Probing spin dynamics and quantum relaxation in LiY0.998Ho0.002F4 via 19F NMR

We report measurements of 19F nuclear spin-lattice relaxation 1/T1 as a function of temperature and external magnetic field in LiY0.998Ho0.002F4 single crystal, a single-ion magnet exhibiting interesting quantum effects. The 19F 1/T1 is found to depend on the coupling with the diluted rare-earth (RE) moments. Depending on the temperature range, a fast spin diffusion regime or a diffusion limited regime is encountered. In both cases we find it possible to use the 19F nucleus as a probe of the rare-earth spin dynamics. The results for 1/T1 show a behavior similar to that observed in molecular nanomagnets, a result which we attribute to the discreteness of the energy levels in both cases. At intermediate temperatures the lifetime broadening of the crystal field split RE magnetic levels follows a T3 power law. At low temperature the field dependence of 1/T1 shows peaks in correspondence to the critical magnetic fields for energy level crossings (LC). The results can be explained by inelastic scattering between the fluorine nuclear spins and the RE magnetic levels. A key result of this study is that the broadening of the levels at LC is found to be become extremely small at low temperatures, about 1.7 mT, a value which is comparable to the weak dipolar fields at the RE lattice positions. Thus, unlike the molecular magnets, decoherence effects are strongly suppressed, and it may be possible to measure directly the level repulsions at avoided level crossings.Comment: 21 pages, 5 figure

Decoding the activity of neuronal populations in macaque primary visual cortex

Visual function depends on the accuracy of signals carried by visual cortical neurons. Combining information across neurons should improve this accuracy because single neuron activity is variable. We examined the reliability of information inferred from populations of simultaneously recorded neurons in macaque primary visual cortex. We considered a decoding framework that computes the likelihood of visual stimuli from a pattern of population activity by linearly combining neuronal responses and tested this framework for orientation estimation and discrimination. We derived a simple parametric decoder assuming neuronal independence and a more sophisticated empirical decoder that learned the structure of the measured neuronal response distributions, including their correlated variability. The empirical decoder used the structure of these response distributions to perform better than its parametric variant, indicating that their structure contains critical information for sensory decoding. These results show how neuronal responses can best be used to inform perceptual decision-making

Fermi-liquid effects in the Fulde-Ferrell-Larkin-Ovchinnikov state of two-dimensional d-wave superconductors

We study the effects of Fermi-liquid interactions on quasi-two-dimensional d-wave superconductors in a magnetic field. The phase diagram of the superconducting state, including the periodic Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) state in high magnetic fields, is discussed for different strengths of quasiparticle many-body interactions within Landau's theory of Fermi liquids. Decreasing the Fermi-liquid parameter $F_0^a$ causes the magnetic spin susceptibility to increase, which in turn leads to a reduction of the FFLO phase. It is shown that a negative $F_0^a$ results in a first-order phase transition from the normal to the uniform superconducting state in a finite temperature interval. Finally, we discuss the thermodynamic implications of a first-order phase transition for CeCoIn$_5$.Comment: published version; removed direct comparison with experiment for the upper critical field, as required by the referee

Brain–machine interface for eye movements

A number of studies in tetraplegic humans and healthy nonhuman primates (NHPs) have shown that neuronal activity from reach-related cortical areas can be used to predict reach intentions using brain–machine interfaces (BMIs) and therefore assist tetraplegic patients by controlling external devices (e.g., robotic limbs and computer cursors). However, to our knowledge, there have been no studies that have applied BMIs to eye movement areas to decode intended eye movements. In this study, we recorded the activity from populations of neurons from the lateral intraparietal area (LIP), a cortical node in the NHP saccade system. Eye movement plans were predicted in real time using Bayesian inference from small ensembles of LIP neurons without the animal making an eye movement. Learning, defined as an increase in the prediction accuracy, occurred at the level of neuronal ensembles, particularly for difficult predictions. Population learning had two components: an update of the parameters of the BMI based on its history and a change in the responses of individual neurons. These results provide strong evidence that the responses of neuronal ensembles can be shaped with respect to a cost function, here the prediction accuracy of the BMI. Furthermore, eye movement plans could be decoded without the animals emitting any actual eye movements and could be used to control the position of a cursor on a computer screen. These findings show that BMIs for eye movements are promising aids for assisting paralyzed patients

