Publications by authors named "Joel Burdick"

Having observed that electrical spinal cord stimulation and training enabled four patients with paraplegia with motor complete paralysis to regain voluntary leg movement, the underlying mechanisms involved in forming the newly established supraspinal-spinal functional connectivity have become of great interest. van den Brand et al. ( 336: 1182-1185, 2012) subsequently, demonstrated the recovery, in response to spinal electro-neuromodulation and locomotor training, of voluntary stepping of the lower limbs in rats that received a lesion that is assumed to eliminate all long-descending cortical axons that project to lumbosacral segments.

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Spinal cord stimulation (SCS) has enabled motor recovery in paraplegics with motor complete spinal cord injury (SCI). However, the physiological mechanisms underlying this recovery are unknown. This paper analyzes muscle synergies in two motor complete SCI patients under SCS during standing and compares them with muscle synergies in healthy subjects, in order to help elucidate the mechanisms that enable motor control through SCS.

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Muscle synergies encode motor activity as a linear superposition of multiple motor units composed of a temporal command exciting a specific network of muscles. This study examines muscle synergies derived from simple standing studies of a complete spinal cord injury (SCI) patient under epidural spinal stimulation. A popular technique for extracting these synergies from EMG data is non-negative matrix factorization (NNMF).

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Neuromodulation of spinal networks can improve motor control after spinal cord injury (SCI). The objectives of this study were to (1) determine whether individuals with chronic paralysis can stand with the aid of non-invasive electrical spinal stimulation with their knees and hips extended without trainer assistance, and (2) investigate whether postural control can be further improved following repeated sessions of stand training. Using a double-blind, balanced, within-subject cross-over, and sham-controlled study design, 15 individuals with SCI of various severity received transcutaneous electrical spinal stimulation to regain self-assisted standing.

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Electrical neuromodulation of spinal networks improves the control of movement of the paralyzed limbs after spinal cord injury (SCI). However, the potential of noninvasive spinal stimulation to facilitate postural trunk control during sitting in humans with SCI has not been investigated. We hypothesized that transcutaneous electrical stimulation of the lumbosacral enlargement can improve trunk posture.

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Epidural electrostimulation has shown promise for spinal cord injury therapy. However, finding effective stimuli on the multi-electrode stimulating arrays employed requires a laborious manual search of a vast space for each patient. Widespread clinical application of these techniques would be greatly facilitated by an autonomous, algorithmic system which choses stimuli to simultaneously deliver effective therapy and explore this space.

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Isolating action potentials of a single neuron (unit) is essential for intra-cortical neurophysiological recordings. Yet, during extracellular recordings in semi-chronic awake preparations, the relationship between neuronal soma and the recording electrode is typically not stationary. Neuronal waveforms often change in shape, and in the absence of counter-measures, merge with the background noise.

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Background: Repeated periods of stimulation of the spinal cord and training increased the ability to control movement in animal models of spinal cord injury. We hypothesised that tonic epidural spinal cord stimulation can modulate spinal circuitry in human beings into a physiological state that enables sensory input from standing and stepping movements to serve as a source of neural control to undertake these tasks.

Methods: A 23-year-old man who had paraplegia from a C7-T1 subluxation as a result of a motor vehicle accident in July 2006, presented with complete loss of clinically detectable voluntary motor function and partial preservation of sensation below the T1 cord segment.

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When proteolytic enzymes were first introduced to common laundry detergents in the 1960s, their ability to cause hypersensitivity due to exposure by inhalation was soon recognized as a problem, especially for production workers. Subsequently, formulations and manufacturing methods were developed to minimize exposure to enzymes via inhaled dust particles. Although detergents containing proteases are now considered safe for consumers, the experience with laundry pre-spotter products is not as extensive.

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This paper develops a method to determine the minimum duration interval which ensures that the process of "sorting" the extracellular action potentials recorded during that interval achieves a desired confidence level of accuracy. During the recording process, a sequential decision theory approach continually evaluates a variant of the likelihood ratio test using the model evidence of the sorting/clustering hypotheses. The test is compared against a threshold which encodes a desired confidence level on the accuracy of the subsequent clustering procedure.

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Over the past 20 years, tremendous advances have been made in the field of spinal cord injury research. Yet, consumed with individual pieces of the puzzle, we have failed as a community to grasp the magnitude of the sum of our findings. Our current knowledge should allow us to improve the lives of patients suffering from spinal cord injury.

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This paper introduces a new, unsupervised method for sorting and tracking the action potentials of individual neurons in multiunit extracellular recordings. Presuming the data are divided into short, sequential recording intervals, the core of our strategy relies upon an extension of a traditional mixture model approach that incorporates clustering results from the preceding interval in a Bayesian manner, while still allowing for signal nonstationarity and changing numbers of recorded neurons. As a natural byproduct of the sorting method, current and prior signal clusters can be matched over time in order to track persisting neurons.

