Formation of a novel supraspinal-spinal connectome that relearns the same motor task after complete paralysis.

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. (Science 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. Here, we used a similar spinal lesion in rats to eliminate long-descending axons to determine whether a novel, trained motor behavior triggered by a unique auditory cue learned before a spinal lesion, could recover after the lesion. Hindlimb stepping recovered 1 mo after the spinal injury, but only after 2 mo, the novel and unique audio-triggered behavior was recovered, meaning that not only was a novel connectivity formed but also further evidence suggested that this highly unique behavioral response was independent of the recovery of the circuitry that generated stepping. The unique features of the newly formed supraspinal-spinal connections that mediated the recovery of the trained behavior is consistent with a guidance mechanism(s) that are highly use dependent.NEW & NOTEWORTHY Electrical spinal cord stimulation has enabled patients with paraplegia to regain voluntary leg movement, and so the underlying mechanisms involved in this recovery are of great interest. Here, we demonstrate in rodents the recovery of trained motor behavior after a spinal lesion. Rodents were trained to kick their right hindlimb in response to an auditory cue. This behavior recovered 2 mo after the paralyzing spinal cord injury but only with the assistance of electrical spinal cord stimulation.

Motor Control After Human SCI Through Activation of Muscle Synergies Under Spinal Cord Stimulation.

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. One challenge is that standard muscle synergy extraction algorithms, such as non-negative matrix factorization (NMF), fail when applied to SCI patients under SCS. We develop a new algorithm-rShiftNMF-to extract muscle synergies in these cases. We find muscle synergies extracted by rShiftNMF are significantly better at interpreting electromyography (EMG) activity, and resulting synergy features are more physiologically meaningful. By analyzing muscle synergies from SCI patients and healthy subjects, we find that: 1) SCI patients rely significantly on muscle synergy activation to generate motor activity; 2) interleaving SCS can selectively activate an additional muscle synergy that is critical to SCI standing; and 3) muscle synergies extracted from SCI patients under SCS differ substantially from those extracted from healthy subjects. We provide evidence that after spinal cord injury, SCS influences motor function through muscle synergy activation.

Self-Assisted Standing Enabled by Non-Invasive Spinal Stimulation after Spinal Cord Injury.

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. The primary outcomes included qualitative comparison of need of external assistance for knee and hip extension provided by trainers during standing without and in the presence of stimulation in the same participants, as well as quantitative measures, such as the level of knee assistance and amount of time spent standing without trainer assistance. None of the participants could stand unassisted without stimulation or in the presence of sham stimulation. With stimulation all participants could maintain upright standing with minimum and some (n = 7) without external assistance applied to the knees or hips, using their hands for upper body balance as needed. Quality of balance control was practice-dependent, and improved with subsequent training. During self-initiated body-weight displacements in standing enabled by spinal stimulation, high levels of leg muscle activity emerged, and depended on the amount of muscle loading. Our findings indicate that the lumbosacral spinal networks can be modulated transcutaneously using electrical spinal stimulation to facilitate self-assisted standing after chronic motor and sensory complete paralysis.

Extraction of Muscle Synergies in Spinal Cord Injured Patients.

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). However, standard NNMF algorithms do not allow for physiological delays for a neural signal to reach different muscles. These delays are prevalent in SCI patients under spinal stimulation, and so we propose a new algorithm (regularized ShiftNMF) to extract muscle synergies which account for signal delays. We find muscle synergies extracted by the regularized ShiftNMF algorithm are significantly better at reconstructing EMG activity, and the resulting features are physiologically consistent and more useful in describing patient behavior.

Trunk Stability Enabled by Noninvasive Spinal Electrical Stimulation after Spinal Cord Injury.

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. Eight participants with non-progressive SCI at C3-T9, American Spinal Injury Association Impairment Scale (AIS) A or C, performed different motor tasks during sitting. Electromyography of the trunk muscles, three-dimensional kinematics, and force plate data were acquired. Spinal stimulation improved trunk control during sitting in all tested individuals. Stimulation resulted in elevated activity of the erector spinae, rectus abdominis, and external obliques, contributing to improved trunk control, more natural anterior pelvic tilt and lordotic curve, and greater multi-directional seated stability. During spinal stimulation, the center of pressure (COP) displacements decreased to 1.36 ± 0.98 mm compared with 4.74 ± 5.41 mm without stimulation (p = 0.0156) in quiet sitting, and the limits of stable displacement increased by 46.92 ± 35.66% (p = 0.0156), 36.92 ± 30.48% (p = 0.0156), 54.67 ± 77.99% (p = 0.0234), and 22.70 ± 26.09% (p = 0.0391) in the forward, backward, right, and left directions, respectively. During self-initiated perturbations, the correlation between anteroposterior arm velocity and the COP displacement decreased from r = 0.5821 (p = 0.0007) without to r = 0.5115 (p = 0.0039) with stimulation, indicating improved trunk stability. These data demonstrate that the spinal networks can be modulated transcutaneously with tonic electrical spinal stimulation to physiological states sufficient to generate a more stable, erect sitting posture after chronic paralysis.

