The genetic architecture of the human cerebral cortex

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

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

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

Music Outlier Detection Using Multiple Sequence Alignment and Independent Ensembles

The automated retrieval of related music documents, such as cover songs or folk melodies belonging to the same tune, has been an important task in the field of Music Information Retrieval (MIR). Yet outlier detection, the process of identifying those documents that deviate significantly from the norm, has remained a rather unexplored topic. Pairwise comparison of music sequences (e.g. chord transcriptions, melodies), from which outlier detection can potentially emerge, has been always in the center of MIR research but the connection has remained uninvestigated. In this paper we firstly argue that for the analysis of musical collections of sequential data, outlier detection can benefit immensely from the advantages of Multiple Sequence Alignment (MSA). We show that certain MSA-based similarity methods can better separate inliers and outliers than the typical similarity based on pairwise comparisons. Secondly, aiming towards an unsupervised outlier detection method that is data-driven and robust enough to be generalizable across different music datasets, we show that ensemble approaches using an entropy-based diversity measure can outperform supervised alternatives

Melody Retrieval and Classification Using Biologically-Inspired Techniques

Retrieval and classification are at the center of Music Information Retrieval research. Both tasks rely on a method to assess the similarity between two music documents. In the context of symbolically encoded melodies, pairwise alignment via dynamic programming has been the most widely used method. However, this approach fails to scale-up well in terms of time complexity and insufficiently models the variance between melodies of the same class. Compact representations and indexing techniques that capture the salient and robust properties of music content, are increasingly important. We adapt two existing bioinformatics tools to improve the melody retrieval and classification tasks. On two datasets of folk tunes and cover song melodies, we apply the extremely fast indexing method of the Basic Local Alignment Search Tool (BLAST) and achieve comparable classification performance to exhaustive approaches. We increase retrieval performance and efficiency by using multiple sequence alignment algorithms for locating variation patterns and profile hidden Markov models for incorporating those patterns into a similarity model

Feature analysis of repeated patterns in Dutch folk songs using Principal Component Analysis

Local structures, namely characteristic motifs, or prominent, nonliterally repeated patterns, play an important role in folk music. This paper uses Principal Component Analysis (PCA) to better understand characteristics of musical patterns and to further use this information for designing and evaluating future pattern discovery algorithms. We show what features can summarise the data variance in musical patterns and propose using feature selection and extraction methods to improve pattern discovery algorithms. Using PCA, we show the prominent features of MTC-ANN patterns. The pitch related and rhythmic features contribute together to the first PCA component; the second and third component consists mainly of pitch-related features and rhythmic features respectively. According to what PCA shows, in designing and evaluating pattern discovery algorithms, we should take metric structures into consideration as well as the repetitions and pitch related features in the patterns

Referenties en concept-maatlatten voor rivieren voor de Kaderrichtlijn Water

In december 2000 is de Europese Kaderrichtlijn Water (KRW) vastgesteld. Eén van de verplichtingen die voortvloeien uit de KRW is het beschrijven van de ecologische referentiesituatie van natuurlijke watertypen, waarvan dit rapport verslag doet voor de categorie Rivieren. Naast de referenties voor de biologische-, hydromorfologische- en algemene fysischchemische kwaliteitselementen per watertype, wordt in dit rapport een voorstel gedaan voor biologische maatlatten ten behoeve van de ecologische beoordeling van natuurlijke wateren. Daarbij is op ecologische gronden een onderscheid in klassen gemaakt, waaronder de Goede Ecologische Toestan

Referenties en concept-maatlatten voor rivieren voor de Kaderrichtlijn Water

In december 2000 is de Europese Kaderrichtlijn Water (KRW) vastgesteld. Eén van de verplichtingen die voortvloeien uit de KRW is het beschrijven van de ecologische referentiesituatie van natuurlijke watertypen, waarvan dit rapport verslag doet voor de categorie Rivieren. Naast de referenties voor de biologische-, hydromorfologische- en algemene fysischchemische kwaliteitselementen per watertype, wordt in dit rapport een voorstel gedaan voor biologische maatlatten ten behoeve van de ecologische beoordeling van natuurlijke wateren. Daarbij is op ecologische gronden een onderscheid in klassen gemaakt, waaronder de Goede Ecologische Toestan