第848回 千葉医学会例会・第7回 磯野外科例会 60.

<p>Shown are membrane voltages of the cortical pyramidal (top) and the thalamic relay population (bottom). During N3 the model shows ongoing slow oscillatory activity. In contrast to sleep stage N2, SOs cannot be identified as isolated events. Furthermore, there are no isolated spindle oscillations and spindle activity is time-locked to SOs. Parameters are given in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005022#pcbi.1005022.t002" target="_blank">Table 2</a>.</p

Potential of Airborne LiDAR Derived Vegetation Structure for the Prediction of Animal Species Richness at Mount Kilimanjaro

The monitoring of species and functional diversity is of increasing relevance for the development of strategies for the conservation and management of biodiversity. Therefore, reliable estimates of the performance of monitoring techniques across taxa become important. Using a unique dataset, this study investigates the potential of airborne LiDAR-derived variables characterizing vegetation structure as predictors for animal species richness at the southern slopes of Mount Kilimanjaro. To disentangle the structural LiDAR information from co-factors related to elevational vegetation zones, LiDAR-based models were compared to the predictive power of elevation models. 17 taxa and 4 feeding guilds were modeled and the standardized study design allowed for a comparison across the assemblages. Results show that most taxa (14) and feeding guilds (3) can be predicted best by elevation with normalized RMSE values but only for three of those taxa and two of those feeding guilds the difference to other models is significant. Generally, modeling performances between different models vary only slightly for each assemblage. For the remaining, structural information at most showed little additional contribution to the performance. In summary, LiDAR observations can be used for animal species prediction. However, the effort and cost of aerial surveys are not always in proportion with the prediction quality, especially when the species distribution follows zonal patterns, and elevation information yields similar results

Characterization of K-Complexes and Slow Wave Activity in a Neural Mass Model

NREM sleep is characterized by two hallmarks, namely K-complexes (KCs) during sleep stage N2 and cortical slow oscillations (SOs) during sleep stage N3. While the underlying dynamics on the neuronal level is well known and can be easily measured, the resulting behavior on the macroscopic population level remains unclear. On the basis of an extended neural mass model of the cortex, we suggest a new interpretation of the mechanisms responsible for the generation of KCs and SOs. As the cortex transitions from wake to deep sleep, in our model it approaches an oscillatory regime via a Hopf bifurcation. Importantly, there is a canard phenomenon arising from a homoclinic bifurcation, whose orbit determines the shape of large amplitude SOs. A KC corresponds to a single excursion along the homoclinic orbit, while SOs are noise-driven oscillations around a stable focus. The model generates both time series and spectra that strikingly resemble real electroencephalogram data and points out possible differences between the different stages of natural sleep

A Thalamocortical Neural Mass Model of the EEG during NREM Sleep and Its Response to Auditory Stimulation

Few models exist that accurately reproduce the complex rhythms of the thalamocortical system that are apparent in measured scalp EEG and at the same time, are suitable for large-scale simulations of brain activity. Here, we present a neural mass model of the thalamocortical system during natural non-REM sleep, which is able to generate fast sleep spindles (12–15 Hz), slow oscillations (<1 Hz) and K-complexes, as well as their distinct temporal relations, and response to auditory stimuli. We show that with the inclusion of detailed calcium currents, the thalamic neural mass model is able to generate different firing modes, and validate the model with EEG-data from a recent sleep study in humans, where closed-loop auditory stimulation was applied. The model output relates directly to the EEG, which makes it a useful basis to develop new stimulation protocols

Data from: Trait patterns of epiphytes compared to other plant life forms along a tropical elevation gradient

Compared to other plant life forms, epiphytes remain understudied. Understanding the responses of epiphytes to changing environmental conditions is necessary to predict changes in ecosystem functioning especially in subtropical and tropical regions. We investigated the functional traits of epiphytes along a large elevation gradient on Mount Kilimanjaro, Tanzania. We measured traits of co-occurring trees and terrestrial non-tree life forms, and compared changes in community-weighted means of traits (CWM) and trait spread, the range of observed trait values. We chose traits linked to growth and persistence: leaf area, specific leaf area, leaf dry matter content, stem specific density, plant height, leaf carbon, leaf nitrogen, and leaf phosphorus. For most traits, differences in community-weighted means between life forms exceeded differences within life forms along the elevation gradient. Many CWM showed linear changes with elevation, but no response and unimodal patterns were also frequent. This was best explained by temperature, or a combination of temperature with precipitation or humidity, indicating effects of these factors on the distribution of epiphytic and non-epiphytic species. Trait spread did not change with elevation in nearly half of the traits, but hump-shaped patterns were also common, probably a result of weaker environmental filtering in the gradient center. The magnitude of trait spread, i.e. the variability between species of the same life form within communities, was highest for terrestrial non-trees. Excluding ferns from the analyses lead to marked differences in trait patterns for epiphytes, as ferns made up 59 % of the epiphytic species, while playing a minor role in the other groups. The observed differences can be explained by a dichotomy in epiphytic life strategies, with tough-leaved xero-tolerant species on one side and succulent soft-leaved species on the other. However, the influence of phylogeny was lower than expected from the taxonomic composition of the three life form groups. Our results emphasize that environmental constraints act upon functional traits of epiphytes, trees and terrestrial non-trees. The differences in trait expressions, arguably adaptations of the different life forms, need to be taken into account in conservation contexts as well as when modeling the effects of global change on ecosystems

