A fast and reliable method for simultaneous waveform, amplitude and latency estimation of single-trial EEG/MEG data

The amplitude and latency of single-trial EEG/MEG signals may provide valuable information concerning human brain functioning. In this article we propose a new method to reliably estimate single-trial amplitude and latency of EEG/MEG signals. The advantages of the method are fourfold. First, no a-priori specified template function is required. Second, the method allows for multiple signals that may vary independently in amplitude and/or latency. Third, the method is less sensitive to noise as it models data with a parsimonious set of basis functions. Finally, the method is very fast since it is based on an iterative linear least squares algorithm. A simulation study shows that the method yields reliable estimates under different levels of latency variation and signal-to-noise ratio?s. Furthermore, it shows that the existence of multiple signals can be correctly determined. An application to empirical data from a choice reaction time study indicates that the method describes these data accurately.     

Leaf and stem economics spectra drive diversity of functional plant traits in a dynamic global vegetation model

Functional diversity is critical for ecosystem dynamics, stability and productivity. However, dynamic global vegetation models (DGVMs) which are increasingly used to simulate ecosystem functions under global change, condense functional diversity to plant functional types (PFTs) with constant parameters. Here, we develop an individual‐ and trait‐based version of the DGVM LPJmL (Lund‐Potsdam‐Jena managed Land) called LPJmL‐ flexible individual traits (LPJmL‐FIT) with flexible individual traits) which we apply to generate plant trait maps for the Amazon basin. LPJmL‐FIT incorporates empirical ranges of five traits of tropical trees extracted from the TRY global plant trait database, namely specific leaf area (SLA), leaf longevity (LL), leaf nitrogen content (N_area), the maximum carboxylation rate of Rubisco per leaf area (), and wood density (WD). To scale the individual growth performance of trees, the leaf traits are linked by trade‐offs based on the leaf economics spectrum, whereas wood density is linked to tree mortality. No preselection of growth strategies is taking place, because individuals with unique trait combinations are uniformly distributed at tree establishment. We validate the modeled trait distributions by empirical trait data and the modeled biomass by a remote sensing product along a climatic gradient. Including trait variability and trade‐offs successfully predicts natural trait distributions and achieves a more realistic representation of functional diversity at the local to regional scale. As sites of high climatic variability, the fringes of the Amazon promote trait divergence and the coexistence of multiple tree growth strategies, while lower plant trait diversity is found in the species‐rich center of the region with relatively low climatic variability. LPJmL‐FIT enables to test hypotheses on the effects of functional biodiversity on ecosystem functioning and to apply the DGVM to current challenges in ecosystem management from local to global scales, that is, deforestation and climate change effects.     

Diversity of Tropical Tree Seedling Responses to Drought

Drought is an important seedling mortality agent in dry and moist tropical forests, and more severe and frequent droughts are predicted in the future. The effect of drought on leaf gas exchange and seedling survival was tested in a dry-down experiment with four tree species from dry and moist forests in Bolivia. Seedlings were droughted and wilting stage and gas exchange were monitored. Drought led to a gradual reduction of photosynthesis and stomatal conductance over time, whereas respiration and photosynthetic water-use efficiency initially increased with drought and then declined. Seedlings gradually went through the different wilting stages, until they eventually died, but the trajectory differed for the four species. The strong relationship between wilting stage and photosynthesis means that simple field observations can provide valuable information on plant physiological performance. Three different drought strategies were identified. Dry forest species Ceiba samauma shed its leaves and survived. The moist forest species Cariniana ianeirensis postponed drought stress by having low rates of transpiration and high water-use efficiency. Dry forest Astronium urundeuva and moist forest Triplaris americana followed an opportunistic strategy; they are early successional species that can quickly grow to maturity but periodic drought can be lethal. Strikingly, dry and moist forest species did not differ clearly in their drought tolerance strategies.     

Growth-Factor-Driven Rescue to Receptor Tyrosine Kinase (RTK) Inhibitors through Akt and Erk Phosphorylation in Pediatric Low Grade Astrocytoma and Ependymoma

Up to now, several clinical studies have been started investigating the relevance of receptor tyrosine kinase (RTK) inhibitors upon progression free survival in various pediatric brain tumors. However, single targeted kinase inhibition failed, possibly due to tumor resistance mechanisms. The present study will extend our previous observations that vascular endothelial growth factor receptor (VEGFR)-2, platelet derived growth factor receptor (PDGFR)β, Src, the epidermal growth factor receptor (ErbB) family, and hepatocyte growth factor receptor (HGFR/cMet) are potentially drugable targets in pediatric low grade astrocytoma and ependymoma with investigations concerning growth-factor-driven rescue. This was investigated in pediatric low grade astrocytoma and ependymoma cell lines treated with receptor tyrosine kinase (RTK) inhibitors e.g. sorafenib, dasatinib, canertinib and crizotinib. Flow cytometry analyses showed high percentage of cells expressing VEGFR-1, fibroblast growth factor receptor (FGFR)-1, ErbB1/EGFR, HGFR and recepteur d’origine nantais (RON) (respectively 52-77%, 34-51%, 63-90%, 83-98%, 65-95%). Their respective inhibitors induced decrease of cell viability, measured with WST-1 cell viability assays. At least this was partially due to increased apoptotic levels measured by Annexin V/Propidium Iodide apoptosis assays. EGF, HGF and FGF, which are normally expressed in brain (tumor) tissue, showed to be effective rescue inducing growth factors resulting in increased cell survival especially during treatment with dasatinib (complete rescue) or sorafenib (partial rescue). Growth-factor-driven rescue was less prominent when canertinib or crizotinib were used. Rescue was underscored by significantly activating downstream Akt and/or Erk phosphorylation and increased tumor cell migration. Combination treatment showed to be able to overcome the growth-factor-driven rescue. In conclusion, our study highlights the extensive importance of environmentally present growth factors in developing tumor escape towards RTK inhibitors in pediatric low grade astrocytoma and ependymoma. It is of great interest to anticipate upon these results for the design of new therapeutic trials with RTK inhibitors in these pediatric brain tumors.     

