Early Cold Stored Platelet Transfusion Following Severe Injury: A Randomized Clinical Trial.

OBJECTIVE: To determine the feasibility, efficacy, and safety of early cold stored platelet transfusion compared to standard care resuscitation in patients with hemorrhagic shock. SUMMARY BACKGROUND DATA: Data demonstrating the safety and efficacy of early cold stored platelet transfusion are lacking following severe injury. METHODS: A phase 2, multicenter, randomized, open label, clinical trial was performed at five U.S. trauma centers. Injured patients at risk of large volume blood transfusion and the need for hemorrhage control procedures were enrolled and randomized. The intervention was the early transfusion of a single apheresis cold stored platelet unit, stored for up to 14 days vs. standard care resuscitation. The primary outcome was feasibility and the principal clinical outcome for efficacy and safety was 24-hour mortality. RESULTS: Mortality at 24 hours was 5.9% in patients who were randomized to early cold stored platelet transfusion compared to 10.2% in the standard care arm (difference, -4.3%; 95% CI, -12.8% to 3.5%; P=0.26). No significant differences were found for any of the prespecified ancillary outcomes. Rates of arterial and/or venous thromboembolism and adverse events did not differ across treatment groups. CONCLUSIONS AND RELEVANCE: In severely injured patients, early cold stored platelet transfusion is feasible, safe and did not result in a significant lower rate of 24-hour mortality. Early cold stored platelet transfusion did not result in a higher incidence of arterial and/or venous thrombotic complications or adverse events. The storage age of the cold stored platelet product was not associated with significant outcome differences.

Creating a neuroprosthesis for active tactile exploration of textures.

Intracortical microstimulation (ICMS) of the primary somatosensory cortex (S1) can produce percepts that mimic somatic sensation and, thus, has potential as an approach to sensorize prosthetic limbs. However, it is not known whether ICMS could recreate active texture exploration-the ability to infer information about object texture by using one's fingertips to scan a surface. Here, we show that ICMS of S1 can convey information about the spatial frequencies of invisible virtual gratings through a process of active tactile exploration. Two rhesus monkeys scanned pairs of visually identical screen objects with the fingertip of a hand avatar-controlled first via a joystick and later via a brain-machine interface-to find the object with denser virtual gratings. The gratings consisted of evenly spaced ridges that were signaled through individual ICMS pulses generated whenever the avatar's fingertip crossed a ridge. The monkeys learned to interpret these ICMS patterns, evoked by the interplay of their voluntary movements and the virtual textures of each object, to perform a sensory discrimination task. Discrimination accuracy followed Weber's law of just-noticeable differences (JND) across a range of grating densities; a finding that matches normal cutaneous sensation. Moreover, 1 monkey developed an active scanning strategy where avatar velocity was integrated with the ICMS pulses to interpret the texture information. We propose that this approach could equip upper-limb neuroprostheses with direct access to texture features acquired during active exploration of natural objects.

Cortical Stimulation Induces Network-Wide Coherence Change In Non-Human Primate Somatosensory Cortex.

Stimulation of the cortex can modulate the connectivity between brain regions. Although targeted neuroplasticity has been demonstrated in-vitro, in-vivo models have been inconsistent in their response to stimulation. In this paper, we tested various stimulation protocols to characterize the effect of stimulation on coherence in the non-human primate cortex in-vivo. We found that the stimulation latency, the state of the cortex during stimulation, and the stimulation site all affected the modulation of cortical coherence. We further investigated features of a resting-state network that could predict how a connection is likely to change with stimulation.

Superior arm-movement decoding from cortex with a new, unsupervised-learning algorithm.

