Improved Mass Accuracy and Isotope Confirmation through Alignment of Ultrahigh-Resolution Mass Spectra of Complex Natural Mixtures.

Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is one of the state-of-the-art methods to analyze complex natural organic mixtures. The precision of detected masses is crucial for molecular formula attribution. Random errors can be reduced by averaging multiple measurements of the same mass, but because of limited availability of ultrahigh-resolution mass spectrometers, most studies cannot afford analyzing each sample multiple times. Here we show that random errors can be eliminated also by averaging mass spectral data from independent environmental samples. By averaging the spectra of 30 samples analyzed on our 15 T instrument we reach a mass precision comparable to a single spectrum of a 21 T instrument. We also show that it is possible to accurately and reproducibly determine isotope ratios with FT-ICR-MS. Intensity ratios of isotopologues were improved to a degree that measured deviations were within the range of natural isotope fractionation effects. In analogy to δ13C in environmental studies, we propose Δ13C as an analytical measure for isotope ratio deviances instead of widely employed C deviances. In conclusion, here we present a simple tool, extensible to Orbitrap-based mass spectrometers, for postdetection data processing that significantly improves mass accuracy and the precision of intensity ratios of isotopologues at no extra cost.

ICBM-OCEAN: Processing Ultrahigh-Resolution Mass Spectrometry Data of Complex Molecular Mixtures.

Untargeted molecular analyses of complex mixtures are relevant for many fields of research, including geochemistry, pharmacology, and medicine. Ultrahigh-resolution mass spectrometry is one of the most powerful tools in this context. The availability of open scripts and online tools for specific data processing steps such as noise removal or molecular formula assignment is growing, but an integrative tool where all crucial steps are reproducibly evaluated and documented is lacking. We developed a novel, server-based tool (ICBM-OCEAN, Institute for Chemistry and Biology of the Marine Environment, Oldenburg-complex molecular mixtures, evaluation & analysis) that integrates published and novel approaches for standardized processing of ultrahigh-resolution mass spectrometry data of complex molecular mixtures. Different from published approaches, we offer diagnostic and validation tools for all relevant steps. Among other features, we included objective and reproducible reduction of noise and systematic errors, spectra recalibration and alignment, and identification of likeliest molecular formulas. With 15 chemical elements, the tool offers high flexibility in formula attribution. Alignment of mass spectra among different samples prior to molecular formula assignment improves mass error and facilitates molecular formula confirmation with the help of isotopologues. The online tool and the detailed instruction manual are freely accessible at www.icbm.de/icbm-ocean.

Encephalography Connectivity on Sources in Male Nonsmokers after Nicotine Administration during the Resting State.

We present an encephalography (EEG) connectivity study where 30 healthy male nonsmokers were randomly allocated either to a nicotine group (14 subjects, 7 mg of transdermal nicotine) or to a placebo group. EEG activity was recorded in an eyes-open (EO) and eyes-closed (EC) condition before and after drug administration. This is a reanalysis of a previous dataset. Through a source reconstruction procedure, we extracted 13 time series representing 13 sources belonging to a resting-state network. Here, we conducted connectivity analysis (renormalized partial directed coherence; rPDC) on sources, focusing on the frequency range of 8.5-18.4 Hz, subdivided into 3 frequency bands (α1, α2, and ß1) with the hypothesis that an increase in vigilance would modulate connectivity. Furthermore, a phase-amplitude coupling (mean resultant vector length; VL) analysis, was performed investigating whether an increase of vigilance would modulate phase-amplitude coupling. In the VL analysis we estimated the coupling of the phases of 3 low frequencies (α1, α2, and ß1), respectively, with the amplitude of high-frequency oscillations (30-40 Hz, low γ). With rPDC we found that during the EC condition, nicotine decreased feedback connectivity (from the precentral gyrus to precuneus, angular gyrus, cuneus and superior occipital gyrus) at 10.5-12.4 Hz. The VL analysis showed nicotine-induced increases in coupling at 10.5-18.4 Hz in the precuneus, cuneus and superior occipital gyrus during the EC condition. During the EO condition, no significant results were found in connectivity or phase-amplitude coupling measures at any frequency range. In conclusion, the results suggest that nicotine potentially increases the level of vigilance in the EC condition.

Temperature-dependent stochastic dynamics of the Huber-Braun neuron model.

