Slowness: an objective for spike-timing-dependent plasticity?

Our nervous system can efficiently recognize objects in spite of changes in contextual variables such as perspective or lighting conditions. Several lines of research have proposed that this ability for invariant recognition is learned by exploiting the fact that object identities typically vary more slowly in time than contextual variables or noise. Here, we study the question of how this "temporal stability" or "slowness" approach can be implemented within the limits of biologically realistic spike-based learning rules. We first show that slow feature analysis, an algorithm that is based on slowness, can be implemented in linear continuous model neurons by means of a modified Hebbian learning rule. This approach provides a link to the trace rule, which is another implementation of slowness learning. Then, we show analytically that for linear Poisson neurons, slowness learning can be implemented by spike-timing-dependent plasticity (STDP) with a specific learning window. By studying the learning dynamics of STDP, we show that for functional interpretations of STDP, it is not the learning window alone that is relevant but rather the convolution of the learning window with the postsynaptic potential. We then derive STDP learning windows that implement slow feature analysis and the "trace rule." The resulting learning windows are compatible with physiological data both in shape and timescale. Moreover, our analysis shows that the learning window can be split into two functionally different components that are sensitive to reversible and irreversible aspects of the input statistics, respectively. The theory indicates that irreversible input statistics are not in favor of stable weight distributions but may generate oscillatory weight dynamics. Our analysis offers a novel interpretation for the functional role of STDP in physiological neurons.     

生态系统服务与景观格局集成研究综述

生态系统服务是综合科学和政策应用的有效工具,可用于应对人类干扰下的景观和生态系统服务的快速退化等复杂生态环境问题。综述生态系统服务与景观格局集成的学科发展、基础理论和模型开发的进展与存在的问题,建立可用的集成建模框架,并提出知识集成的概念框架:1)在要素层,"政策-决策—景观—生态系统服务—社会经济系统"的跨学科知识反馈环是集成理论基础; 2)在模型层,结构化、多层次的集成模拟模型是核心方法; 3)在数据层,多源数据集成是模拟模型的数据基础。集成生态系统服务与景观格局为区域生态环境治理实践提供了科学参考,能更好地应对生态系统服务科学与应用的挑战。     

Input-dependent learning rule for the memory of spatiotemporal sequences in hippocampal network with theta phase precession

Theta phase precession in rat hippocampal place cells is hypothesized to contribute to memory encoding of running experience in the sense that it provides the ideal timing for synaptic plasticity and enables the asymmetric associative connections under the Hebbian learning rule with asymmetric time window (Yamaguchi 2003). When the sequence of place fields is considered as the episodic memory of running experience, a given spatial route should be accurately stored in spite of differing overlap extent among place fields and varying running velocity. Using a hippocampal network model with phase precession and the Hebbian learning rule with asymmetric time window, we investigate the memory encoding of place field sequences in a single traversal experience. Computer experiments show that place fields cannot be stored correctly until an input-dependent feature is introduced into the learning rule. These experiments further indicate that there exists an optimum value for the saturation level of synaptic plasticity and the speed of synaptic plasticity in the learning rule, which are correlated with, respectively, the overlap extent of place field sequence and the running velocity of animal during traversal. A comparison of these results with biological evidences shows good agreement and suggests that behavior-dependent regulation of the learning rule is necessary for memory encoding.     

Effects of static magnetic fields at the cellular level

There have been few studies on the effects of static magnetic fields at the cellular level, compared to those of extremely low frequency magnetic fields. Past studies have shown that a static magnetic field alone does not have a lethal effect on the basic properties of cell growth and survival under normal culture conditions, regardless of the magnetic density. Most but not all studies have also suggested that a static magnetic field has no effect on changes in cell growth rate. It has also been shown that cell cycle distribution is not influenced by extremely strong static magnetic fields (up to a maximum of 10 T). A further area of interest is whether static magnetic fields cause DNA damage, which can be evaluated by determination of the frequency of micronucleus formation. The presence or absence of such micronuclei can confirm whether a particular treatment damages cellular DNA. This method has been used to confirm that a static magnetic field alone has no such effect. However, the frequency of micronucleus formation increases significantly when certain treatments (e.g., X-irradiation) are given prior to exposure to a 10 T static magnetic field. It has also been reported that treatment with trace amounts of ferrous ions in the cell culture medium and exposure to a static magnetic field increases DNA damage, which is detected using the comet assay. In addition, many studies have found a strong magnetic field that can induce orientation phenomena in cell culture.     

