bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving the quality of combined EEG-TMS neural recordings: Introducing the Coil Spacer
Authors: Ruddy K.L. , Woolley D.G. , Mantini D. , Balsters J.H. , Enz N. , Wenderoth N. 
Published: August 2017

ABSTRACTBackgroundIn the last decade, interest in combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) approaches has grown substantially. Aside from the obvious artifacts induced by the magnetic pulses themselves, separate and more sinister signal disturbances arise as a result of contact between the TMS coil and EEG electrodes.New methodHere we profile the characteristics of these artifacts and introduce a simple device – the coil spacer - to provide a platform allowing physical separation between the coil and electrodes during stimulation.ResultsEEG data revealed high amplitude signal disturbances when the TMS coil was in direct contact with the EEG electrodes, well within the physiological range of viable EEG signals. The largest artifacts were located in the Delta and Theta frequency range, and standard data cleanup using independent components analysis (ICA) was ineffective due to the artifact’s similarity to real brain oscillations.Comparison with Existing MethodWhile the current best practice is to use a large coil holding apparatus to fixate the coil ‘hovering’ over the head with an air gap, the spacer provides a simpler solution that ensures this distance is kept constant throughout testing.ConclusionsThe results strongly suggest that data collected from combined TMS-EEG studies with the coil in direct contact with the EEG cap are polluted with low frequency artifacts that are indiscernible from physiological brain signals. The coil spacer provides a cheap and simple solution to this problem and is recommended for use in future simultaneous TMS-EEG recordings.
Activation of serotonin neurons promotes active exploitation in a probabilistic foraging task
Authors: Lottem Eran , Banerjee Dhruba , Vertechi Pietro , Sarra Dario , Lohuis Matthijs oude , Mainen Zachary F. 
Published: August 2017

AbstractThe neuromodulator serotonin (5-HT) has been implicated in a variety of functions that involve patience or impulse control. For example, activation of 5-HT neurons promotes waiting for delayed rewards. Many of these effects are consistent with a long-standing theory that 5-HT promotes behavioral inhibition, a motivational bias favoring passive over active behaviors. To further test this idea, we studied the impact of 5-HT in a probabilistic foraging task, in which mice must learn the statistics of the environment and infer when to leave a depleted foraging site for the next. Critically, mice were required to actively nose poke in order to exploit a given site. We found that optogenetic activation of 5-HT neurons in the dorsal raphe nucleus increased the willingness of mice to actively attempt to exploit a reward site before giving up. These results indicate that behavioral inhibition is not an adequate description of 5-HT function and suggest that a unified account must be based on a higher-order function.
Microbiome–host systems interactions: Protective effects of propionate upon the blood–brain barrier
Authors: Hoyles Lesley , Snelling Tom , Umlai Umm-Kulthum , Nicholson Jeremy K. , Carding Simon R. , Glen Robert C. , McArthur Simon 
Published: August 2017

AbstractBackgroundGut microbiota composition and function are symbiotically linked with host health, and altered in metabolic, inflammatory and neurodegenerative disorders. Three recognized mechanisms exist by which the microbiome influences the gut-brain axis: modification of autonomic/sensorimotor connections, immune activation, and neuroendocrine pathway regulation. We hypothesized interactions between circulating gut–derived microbial metabolites and the blood–brain barrier (BBB) also contribute to the gut–brain axis. Propionate, produced from dietary substrates by colonic bacteria, stimulates intestinal gluconeogenesis and is associated with reduced stress behaviours, but its potential endocrine role has not been addressed.ResultsAfter demonstrating expression of the propionate receptor FFAR3 on human brain endothelium, we examined the impact of a physiologically relevant propionate concentration (1 μM) on BBB propertiesin vitro. Propionate inhibited pathways associated with non-specific microbial infections via a CD14-dependent mechanism, suppressed expression of LRP-1 and protected the BBB from oxidative stress via NRF2 (NFE2L2) signaling.ConclusionsTogether, these results suggest gut-derived microbial metabolites interact with the BBB, representing a fourth facet of the gut–brain axis that warrants further attention.
RAPID: Real-time image-based autofocus for all wide-field optical microscopy systems
Authors: Silvestri L. , Müllenbroich M. C. , Costantini I. , Di Giovanna A. P. , Sacconi L. , Pavone F. S. 
Published: August 2017

