Extracting Information from the Power Spectrum of Synaptic Noise

In cortical neurons, synaptic "noise" is caused by the nearly random release of thousands of synapses. Few methods are presently available to analyze synaptic noise and deduce properties of the underlying synaptic inputs. We focus here on the power spectral density (PSD) of several models of synaptic noise. We examine different classes of analytically solvable kinetic models for synaptic currents, such as the "delta kinetic models," which use Dirac delta functions to represent the activation of the ion channel. We first show that, for this class of kinetic models, one can obtain an analytic expression for the PSD of the total synaptic conductance and derive equivalent stochastic models with only a few variables. This yields a method for constraining models of synaptic currents by analyzing voltage-clamp recordings of synaptic noise. Second, we show that a similar approach can be followed for the PSD of the the membrane potential (Vm) through an effective-leak approximation. Third, we show that this approach is also valid for inputs distributed in dendrites. In this case, the frequency scaling of the Vm PSD is preserved, suggesting that this approach may be applied to intracellular recordings of real neurons. In conclusion, using simple mathematical tools, we show that Vm recordings can be used to constrain kinetic models of synaptic currents, as well as to estimate equivalent stochastic models. This approach, therefore, provides a direct link between intracellular recordings in vivo and the design of models consistent with the dynamics and spectral structure of synaptic noise.     

Initial effects of a petroleum operation on Amazonian birds: terrestrial insectivores retreat

Impacts of petroleum activities on birds in the Amazonian forest of Yasuní National Park and the Huaorani Territory, Ecuador, were evaluated using data from 32 standardized 1-day surveys of twenty one 2-ha sites, spread out over 90 km, located at four different distances (0, 0.5, 1.5, and 4.5 km) into floristically diverse, primary, terra firme forest (240–320 m elev.), except one that was in 6-year-old secondary forest. Width of deforestation for roads was 25 m. The 263 species, identified via sight, sound, and mist-netting (4 nets) between 5:45 and 13:30 on days without heavy or constant rain, were grouped into 14 foraging guilds. Discriminant Function Analysis achieved complete separation of the 10 surveys adjacent to roads from the 22 surveys > 0.3 km into the forest, based on species richness per guild. Terrestrial insectivores contributed by far the most (76%) to this separation, and were the only guild to show a significant difference in the average number of species registered between the 6-edge sites and the 15 interior sites (Mann–Whitney U = 4, P = 0.001). Machinery noise seems to particularly affect this guild.     

Do neocortical pyramidal neurons display stochastic resonance?

Neocortical pyramidal neurons in vivo are subject to an intense synaptic background activity that has a significant impact on various electrophysiological properties and dendritic integration. Using detailed biophysical models of a morphologically reconstructed neocortical pyramidal neuron, in which synaptic background activity was simulated according to recent measurements in cat parietal cortex in vivo, we show that the responsiveness of the cell to additional periodic subthreshold stimuli can be significantly enhanced through mechanisms similar to stochastic resonance. We compare several paradigms leading to stochastic resonance-like behavior, such as varying the strength or the correlation in the background activity. A new type of resonance-like behavior was obtained when the correlation was varied, in which case the responsiveness is sensitive to the statistics rather than the strength of the noise. We suggest that this type of resonance may be relevant to information processing in the cerebral cortex.     

Low frequency noise enhances cortisol among noise sensitive subjects during work performance

Salivary free cortisol concentration, rated stress and annoyance were determined in 32 subjects before, during and after carrying out a battery of performance tasks for 2 hours during exposure to ventilation noise, with dominant low frequencies (low frequency noise) or a flat frequency spectrum (reference noise). Both noises had a level of 40 dBA. All subjects were studied on two occasions and were exposed to both noises in strict rotation. Subjects were categorised as high- or low-sensitive to noise in general and low frequency noise in particular on the basis of questionnaires. Cortisol concentrations during the task were not significantly modulated by the noises or related to noise sensitivity alone. The normal circadian decline in cortisol concentration was however significantly attenuated in subjects high-sensitive to noise in general, when they were exposed to the low frequency noise. This noise was rated as more annoying and more disruptive to working capacity than the reference noise. The study showed physiological evidence of increased stress related to noise sensitivity and noise exposure during work. This is the first study to demonstrate an effect of moderate levels of noise on neuroendocrine activity. The impact of long-term exposure to moderate noise levels, and particularly low frequency noise, in the workplace deserves further investigation.     