From neuronal populations to behavior: a computational journey

Cognitive behaviors originate in the responses of neuronal populations. We have a reasonable understanding of how the activity of a single neuron can be related to a specific behavior. However, it is still unclear how more complex behaviors are inferred from the responses of neuronal populations. This is a particularly timely problem because multi-neuronal recording techniques have recently become increasingly available, simultaneously spurring advances in the analysis of neuronal population data. These developments are, however, constrained by the challenges of combining theoretical and experimental approaches because both approaches have their unique set of constraints. A solution to this problem is to design computational models that are either derived or inspired by cortical computations

Strong correlation effects and optical conductivity in electron doped cuprates

We demonstrate that most features ascribed to strong correlation effects in various spectroscopies of the cuprates are captured by a calculation of the self-energy incorporating effects of spin and charge fluctuations. The self energy is calculated over the full doping range of electron-doped cuprates from half filling to the overdoped system. The spectral function reveals four subbands, two widely split incoherent bands representing the remnant of the split Hubbard bands, and two additional coherent, spin- and charge-dressed in-gap bands split by a spin-density wave, which collapses in the overdoped regime. The incoherent features persist to high doping, producing a remnant Mott gap in the optical spectra, while transitions between the in-gap states lead to pseudogap features in the mid-infrared.Comment: 5 pages, 4 figure

Microscopic evidence for field-induced magnetism in CeCoIn5_5

We present NMR data in the normal and superconducting states of CeCoIn$_5$ for fields close to $H_{\rm c2}(0)=11.8$ T in the $ab$ plane. Recent experiments identified a first-order transition from the normal to superconducting state for $H> 10.5$ T, and a new thermodynamic phase below 290 mK within the superconducting state. We find that the Knight shifts of the In(1), In(2) and the Co are discontinuous across the first-order transition and the magnetic linewidths increase dramatically. The broadening differs for the three sites, unlike the expectation for an Abrikosov vortex lattice, and suggests the presence of static spin moments in the vortex cores. In the low-temperature and high-field phase the broad NMR lineshapes suggest ordered local moments, rather than a long wavelength quasiparticle spin density modulation expected for an FFLO phase.Comment: 4 pages, 4 figures. to appear in Phys. Rev. Let

Atmospheric transport and deposition of Indonesian volcanic emissions

International audienceA regional climate model has been used to study the transport and deposition of sulfur (SO2 and SO42-) and PbCl2 emissions from Indonesian volcanoes. The sensitivity of the atmospheric loss of these trace species to meteorological conditions and their solubility was examined. Two experiments were conducted: 1) volcanic sulfur released as primarily SO2 and subject to transport, deposition, and oxidation to SO42-; and 2) PbCl2 released as an infinitely soluble passive tracer subject to only transport and deposition. The first experiment was used to calculate SO2 loss rates from each active Indonesian volcano producing an annual mean loss rate for all volcanoes of 1.1×10-5 s-1, or an e-folding rate of approximately 1 day. SO2 loss rate was found to vary seasonally, be poorly correlated with wind speed, and uncorrelated with temperature or relative humidity. The variability of SO2 loss rates is found to be correlated with the variability of wind speeds, suggesting that it is much more difficult to establish a "typical'' SO2 loss rate for volcanoes that are exposed to changeable winds. Within an average distance of 70 km away from the active Indonesian volcanoes, 53% of SO2 loss is due to conversion to SO42-, 42% due to dry deposition, and 5% due to lateral transport away from the dominant direction of plume travel. The solubility of volcanic emissions in water is shown to influence their atmospheric transport and deposition. High concentrations of PbCl2 are predicted to be deposited near to the volcanoes while volcanic S travels further away until removal from the atmosphere primarily via the wet deposition of H2SO4. The ratio of the concentration of PbCl2 to SO2 is found to exponentially decay at increasing distance from the volcanoes. The more rapid removal of highly soluble species should be considered when observing SO2 in an aged plume and relating this concentration to other volcanic species. An assumption that the ratio between the concentrations of highly soluble volcanic compounds and SO2 within a plume is equal to that observed in fumarolic gases is reasonable at small distances from the volcanic vent, but will result in an underestimation of the emission flux of highly soluble species

Predicting oculomotor behaviour from correlated populations of posterior parietal neurons

Oculomotor function critically depends on how signals representing saccade direction and eye position are combined across neurons in the lateral intraparietal (LIP) area of the posterior parietal cortex. Here we show that populations of parietal neurons exhibit correlated variability, and that using these interneuronal correlations yields oculomotor predictions that are more accurate and also less uncertain. The structure of LIP population responses is therefore essential for reliable read-out of oculomotor behaviour