Modularity and intra-floral integration in metameric organisms: plants are more than the sum of their parts

Within-individual variation in virtually every conceivable morphological and functional feature of reiterated structures is a pervasive feature of plant phenotypes. In particular, architectural effects, regular, repeatable patterns of intra-individual variation in form and function that are associated with position are nearly ubiquitous. Yet, flowers also are predicted to be highly integrated. For animal-pollinated plants, the coordination of multiple organs within each flower is required to achieve the complex functions of pollinator attraction and orientation, pollen donation and pollen receipt. To the extent that pollinators may select for multiple independent functions, phenotypic integration within flowers may also be modular. That is, subsets of floral structures may be integrated but vary independently of other subsets of structures that are themselves integrated. How can phenotypic integration and modularity be understood within the context of architectural effects? This essay reviews recent research on patterns of floral integration and modularity and explores the potential for spatial and temporal changes in the selective environment of individual flowers to result in positional variation in patterns of morphological integration.     

The 'right' size in nanobiotechnology

The biological and physical sciences share a common interest in small structures (the definition of 'small' depends on the application, but can range from 1 nm to 1 mm). A vigorous trade across the borders of these areas of science is developing around new materials and tools (largely from the physical sciences) and new phenomena (largely from the biological sciences). The physical sciences offer tools for synthesis and fabrication of devices for measuring the characteristics of cells and sub-cellular components, and of materials useful in cell and molecular biology; biology offers a window into the most sophisticated collection of functional nanostructures that exists.     

Benefits of hierarchical generalization and storage of the representations of "object-place" associations in the hippocampal subfields (a hypothesis)

We analyzed the results of experimental research of features of processing sensory information in the hippocampus and neocortex available in literature and results of modelling the perception of information in the neocortex. It is noted that "place" fields of neurons become wider, and overlapping of receptive fields increases during upward moving in trisynaptic hippocampal pathway. These effects specify the generalization of the information processed. The results of our analysis allow us to put forward a hypothesis that a hierarchical complication of"object - place" associations occurs during upward propagation of signals through all hippocampal subfields. Complexity of neural representations of "object - place" associations that are formed and permanently stored in the hippocampal areas increases in process of propagation of signals from the entorhinal cortex to the hierarchically higher dentate gyrus, area CA3 and area CA1. Therefore, with the aim to extract information about "object - place" associations with certain details it is necessary to access that hippocampal area in which associations were processed and stored with the required degree of elaboration. By analogy with the neocortex, it is proposed that such processing of information in the hippocampus makes it possible to avoid the combinatorial explosion and provides storing (memory) the associations accumulated during the life. The proposed mechanism can serve as an addition to the known multiple trace theory, which states that the hippocampus is an integrating part of memory trace and is always involved in recall of long-delayed episodes.     

ELF electromagnetic environment in power substations

This paper presents a theoretical analysis of electromagnetic environments in power substations in service. A new analytical method is developed and applied to magnetic field calculations in 187-kV and 66-kV substations. Experimental results verify that the method offers a good prediction of the magnetic field profiles in the substations except for the areas where localized field sources exist. The analytical results show that the magnetic field strength depends to a great extent on how the load powers distribute on individual lines and buses, that the magnetic fields in substations have a three-dimensional characteristic, and that the predominant field component depends on the position of interest. Moreover, it is suggested that objects placed in substations are exposed not only to magnetic fields of high strength in comparison to those in houses or near the distribution networks but also to fields with several percent of harmonic distortion.     

Selection of target sites for mobile DNA integration in the human genome

DNA sequences from retroviruses, retrotransposons, DNA transposons, and parvoviruses can all become integrated into the human genome. Accumulation of such sequences accounts for at least 40% of our genome today. These integrating elements are also of interest as gene-delivery vectors for human gene therapy. Here we present a comprehensive bioinformatic analysis of integration targeting by HIV, MLV, ASLV, SFV, L1, SB, and AAV. We used a mathematical method which allowed annotation of each base pair in the human genome for its likelihood of hosting an integration event by each type of element, taking advantage of more than 200 types of genomic annotation. This bioinformatic resource documents a wealth of new associations between genomic features and integration targeting. The study also revealed that the length of genomic intervals analyzed strongly affected the conclusions drawn--thus, answering the question "What genomic features affect integration?" requires carefully specifying the length scale of interest.     

