Improving P300 Speller performance by means of optimization and machine learning

Brain-Computer Interfaces (BCIs) are systems allowing people to interact with the environment bypassing the natural neuromuscular and hormonal outputs of the peripheral nervous system (PNS). These interfaces record a user’s brain activity and translate it into control commands for external devices, thus providing the PNS with additional artificial outputs. In this framework, the BCIs based on the P300 Event-Related Potentials (ERP), which represent the electrical responses recorded from the brain after specific events or stimuli, have proven to be particularly successful and robust. The presence or the absence of a P300 evoked potential within the EEG features is determined through a classification algorithm. Linear classifiers such as stepwise linear discriminant analysis and support vector machine (SVM) are the most used discriminant algorithms for ERPs’ classification. Due to the low signal-to-noise ratio of the EEG signals, multiple stimulation sequences (a.k.a. iterations) are carried out and then averaged before the signals being classified. However, while augmenting the number of iterations improves the Signal-to-Noise Ratio, it also slows down the process. In the early studies, the number of iterations was fixed (no stopping environment), but recently several early stopping strategies have been proposed in the literature to dynamically interrupt the stimulation sequence when a certain criterion is met in order to enhance the communication rate. In this work, we explore how to improve the classification performances in P300 based BCIs by combining optimization and machine learning. First, we propose a new decision function that aims at improving classification performances in terms of accuracy and Information Transfer Rate both in a no stopping and early stopping environment. Then, we propose a new SVM training problem that aims to facilitate the target-detection process. Our approach proves to be effective on several publicly available datasets

THE CLINICAL SIGNIFICANCE OF TWO DIFFERENT ELECTROMYOGRAPHY NORMALISATION TECHNIQUES IN PATIENTS WITH ANTERIOR CRUCIATE LIGAMENT INSTABILITY DURING TREADMILL WALKING

The purpose of this study is to investigate the clinical outcome of two normalisation techniques in detecting neuromuscular alterations of the quadriceps muscles between injured and non-injured patients diagnosed with ACL knee instability in their right knee during repeated gait cycles on a treadmill. The ensemble average muscle activity of the vastus lateralis and vastus medialis were normalised to either MVC or maximal activation during the gait cycle in eight male and female subjects. Results indicate that the EMG normalised to MVC was more sensitive in detecting differences in activation between the vastus lateralis and vastus medialis than the normalisation to maximal activity during repeated strides. This study indicates the importance of choosing the appropriate normalisation technique when seeking a clinical outcome measure

Population Size, Sex and Purifying Selection: Comparative Genomics of Two Sister Taxa of the Wild Yeast Saccharomyces paradoxus

This study uses population genomic data to estimate demographic and selection parameters in two sister lineages of the wild yeast Saccharomyces paradoxus and compare their evolution. We first estimate nucleotide and recombinational diversities in each of the two lineages to infer their population size and frequency of sex and then analyze the rate of mutation accumulation since divergence from their inferred common ancestor to estimate the generation time and efficacy of selection. We find that one of the lineages has significantly higher silent nucleotide diversity and lower linkage disequilibrium, indicating a larger population with more frequent sexual generations. The same lineage also shows shorter generation time and higher efficacy of purifying selection, the latter consistent with the finding of larger population size and more frequent sex. Similar analyses are also performed on the ancestries of individual strains within lineages and we find significant differences between strains implying variation in rates of mitotic cell divisions. Our sample includes some strains originating in the Chernobyl nuclear-accident exclusion zone, which has been subjected to high levels of radiation for nearly 30 years now. We find no evidence, however, for increased rates of mutation. Finally, there is a positive correlation between rates of mutation accumulation and length of growing period, as measured by latitude of the place of origin of strains. Our study illustrates the power of genomic analyses in estimating population and life history parameters and testing predictions based on population genetic theory

