scholarly journals White matter maturation profiles through early childhood predict general cognitive ability

2014 ◽  
Vol 221 (2) ◽  
pp. 1189-1203 ◽  
Author(s):  
Sean C. L. Deoni ◽  
Jonathan O’Muircheartaigh ◽  
Jed T. Elison ◽  
Lindsay Walker ◽  
Ellen Doernberg ◽  
...  
NeuroImage ◽  
2006 ◽  
Vol 29 (2) ◽  
pp. 493-504 ◽  
Author(s):  
Laurent Hermoye ◽  
Christine Saint-Martin ◽  
Guy Cosnard ◽  
Seung-Koo Lee ◽  
Jinna Kim ◽  
...  

2021 ◽  
Author(s):  
Max Lam ◽  
Chia-Yen Chen ◽  
W. David Hill ◽  
Charley Xia ◽  
Ruoyu Tian ◽  
...  

Cognitive deficits are known to be related to most forms of psychopathology. Here, we perform local genetic correlation analysis as a means of identifying independent segments of the genome that show biologically interpretable pleiotropic associations between cognitive dimensions and psychopathology. We identified collective segments of the genome, which we call "meta-loci", that showed differential pleiotropic patterns for psychopathology relative to either General Cognitive Ability (GCA) or Non-Cognitive Skills (NCS). We observed that neurodevelopmental gene sets expressed during the prenatal-early childhood predominated in GCA-relevant meta-loci, while post-natal synaptic gene sets were more involved in NCS-relevant meta-loci. Notably, we found that GABA-ergic, cholinergic, and glutamatergic genes drove pleiotropic relationships within dissociable NCS meta-loci.


Author(s):  
Frances M. Nilsen ◽  
Jazmin D.C. Ruiz ◽  
Nicolle S. Tulve

General cognitive ability, often referred to as ‘general intelligence’, comprises a variety of correlated abilities. Childhood general cognitive ability is a well-studied area of research and can be used to predict social outcomes and perceived success. Early life stage (e.g., prenatal, postnatal, toddler) exposures to stressors (i.e., chemical and non-chemical stressors from the total (built, natural, social) environment) can impact the development of childhood cognitive ability. Building from our systematic scoping review (Ruiz et al., 2016), we conducted a meta-analysis to evaluate more than 100 stressors related to cognitive development. Our meta-analysis identified 23 stressors with a significant increase in their likelihood to influence childhood cognitive ability by 10% or more, and 80 stressors were observed to have a statistically significant effect on cognitive ability. Stressors most impactful to cognition during the prenatal period were related to maternal health and the mother’s ability to access information relevant to a healthy pregnancy (e.g., diet, lifestyle). Stressors most impactful to cognition during the early childhood period were dietary nutrients (infancy), quality of social interaction (toddler), and exposure to toxic substances (throughout early childhood). In conducting this analysis, we examined the relative impact of real-world exposures on cognitive development to attempt to understand the inter-relationships between exposures to both chemical and non-chemical stressors and early developmental life stages. Our findings suggest that the stressors observed to be the most influential to childhood cognitive ability are not permanent and can be broadly categorized as activities/behaviors which can be modified to improve childhood cognition. This meta-analysis supports the idea that there are complex relationships between a child’s total environment and early cognitive development.


2019 ◽  
Author(s):  
Dennis Dimond ◽  
Christiane S. Rohr ◽  
Robert E. Smith ◽  
Thijs Dhollander ◽  
Ivy Cho ◽  
...  

ABSTRACTEarly childhood is an important period for cognitive and brain development, though white matter changes specific to this period remain understudied. Here we utilize a novel analytic approach to quantify and track developmental changes in white matter micro- and macro-structure, calculated from individually oriented fiber-bundle populations, termed “fixels”. Fixel-based analysis and mixed-effects models were used to assess tract-wise changes in fiber density and bundle morphology in 73 girls scanned at baseline (ages 4.09-7.02, mean=5.47, SD=0.81), 6-month (N=7), and one-year follow-up (N=42). For comparison, we also assessed changes in commonly utilized diffusion tensor metrics: fractional anisotropy (FA), and mean, radial and axial diffusivity (MD, RD, AD). Maturational increases in fixel-metrics were seen in most major white matter tracts, with the most rapid increases in the corticospinal tract and slowest or non-significant increases in the genu of the corpus callosum and uncinate fasciculi. As expected, we observed developmental increases in FA and decreases in MD, RD and AD, though percentage changes were smaller relative to fixel-metrics. The majority of tracts showed more substantial morphological than microstructural changes. These findings highlight early childhood as a period of dynamic white matter maturation, characterized by large increases in macroscopic fiber bundle size, mild changes in axonal density, and parallel, albeit less substantial, changes in diffusion tensor metrics.


2019 ◽  
Vol 40 (14) ◽  
pp. 4130-4145 ◽  
Author(s):  
Xiongtao Dai ◽  
Pantelis Hadjipantelis ◽  
Jane‐Ling Wang ◽  
Sean C. L. Deoni ◽  
Hans‐Georg Müller

PLoS ONE ◽  
2012 ◽  
Vol 7 (11) ◽  
pp. e50321 ◽  
Author(s):  
Thomas S. Scerri ◽  
Fahimeh Darki ◽  
Dianne F. Newbury ◽  
Andrew J. O. Whitehouse ◽  
Myriam Peyrard-Janvid ◽  
...  

2017 ◽  
Vol 8 (1) ◽  
Author(s):  
Charlotte Grosse Wiesmann ◽  
Jan Schreiber ◽  
Tania Singer ◽  
Nikolaus Steinbeis ◽  
Angela D. Friederici

Author(s):  
Sarah E. Harris ◽  
Stuart J Ritchie ◽  
Gonçalo D S Correia ◽  
Beatriz Jiménez ◽  
Chloe Fawns-Ritchie ◽  
...  

AbstractIdentifying predictors of cognitive ability and brain structure in later life is an important step towards understanding the mechanisms leading to cognitive decline and dementia. This study used ultra-performance liquid chromatography mass spectrometry (UPLC-MS) and nuclear magnetic resonance (NMR) to measure targeted and untargeted metabolites, mainly lipids and lipoproteins, in ∼600 members of the Lothian Birth Cohort 1936 (LBC1936) at aged ∼73 years. Penalized regression models (LASSO) were then used to identify sets of metabolites that predict variation in general cognitive ability and structural brain variables. UPLC-MS-POS measured lipids, together predicted 19% of the variance in total brain volume and 17% of the variance in both grey matter and normal appearing white matter volumes. Multiple subclasses of lipids were included in the predictor, but the best performing lipid was the sphingomyelin SM(d18:2/14:0) which occurred in 100% of iterations of all three significant models. No metabolite set predicted cognitive ability, or white matter hyperintensities or connectivity. Future studies should concentrate on identifying specific lipids as potential cognitive and brain-structural biomarkers in older individuals.


Sign in / Sign up

Export Citation Format

Share Document