178 research outputs found
Analysis of the magnetization switching using the rotational hysteresis integral
No full textThe relation of the rotational hysteresis integral with the magnetization switching mode is experimentally analysed in materials which are subjected to different treatments which can modify the magnetization switching mode. As expected, the value of the integral depends on the basic processes of magnetization. They evolve with the evolution of the switching in the expected way, both when the switching changes from wall motion to rotation of the magnetization, and when, in single-domain particles, the rotation occurs with different reversal modes. © 1999 Elsevier Science B.V. All rights reserved
Stellate cell computational modeling predicts signal filtering in the molecular layer circuit of cerebellum
No full textThe functional properties of cerebellar stellate cells and the way they regulate molecular layer activity are still unclear. We have measured stellate cells electroresponsiveness and their activation by parallel fiber bursts. Stellate cells showed intrinsic pacemaking, along with characteristic responses to depolarization and hyperpolarization, and showed a marked short-term facilitation during repetitive parallel fiber transmission. Spikes were emitted after a lag and only at high frequency, making stellate cells to operate as delay-high-pass filters. A detailed computational model summarizing these physiological properties allowed to explore different functional configurations of the parallel fiber—stellate cell—Purkinje cell circuit. Simulations showed that, following parallel fiber stimulation, Purkinje cells almost linearly increased their response with input frequency, but such an increase was inhibited by stellate cells, which leveled the Purkinje cell gain curve to its 4 Hz value. When reciprocal inhibitory connections between stellate cells were activated, the control of stellate cells over Purkinje cell discharge was maintained only at very high frequencies. These simulations thus predict a new role for stellate cells, which could endow the molecular layer with low-pass and band-pass filtering properties regulating Purkinje cell gain and, along with this, also burst delay and the burst-pause responses pattern
Realistic Models of Cerebellar Stellate Neurons Predicts Intrinsic Excitability and the Impact of Synaptic Inputs.
No full textThe cerebellar stellate cells (SC) are inhibitory interneurons located in the molecular layer (ML) of the cerebellum. These cells receive excitatory inputs from parallel fibers (pf) and their branched axons make inhibitory synapses with Purkinje cells and other SCs. We reconstructed a multi-compartmental biophysically realistic SC model in Python-NEURON (Python 2.7; NEURON 7.5) to investigate the SC electrophysiological properties. 3D morphologies of mouse neurons were reconstructed from fluorescent images obtained with a confocal microscope and analyzed with Neurolucida. Ionic channels were located on the morphology compartments according to immunohistochemistry data. The maximum ionic conductances (Gi-max) were tuned to match the firing pattern revealed by electrophysiological recordings in mice cerebellar slices using patch-clamp techniques. SC discharges elicited by step current injections were used as templates to extract the features needed to assess the fitness function for the optimization procedure. Gi-max tuning was performed by automatic parameter estimation algorithms, using the multi-objective genetic algorithm in Blue Brain Python Optimisation Library (BluePyOpt). Optimized models reproduced the experimental results, showing spontaneous firing, an almost linear I/O relationship following positive somatic current injections, sag in hyperpolarizing direction following negative current injections, synaptic responses and PSTH following pf inputs and synchronization through gap-junctions. The optimization technique gave satisfactory results, reproducing SC electrophysiological behaviors. The model provided a valuable tool to further investigate the SC function in cerebellar network activity
GPU Parallelization of Realistic Purkinje Cells with Complex Morphology
No full textHigh performance computing (HPC) is becoming mandatory for the simulation of complex and realistic neuronal models. The development of such realistic models will allow to discover innovative therapies and to study brain diseases without undertaking invasive experiments that are not always possible. However, the models complexity requires adopting suitable technologies in order to provide results in short times, hopefully in real-time. To address this issue, the authors decided to exploit Graphics Processing Units (GPUs) in order to develop a realistic and morphologically detailed Purkinje cell model. This paper describes the simulation of the Purkinje cell activity adopting both single and multi-GPU strategy, together with the exploitation of different NVIDIA architectures. Results shows that the simulation times of 10000 cells is reduced from 13 days and 18 hours to about 2 hours
Model simulations unveil the structure-function-dynamics relationship of the cerebellar cortical microcircuit
No full textThe cerebellar network is renowned for its regular architecture that has inspired foundational computational theories. However, the relationship between circuit structure, function and dynamics remains elusive. To tackle the issue, we developed an advanced computational modeling framework that allows us to reconstruct and simulate the structure and function of the mouse cerebellar cortex using morphologically realistic multi-compartmental neuron models. The cerebellar connectome is generated through appropriate connection rules, unifying a collection of scattered experimental data into a coherent construct and providing a new model-based ground-truth about circuit organization. Naturalistic background and sensory-burst stimulation are used for functional validation against recordings in vivo, monitoring the impact of cellular mechanisms on signal propagation, inhibitory control, and long-term synaptic plasticity. Our simulations show how mossy fibers entrain the local neuronal microcircuit, boosting the formation of columns of activity travelling from the granular to the molecular layer providing a new resource for the investigation of local microcircuit computation and of the neural correlates of behavior
Coincidence detection between apical and basal dendrites drives STDP in cerebellar Golgi cells
No full textCerebellar Golgi cells (GoCs), segregate parallel fiber (pf), and mossy fiber (mf) inputs on apical and basal dendrites. Computational modeling predicted that this anatomical arrangement, coupled with a specific ionic channel localization, could be instrumental to drive STDP at mf-GoC synapses. Here, we test this hypothesis with GoC patch-clamp recordings in acute mouse cerebellar slices. Repeated mf-pf pairing on the theta-band within a ± 50 ms time window induces anti-symmetric Hebbian-STDP, with spike-timing long-term potentiation or depression (st-LTP or st-LTD) occurring when action potentials (APs) elicited by pf stimulation follow or precede the activation of mf synapses, respectively. Mf-GoC STDP induction requires AP backpropagation from apical to basal dendrites, NMDA receptor activation at mf-GoC synapses, and intracellular calcium changes. Importantly, STDP is inverted by inhibitory control. Thus, experimental evidence confirms and extends model predictions suggesting that GoC STDP can bind molecular layer to granular layer activity, regulating cerebellar computation and learning
Ostracod valves from core sediments collected in Brbinj, Dugi Otok, Dalmatian coast, Croatia.
