Cortical Imaging Based on an Analytic High Resolution EEG

It is well known that the EEG is a blurred and spatially low-pass filtered representation of the cortical activity. Since additional recording electrodes will not necessarily lead to an improved spatial resolution, further steps have to be taken. We derived the analytic downward continuation of the scalp potential field to an arbitrary inner surface for a spherical volume conductor model with piecewise constant conductivities. The basic idea of the Analytic High Resolution BEG (AHREEG) is the fact that a function defined on a sphere can be expressed as a weighted sum of spherical harmonics. Considering the spatial transfer function between the cortex and the scalp surface, the potential distribution on the cortex is theoretically computed by the application of the inverse transfer function to the scalp potential field. Compared to source localization procedures, the AHREEG is not based on any source distribution or on the nature of the sources. Furthermore the proposed method is unique, though ill-posed. Due to this fact and the fact that real world data are always contaminated by noise, a regularization based on general cross validation is performed to stabilize the inverse solution. Simulation results as well as the application of the AHREEG to EEG recorded during median nerve stimulation will be presented and critically discussed

Time/space regularization of the inward continuation problem in EEG using the Boundary Element Method

The inward continuation problem in EEG consists in the computation of the cortical potential distribution from the measured potential distribution on the scalp. Although unique this inverse problem is ill-posed. That is, low-level noise in the scalp potential data or a small error in the geometrical data can lead to unbounded errors in the solution. Regularization techniques have to be used to minimize these effects. The inverse problem is solved in two steps. First Tikhonov regularization is applied yielding a solution of the potential on the inside of the skull surface for every timestep. Than the solution of the first step is used for Twomey regularization. At each moment in time a new solution is found by using as a priori estimate the average of the first solution one timestep prior and one timestep after. This combination of spatial (Tikhonov) and temporal (Twomey) regularization improves the solution and smoothes the solution in space and time. Both simulations and the application to EEG data of a Median Nerve stimulation experiment yield encouraging results. Further comparative studies have to be carried out to evaluate the application of time/space regularization of the inward continuation problem in EEG

Biomimetic Strategy To Reversibly Trigger Functionality of Catalytic Nanocompartments by the Insertion of pH-Responsive Biovalves

We describe an innovative strategy to generate catalytic compartments with triggered functionality at the nanoscale level by combining pH-reversible biovalves and enzyme-loaded synthetic compartments. The biovalve has been engineered by the attachment of stimuli-responsive peptides to a genetically modified channel porin, enabling a reversible change of the molecular flow through the pores of the porin in response to a pH change in the local environment. The biovalve functionality triggers the reaction inside the cavity of the enzyme-loaded compartments by switching the in situ activity of the enzymes on/off based on a reversible change of the permeability of the membrane, which blocks or allows the passage of substrates and products. The complex functionality of our catalytic compartments is based on the preservation of the integrity of the compartments to protect encapsulated enzymes. An increase of the in situ activity compared to that of the free enzyme and a reversible on/off switch of the activity upon the presence of a specific stimulus is achieved. This strategy provides straightforward solutions for the development of catalytic nanocompartments efficiently producing desired molecules in a controlled, stimuli-responsive manner with high potential in areas, such as medicine, analytical chemistry, and catalysis

A frequency-tunable nanomembrane mechanical oscillator with embedded quantum dots

Hybrid systems consisting of a quantum emitter coupled to a mechanical oscillator are receiving increasing attention for fundamental science and potential applications in quantum technologies. In contrast to most of the presented works, in which the oscillator eigenfrequencies are irreversibly determined by the fabrication process, we present here a simple approach to obtain frequency-tunable mechanical resonators based on suspended nanomembranes. The method relies on a micromachined piezoelectric actuator, which we use both to drive resonant oscillations of a suspended Ga(Al)As membrane with embedded quantum dots and to fine tune their mechanical eigenfrequencies. Specifically, we excite oscillations with frequencies of at least 60 MHz by applying an AC voltage to the actuator and tune the eigenfrequencies by at least 25 times their linewidth by continuously varying the elastic stress state in the membranes through a DC voltage. The light emitted by optically excited quantum dots is used as sensitive local strain gauge to monitor the oscillation frequency and amplitude. We expect that our method has the potential to be applicable to other optomechanical systems based on dielectric and semiconductor membranes possibly operating in the quantum regime.Comment: 17 pages, 4 figure

Soil microbial biodiversity promotes crop productivity and agro-ecosystem functioning in experimental microcosms

Soil biota contribute substantially to multiple ecosystem functions that are key for geochemical cycles and plant performance. However, soil biodiversity is currently threatened by land-use intensification, and a mechanistic understanding of how soil biodiversity loss interacts with the myriad of intensification elements (e.g., the application of chemical fertilizers) is still unresolved. Here we experimentally simplified soil biological communities in microcosms to test whether changes in the soil microbiome influenced soil multifunctionality including crop productivity (leek, Allium porrum). Additionally, half of microcosms were fertilized to further explore how different levels of soil biodiversity interact with nutrient additions. Our experimental manipulation achieved a significant reduction of soil alpha-diversity (45.9 % reduction in bacterial richness, 82.9 % reduction in eukaryote richness) and resulted in the complete removal of key taxa (i.e., arbuscular mycorrhizal fungi). Soil community simplification led to an overall decrease in ecosystem multifunctionality; particularly, plant productivity and soil nutrient retention capacity were reduced with reduced levels of soil biodiversity. Ecosystem multifunctionality was positively correlated with soil biodiversity (R = 0.79). Mineral fertilizer application had little effect on multifunctionality compared to soil biodiversity reduction, but it reduced leek nitrogen uptake from decomposing litter by 38.8 %. This suggests that natural processes and organic nitrogen acquisition are impaired by fertilization. Random forest analyses revealed a few members of protists (i.e., Paraflabellula), Actinobacteria (i.e., Micolunatus), and Firmicutes (i.e., Bacillus) as indicators of ecosystem multifunctionality. Our results suggest that preserving the diversity of soil bacterial and eukaryotic communities within agroecosystems is crucial to ensure the provisioning of multiple ecosystem functions, particularly those directly related to essential ecosystem services such as food provision