AbstractAutofocus methods used in biomicroscopy are either based on the search of an optimal focus position – which requires suspending data collection during the optimization process – or on the continuous monitoring of the position of a fiducial plane – which may not coincide with the sample itself. Here, we introduce RAPID (Rapid Autofocus via Pupil-split Image phase Detection), a method for real-time image-based focus stabilization, applicable in all wide-field microscopy systems. We demonstrate that RAPID maintains high image quality in various settings, fromin vivofluorescence imaging to light-sheet microscopy. RAPID provides a universal autofocus solution for automated microscopy, and enables quantitative assays otherwise impossible in a standard microscope, such as 3D tracking of fast-moving organisms.
Population turnover reverses classic island biogeography predictions in river-like landscapes
Authors: Harvey Eric , Gounand Isabelle , Fronhofer Emanuel A. , Altermatt Florian 
Published: August 2017

Statement of authorshipEH, IG, EAF and FA designed the research; IG and EAF designed the model; IG programmed and ran the model, analyzed the simulation data with support from EAF and produced the figures; EH conducted the lab experiment with support from IG, EAF and FA, processed the experimental data with support from IG, and carried out the analysis of experimental data; all authors participated in results interpretation; EH wrote the first draft of the manuscript; All authors significantly contributed to further manuscript revisions. EH and IG contributed equally to this work.
Supervised machine learning reveals introgressed loci in the genomes ofDrosophila simulansandD. sechellia
Authors: Schrider Daniel R. , Ayroles Julien , Matute Daniel R. , Kern Andrew D. 
Published: August 2017

ABSTRACTHybridization and gene flow between species appears to be common. Even though it is clear that hybridization is widespread across all surveyed taxonomic groups, the magnitude and consequences of introgression are still largely unknown. Thus it is crucial to develop the statistical machinery required to uncover which genomic regions have recently acquired haplotypes via introgression from a sister population. We developed a novel machine learning framework, called FILET (Finding Introgressed Loci via Extra-Trees) capable of revealing genomic introgression with far greater power than competing methods. FILET works by combining information from a number of population genetic summary statistics, including several new statistics that we introduce, that capture patterns of variation across two populations. We show that FILET is able to identify loci that have experienced gene flow between related species with high accuracy, and in most situations can correctly infer which population was the donor and which was the recipient. Here we describe a data set of outbred diploidDrosophila sechelliagenomes, and combine them with data fromD. simulansto examine recent introgression between these species using FILET. Although we find that these populations may have split more recently than previously appreciated, FILET confirms that there has indeed been appreciable recent introgression (some of which might have been adaptive) between these species, and reveals that this gene flow is primarily in the direction ofD. simulanstoD. sechellia.AUTHOR SUMMARYUnderstanding the extent to which species or diverged populations hybridize in nature is crucially important if we are to understand the speciation process. Accordingly numerous research groups have developed methodology for finding the genetic evidence of such introgression. In this report we develop a supervised machine learning approach for uncovering loci which have introgressed across species boundaries. We show that our method, FILET, has greater accuracy and power than competing methods in discovering introgression, and in addition can detect the directionality associated with the gene flow between species. Using whole genome sequences fromDrosophila simulansandDrosophila sechelliawe show that FILET discovers quite extensive introgression between these species that has occurred mostly fromD. simulanstoD. sechellia.Our work highlights the complex process of speciation even within a well-studied system and points to the growing importance of supervised machine learning in population genetics.
Small GTPases and BAR domain proteins regulate branched actin to make clathrin and dynamin independent endocytic vesicles
Authors: Sathe Mugdha , Muthukrishnan Gayatri , Rae James , Disanza Andrea , Thattai Mukund , Scita Giorgio , Parton Robert G. , Mayor Satyajit 
Published: August 2017

AbstractNumerous endocytic pathways operate simultaneously at the cell surface. Here we focus on the molecular machinery involved in the generation of endocytic vesicles of the clathrin and dynamin-independent CLIC/GEEC (CG) pathway. This pathway internalises many GPI-anchored proteins and a large fraction of the fluid-phase in different cell types. We developed a real-time TIRF assay using pH-sensitive GFP-GPI to identify nascent CG endocytic sites. The temporal profile of known CG pathway modulators showed that ARF1/GBF1 (GTPase/GEF pair) and CDC42 (RhoGTPase) are recruited sequentially to CG endocytic sites, ∼60s and ∼9s prior to scission. Using a limited RNAi screen, we found several BAR domain proteins affecting CG endocytosis and focused on IRSp53 and PICK1 that have interactions with CDC42 and ARF1 respectively. IRSp53, an I-BAR domain containing protein, was recruited to the plasma membrane at the site of forming CG endocytic vesicles and in its absence, nascent endocytic CLICs, did not form. The requirement for actin polymerization in the CG pathway suggested a role for nucleators of actin polymerization, and ARP2/3 was found enriched at the site of the forming endocytic vesicle. PICK1, a BAR domain containing protein and the ARP2/3 inhibitor is recruited at an early stage along with ARP2/3, but is removed from the endocytic site coincident with CDC42 recruitment and a burst of Factin polymerization. This study provides a spatio-temporal understanding of the molecular machinery necessary to build a CG endocytic vesicle.
Bayesian Optimisation of Large-Scale Biophysical Networks
Authors: Hadida J. , Sotiropoulos S.N. , Abeysuriya R.G. , Woolrich M.W. , Jbabdi S. 
Published: August 2017