The response of a four-dimensional mammalian cold receptor model to different implementations of noise is studied across a wide temperature range. It is observed that for noisy activation kinetics, the parameter range decomposes into two regions in which the system reacts qualitatively completely different to small perturbations through noise, and these regions are separated by a homoclinic bifurcation. Noise implemented as an additional current yields a substantially different system response at low temperature values, while the response at high temperatures is comparable to activation-kinetic noise. We elucidate how this phenomenon can be understood in terms of state space dynamics and gives quantitative results on the statistics of interspike interval distributions across the relevant parameter range.

Phase locking below rate threshold in noisy model neurons.

The property of a neuron to phase-lock to an oscillatory stimulus before adapting its spike rate to the stimulus frequency plays an important role for the auditory system. We investigate under which conditions neurons exhibit this phase locking below rate threshold. To this end, we simulate neurons employing the widely used leaky integrate-and-fire (LIF) model. Tuning parameters, we can arrange either an irregular spontaneous or a tonic spiking mode. When the neuron is stimulated in both modes, a significant rise of vector strength prior to a noticeable change of the spike rate can be observed. Combining analytic reasoning with numerical simulations, we trace this observation back to a modulation of interspike intervals, which itself requires spikes to be only loosely coupled. We test the limits of this conception by simulating an LIF model with threshold fatigue, which generates pronounced anticorrelations between subsequent interspike intervals. In addition we evaluate the LIF response for harmonic stimuli of various frequencies and discuss the extension to more complex stimuli. It seems that phase locking below rate threshold occurs generically for all zero mean stimuli. Finally, we discuss our findings in the context of stimulus detection.

On the role of subthreshold currents in the Huber-Braun cold receptor model.

We study the role of the strength of subthreshold currents in a four-dimensional Hodgkin-Huxley-type model of mammalian cold receptors. Since a total diminution of subthreshold activity corresponds to a decomposition of the model into a slow, subthreshold, and a fast, spiking subsystem, we first elucidate their respective dynamics separately and draw conclusions about their role for the generation of different spiking patterns. These results motivate a numerical bifurcation analysis of the effect of varying the strength of subthreshold currents, which is done by varying a suitable control parameter. We work out the key mechanisms which can be attributed to subthreshold activity and furthermore elucidate the dynamical backbone of different activity patterns generated by this model.

Density-dependent growth in 'catch-and-wait' fisheries has implications for fisheries management and Marine Protected Areas.

Stock enhancement activities provide an opportunity to examine density-dependent suppression of population biomass which is a fundamental issue for resource management and design of no-take-zones. We document 'catch-and-wait' fisheries enhancement where all but the largest lobsters are thrown back, recapturing them later after they have grown to a larger size. The residency, rate of return, and potential negative density-dependent effects of this activity are described using a combination of tagging and v-notching and by relating spatial growth patterns to population density defined with Catch Per Unit Effort. The results successfully demonstrated the concept of catch-and-wait practices. However, a density-dependent suppression of growth (in body size) was observed in male lobsters. This demonstrates a mechanism to explain differences in lobster sizes previously observed across EU fishing grounds with different stock densities. This negative effect of density could also affect individual biomass production in marine reserve or no-take zones.

Sleep apnea: Tracking effects of a first session of CPAP therapy by means of Granger causality.

Connectivity between physiological networks is an issue of particular importance for understanding the complex interaction brain-heart. In the present study, this interaction was analyzed in polysomnography recordings of 28 patients diagnosed with obstructive sleep apnea (OSA) and compared with a group of 10 control subjects. Electroencephalography and electrocardiography signals from these polysomnography time series were characterized employing Granger causality computation to measure the directed connectivity among five brain waves and three spectral subbands of heart rate variability. Polysomnography data from OSA patients were recorded before and during a first session of continuous positive air pressure (CPAP) therapy in a split-night study. Results showed that CPAP therapy allowed the recovery of inner brain connectivities, mainly in subsystems involving the theta wave. In addition, differences between control and OSA patients were established in connections that involve lower frequency ranges of heart rate variability. This information can be potentially useful in the initial diagnosis of OSA, and determine the role of cardiac activity in sleep dynamics based on the use of three subbands of heart rate variability.

Thresholds for ecological responses to global change do not emerge from empirical data.

