Electron-impact excitation of X 1Sigma_g⁺(v[double-prime]=0) to the a[double-prime] 1Sigma_g⁺, b 1Piu, c3 1Piu, o3 1Piu, b[prime] 1Sigma_u⁺, c₄^[prime] 1Sigma_u⁺, G 3Piu, and F 3Piu states of molecular nitrogen

Measurements of differential cross sections (DCSs) for electron-impact excitation of the a[double-prime] 1Sigmag+, b 1Piu, c3 1Piu, o3 1Piu, b[prime] 1Sigmau+, c4[prime] 1Sigmau+, G 3Piu, and F 3Piu states in N2 from the X 1Sigmag+(v[double-prime]=0) ground level are presented. The DCSs were obtained from energy-loss spectra in the region of 12 to 13.82 eV measured at incident energies of 17.5, 20, 30, 50, and 100 eV and for scattering angles ranging from 2° to 130°. The analysis of the spectra follows a different algorithm from that employed in a previous study of N2 for the valence states [Khakoo et al. Phys. Rev. A 71, 062703 (2005)], since the 1Piu and 1Sigmau+ states form strongly interacting Rydberg-valence series. The results are compared with existing data

Neural population dynamics in human motor cortex during movements in people with ALS

The prevailing view of motor cortex holds that motor cortical neural activity represents muscle or movement parameters. However, recent studies in non-human primates have shown that neural activity does not simply represent muscle or movement parameters; instead, its temporal structure is well-described by a dynamical system where activity during movement evolves lawfully from an initial pre-movement state. In this study, we analyze neuronal ensemble activity in motor cortex in two clinical trial participants diagnosed with Amyotrophic Lateral Sclerosis (ALS). We find that activity in human motor cortex has similar dynamical structure to that of non-human primates, indicating that human motor cortex contains a similar underlying dynamical system for movement generation. DOI: http://dx.doi.org/10.7554/eLife.07436.00

Sleep duration and cardiometabolic outcomes in American Indians/Alaska Natives and other race/ethnicities

While there is evidence in previous epidemiological studies that sleep duration is an important contributor to morbidity and mortality, variability by race/ethnicity in the association between sleep duration and adverse health outcomes has not been extensively studied in the literature. In particular, prior studies have essentially ignored sleep duration and its association with cardiometabolic diseases within the American Indian and Alaska Native (AI/AN) population, a group that exhibits an alarmingly high rate of diabetes and relevant cardiometabolic conditions. In this dissertation, I investigated the relationship between sleep duration and cardiometabolic outcomes using two cohorts of AI/ANs: 1) a unique longitudinal lifestyle intervention project; 2) a large cross-sectional survey. The main findings of this dissertation include: 1) suboptimal sleep duration is prevalent in the AI/AN population, as with other minority populations; 2) among AI/ANs with prediabetes undergoing lifestyle intervention, those with adequate sleep benefit more from the intervention than those with short sleep duration; 3) the association between suboptimal sleep and diabetes is stronger in AI/ANs than other race/ethnic groups; and 4) adherence to a set of healthy lifestyle factors confers significant reduction in risk of diabetes and CVD in AI/ANs. This work represents an important step forward in systematically characterizing sleep duration and its cardiometabolic consequences in the AI/AN population and may have a significant impact for future public health interventions in this severely underserved population

Sleep duration and cardiometabolic outcomes in American Indians/Alaska Natives and other race/ethnicities

While there is evidence in previous epidemiological studies that sleep duration is an important contributor to morbidity and mortality, variability by race/ethnicity in the association between sleep duration and adverse health outcomes has not been extensively studied in the literature. In particular, prior studies have essentially ignored sleep duration and its association with cardiometabolic diseases within the American Indian and Alaska Native (AI/AN) population, a group that exhibits an alarmingly high rate of diabetes and relevant cardiometabolic conditions. In this dissertation, I investigated the relationship between sleep duration and cardiometabolic outcomes using two cohorts of AI/ANs: 1) a unique longitudinal lifestyle intervention project; 2) a large cross-sectional survey. The main findings of this dissertation include: 1) suboptimal sleep duration is prevalent in the AI/AN population, as with other minority populations; 2) among AI/ANs with prediabetes undergoing lifestyle intervention, those with adequate sleep benefit more from the intervention than those with short sleep duration; 3) the association between suboptimal sleep and diabetes is stronger in AI/ANs than other race/ethnic groups; and 4) adherence to a set of healthy lifestyle factors confers significant reduction in risk of diabetes and CVD in AI/ANs. This work represents an important step forward in systematically characterizing sleep duration and its cardiometabolic consequences in the AI/AN population and may have a significant impact for future public health interventions in this severely underserved population

A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm

peer reviewedMotor prostheses aim to restore function to disabled patients. Despite compelling proof of concept systems, barriers to clinical translation remain. One challenge is to develop a low-power, fully-implantable system that dissipates only minimal power so as not to damage tissue. To this end, we implemented a Kalman-filter based decoder via a spiking neural network (SNN) and tested it in brain-machine interface (BMI) experiments with a rhesus monkey. The Kalman filter was trained to predict the arm’s velocity and mapped on to the SNN using the Neural Engineer- ing Framework (NEF). A 2,000-neuron embedded Matlab SNN implementation runs in real-time and its closed-loop performance is quite comparable to that of the standard Kalman filter. The success of this closed-loop decoder holds promise for hardware SNN implementations of statistical signal processing algorithms on neu- romorphic chips, which may offer power savings necessary to overcome a major obstacle to the successful clinical translation of neural motor prostheses

Associations of sleep duration with cardiometabolic outcomes in American Indians and Alaska Natives and other race/ethnicities: results from the BRFSS.

OBJECTIVES: This study assessed the associations between short and long sleep duration and prevalence of cardiometabolic outcomes in American Indians and Alaska Natives (AI/ANs) and compared these associations to those evident among other race/ethnicities. METHODS: We analyzed data from the 2013-2014 Behavioral Risk Factor Surveillance System. In total, 14,536 AI/ANs, 729,962 non-Hispanic whites, 71,765 blacks, and 59,472 Hispanics were included. Logistic regressions were conducted to compute unadjusted and adjusted odds ratios (OR) for the associations of interest. RESULTS: Among AI/ANs, 38.6% reported sleeping <7 hours per night (short sleepers) while 39.3% reported 8+ hours of sleep (long sleepers). After adjusting for age and gender, both short and long sleep durations were associated with higher odds of reporting diabetes, stroke, coronary heart disease and heart attack in almost all race/ethnic groups. After multiple adjustments, the sleep-diabetes association was more pronounced (OR = 1.71 and OR = 1.56 for short and long sleepers, respectively) among AI/ANs than other race/ethnicities. CONCLUSIONS: Future studies are warranted to examine race/ethnic variability in the association between sleep duration and cardiometabolic outcomes

A Brain-Machine Interface with an Innovative Spiking Neural Network Decoder

Motor prostheses aim to restore functions lost to neurological disease and injury by translating neural signals into control signals for prosthetic limbs. Despite compelling proof of concept systems, barriers to clinical translation—mainly strict power dissipation constraints—still remain. The proposed solution is to use the ultra-low-power neuromorphic approach to potentially meet these constraints