A Brain-Machine Interface Instructed by Direct Intracortical Microstimulation

Brain–machine interfaces (BMIs) establish direct communication between the brain and artificial actuators. As such, they hold considerable promise for restoring mobility and communication in patients suffering from severe body paralysis. To achieve this end, future BMIs must also provide a means for delivering sensory signals from the actuators back to the brain. Prosthetic sensation is needed so that neuroprostheses can be better perceived and controlled. Here we show that a direct intracortical input can be added to a BMI to instruct rhesus monkeys in choosing the direction of reaching movements generated by the BMI. Somatosensory instructions were provided to two monkeys operating the BMI using either: (a) vibrotactile stimulation of the monkey's hands or (b) multi-channel intracortical microstimulation (ICMS) delivered to the primary somatosensory cortex (S1) in one monkey and posterior parietal cortex (PP) in the other. Stimulus delivery was contingent on the position of the computer cursor: the monkey placed it in the center of the screen to receive machine–brain recursive input. After 2 weeks of training, the same level of proficiency in utilizing somatosensory information was achieved with ICMS of S1 as with the stimulus delivered to the hand skin. ICMS of PP was not effective. These results indicate that direct, bi-directional communication between the brain and neuroprosthetic devices can be achieved through the combination of chronic multi-electrode recording and microstimulation of S1. We propose that in the future, bidirectional BMIs incorporating ICMS may become an effective paradigm for sensorizing neuroprosthetic devices

Informative g-Priors for Logistic Regression

Eliciting information from experts for use in constructing prior distributions for logistic regression coefficients can be challenging. The task is especially difficult when the model contains many predictor variables, because the expert is asked to provide summary information about the probability of “success” for many subgroups of the population. Often, however, experts are confident only in their assessment of the population as a whole. This paper is about incorporating such overall information easily into a logistic regression data analysis using g-priors. We present a version of the g-prior such that the prior distribution on the overall population logistic regression probabilities of success can be set to match a beta distribution. A simple data augmentation formulation allows implementation in standard statistical software packages.Keywords: Generalized linear model, Prior elicitation, Binomial regressio

Unscented Kalman Filter for Brain-Machine Interfaces

Brain machine interfaces (BMIs) are devices that convert neural signals into commands to directly control artificial actuators, such as limb prostheses. Previous real-time methods applied to decoding behavioral commands from the activity of populations of neurons have generally relied upon linear models of neural tuning and were limited in the way they used the abundant statistical information contained in the movement profiles of motor tasks. Here, we propose an n-th order unscented Kalman filter which implements two key features: (1) use of a non-linear (quadratic) model of neural tuning which describes neural activity significantly better than commonly-used linear tuning models, and (2) augmentation of the movement state variables with a history of n-1 recent states, which improves prediction of the desired command even before incorporating neural activity information and allows the tuning model to capture relationships between neural activity and movement at multiple time offsets simultaneously. This new filter was tested in BMI experiments in which rhesus monkeys used their cortical activity, recorded through chronically implanted multielectrode arrays, to directly control computer cursors. The 10th order unscented Kalman filter outperformed the standard Kalman filter and the Wiener filter in both off-line reconstruction of movement trajectories and real-time, closed-loop BMI operation

Applying phylogenomics to understand the emergence of Shiga Toxin producing Escherichia coli O157:H7 strains causing severe human disease in the United Kingdom

Shiga Toxin producing Escherichia coli (STEC) O157:H7 is a recently emerged zoonotic pathogen with considerable morbidity. Since the serotype emerged in the 1980s, research has focussed on unravelling the evolutionary events from the E. coli O55:H7 ancestor to the contemporaneous globally dispersed strains. In this study the genomes of over 1000 isolates from human clinical cases and cattle, spanning the history of STEC O157:H7 in the United Kingdom were sequenced. Phylogenetic analysis reveals the ancestry, key acquisition events and global context of the strains. Dated phylogenies estimate the time to the most recent common ancestor of the current circulating global clone to 175 years ago, followed by rapid diversification. We show the acquisition of specific virulence determinates occurred relatively recently and coincides with its recent detection in the human population. Using clinical outcome data from 493 cases of STEC O157:H7 we assess the relative risk of severe disease including HUS from each of the defined clades in the population and show the dramatic effect Shiga toxin complement has on virulence. We describe two strain replacement events that have occurred in the cattle population in the UK over the last 30 years; one resulting in a highly virulent strain that has accounted for the majority of clinical cases in the UK over the last decade. This work highlights the need to understand the selection pressures maintaining Shiga-toxin encoding bacteriophages in the ruminant reservoir and the study affirms the requirement for close surveillance of this pathogen in both ruminant and human populations

