Exploring crystallized and fluid intelligence in down syndrome using graph theory

利用图论探索唐氏综合征患者的晶体智力和流体智力

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Abstract

This cross-sectional study examined the cognitive performance of crystallized intelligence (Gc) and fluid intelligence (Gf) in 340 individuals, comparing adults (aged 22-45) to adolescents (aged 16-21) in two groups of etiologies. Down syndrome (DS) and non-specific intellectual disability (NSID). The aim was to estimate whether their cognitive performance reflected accelerated, stable, or continuous trajectories. Participants were assessed using the Vocabulary, Similarities, Block Design, and Raven Matrix tests. ANOVA analysis indicated that adults exhibited higher scores than adolescents on three of the crystallized and fluid intelligence tests, with similar trends observed in the Raven Matrix test, thus supporting the Compensation Age Theory. Participants with NSID exhibited higher scores in Vocabulary than participants with DS. Participants with DS exhibited higher scores in Block Design and Raven than participants with NSID. There was no difference between the groups in Similarities, suggesting that the verbal ability of individuals with DS is not so impaired relative to participants with NSID. Graph analysis demonstrated divergent Gc-Gf networks between the two groups of etiologies. The DS etiology revealed more coherent connections between crystallized and fluid intelligence, especially in adulthood, compared to the diffuse and absent connections seen in adults with NSID. Thus, the relative strength in Similarities and the more coherent Gc-Gf interconnections in the DS etiology suggested a more coherent and not-so-impaired profile in a clear diagnostic etiology such as DS, especially in adulthood, compared to unclear genetic etiologies such as NSID. The findings hold educational implications for adults with ID with and without Down syndrome at least until their 40's as a time for growth and development, perhaps serving as a protective factor against possible cognitive decline in the future.

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