Diversity of archaea and niche preferences among putative ammonia-oxidizing Nitrososphaeria dominating across European arable soils

Archaeal communities in arable soils are dominated by Nitrososphaeria, a class within Thaumarchaeota comprising all known ammonia-oxidizing archaea (AOA). AOA are key players in the nitrogen cycle and defining their niche specialization can help predicting effects of environmental change on these communities. However, hierarchical effects of environmental filters on AOA and the delineation of niche preferences of nitrososphaerial lineages remain poorly understood. We used phylogenetic information at fine scale and machine learning approaches to identify climatic, edaphic and geomorphological drivers of Nitrososphaeria and other archaea along a 3000 km European gradient. Only limited insights into the ecology of the low-abundant archaeal classes could be inferred, but our analyses underlined the multifactorial nature of niche differentiation within Nitrososphaeria. Mean annual temperature, C:N ratio and pH were the best predictors of their diversity, evenness and distribution. Thresholds in the predictions could be defined for C:N ratio and cation exchange capacity. Furthermore, multiple, independent and recent specializations to soil pH were detected in the Nitrososphaeria phylogeny. The coexistence of widespread ecophysiological differences between closely related soil Nitrososphaeria highlights that their ecology is best studied at fine phylogenetic scale

The impact of agricultural management on soil aggregation and carbon storage is regulated by climatic thresholds across a 3000 km European gradient

Organic carbon and aggregate stability are key features of soil quality and are important to consider when evaluating the potential of agricultural soils as carbon sinks. However, we lack a comprehensive understanding of how soil organic carbon (SOC) and aggregate stability respond to agricultural management across wide environmental gradients. Here, we assessed the impact of climatic factors, soil properties and agricultural management (including land use, crop cover, crop diversity, organic fertilization, and management intensity) on SOC and the mean weight diameter of soil aggregates, commonly used as an indicator for soil aggregate stability, across a 3000 km European gradient. Soil aggregate stability (-56%) and SOC stocks (-35%) in the topsoil (20 cm) were lower in croplands compared with neighboring grassland sites (uncropped sites with perennial vegetation and little or no external inputs). Land use and aridity were strong drivers of soil aggregation explaining 33% and 20% of the variation, respectively. SOC stocks were best explained by calcium content (20% of explained variation) followed by aridity (15%) and mean annual temperature (10%). We also found a threshold-like pattern for SOC stocks and aggregate stability in response to aridity, with lower values at sites with higher aridity. The impact of crop management on aggregate stability and SOC stocks appeared to be regulated by these thresholds, with more pronounced positive effects of crop diversity and more severe negative effects of crop management intensity in nondryland compared with dryland regions. We link the higher sensitivity of SOC stocks and aggregate stability in nondryland regions to a higher climatic potential for aggregate-mediated SOC stabilization. The presented findings are relevant for improving predictions of management effects on soil structure and C storage and highlight the need for site-specific agri-environmental policies to improve soil quality and C sequestration

The impact of agricultural management on soil aggregation and carbon storage is regulated by climatic thresholds across a 3000 km European gradient

Organic carbon and aggregate stability are key features of soil quality and are important to consider when evaluating the potential of agricultural soils as carbon sinks. However, we lack a comprehensive understanding of how soil organic carbon (SOC) and aggregate stability respond to agricultural management across wide environmental gradients. Here, we assessed the impact of climatic factors, soil properties and agricultural management (including land use, crop cover, crop diversity, organic fertilization, and management intensity) on SOC and the mean weight diameter of soil aggregates, commonly used as an indicator for soil aggregate stability, across a 3000 km European gradient. Soil aggregate stability (-56%) and SOC stocks (-35%) in the topsoil (20 cm) were lower in croplands compared with neighboring grassland sites (uncropped sites with perennial vegetation and little or no external inputs). Land use and aridity were strong drivers of soil aggregation explaining 33% and 20% of the variation, respectively. SOC stocks were best explained by calcium content (20% of explained variation) followed by aridity (15%) and mean annual temperature (10%). We also found a threshold-like pattern for SOC stocks and aggregate stability in response to aridity, with lower values at sites with higher aridity. The impact of crop management on aggregate stability and SOC stocks appeared to be regulated by these thresholds, with more pronounced positive effects of crop diversity and more severe negative effects of crop management intensity in nondryland compared with dryland regions. We link the higher sensitivity of SOC stocks and aggregate stability in nondryland regions to a higher climatic potential for aggregate-mediated SOC stabilization. The presented findings are relevant for improving predictions of management effects on soil structure and C storage and highlight the need for site-specific agri-environmental policies to improve soil quality and C sequestration