356 research outputs found
Simultaneous whole-animal 3D-imaging of neuronal activity using light field microscopy
3D functional imaging of neuronal activity in entire organisms at single cell
level and physiologically relevant time scales faces major obstacles due to
trade-offs between the size of the imaged volumes, and spatial and temporal
resolution. Here, using light-field microscopy in combination with 3D
deconvolution, we demonstrate intrinsically simultaneous volumetric functional
imaging of neuronal population activity at single neuron resolution for an
entire organism, the nematode Caenorhabditis elegans. The simplicity of our
technique and possibility of the integration into epi-fluoresence microscopes
makes it an attractive tool for high-speed volumetric calcium imaging.Comment: 25 pages, 7 figures, incl. supplementary informatio
Complexity without chaos: Plasticity within random recurrent networks generates robust timing and motor control
It is widely accepted that the complex dynamics characteristic of recurrent
neural circuits contributes in a fundamental manner to brain function. Progress
has been slow in understanding and exploiting the computational power of
recurrent dynamics for two main reasons: nonlinear recurrent networks often
exhibit chaotic behavior and most known learning rules do not work in robust
fashion in recurrent networks. Here we address both these problems by
demonstrating how random recurrent networks (RRN) that initially exhibit
chaotic dynamics can be tuned through a supervised learning rule to generate
locally stable neural patterns of activity that are both complex and robust to
noise. The outcome is a novel neural network regime that exhibits both
transiently stable and chaotic trajectories. We further show that the recurrent
learning rule dramatically increases the ability of RRNs to generate complex
spatiotemporal motor patterns, and accounts for recent experimental data
showing a decrease in neural variability in response to stimulus onset
C-reactive protein reference percentiles among pre-adolescent children in Europe based on the IDEFICS study population
OBJECTIVES: C-reactive protein (CRP) is involved in a wide range of diseases. It is a powerful marker for inflammatory processes used for diagnostic and monitoring purposes. We aimed to establish reference values as data on the distribution of serum CRP levels in young European children are scarce.
SUBJECTS: Reference values of high-sensitivity CRP concentrations were calculated for 9855 children aged 2.0-10.9 years, stratified by age and sex. The children were recruited during the population-based European IDEFICS study (Identification and prevention of Dietary-and lifestyle-induced health Effects in Children and infantS) with 18 745 participants recruited from 2007 to 2010.
RESULTS: In 44.1 % of the children, CRP values were below or equal the detection limit of 0.2 mg/l. Median CRP concentrations showed a slight negative age trend in boys and girls, whereas serum CRP values were slightly higher in girls than in boys across all age groups.
CONCLUSIONS: Our population-based reference values of CRP may guide paediatric practice as elevated values may require further investigation or treatment. Therefore, the presented reference values represent a basis for clinical evaluation and for future research on risk assessment of diseases associated with increased CRP levels among children
A Generalized Linear Model for Estimating Spectrotemporal Receptive Fields from Responses to Natural Sounds
In the auditory system, the stimulus-response properties of single neurons are often described in terms of the spectrotemporal receptive field (STRF), a linear kernel relating the spectrogram of the sound stimulus to the instantaneous firing rate of the neuron. Several algorithms have been used to estimate STRFs from responses to natural stimuli; these algorithms differ in their functional models, cost functions, and regularization methods. Here, we characterize the stimulus-response function of auditory neurons using a generalized linear model (GLM). In this model, each cell's input is described by: 1) a stimulus filter (STRF); and 2) a post-spike filter, which captures dependencies on the neuron's spiking history. The output of the model is given by a series of spike trains rather than instantaneous firing rate, allowing the prediction of spike train responses to novel stimuli. We fit the model by maximum penalized likelihood to the spiking activity of zebra finch auditory midbrain neurons in response to conspecific vocalizations (songs) and modulation limited (ml) noise. We compare this model to normalized reverse correlation (NRC), the traditional method for STRF estimation, in terms of predictive power and the basic tuning properties of the estimated STRFs. We find that a GLM with a sparse prior predicts novel responses to both stimulus classes significantly better than NRC. Importantly, we find that STRFs from the two models derived from the same responses can differ substantially and that GLM STRFs are more consistent between stimulus classes than NRC STRFs. These results suggest that a GLM with a sparse prior provides a more accurate characterization of spectrotemporal tuning than does the NRC method when responses to complex sounds are studied in these neurons
New Constraints (and Motivations) for Abelian Gauge Bosons in the MeV-TeV Mass Range
We survey the phenomenological constraints on abelian gauge bosons having
masses in the MeV to multi-GeV mass range (using precision electroweak
