@article{7712, abstract = {Male pattern baldness (MPB) is a sex-limited, age-related, complex trait. We study MPB genetics in 205,327 European males from the UK Biobank. Here we show that MPB is strongly heritable and polygenic, with pedigree-heritability of 0.62 (SE = 0.03) estimated from close relatives, and SNP-heritability of 0.39 (SE = 0.01) from conventionally-unrelated males. We detect 624 near-independent genome-wide loci, contributing SNP-heritability of 0.25 (SE = 0.01), of which 26 X-chromosome loci explain 11.6%. Autosomal genetic variance is enriched for common variants and regions of lower linkage disequilibrium. We identify plausible genetic correlations between MPB and multiple sex-limited markers of earlier puberty, increased bone mineral density (rg = 0.15) and pancreatic β-cell function (rg = 0.12). Correlations with reproductive traits imply an effect on fitness, consistent with an estimated linear selection gradient of -0.018 per MPB standard deviation. Overall, we provide genetic insights into MPB: a phenotype of interest in its own right, with value as a model sex-limited, complex trait.}, author = {Yap, Chloe X. and Sidorenko, Julia and Wu, Yang and Kemper, Kathryn E. and Yang, Jian and Wray, Naomi R. and Robinson, Matthew Richard and Visscher, Peter M.}, issn = {2041-1723}, journal = {Nature Communications}, publisher = {Springer Nature}, title = {{Dissection of genetic variation and evidence for pleiotropy in male pattern baldness}}, doi = {10.1038/s41467-018-07862-y}, volume = {9}, year = {2018}, } @article{7713, abstract = {There are mean differences in complex traits among global human populations. We hypothesize that part of the phenotypic differentiation is due to natural selection. To address this hypothesis, we assess the differentiation in allele frequencies of trait-associated SNPs among African, Eastern Asian, and European populations for ten complex traits using data of large sample size (up to ~405,000). We show that SNPs associated with height (P=2.46×10−5), waist-to-hip ratio (P=2.77×10−4), and schizophrenia (P=3.96×10−5) are significantly more differentiated among populations than matched “control” SNPs, suggesting that these trait-associated SNPs have undergone natural selection. We further find that SNPs associated with height (P=2.01×10−6) and schizophrenia (P=5.16×10−18) show significantly higher variance in linkage disequilibrium (LD) scores across populations than control SNPs. Our results support the hypothesis that natural selection has shaped the genetic differentiation of complex traits, such as height and schizophrenia, among worldwide populations.}, author = {Guo, Jing and Wu, Yang and Zhu, Zhihong and Zheng, Zhili and Trzaskowski, Maciej and Zeng, Jian and Robinson, Matthew Richard and Visscher, Peter M. and Yang, Jian}, issn = {2041-1723}, journal = {Nature Communications}, publisher = {Springer Nature}, title = {{Global genetic differentiation of complex traits shaped by natural selection in humans}}, doi = {10.1038/s41467-018-04191-y}, volume = {9}, year = {2018}, } @article{7714, abstract = {Health risk factors such as body mass index (BMI) and serum cholesterol are associated with many common diseases. It often remains unclear whether the risk factors are cause or consequence of disease, or whether the associations are the result of confounding. We develop and apply a method (called GSMR) that performs a multi-SNP Mendelian randomization analysis using summary-level data from genome-wide association studies to test the causal associations of BMI, waist-to-hip ratio, serum cholesterols, blood pressures, height, and years of schooling (EduYears) with common diseases (sample sizes of up to 405,072). We identify a number of causal associations including a protective effect of LDL-cholesterol against type-2 diabetes (T2D) that might explain the side effects of statins on T2D, a protective effect of EduYears against Alzheimer’s disease, and bidirectional associations with opposite effects (e.g., higher BMI increases the risk of T2D but the effect of T2D on BMI is negative).