OBJECTIVE: The aim of this work is to improve the state of the art for motor-control with a brain-machine interface (BMI). BMIs use neurological recording devices and decoding algorithms to transform brain activity directly into real-time control of a machine, archetypically a robotic arm or a cursor. The standard procedure treats neural activity-vectors of spike counts in small temporal windows-as noisy observations of the kinematic state (position, velocity, acceleration) of the fingertip. Inferring the state from the observations then takes the form of a dynamical filter, typically some variant on Kalman's (KF). The KF, however, although fairly robust in practice, is optimal only when the relationships between variables are linear and the noise is Gaussian, conditions usually violated in practice. APPROACH: To overcome these limitations we introduce a new filter, the 'recurrent exponential-family harmonium' (rEFH), that models the spike counts explicitly as Poisson-distributed, and allows for arbitrary nonlinear dynamics and observation models. Furthermore, the model underlying the filter is acquired through unsupervised learning, which allows temporal correlations in spike counts to be explained by latent dynamics that do not necessarily correspond to the kinematic state of the fingertip. MAIN RESULTS: We test the rEFH on offline reconstruction of the kinematics of reaches in the plane. The rEFH outperforms the standard, as well as three other state-of-the-art, decoders, across three monkeys, two different tasks, most kinematic variables, and a range of bin widths, amounts of training data, and numbers of neurons. SIGNIFICANCE: Our algorithm establishes a new state of the art for offline decoding of reaches-in particular, for fingertip velocities, the variable used for control in most online decoders.

A learning-based approach to artificial sensory feedback leads to optimal integration.

Proprioception-the sense of the body's position in space-is important to natural movement planning and execution and will likewise be necessary for successful motor prostheses and brain-machine interfaces (BMIs). Here we demonstrate that monkeys were able to learn to use an initially unfamiliar multichannel intracortical microstimulation signal, which provided continuous information about hand position relative to an unseen target, to complete accurate reaches. Furthermore, monkeys combined this artificial signal with vision to form an optimal, minimum-variance estimate of relative hand position. These results demonstrate that a learning-based approach can be used to provide a rich artificial sensory feedback signal, suggesting a new strategy for restoring proprioception to patients using BMIs, as well as a powerful new tool for studying the adaptive mechanisms of sensory integration.

Expanding the primate body schema in sensorimotor cortex by virtual touches of an avatar.

The brain representation of the body, called the body schema, is susceptible to plasticity. For instance, subjects experiencing a rubber hand illusion develop a sense of ownership of a mannequin hand when they view it being touched while tactile stimuli are simultaneously applied to their own hand. Here, the cortical basis of such an embodiment was investigated through concurrent recordings from primary somatosensory (i.e., S1) and motor (i.e., M1) cortical neuronal ensembles while two monkeys observed an avatar arm being touched by a virtual ball. Following a period when virtual touches occurred synchronously with physical brushes of the monkeys' arms, neurons in S1 and M1 started to respond to virtual touches applied alone. Responses to virtual touch occurred 50 to 70 ms later than to physical touch, consistent with the involvement of polysynaptic pathways linking the visual cortex to S1 and M1. We propose that S1 and M1 contribute to the rubber hand illusion and that, by taking advantage of plasticity in these areas, patients may assimilate neuroprosthetic limbs as parts of their body schema.

An adaptable system for improving transposon-based gene expression in vivo via transient transgene repression.

Transposons permit permanent cellular genome engineering in vivo. However, transgene expression falls rapidly postdelivery due to a variety of mechanisms, including immune responses. We hypothesized that delaying initial transgene expression would improve long-term transgene expression by using an engineered piggyBac transposon system that can regulate expression. We found that a 2-part nonviral Tet-KRAB inducible expression system repressed expression of a luciferase reporter in vitro. However, we also observed nonspecific promoter-independent repression. Thus, to achieve temporary transgene repression after gene delivery in vivo, we utilized a nonintegrating version of the repressor plasmid while the gene of interest was delivered in an integrating piggyBac transposon vector. When we delivered the luciferase transposon and repressor to immunocompetent mice by hydrodynamic injection, initial luciferase expression was repressed by 2 orders of magnitude. When luciferase expression was followed long term in vivo, we found that expression was increased >200-fold compared to mice that received only the luciferase transposon and piggyBac transposase. We found that repression of early transgene expression could prevent the priming of luciferase-specific T cells in vivo. Therefore, transient transgene repression postgene delivery is an effective strategy for inhibiting the antitransgene immune response and improving long-term expression in vivo without using immunosuppression.

piggyBac transposon system modification of primary human T cells.

