Variability in neurocognitive performance: Age, gender, and school-related differences in children and from ages 6 to 12

Kochhann, Renata; Gonçalves, Hosana Alves; Pureza, Janice da Rosa; Viapiana, Vanisa Fante; Fonseca, Flavia dos Passos; Salles, Jerusa Fumagalli de; Fonseca, Róchele Paz

doi:10.1080/21622965.2017.1312403

Cited by 7 publications

(3 citation statements)

References 43 publications

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“…Cognition is a complex phenotypic construct with great heterogeneity across individuals. This phenotype variability within the population is the consequence of many factors, both genetic and environmental, that determine brain formation and neurodevelopment during the foetal stage and first decades of life (Davies et al, 2011; Gräff and Mansuy, 2008; Haworth et al, 2010; Kochhann et al, 2017). Therefore, the genetic makeup of each individual, the influence of different environmental factors and the interaction between them all contribute to the wide range of capacities observed in human cognition.…”

Section: Introductionmentioning

confidence: 99%

The effect of the AKT1 gene and cannabis use on cognitive performance in healthy subjects

et al. 2020

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Background: Evidence suggests that the AKT1 gene may modulate the degree to which cannabis use induces cognitive alterations in patients with a psychotic disorder. Aim: To examine the interplay between AKT1 and cannabis use in terms of the cognitive performance of the general population. Methods: Our sample consisted of 389 Spanish university students. Sustained attention was measured via the Continuous Performance Test–Identical Pairs, immediate and delayed verbal memory with the Logical Memory subtest of the Wechsler Memory Scale, and working memory with the Wisconsin Card Sorting Test. Lifetime cannabis use frequency was assessed and individuals were classified as cannabis users or non-users. Two single nucleotide polymorphisms of the AKT1 gene were genotyped and, according to previous studies, each subject was defined as a carrier of two, one or no copies of the haplotype (rs2494732(C)–rs1130233(A)). Multiple linear regressions were conducted to test the effect of the genetic variability and cannabis use (and their interaction) on cognitive performance. Results: An effect of the AKT1 haplotype was found on attention scores: individuals with two copies of the haplotype performed better (β=0.18, p<0.001 (adjusted for false discovery rate)), while neither cannabis nor the AKT1–cannabis interaction was associated with attention. No effect of AKT1, cannabis or the AKT1–cannabis interaction was found on verbal memory or working memory. Conclusions: Our study provides additional evidence that AKT1 modulates cognitive performance. However, in our non-clinical sample, the previously reported interaction between cannabis use and the AKT1 gene was not replicated.

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Section: Introductionmentioning

confidence: 99%

The effect of the AKT1 gene and cannabis use on cognitive performance in healthy subjects

et al. 2020

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“…En general, se propone que en las tareas de fluencia o fluidez verbal participan los procesos de memoria de trabajo, atención sostenida, monitoreo e inhibición (componente ejecutivo), memoria semántica, estrategias de búsqueda y activación de ítems léxicos (Gaillard et al, 2000;García Coni & Vivas, 2014;Marino & Alderete, 2008;Marino & Alderete, 2010;Shao, et al, 2014). Diversas investigaciones han propuesto que tanto factores biológicos como socioculturales tienen incidencia en el desempeño en dichas tareas (Jacobsen et al, 2016;Kochhann et al, 2017;Van der Elst, Hurks, Wassenberg, Meijs, & Jolles, 2011).…”

Section: Introductionunclassified

Patrones de correlación de fluencias semánticas y fonológicas en niños en edad escolar

Fumagalli

Soriano

Shalóm³

et al. 2018

CES Psico

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“…Adolescence is the developmental period during which functional brain maturation interacts with sexual divergence in social, behavior, and biological changes (Kochhann et al 2017). Particularly, sex differences are prominent in behavior and have been studying for a long time (Hardee et al 2017;Qian et al 2015a).…”

Section: Introductionmentioning

confidence: 99%

Parameter-Free Centralized Multi-Task Learning for Characterizing Developmental Sex Differences in Resting State Functional Connectivity

Zhu

Fan

2018

AAAI

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In contrast to most existing studies that typically characterize the developmental sex differences using analysis of variance or equivalently multiple linear regression, we present a parameter-free centralized multi-task learning method to identify sex specific and common resting state functional connectivity (RSFC) patterns underlying the brain development based on resting state functional MRI (rs-fMRI) data. Specifically, we design a novel multi-task learning model to characterize sex specific and common RSFC patterns in an age prediction framework by regarding the age prediction for males and females as separate tasks. Moreover, the importance of each task and the balance of these two patterns, respectively, are automatically learned in order to make the multi-task learning robust as well as free of tunable parameters, i.e., parameter-free for short. Our experimental results on synthetic datasets verified the effectiveness of our method with respect to prediction performance, and experimental results on rs-fMRI scans of 1041 subjects (651 males) of the Philadelphia Neurodevelopmental Cohort (PNC) showed that our method could improve the age prediction on average by 5.82% with statistical significance than the best alternative methods under comparison, in addition to characterizing the developmental sex differences in RSFC patterns.

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Variability in neurocognitive performance: Age, gender, and school-related differences in children and from ages 6 to 12

Cited by 7 publications

References 43 publications

The effect of the AKT1 gene and cannabis use on cognitive performance in healthy subjects

The effect of the AKT1 gene and cannabis use on cognitive performance in healthy subjects

Patrones de correlación de fluencias semánticas y fonológicas en niños en edad escolar

Parameter-Free Centralized Multi-Task Learning for Characterizing Developmental Sex Differences in Resting State Functional Connectivity

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