Conclusions and Clinical Relevance-Dogs with complications were more likely to have had intracranial lesions than were dogs without complications, but few dogs had severe complications. Abnormal mentation was more common in dogs with than in dogs without complications. Prospective studies to further evaluate perianesthetic risk factors and procedures for improving outcomes in these patients are warranted.”
“Strongly correlated electronic systems in the quantum Hall regime start displaying very strong magnetotransport anisotropy at certain low values of the Torin 2 cost magnetic field below a given critical temperature. The ultimate

nature of this emergent anisotropic quantum Hall phase is still elusive despite a decade of studies since their experimental discovery in high mobility

GaAs/AlGaAs heterostructures. So far, anisotropy has been observed only in high Landau levels with quantum index n >= 2 and is more pronounced at half-filling of the upper Landau level. Despite the efforts, many questions about the microscopic origin of anisotropy and the physical mechanism of stabilization of anisotropic phases still remain. One way to explain the emergence of anisotropy is to assume that the electrons have formed a unidirectional (or striped) charge density wave state and this path has been followed by many authors. Another scenario consistent with the experimental findings would view the appearance of anisotropy as signature of a phase transition of electrons

selleckchem from an isotropic phase to an anisotropic liquid crystalline phase similar to an isotropic-to-nematic liquid transition. In this work we study the anisotropy of the state with filling factor nu=9/2 in which the Landau level with index n=2 is half-filled while the lower Landau levels of each spin are full and considered inert thus causing no Landau level mixing. (C) 2010 American Institute of Physics. [doi:10.1063/1.3355394]“
“Temporal integration of input is essential to the accumulation of information GSK923295 in various cognitive and behavioral processes, and gradually increasing neuronal activity, typically occurring within a range of seconds, is considered to reflect such computation by the brain. Some psychological evidence suggests that temporal integration by the brain is nearly perfect, that is, the integration is non-leaky, and the output of a neural integrator is accurately proportional to the strength of input. Neural mechanisms of perfect temporal integration, however, remain largely unknown. Here, we propose a recurrent network model of cortical neurons that perfectly integrates partially correlated, irregular input spike trains. We demonstrate that the rate of this temporal integration changes proportionately to the probability of spike coincidences in synaptic inputs.