}, author = {Zhu, Zhihong and Zheng, Zhili and Zhang, Futao and Wu, Yang and Trzaskowski, Maciej and Maier, Robert and Robinson, Matthew Richard and McGrath, John J. and Visscher, Peter M. and Wray, Naomi R. and Yang, Jian}, issn = {2041-1723}, journal = {Nature Communications}, publisher = {Springer Nature}, title = {{Causal associations between risk factors and common diseases inferred from GWAS summary data}}, doi = {10.1038/s41467-017-02317-2}, volume = {9}, year = {2018}, } @article{7715, abstract = {Preference for mates with similar phenotypes; that is, assortative mating, is widely observed in humans1,2,3,4,5 and has evolutionary consequences6,7,8. Under Fisher's classical theory6, assortative mating is predicted to induce a signature in the genome at trait-associated loci that can be detected and quantified. Here, we develop and apply a method to quantify assortative mating on a specific trait by estimating the correlation (θ) between genetic predictors of the trait from single nucleotide polymorphisms on odd- versus even-numbered chromosomes. We show by theory and simulation that the effect of assortative mating can be quantified in the presence of population stratification. We applied this approach to 32 complex traits and diseases using single nucleotide polymorphism data from ~400,000 unrelated individuals of European ancestry. We found significant evidence of assortative mating for height (θ = 3.2%) and educational attainment (θ = 2.7%), both of which were consistent with theoretical predictions. Overall, our results imply that assortative mating involves multiple traits and affects the genomic architecture of loci that are associated with these traits, and that the consequence of mate choice can be detected from a random sample of genomes.}, author = {Yengo, Loic and Robinson, Matthew Richard and Keller, Matthew C. and Kemper, Kathryn E. and Yang, Yuanhao and Trzaskowski, Maciej and Gratten, Jacob and Turley, Patrick and Cesarini, David and Benjamin, Daniel J. and Wray, Naomi R. and Goddard, Michael E. and Yang, Jian and Visscher, Peter M.}, issn = {2397-3374}, journal = {Nature Human Behaviour}, number = {12}, pages = {948--954}, publisher = {Springer Nature}, title = {{Imprint of assortative mating on the human genome}}, doi = {10.1038/s41562-018-0476-3}, volume = {2}, year = {2018}, } @article{7716, abstract = {Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7% for height to 47% for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait.}, author = {Maier, Robert M. and Zhu, Zhihong and Lee, Sang Hong and Trzaskowski, Maciej and Ruderfer, Douglas M. and Stahl, Eli A. and Ripke, Stephan and Wray, Naomi R. and Yang, Jian and Visscher, Peter M. and Robinson, Matthew Richard}, issn = {2041-1723}, journal = {Nature Communications}, publisher = {Springer Nature}, title = {{Improving genetic prediction by leveraging genetic correlations among human diseases and traits}}, doi = {10.1038/s41467-017-02769-6}, volume = {9}, year = {2018}, } @article{7717, abstract = {Background: DNA methylation levels change along with age, but few studies have examined the variation in the rate of such changes between individuals. Methods: We performed a longitudinal analysis to quantify the variation in the rate of change of DNA methylation between individuals using whole blood DNA methylation array profiles collected at 2–4 time points (N = 2894) in 954 individuals (67–90 years). Results: After stringent quality control, we identified 1507 DNA methylation CpG sites (rsCpGs) with statistically significant variation in the rate of change (random slope) of DNA methylation among individuals in a mixed linear model analysis. Genes in the vicinity of these rsCpGs were found to be enriched in Homeobox transcription factors and the Wnt signalling pathway, both of which are related to ageing processes. Furthermore, we investigated the SNP effect on the random slope. We found that 4 out of 1507 rsCpGs had one significant (P < 5 × 10−8/1507) SNP effect and 343 rsCpGs had at least one SNP effect (436 SNP-probe pairs) reaching genome-wide significance (P < 5 × 10−8). Ninety-five percent of the significant (P < 5 × 10−8) SNPs are on different chromosomes from their corresponding probes. Conclusions: We identified CpG sites that have variability in the rate of change of DNA methylation between individuals, and our results suggest a genetic basis of this variation. Genes around these CpG sites have been reported to be involved in the ageing process.