Modeling sparse connectivity between underlying brain sources for EEG/MEG

We propose a novel technique to assess functional brain connectivity in EEG/MEG signals. Our method, called Sparsely-Connected Sources Analysis (SCSA), can overcome the problem of volume conduction by modeling neural data innovatively with the following ingredients: (a) the EEG is assumed to be a linear mixture of correlated sources following a multivariate autoregressive (MVAR) model, (b) the demixing is estimated jointly with the source MVAR parameters, (c) overfitting is avoided by using the Group Lasso penalty. This approach allows to extract the appropriate level cross-talk between the extracted sources and in this manner we obtain a sparse data-driven model of functional connectivity. We demonstrate the usefulness of SCSA with simulated data, and compare to a number of existing algorithms with excellent results.Comment: 9 pages, 6 figure

How to Explain Individual Classification Decisions

After building a classifier with modern tools of machine learning we typically have a black box at hand that is able to predict well for unseen data. Thus, we get an answer to the question what is the most likely label of a given unseen data point. However, most methods will provide no answer why the model predicted the particular label for a single instance and what features were most influential for that particular instance. The only method that is currently able to provide such explanations are decision trees. This paper proposes a procedure which (based on a set of assumptions) allows to explain the decisions of any classification method.Comment: 31 pages, 14 figure

Robust Statistical Detection of Power-Law Cross-Correlation

We show that widely used approaches in statistical physics incorrectly indicate the existence of power-law cross-correlations between financial stock market fluctuations measured over several years and the neuronal activity of the human brain lasting for only a few minutes. While such cross-correlations are nonsensical, no current methodology allows them to be reliably discarded, leaving researchers at greater risk when the spurious nature of cross- correlations is not clear from the unrelated origin of the time series and rather requires careful statistical estimation. Here we propose a theory and method (PLCC-test) which allows us to rigorously and robustly test for power- law cross-correlations, correctly detecting genuine and discarding spurious cross-correlations, thus establishing meaningful relationships between processes in complex physical systems. Our method reveals for the first time the presence of power-law cross-correlations between amplitudes of the alpha and beta frequency ranges of the human electroencephalogram

Contribution of Particulate and Mineral-Associated Organic Matter to Potential Denitrification of Agricultural Soils

Water-extractable organic carbon (WEOC) is considered as the most important carbon (C) source for denitrifying organisms, but the contribution of individual organic matter (OM) fractions (i.e., particulate (POM) and mineral-associated (MOM)) to its release and, thus, to denitrification remains unresolved. Here we tested short-time effects of POM and MOM on potential denitrification and estimated the contribution of POM- and MOM-derived WEOC to denitrification and CO2 production of three agricultural topsoils. Suspensions of bulk soils with and without addition of soil-derived POM or MOM were incubated for 24 h under anoxic conditions. Acetylene inhibition was used to determine the potential denitrification and respective product ratio at constant nitrate supply. Normalized to added OC, effects of POM on CO2 production, total denitrification, and its product ratios were much stronger than those of MOM. While the addition of OM generally increased the (N2O + N2)-N/CO2-C ratio, the N2O/(N2O + N2) ratio changed differently depending on the soil. Gas emissions and the respective shares of initial WEOC were then used to estimate the contribution of POM and MOM-derived WEOC to total CO2, N2O, and N2O + N2 production. Water-extractable OC derived from POM accounted for 53–85% of total denitrification and WEOC released from MOM accounted for 15–47%. Total gas emissions from bulk soils were partly over- or underestimated, mainly due to nonproportional responses of denitrification to the addition of individual OM fractions. Our findings show that MOM plays a role in providing organic substrates during denitrification but is generally less dominant than POM. We conclude that the denitrification potential of soils is not predictable based on the C distribution over POM and MOM alone. Instead, the source strength of POM and MOM for WEOC plus the WEOC’s quality turned out as the most decisive determinants of potential denitrification

Potential denitrification stimulated by water-soluble organic carbon from plant residues during initial decomposition