Availability of Advance Care Planning Documentation for Older Emergency Department Patients: A Cross-Sectional Study

Introduction: Increasing advance care planning (ACP) among older adults is a national priority. Documentation of ACP in the electronic health record (EHR) is particularly important during emergency care

Drought drove forest decline and dune building in eastern upper Michigan, USA, as the upper Great Lakes became closed basins

Current models of landscape response to Holocene climate change in midcontinent North America largely reconcile Earth orbital and atmospheric climate forcing with pollen-based forest histories on the east and eolian chronologies in Great Plains grasslands on the west. However, thousands of sand dunes spread across 12,000 km2 in eastern upper Michigan (EUM), more than 500 km east of the present forest-prairie ecotone, present a challenge to such models. We use 65 optically stimulated luminescence (OSL) ages on quartz sand deposited in silt caps (n = 8) and dunes (n = 57) to document eolian activity in EUM. Dune building was widespread ca. 10–8 ka, indicating a sharp, sustained decline in forest cover during that period. This decline was roughly coincident with hydrologic closure of the upper Great Lakes, but temporally inconsistent with most pollen-based models that imply canopy closure throughout the Holocene. Early Holocene forest openings are rarely recognized in pollen sums from EUM because faint signatures of non-arboreal pollen are largely obscured by abundant and highly mobile pine pollen. Early Holocene spikes in nonarboreal pollen are recorded in cores from small ponds, but suggest only a modest extent of forest openings. OSL dating of dune emplacement provides a direct, spatially explicit archive of greatly diminished forest cover during a very dry climate in eastern midcontinent North America ca. 10–8 ka

The Southern Proper Motion Program IV. The SPM4 Catalog

We present the fourth installment of the Yale/San Juan Southern Proper Motion Catalog, SPM4. The SPM4 contains absolute proper motions, celestial coordinates, and (B,V) photometry for over 103 million stars and galaxies between the south celestial pole and -20 deg declination. The catalog is roughly complete to V=17.5 and is based on photographic and CCD observations taken with the Yale Southern Observatory's double-astrograph at Cesco Observatory in El Leoncito, Argentina. The proper-motion precision, for well-measured stars, is estimated to be 2 to 3 mas/yr, depending on the type of second-epoch material. At the bright end, proper motions are on the International Celestial Reference System by way of Hipparcos Catalog stars, while the faint end is anchored to the inertial system using external galaxies. Systematic uncertainties in the absolute proper motions are on the order of 1 mas/yr.Comment: 34 pages, 8 figures, 3 tables; accepted for publication in AJ; note - modified author list and acknowledgements sectio

Future developments in brain-machine interface research

Neuroprosthetic devices based on brain-machine interface technology hold promise for the restoration of body mobility in patients suffering from devastating motor deficits caused by brain injury, neurologic diseases and limb loss. During the last decade, considerable progress has been achieved in this multidisciplinary research, mainly in the brain-machine interface that enacts upper-limb functionality. However, a considerable number of problems need to be resolved before fully functional limb neuroprostheses can be built. To move towards developing neuroprosthetic devices for humans, brain-machine interface research has to address a number of issues related to improving the quality of neuronal recordings, achieving stable, long-term performance, and extending the brain-machine interface approach to a broad range of motor and sensory functions. Here, we review the future steps that are part of the strategic plan of the Duke University Center for Neuroengineering, and its partners, the Brazilian National Institute of Brain-Machine Interfaces and the École Polytechnique Fédérale de Lausanne (EPFL) Center for Neuroprosthetics, to bring this new technology to clinical fruition