To understand ecosystem responses to anthropogenic global change, a prevailing framework is the definition of threshold levels of pressure, above which response magnitudes and their variances increase disproportionately. However, we lack systematic quantitative evidence as to whether empirical data allow definition of such thresholds. Here, we summarize 36 meta-analyses measuring more than 4,600 global change impacts on natural communities. We find that threshold transgressions were rarely detectable, either within or across meta-analyses. Instead, ecological responses were characterized mostly by progressively increasing magnitude and variance when pressure increased. Sensitivity analyses with modelled data revealed that minor variances in the response are sufficient to preclude the detection of thresholds from data, even if they are present. The simulations reinforced our contention that global change biology needs to abandon the general expectation that system properties allow defining thresholds as a way to manage nature under global change. Rather, highly variable responses, even under weak pressures, suggest that 'safe-operating spaces' are unlikely to be quantifiable.

Field-recorded data on habitat, density, growth and movement of Nephrops norvegicus.

The availability of growth data in N. norvegicus is important for management purposes due to a lack of aging criteria and the commercial importance of fisheries in this species. Growth varies as a function of stock density, hence comparisons of growth rates between stocks at known density is particularly valuable. Growth is also related to starting size in males, making raw data on size-specific growth rates more valuable. Internally injected passive tags allowed us to track the growth of male and female individuals over one or two years. The spatial position of tagged recaptures was recorded to measure site fidelity of tagged releases. A total of 3300 pots were fished and their spatial positions were recorded to enable Catch Per Unit Effort calculations. Similarly, spatially geo-referenced v-notching and notched recovery enables spatially gridded densities to be calculated. Finally, acoustic mapping was carried out both on and off the fishing ground and was ground-truthed with sedimentology from grabs at 22 stations. These data are useful for fisheries and macroecological studies.

Enhanced signal detectability in comodulated noise introduced by compression.

Many examples of natural noise show common amplitude modulations at different frequency regions. This kind of noise has been termed comodulated noise and is widely examined in hearing research, where an enhanced detectability of pure tones and narrow noise bands in comodulated noise compared to unmodulated noise is well known as the CMR or CDD effects, respectively. Here it is shown that only one signal processing step, a compressive nonlinearity motivated by the peripheral auditory system, is sufficient to explain a considerable contribution to these effects. Using an analytical approach, the influence of compression on the detectability of periodic and narrow band signals in the presence of unmodulated and comodulated noise is investigated. This theoretical treatment allows for identifying the mechanism leading to improved signal detection. The compressive nonlinearity constitutes an adaptive gain which selectively boosts a stimulus during time spans of inherently increased signal-to-noise ratio and attenuates it during time spans dominated by noise. On average, these time spans are more pronounced in stimuli with comodulated noise than with unmodulated noise, thus giving rise to the observed CMR and CDD effects.

Granger-causality maps of diffusion processes.

Granger causality is a statistical concept devised to reconstruct and quantify predictive information flow between stochastic processes. Although the general concept can be formulated model-free it is often considered in the framework of linear stochastic processes. Here we show how local linear model descriptions can be employed to extend Granger causality into the realm of nonlinear systems. This novel treatment results in maps that resolve Granger causality in regions of state space. Through examples we provide a proof of concept and illustrate the utility of these maps. Moreover, by integration we convert the local Granger causality into a global measure that yields a consistent picture for a global Ornstein-Uhlenbeck process. Finally, we recover invariance transformations known from the theory of autoregressive processes.

Finite-sample frequency distributions originating from an equiprobability distribution.

Given an equidistribution for probabilities p(i)=1/N, i=1, ..., N. What is the expected corresponding rank ordered frequency distribution f(i), i=1, ..., N, if an ensemble of M events is drawn?

Signal detection by means of phase coherence induced through phase resetting.

Detection and location of moving prey utilizing electrosense or mechanosense is a strategy commonly followed by animals which cannot rely on visual sense or hearing. In this paper we consider the possibility to detect the source of a localized stimulus that travels along a chain of detectors at constant speed. The detectors are autonomous oscillators whose frequencies have a given natural spread. The detection mechanism is based on phase coherence which is built up by phase resetting induced by the passing stimulus.

Oscillatory systems driven by noise: frequency and phase synchronization.

The phenomenon of effective phase synchronization in stochastic oscillatory systems can be quantified by an average frequency and a phase diffusion coefficient. A different approach to compute the noise-averaged frequency is put forward. The method is based on a threshold crossing rate pioneered by Rice. After the introduction of the Rice frequency for noisy systems we compare this quantifier with those obtained in the context of other phase concepts, such as the natural and the Hilbert phase, respectively. It is demonstrated that the average Rice frequency R typically supersedes the Hilbert frequency H, i.e. R > or = H. We investigate next the Rice frequency for the harmonic and the damped, bistable Kramers oscillator, both without and with external periodic driving. Exact and approximative analytic results are corroborated by numerical simulation results. Our results complement and extend previous findings for the case of noise-driven inertial systems.

