128 research outputs found

    Brain Rhythms Reveal a Hierarchical Network Organization

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    Recordings of ongoing neural activity with EEG and MEG exhibit oscillations of specific frequencies over a non-oscillatory background. The oscillations appear in the power spectrum as a collection of frequency bands that are evenly spaced on a logarithmic scale, thereby preventing mutual entrainment and cross-talk. Over the last few years, experimental, computational and theoretical studies have made substantial progress on our understanding of the biophysical mechanisms underlying the generation of network oscillations and their interactions, with emphasis on the role of neuronal synchronization. In this paper we ask a very different question. Rather than investigating how brain rhythms emerge, or whether they are necessary for neural function, we focus on what they tell us about functional brain connectivity. We hypothesized that if we were able to construct abstract networks, or “virtual brains”, whose dynamics were similar to EEG/MEG recordings, those networks would share structural features among themselves, and also with real brains. Applying mathematical techniques for inverse problems, we have reverse-engineered network architectures that generate characteristic dynamics of actual brains, including spindles and sharp waves, which appear in the power spectrum as frequency bands superimposed on a non-oscillatory background dominated by low frequencies. We show that all reconstructed networks display similar topological features (e.g. structural motifs) and dynamics. We have also reverse-engineered putative diseased brains (epileptic and schizophrenic), in which the oscillatory activity is altered in different ways, as reported in clinical studies. These reconstructed networks show consistent alterations of functional connectivity and dynamics. In particular, we show that the complexity of the network, quantified as proposed by Tononi, Sporns and Edelman, is a good indicator of brain fitness, since virtual brains modeling diseased states display lower complexity than virtual brains modeling normal neural function. We finally discuss the implications of our results for the neurobiology of health and disease

    Regional disparities in the beneficial effects of rising CO2 concentrations on crop water productivity

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    Rising atmospheric CO2 concentrations ([CO2]) are expected to enhance photosynthesis and reduce crop water use1. However, there is high uncertainty about the global implications of these effects for future crop production and agricultural water requirements under climate change. Here we combine results from networks of field experiments1, 2 and global crop models3 to present a spatially explicit global perspective on crop water productivity (CWP, the ratio of crop yield to evapotranspiration) for wheat, maize, rice and soybean under elevated [CO2] and associated climate change projected for a high-end greenhouse gas emissions scenario. We find CO2 effects increase global CWP by 10[0;47]%–27[7;37]% (median[interquartile range] across the model ensemble) by the 2080s depending on crop types, with particularly large increases in arid regions (by up to 48[25;56]% for rainfed wheat). If realized in the fields, the effects of elevated [CO2] could considerably mitigate global yield losses whilst reducing agricultural consumptive water use (4–17%). We identify regional disparities driven by differences in growing conditions across agro-ecosystems that could have implications for increasing food production without compromising water security. Finally, our results demonstrate the need to expand field experiments and encourage greater consistency in modelling the effects of rising [CO2] across crop and hydrological modelling communities

    On How Network Architecture Determines the Dominant Patterns of Spontaneous Neural Activity

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    In the absence of sensory stimulation, neocortical circuits display complex patterns of neural activity. These patterns are thought to reflect relevant properties of the network, including anatomical features like its modularity. It is also assumed that the synaptic connections of the network constrain the repertoire of emergent, spontaneous patterns. Although the link between network architecture and network activity has been extensively investigated in the last few years from different perspectives, our understanding of the relationship between the network connectivity and the structure of its spontaneous activity is still incomplete. Using a general mathematical model of neural dynamics we have studied the link between spontaneous activity and the underlying network architecture. In particular, here we show mathematically how the synaptic connections between neurons determine the repertoire of spatial patterns displayed in the spontaneous activity. To test our theoretical result, we have also used the model to simulate spontaneous activity of a neural network, whose architecture is inspired by the patchy organization of horizontal connections between cortical columns in the neocortex of primates and other mammals. The dominant spatial patterns of the spontaneous activity, calculated as its principal components, coincide remarkably well with those patterns predicted from the network connectivity using our theory. The equivalence between the concept of dominant pattern and the concept of attractor of the network dynamics is also demonstrated. This in turn suggests new ways of investigating encoding and storage capabilities of neural networks

    Longitudinal Study of the Dynamics of Vaginal Microflora during Two Consecutive Menstrual Cycles

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    Although the vaginal microflora (VMF) has been well studied, information on the fluctuation of the different bacterial species throughout the menstrual cycle and the information on events preceding the presence of disturbed VMF is still very limited. Documenting the dynamics of the VMF during the menstrual cycle might provide better insights. In this study, we assessed the presence of different Lactobacillus species in relation to the BV associated species during the menstrual cycle, assessed the influence of the menstrual cycle on the different categories of vaginal microflora and assessed possible causes, such as menstruation and sexual intercourse, of VMF disturbance. To our knowledge, this is the first longitudinal study in which swabs and Gram stains were available for each day of two consecutive menstrual cycles, whereby 8 grades of VMF were distinguished by Gram stain analysis, and whereby the swabs were cultured every 7(th) day and identification of the bacterial isolates was carried out with a molecular technique.status: publishe

    Incorporating field wind data to improve crop evapotranspiration parameterization in heterogeneous regions