A technique for estimating maximum harvesting effort in a stochastic fishery model

Exploitation of biological resources and the harvest of population species are commonly practiced in fisheries, forestry and wild life management. Estimation of maximum harvesting effort has a great impact on the economics of fisheries and other bio-resources. The present paper deals with the problem of a bioeconomic fishery model under environmental variability. A technique for finding the maximum harvesting effort in fluctuating environment has been developed in a two-species competitive system, which shows that under realistic environmental variability the maximum harvesting effort is less than what is estimated in the deterministic model. This method also enables us to find out the safe regions in the parametric space for which the chance of extinction of the species is minimized. A real life fishery problem has been considered to obtain the inaccessible parameters of the system in a systematic way. Such studies may help resource managers to get an idea for controlling the system.     

蛋白质结构确定领域中的几种矩阵填充算法的对比评估

目的 目前,如何从核磁共振(nuclear magnetic resonance,NMR)光谱实验中准确地确定蛋白质的三维结构是生物物理学中的一个热门课题,因为蛋白质是生物体的重要组成成分,了解蛋白质的空间结构对研究其功能至关重要,然而由于实验数据的严重缺乏使其成为一个很大的挑战。方法 在本文中,通过恢复距离矩阵的矩阵填充(matrix completion,MC)算法来解决蛋白质结构确定问题。首先,初始距离矩阵模型被建立,由于实验数据的缺乏,此时的初始距离矩阵为不完整矩阵,随后通过MC算法恢复初始距离矩阵的缺失数据,从而获得整个蛋白质三维结构。为了进一步测试算法的性能,本文选取了4种不同拓扑结构的蛋白质和6种现有的MC算法进行了测试,探究了算法在不同的采样率以及不同程度噪声的情况下算法的恢复效果。结果 通过分析均方根偏差(root-mean-square deviation,RMSD)和计算时间这两个重要指标的平均值及标准差评估了算法的性能,结果显示当采样率和噪声因子控制在一定范围内时,RMSD值和标准差都能达到很小的值。另外本文更加具体地比较了不同算法的特点和优势,在精确采样情况下...     

能谱CT优化胃肿瘤扫描辐射剂量对肾上腺嗜铬细胞瘤的诊断价值

目的:探讨能谱CT优化胃肿瘤扫描辐射剂量对肾上腺嗜铬细胞瘤的诊断价值。方法:采用回顾性、抽样、随机研究方法选择2012年9月到2017年2月在我院诊治的肾上腺嗜铬细胞瘤患者59例作为研究对象,所有患者都给予常规CT扫描与能谱CT优化胃肿瘤扫描,记录和比较辐射剂量与图像质量。结果:所有病例包膜均完整,边缘清楚,肿瘤内见单发或多发低密度区,肿瘤实质区呈不均匀显著强化。常规CT与能谱CT的图像质量主观评分分别为3.89±0.45分和4.54±0.34分;常规CT与能谱CT图像的胃肿瘤CT值分别为31.94±6.39HU和35.29±5.19HU,对比都有显著差异(P0.05)。能谱CT图像的膀胱和皮下脂肪图像噪声值都显著低于常规CT图像,对比差异都有统计学意义(P0.05);能谱CT扫描的CTDIvol和DLP分别为12.39±3.48mGy和624.10±39.19mGy.cm,都显著低于常规CT扫描的14.09±4.13mGy和653.92±56.29mGy.cm(P0.05)。结论:能谱CT优化胃肿瘤扫描在肾上腺嗜铬细胞瘤诊断中的应用能有效减少辐射剂量与图像噪声,提高图像CT值与主观质量,临床应用价值更高。     

Comparing environmental and genetic variance as adaptive response to fluctuating selection

Phenotypic variation within populations has two sources: genetic variation and environmental variation. Here, we investigate the coevolution of these two components under fluctuating selection. Our analysis is based on the lottery model in which genetic polymorphism can be maintained by negative frequency-dependent selection, whereas environmental variation can be favored due to bet-hedging. In our model, phenotypes are characterized by a quantitative trait under stabilizing selection with the optimal phenotype fluctuating in time. Genotypes are characterized by their phenotypic offspring distribution, which is assumed to be Gaussian with heritable variation for its mean and variance. Polymorphism in the mean corresponds to genetic variance while the width of the offspring distribution corresponds to environmental variance. We show that increased environmental variance is favored whenever fluctuations in the selective optima are sufficiently strong. Given the environmental variance has evolved to its optimum, genetic polymorphism can still emerge if the distribution of selective optima is sufficiently asymmetric or leptokurtic. Polymorphism evolves in a diagonal direction in trait space: one type becomes a canalized specialist for the more common ecological conditions and the other type a de-canalized bet-hedger thriving on the less-common conditions. All results are based on analytical approximations, complemented by individual-based simulations.