Dynamic heterogeneities in the out-of-equilibrium dynamics of simple spherical spin models

The response of spherical two-spin interaction models, the spherical ferromagnet (s-FM) and the spherical Sherrington-Kirkpatrick (s-SK) model, is calculated for the protocol of the so-called nonresonant hole burning experiment (NHB) for temperatures below the respective critical temperatures. It is shown that it is possible to select dynamic features in the out-of-equilibrium dynamics of both models, one of the hallmarks of dynamic heterogeneities. The behavior of the s-SK model and the s-FM in three dimensions is very similar, showing dynamic heterogeneities in the long time behavior, i.e. in the aging regime. The appearence of dynamic heterogeneities in the s-SK model explicitly demonstrates that these are not necessarily related to {\it spatial} heterogeneities. For the s-FM it is shown that the nature of the dynamic heterogeneities changes as a function of dimensionality. With incresing dimension the frequency selectivity of the NHB diminishes and the dynamics in the mean-field limit of the s-FM model becomes homogeneous.Comment: 16 pages, 8 figure

Mutations in RSPH1 cause primary ciliary dyskinesia with a unique clinical and ciliary phenotype

Rationale: Primary ciliary dyskinesia (PCD) is a genetically heterogeneous recessive disorder of motile cilia, but the genetic cause is not defined for all patients with PCD. Objectives: To identify disease-causingmutations in novel genes, we performed exome sequencing, follow-up characterization, mutation scanning, and genotype-phenotype studies in patients with PCD. Methods: Whole-exome sequencing was performed using NimbleGen capture and Illumina HiSeq sequencing. Sanger-based sequencing was used for mutation scanning, validation, and segregation analysis. Measurements and Main Results: We performed exome sequencing on an affected sib-pair with normal ultrastructure in more than 85% of cilia. A homozygous splice-site mutation was detected in RSPH1 in both siblings; parents were carriers. Screening RSPH1 in 413 unrelated probands, including 325 with PCD and 88 with idiopathic bronchiectasis, revealed biallelic loss-of-function mutations in nine additional probands. Five affected siblings of probands in RSPH1 families harbored the familial mutations. The 16 individuals with RSPH1 mutations had some features of PCD; however, nasal nitric oxide levels were higher than in patients with PCD with other gene mutations (98.3 vs. 20.7 nl/min; P , 0.0003). Additionally, individuals with RSPH1 mutations had a lower prevalence (8 of 16) of neonatal respiratory distress, and later onset of daily wet cough than typical for PCD, and better lung function (FEV1), compared with 75 age- and sex-matched PCD cases (73.0 vs. 61.8, FEV1 % predicted; P = 0.043). Cilia from individuals with RSPH1 mutations had normal beat frequency (6.16Hz at 258C), but an abnormal, circular beat pattern. Conclusions: The milder clinical disease and higher nasal nitric oxide in individuals with biallelic mutations in RSPH1 provides evidence of a unique genotype-phenotype relationship in PCD, and suggests that mutations in RSPH1 may be associated with residual ciliary function

Reproducibility in the absence of selective reporting : An illustration from large-scale brain asymmetry research

Altres ajuts: Max Planck Society (Germany).The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p-hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left-right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta-analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an "ideal publishing environment," that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically-used sample sizes

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