scholarly journals Greater male than female variability in regional brain structure across the lifespan

2020 ◽  
Author(s):  
Lara M Wierenga ◽  
Gaelle E Doucet ◽  
Danai Dima ◽  
Ingrid Agartz ◽  
Moji Aghajani ◽  
...  
Keyword(s):  
Sex Differences ◽  
Surface Area ◽  
Cortical Thickness ◽  
Brain Structure ◽  
Meta Analysis ◽  
Imaging Genetics ◽  
Environment Interaction ◽  
Cortical Surface ◽  
Subcortical Structures ◽  
Cortical Surface Area

AbstractFor many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.

scholarly journals Cognitive and brain development is independently influenced by socioeconomic status and polygenic scores for educational attainment

2020 ◽  
Vol 117 (22) ◽  
pp. 12411-12418 ◽  
Author(s):  
Nicholas Judd ◽  
Bruno Sauce ◽  
John Wiedenhoeft ◽  
Jeshua Tromp ◽  
Bader Chaarani ◽  
...  
Keyword(s):  
Socioeconomic Status ◽  
Educational Attainment ◽  
Brain Development ◽  
Surface Area ◽  
Brain Structure ◽  
Parental Education ◽  
Cortical Surface ◽  
Cortical Surface Area ◽  
Regional Association ◽  
Polygenic Scores

Genetic factors and socioeconomic status (SES) inequalities play a large role in educational attainment, and both have been associated with variations in brain structure and cognition. However, genetics and SES are correlated, and no prior study has assessed their neural associations independently. Here we used a polygenic score for educational attainment (EduYears-PGS), as well as SES, in a longitudinal study of 551 adolescents to tease apart genetic and environmental associations with brain development and cognition. Subjects received a structural MRI scan at ages 14 and 19. At both time points, they performed three working memory (WM) tasks. SES and EduYears-PGS were correlated (r= 0.27) and had both common and independent associations with brain structure and cognition. Specifically, lower SES was related to less total cortical surface area and lower WM. EduYears-PGS was also related to total cortical surface area, but in addition had a regional association with surface area in the right parietal lobe, a region related to nonverbal cognitive functions, including mathematics, spatial cognition, and WM. SES, but not EduYears-PGS, was related to a change in total cortical surface area from age 14 to 19. This study demonstrates a regional association of EduYears-PGS and the independent prediction of SES with cognitive function and brain development. It suggests that the SES inequalities, in particular parental education, are related to global aspects of cortical development, and exert a persistent influence on brain development during adolescence.

Cortical surface area and cortical thickness in the precuneus of adult humans

Neuroscience ◽  
2015 ◽  
Vol 286 ◽  
pp. 345-352 ◽  
Author(s):  
E. Bruner ◽  
F.J. Román ◽  
J.M. de la Cuétara ◽  
M. Martin-Loeches ◽  
R. Colom
Keyword(s):  
Surface Area ◽  
Cortical Thickness ◽  
Cortical Surface ◽  
Cortical Surface Area ◽  
Adult Humans

scholarly journals Cortical thickness and surface area relate to specific symptoms in early relapsing–remitting multiple sclerosis

2014 ◽  
Vol 21 (4) ◽  
pp. 402-414 ◽  
Author(s):  
Gro O Nygaard ◽  
Kristine B Walhovd ◽  
Piotr Sowa ◽  
Joy-Loi Chepkoech ◽  
Atle Bjørnerud ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Surface Area ◽  
Cortical Thickness ◽  
Clinical Symptoms ◽  
Cortical Surface ◽  
Healthy Controls ◽  
Neurological Disability ◽  
Cortical Surface Area ◽  
Relapsing Remitting ◽  
Relapsing Remitting Multiple Sclerosis

