Magnetoelastic interaction in the two-dimensional magnetic material MnPS3_3 studied by first principles calculations and Raman experiments

We report experimental and theoretical studies on the magnetoelastic interactions in MnPS$_3$. Raman scattering response measured as a function of temperature shows a blue shift of the Raman active modes at 120.2 and 155.1 cm$^{-1}$, when the temperature is raised across the antiferromagnetic-paramagnetic transition. Density functional theory (DFT) calculations have been performed to estimate the effective exchange interactions and calculate the Raman active phonon modes. The calculations lead to the conclusion that the peculiar behavior with temperature of the two low energy phonon modes can be explained by the symmetry of their corresponding normal coordinates which involve the virtual modification of the super-exchange angles associated with the leading antiferromagnetic (AFM) interactions.Comment: Main: 9 pages, 7 figures. Supplementary : 5 pages, 4 figure

Statistical Analysis of Sleep Spindle Occurrences

Spindles - a hallmark of stage II sleep - are a transient oscillatory phenomenon in the EEG believed to reflect thalamocortical activity contributing to unresponsiveness during sleep. Currently spindles are often classified into two classes: fast spindles, with a frequency of around 14 Hz, occurring in the centro-parietal region; and slow spindles, with a frequency of around 12 Hz, prevalent in the frontal region. Here we aim to establish whether the spindle generation process also exhibits spatial heterogeneity. Electroencephalographic recordings from 20 subjects were automatically scanned to detect spindles and the time occurrences of spindles were used for statistical analysis. Gamma distribution parameters were fit to each inter-spindle interval distribution, and a modified Wald-Wolfowitz lag-1 correlation test was applied. Results indicate that not all spindles are generated by the same statistical process, but this dissociation is not spindle-type specific. Although this dissociation is not topographically specific, a single generator for all spindle types appears unlikely

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

Towards an optimization of stimulus parameters for brain-computer interfaces based on steady state visual evoked potentials.

Efforts to construct an effective brain-computer interface (BCI) system based on Steady State Visual Evoked Potentials (SSVEP) commonly focus on sophisticated mathematical methods for data analysis. The role of different stimulus features in evoking strong SSVEP is less often considered and the knowledge on the optimal stimulus properties is still fragmentary. The goal of this study was to provide insight into the influence of stimulus characteristics on the magnitude of SSVEP response. Five stimuli parameters were tested: size, distance, colour, shape, and presence of a fixation point in the middle of each flickering field. The stimuli were presented on four squares on LCD screen, with each square highlighted by LEDs flickering with different frequencies. Brighter colours and larger dimensions of flickering fields resulted in a significantly stronger SSVEP response. The distance between stimulation fields and the presence or absence of the fixation point had no significant effect on the response. Contrary to a popular belief, these results suggest that absence of the fixation point does not reduce the magnitude of SSVEP response. However, some parameters of the stimuli such as colour and the size of the flickering field play an important role in evoking SSVEP response, which indicates that stimuli rendering is an important factor in building effective SSVEP based BCI systems

On the quantification of SSVEP frequency responses in human EEG in realistic BCI conditions.

This article concerns one of the most important problems of brain-computer interfaces (BCI) based on Steady State Visual Evoked Potentials (SSVEP), that is the selection of the a-priori most suitable frequencies for stimulation. Previous works related to this problem were done either with measuring systems that have little in common with actual BCI systems (e.g., single flashing LED) or were presented on a small number of subjects, or the tested frequency range did not cover a broad spectrum. Their results indicate a strong SSVEP response around 10 Hz, in the range 13-25 Hz, and at high frequencies in the band of 40-60 Hz. In the case of BCI interfaces, stimulation with frequencies from various ranges are used. The frequencies are often adapted for each user separately. The selection of these frequencies, however, was not yet justified in quantitative group-level study with proper statistical account for inter-subject variability. The aim of this study is to determine the SSVEP response curve, that is, the magnitude of the evoked signal as a function of frequency. The SSVEP response was induced in conditions as close as possible to the actual BCI system, using a wide range of frequencies (5-30 Hz, in step of 1 Hz). The data were obtained for 10 subjects. SSVEP curves for individual subjects and the population curve was determined. Statistical analysis were conducted both on the level of individual subjects and for the group. The main result of the study is the identification of the optimal range of frequencies, which is 12-18 Hz, for the registration of SSVEP phenomena. The applied criterion of optimality was: to find the largest contiguous range of frequencies yielding the strong and constant-level SSVEP response

Subject with clear topographical separation of spindles.

<p>Amplitude-frequency plot of an example subject from the group that exhibits a clear topographical separation of low and high frequency spindles: in the frontal channel, <b>(A)</b> Fpz, most spindles do not exceed 12 Hz, with nearly no activity over 14 Hz; in the parietal channel, <b>(D)</b> Pz, most spindles fall between 13 and 16 Hz, with only a few appearing below 12 Hz.</p

Fitted shape parameter across subjects.

<p>Values of the shape parameter of fitted gamma distribution for each of the scalp locations, assembled subject-wise; unreliable fits (as assessed by the KS plot) were removed; bars denote 95% confidence bounds of fitted parameter. There is no consistent effect of location on the shape parameter that would be exhibited across subjects and that would point to two distinct statistical processes governing frontal and parietal spindles.</p

Fitted shape parameter across locations.

<p>Values of the shape parameter of fitted gamma distribution for each subject; each panel represents a different scalp location (<b>(A)</b> Fpz, <b>(B)</b> Fz, <b>(C)</b> Cz, and <b>(D)</b> Pz); unreliable fits (as assessed by the KS plot) were removed; bars denote 95% confidence bounds of fitted parameter. Shape parameter reflects the statistical nature of the generation process and, as can be seen above, most channels and most subjects exhibit hallmarks of a Poisson random process (shape parameter not different than 1).</p