333 research outputs found
Dynamic Hebbian Cross-Correlation Learning Resolves the Spike Timing Dependent Plasticity Conundrum
Spike Timing-Dependent Plasticity has been found to assume many different forms. The classic STDP curve, with one potentiating and one depressing window, is only one of many possible curves that describe synaptic learning using the STDP mechanism. It has been shown experimentally that STDP curves may contain multiple LTP and LTD windows of variable width, and even inverted windows. The underlying STDP mechanism that is capable of producing such an extensive, and apparently incompatible, range of learning curves is still under investigation. In this paper, it is shown that STDP originates from a combination of two dynamic Hebbian cross-correlations of local activity at the synapse. The correlation of the presynaptic activity with the local postsynaptic activity is a robust and reliable indicator of the discrepancy between the presynaptic neuron and the postsynaptic neuron's activity. The second correlation is between the local postsynaptic activity with dendritic activity which is a good indicator of matching local synaptic and dendritic activity. We show that this simple time-independent learning rule can give rise to many forms of the STDP learning curve. The rule regulates synaptic strength without the need for spike matching or other supervisory learning mechanisms. Local differences in dendritic activity at the synapse greatly affect the cross-correlation difference which determines the relative contributions of different neural activity sources. Dendritic activity due to nearby synapses, action potentials, both forward and back-propagating, as well as inhibitory synapses will dynamically modify the local activity at the synapse, and the resulting STDP learning rule. The dynamic Hebbian learning rule ensures furthermore, that the resulting synaptic strength is dynamically stable, and that interactions between synapses do not result in local instabilities. The rule clearly demonstrates that synapses function as independent localized computational entities, each contributing to the global activity, not in a simply linear fashion, but in a manner that is appropriate to achieve local and global stability of the neuron and the entire dendritic structure
Lack of Mutual Respect in Relationship The Endangered Partner
Violence in a relationship and in a family setting has been
an issue of concern to various interest groups and professional organizations.
Of particular interest in this article is violence against women
in a relationship. While there is an abundance of knowledge on violence
against women in general, intimate or partner femicide seems to have
received less attention. Unfortunately, the incidence of violence against
women, and intimate femicide in particular, has been an issue of concern
in the African setting.
This article examines the trends of intimate femicide in an African setting
in general, and in Botswana in particular. The increase in intimate
femicide is an issue of concern, which calls for collective effort to address.
This article also examines trends offemicide in Botswana, and the
antecedents and the precipitating factors. Some studies have implicated
societal and cultural dynamics as playing significant roles in intimate
femicide in the African setting. It is believed that the patriarchal nature
of most African settings and the ideology of male supremacy have relegated
women to a subordinate role. Consequently, respect for women
in any relationship with men is lopsided in favor of men and has led to
abuse of women, including intimate femicide. Other militating factors in
intimate femicide ,are examined and the implications for counseling to
assist the endangered female partner are discussed
COSMOGRAIL: the COSmological MOnitoring of GRAvItational Lenses IX. Time delays, lens dynamics and baryonic fraction in HE 0435-1223
We present accurate time delays for the quadruply imaged quasar HE 0435-1223.
The delays were measured from 575 independent photometric points obtained in
the R-band between January 2004 and March 2010. With seven years of data, we
clearly show that quasar image A is affected by strong microlensing variations
and that the time delays are best expressed relative to quasar image B. We
measured Delta_t(BC) = 7.8+/-0.8 days, Delta_t(BD) = -6.5+/-0.7 days and
Delta_t_CD = -14.3+/-0.8 days. We spacially deconvolved HST NICMOS2 F160W
images to derive accurate astrometry of the quasar images and to infer the
light profile of the lensing galaxy. We combined these images with a stellar
population fitting of a deep VLT spectrum of the lensing galaxy to estimate the
baryonic fraction, , in the Einstein radius. We measured f_b =
0.65+0.13-0.10 if the lensing galaxy has a Salpeter IMF and f_b =
0.45+0.04-0.07 if it has a Kroupa IMF. The spectrum also allowed us to estimate
the velocity dispersion of the lensing galaxy, sigma_ap = 222+/-34 km/s. We
used f_b and sigma_ap to constrain an analytical model of the lensing galaxy
composed of an Hernquist plus generalized NFW profile. We solve the Jeans
equations numerically for the model and explored the parameter space under the
additional requirement that the model must predict the correct astrometry for
the quasar images. Given the current error bars on f_b and sigma_ap, we did not
constrain H0 yet with high accuracy, i.e., we found a broad range of models
with chi^2 < 1. However, narrowing this range is possible, provided a better
