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Dendrite morphology, a neuron's anatomical fingerprint, is a neuroscientist's asset in unveiling organizational principles in the brain. However, the genetic program encoding the morphological identity of a single dendrite remains a mystery. In order to obtain a formal understanding of dendritic branching, we studied distributions of morphological parameters in a group of four individually identifiable neurons of the fly visual system. We found that parameters relating to the branching topology were similar throughout all cells. Only parameters relating to the area covered by the dendrite were cell type specific. With these areas, artificial dendrites were grown based on optimization principles minimizing the amount of wiring and maximizing synaptic democracy. Although the same branching rule was used for all cells, this yielded dendritic structures virtually indistinguishable from their real counterparts. From these principles we derived a fully-automated model-based neuron reconstruction procedure validating the artificial branching rule. In conclusion, we suggest that the genetic program implementing neuronal branching could be constant in all cells whereas the one responsible for the dendrite spanning field should be cell specific.

Dendrite morphology, a neuron's anatomical fingerprint, is a neuroscientist's asset in unveiling organizational principles in the brain. However, the genetic program encoding the morphological identity of a single dendrite remains a mystery. In order to obtain a formal understanding of dendritic branching, we studied distributions of morphological parameters in a group of four individually identifiable neurons of the fly visual system. We found that parameters relating to the branching topology were similar throughout all cells. Only parameters relating to the area covered by the dendrite were cell type specific. With these areas, artificial dendrites were grown based on optimization principles minimizing the amount of wiring and maximizing synaptic democracy. Although the same branching rule was used for all cells, this yielded dendritic structures virtually indistinguishable from their real counterparts. From these principles we derived a fully-automated model-based neuron reconstruction procedure validating the artificial branching rule. In conclusion, we suggest that the genetic program implementing neuronal branching could be constant in all cells whereas the one responsible for the dendrite spanning field should be cell specific.

Neuronal dendritic trees are complex structures that endow the cell with powerful computing capabilities and allow for high neural interconnectivity. Studying the function of dendritic structures has a long tradition in theoretical neuroscience, starting with the pioneering work by Wilfrid Rall in the 1950s. Recent advances in experimental techniques allow us to study dendrites with a new perspective and in greater detail. The goal of this volume is to provide a rsum of the state-of-the-art in experimental, computational, and mathematical investigations into the functions of dendrites in a variety of neural systems. Thebook firstlooks at morphological properties of dendrites and summarizes the approaches to measure dendrite morphology quantitatively and to actually generate synthetic dendrite morphologies in computer models. This morphological characterization ranges from the study of fractal principles to describe dendrite topologies, to the consequences of optimization principles for dendrite shape. Individual approaches are collected to study the aspects of dendrite shape that relate directly to underlying circuit constraints and computation. The second main theme focuses on how dendrites contribute to the computations that neurons perform. What role do dendritic morphology andthe distributions of synapses and membrane properties over the dendritic tree have in determining the output of a neuron in response to its input? A wide range of studies is brought together, with topics ranging from general to system-specific phenomenasome having a strong experimental component, and others being fully theoretical. The studies come from many different neural systems and animal species ranging from invertebrates to mammals. Withthis broad focus, an overview is given of the diversity of mechanisms that dendrites can employ to shape neural computations.

We explored in a computational study the effect of dendrites on excitatory synapses undergoing spike-timing–dependent plasticity (STDP), using both cylindrical dendritic models and reconstructed dendritic trees. We show that even if the initial strength, gpeak, of distal synapses is augmented in a location independent manner, the efficacy of distal synapses diminishes following STDP and proximal synapses would eventually dominate. Indeed, proximal synapses always win over distal synapses following linear STDP rule, independent of the initial synaptic strength distribution in the dendritic tree. This effect is more pronounced as the dendritic cable length increases but it does not depend on the dendritic branching structure. Adding a small multiplicative component to the linear STDP rule, whereby already strong synapses tend to be less potentiated than depressed (and vice versa for weak synapses) did partially "save" distal synapses from "dying out." Another successful strategy for balancing the efficacy of distal and proximal synapses following STDP is to increase the upper bound for the synaptic conductance (gmax) with distance from the soma. We conclude by discussing an experiment for assessing which of these possible strategies might actually operate in dendrites.

AbstractAqueous zinc-ion batteries (AZIBs) are promising for future large-scale energy storage systems, however, suffer from inferior cycling life due to the dendrites growth and side reaction on Zn metal anode. Herein, a fast ion conductor Na5YSi4O12 (NYSO) was synthesized and fabricated as a protection layer of the Zn metal anode. By adjusting the thickness, an optimized NYSO coating of 20.3 µm was obtained and the corresponding symmetry cell demonstrates an extended life span of 1896 h at the current density of 0.5 mA cm−2. In addition, a favorable rate performance of the NYSO@Zn anode at a high current density of 10 mA cm−2 was achieved. Benefiting from the NYSO coating, uniform diffusion and deposition of Zn2+ on the Zn anode could be realized, leading to the elimination of Zn dendrites and side reactions. Therefore, the aqueous NYSO@Zn|CNT@MnO2 full cell shows superior capacity and cycling stability to that of the bare Zn full cell.

