884 research outputs found
Improved algorithm for neuronal ensemble inference by Monte Carlo method
Neuronal ensemble inference is one of the significant problems in the study
of biological neural networks. Various methods have been proposed for ensemble
inference from their activity data taken experimentally. Here we focus on
Bayesian inference approach for ensembles with generative model, which was
proposed in recent work. However, this method requires large computational
cost, and the result sometimes gets stuck in bad local maximum solution of
Bayesian inference. In this work, we give improved Bayesian inference algorithm
for these problems. We modify ensemble generation rule in Markov chain Monte
Carlo method, and introduce the idea of simulated annealing for hyperparameter
control. We also compare the performance of ensemble inference between our
algorithm and the original one.Comment: 14 pages, 3 figure
Pharmacological Analysis of Ionotropic Glutamate Receptor Function in Neuronal Circuits of the Zebrafish Olfactory Bulb
Although synaptic functions of ionotropic glutamate receptors in the olfactory bulb have been studied in vitro, their roles in pattern processing in the intact system remain controversial. We therefore examined the functions of ionotropic glutamate receptors during odor processing in the intact olfactory bulb of zebrafish using pharmacological manipulations. Odor responses of mitral cells and interneurons were recorded by electrophysiology and 2-photon Ca2+ imaging. The combined blockade of AMPA/kainate and NMDA receptors abolished odor-evoked excitation of mitral cells. The blockade of AMPA/kainate receptors alone, in contrast, increased the mean response of mitral cells and decreased the mean response of interneurons. The blockade of NMDA receptors caused little or no change in the mean responses of mitral cells and interneurons. However, antagonists of both receptor types had diverse effects on the magnitude and time course of individual mitral cell and interneuron responses and, thus, changed spatio-temporal activity patterns across neuronal populations. Oscillatory synchronization was abolished or reduced by AMPA/kainate and NMDA receptor antagonists, respectively. These results indicate that (1) interneuron responses depend mainly on AMPA/kainate receptor input during an odor response, (2) interactions among mitral cells and interneurons regulate the total olfactory bulb output activity, (3) AMPA/kainate receptors participate in the synchronization of odor-dependent neuronal ensembles, and (4) ionotropic glutamate receptor-containing synaptic circuits shape odor-specific patterns of olfactory bulb output activity. These mechanisms are likely to be important for the processing of odor-encoding activity patterns in the olfactory bulb
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
Neurogenesis Drives Stimulus Decorrelation in a Model of the Olfactory Bulb
The reshaping and decorrelation of similar activity patterns by neuronal
networks can enhance their discriminability, storage, and retrieval. How can
such networks learn to decorrelate new complex patterns, as they arise in the
olfactory system? Using a computational network model for the dominant neural
populations of the olfactory bulb we show that fundamental aspects of the adult
neurogenesis observed in the olfactory bulb -- the persistent addition of new
inhibitory granule cells to the network, their activity-dependent survival, and
the reciprocal character of their synapses with the principal mitral cells --
are sufficient to restructure the network and to alter its encoding of odor
stimuli adaptively so as to reduce the correlations between the bulbar
representations of similar stimuli. The decorrelation is quite robust with
respect to various types of perturbations of the reciprocity. The model
parsimoniously captures the experimentally observed role of neurogenesis in
perceptual learning and the enhanced response of young granule cells to novel
stimuli. Moreover, it makes specific predictions for the type of odor
enrichment that should be effective in enhancing the ability of animals to
discriminate similar odor mixtures
Information transmission in oscillatory neural activity
Periodic neural activity not locked to the stimulus or to motor responses is
usually ignored. Here, we present new tools for modeling and quantifying the
information transmission based on periodic neural activity that occurs with
quasi-random phase relative to the stimulus. We propose a model to reproduce
characteristic features of oscillatory spike trains, such as histograms of
inter-spike intervals and phase locking of spikes to an oscillatory influence.