How to make epidemiological training infectious

Modern infectious disease epidemiology builds on two independently developed fields: classical epidemiology and dynamical epidemiology. Over the past decade, integration of the two fields has increased in research practice, but training options within the fields remain distinct with few opportunities for integration in the classroom. The annual Clinic on the Meaningful Modeling of Epidemiological Data (MMED) at the African Institute for Mathematical Sciences has begun to address this gap. MMED offers participants exposure to a broad range of concepts and techniques from both epidemiological traditions. During MMED 2010 we developed a pedagogical approach that bridges the traditional distinction between classical and dynamical epidemiology and can be used at multiple educational levels, from high school to graduate level courses. The approach is hands-on, consisting of a real-time simulation of a stochastic outbreak in course participants, including realistic data reporting, followed by a variety of mathematical and statistical analyses, stemming from both epidemiological traditions. During the exercise, dynamical epidemiologists developed empirical skills such as study design and learned concepts of bias while classical epidemiologists were trained in systems thinking and began to understand epidemics as dynamic nonlinear processes. We believe this type of integrated educational tool will prove extremely valuable in the training of future infectious disease epidemiologists. We also believe that such interdisciplinary training will be critical for local capacity building in analytical epidemiology as Africa continues to produce new cohorts of well-trained mathematicians, statisticians, and scientists. And because the lessons draw on skills and concepts from many fields in biology--from pathogen biology, evolutionary dynamics of host--pathogen interactions, and the ecology of infectious disease to bioinformatics, computational biology, and statistics--this exercise can be incorporated into a broad array of life sciences courses.     

A sensitive multidimensional method for the detection,characterization, and quantification of trace free drug species in antibody-drug conjugate samples using mass spectral detection

Conjugation processes and stability studies associated with the production and shelf life of antibody-drug conjugates (ADCs) can result in free (non-conjugated) drug species. These free drug species can increase the risk to patients and reduce the efficacy of the ADC. Despite stringent purification steps, trace levels of free drug species may be present in formulated ADCs, reducing the therapeutic window. The reduction of sample preparation steps through the incorporation of multidimensional techniques has afforded analysts more efficient methods to assess trace drug species. Multidimensional methods coupling size-exclusion and reversed phase liquid chromatography with ultra-violet detection (SEC-RPLC/UV) have been reported, but offer limited sensitivity and can limit method optimization. The current study addresses these challenges with a multidimensional method that is specific, sensitive, and enables method control in both dimensions via coupling of an on-line solid phase extraction column to RPLC with mass spectral detection (SPE-RPLC/MS). The proposed method was evaluated using an antibody-fluorophore conjugate (AFC) as an ADC surrogate to brentuximab vedotin and its associated parent maleimide-val-cit-DSEA payload and the derived N-acetylcysteine adduct formed during the conjugation process. Assay sensitivity was found to be 2 orders more sensitive using MS detection in comparison to UV-based detection with a nominal limit of quantitation of 0.30 ng/mL (1.5 pg on-column). Free-drug species were present in an unadulterated ADC surrogate sample at concentrations below 7 ng/mL, levels not detectable by UV alone. The proposed SPE-RPLC/MS method provides a high degree of specificity and sensitivity in the assessment of trace free drug species and offers improved control over each dimension, enabling straightforward integration into existing or novel workflows.     

Projected benefits from integrating NTD programs in sub-Saharan Africa

The integration of preventive chemotherapy programs (PCPs) targeting multiple neglected tropical diseases (NTDs) with similar strategic approaches offers opportunities for enhanced cost-effectiveness. To estimate the potential cost savings and health outcomes of integrated programs, the data available for five NTDs (lymphatic filariasis, onchocerciasis, intestinal helminthiasis, schistosomiasis and trachoma) can be used to define eligible target populations, the probable overlap of at-risk populations, and the cost per person treated in stand-alone and integrated programs. If all targets for 2006 in sub-Saharan Africa are met, then savings of 26-47% can be projected from such integration (a cost of US dollar 58-81 million versus dollar 110 million for stand-alone PCPs). These first estimates can be refined as empirical data become available from integrated PCPs in the future.     

Manipulation and extraction of genomic DNA from cell lysate by functionalized magnetic particles for lab on a chip applications

A novel approach for extracting living cells' genomic DNA materials utilizing functionalized magnetic particles (MPs) is reported in this investigation. This strategy is amenable to handle bio-samples in a miniaturized environment and it offers a possibility to separate and purify DNA from other cell lysate mixtures "on-chip", which is known to be a bottle-neck step in an integrated micro-total-analysis-system (muTAS). "Species-specific" genomic DNA of interest is captured by the MPs based on the hybridization interaction between the biotinylated probes modified MPs and a complementary region of the targeted genome. The genome DNA anchored on the particles can be separated from the rest of cellular mixtures by a simple buffer washing upon the exertion of external magnetic force. Surface modifications of MPs and hybridization conditions affecting the genome capturing efficiency are investigated. Extraction of genomic DNA from E. coli is demonstrated in a silicon/glass-based micro-reactor patterned with a platinum heater and sensors. On-chip extraction and manipulation of genomic DNAs illustrated in this study is a step forward toward a total integrated bioanalytical microsystem for crude cells/sample analysis.     