Population genomics of domestic and wild yeasts

The natural genetics of an organism is determined by the distribution of sequences of its genome. Here we present one- to four-fold, with some deeper, coverage of the genome sequences of over seventy isolates of the domesticated baker's yeast, _Saccharomyces cerevisiae_, and its closest relative, the wild _S. paradoxus_, which has never been associated with human activity. These were collected from numerous geographic locations and sources (including wild, clinical, baking, wine, laboratory and food spoilage). These sequences provide an unprecedented view of the population structure, natural (and artificial) selection and genome evolution in these species. Variation in gene content, SNPs, indels, copy numbers and transposable elements provide insights into the evolution of different lineages. Phenotypic variation broadly correlates with global genome-wide phylogenetic relationships however there is no correlation with source. _S. paradoxus_ populations are well delineated along geographic boundaries while the variation among worldwide _S. cerevisiae_ isolates show less differentiation and is comparable to a single _S. paradoxus_ population. Rather than one or two domestication events leading to the extant baker's yeasts, the population structure of _S. cerevisiae_ shows a few well defined geographically isolated lineages and many different mosaics of these lineages, supporting the notion that human influence provided the opportunity for outbreeding and production of new combinations of pre-existing variation

The genetic architecture of low-temperature adaptation in the wine yeast Saccharomyces cerevisiae

[Background] Low-temperature growth and fermentation of wine yeast can enhance wine aroma and make them highly desirable traits for the industry. Elucidating response to cold in Saccharomyces cerevisiae is, therefore, of paramount importance to select or genetically improve new wine strains. As most enological traits of industrial importance in yeasts, adaptation to low temperature is a polygenic trait regulated by many interacting loci.[Results] In order to unravel the genetic determinants of low-temperature fermentation, we mapped quantitative trait loci (QTLs) by bulk segregant analyses in the F13 offspring of two Saccharomyces cerevisiae industrial strains with divergent performance at low temperature. We detected four genomic regions involved in the adaptation at low temperature, three of them located in the subtelomeric regions (chromosomes XIII, XV and XVI) and one in the chromosome XIV. The QTL analysis revealed that subtelomeric regions play a key role in defining individual variation, which emphasizes the importance of these regions’ adaptive nature.[Conclusions] The reciprocal hemizygosity analysis (RHA), run to validate the genes involved in low-temperature fermentation, showed that genetic variation in mitochondrial proteins, maintenance of correct asymmetry and distribution of phospholipid in the plasma membrane are key determinants of low-temperature adaptation.This work has been financially supported from the Spanish Government through MINECO and FEDER funds (AGL2013-47300-C3-3-R and PCIN-2015-143 grants) and from Generalitat Valenciana through PROMETEOII/2014/042 grant, awarded to JMG. This study has been carried out in the context of the European Project ERA-IB “YeastTempTation” EGR thanks the Spanish government for an FPI grant BES-2011-044498 and MM also thanks the Generalitat Valenciana for a VALi+d ACIF/2015/194 grant. We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI).Peer reviewe

Identification of furfural resistant strains of Saccharomyces cerevisiae and Saccharomyces paradoxus from a collection of environmental and industrial isolates

Background Fermentation of bioethanol using lignocellulosic biomass as a raw material provides a sustainable alternative to current biofuel production methods by utilising waste food streams as raw material. Before lignocellulose can be fermented it requires physical, chemical and enzymatic treatment in order to release monosaccharides, a process that causes the chemical transformation of glucose and xylose into the cyclic aldehydes furfural and hydroxyfurfural. These furan compounds are potent inhibitors of Saccharomyces fermentation, and consequently furfural tolerant strains of Saccharomyces are required for lignocellulosic fermentation. Results This study investigated yeast tolerance to furfural and hydroxyfurfural using a collection of 71 environmental and industrial isolates of the baker’s yeast Saccharomyces cerevisiae and its closest relative Saccharomyces paradoxus. The Saccharomyces strains were initially screened for growth on media containing 100 mM glucose and 1.5 mg ml-1 furfural. Five strains were identified that showed a significant tolerance to growth in the presence of furfural and these were then screened for growth and ethanol production in the presence of increasing amounts (0.1-4 mg ml-1) of furfural. Conclusions Of the five furfural tolerant strains S. cerevisiae NCYC 3451 displayed the greatest furfural resistance, and was able to grow in the presence of up to 3.0 mg ml-1 furfural. Furthermore, ethanol production in this strain did not appear to be inhibited by furfural, with the highest ethanol yield observed at 3.0 mg ml-1 furfural. Although furfural resistance was not found to be a trait specific to any one particular lineage or population, three of the strains were isolated from environments where they might be continually exposed to low levels of furfural through the on-going natural degradation of lignocelluloses, and would therefore develop elevated levels of resistance to these furan compounds. Thus these strains represent good candidates for future studies of genetic variation relevant to understanding and manipulating furfural resistance and in the development of tolerant ethanologenic yeast strains for use in bioethanol production from lignocellulose processing

Phenotypic characterisation of Saccharomyces spp. yeast for tolerance to stresses encountered during fermentation of lignocellulosic residues to produce bioethanol.