}, author = {Zhang, Qian and Marioni, Riccardo E and Robinson, Matthew Richard and Higham, Jon and Sproul, Duncan and Wray, Naomi R and Deary, Ian J and McRae, Allan F and Visscher, Peter M}, issn = {1756-994X}, journal = {Genome Medicine}, number = {1}, publisher = {Springer Nature}, title = {{Genotype effects contribute to variation in longitudinal methylome patterns in older people}}, doi = {10.1186/s13073-018-0585-7}, volume = {10}, year = {2018}, } @article{7718, abstract = {Flores Island, Indonesia, was inhabited by the small-bodied hominin species Homo floresiensis, which has an unknown evolutionary relationship to modern humans. This island is also home to an extant human pygmy population. Here we describe genome-scale single-nucleotide polymorphism data and whole-genome sequences from a contemporary human pygmy population living on Flores near the cave where H. floresiensis was found. The genomes of Flores pygmies reveal a complex history of admixture with Denisovans and Neanderthals but no evidence for gene flow with other archaic hominins. Modern individuals bear the signatures of recent positive selection encompassing the FADS (fatty acid desaturase) gene cluster, likely related to diet, and polygenic selection acting on standing variation that contributed to their short-stature phenotype. Thus, multiple independent instances of hominin insular dwarfism occurred on Flores.}, author = {Tucci, Serena and Vohr, Samuel H. and McCoy, Rajiv C. and Vernot, Benjamin and Robinson, Matthew Richard and Barbieri, Chiara and Nelson, Brad J. and Fu, Wenqing and Purnomo, Gludhug A. and Sudoyo, Herawati and Eichler, Evan E. and Barbujani, Guido and Visscher, Peter M. and Akey, Joshua M. and Green, Richard E.}, issn = {0036-8075}, journal = {Science}, number = {6401}, pages = {511--516}, publisher = {American Association for the Advancement of Science}, title = {{Evolutionary history and adaptation of a human pygmy population of Flores Island, Indonesia}}, doi = {10.1126/science.aar8486}, volume = {361}, year = {2018}, } @article{7721, abstract = {The availability of genome-wide genetic data on hundreds of thousands of people has led to an equally rapid growth in methodologies available to analyse these data. While the motivation for undertaking genome-wide association studies (GWAS) is identification of genetic markers associated with complex traits, once generated these data can be used for many other analyses. GWAS have demonstrated that complex traits exhibit a highly polygenic genetic architecture, often with shared genetic risk factors across traits. New methods to analyse data from GWAS are increasingly being used to address a diverse set of questions about the aetiology of complex traits and diseases, including psychiatric disorders. Here, we give an overview of some of these methods and present examples of how they have contributed to our understanding of psychiatric disorders. We consider: (i) estimation of the extent of genetic influence on traits, (ii) uncovering of shared genetic control between traits, (iii) predictions of genetic risk for individuals, (iv) uncovering of causal relationships between traits, (v) identifying causal single-nucleotide polymorphisms and genes or (vi) the detection of genetic heterogeneity. This classification helps organise the large number of recently developed methods, although some could be placed in more than one category. While some methods require GWAS data on individual people, others simply use GWAS summary statistics data, allowing novel well-powered analyses to be conducted at a low computational burden.}, author = {Maier, R. M. and Visscher, P. M. and Robinson, Matthew Richard and Wray, N. R.}, issn = {0033-2917}, journal = {Psychological Medicine}, number = {7}, pages = {1055--1067}, publisher = {Cambridge University Press}, title = {{Embracing polygenicity: A review of methods and tools for psychiatric genetics research}}, doi = {10.1017/s0033291717002318}, volume = {48}, year = {2018}, } @article{7722, abstract = {We develop a Bayesian mixed linear model that simultaneously estimates single-nucleotide polymorphism (SNP)-based heritability, polygenicity (proportion of SNPs with nonzero effects), and the relationship between SNP effect size and minor allele frequency for complex traits in conventionally unrelated individuals using genome-wide SNP data. We apply the method to 28 complex traits in the UK Biobank data (N = 126,752) and show that on average, 6% of SNPs have nonzero effects, which in total explain 22% of phenotypic variance. We detect significant (P < 0.05/28) signatures of natural selection in the genetic architecture of 23 traits, including reproductive, cardiovascular, and anthropometric traits, as well as educational attainment. The significant estimates of the relationship between effect size and minor allele frequency in complex traits are consistent with a model of negative (or purifying) selection, as confirmed by forward simulation. We conclude that negative selection acts pervasively on the genetic variants associated with human complex traits.