AbstractThe relationship between structure and function in the human brain is well established, but not yet well characterised. Large-scale biophysical models allow us to investigate this relationship, by leveraging structural information (e.g. derived from diffusion tractography) in order to couple dynamical models of local neuronal activity into networks of interacting regions distributed across the cortex. In practice however, these models are difficult to parametrise, and their simulation is often delicate and computationally expensive. This undermines the experimental aspect of scientific modelling, and stands in the way of comparing different parametrisations, network architectures, or models in general, with confidence. Here, we advocate the use of Bayesian optimisation for assessing the capabilities of biophysical network models, given a set of desired properties (e.g. band-specific functional connectivity); and in turn the use of this assessment as a principled basis for incremental modelling and model comparison. We adapt an optimisation method designed to cope with costly, high-dimensional, non-convex problems, and demonstrate its use and effectiveness. We find that this method is able to converge to regions of high functional similarity with real MEG data, with very few samples given the number of parameters, without getting stuck in local extrema, and while building and exploiting a map of uncertainty defined smoothly across the parameter space. We compare the results obtained using different methods of structural connectivity estimation from diffusion tractography, and find that one method leads to better simulations.
PyBoost: A parallelized Python implementation of 2D boosting with hierarchies
Authors: Greenside Peyton G. , Hussami Nadine , Chang Jessica , Kundaje Anshul 
Published: August 2017

AbstractMotivation:Gene expression is controlled by networks of transcription factors that bind specific sequence motifs in regulatory DNA elements such as promoters and enhancers. GeneClass is a boosting-based algorithm that learns gene regulatory networks from complementary paired feature sets such as transcription factor expression levels and binding motifs across conditions. This algorithm can be used to predict functional genomics measures of cell state, such as gene expression and chromatin accessibility, in different cellular conditions. We present a parallelized, Python-based implementation of GeneClass, called PyBoost, along with a novel hierarchical implementation of the algorithm, called HiBoost. HiBoost allows regulatory logic to be constrained to a hierarchical group of conditions or cell types. The software can be used to dissect differentiation cascades, time courses or other perturbation data that naturally form a hierarchy or trajectory. We demonstrate the application of PyBoost and HiBoost to learn regulators of tadpole tail regeneration and hematopoeitic stem cell differentiation and validate learned regulators through an inducible CRISPR system.Availability:The implementation is publicly available here:https://github.com/kundajelab/boosting2D/.
Forgot what you like? Evidence for hippocampal dependence of value-based decisions
Authors: Enkavi A. Z. , Weber B. , Zweyer I. , Wagner J. , Elger C.E. , Weber E. U. , Johnson E. J. 
Published: August 2017

AbstractConsistent decisions are intuitively desirable and theoretically important for utility maximization. Neuroeconomics has established the neurobiological substrate of value representation, but brain regions that provide input to the value-processing network is less explored. The constructed-preference tradition within behavioral decision research gives a critical role to cognitive processes that rely on associations, suggesting a role for the hippocampus in making decisions and to do so consistently. We compared the performance of 31 patients with mediotemporal lobe (MTL) epilepsy and hippocampal lesions, 30 patients with extratemporal lobe epilepsy, and 30 healthy controls on two tasks: binary choices between candy bars based on their preferences and a number-comparison control task where the larger number is chosen. MTL patients make more inconsistent choices than the other two groups for the value-based choice but not the number-comparison task. These inconsistencies increase with the volume of compromised hippocampal tissue. These results suggest a critical involvement of the MTL in preference construction and value-based choices.SignificanceOur days are full of choices that reflect our preferences. Economics lays out models of how to optimally make these decisions. Neuroeconomics has identified a cortical value-processing network whose activity correlates with constructs related to valuation and choice in economic models. However open questions remain: How are these value signals formed, and what regions might be necessary for retrieving and computing these value signals? Inspired by cognitive models calling on associative processes in value-based decisions, this paper uses unique neuropsychological data to establish the critical role of the medial temporal lobe in making consistent choices and further informs our understanding of the value-processing network.
Switching to renewables: what will Russia gain?
Authors: Ermolenko Georgy V. , Proskuryakova Liliana , Ermolenko Boris V. 
Published: August 2017

Purpose
The purpose of the study is to show the technical potentials of a variety of renewable energy sources in Russia, as well as benefits from their deployment including hydrocarbon savings, emission reduction and lower energy cost.