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The fruit fly Drosophila melanogaster is a widely used model organism in studies of genetics, developmental biology and biomechanics. One limitation for exploiting Drosophila as a model system for behavioral neurobiology is that measuring body kinematics during behavior is labor intensive and subjective. In order to quantify flight kinematics during different types of maneuvers, we have developed a visual tracking system that estimates the posture of the fly from multiple calibrated cameras.

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The zebrafish Danio rerio is a widely used model organism in studies of genetics, developmental biology, and recently, biomechanics. In order to quantify changes in swimming during all stages of development, we have developed a visual tracking system that estimates the posture of fish. Our current approach assumes planar motion of the fish, given image sequences taken from a top view.

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For a complete adult spinal rat to regain some weight-bearing stepping capability, it appears that a sequence of specific proprioceptive inputs that are similar, but not identical, from step to step must be generated over repetitive step cycles. Furthermore, these cycles must include the activation of specific neural circuits that are intrinsic to the lumbosacral spinal cord segments. For these sensorimotor pathways to be effective in generating stepping, the spinal circuitry must be modulated to an appropriate excitability level.

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Active sensing organisms, such as bats, dolphins, and weakly electric fish, generate a 3-D space for active sensation by emitting self-generated energy into the environment. For a weakly electric fish, we demonstrate that the electrosensory space for prey detection has an unusual, omnidirectional shape. We compare this sensory volume with the animal's motor volume--the volume swept out by the body over selected time intervals and over the time it takes to come to a stop from typical hunting velocities.

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This paper presents a method for model based automated tracking of multiple worm-like creatures. These methods are essential for accurate quantitative analysis into the genetic basis of behavior that involve more than one organism. An accurate worm model is designed using the geometry of planar curves and nonlinear estimation of the model's parameters are performed using a central difference Kalman filter (CDKF).

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This work presents a new multi-site probe array applied with parylene technology, used for neural prostheses to record high-level cognitive neural signals. Instead of inorganic materials (e.g.

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Robotic training paradigms that enforce a fixed kinematic control might be suboptimal for rehabilitative training because they abolish variability, an intrinsic property of neuromuscular control (Jezernik et al., 2003). In the present study we introduce "assist-as-needed" (AAN) robotic training paradigms for rehabilitation of spinal cord injury subjects.

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Reliable exposure information for cosmetic and other personal care products and ingredients is needed in order to conduct safety assessments. Essential information includes both the amount of product applied, and the frequency of use. To obtain current data, studies to assess consumer use practices were undertaken.

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This paper develops a control algorithm that can autonomously position an electrode so as to find and then maintain an optimal extracellular recording position. The algorithm was developed and tested in a two-neuron computational model representative of the cells found in cerebral cortex. The algorithm is based on a stochastic optimization of a suitably defined signal quality metric and is shown capable of finding the optimal recording position along representative sampling directions, as well as maintaining the optimal signal quality in the face of modeled tissue movements.

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In the present study, concurrent treatment with robotic step training and a serotonin agonist, quipazine, generated significant recovery of locomotor function in complete spinal cord-transected mice (T7-T9) that otherwise could not step. The extent of recovery achieved when these treatments were combined exceeded that obtained when either treatment was applied independently. We quantitatively analyzed the stepping characteristics of spinal mice after alternatively administering no training, manual training, robotic training, quipazine treatment, or a combination of robotic training with quipazine treatment, to examine the mechanisms by which training and quipazine treatment promote functional recovery.

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This paper combines wavelet transforms with basic detection theory to develop a new unsupervised method for robustly detecting and localizing spikes in noisy neural recordings. The method does not require the construction of templates, or the supervised setting of thresholds. We present extensive Monte Carlo simulations, based on actual extracellular recordings, to show that this technique surpasses other commonly used methods in a wide variety of recording conditions.

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A system was developed that can autonomously position recording electrodes to isolate and maintain optimal quality extracellular signals. The system consists of a novel motorized miniature recording microdrive and a control algorithm. The microdrive was designed for chronic operation and can independently position four glass-coated Pt-Ir electrodes with micrometer precision over a 5-mm range using small (3 mm diam) piezoelectric linear actuators.

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The prospect of assisting disabled patients by translating neural activity from the brain into control signals for prosthetic devices, has flourished in recent years. Current systems rely on neural activity present during natural arm movements. We propose here that neural activity present before or even without natural arm movements can provide an important, and potentially advantageous, source of control signals.

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