918 resultados para Neuronal oscillations


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The crossover between two regimes has been observed in the vertical electric transport of weakly coupled GaAs/AlAs superlattices (SLs). At fixed d.c. bias, the SLs can be triggered by illumination to switch from a regime of temporal current oscillation to the formation of a stable electric field domain. The conversion can be reversed by raising the sample temperature to about 200 K. An effective carrier injection model is proposed to explain the conversion processes, taking into account the contact resistance originating from DX centres in the n(+)-Al0.5Ga0.5As contact layers which is sensitive to light illumination and temperature. In addition, quasiperiodic oscillations have been observed at a particular d.c. bias voltage.

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The magnetotransport properties of the two-dimensional (2D) electron gas confined in a modulation-doped Zn0.80Cd0.20Se/ZnS0.06Se0.94 single quantum well structure were studied at temperatures down to 0.35 K in magnetic fields up to 7.5 T. Well resolved 2D Shubnikovde Haas (SdH) oscillations were observed, although the conductivity of the sample in the as grown state was dominated by a bulk parallel conduction layer. After removing most of the parallel conduction layer by wet chemical etching the amplitude and number of SdH oscillations increased. From the temperature dependence of the amplitude the effective mass of the electrons was estimated as 0.17 m(0). Copyright (C) 1996 Published by Elsevier Science Ltd

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We have investigated the influence of transverse magnetic field B up to 14 T at 1.6 K on the tunneling processes of electric field domains in doped weakly coupled GaAs/AlAs superlattices. Three regimes, i.e, stable field domains, current self-sustained oscillations and averaged field distribution are successively observed with increasing B. The mechanisms of switching-over among these regimes are due to B-induced modification of the dependence of the effective electron drift velocity on electric field. The simulated calculation gives a good agreement with the observed experimental results. (C) 2000 Published by Elsevier Science B.V. All rights reserved.

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We established a theoretical framework for studying nonequilibrium networks with two distinct natures essential for characterizing the global probabilistic dynamics: the underlying potential landscape and the corresponding curl flux. We applied the idea to a biochemical oscillation network and found that the underlying potential landscape for the oscillation limit cycle has a distinct closed ring valley (Mexican hat-like) shape when the fluctuations are small. This global landscape structure leads to attractions of the system to the ring valley.

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The main modes of interannal variabilities of thermocline and sea surface wind stress in the tropical Pacific and their interactions are investigated, which show the following results. (1) The thermocline anomalies in the tropical Pacific have a zonal dipole pattern with 160 W as its axis and a meridional seesaw pattern with 6-8 degrees N as its transverse axis. The meridional oscillation has a phase lag of about 90 to the zonal oscillation, both oscillations get together to form the El Nino/La Nina cycle, which behaves as a mixed layer water oscillates anticlockwise within the tropical Pacific basin between equator and 12 degrees N. (2) There are two main patterns of wind stress anomalies in the tropical Pacific, of which the first component caused by trade wind anomaly is characterized by the zonal wind stress anomalies and its corresponding divergences field in the equatorial Pacific, and the abnormal cross- equatorial flow wind stress and its corresponding divergence field, which has a sign opposite to that of the equatorial region, in the off-equator of the tropical North Pacific, and the second component represents the wind stress anomalies and corresponding divergences caused by the ITCZ anomaly. (3) The trade winds anomaly plays a decisive role in the strength and phase transition of the ENSO cycle, which results in the sea level tilting, provides an initial potential energy to the mixed layer water oscillation, and causes the opposite thermocline displacement between the west side and east side of the equator and also between the equator and 12 degrees N of the North Pacific basin, therefore determines the amplitude and route for ENSO cycle. The ITCZ anomaly has some effects on the phase transition. (4) The thermal anomaly of the tropical western Pacific causes the wind stress anomaly and extends eastward along the equator accompanied with the mixed layer water oscillation in the equatorial Pacific, which causes the trade winds anomaly and produces the anomalous wind stress and the corresponding divergence in favor to conduce the oscillation, which in turn intensifies the oscillation. The coupled system of ocean-atmosphere interactions and the inertia gravity of the mixed layer water oscillation provide together a phase-switching mechanism and interannual memory for the ENSO cycle. In conclusion, the ENSO cycle essentially is an inertial oscillation of the mixed layer water induced by both the trade winds anomaly and the coupled ocean-atmosphere interaction in the tropical Pacific basin between the equator and 12 degrees N. When the force produced by the coupled ocean-atmosphere interaction is larger than or equal to the resistance caused by the mixed layer water oscillation, the oscillation will be stronger or maintain as it is, while when the force is less than the resistance, the oscillation will be weaker, even break.