Design/methodology/approach
In the paper, Russia is compared with other countries in terms of actual installed capacity and its dynamics, actual and projected share of renewables in the energy mix. The authors offer calculations of the technical potentials (fuel, heat energy, electrical energy, resource saving and environmental) of renewables (solar PV, wind, biomass, geothermal, low-grade heat, small hydro), identify social and economic preconditions and key effects of their deployment.

Findings
The paper features calculations on the renewable energy technology potential, based on the data by Andreenko et al. (2015), authors' calculations and statistical data. This study proves that the cumulative technical potential of the renewables in Russia amounts to 133,935 million units of oil equivalent. This study also offers assessments of oil fuel, black coal and natural gas savings that may be achieved by replacing fossil fuels with renewables; assessments of avoided air pollution calculated as CO- and CO2-equivalents.

Originality/value
The paper fills in the gap of comprehensive assessments of renewable energy potentials in Russia and a variety of effects that their deployment may entail, based on a single integral methodology. The authors offer a new evaluation of existing and future renewable energy potentials, overcoming the methodological and data constraints faced by previous similar studies. The up-to-date, comprehensive and accurate data will help make the right investment and policy choices.
Creating sustainable impact from Foresight on STI Policy
Authors: Meissner Dirk , Rudnik Pavel 
Published: August 2017

Purpose
Foresight is frequently used to establish science and technology investment priorities and develop corresponding technology and innovation support programmes. In the light of technology and innovation policy, many individual Foresight studies are undertaken which are separate and little linked with the broader policy scope and ambition. This paper aims to look at an approach towards a consistent Foresight system which is linked closely to science, technology and innovation policy.

Design/methodology/approach
The paper provides an in-depth case study of the Russian Foresight system. The case study is based on desk research and extensive experience of the authors with the system.

Findings
Russia has developed a systematic approach towards organising Foresight which involves and serves multiple stakeholders, including government, ministries, federal and regional agencies, higher education institutions, public research institutes, state-owned companies and private businesses and a large range of associations. Under the auspicious of a dedicated commission, targeted Foresight is undertaken with clearly defined scope for each. The paper finds that the Russian system is unique in its organisational structure and in the integration of Foresight with science, technology and innovation policy measures.

Originality/value
The paper describes all facets of the Russian Foresight system which has not been done before. It also outlines the practical steps to further develop and leverage the system.
Using foresight for smart policy actions: the case of Russian energy exports
Authors: Chulok Alexander , Slobodianik Svetlana N. , Moiseichev Evgeny 
Published: August 2017

Purpose
This study aims to assess future prospects for Russian energy exports until 2040, as global energy markets are undergoing major changes, with possible impacts on Russia.

Design/methodology/approach
Qualitative and quantitative approaches are integrated under a proposed foresight framework. The qualitative method involves an expert survey aimed at identifying major energy trends and their influence on Russia. As the trends are validated, an algorithm is proposed to assess the contribution of separate trends to Russian energy exports.

Findings
Experimental quantitative scenarios are conducted to assess the prospects for Russian energy exports until 2040 under the given exogenous scenario calculations of the IEA. Factor analysis allows for an assessment of the contribution of separate factors in dynamics of net energy imports into the regional economies. The future prospects for fossil fuels’ exports on regional markets are considered. Priority markets for Russian energy exporters are identified.

Practical implications
The results of the paper may be used by decision-makers for adjustments in the system of government policy or corporate strategy.

Originality/value
The paper provides an algorithm to assess energy export flows to macroregions based upon the synthesis of quantitative and qualitative information. Experimental scenario calculations of the Russian fossil fuels’ exports are provided. Strategic decision-making map is elaborated.
Flow of a radioactive Casson fluid through a deformable asymmetric porous channel
Authors: Mohyud-Din Syed Tauseef , Ahmed Naveed , Khan Umar 
Published: August 2017

Purpose
The purpose of this study is to investigate numerically the influence of nonlinear thermal radiation on the flow of a viscous fluid. The flow is confined in a channel with deformable porous walls.

Design/methodology/approach
Two numerical schemes, namely, Galerkin’s method (GM) and Runge–Kutta–Fehlberg (RKF) method have been used to obtain solutions after reducing the governing equations to a system of nonlinear ordinary differential equations.

Findings
Heat transfer rate falls at the upper wall owing to the decreasing values of the permeability parameter. However, at the lower wall, the same rate rises. Increment in θw increases the rate of heat transfer at both walls. Nusselt number also increases with the increasing values of Rd. Rd also uplifts the temperature distribution, except for the case where it falls near the lower wall owing to the contraction coupled with injection.

Originality/value
It is confirmed that the presented work is original.