}, author = {Zeng, Jian and de Vlaming, Ronald and Wu, Yang and Robinson, Matthew Richard and Lloyd-Jones, Luke R. and Yengo, Loic and Yap, Chloe X. and Xue, Angli and Sidorenko, Julia and McRae, Allan F. and Powell, Joseph E. and Montgomery, Grant W. and Metspalu, Andres and Esko, Tonu and Gibson, Greg and Wray, Naomi R. and Visscher, Peter M. and Yang, Jian}, issn = {1061-4036}, journal = {Nature Genetics}, number = {5}, pages = {746--753}, publisher = {Springer Nature}, title = {{Signatures of negative selection in the genetic architecture of human complex traits}}, doi = {10.1038/s41588-018-0101-4}, volume = {50}, year = {2018}, } @article{7723, abstract = {Genome-wide association studies (GWAS) have identified thousands of loci that are robustly associated with complex diseases. The use of linear mixed model (LMM) methodology for GWAS is becoming more prevalent due to its ability to control for population structure and cryptic relatedness and to increase power. The odds ratio (OR) is a common measure of the association of a disease with an exposure (e.g., a genetic variant) and is readably available from logistic regression. However, when the LMM is applied to all-or-none traits it provides estimates of genetic effects on the observed 0–1 scale, a different scale to that in logistic regression. This limits the comparability of results across studies, for example in a meta-analysis, and makes the interpretation of the magnitude of an effect from an LMM GWAS difficult. In this study, we derived transformations from the genetic effects estimated under the LMM to the OR that only rely on summary statistics. To test the proposed transformations, we used real genotypes from two large, publicly available data sets to simulate all-or-none phenotypes for a set of scenarios that differ in underlying model, disease prevalence, and heritability. Furthermore, we applied these transformations to GWAS summary statistics for type 2 diabetes generated from 108,042 individuals in the UK Biobank. In both simulation and real-data application, we observed very high concordance between the transformed OR from the LMM and either the simulated truth or estimates from logistic regression. The transformations derived and validated in this study improve the comparability of results from prospective and already performed LMM GWAS on complex diseases by providing a reliable transformation to a common comparative scale for the genetic effects.}, author = {Lloyd-Jones, Luke R. and Robinson, Matthew Richard and Yang, Jian and Visscher, Peter M.}, issn = {0016-6731}, journal = {Genetics}, number = {4}, pages = {1397--1408}, publisher = {Genetics Society of America}, title = {{Transformation of summary statistics from linear mixed model association on all-or-none traits to odds ratio}}, doi = {10.1534/genetics.117.300360}, volume = {208}, year = {2018}, } @article{7724, abstract = {Modern molecular genetic datasets, primarily collected to study the biology of human health and disease, can be used to directly measure the action of natural selection and reveal important features of contemporary human evolution. Here we leverage the UK Biobank data to test for the presence of linear and nonlinear natural selection in a contemporary population of the United Kingdom. We obtain phenotypic and genetic evidence consistent with the action of linear/directional selection. Phenotypic evidence suggests that stabilizing selection, which acts to reduce variance in the population without necessarily modifying the population mean, is widespread and relatively weak in comparison with estimates from other species.}, author = {Sanjak, Jaleal S. and Sidorenko, Julia and Robinson, Matthew Richard and Thornton, Kevin R. and Visscher, Peter M.