77 research outputs found

    Evolution of active and polar photospheric magnetic fields during the rise of Cycle 24 compared to previous cycles

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    The evolution of the photospheric magnetic field during the declining phase and minimum of Cycle 23 and the recent rise of Cycle 24 are compared with the behavior during previous cycles. We used longitudinal full-disk magnetograms from the NSO's three magnetographs at Kitt Peak, the Synoptic Optical Long-term Investigations of the Sun (SOLIS) Vector Spectro-Magnetograph (VSM), the Spectromagnetograph and the 512-Channel Magnetograph instruments, and longitudinal full-disk magnetograms from the Mt. Wilson 150-foot tower. We analyzed 37 years of observations from these two observatories that have been observing daily, weather permitting, since 1974, offering an opportunity to study the evolving relationship between the active region and polar fields in some detail over several solar cycles. It is found that the annual averages of a proxy for the active region poloidal magnetic field strength, the magnetic field strength of the high-latitude poleward streams, and the time derivative of the polar field strength are all well correlated in each hemisphere. These results are based on statistically significant cyclical patterns in the active region fields and are consistent with the Babcock-Leighton phenomenological model for the solar activity cycle. There was more hemispheric asymmetry in the activity level, as measured by total and maximum active region flux, during late Cycle 23 (after around 2004), when the southern hemisphere was more active, and Cycle 24 up to the present, when the northern hemisphere has been more active, than at any other time since 1974. The active region net proxy poloidal fields effectively disappeared in both hemispheres around 2004, and the polar fields did not become significantly stronger after this time. We see evidence that the process of Cycle 24 field reversal has begun at both poles.Comment: Accepted for publication in Solar Physic

    Novel genetic loci associated with hippocampal volume

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    The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg =-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness

    The genetic architecture of the human cerebral cortex

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    INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 306 nominally genome-wide significant loci (P < 5 × 10−8) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained significant after replication, with 199 loci passing multiple testing correction (P < 8.3 × 10−10; 187 influencing surface area and 12 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation (rG = −0.32, SE = 0.05, P = 6.5 × 10−12), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 10 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function

    Solar Surface Magnetism and Irradiance on Time Scales from Days to the 11-Year Cycle

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    Subcortical volumes across the lifespan: data from 18,605 healthy individuals aged 3-90 years

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    Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.Education and Child Studie

    Parenting, personality, and culture as predictors of perfectionism

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    This study examined the relationship between parenting styles, personality traits, culture, and perfectionism. Male and female undergraduate university students from the US (n = 168) and the Middle East (n = 74) completed self-report measures regarding their perceptions of how they were parented, the Big Five Personality Inventory, and two multidimensional measures of perfectionism. As predicted, authoritarian and neglectful parenting was positively correlated with maladaptive forms of perfectionism; they were also positively correlated with personal standards, but only authoritarian parenting was significantly correlated with self-oriented perfectionism. In terms of personality and perfectionism, conscientiousness was positively correlated with adaptive dimensions of perfectionism (personal standards, organization, and self-oriented perfectionism), whereas emotional stability was negatively associated with the maladaptive dimensions of perfectionism (parental criticism, doubts about abilities, concerns about mistakes, and socially prescribed perfectionism). Parenting was more predictive than personality regarding parental expectations, parental criticism, and socially prescribed perfectionism, while personality was more predictive of doubts about abilities, concern over mistakes, personal standards, organization, and self-oriented perfectionism. Middle Eastern participants scored significantly higher than US participants on parental expectations and self-oriented perfectionism. 2018 Springer Science+Business Media, LLC, part of Springer NatureScopu
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