Large-scale Spatiotemporal Spike Patterning Consistent with Wave Propagation in Motor Cortex

Aggregate signals in cortex are known to be spatiotemporally organized as propagating waves across the cortical surface, but it remains unclear whether the same is true for spiking activity in individual neurons. Furthermore, the functional interactions between cortical neurons are well documented but their spatial arrangement on the cortical surface has been largely ignored. Here we use a functional network analysis to demonstrate that a subset of motor cortical neurons in non-human primates spatially coordinate their spiking activity in a manner that closely matches wave propagation measured in the beta oscillatory band of the local field potential. We also demonstrate that sequential spiking of pairs of neuron contains task-relevant information that peaks when the neurons are spatially oriented along the wave axis. We hypothesize that the spatial anisotropy of spike patterning may reflect the underlying organization of motor cortex and may be a general property shared by other cortical areas

The robustness of speech representations obtained from simulated auditory nerve fibers under different noise conditions

Different methods of extracting speech features from an auditory model were systematically investigated in terms of their robustness to different noises. The methods either computed the average firing rate within frequency channels (spectral features) or inter-spike-intervals (timing features) from the simulated auditory nerve response. When used as the front-end for an automatic speech recognizer, timing features outperformed spectral features in Gaussian noise. However, this advantage was lost in babble, because timing features extracted the spectro-temporal structure of babble noise, which is similar to the target speaker. This suggests that different feature extraction methods are optimal depending on the background noise

Towards understanding interactions between Sustainable Development Goals: the role of environment–human linkages

Only 10 years remain to achieve all Sustainable Development Goals (SDGs) globally, so there is a growing need to increase the effectiveness and efficiency of action by targeting multiple SDGs. The SDGs were conceived as an ‘indivisible whole’, but interactions between SDGs need to be better understood. Several previous assessments have begun to explore interactions including synergies and possible conflicts between the SDGs, and differ widely in their conclusions. Although some highlight the role of the more environmentally-focused SDGs in underpinning sustainable development, none specifically focuses on environment-human linkages. Assessing interactions between SDGs, and the influence of environment on them, can make an important contribution to informing decisions in 2020 and beyond. Here, we review previous assessments of interactions among SDGs, apply an influence matrix to assess pairwise interactions between all SDGs, and show how viewing these from the perspective of environment-human linkages can influence the outcome. Environment, and environment-human linkages, influence most interactions between SDGs. Our action-focused assessment enables decision makers to focus environmental management to have the greatest impacts, and to identify opportunities to build on synergies and reduce trade-offs between particular SDGs. It may enable sectoral decision makers to seek support from environment managers for achieving their goals. We explore cross-cutting issues and the relevance and potential application of our approach in supporting decision making for progress to achieve the SDGs

Formation and Disruption of W-Phase in High-Entropy Alloys

High-entropy alloys (HEAs) are single-phase systems prepared from equimolar or near-equimolar concentrations of at least five principal elements. The combination of high mixing entropy, severe lattice distortion, sluggish diffusion and cocktail effect favours the formation of simple phases—usually a bcc or fcc matrix with minor inclusions of ordered binary intermetallics. HEAs have been proposed for applications in which high temperature stability (including mechanical and chemical stability under high temperature and high mechanical impact) is required. On the other hand, the major challenge to overcome for HEAs to become commercially attractive is the achievement of lightweight alloys of extreme hardness and low brittleness. The multicomponent AlCrCuScTi alloy was prepared and characterized using powder X-ray diffraction (PXRD), scanning-electron microscope (SEM) and atomic-force microscope equipped with scanning Kelvin probe (AFM/SKP) techniques. Results show that the formation of complex multicomponent ternary intermetallic compounds upon heating plays a key role in phase evolution. The formation and degradation of W-phase, Al2Cu3Sc, in the AlCrCuScTi alloy plays a crucial role in its properties and stability. Analysis of as-melted and annealed alloy suggests that the W-phase is favoured kinetically, but thermodynamically unstable. The disruption of the W-phase in the alloy matrix has a positive effect on hardness (890 HV), density (4.83 g·cm−3) and crack propagation. The hardness/density ratio obtained for this alloy shows a record value in comparison with ordinary heavy refractory HEAs

Dynamical Mass Constraints on Low-Mass Pre-Main-Sequence Stellar Evolutionary Tracks: An Eclipsing Binary in Orion with a 1.0 Msun Primary and an 0.7 Msun Secondary

We report the discovery of a double-lined, spectroscopic, eclipsing binary in the Orion star-forming region. We analyze the system spectroscopically and photometrically to empirically determine precise, distance-independent masses, radii, effective temperatures, and luminosities for both components. The measured masses for the primary and secondary, accurate to ~1%, are 1.01 Msun and 0.73 Msun, respectively; thus the primary is a definitive pre-main-sequence solar analog, and the secondary is the lowest-mass star yet discovered among pre-main-sequence eclipsing binary systems. We use these fundamental measurements to test the predictions of pre-main-sequence stellar evolutionary tracks. None of the models we examined correctly predict the masses of the two components simultaneously, and we implicate differences between the theoretical and empirical effective temperature scales for this failing. All of the models predict the observed slope of the mass-radius relationship reasonably well, though the observations tend to favor models with low convection efficiencies. Indeed, considering our newly determined mass measurements together with other dynamical mass measurements of pre-main-sequence stars in the literature, as well as measurements of Li abundances in these stars, we show that the data strongly favor evolutionary models with inefficient convection in the stellar interior, even though such models cannot reproduce the properties of the present-day Sun.Comment: Accepted by Ap