Regulation of Spike Timing-Dependent Plasticity of Olfactory Inputs in Mitral Cells in the Rat Olfactory Bulb

The recent history of activity input onto granule cells (GCs) in the main olfactory bulb can affect the strength of lateral inhibition, which functions to generate contrast enhancement. However, at the plasticity level, it is unknown whether and how the prior modification of lateral inhibition modulates the subsequent induction of long-lasting changes of the excitatory olfactory nerve (ON) inputs to mitral cells (MCs). Here we found that the repetitive stimulation of two distinct excitatory inputs to the GCs induced a persistent modification of lateral inhibition in MCs in opposing directions. This bidirectional modification of inhibitory inputs differentially regulated the subsequent synaptic plasticity of the excitatory ON inputs to the MCs, which was induced by the repetitive pairing of excitatory postsynaptic potentials (EPSPs) with postsynaptic bursts. The regulation of spike timing-dependent plasticity (STDP) was achieved by the regulation of the inter-spike-interval (ISI) of the postsynaptic bursts. This novel form of inhibition-dependent regulation of plasticity may contribute to the encoding or processing of olfactory information in the olfactory bulb

The effect of particle size on the core losses of soft magnetic composites

In the field of electrical machines, the actual research activities mainly focus on improving the energetic aspects; for this reason, new magnetic materials are currently investigated and proposed, supporting the design and production of magnetic cores. The innovative aspects are related to both hard and soft magnetic materials. In the case of permanent magnets, the use of NdFeB bonded magnets represents a good solution in place of ferrites. For what concerns the soft magnetic materials, the adoption of Soft Magnetic Composites (SMCs) cores permits significant advantages compared to the laminated sheets, such as complex geometries and reduced eddy currents losses. SMC materials are ferromagnetic grains covered with an insulating layer that can be of an organic or inorganic type. The proposed study focuses on the impact of the particle size and distribution on the final material properties. The original powder was cut into three different fractions, and different combinations have been prepared, varying the fractions percentages. The magnetic and energetic properties have been evaluated in different frequency ranges, thus ranking the best combinations. The best specimens were then tested to evaluate the mechanical performances. The preliminary results are promising, but deeper analysis and tests are required to refine the selection and evaluate the improvements against the original composition taken as a reference.In the field of electrical machines, the actual research activities mainly focus on improving the energetic aspects; for this reason, new magnetic materials are currently investigated and proposed, supporting the design and production of magnetic cores. The innovative aspects are related to both hard and soft magnetic materials. In the case of permanent magnets, the use of NdFeB bonded magnets represents a good solution in place of ferrites. For what concerns the soft magnetic materials, the adoption of Soft Magnetic Composites (SMCs) cores permits significant advantages compared to the laminated sheets, such as complex geometries and reduced eddy currents losses. SMC materials are ferromagnetic grains covered with an insulating layer that can be of an organic or inorganic type. The proposed study focuses on the impact of the particle size and distribution on the final material properties. The original powder was cut into three different fractions, and different combinations have been prepared, varying th..

Simple, Fast and Accurate Implementation of the Diffusion Approximation Algorithm for Stochastic Ion Channels with Multiple States

The phenomena that emerge from the interaction of the stochastic opening and closing of ion channels (channel noise) with the non-linear neural dynamics are essential to our understanding of the operation of the nervous system. The effects that channel noise can have on neural dynamics are generally studied using numerical simulations of stochastic models. Algorithms based on discrete Markov Chains (MC) seem to be the most reliable and trustworthy, but even optimized algorithms come with a non-negligible computational cost. Diffusion Approximation (DA) methods use Stochastic Differential Equations (SDE) to approximate the behavior of a number of MCs, considerably speeding up simulation times. However, model comparisons have suggested that DA methods did not lead to the same results as in MC modeling in terms of channel noise statistics and effects on excitability. Recently, it was shown that the difference arose because MCs were modeled with coupled activation subunits, while the DA was modeled using uncoupled activation subunits. Implementations of DA with coupled subunits, in the context of a specific kinetic scheme, yielded similar results to MC. However, it remained unclear how to generalize these implementations to different kinetic schemes, or whether they were faster than MC algorithms. Additionally, a steady state approximation was used for the stochastic terms, which, as we show here, can introduce significant inaccuracies. We derived the SDE explicitly for any given ion channel kinetic scheme. The resulting generic equations were surprisingly simple and interpretable - allowing an easy and efficient DA implementation. The algorithm was tested in a voltage clamp simulation and in two different current clamp simulations, yielding the same results as MC modeling. Also, the simulation efficiency of this DA method demonstrated considerable superiority over MC methods.Comment: 32 text pages, 10 figures, 1 supplementary text + figur