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Schrijver, C.J. and Brown, D.S., 2000, Oscillations in the magnetic field of the solar corona in response to flares near the photosphere, Astrophysical Journal, 537, L69-L72. Sponsorship: PPARC

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Chaplin, W. J.; Dumbill, A. M.; Elsworth, Y.; Isaak, G. R.; McLeod, C. P.; Miller, B. A.; New, R.; Pint?r, B., Studies of the solar mean magnetic field with the Birmingham Solar-Oscillations Network (BiSON), Monthly Notice of the Royal Astronomical Society, Volume 343, Issue 3, pp. 813-818. RAE2008

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Pint?r, B.; Erd?lyi, R.; Goossens, M., Global oscillations in a magnetic solar model. II. Oblique propagation, Astronomy and Astrophysics, Volume 466, Issue 1, April IV 2007, pp.377-388 Pint?r, B.; Erd?lyi, R.; Goossens, M., (2007) 'Global oscillations in a magnetic solar model II. Oblique propagation', Astronomy and Astrophysics 466(1) pp.377-388 RAE2008

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This article develops the Synchronous Matching Adaptive Resonance Theory (SMART) neural model to explain how the brain may coordinate multiple levels of thalamocortical and corticocortical processing to rapidly learn, and stably remember, important information about a changing world. The model clarifies how bottom-up and top-down processes work together to realize this goal, notably how processes of learning, expectation, attention, resonance, and synchrony are coordinated. The model hereby clarifies, for the first time, how the following levels of brain organization coexist to realize cognitive processing properties that regulate fast learning and stable memory of brain representations: single cell properties, such as spiking dynamics, spike-timing-dependent plasticity (STDP), and acetylcholine modulation; detailed laminar thalamic and cortical circuit designs and their interactions; aggregate cell recordings, such as current-source densities and local field potentials; and single cell and large-scale inter-areal oscillations in the gamma and beta frequency domains. In particular, the model predicts how laminar circuits of multiple cortical areas interact with primary and higher-order specific thalamic nuclei and nonspecific thalamic nuclei to carry out attentive visual learning and information processing. The model simulates how synchronization of neuronal spiking occurs within and across brain regions, and triggers STDP. Matches between bottom-up adaptively filtered input patterns and learned top-down expectations cause gamma oscillations that support attention, resonance, and learning. Mismatches inhibit learning while causing beta oscillations during reset and hypothesis testing operations that are initiated in the deeper cortical layers. The generality of learned recognition codes is controlled by a vigilance process mediated by acetylcholine.

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A neural network model of synchronized oscillations in visual cortex is presented to account for recent neurophysiological findings that such synchronization may reflect global properties of the stimulus. In these experiments, synchronization of oscillatory firing responses to moving bar stimuli occurred not only for nearby neurons, but also occurred between neurons separated by several cortical columns (several mm of cortex) when these neurons shared some receptive field preferences specific to the stimuli. These results were obtained for single bar stimuli and also across two disconnected, but colinear, bars moving in the same direction. Our model and computer simulations obtain these synchrony results across both single and double bar stimuli using different, but formally related, models of preattentive visual boundary segmentation and attentive visual object recognition, as well as nearest-neighbor and randomly coupled models.

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A neural network model of synchronized oscillator activity in visual cortex is presented in order to account for recent neurophysiological findings that such synchronization may reflect global properties of the stimulus. In these recent experiments, it was reported that synchronization of oscillatory firing responses to moving bar stimuli occurred not only for nearby neurons, but also occurred between neurons separated by several cortical columns (several mm of cortex) when these neurons shared some receptive field preferences specific to the stimuli. These results were obtained not only for single bar stimuli but also across two disconnected, but colinear, bars moving in the same direction. Our model and computer simulations obtain these synchrony results across both single and double bar stimuli. For the double bar case, synchronous oscillations are induced in the region between the bars, but no oscillations are induced in the regions beyond the stimuli. These results were achieved with cellular units that exhibit limit cycle oscillations for a robust range of input values, but which approach an equilibrium state when undriven. Single and double bar synchronization of these oscillators was achieved by different, but formally related, models of preattentive visual boundary segmentation and attentive visual object recognition, as well as nearest-neighbor and randomly coupled models. In preattentive visual segmentation, synchronous oscillations may reflect the binding of local feature detectors into a globally coherent grouping. In object recognition, synchronous oscillations may occur during an attentive resonant state that triggers new learning. These modelling results support earlier theoretical predictions of synchronous visual cortical oscillations and demonstrate the robustness of the mechanisms capable of generating synchrony.

