Brain Control of Movement Execution Onset Using Local Field Potentials in Posterior Parietal Cortex

The precise control of movement execution onset is essential for safe and autonomous cortical motor prosthetics. A recent study from the parietal reach region (PRR) suggested that the local field potentials (LFPs) in this area might be useful for decoding execution time information because of the striking difference in the LFP spectrum between the plan and execution states (Scherberger et al., 2005). More specifically, the LFP power in the 0–10 Hz band sharply rises while the power in the 20–40 Hz band falls as the state transitions from plan to execution. However, a change of visual stimulus immediately preceded reach onset, raising the possibility that the observed spectral change reflected the visual event instead of the reach onset. Here, we tested this possibility and found that the LFP spectrum change was still time locked to the movement onset in the absence of a visual event in self-paced reaches. Furthermore, we successfully trained the macaque subjects to use the LFP spectrum change as a "go" signal in a closed-loop brain-control task in which the animals only modulated the LFP and did not execute a reach. The execution onset was signaled by the change in the LFP spectrum while the target position of the cursor was controlled by the spike firing rates recorded from the same site. The results corroborate that the LFP spectrum change in PRR is a robust indicator for the movement onset and can be used for control of execution onset in a cortical prosthesis

Interstellar and Ejecta Dust in the Cas A Supernova Remnant

Infrared continuum observations provide a means of investigating the physical composition of the dust in the ejecta and swept up medium of the Cas A supernova remnant. Using low resolution Spitzer IRS spectra (5-35 $\mu$m), and broad-band Herschel PACS imaging (70, 100, and 160 $\mu$m), we identify characteristic dust spectra, associated with ejecta layers that underwent distinct nuclear burning histories. The most luminous spectrum exhibits strong emission features at $\sim9$ and 21 $\mu$m and is closely associated with ejecta knots with strong Ar emission lines. The dust features can be reproduced by magnesium silicate grains with relatively low Mg to Si ratios. Another dust spectrum is associated with ejecta having strong Ne emission lines. It has no indication of any silicate features, and is best fit by Al$_2$O$_3$ dust. A third characteristic dust spectrum shows features that are best matched by magnesium silicates with a relatively high Mg to Si ratio. This dust is primarily associated with the X-ray emitting shocked ejecta, but it is also evident in regions where shocked interstellar or circumstellar material is expected. However, the identification of dust composition is not unique, and each spectrum includes an additional featureless dust component of unknown composition. Colder dust of indeterminate composition is associated with emission from the interior of the SNR, where the reverse shock has not yet swept up and heated the ejecta. Most of the dust mass in Cas A is associated with this unidentified cold component, which is $\lesssim0.1$ $M_{\odot}$. The mass of warmer dust is only $\sim 0.04$ $M_{\odot}$.Comment: 45 pages. 21 Figures. Accepted for publication in Ap

Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range

Value-at-Risk (VaR) is commonly used for financial risk measurement. It has recently become even more important, especially during the 2008-09 global financial crisis. We propose some novel nonlinear threshold conditional autoregressive VaR (CAViaR) models that incorporate intra-day price ranges. Model estimation and inference are performed using the Bayesian approach via the link with the Skewed-Laplace distribution. We examine how a range of risk models perform during the 2008-09 financial crisis, and evaluate how the crisis affects the performance of risk models via forecasting VaR. Empirical analysis is conducted on five Asia-Pacific Economic Cooperation stock market indices as well as two exchange rate series. We examine violation rates, back-testing criteria, market risk charges and quantile loss function values to measure and assess the forecasting performance of a variety of risk models. The proposed threshold CAViaR model, incorporating range information, is shown to forecast VaR more efficiently than other models, across the series considered, which should be useful for financial practitioners.Value-at-Risk; CAViaR model; Skewed-Laplace distribution; intra-day range; backtesting; Markov chain Monte Carlo

Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range

Value-at-Risk (VaR) is commonly used for financial risk measurement. It has recently become even more important, especially during the 2008-09 global financial crisis. We pro- pose some novel nonlinear threshold conditional autoregressive VaR (CAViaR) models that incorporate intra-day price ranges. Model estimation and inference are performed using the Bayesian approach via the link with the Skewed-Laplace distribution. We examine how a range of risk models perform during the 2008-09 financial crisis, and evaluate how the crisis aects the performance of risk models via forecasting VaR. Empirical analysis is conducted on five Asia-Pacific Economic Cooperation stock market indices as well as two exchange rate series. We examine violation rates, back-testing criteria, market risk charges and quantile loss function values to measure and assess the forecasting performance of a variety of risk models. The proposed threshold CAViaR model, incorporating range information, is shown to forecast VaR more eficiently than other models, across the series considered, which should be useful for financial practitioners.Value-at-Risk; CAViaR model; Skewed-Laplace distribution; intra-day range; backtesting, Markov chain Monte Carlo.

Cognitively driven brain machine control using neural signals in the parietal reach region

This study demonstrates that the spiking and local field potential (LFP) activity in the parietal reach region (PRR) of the macaque monkey can be jointly used to control the location of the computer cursor when the correct target location must be inferred symbolically, e.g., leftward arrow for the leftward target, etc. The average correct target acquisition rate during this brain machine control task without actual movements was 86% for the six discrete target locations when using spikes and LFPs from 16 electrodes. This performance was significantly better than using spikes or LFPs alone. These results, together with our previous findings, suggest that a single decoder based on both spikes and LFPs in PRR can robustly provide the subjects’ motor intent under varying contexts for neural prosthetic applications

Climate Policy Under Fat‐Tailed Risk: An Application of Dice. ESRI WP403. August 2011

Uncertainty plays a significant role in evaluating climate policy, and fat‐tailed uncertainty may dominate policy advice. Should we make our utmost effort to prevent the arbitrarily large impacts of climate change under deep uncertainty? In order to answer to this question we propose an new way of investigating the impact of (fat‐tailed) uncertainty on optimal climate policy: the curvature of carbon tax against the uncertainty. We find that the optimal carbon tax increases as the uncertainty about climate sensitivity increases, but it does not accelerate as implied by Weitzman’s Dismal Theorem. We find the same result in a wide variety of sensitivity analyses. These results emphasize the importance of balancing of the costs and the benefits of climate policy, also under deep uncertainty

Webs of Lagrangian Tori in Projective Symplectic Manifolds

For a Lagrangian torus A in a simply-connected projective symplectic manifold M, we prove that M has a hypersurface disjoint from a deformation of A. This implies that a Lagrangian torus in a compact hyperk\"ahler manifold is a fiber of an almost holomorphic Lagrangian fibration, giving an affirmative answer to a question of Beauville's. Our proof employs two different tools: the theory of action-angle variables for algebraically completely integrable Hamiltonian systems and Wielandt's theory of subnormal subgroups.Comment: 18 pages, minor latex problem fixe