}, issn = {0027-8424}, journal = {Proceedings of the National Academy of Sciences}, number = {1}, pages = {151--156}, publisher = {Proceedings of the National Academy of Sciences}, title = {{Evidence of directional and stabilizing selection in contemporary humans}}, doi = {10.1073/pnas.1707227114}, volume = {115}, year = {2018}, } @article{7754, abstract = {Creating a selective gel that filters particles based on their interactions is a major goal of nanotechnology, with far-reaching implications from drug delivery to controlling assembly pathways. However, this is particularly difficult when the particles are larger than the gel’s characteristic mesh size because such particles cannot passively pass through the gel. Thus, filtering requires the interacting particles to transiently reorganize the gel’s internal structure. While significant advances, e.g., in DNA engineering, have enabled the design of nano-materials with programmable interactions, it is not clear what physical principles such a designer gel could exploit to achieve selective permeability. We present an equilibrium mechanism where crosslink binding dynamics are affected by interacting particles such that particle diffusion is enhanced. In addition to revealing specific design rules for manufacturing selective gels, our results have the potential to explain the origin of selective permeability in certain biological materials, including the nuclear pore complex.}, author = {Goodrich, Carl Peter and Brenner, Michael P. and Ribbeck, Katharina}, issn = {2041-1723}, journal = {Nature Communications}, publisher = {Springer Nature}, title = {{Enhanced diffusion by binding to the crosslinks of a polymer gel}}, doi = {10.1038/s41467-018-06851-5}, volume = {9}, year = {2018}, } @unpublished{7783, abstract = {The Drosophila Genetic Reference Panel (DGRP) serves as a valuable resource to better understand the genetic landscapes underlying quantitative traits. However, such DGRP studies have so far only focused on nuclear genetic variants. To address this, we sequenced the mitochondrial genomes of >170 DGRP lines, identifying 229 variants including 21 indels and 7 frameshifts. We used our mitochondrial variation data to identify 12 genetically distinct mitochondrial haplotypes, thus revealing important population structure at the mitochondrial level. We further examined whether this population structure was reflected on the nuclear genome by screening for the presence of potential mito-nuclear genetic incompatibilities in the form of significant genotype ratio distortions (GRDs) between mitochondrial and nuclear variants. In total, we detected a remarkable 1,845 mito-nuclear GRDs, with the highest enrichment observed in a 40 kb region around the gene Sex-lethal (Sxl). Intriguingly, downstream phenotypic analyses did not uncover major fitness effects associated with these GRDs, suggesting that a large number of mito-nuclear GRDs may reflect population structure at the mitochondrial level rather than actual genomic incompatibilities. This is further supported by the GRD landscape showing particular large genomic regions associated with a single mitochondrial haplotype. Next, we explored the functional relevance of the detected mitochondrial haplotypes through an association analysis on a set of 259 assembled, non-correlating DGRP phenotypes. We found multiple significant associations with stress- and metabolism-related phenotypes, including food intake in males. We validated the latter observation by reciprocal swapping of mitochondrial genomes from high food intake DGRP lines to low food intake ones. In conclusion, our study uncovered important mitochondrial population structure and haplotype-specific metabolic variation in the DGRP, thus demonstrating the significance of incorporating mitochondrial haplotypes in geno-phenotype relationship studies.}, author = {Bevers, Roel P.J. and Litovchenko, Maria and Kapopoulou, Adamandia and Braman, Virginie S. and Robinson, Matthew Richard and Auwerx, Johan and Hollis, Brian and Deplancke, Bart}, booktitle = {bioRxiv}, pages = {49}, publisher = {Cold Spring Harbor Laboratory}, title = {{Extensive mitochondrial population structure and haplotype-specific phenotypic variation in the Drosophila Genetic Reference Panel}}, year = {2018}, } @inproceedings{78, abstract = {We provide a procedure for detecting the sub-segments of an incrementally observed Boolean signal ω that match a given temporal pattern ϕ. As a pattern specification language, we use timed regular expressions, a formalism well-suited for expressing properties of concurrent asynchronous behaviors embedded in metric time. We construct a timed automaton accepting the timed language denoted by ϕ and modify it slightly for the purpose of matching. We then apply zone-based reachability computation to this automaton while it reads ω, and retrieve all the matching segments from the results. Since the procedure is automaton based, it can be applied to patterns specified by other formalisms such as timed temporal logics reducible to timed automata or directly encoded as timed automata. The procedure has been implemented and its performance on synthetic examples is demonstrated.