The proposed model is based on an inhomogeneous Gamma process governed by a
density function that is a product of the usual stimulus-dependent rate and a
quasi-periodic function. Further, we present an analysis method generalizing
the direct method (Rieke et al, 1999; Brenner et al, 2000) to assess the
information content in such data. We demonstrate these tools on recordings from
relay cells in the lateral geniculate nucleus of the cat.Comment: 18 pages, 8 figures, to appear in Biological Cybernetic
Self-organization in the olfactory system: one shot odor recognition in insects
We show in a model of spiking neurons that synaptic plasticity in the mushroom bodies in combination with the general fan-in, fan-out properties of the early processing layers of the olfactory system might be sufficient to account for its efficient recognition of odors. For a large variety of initial conditions the model system consistently finds a working solution without any fine-tuning, and is, therefore, inherently robust. We demonstrate that gain control through the known feedforward inhibition of lateral horn interneurons increases the capacity of the system but is not essential for its general function. We also predict an upper limit for the number of odor classes Drosophila can discriminate based on the number and connectivity of its olfactory neurons
Whole-body integration of gene expression and single-cell morphology
Animal bodies are composed of cell types with unique expression programs that implement their distinct locations, shapes, structures, and functions. Based on these properties, cell types assemble into specific tissues and organs. To systematically explore the link between cell-type-specific gene expression and morphology, we registered an expression atlas to a whole-body electron microscopy volume of the nereid Platynereis dumerilii. Automated segmentation of cells and nuclei identifies major cell classes and establishes a link between gene activation, chromatin topography, and nuclear size. Clustering of segmented cells according to gene expression reveals spatially coherent tissues. In the brain, genetically defined groups of neurons match ganglionic nuclei with coherent projections. Besides interneurons, we uncover sensory-neurosecretory cells in the nereid mushroom bodies, which thus qualify as sensory organs. They furthermore resemble the vertebrate telencephalon by molecular anatomy. We provide an integrated browser as a Fiji plugin for remote exploration of all available multimodal datasets
Characteristic Evolution and Matching
I review the development of numerical evolution codes for general relativity
based upon the characteristic initial value problem. Progress in characteristic
evolution is traced from the early stage of 1D feasibility studies to 2D
axisymmetric codes that accurately simulate the oscillations and gravitational
collapse of relativistic stars and to current 3D codes that provide pieces of a
binary black hole spacetime. Cauchy codes have now been successful at
simulating all aspects of the binary black hole problem inside an artificially
constructed outer boundary. A prime application of characteristic evolution is
to extend such simulations to null infinity where the waveform from the binary
inspiral and merger can be unambiguously computed. This has now been
accomplished by Cauchy-characteristic extraction, where data for the
characteristic evolution is supplied by Cauchy data on an extraction worldtube
inside the artificial outer boundary. The ultimate application of
characteristic evolution is to eliminate the role of this outer boundary by
constructing a global solution via Cauchy-characteristic matching. Progress in
this direction is discussed.Comment: New version to appear in Living Reviews 2012. arXiv admin note:
updated version of arXiv:gr-qc/050809
Learning curves and long-term outcome of simulation-based thoracentesis training for medical students
<p>Abstract</p> <p>Background</p> <p>Simulation-based medical education has been widely used in medical skills training; however, the effectiveness and long-term outcome of simulation-based training in thoracentesis requires further investigation. The purpose of this study was to assess the learning curve of simulation-based thoracentesis training, study skills retention and transfer of knowledge to a clinical setting following simulation-based education intervention in thoracentesis procedures.</p> <p>Methods</p> <p>Fifty-two medical students were enrolled in this study. Each participant performed five supervised trials on the simulator. Participant's performance was assessed by performance score (PS), procedure time (PT), and participant's confidence (PC). Learning curves for each variable were generated. Long-term outcome of the training was measured by the retesting and clinical performance evaluation 6 months and 1 year, respectively, after initial training on the simulator.</p> <p>Results</p> <p>Significant improvements in PS, PT, and PC were noted among the first 3 to 4 test trials (p < 0.05). A plateau for PS, PT, and PC in the learning curves occurred in trial 4. Retesting 6 months after training yielded similar scores to trial 5 (p > 0.05). Clinical competency in thoracentesis was improved in participants who received simulation training relative to that of first year medical residents without such experience (p < 0.05).</p> <p>Conclusions</p> <p>This study demonstrates that simulation-based thoracentesis training can significantly improve an individual's performance. The saturation of learning from the simulator can be achieved after four practice sessions. Simulation-based training can assist in long-term retention of skills and can be partially transferred to clinical practice.</p
GRIPS - Gamma-Ray Imaging, Polarimetry and Spectroscopy
We propose to perform a continuously scanning all-sky survey from 200 keV to
80 MeV achieving a sensitivity which is better by a factor of 40 or more
compared to the previous missions in this energy range. The Gamma-Ray Imaging,
Polarimetry and Spectroscopy (GRIPS) mission addresses fundamental questions in
ESA's Cosmic Vision plan. Among the major themes of the strategic plan, GRIPS
has its focus on the evolving, violent Universe, exploring a unique energy
window. We propose to investigate -ray bursts and blazars, the
mechanisms behind supernova explosions, nucleosynthesis and spallation, the
enigmatic origin of positrons in our Galaxy, and the nature of radiation
processes and particle acceleration in extreme cosmic sources including pulsars
and magnetars. The natural energy scale for these non-thermal processes is of
the order of MeV. Although they can be partially and indirectly studied using
other methods, only the proposed GRIPS measurements will provide direct access
to their primary photons. GRIPS will be a driver for the study of transient
sources in the era of neutrino and gravitational wave observatories such as
IceCUBE and LISA, establishing a new type of diagnostics in relativistic and
nuclear astrophysics. This will support extrapolations to investigate star
formation, galaxy evolution, and black hole formation at high redshifts.Comment: to appear in Exp. Astron., special vol. on M3-Call of ESA's Cosmic
Vision 2010; 25 p., 25 figs; see also www.grips-mission.e
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