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

Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fninf. 2017.00007/full#supplementary-materialModeling and simulating the neural structures which make up our central neural system is instrumental for deciphering the computational neural cues beneath. Higher levels of biological plausibility usually impose higher levels of complexity in mathematical modeling, from neural to behavioral levels. This paper focuses on overcoming the simulation problems (accuracy and performance) derived from using higher levels of mathematical complexity at a neural level. This study proposes different techniques for simulating neural models that hold incremental levels of mathematical complexity: leaky integrate-and-fire (LIF), adaptive exponential integrate-and-fire (AdEx), and Hodgkin-Huxley (HH) neural models (ranged from low to high neural complexity). The studied techniques are classified into two main families depending on how the neural-model dynamic evaluation is computed: the event-driven or the time-driven families. Whilst event-driven techniques pre-compile and store the neural dynamics within look-up tables, time-driven techniques compute the neural dynamics iteratively during the simulation time. We propose two modifications for the event-driven family: a look-up table recombination to better cope with the incremental neural complexity together with a better handling of the synchronous input activity. Regarding the time-driven family, we propose a modification in computing the neural dynamics: the bi-fixed-step integration method. This method automatically adjusts the simulation step size to better cope with the stiffness of the neural model dynamics running in CPU platforms. One version of this method is also implemented for hybrid CPU-GPU platforms. Finally, we analyze how the performance and accuracy of these modifications evolve with increasing levels of neural complexity. We also demonstrate how the proposed modifications which constitute the main contribution of this study systematically outperform the traditional event- and time-driven techniques under increasing levels of neural complexity.This study was supported by the European Union NR (658479-Spike Control), the Spanish National Grant NEUROPACT (TIN2013-47069-P) and by the Spanish National Grant PhD scholarship (AP2012-0906). We gratefully acknowledge the support of NVIDIA Corporation with the donation of two Titan GPUs for current EDLUT development

Mode shift of the voltage sensors in Shaker K+ channels is caused by energetic coupling to the pore domain

The voltage sensors of voltage-gated ion channels undergo a conformational change upon depolarization of the membrane that leads to pore opening. This conformational change can be measured as gating currents and is thought to be transferred to the pore domain via an annealing of the covalent link between voltage sensor and pore (S4-S5 linker) and the C terminus of the pore domain (S6). Upon prolonged depolarizations, the voltage dependence of the charge movement shifts to more hyperpolarized potentials. This mode shift had been linked to C-type inactivation but has recently been suggested to be caused by a relaxation of the voltage sensor itself. In this study, we identified two ShakerIR mutations in the S4-S5 linker (I384N) and S6 (F484G) that, when mutated, completely uncouple voltage sensor movement from pore opening. Using these mutants, we show that the pore transfers energy onto the voltage sensor and that uncoupling the pore from the voltage sensor leads the voltage sensors to be activated at more negative potentials. This uncoupling also eliminates the mode shift occurring during prolonged depolarizations, indicating that the pore influences entry into the mode shift. Using voltage-clamp fluorometry, we identified that the slow conformational change of the S4 previously correlated with the mode shift disappears when uncoupling the pore. The effects can be explained by a mechanical load that is imposed upon the voltage sensors by the pore domain and allosterically modulates its conformation. Mode shift is caused by the stabilization of the open state but leads to a conformational change in the voltage sensor