Background: Cortical atrophy is common in early relapsing–remitting multiple sclerosis (RRMS). Whether this atrophy is caused by changes in cortical thickness or cortical surface area is not known, nor is their separate contributions to clinical symptoms. Objectives: To investigate the difference in cortical surface area, thickness and volume between early RRMS patients and healthy controls; and the relationship between these measures and neurological disability, cognitive decline, fatigue and depression. Methods: RRMS patients ( n = 61) underwent magnetic resonance imaging (MRI), neurological and neuropsychological examinations. We estimated cortical surface area, thickness and volume and compared them with matched healthy controls ( n = 61). We estimated the correlations between clinical symptoms and cortical measures within the patient group. Results: We found no differences in cortical surface area, but widespread differences in cortical thickness and volume between the groups. Neurological disability was related to regionally smaller cortical thickness and volume. Better verbal memory was related to regionally larger surface area; and better visuo-spatial memory, to regionally larger cortical volume. Higher depression scores and fatigue were associated with regionally smaller cortical surface area and volume. Conclusions: We found that cortical thickness, but not cortical surface area, is affected in early RRMS. We identified specific structural correlates to the main clinical symptoms in early RRMS.

scholarly journals Brain structural differences between 73- and 92-year olds matched for childhood intelligence, social background, and intracranial volume

2017 ◽  
Author(s):  
Stuart J. Ritchie ◽  
David Alexander Dickie ◽  
Simon R. Cox ◽  
Maria del C. Valdés Hernández ◽  
Alison Pattie ◽  
...  
Keyword(s):  
White Matter ◽  
Cognitive Ability ◽  
Surface Area ◽  
Cortical Thickness ◽  
White Matter Hyperintensity ◽  
Socioeconomic Background ◽  
Intracranial Volume ◽  
Cortical Surface ◽  
Age Cohorts ◽  
Cortical Surface Area

AbstractFully characterizing age differences in the brain is a key task for combatting ageing-related cognitive decline. Using propensity score matching on two independent, narrow-age cohorts, we used data on childhood cognitive ability, socioeconomic background, and intracranial volume to match participants at mean age 92 years (n = 42) to very similar participants at mean age 73 (n = 126). Examining a variety of global and regional structural neuroimaging variables, there were large differences in grey and white matter volumes, cortical surface area, cortical thickness, and white matter hyperintensity volume and spatial extent. In a mediation analysis, the total volume of white matter hyperintensities and total cortical surface area jointly mediated 24.9% of the relation between age and general cognitive ability (tissue volumes and cortical thickness were not significant mediators in this analysis). These findings provide an unusual and valuable perspective on neurostructural ageing, in which brains from the eighth and tenth decades of life differ widely despite the same cognitive, socio-economic, and brain-volumetric starting points.

Quantification of Cortical Thickness and Cortical Surface Area Abnormalities in Patients Affected by Migraine (S16.005)

Neurology ◽  
2012 ◽  
Vol 78 (Meeting Abstracts 1) ◽  
pp. S16.005-S16.005
Author(s):  
R. Messina ◽  
M. Rocca ◽  
P. Valsasina ◽  
B. Colombo ◽  
A. Falini ◽  
...  
Keyword(s):  
Surface Area ◽  
Cortical Thickness ◽  
Cortical Surface ◽  
Cortical Surface Area

Cortical folding scales universally with surface area and thickness, not number of neurons

Science ◽  
2015 ◽  
Vol 349 (6243) ◽  
pp. 74-77 ◽  
Author(s):  
Bruno Mota ◽  
Suzana Herculano-Houzel
Keyword(s):  
Free Energy ◽  
Physical Model ◽  
Surface Area ◽  
Cortical Thickness ◽  
Cortical Surface ◽  
Square Root ◽  
Cortical Folding ◽  
Axonal Elongation ◽  
Cortical Surface Area ◽  
Simple Physical Model

Larger brains tend to have more folded cortices, but what makes the cortex fold has remained unknown. We show that the degree of cortical folding scales uniformly across lissencephalic and gyrencephalic species, across individuals, and within individual cortices as a function of the product of cortical surface area and the square root of cortical thickness. This relation is derived from the minimization of the effective free energy associated with cortical shape according to a simple physical model, based on known mechanisms of axonal elongation. This model also explains the scaling of the folding index of crumpled paper balls. We discuss the implications of this finding for the evolutionary and developmental origin of folding, including the newfound continuum between lissencephaly and gyrencephaly, and for pathologies such as human lissencephaly.

scholarly journals Variations in structural MRI quality significantly impact commonly used measures of brain anatomy