How to decide whether small samples comply with an equidistribution.

The decision whether a measured distribution complies with an equidistribution is a central element of many biostatistical methods. High throughput differential expression measurements, for instance, necessitate to judge possible over-representation of genes. The reliability of this judgement, however, is strongly affected when rarely expressed genes are pooled. We propose a method that can be applied to frequency ranked distributions and that yields a simple but efficient criterion to assess the hypothesis of equiprobable expression levels. By applying our technique to surrogate data we exemplify how the decision criterion can differentiate between a true equidistribution and a triangular distribution. The distinction succeeds even for small sample sizes where standard tests of significance (e.g. chi(2)) fail. Our method will have a major impact on several problems of computational biology where rare events baffle a reliable assessment of frequency distributions. The program package is available upon request from the authors.

Non-linear EEG analyses predict non-response to rTMS treatment in major depressive disorder.

OBJECTIVE: Several linear electroencephalographic (EEG) measures at baseline have been demonstrated to be associated with treatment outcome after antidepressant treatment. In this study we investigated the added value of non-linear EEG metrics in the alpha band in predicting treatment outcome to repetitive transcranial magnetic stimulation (rTMS). METHODS: Subjects were 90 patients with major depressive disorder (MDD) and a group of 17 healthy controls (HC). MDD patients were treated with rTMS and psychotherapy for on average 21 sessions. Three non-linear EEG metrics (Lempel-Ziv Complexity (LZC); False Nearest Neighbors and Largest Lyapunov Exponent) were applied to the alpha band (7-13 Hz) for two 1-min epochs EEG and the association with treatment outcome was investigated. RESULTS: No differences were found between a subgroup of unmedicated MDD patients and the HC. Non-responders showed a significant decrease in LZC from minute 1 to minute 2, whereas the responders and HC showed an increase in LZC. CONCLUSIONS: There is no difference in EEG complexity between MDD and HC and the change in LZC across time demonstrated value in predicting outcome to rTMS. SIGNIFICANCE: This is the first study demonstrating utility of non-linear EEG metrics in predicting treatment outcome in MDD.

Classifying the motion of visual stimuli from the spike response of a population of retinal ganglion cells.

We present an analysis of the spike response of a retinal ganglion cell ensemble. The retina of a turtle was stimulated in vitro by moving light patterns. Its non-steady motion was specified by two features: changes of direction and changes of speed. The spike response of a ganglion cell population was recorded extracellularly with a multielectrode array and responding neurons were identified through spike sorting. Restricting further analysis to a time window of greatest firing activity, we selected a subset of cells with reliable firing patterns, excluding cells that were not selective to the stimulus. The reliability of a firing pattern was assessed on the single cell level in terms of two measures: temporal precision (jitter) of the first spike and the fraction of trials in which a spike was generated. We then condensed the spike response of the extracted group by merging the multivariate spike trains into a single spike train. Finally, we compared different coding hypotheses that are based on the timing of the first and the second spike of the population or the spike count in the preselected time window. We found that the second spike of the population significantly increases the classification efficiency beyond that of the first spike. Moreover, the combination of first plus second spike is comparably efficient as the combination of the first spike plus the spike count but allows for a classification that is much faster.

The role of the auditory periphery in comodulation detection difference and comodulation masking release.

Natural sounds often exhibit correlated amplitude modulations at different frequency regions, so-called comodulation. Therefore, the ear might be especially adapted to these kinds of sounds. Two effects have been related to the sensitivity of the auditory system to common modulations across frequency: comodulation detection difference (CDD) and comodulation masking release (CMR). Research on these effects has been done on the psychophysical and on the neurophysiological level in humans and other animals. Until now, models have focused only on one of the effects. In the present study, a simple model based on data from neuronal recordings obtained during CDD experiments with starlings is discussed. This model demonstrates that simple peripheral processing in the ear can go a substantial way to explaining psychophysical signal detection thresholds in response to CDD and CMR stimuli. Moreover, it is largely analytically tractable. The model is based on peripheral processing and incorporates the basic steps frequency filtering, envelope extraction, and compression. Signal detection is performed based on changes in the mean compressed envelope of the filtered stimulus. Comparing the results of the model with data from the literature, the scope of this unifying approach to CDD and CMR is discussed.