BACKGROUND: During industrial fermentation of lignocellulose residues to produce bioethanol, microorganisms are exposed to a number of factors that influence productivity. These include inhibitory compounds produced by the pre-treatment processes required to release constituent carbohydrates from biomass feed-stocks and during fermentation, exposure of the organisms to stressful conditions. In addition, for lignocellulosic bioethanol production, conversion of both pentose and hexose sugars is a pre-requisite for fermentative organisms for efficient and complete conversion. All these factors are important to maximise industrial efficiency, productivity and profit margins in order to make second-generation bioethanol an economically viable alternative to fossil fuels for future transport needs. RESULTS: The aim of the current study was to assess Saccharomyces yeasts for their capacity to tolerate osmotic, temperature and ethanol stresses and inhibitors that might typically be released during steam explosion of wheat straw. Phenotypic microarray analysis was used to measure tolerance as a function of growth and metabolic activity. Saccharomyces strains analysed in this study displayed natural variation to each stress condition common in bioethanol fermentations. In addition, many strains displayed tolerance to more than one stress, such as inhibitor tolerance combined with fermentation stresses. CONCLUSIONS: Our results suggest that this study could identify a potential candidate strain or strains for efficient second generation bioethanol production. Knowledge of the Saccharomyces spp. strains grown in these conditions will aid the development of breeding programmes in order to generate more efficient strains for industrial fermentations

Inference of population splits and mixtures from genome-wide allele frequency data

Many aspects of the historical relationships between populations in a species are reflected in genetic data. Inferring these relationships from genetic data, however, remains a challenging task. In this paper, we present a statistical model for inferring the patterns of population splits and mixtures in multiple populations. In this model, the sampled populations in a species are related to their common ancestor through a graph of ancestral populations. Using genome-wide allele frequency data and a Gaussian approximation to genetic drift, we infer the structure of this graph. We applied this method to a set of 55 human populations and a set of 82 dog breeds and wild canids. In both species, we show that a simple bifurcating tree does not fully describe the data; in contrast, we infer many migration events. While some of the migration events that we find have been detected previously, many have not. For example, in the human data we infer that Cambodians trace approximately 16% of their ancestry to a population ancestral to other extant East Asian populations. In the dog data, we infer that both the boxer and basenji trace a considerable fraction of their ancestry (9% and 25%, respectively) to wolves subsequent to domestication, and that East Asian toy breeds (the Shih Tzu and the Pekingese) result from admixture between modern toy breeds and "ancient" Asian breeds. Software implementing the model described here, called TreeMix, is available at http://treemix.googlecode.comComment: 28 pages, 6 figures in main text. Attached supplement is 22 pages, 15 figures. This is an updated version of the preprint available at http://precedings.nature.com/documents/6956/version/

Evidence for Pervasive Adaptive Protein Evolution in Wild Mice

The relative contributions of neutral and adaptive substitutions to molecular evolution has been one of the most controversial issues in evolutionary biology for more than 40 years. The analysis of within-species nucleotide polymorphism and between-species divergence data supports a widespread role for adaptive protein evolution in certain taxa. For example, estimates of the proportion of adaptive amino acid substitutions (alpha) are 50% or more in enteric bacteria and Drosophila. In contrast, recent estimates of alpha for hominids have been at most 13%. Here, we estimate alpha for protein sequences of murid rodents based on nucleotide polymorphism data from multiple genes in a population of the house mouse subspecies Mus musculus castaneus, which inhabits the ancestral range of the Mus species complex and nucleotide divergence between M. m. castaneus and M. famulus or the rat. We estimate that 57% of amino acid substitutions in murids have been driven by positive selection. Hominids, therefore, are exceptional in having low apparent levels of adaptive protein evolution. The high frequency of adaptive amino acid substitutions in wild mice is consistent with their large effective population size, leading to effective natural selection at the molecular level. Effective natural selection also manifests itself as a paucity of effectively neutral nonsynonymous mutations in M. m. castaneus compared to humans