measurements, neutrino-electron and neutrino-nucleon scattering, electron and
muon anomalous magnetic moments, upsilon decay, beam dump experiments, atomic
parity violation, low-energy neutron scattering and primordial
nucleosynthesis). We compute their implications for the three parameters that
in general describe the low-energy properties of such bosons: their mass and
their two possible types of dimensionless couplings (direct couplings to
ordinary fermions and kinetic mixing with Standard Model hypercharge). We argue
that gauge bosons with very small couplings to ordinary fermions in this mass
range are natural in string compactifications and are likely to be generic in
theories for which the gravity scale is systematically smaller than the Planck
mass - such as in extra-dimensional models - because of the necessity to
suppress proton decay. Furthermore, because its couplings are weak, in the
low-energy theory relevant to experiments at and below TeV scales the charge
gauged by the new boson can appear to be broken, both by classical effects and
by anomalies. In particular, if the new gauge charge appears to be anomalous,
anomaly cancellation does not also require the introduction of new light
fermions in the low-energy theory. Furthermore, the charge can appear to be
conserved in the low-energy theory, despite the corresponding gauge boson
having a mass. Our results reduce to those of other authors in the special
cases where there is no kinetic mixing or there is no direct coupling to
ordinary fermions, such as for recently proposed dark-matter scenarios.Comment: 49 pages + appendix, 21 figures. This is the final version which
appears in JHE
A theory of how active behavior stabilises neural activity: neural gain modulation by closed-loop environmental feedback
During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence of neural fluctuations, across the brain, on closed-loop brain/body/environment interactions strongly supporting the idea that brain function cannot be fully understood through open-loop approaches alone
Maternal Dietary Supplementation with Oligofructose-Enriched Inulin in Gestating/Lactating Rats Preserves Maternal Bone and Improves Bone Microarchitecture in Their Offspring
This study received financial support from Abbott Nutrition, a commercial company, and coauthors PBV, MM, JMLP and RR are employees of Abbott Nutrition. There are two patents related with the data presented (EP 2502507 A1 and EP 2745706 A1).Some of these results were presented in the 7th World Congress of DOHaD (2011) and in the World Congress on Osteoporosis, Osteoarthritis and Musculoskeletal Disease (WCO-IOF-ESCEO) (2014).Nutrition during pregnancy and lactation could exert a key role not only on maternal bone, but also could influence the skeletal development of the offspring. This study was performed in rats to assess the relationship between maternal dietary intake of prebiotic oligofructose-enriched inulin and its role in bone turnover during gestation and lactation, as well as its effect on offspring peak bone mass/architecture during early adulthood. Rat dams were fed either with standard rodent diet (CC group), calcium-fortified diet (Ca group), or prebiotic oligofructose-enriched inulin supplemented diet (Pre group), during the second half of gestation and lactation. Bone mineral density (BMD) and content (BMC), as well as micro-structure of dams and offspring at different stages were analysed. Dams in the Pre group had significantly higher trabecular thickness (Tb.Th), trabecular bone volume fraction (BV/TV) and smaller specific bone surface (BS/BV) of the tibia in comparison with CC dams. The Pre group offspring during early adulthood had an increase of the lumbar vertebra BMD when compared with offspring of CC and Ca groups. The Pre group offspring also showed significant increase versus CC in cancellous and cortical structural parameters of the lumbar vertebra 4 such as Tb.Th, cortical BMD and decreased BS/BV. The results indicate that oligofructose-enriched inulin supplementation can be considered as a plausible nutritional option for protecting against maternal bone loss during gestation and lactation preventing bone fragility and for optimizing peak bone mass and architecture of the offspring in order to increase bone strength.This study was funded by Abbott Nutrition R&D, and co-authors PBV, MM, JMLP and RR receive salary from Abbott Nutrition
In vivo biomolecular imaging of zebrafish embryos using confocal Raman spectroscopy
Zebrafish embryos provide a unique opportunity to visualize complex biological processes, yet conventional imaging modalities are unable to access intricate biomolecular information without compromising the integrity of the embryos. Here, we report the use of confocal Raman spectroscopic imaging for the visualization and multivariate analysis of biomolecular information extracted from unlabeled zebrafish embryos. We outline broad applications of this method in: (i) visualizing the biomolecular distribution of whole embryos in three dimensions, (ii) resolving anatomical features at subcellular spatial resolution, (iii) biomolecular profiling and discrimination of wild type and ΔRD1 mutant Mycobacterium marinum strains in a zebrafish embryo model of tuberculosis and (iv) in vivo temporal monitoring of the wound response in living zebrafish embryos. Overall, this study demonstrates the application of confocal Raman spectroscopic imaging for the comparative bimolecular analysis of fully intact and living zebrafish embryos
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