The piggyBac transposon system is naturally active, originally derived from the cabbage looper moth. This non-viral system is plasmid based, most commonly utilizing two plasmids with one expressing the piggyBac transposase enzyme and a transposon plasmid harboring the gene(s) of interest between inverted repeat elements which are required for gene transfer activity. PiggyBac mediates gene transfer through a "cut and paste" mechanism whereby the transposase integrates the transposon segment into the genome of the target cell(s) of interest. PiggyBac has demonstrated efficient gene delivery activity in a wide variety of insect, mammalian, and human cells6 including primary human T cells. Recently, a hyperactive piggyBac transposase was generated improving gene transfer efficiency. Human T lymphocytes are of clinical interest for adoptive immunotherapy of cancer. Of note, the first clinical trial involving transposon modification of human T cells using the Sleeping beauty transposon system has been approved. We have previously evaluated the utility of piggyBac as a non-viral methodology for genetic modification of human T cells. We found piggyBac to be efficient in genetic modification of human T cells with a reporter gene and a non-immunogenic inducible suicide gene. Analysis of genomic integration sites revealed a lack of preference for integration into or near known proto-oncogenes. We used piggyBac to gene-modify cytotoxic T lymphocytes to carry a chimeric antigen receptor directed against the tumor antigen HER2, and found that gene-modified T cells mediated targeted killing of HER2-positive tumor cells in vitro and in vivo in an orthotopic mouse model. We have also used piggyBac to generate human T cells resistant to rapamycin, which should be useful in cancer therapies where rapamycin is utilized. Herein, we describe a method for using piggyBac to genetically modify primary human T cells. This includes isolation of peripheral blood mononuclear cells (PBMCs) from human blood followed by culture, gene modification, and activation of T cells. For the purpose of this report, T cells were modified with a reporter gene (eGFP) for analysis and quantification of gene expression by flow cytometry. PiggyBac can be used to modify human T cells with a variety of genes of interest. Although we have used piggyBac to direct T cells to tumor antigens, we have also used piggyBac to add an inducible safety switch in order to eliminate gene modified cells if needed. The large cargo capacity of piggyBac has also enabled gene transfer of a large rapamycin resistant mTOR molecule (15 kb). Therefore, we present a non-viral methodology for stable gene-modification of primary human T cells for a wide variety of purposes.

Stochastic facilitation of artificial tactile sensation in primates.

Artificial sensation via electrical or optical stimulation of brain sensory areas offers a promising treatment for sensory deficits. For a brain-machine-brain interface, such artificial sensation conveys feedback signals from a sensorized prosthetic limb. The ways neural tissue can be stimulated to evoke artificial sensation and the parameter space of such stimulation, however, remain largely unexplored. Here we investigated whether stochastic facilitation (SF) could enhance an artificial tactile sensation produced by intracortical microstimulation (ICMS). Two rhesus monkeys learned to use a virtual hand, which they moved with a joystick, to explore virtual objects on a computer screen. They sought an object associated with a particular artificial texture (AT) signaled by a periodic ICMS pattern delivered to the primary somatosensory cortex (S1) through a pair of implanted electrodes. During each behavioral trial, aperiodic ICMS (i.e., noise) of randomly chosen amplitude was delivered to S1 through another electrode pair implanted 1 mm away from the site of AT delivery. Whereas high-amplitude noise worsened AT detection, moderate noise clearly improved the detection of weak signals, significantly raising the proportion of correct trials. These findings suggest that SF could be used to enhance prosthetic sensation.

High-side digitally current controlled biphasic bipolar microstimulator.

Electrical stimulation of nervous tissue has been extensively used as both a tool in experimental neuroscience research and as a method for restoring of neural functions in patients suffering from sensory and motor disabilities. In the central nervous system, intracortical microstimulation (ICMS) has been shown to be an effective method for inducing or biasing perception, including visual and tactile sensation. ICMS also holds promise for enabling brain-machine-brain interfaces (BMBIs) by directly writing information into the brain. Here we detail the design of a high-side, digitally current-controlled biphasic, bipolar microstimulator, and describe the validation of the device in vivo. As many applications of this technique, including BMBIs, require recording as well as stimulation, we pay careful attention to isolation of the stimulus channels and parasitic current injection. With the realized device and standard recording hardware-without active artifact rejection-we are able to observe stimulus artifacts of less than 2 ms in duration.