Electrorefining is a key step in pyroprocessing. The solid cathode processing is necessary to separate the salt from the cathode of the electrorefiner since the uranium deposit in a solid cathode contains electrolyte salt. Moreover, it is very important to increase the throughput of the salt separation system due to the high uranium content of the spent nuclear fuel and high salt fraction of uranium dendrites. Therefore, in this study, the effect of deposit on the evaporation of the adhered salt in a uranium deposit was investigated by using the samples of salt in the uranium deposit and salt in the deposit of the surrogate material for the effective separation of the salt. It was found that the salt evaporation rate is dependent on the deposit type and bulk density in the crucible. Additionally, the evaporation rate was found to be lower when the deposit structure is complex; the rate also decreases as the bulk density of the deposit is increased owing to the retardation of the salt vapour transport process. It was concluded that the mass transfer of the salt vapour is an important parameter for the achievement of a high throughput performance in the salt distillation process.

Dendrite size and morphology are key determinants of the functional properties of neurons. Here, we show that growth differentiation factor 5 (GDF5), a member of the bone morphogenetic protein (BMP) subclass of the transforming growth factor β superfamily with a wellcharacterised role in limb morphogenesis, is a key regulator of the growth and elaboration of pyramidal cell dendrites in the developing hippocampus. Pyramidal cells co-express GDF5 and its preferred receptors, BMP receptor 1B and BMP receptor 2, during development. In culture, GDF5 substantially increased dendrite, but not axon, elongation from these neurons by a mechanism that depends on activation of SMADs 1/5/8 and upregulation of the transcription factor HES5. In vivo, the apical and basal dendritic arbours of pyramidal cells throughout the hippocampus were markedly stunted in both homozygous and heterozygous Gdf5 null mutants, indicating that dendrite size and complexity are exquisitely sensitive to the level of endogenous GDF5 synthesis. © 2013. ; This work was supported by the Wellcome Trust [grant number 085984 to A.M.D.]; Proyecto de Excelencia of Regional Government Andalussia [grant number P10- CVI-6740 to A.R.-T.]; Fundação para a Ciencia e a Tecnologia [grant SFRH/BD/60498/2009 to C.O.]; and a 'Sara Borrell' Postdoctoral Fellowship from the National Institutes of Health 'Carlos III', Spain [grant number CD08/00078 to P.J.C.]. Deposited in PMC for immediate release ; Peer Reviewed

Dendritic democracy and independence have been characterized for near-instantaneous processing of synaptic inputs. However, a wide class of neuronal computations requires input integration on long timescales. As a paradigmatic example, entorhinal grid fields have been thought to be generated by the democratic summation of independent dendritic oscillations performing direction-selective path integration. We analyzed how multiple dendritic oscillators embedded in the same neuron integrate inputs separately and determine somatic membrane voltage jointly. We found that the interaction of dendritic oscillations leads to phase locking, which sets an upper limit on the timescale for independent input integration. Factors that increase this timescale also decrease the influence that the dendritic oscillations exert on somatic voltage. In entorhinal stellate cells, interdendritic coupling dominates and causes these cells to act as single oscillators. Our results suggest a fundamental trade-off between local and global processing in dendritic trees integrating ongoing signals.

The aim of this work is to give an overview of existing methods and to introduce three new methods for the determination of the Dendrite Coherency Point (DCP) for AlSi10Mg alloys, as well as to compare the acquired values of DCP based on a thermal analysis and on the analysis of cooling curves working with only one thermocouple. Additionally, the impact of alloying and contaminant elements on the DCP will be also studied. The first two proposed methods employ the higher order derivatives of the cooling curves. The DCP was determined as the crossing point of the second and third derivative curves plotted versus time (method 1) or that of the temperature (method 2) with the zero line just after the maximum liquidus temperature. The third proposed method is based on the determination of the crossing point of the third solid fraction derivative curve with the zero line, corresponding to a minimum of the second derivative. A Taguchi design for the experiments was developed to study the DCP values in the AlSi10Mg alloy. The DCP temperature values of the test alloys were compared with the DCP temperatures predicted by the previous methods and the influence of the major and minor alloying elements and contaminants over the DCP. The new processes obtained a correlation factor r2 from 0.954 and 0.979 and a standard deviation from 1.84 to 2.6 °C. The obtained correlation values are higher or similar than those obtained using previous methods with an easier way to define the DCP, allowing for a better automation of the accuracy of DCP determination. The use of derivative curves plotted versus temperature employed in the last two proposed methods, where the test samples did not have an influence over the registration curves, is proposed to have a better accuracy than those of the previously described methods. ; This work has been partially funded by the Basque Government through the ETORGAI programme ZE-2016/00018 and from the European Union's Seventh Programme for research, technological development and demonstration under grant agreement No. 296024.