velocity dispersion measurement becomes available. In addition, increasing the
depth of the current HST imaging data of HE 0435-1223 will allow us to combine
our constraints with lens reconstruction techniques that make use of the full
Einstein ring that is visible in this object.Comment: 12 pages, 10 figures, final version accepted for publication by A&
COSMOGRAIL: the COSmological MOnitoring of GRAvItational Lenses VII. Time delays and the Hubble constant from WFI J2033-4723
Gravitationally lensed quasars can be used to map the mass distribution in
lensing galaxies and to estimate the Hubble constant H0 by measuring the time
delays between the quasar images. Here we report the measurement of two
independent time delays in the quadruply imaged quasar WFI J2033-4723 (z =
1.66). Our data consist of R-band images obtained with the Swiss 1.2 m EULER
telescope located at La Silla and with the 1.3 m SMARTS telescope located at
Cerro Tololo. The light curves have 218 independent epochs spanning 3 full
years of monitoring between March 2004 and May 2007, with a mean temporal
sampling of one observation every 4th day. We measure the time delays using
three different techniques, and we obtain Dt(B-A) = 35.5 +- 1.4 days (3.8%) and
Dt(B-C) = 62.6 +4.1/-2.3 days (+6.5%/-3.7%), where A is a composite of the
close, merging image pair. After correcting for the time delays, we find R-band
flux ratios of F_A/F_B = 2.88 +- 0.04, F_A/F_C = 3.38 +- 0.06, and F_A1/F_A2 =
1.37 +- 0.05 with no evidence for microlensing variability over a time scale of
three years. However, these flux ratios do not agree with those measured in the
quasar emission lines, suggesting that longer term microlensing is present. Our
estimate of H0 agrees with the concordance value: non-parametric modeling of
the lensing galaxy predicts H0 = 67 +13/-10 km s-1 Mpc-1, while the Single
Isothermal Sphere model yields H0 = 63 +7/-3 km s-1 Mpc-1 (68% confidence
level). More complex lens models using a composite de Vaucouleurs plus NFW
galaxy mass profile show twisting of the mass isocontours in the lensing
galaxy, as do the non-parametric models. As all models also require a
significant external shear, this suggests that the lens is a member of the
group of galaxies seen in field of view of WFI J2033-4723.Comment: 14 pages, 12 figures, published in A&
Dendritic Morphology Predicts Pattern Recognition Performance in Multi-compartmental Model Neurons with and without Active Conductances
This is an Open Access article published under the Creative Commons Attribution license CC BY 4.0 which allows users to read, copy, distribute and make derivative works, as long as the author of the original work is citedIn this paper we examine how a neuron’s dendritic morphology can affect its pattern recognition performance. We use two different algorithms to systematically explore the space of dendritic morphologies: an algorithm that generates all possible dendritic trees with 22 terminal points, and one that creates representative samples of trees with 128 terminal points. Based on these trees, we construct multi-compartmental models. To assess the performance of the resulting neuronal models, we quantify their ability to discriminate learnt and novel input patterns. We find that the dendritic morphology does have a considerable effect on pattern recognition performance and that the neuronal performance is inversely correlated with the mean depth of the dendritic tree. The results also reveal that the asymmetry index of the dendritic tree does not correlate with the performance for the full range of tree morphologies. The performance of neurons with dendritic tapering is best predicted by the mean and variance of the electrotonic distance of their synapses to the soma. All relationships found for passive neuron models also hold, even in more accentuated form, for neurons with active membranesPeer reviewedFinal Published versio
Predicting consumer biomass, size-structure, production, catch potential, responses to fishing and associated uncertainties in the world's marine ecosystems
Existing estimates of fish and consumer biomass in the world’s oceans are disparate. This creates uncertainty about the roles of fish and other consumers in biogeochemical cycles and ecosystem processes, the extent of human and environmental impacts and fishery potential. We develop and use a size-based macroecological model to assess the effects of parameter uncertainty on predicted consumer biomass, production and distribution. Resulting uncertainty is large (e.g. median global biomass 4.9 billion tonnes for consumers weighing 1 g to 1000 kg; 50% uncertainty intervals of 2 to 10.4 billion tonnes; 90% uncertainty intervals of 0.3 to 26.1 billion tonnes) and driven primarily by uncertainty in trophic transfer efficiency and its relationship with predator-prey body mass ratios. Even the upper uncertainty intervals for global predictions of consumer biomass demonstrate the remarkable scarcity of marine consumers, with less than one part in 30 million by volume of the global oceans comprising tissue of macroscopic animals. Thus the apparently high densities of marine life seen in surface and coastal waters and frequently visited abundance hotspots will likely give many in society a false impression of the abundance of marine animals. Unexploited baseline biomass predictions from the simple macroecological model were used to calibrate a more complex size- and trait-based model to estimate fisheries yield and