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This article describes a. neural pattern generator based on a cooperative-competitive feedback neural network. The two-channel version of the generator supports both in-phase and anti-phase oscillations. A scalar arousal level controls both the oscillation phase and frequency. As arousal increases, oscillation frequency increases and bifurcations from in-phase to anti-phase, or anti-phase to in-phase oscillations can occur. Coupled versions of the model exhibit oscillatory patterns which correspond to the gaits used in locomotion and other oscillatory movements by various animals.

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Modern neuroscience relies heavily on sophisticated tools that allow us to visualize and manipulate cells with precise spatial and temporal control. Transgenic mouse models, for example, can be used to manipulate cellular activity in order to draw conclusions about the molecular events responsible for the development, maintenance and refinement of healthy and/or diseased neuronal circuits. Although it is fairly well established that circuits respond to activity-dependent competition between neurons, we have yet to understand either the mechanisms underlying these events or the higher-order plasticity that synchronizes entire circuits. In this thesis we aimed to develop and characterize transgenic mouse models that can be used to directly address these outstanding biological questions in different ways. We present SLICK-H, a Cre-expressing mouse line that can achieve drug-inducible, widespread, neuron-specific manipulations in vivo. This model is a clear improvement over existing models because of its particularly strong, widespread, and even distribution pattern that can be tightly controlled in the absence of drug induction. We also present SLICK-V::Ptox, a mouse line that, through expression of the tetanus toxin light chain, allows long-term inhibition of neurotransmission in a small subset (<1%) of fluorescently labeled pyramidal cells. This model, which can be used to study how a silenced cell performs in a wildtype environment, greatly facilitates the in vivo study of activity-dependent competition in the mammalian brain. As an initial application we used this model to show that tetanus toxin-expressing CA1 neurons experience a 15% - 19% decrease in apical dendritic spine density. Finally, we also describe the attempt to create additional Cre-driven mouse lines that would allow conditional alteration of neuronal activity either by hyperpolarization or inhibition of neurotransmission. Overall, the models characterized in this thesis expand upon the wealth of tools available that aim to dissect neuronal circuitry by genetically manipulating neurons in vivo.

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Huntington’s Disease (HD) is a rare autosomal dominant neurodegenerative disease caused by the expression of a mutant Huntingtin (muHTT) protein. Therefore, preventing the expression of muHTT by harnessing the specificity of the RNA interference (RNAi) pathway is a key research avenue for developing novel therapies for HD. However, the biggest caveat in the RNAi approach is the delivery of short interfering RNA (siRNAs) to neurons, which are notoriously difficult to transfect. Indeed, despite the great advances in the field of nanotechnology, there remains a great need to develop more effective and less toxic carriers for siRNA delivery to the Central Nervous System (CNS). Thus, the aim of this thesis was to investigate the utility of modified amphiphilic β-cyclodextrins (CDs), oligosaccharide-based molecules, as non-viral vectors for siRNA delivery for HD. Modified CDs were able to bind and complex siRNAs forming nanoparticles capable of delivering siRNAs to ST14A-HTT120Q cells and to human HD fibroblasts, and reducing the expression of the HTT gene in these in vitro models of HD. Moreover, direct administration of CD.siRNA nanoparticles into the R6/2 mouse brain resulted in significant HTT gene expression knockdown and selective alleviation of rotarod motor deficits in this mouse model of HD. In contrast to widely used transfection reagents, CD.siRNA nanoparticles only induced limited cytotoxic and neuroinflammatory responses in multiple brain-derived cell-lines, and also in vivo after single direct injections into the mouse brain. Alternatively, we have also described a PEGylation-based formulation approach to further stabilise CD.siRNA nanoparticles and progress towards a systemic delivery nanosystem. Resulting PEGylated CD.siRNA nanoparticles showed increased stability in physiological saltconditions and, to some extent, reduced protein-induced aggregation. Taken together, the work outlined in this thesis identifies modified CDs as effective, safe and versatile siRNA delivery systems that hold great potential for the treatment of CNS disorders, such as HD.