Hyperactive piggyBac gene transfer in human cells and in vivo.

We characterized a recently developed hyperactive piggyBac (pB) transposase enzyme [containing seven mutations (7pB)] for gene transfer in human cells in vitro and to somatic cells in mice in vivo. Despite a protein level expression similar to that of native pB, 7pB significantly increased the gene transfer efficiency of a neomycin resistance cassette transposon in both HEK293 and HeLa cultured human cells. Native pB and SB100X, the most active transposase of the Sleeping Beauty transposon system, exhibited similar transposition efficiency in cultured human cell lines. When delivered to primary human T cells ex vivo, 7pB increased gene delivery two- to threefold compared with piggyBac and SB100X. The activity of hyperactive 7pB transposase was not affected by the addition of a 24-kDa N-terminal tag, whereas SB100X manifested a 50% reduction in transposition. Hyperactive 7pB was compared with native pB and SB100X in vivo in mice using hydrodynamic tail-vein injection of a limiting dose of transposase DNA combined with luciferase reporter transposons. We followed transgene expression for up to 6 months and observed approximately 10-fold greater long-term gene expression in mice injected with a codon-optimized version of 7pB compared with mice injected with native pB or SB100X. We conclude that hyperactive piggyBac elements can increase gene transfer in human cells and in vivo and should enable improved gene delivery using the piggyBac transposon system in a variety of cell and gene-therapy applications.

Virtual active touch using randomly patterned intracortical microstimulation.

Intracortical microstimulation (ICMS) has promise as a means for delivering somatosensory feedback in neuroprosthetic systems. Various tactile sensations could be encoded by temporal, spatial, or spatiotemporal patterns of ICMS. However, the applicability of temporal patterns of ICMS to artificial tactile sensation during active exploration is unknown, as is the minimum discriminable difference between temporally modulated ICMS patterns. We trained rhesus monkeys in an active exploration task in which they discriminated periodic pulse-trains of ICMS (200 Hz bursts at a 10 Hz secondary frequency) from pulse trains with the same average pulse rate, but distorted periodicity (200 Hz bursts at a variable instantaneous secondary frequency). The statistics of the aperiodic pulse trains were drawn from a gamma distribution with mean inter-burst intervals equal to those of the periodic pulse trains. The monkeys distinguished periodic pulse trains from aperiodic pulse trains with coefficients of variation 0.25 or greater. Reconstruction of movement kinematics, extracted from the activity of neuronal populations recorded in the sensorimotor cortex concurrent with the delivery of ICMS feedback, improved when the recording intervals affected by ICMS artifacts were removed from analysis. These results add to the growing evidence that temporally patterned ICMS can be used to simulate a tactile sense for neuroprosthetic devices.

Active tactile exploration using a brain-machine-brain interface.

Brain-machine interfaces use neuronal activity recorded from the brain to establish direct communication with external actuators, such as prosthetic arms. It is hoped that brain-machine interfaces can be used to restore the normal sensorimotor functions of the limbs, but so far they have lacked tactile sensation. Here we report the operation of a brain-machine-brain interface (BMBI) that both controls the exploratory reaching movements of an actuator and allows signalling of artificial tactile feedback through intracortical microstimulation (ICMS) of the primary somatosensory cortex. Monkeys performed an active exploration task in which an actuator (a computer cursor or a virtual-reality arm) was moved using a BMBI that derived motor commands from neuronal ensemble activity recorded in the primary motor cortex. ICMS feedback occurred whenever the actuator touched virtual objects. Temporal patterns of ICMS encoded the artificial tactile properties of each object. Neuronal recordings and ICMS epochs were temporally multiplexed to avoid interference. Two monkeys operated this BMBI to search for and distinguish one of three visually identical objects, using the virtual-reality arm to identify the unique artificial texture associated with each. These results suggest that clinical motor neuroprostheses might benefit from the addition of ICMS feedback to generate artificial somatic perceptions associated with mechanical, robotic or even virtual prostheses.