No full text(1) Cyprideis torosa f. littoralis (Jones 1850) left valve (LV); (2–3) Aurila woodwardi (Brady 1868), (2) right valve (RV), (3) LV; (4) Leptocythere lagunae Hartmann 1958 RV; (5) Leptocythere cf. bacescoi (Rome 1942) RV; (6) Leptocythere cf. bituberculata Bonaduce, Ciampo and Masoli 1976 LV; (7) Callistocythere cf. adriatica Masoli 1968 RV; (8) Xestoleberis communis Müller 1894 RV; (9) Loxoconcha rhomboidea (Fischer 1855) LV; (10) Loxoconcha cf. ovulata (Costa 1853) RV; (11) Loxoconcha cf. elliptica Brady 1868 juvenile, LV.</p
The effect of multiple anisotropies in fine particles
No full textTo investigate the effects of multiple anisotropies, morphology and size on magnetic properties of fine particles, cobalt-modified materials with different shapes were tested at temperatures from liquid nitrogen to 400 K. Some interesting and original conclusions were drawn: (a) When multiple easy axes are available, thermal fluctuations can induce the magnetization to switch from one axis to the other; the overall effect will be an increase of the fraction of particles with superparamagnetic behaviour. (b) The phenomenon will be greater for materials where the conflicting anisotropy constants are similar (isotropic particles); thus, for a given composition, the lower the shape anisotropy and the larger the superparamagnetic fraction. (c) Porosity and particle defects will contribute to increase the super-paramagnetic fraction. (d) In practical media (tapes) the effect of the superparamagnetic fraction is much lower than expected: a "constricted magnetization" phenomenon could account for such behaviour. (e) The lack of interactions predicted for truly isotropic media is experimentally verified only at extremely low temperatures. (f) Partial orientation in the plane of the strongest anisotropy axis must be taken into account for explaining the behaviour of SFD; under such assumption, "quasi-spherical" particles will behave quite differently from elongated ones. (g) Rotational hysteresis, CF and (1 - S*) for isotropic particles seems to indicate that the rotational mechanism might not be accounted for by known models. © 1984
Single Neuron Optimization as a Basis for Accurate Biophysical Modeling: The Case of Cerebellar Granule Cells
No full textIn realistic neuronal modeling, once the ionic channel complement has been defined, the maximum ionic conductance (Gi-max) values need to be tuned in order to match the firing pattern revealed by electrophysiological recordings. Recently, selection/mutation genetic algorithms have been proposed to efficiently and automatically tune these parameters. Nonetheless, since similar firing patterns can be achieved through different combinations of Gi-max values, it is not clear how well these algorithms approximate the corresponding properties of real cells. Here we have evaluated the issue by exploiting a unique opportunity offered by the cerebellar granule cell (GrC), which is electrotonically compact and has therefore allowed the direct experimental measurement of ionic currents. Previous models were constructed using empirical tuning of Gi-max values to match the original data set. Here, by using repetitive discharge patterns as a template, the optimization procedure yielded models that closely approximated the experimental Gi-max values. These models, in addition to repetitive firing, captured additional features, including inward rectification, near-threshold oscillations, and resonance, which were not used as features. Thus, parameter optimization using genetic algorithms provided an efficient modeling strategy for reconstructing the biophysical properties of neurons and for the subsequent reconstruction of large-scale neuronal network models.BBP-COR
Experimental study on the production of high density electron bunches from a GaAs photocathode
No full textIn order to obtain a high charge, low emittance electron source, useful for FEL electron injector and for e+ e− collider experiments, we performed a test experiment on a gallium arsenide photocathode, activated by negative electron affinity technique and illuminated with a 10 ns long laser pulse of 532 nm wavelength. We measured a maximum charge delivered, at relatively low potentials, of about 18 nC/bunch. The mean lifetime is greater than 60 h
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