}, author = {Bakhirkin, Alexey and Ferrere, Thomas and Nickovic, Dejan and Maler, Oded and Asarin, Eugene}, isbn = {978-3-030-00150-6}, location = {Bejing, China}, pages = {215 -- 232}, publisher = {Springer}, title = {{Online timed pattern matching using automata}}, doi = {10.1007/978-3-030-00151-3_13}, volume = {11022}, year = {2018}, } @inproceedings{7812, abstract = {Deep neural networks (DNNs) continue to make significant advances, solving tasks from image classification to translation or reinforcement learning. One aspect of the field receiving considerable attention is efficiently executing deep models in resource-constrained environments, such as mobile or embedded devices. This paper focuses on this problem, and proposes two new compression methods, which jointly leverage weight quantization and distillation of larger teacher networks into smaller student networks. The first method we propose is called quantized distillation and leverages distillation during the training process, by incorporating distillation loss, expressed with respect to the teacher, into the training of a student network whose weights are quantized to a limited set of levels. The second method, differentiable quantization, optimizes the location of quantization points through stochastic gradient descent, to better fit the behavior of the teacher model. We validate both methods through experiments on convolutional and recurrent architectures. We show that quantized shallow students can reach similar accuracy levels to full-precision teacher models, while providing order of magnitude compression, and inference speedup that is linear in the depth reduction. In sum, our results enable DNNs for resource-constrained environments to leverage architecture and accuracy advances developed on more powerful devices.}, author = {Polino, Antonio and Pascanu, Razvan and Alistarh, Dan-Adrian}, booktitle = {6th International Conference on Learning Representations}, location = {Vancouver, Canada}, title = {{Model compression via distillation and quantization}}, year = {2018}, } @inproceedings{79, abstract = {Markov Decision Processes (MDPs) are a popular class of models suitable for solving control decision problems in probabilistic reactive systems. We consider parametric MDPs (pMDPs) that include parameters in some of the transition probabilities to account for stochastic uncertainties of the environment such as noise or input disturbances. We study pMDPs with reachability objectives where the parameter values are unknown and impossible to measure directly during execution, but there is a probability distribution known over the parameter values. We study for the first time computing parameter-independent strategies that are expectation optimal, i.e., optimize the expected reachability probability under the probability distribution over the parameters. We present an encoding of our problem to partially observable MDPs (POMDPs), i.e., a reduction of our problem to computing optimal strategies in POMDPs. We evaluate our method experimentally on several benchmarks: a motivating (repeated) learner model; a series of benchmarks of varying configurations of a robot moving on a grid; and a consensus protocol.}, author = {Arming, Sebastian and Bartocci, Ezio and Chatterjee, Krishnendu and Katoen, Joost P and Sokolova, Ana}, location = {Beijing, China}, pages = {53--70}, publisher = {Springer}, title = {{Parameter-independent strategies for pMDPs via POMDPs}}, doi = {10.1007/978-3-319-99154-2_4}, volume = {11024}, year = {2018}, } @article{7983, abstract = {Feste Alkalicarbonate sind universelle Bestandteile von Passivierungsschichten an Materialien für Interkalationsbatterien, übliche Nebenprodukte in Metall‐O2‐Batterien, und es wird angenommen, dass sie sich reversibel in Metall‐O2 /CO2‐Zellen bilden und zersetzen. In all diesen Kathoden zersetzt sich Li2CO3 zu CO2, sobald es Spannungen >3.8 V vs. Li/Li+ ausgesetzt wird. Beachtenswert ist, dass keine O2‐Entwicklung detektiert wird, wie gemäß der Zersetzungsreaktion 2 Li2CO3 → 4 Li+ + 4 e− + 2 CO2 + O2 zu erwarten wäre. Deswegen war der Verbleib eines der O‐Atome ungeklärt und wurde nicht identifizierten parasitären Reaktionen zugerechnet. Hier zeigen wir, dass hochreaktiver Singulett‐Sauerstoff (1O2) bei der Oxidation von Li2CO3 in einem aprotischen Elektrolyten gebildet und daher nicht als O2 freigesetzt wird. Diese Ergebnisse haben weitreichende Auswirkungen auf die langfristige Zyklisierbarkeit von Batterien: sie untermauern die Wichtigkeit, 1O2 in Metall‐O2‐Batterien zu verhindern, stellen die Möglichkeit einer reversiblen Metall‐O2 /CO2‐Batterie basierend auf einem Carbonat‐Entladeprodukt in Frage und helfen, Grenzflächenreaktivität von Übergangsmetallkathoden mit Li2CO3‐Resten zu erklären.