Adaptive decoding for brain-machine interfaces through Bayesian parameter updates.

Brain-machine interfaces (BMIs) transform the activity of neurons recorded in motor areas of the brain into movements of external actuators. Representation of movements by neuronal populations varies over time, during both voluntary limb movements and movements controlled through BMIs, due to motor learning, neuronal plasticity, and instability in recordings. To ensure accurate BMI performance over long time spans, BMI decoders must adapt to these changes. We propose the Bayesian regression self-training method for updating the parameters of an unscented Kalman filter decoder. This novel paradigm uses the decoder's output to periodically update its neuronal tuning model in a Bayesian linear regression. We use two previously known statistical formulations of Bayesian linear regression: a joint formulation, which allows fast and exact inference, and a factorized formulation, which allows the addition and temporary omission of neurons from updates but requires approximate variational inference. To evaluate these methods, we performed offline reconstructions and closed-loop experiments with rhesus monkeys implanted cortically with microwire electrodes. Offline reconstructions used data recorded in areas M1, S1, PMd, SMA, and PP of three monkeys while they controlled a cursor using a handheld joystick. The Bayesian regression self-training updates significantly improved the accuracy of offline reconstructions compared to the same decoder without updates. We performed 11 sessions of real-time, closed-loop experiments with a monkey implanted in areas M1 and S1. These sessions spanned 29 days. The monkey controlled the cursor using the decoder with and without updates. The updates maintained control accuracy and did not require information about monkey hand movements, assumptions about desired movements, or knowledge of the intended movement goals as training signals. These results indicate that Bayesian regression self-training can maintain BMI control accuracy over long periods, making clinical neuroprosthetics more viable.

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.

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.

PiggyBac transposon-based inducible gene expression in vivo after somatic cell gene transfer.

Somatic cell gene transfer has permitted inducible gene expression in vivo through coinfection of multiple viruses. We hypothesized that the highly efficient plasmid-based piggyBac transposon system would enable long-term inducible gene expression in mice in vivo. We used a multiple-transposon delivery strategy to create a tetracycline-inducible expression system in vitro in human cells by delivering the two genes on separate transposons for inducible reporter gene expression along with a separate selectable transposon marker. Evaluation of stable cell lines revealed 100% of selected clones exhibited inducible expression via stable expression from three separate transposons simultaneously. We next tested and found that piggyBac-mediated gene transfer to liver or lung could achieve stable reporter gene expression in mice in vivo in either immunocompetent or immune deficient animals. A single injection of piggyBac transposons could achieve long-term inducible gene expression in the livers of mice in vivo, confirming our multiple-transposon strategy used in cultured cells. The plasmid-based piggyBac transposon system enables constitutive or inducible gene expression in vivo for potential therapeutic and biological applications without using viral vectors.

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.

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.

Decoding of temporal intervals from cortical ensemble activity.

Neurophysiological, neuroimaging, and lesion studies point to a highly distributed processing of temporal information by cortico-basal ganglia-thalamic networks. However, there are virtually no experimental data on the encoding of behavioral time by simultaneously recorded cortical ensembles. We predicted temporal intervals from the activity of hundreds of neurons recorded in motor and premotor cortex as rhesus monkeys performed self-timed hand movements. During the delay periods, when animals had to estimate temporal intervals and prepare hand movements, neuronal ensemble activity encoded both the time that elapsed from the previous hand movement and the time until the onset of the next. The neurons that were most informative of these temporal intervals increased or decreased their rates throughout the delay until reaching a threshold value, at which point a movement was initiated. Variability in the self-timed delays was explainable by the variability of neuronal rates, but not of the threshold. In addition to predicting temporal intervals, the same neuronal ensemble activity was informative for generating predictions that dissociated the delay periods of the task from the movement periods. Left hemispheric areas were the best source of predictions in one bilaterally implanted monkey overtrained to perform the task with the right hand. However, after that monkey learned to perform the task with the left hand, its left hemisphere continued and the right hemisphere started contributing to the prediction. We suggest that decoding of temporal intervals from bilaterally recorded cortical ensembles could improve the performance of neural prostheses for restoration of motor function.