impacts. Yields are highly dependent on baseline biomass and fisheries selectivity. Predicted global sustainable fisheries yield increases ≈4 fold when smaller individuals (< 20 cm from species of maximum mass < 1kg) are targeted in all oceans, but the predicted yields would rarely be accessible in practice and this fishing strategy leads to the collapse of larger species if fishing mortality rates on different size classes cannot be decoupled. Our analyses show that models with minimal parameter demands that are based on a few established ecological principles can support equitable analysis and comparison of diverse ecosystems. The analyses provide insights into the effects of parameter uncertainty on global biomass and production estimates, which have yet to be achieved with complex models, and will therefore help to highlight priorities for future research and data collection. However, the focus on simple model structures and global processes means that non-phytoplankton primary production and several groups, structures and processes of ecological and conservation interest are not represented. Consequently, our simple models become increasingly less useful than more complex alternatives when addressing questions about food web structure and function, biodiversity, resilience and human impacts at smaller scales and for areas closer to coasts
Fat induces glucose metabolism in nontransformed liver cells and promotes liver tumorigenesis
Hepatic fat accumulation is associated with diabetes and hepatocellular carcinoma (HCC). Here, we characterize the metabolic response that high-fat availability elicits in livers before disease development. After a short term on a high-fat diet (HFD), otherwise healthy mice showed elevated hepatic glucose uptake and increased glucose contribution to serine and pyruvate carboxylase activity compared with control diet (CD) mice. This glucose phenotype occurred independently from transcriptional or proteomic programming, which identifies increased peroxisomal and lipid metabolism pathways. HFD-fed mice exhibited increased lactate production when challenged with glucose. Consistently, administration of an oral glucose bolus to healthy individuals revealed a correlation between waist circumference and lactate secretion in a human cohort. In vitro, palmitate exposure stimulated production of reactive oxygen species and subsequent glucose uptake and lactate secretion in hepatocytes and liver cancer cells. Furthermore, HFD enhanced the formation of HCC compared with CD in mice exposed to a hepatic carcinogen. Regardless of the dietary background, all murine tumors showed similar alterations in glucose metabolism to those identified in fat exposed nontransformed mouse livers, however, particular lipid species were elevated in HFD tumor and nontumor-bearing HFD liver tissue. These findings suggest that fat can induce glucose-mediated metabolic changes in nontransformed liver cells similar to those found in HCC
Investigating the impact of electrical stimulation temporal distribution on cortical network responses
Convergence among Non-Sister Dendritic Branches: An Activity-Controlled Mean to Strengthen Network Connectivity
The manner by which axons distribute synaptic connections along dendrites remains a fundamental unresolved issue in neuronal development and physiology. We found in vitro and in vivo indications that dendrites determine the density, location and strength of their synaptic inputs by controlling the distance of their branches from those of their neighbors. Such control occurs through collective branch convergence, a behavior promoted by AMPA and NMDA glutamate receptor activity. At hubs of convergence sites, the incidence of axo-dendritic contacts as well as clustering levels, pre- and post-synaptic protein content and secretion capacity of synaptic connections are higher than found elsewhere. This coupling between synaptic distribution and the pattern of dendritic overlapping results in ‘Economical Small World Network’, a network configuration that enables single axons to innervate multiple and remote dendrites using short wiring lengths. Thus, activity-mediated regulation of the proximity among dendritic branches serves to pattern and strengthen neuronal connectivity
Comparing Pandemic to Seasonal Influenza Mortality: Moderate Impact Overall but High Mortality in Young Children
Background: We assessed the severity of the 2009 influenza pandemic by comparing pandemic mortality to seasonal influenza mortality. However, reported pandemic deaths were laboratory-confirmed - and thus an underestimation - whereas seasonal influenza mortality is often more inclusively estimated. For a valid comparison, our study used the same statistical methodology and data types to estimate pandemic and seasonal influenza mortality. Methods and Findings: We used data on all-cause mortality (1999-2010, 100% coverage, 16.5 million Dutch population) and influenza-like-illness (ILI) incidence (0.8% coverage). Data was aggregated by week and age category. Using generalized estimating equation regression models, we attributed mortality to influenza by associating mortality with ILI-incidence, while adjusting for annual shifts in association. We also adjusted for respiratory syncytial virus, hot/cold weather, other seasonal factors and autocorrelation. For the 2009 pandemic season, we estimated 612 (range 266-958) influenza-attributed deaths; for seasonal influen
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