Denitrification usually takes place under anoxic conditions and over short periods of time, and depends on readily available nitrate and carbon sources. Variations in CO2 and N2O emissions associated with plant residues have mainly been explained by differences in their decomposability. A factor rarely considered so far is water-extractable organic matter (WEOM) released to the soil during residue decomposition. Here, we examined the potential effect of plant residues on denitrification with special emphasis on WEOM. A range of fresh and leached plant residues was characterized by elemental analyses, 13C-NMR spectroscopy, and extraction with ultrapure water. The obtained solutions were analyzed for the concentrations of organic carbon (OC) and organic nitrogen (ON), and by UV-VIS spectroscopy. To test the potential denitrification induced by plant residues or three different OM solutions, these carbon sources were added to soil suspensions and incubated for 24 h at 20 °C in the dark under anoxic conditions; KNO3 was added to ensure unlimited nitrate supply. Evolving N2O and CO2 were analyzed by gas chromatography, and acetylene inhibition was used to determine denitrification and its product ratio. The production of all gases, as well as the molar (N2O + N2)–N/CO2–C ratio, was directly related to the water-extractable OC (WEOC) content of the plant residues, and the WEOC increased with carboxylic/carbonyl C and decreasing OC/ON ratio of the plant residues. Incubation of OM solutions revealed that the molar (N2O + N2)–N/CO2–C ratio and share of N2O are influenced by the WEOM's chemical composition. In conclusion, our results emphasize the potential of WEOM in largely undecomposed plant residues to support short-term denitrification activity in a typical ˈhot spot–hot momentˈ situation

Algebraic Geometric Comparison of Probability Distributions

We propose a novel algebraic framework for treating probability distributions represented by their cumulants such as the mean and covariance matrix. As an example, we consider the unsupervised learning problem of finding the subspace on which several probability distributions agree. Instead of minimizing an objective function involving the estimated cumulants, we show that by treating the cumulants as elements of the polynomial ring we can directly solve the problem, at a lower computational cost and with higher accuracy. Moreover, the algebraic viewpoint on probability distributions allows us to invoke the theory of Algebraic Geometry, which we demonstrate in a compact proof for an identifiability criterion

Nanolithography Based on the Formation and Manipulation of Nanometer-Size Organic Liquid Menisci

In this work we form and manipulate nanometer-size liquid bridges of nonpolar organic solvents such as octane and 1-octene with a dynamic force microscope. These menisci have been used to confine chemical reactions that gave rise to the fabrication of nanometer-size structures.Peer reviewe

Differences in labile soil organic matter explain potential denitrification and denitrifying communities in a long-term fertilization experiment

Content and quality of organic matter (OM) may strongly affect the denitrification potential of soils. In particular, the impact of soil OM fractions of differing bioavailability (soluble, particulate, and mineral-associated OM) on denitrification remains unresolved. We determined the potential N2O and N2 as well as CO2 production for samples of a Haplic Chernozem from six treatment plots (control, mineral N and NP, farmyard manure - FYM, and FYM + mineral N or NP) of the Static Fertilization Experiment Bad Lauchstädt (Germany) as related to OM properties and denitrifier gene abundances. Soil OM was analyzed for bulk chemical composition (13C-CPMAS NMR spectroscopy) as well as water-extractable, particulate, and mineral-associated fractions. Soils receiving FYM had more total OM and larger portions of labile fractions such as particulate and water-extractable OM. Incubations were run under anoxic conditions without nitrate limitation for seven days at 25 °C in the dark to determine the denitrification potential (N2O and N2) using the acetylene inhibition technique. Abundances of nirS, nirK, and nosZ (I + II) genes were analyzed before and after incubation. The denitrification potential, defined as the combined amount of N released as N2O + N2 over the experimental period, was larger for plots receiving FYM (25.9–27.2 mg N kg−1) than pure mineral fertilization (17.1–19.2 mg N kg−1) or no fertilization (12.6 mg N kg−1). The CO2 and N2O production were well related and up to three-fold larger for FYM-receiving soils than under pure mineral fertilization. The N2 production differed significantly only between all manured and non-manured soils. Nitrogenous gas emissions related most closely to water-extractable organic carbon (WEOC), which again related well to free particulate OM. The larger contribution of N2 production in soils without FYM application, and thus, with less readily decomposable OM, coincided with decreasing abundances of nirS genes (NO2− reductase) and increasing abundances of genes indicating complete denitrifying organisms (nosZ I) during anoxic conditions. Limited OM sources, thus, favored a microbial community more efficient in resource use. This study suggests that WEOC, representing readily bioavailable OM, is a straightforward indicator of the denitrification potential of soils