Slowness: An Objective for Spike-Timing–Dependent Plasticity?

Our nervous system can efficiently recognize objects in spite of changes in contextual variables such as perspective or lighting conditions. Several lines of research have proposed that this ability for invariant recognition is learned by exploiting the fact that object identities typically vary more slowly in time than contextual variables or noise. Here, we study the question of how this “temporal stability” or “slowness” approach can be implemented within the limits of biologically realistic spike-based learning rules. We first show that slow feature analysis, an algorithm that is based on slowness, can be implemented in linear continuous model neurons by means of a modified Hebbian learning rule. This approach provides a link to the trace rule, which is another implementation of slowness learning. Then, we show analytically that for linear Poisson neurons, slowness learning can be implemented by spike-timing–dependent plasticity (STDP) with a specific learning window. By studying the learning dynamics of STDP, we show that for functional interpretations of STDP, it is not the learning window alone that is relevant but rather the convolution of the learning window with the postsynaptic potential. We then derive STDP learning windows that implement slow feature analysis and the “trace rule.” The resulting learning windows are compatible with physiological data both in shape and timescale. Moreover, our analysis shows that the learning window can be split into two functionally different components that are sensitive to reversible and irreversible aspects of the input statistics, respectively. The theory indicates that irreversible input statistics are not in favor of stable weight distributions but may generate oscillatory weight dynamics. Our analysis offers a novel interpretation for the functional role of STDP in physiological neurons.     

Experimental Study of a Starting Vortex Ring Generated by a Thin Circular Disk

The formation process of vortex ring generated by a thin circular disk was studied experimentally in this paper. A thin circular disk installed a linear motion stage was used to generate the vortex rings. Digital Particle Image Velocimetry (DPIV) was used to measure the velocity and vorticity fields. The finite-time Lyapunov exponent field corresponding to the vortex flow was computed to identify Lagrangian coherent structures of the starting vortex. The results reveal the existence of a flux window between repelling Lagrangian Coherent Structures (rLCS) and attracting Lagrangian Coherent Structures (aLCS), through which the shear flow is entrained into the vortex. The flux window is closed gradually during the starting process. Once the flux window shut down, the formation process of the vortex ring finishes, as the shear flow with vorticity cannot be entrained in the vortex ring.     

Spider: an R package for the analysis of species identity and evolution, with particular reference to DNA barcoding

Spider: SPecies IDentity and Evolution in R is a new R package implementing a number of useful analyses for DNA barcoding studies and associated research into species delimitation and speciation. Included are functions essential for generating important summary statistics from DNA barcode data, assessing specimen identification efficacy, and for testing and optimizing divergence threshold limits. In terms of investigating evolutionary and taxonomic questions, techniques for assessing diagnostic nucleotides and probability of reciprocal monophyly are also provided. Additionally, a sliding window function offers opportunities to analyse information across a gene, essential for marker design in degraded DNA studies. Spider capitalizes on R's extensible ethos and offers an integrated platform ideal for the analysis of both nucleotide and morphological data. The program can be obtained from the comprehensive R archive network (CRAN, http://cran.r-project.org) and from the R-Forge package development site (http://spider.r-forge.r-project.org/).     

Temporal integration in auditory sensory memory: neuromagnetic evidence

The cortical mechanisms of auditory sensory memory were investigated by analysis of neuromagnetic evoked responses. The major deflection of the auditory evoked field (N100m) appears to comprise an early posterior component (N100m^P) and a late anterior component (N100m^A) which is sensitive to temporal factors. When pairs of identical sounds are presented at intervals less than about 250 msec, the second sound evokes N100m^A with enhanced amplitude at a latency of about 150 msec. We suggest that N100m^A may index the activity of two distinct processes in auditory sensory memory. Its recovery cycle may reflect the activity of a memory trace which, according to previous studies, can retain processed information about an auditory sequence for about 10 sec. The enhancement effect may reflect the activity of a temporal integration process, whose time constant is such that sensation persists for 200–300 msec after stimulus offset, and so serves as a short memory store. Sound sequences falling within this window of integration seem to be coded holistically as unitary events.