Biodiversity in species,traits, and structure determines carbon stocks and uptake in tropical forests

Impacts of climate change require that society urgently develops ways to reduce amounts of carbon in the atmosphere. Tropical forests present an important opportunity, as they take up and store large amounts of carbon. It is often suggested that forests with high biodiversity have large stocks and high rates of carbon uptake. Evidence is, however, scattered across geographic areas and scales, and it remains unclear whether biodiversity is just a co‐benefit or also a requirement for the maintenance of carbon stocks and uptake. Here, we perform a quantitative review of empirical studies that analyzed the relationships between plant biodiversity attributes and carbon stocks and carbon uptake in tropical forests. Our results show that biodiversity attributes related to species, traits or structure significantly affect carbon stocks or uptake in 64% of the evaluated relationships. Average vegetation attributes (community‐mean traits and structural attributes) are more important for carbon stocks, whereas variability in vegetation attributes (i.e., taxonomic diversity) is important for both carbon stocks and uptake. Thus, different attributes of biodiversity have complementary effects on carbon stocks and uptake. These biodiversity effects tend to be more often significant in mature forests at broad spatial scales than in disturbed forests at local spatial scales. Biodiversity effects are also more often significant when confounding variables are not included in the analyses, highlighting the importance of performing a comprehensive analysis that adequately accounts for environmental drivers. In summary, biodiversity is not only a co‐benefit, but also a requirement for short‐ and long‐term maintenance of carbon stocks and enhancement of uptake. Climate change policies should therefore include the maintenance of multiple attributes of biodiversity as an essential requirement to achieve long‐term climate change mitigation goals.     

Making Large-Scale Networks from fMRI Data

Pairwise correlations are currently a popular way to estimate a large-scale network (> 1000 nodes) from functional magnetic resonance imaging data. However, this approach generally results in a poor representation of the true underlying network. The reason is that pairwise correlations cannot distinguish between direct and indirect connectivity. As a result, pairwise correlation networks can lead to fallacious conclusions; for example, one may conclude that a network is a small-world when it is not. In a simulation study and an application to resting-state fMRI data, we compare the performance of pairwise correlations in large-scale networks (2000 nodes) against three other methods that are designed to filter out indirect connections. Recovery methods are evaluated in four simulated network topologies (small world or not, scale-free or not) in scenarios where the number of observations is very small compared to the number of nodes. Simulations clearly show that pairwise correlation networks are fragmented into separate unconnected components with excessive connectedness within components. This often leads to erroneous estimates of network metrics, like small-world structures or low betweenness centrality, and produces too many low-degree nodes. We conclude that using partial correlations, informed by a sparseness penalty, results in more accurate networks and corresponding metrics than pairwise correlation networks. However, even with these methods, the presence of hubs in the generating network can be problematic if the number of observations is too small. Additionally, we show for resting-state fMRI that partial correlations are more robust than correlations to different parcellation sets and to different lengths of time-series.     

Book reviews

Book reviewed in this article: A. V. DOLMATOVA et N. A. DEMINA: Les Phlébotomes (Phlebotominae) et les maladies qu'ils transmettent. Traduction française: A. Kobylansky ANONYMUS: La lutte biologique en forét. T. N. ANANTHAKRISHNAN: Indian Thysanoptera R. Fritsche , E. Karl , W. Lehman & G. Proesler : Tierische Vektoren pftanzenpathogener Viren.     

Pathways, mechanisms and predictability of vegetation change during tropical dry forest succession

The development of forest succession theory has been based on studies in temperate and tropical wet forests. As rates and pathways of succession vary with the environment, advances in successional theory and study approaches are challenged by controversies derived from such variation and by the scarcity of studies in other ecosystems. During five years, we studied development pathways and dynamics in a chronosequence spanning from very early to late successional stages (ca. 1–60 years) in a tropical dry forest of Mexico. We (1) contrasted dynamic pathways of change in structure, diversity, and species composition with static, chronosequence-based trends, (2) examined how structure and successional dynamics of guilds of trees shape community change, and (3) assessed the predictability of succession in this system. Forest diversity and structure increased with time but tree density stabilized early in succession. Dynamic pathways matched chronosequence trends. Succession consisted of two tree-dominated phases characterized by the development and dynamics of a pioneer and a mature forest species guild, respectively. Pioneer species dominated early recruitment (until ca. 10 years after abandonment), and declined before slower growing mature-forest species became dominant or reached maximum development rates (after 40–45 years). Pioneers promoted their replacement early in succession, while mature-forest species recruited and grew constantly throughout the process, with their lowest mortality coinciding with the peak of pioneer abundance. In contrast to prevailing stochastic views, we observed an orderly, community driven series of changes in this dry forest secondary succession. Chronosequences thus represent a valuable approach for revealing system-specific successional pathways, formulating hypotheses on causes and mechanisms and, in combination with repeated sampling, evaluating the effects of vegetation dynamics in pathway variation.