Lipid-dependent gating of a voltage-gated potassium channel

Recent studies hypothesized that phospholipids stabilize two voltage-sensing arginine residues of certain voltage-gated potassium channels in activated conformations. It remains unclear how lipids directly affect these channels. Here, by examining the conformations of the KvAP in different lipids, we showed that without voltage change, the voltage-sensor domains switched from the activated to the resting state when their surrounding lipids were changed from phospholipids to nonphospholipids. Such lipid-determined conformational change was coupled to the ion-conducting pore, suggesting that parallel to voltage gating, the channel is gated by its annular lipids. Our measurements recognized that the energetic cost of lipid-dependent gating approaches that of voltage gating, but kinetically it appears much slower. Our data support that a channel and its surrounding lipids together constitute a functional unit, and natural nonphospholipids such as cholesterol should exert strong effects on voltage-gated channels. Our first observation of lipid-dependent gating may have general implications to other membrane proteins

Large-Scale Streamwise Vortices in Turbulent Channel Flow Induced by Active Wall Actuations

© 2017, Springer Science+Business Media B.V., part of Springer Nature. Direct numerical simulations of turbulent flow in a plane channel using spanwise alternatively distributed strips (SADS) are performed to investigate the characteristics of large-scale streamwise vortices (LSSVs) induced by small-scale active wall actuations, and their role in suppressing flow separation. SADS control is obtained by alternatively applying out-of-phase control (OPC) and in-phase control (IPC) to the wall-normal velocity component of the lower channel wall, in the spanwise direction. Besides the non-controlled channel flow simulated as a reference, four controlled cases with 1, 2, 3 and 4 pairs of OPC/IPC strips are studied at M = 0.2 and Re = 6,000, based on the bulk velocity and the channel half height. The case with 2 pairs of strips, whose width is Δz+ = 264 based on the friction velocity of the non-controlled case, is the most effective in terms of generating large-scale motions. It is also found that the OPC (resp. IPC) strips suppress (resp. enhance) the coherent structures and that leads to the creation of a vertical shear layer, which is responsible for the LSSVs presence. They are in a statistically steady state and their cores are located between two neighbouring OPC and IPC strips. These motions contribute significantly to the momentum transport in the wall-normal and spanwise directions showing potential for flow separation suppression

Voltage- and cold-dependent gating of single TRPM8 ion channels

Transient receptor potential (TRP) channels play critical roles in cell signaling by coupling various environmental factors to changes in membrane potential that modulate calcium influx. TRP channels are typically activated in a polymodal manner, thus integrating multiple stimuli. Although much progress has been made, the underlying mechanisms of TRP channel activation are largely unknown. The TRPM8 cation channel has been extensively investigated as a major neuronal cold sensor but is also activated by voltage, calcium store depletion, and some lipids as well as by compounds that produce cooling sensations, such as menthol or icilin. Several models of TRPM8 activation have been proposed to explain the interaction between these diverse stimuli. However, a kinetic scheme is not yet available that can describe the detailed single-channel kinetics to gain further insight into the underlying gating mechanism. To work toward this goal, we investigated voltage-dependent single-channel gating in cell-attached patches at two different temperatures (20 and 30°C) using HEK293 cells stably expressing TRPM8. Both membrane depolarization and cooling increased channel open probability (Po) mainly by decreasing the duration of closed intervals, with a smaller increase in the duration of open intervals. Maximum likelihood analysis of dwell times at both temperatures indicated gating in a minimum of five closed and two open states, and global fitting over a wide range of voltages identified a seven-state model that described the voltage dependence of Po, the single-channel kinetics, and the response of whole-cell currents to voltage ramps and steps. The major action of depolarization and cooling was to accelerate forward transitions between the same two sets of adjacent closed states. The seven-state model provides a general mechanism to account for TRPM8 activation by membrane depolarization at two temperatures and can serve as a starting point for further investigations of multimodal TRP activation