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    Accurate parameterization of reference evapotranspiration ( ET0) is necessary for optimizing irrigation scheduling and avoiding costs associated with over-irrigation (water expense, loss of water productivity, energy costs, and pollution) or with under-irrigation (crop stress and suboptimal yields or quality). ET0 is often estimated using the FAO-56 method with meteorological data gathered over a reference surface, usually short grass. However, the density of suitable ET0 stations is often low relative to the microclimatic variability of many arid and semi-arid regions, leading to a potentially inaccurate ET0 for irrigation scheduling. In this study, we investigated multiple ET0 products from six meteorological stations, a satellite ET0 product, and integration (merger) of two stations’ data in Southern California, USA. We evaluated ET0 against lysimetric ET observations from two lysimeter systems (weighing and volumetric) and two crops (wine grapes and Jerusalem artichoke) by calculating crop ET ( ETc) using crop coefficients for the lysimetric crops with the different ET0. ETc calculated with ET0 products that incorporated field-specific wind speed had closer agreement with lysimetric ET, with RMSE reduced by 36 and 45% for grape and Jerusalem artichoke, respectively, with on-field anemometer data compared to wind data from the nearest station. The results indicate the potential importance of on-site meteorological sensors for ET0 parameterization; particularly where microclimates are highly variable and/or irrigation water is expensive or scarce

    Mutational analysis of the C-terminal FATC domain of Saccharomyces cerevisiae Tra1

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    Tra1 is a component of the Saccharomyces cerevisiae SAGA and NuA4 complexes and a member of the PIKK family, which contain a C-terminal phosphatidylinositol 3-kinase-like (PI3K) domain followed by a 35-residue FATC domain. Single residue changes of L3733A and F3744A, within the FATC domain, resulted in transcriptional changes and phenotypes that were similar but not identical to those caused by mutations in the PI3K domain or deletions of other SAGA or NuA4 components. The distinct nature of the FATC mutations was also apparent from the additive effect of tra1-L3733A with SAGA, NuA4, and tra1 PI3K domain mutations. Tra1-L3733A associates with SAGA and NuA4 components and with the Gal4 activation domain, to the same extent as wild-type Tra1; however, steady-state levels of Tra1-L3733A were reduced. We suggest that decreased stability of Tra1-L3733A accounts for the phenotypes since intragenic suppressors of tra1-L3733A restored Tra1 levels, and reducing wild-type Tra1 led to comparable growth defects. Also supporting a key role for the FATC domain in the structure/function of Tra1, addition of a C-terminal glycine residue resulted in decreased association with Spt7 and Esa1, and loss of cellular viability. These findings demonstrate the regulatory potential of mechanisms targeting the FATC domains of PIKK proteins

    Water balance creates a threshold in soil pH at the global scale

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    Soil pH regulates the capacity of soils to store and supply nutrients, and thus contributes substantially to controlling productivity in terrestrial ecosystems. However, soil pH is not an independent regulator of soil fertility-rather, it is ultimately controlled by environmental forcing. In particular, small changes in water balance cause a steep transition from alkaline to acid soils across natural climate gradients. Although the processes governing this threshold in soil pH are well understood, the threshold has not been quantified at the global scale, where the influence of climate may be confounded by the effects of topography and mineralogy. Here we evaluate the global relationship between water balance and soil pH by extracting a spatially random sample (n = 20,000) from an extensive compilation of 60,291 soil pH measurements. We show that there is an abrupt transition from alkaline to acid soil pH that occurs at the point where mean annual precipitation begins to exceed mean annual potential evapotranspiration. We evaluate deviations from this global pattern, showing that they may result from seasonality, climate history, erosion and mineralogy. These results demonstrate that climate creates a nonlinear pattern in soil solution chemistry at the global scale; they also reveal conditions under which soils maintain pH out of equilibrium with modern climate

    Development of the serotonergic cells in murine raphe nuclei and their relations with rhombomeric domains

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    Educational change, inertia and potential futures

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    The point of departure of the paper is that there are profound social, cultural, technological, scientific and environmental changes which occur at most local but also at global levels of the modern world. From these will stem huge challenges in all spheres of life. These demand changes in education, not necessarily in the system or how it operates, but perhaps in its aims, and most certainly in its content. Knowledge that was once powerful to understand the world, to develop as a person and address the challenges of life, should be replaced with new knowledge which may often be outside the traditional disciplines. Moreover, a host of new skills may be relevant for the world of tomorrow. There are, however, many obstacles to change, both reasonable and unreasonable ones. The thrust of the paper is to provide a discussion of nine categories of inertia or constraints that are seen to stifle change, in particular, as it relates to the content of education. The categories are discussed under the headings of general conservativism, system stability, standards, fuzziness of new ideas, the strength of old ideas, vested interests, teacher education, lack of space and motivation for initiative, and lack of consequence of no change. Added to this there are serious logistic problems for those who want to foster change. It is argued that very little change in content will be seen if these inertial constraints are not recognised. Assuming there is a will to change, the institutional infrastructures that should facilitate sustained change must be scutinised and it must be ensured that the teachers, i.e. the professionals that operate the system, are involved.Peer Reviewe
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