}, author = {Mahne, Nika and Renfrew, Sara E. and McCloskey, Bryan D. and Freunberger, Stefan Alexander}, issn = {0044-8249}, journal = {Angewandte Chemie}, number = {19}, pages = {5627--5631}, publisher = {Wiley}, title = {{Elektrochemische Oxidation von Lithiumcarbonat generiert Singulett-Sauerstoff}}, doi = {10.1002/ange.201802277}, volume = {130}, year = {2018}, } @article{8015, abstract = {The neural code of cortical processing remains uncracked; however, it must necessarily rely on faithful signal propagation between cortical areas. In this issue of Neuron, Joglekar et al. (2018) show that strong inter-areal excitation balanced by local inhibition can enable reliable signal propagation in data-constrained network models of macaque cortex. }, author = {Stroud, Jake P. and Vogels, Tim P}, issn = {0896-6273}, journal = {Neuron}, number = {1}, pages = {8--9}, publisher = {Elsevier}, title = {{Cortical signal propagation: Balance, amplify, transmit}}, doi = {10.1016/j.neuron.2018.03.028}, volume = {98}, year = {2018}, } @article{806, abstract = {Social insect colonies have evolved many collectively performed adaptations that reduce the impact of infectious disease and that are expected to maximize their fitness. This colony-level protection is termed social immunity, and it enhances the health and survival of the colony. In this review, we address how social immunity emerges from its mechanistic components to produce colony-level disease avoidance, resistance, and tolerance. To understand the evolutionary causes and consequences of social immunity, we highlight the need for studies that evaluate the effects of social immunity on colony fitness. We discuss the role that host life history and ecology have on predicted eco-evolutionary dynamics, which differ among the social insect lineages. Throughout the review, we highlight current gaps in our knowledge and promising avenues for future research, which we hope will bring us closer to an integrated understanding of socio-eco-evo-immunology.}, author = {Cremer, Sylvia and Pull, Christopher and Fürst, Matthias}, issn = {1545-4487}, journal = {Annual Review of Entomology}, pages = {105 -- 123}, publisher = {Annual Reviews}, title = {{Social immunity: Emergence and evolution of colony-level disease protection}}, doi = {10.1146/annurev-ento-020117-043110}, volume = {63}, year = {2018}, } @article{8073, abstract = {Motor cortex (M1) exhibits a rich repertoire of neuronal activities to support the generation of complex movements. Although recent neuronal-network models capture many qualitative aspects of M1 dynamics, they can generate only a few distinct movements. Additionally, it is unclear how M1 efficiently controls movements over a wide range of shapes and speeds. We demonstrate that modulation of neuronal input–output gains in recurrent neuronal-network models with a fixed architecture can dramatically reorganize neuronal activity and thus downstream muscle outputs. Consistent with the observation of diffuse neuromodulatory projections to M1, a relatively small number of modulatory control units provide sufficient flexibility to adjust high-dimensional network activity using a simple reward-based learning rule. Furthermore, it is possible to assemble novel movements from previously learned primitives, and one can separately change movement speed while preserving movement shape. Our results provide a new perspective on the role of modulatory systems in controlling recurrent cortical activity.}, author = {Stroud, Jake P. and Porter, Mason A. and Hennequin, Guillaume and Vogels, Tim P}, issn = {1097-6256}, journal = {Nature Neuroscience}, number = {12}, pages = {1774--1783}, publisher = {Springer Nature}, title = {{Motor primitives in space and time via targeted gain modulation in cortical networks}}, doi = {10.1038/s41593-018-0276-0}, volume = {21}, year = {2018}, }