi:10.3390/jintelligence9020032

Cited by 14 publications

(11 citation statements)

References 90 publications

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“…Without directly studying this link, it remains speculative how the cognitive networks in our study relate to the alterations in brain connectivity in VP born children. Based on a behaviour-brain combined multilayer network, Simpson-Kent et al (2021) concluded that such relations are complex and not necessarily straightforward.…”

Section: Discussionmentioning

confidence: 99%

The interrelatedness of cognitive abilities in very preterm and full‐term born children at 5.5 years of age: a psychometric network analysis approach

Rapuc,

Pierrat,

Marchand‐Martin

et al. 2023

Child Psychology Psychiatry

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BackgroundVery preterm (VP) birth is associated with a considerable risk for cognitive impairment, putting children at a disadvantage in academic and everyday life. Despite lower cognitive ability on the group level, there are large individual differences among VP born children. Contemporary theories define intelligence as a network of reciprocally connected cognitive abilities. Therefore, intelligence was studied as a network of interrelated abilities to provide insight into interindividual differences. We described and compared the network of cognitive abilities, including strength of interrelations between and the relative importance of abilities, of VP and full‐term (FT) born children and VP children with below‐average and average‐high intelligence at 5.5 years.MethodsA total of 2,253 VP children from the EPIPAGE‐2 cohort and 578 FT controls who participated in the 5.5‐year‐follow‐up were eligible for inclusion. The WPPSI‐IV was used to measure verbal comprehension, visuospatial abilities, fluid reasoning, working memory, and processing speed. Psychometric network analysis was applied to analyse the data.ResultsCognitive abilities were densely and positively interconnected in all networks, but the strength of connections differed between networks. The cognitive network of VP children was more strongly interconnected than that of FT children. Furthermore, VP children with below average IQ had a more strongly connected network than VP children with average‐high IQ. Contrary to our expectations, working memory had the least central role in all networks.ConclusionsIn line with the ability differentiation hypothesis, children with higher levels of cognitive ability had a less interconnected and more specialised cognitive structure. Composite intelligence scores may therefore mask domain‐specific deficits, particularly in children at risk for cognitive impairments (e.g., VP born children), even when general intelligence is unimpaired. In children with strongly and densely connected networks, domain‐specific deficits may have a larger overall impact, resulting in lower intelligence levels.

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Section: Discussionmentioning

confidence: 99%

The interrelatedness of cognitive abilities in very preterm and full‐term born children at 5.5 years of age: a psychometric network analysis approach

Rapuc,

Pierrat,

Marchand‐Martin

et al. 2023

Child Psychology Psychiatry

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“…They enable the simultaneous modelling of multiple routes to a specific outcome and can incorporate multidirectional interactions across levels of description. They can therefore be used to test competing theories about how abilities are related across groups and/or time points, and to characterise how genetic, neural, and environmental factors influence these relationships (e.g., Isvoranu et al, 2020; Simpson-Kent et al, 2021). Such applications will be crucial for building an understanding of not only how abilities are related but also which mechanisms enable their wiring.…”

Section: Discussionmentioning

confidence: 99%

Cognitive and academic skills in two developmental cohorts of different ability level: A mutualistic network perspective.

Mareva¹,

Team²,

Holmes³

2022

Journal of Applied Research in Memory and Cognition

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Mutualistic theories assume that the mastering of a skill, either cognitive or academic, supports and amplifies the development of other such abilities. The current study uses network science to model cross-sectional associations between cognitive and academic performance in two age-matched developmental cohorts. One cohort was a community sample drawn from the general school population, while the other included struggling learners. The community sample outperformed the struggling learners across all measures. Network models suggested that although the tasks were similarly interrelated across cohorts, there were some notable differences in association strength: Academic skills were more closely coupled in the community sample, while maths was more strongly related to cognitive skills in the struggling learners. We demonstrate the utility of network models as an analytic framework that is consistent with contemporary theories of learning difficulties and the nature of the relationship between cognitive and learning skills more broadly.

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“…Finally, the need for more studies with multilayer networks (network of networks) is highlighted since they allow better statistical accuracy of the joint use of neurophysiological and psychological data [81,82]. This may be important in the current pandemic context, as COVID-19 can affect the central nervous system and cause neuropsychiatric disorders [83].…”

Section: The Use Of Psychological Network Models In the Context Of Ne...mentioning

confidence: 99%

Psychometric Networks and Their Implications for the Treatment and Diagnosis of Psychopathologies

Ramos-Vera¹,

Franco²,

Saldarriaga³

et al. 2023

Psychometrics - New Insights in the Diagnosis of Mental Disorders

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In this chapter, we present the main methodological principles of psychological networks as a way of conceptualizing mental disorders. In the network approach, mental disorders are conceptualized as the consequence of direct interactions between symptoms, which may involve biological, psychological, and social mechanisms. If these cause-and-effect relationships are strong enough, symptoms can generate a degree of feedback to sustain them. It is discussed how such an approach contrasts with the traditional psychometric approach, known as the Latent Variable Theory, which assumes that disorders are constructs that exist but are not directly observable. Furthermore, it is also discussed how new neuropsychological hypotheses have been derived in the network approach and how such hypotheses generate direct implications for the understanding of diagnosis and treatment of psychological disorders. Finally, the recentness of the network approach in psychology and how future studies can establish its robustness are discussed.

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Bridging Brain and Cognition: A Multilayer Network Analysis of Brain Structural Covariance and General Intelligence in a Developmental Sample of Struggling Learners

Cited by 14 publications

References 90 publications

The interrelatedness of cognitive abilities in very preterm and full‐term born children at 5.5 years of age: a psychometric network analysis approach

The interrelatedness of cognitive abilities in very preterm and full‐term born children at 5.5 years of age: a psychometric network analysis approach

Cognitive and academic skills in two developmental cohorts of different ability level: A mutualistic network perspective.

Psychometric Networks and Their Implications for the Treatment and Diagnosis of Psychopathologies

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