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Alysha D. Gilmore ◽  
Nicholas J. Buser ◽  
Jamie L. Hanson
Keyword(s):  
Image Quality ◽  
Surface Area ◽  
Cortical Thickness ◽  
Structural Mri ◽  
Public Access ◽  
Brain Anatomy ◽  
Cortical Surface ◽  
Cortical Surface Area ◽  
Multiple Regions ◽  
Subcortical Volumes

AbstractSubject motion can introduce noise into neuroimaging data and result in biased estimations of brain structure. In-scanner motion can compromise data quality in a number of ways and varies widely across developmental and clinical populations. However, quantification of structural image quality is often limited to proxy or indirect measures gathered from functional scans; this may be missing true differences related to these potential artifacts. In this study, we take advantage of novel informatic tools, the CAT12 toolbox, to more directly measure image quality from T1-weighted images to understand if these measures of image quality: (1) relate to rigorous quality-control checks visually completed by human raters; (2) are associated with sociodemographic variables of interest; (3) influence regional estimates of cortical surface area, cortical thickness, and subcortical volumes from the commonly used Freesurfer tool suite. We leverage public-access data that includes a community-based sample of children and adolescents, spanning a large age-range (N = 388; ages 5–21). Interestingly, even after visually inspecting our data, we find image quality significantly impacts derived cortical surface area, cortical thickness, and subcortical volumes from multiple regions across the brain (~ 23.4% of all areas investigated). We believe these results are important for research groups completing structural MRI studies using Freesurfer or other morphometric tools. As such, future studies should consider using measures of image quality to minimize the influence of this potential confound in group comparisons or studies focused on individual differences.

scholarly journals Cognitive and brain development is independently influenced by socioeconomic status and polygenic scores for educational attainment

2019 ◽  
Author(s):  
Nicholas Judd ◽  
Bruno Sauce ◽  
John Wiedenhoeft ◽  
Jeshua Tromp ◽  
Bader Chaarani ◽  
...  
Keyword(s):  
Educational Attainment ◽  
Brain Development ◽  
Surface Area ◽  
Brain Structure ◽  
Parental Education ◽  
Genetic Factors ◽  
Cortical Surface ◽  
Cortical Surface Area ◽  
Regional Association ◽  
Polygenic Scores

AbstractGenetic factors and socioeconomic (SES) inequalities play a large role in educational attainment, and both have been associated with variations in brain structure and cognition. However, genetics and SES are correlated, and no prior study has assessed their neural associations independently. Here we used polygenic score for educational attainment (EduYears-PGS) as well as SES, in a longitudinal study of 551 adolescents, to tease apart genetic and environmental associations with brain development and cognition. Subjects received a structural MRI scan at ages 14 and 19. At both time-points, they performed three working memory (WM) tasks. SES and EduYears-PGS were correlated (r = 0.27) and had both common and independent associations with brain structure and cognition. Specifically, lower SES was related to less total cortical surface area and lower WM. EduYears-PGS was also related to total cortical surface area, but in addition had a regional association with surface area in the right parietal lobe, a region related to non-verbal cognitive functions, including mathematics, spatial cognition, and WM. SES, but not EduYears-PGS, was related to a change in total cortical surface area from age 14 to 19. This is the first study demonstrating a regional association of EduYears-PGS and the independent prediction of SES on cognitive function and brain development. It suggests that the SES inequalities, in particular parental education, are related to global aspects of cortical development, and exert a persistent influence on brain development during adolescence.Significance statementThe influence of socioeconomic (SES) inequalities on brain and cognitive development is a hotly debated topic. However, previous studies have not considered that genetic factors overlap with SES. Here we showed, for the first time, that SES and EduYears-PGS (a score from thousands of genetic markers for educational attainment) have independent associations with both cognition and global cortical surface area in adolescents. EduYears-PGS also had a localized association in the brain: the intraparietal sulcus, a region related to non-verbal intelligence. In contrast, SES had global, but not regional, associations, and these persisted throughout adolescence. This suggests that the influence of SES inequalities is widespread – a result that opposes the current paradigm and can help inform policies in education.

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