Plant traits mediate the effects of climate on phytophagous beetle diversity on Mt. Kilimanjaro

Patterns of insect diversity along elevational gradients are well described in ecology. However, it remains little tested how variation in the quantity, quality, and diversity of food resources influence these patterns. Here we analyzed the direct and indirect effects of climate, food quantity (estimated by net primary productivity), quality (variation in the specific leaf area index, leaf nitrogen to phosphorus and leaf carbon to nitrogen ratio), and food diversity (diversity of leaf traits) on the species richness of phytophagous beetles along the broad elevation and land use gradients of Mt. Kilimanjaro, Tanzania. We sampled beetles at 65 study sites located in both natural and anthropogenic habitats, ranging from 866 to 4,550 m asl. We used path analysis to unravel the direct and indirect effects of predictor variables on species richness. In total, 3,154 phytophagous beetles representing 19 families and 304 morphospecies were collected. We found that the species richness of phytophagous beetles was bimodally distributed along the elevation gradient with peaks at the lowest (˜866 m asl) and upper mid-elevations (˜3,200 m asl) and sharply declined at higher elevations. Path analysis revealed temperature- and climate-driven changes in primary productivity and leaf trait diversity to be the best predictors of changes in the species richness of phytophagous beetles. Species richness increased with increases in mean annual temperature, primary productivity, and with increases in the diversity of leaf traits of local ecosystems. Our study demonstrates that, apart from temperature, the quantity and diversity of food resources play a major role in shaping diversity gradients of phytophagous insects. Drivers of global change, leading to a change of leaf traits and causing reductions in plant diversity and productivity, may consequently reduce the diversity of herbivore assemblages

Relationships between abiotic environment, plant functional traits, and animal body size at Mount Kilimanjaro, Tanzania

The effect-response framework states that plant functional traits link the abiotic environment to ecosystem functioning. One ecosystem property is the body size of the animals living in the system, which is assumed to depend on temperature or resource availability, among others. For primary consumers, resource availability may directly be related to plant traits, while for secondary consumers the relationship is indirect. We used plant traits to describe resource availability along an elevational gradient on Mount Kilimanjaro, Tanzania. Using structural equation models, we determined the response of plant traits to changes in precipitation, temperature and disturbance with and assessed whether abiotic conditions or community-weighted means of plant traits are stronger predictors of the mean size of bees, moths, frugivorous birds, and insectivorous birds. Traits indicating tissue density and nutrient content strongly responded to variations in precipitation, temperature and disturbance. They had direct effects on pollination and fruit traits. However, the average body sizes of the animal groups considered could only be explained by temperature and habitat structure, not by plant traits. Our results demonstrate a strong link between traits and the abiotic environment, but suggest that temperature is the most relevant predictor of mean animal body size. Community-weighted means of plant traits and body sizes appear unsuitable to capture the complexity of plant-animal interactions

Comparison of human EEG with model output in regime N2.

<p>Qualitative comparison of (a) human EEG data of sleep stage N2 from electrode Cz with (b) the isolated cortical module in regime N2 (region IV in the bifurcation diagram in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003923#pcbi-1003923-g002" target="_blank">Figure 2</a>). The traces illustrate the medium-amplitude background oscillations and the stereotypical shape of spontaneous KCs at the EEG level. It may or may not have an initial bump followed by a large negative peak and a pronounced positive overshoot. The model-KC is noise induced and represents a single relaxation cycle. An evoked KC in the noise-free case is shown in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003923#pcbi-1003923-g004" target="_blank">Figure 4a</a>. Model output is excitatory membrane voltage <i>V_e</i>, and both time series are z-scored (Parameters as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003923#pcbi-1003923-t002" target="_blank">Table 2</a>).</p