An Active Learning Algorithm for Control of Epidural Electrostimulation.

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. We propose a method based on GP-BUCB, a Gaussian process bandit algorithm. In n = 4 spinally transected rats, we implant epidural electrode arrays and examine the algorithm's performance in selecting bipolar stimuli to elicit specified muscle responses. These responses are compared with temporally interleaved intra-animal stimulus selections by a human expert. GP-BUCB successfully controlled the spinal electrostimulation preparation in 37 testing sessions, selecting 670 stimuli. These sessions included sustained autonomous operations (ten-session duration). Delivered performance with respect to the specified metric was as good as or better than that of the human expert. Despite receiving no information as to anatomically likely locations of effective stimuli, GP-BUCB also consistently discovered such a pattern. Further, GP-BUCB was able to extrapolate from previous sessions' results to make predictions about performance in new testing sessions, while remaining sufficiently flexible to capture temporal variability. These results provide validation for applying automated stimulus selection methods to the problem of spinal cord injury therapy.

Expert-like performance of an autonomous spike tracking algorithm in isolating and maintaining single units in the macaque cortex.

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. To avoid this, experimenters can repeatedly re-adjust electrode positions to maintain the shapes of isolated spikes. In recordings with a larger number of electrodes, this process becomes extremely difficult. We report the performance of an automated algorithm that tracks neurons to obtain well isolated spiking, and autonomously adjusts electrode position to maintain good isolation. We tested the performance of this algorithm in isolating units with multiple individually adjustable micro-electrodes in a cortical surface area of macaque monkeys. We compared the performance in terms of signal quality and signal stability against passive placement of microelectrodes and against the performance of three human experts. The results show that our SpikeTrack2 algorithm achieves significantly better signal quality compared to passive placement. It is as least as good as humans in initially finding and isolating units, and better as the average and at least as good as the most proficient of three human experimenters in maintaining signal quality and signal stability. The autonomous tracking performance, the scalability of the system to large numbers of individual channels, and the possibility to objectify single unit recording criteria makes SpikeTrack2 a highly valuable tool for all multi-channel recording systems with individually adjustable electrodes.

Effect of epidural stimulation of the lumbosacral spinal cord on voluntary movement, standing, and assisted stepping after motor complete paraplegia: a case study.

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. After 170 locomotor training sessions over 26 months, a 16-electrode array was surgically placed on the dura (L1-S1 cord segments) in December 2009, to allow for chronic electrical stimulation. Spinal cord stimulation was done during sessions that lasted up to 250 min. We did 29 experiments and tested several stimulation combinations and parameters with the aim of the patient achieving standing and stepping. FINDINGS: Epidural stimulation enabled the man to achieve full weight-bearing standing with assistance provided only for balance for 4·25 min. The patient achieved this standing during stimulation using parameters identified as specific for standing while providing bilateral load-bearing proprioceptive input. We also noted locomotor-like patterns when stimulation parameters were optimised for stepping. Additionally, 7 months after implantation, the patient recovered supraspinal control of some leg movements, but only during epidural stimulation. INTERPRETATION: Task-specific training with epidural stimulation might reactivate previously silent spared neural circuits or promote plasticity. These interventions could be a viable clinical approach for functional recovery after severe paralysis. FUNDING: National Institutes of Health and Christopher and Dana Reeve Foundation.

Assessment of sensitization risk of a laundry pre-spotter containing protease.

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. Two studies were undertaken to examine the risk of sensitization to protease (i.e. Savinase(®)) used in a trigger-spray laundry pre-spotter product. The first was a laboratory study simulating a very heavy-use scenario in a controlled environment cubical chamber (14.5 m(3)). The product was applied to a series of fabric targets held vertically over a standard washing machine. Eight replicates of the experiment were done, using 30 sprays for each replicate. Airborne particle distributions in the breathing zone were characterized using a TSI particle analyzer. Enzyme concentrations in air were measured using PTFE membrane filters that were frozen until analyzed by an enzyme linked immunosorbent assay (ELISA). Results indicated that aerosol concentrations returned to baseline within 10 min, during which the average enzyme concentration in air was 17 ± 1.6 and 12 ± 0.92 ng/m(3) using low- and high-volume samplers, respectively. The corresponding amount of enzyme that could be inhaled was significantly less than allowed in occupational situations. The second study was a 6-month, controlled-use study involving approximately 100 subjects with confirmed atopic status by skin prick testing with common aeroallergens. The study involved daily exaggerated use of the pre-spotter product for 6 months, with prick testing for the protease carried out at baseline, 3 and 6 months. Results from the clinical study indicated that none of the subjects exhibited reactions that would indicate sensitization to the protease by inhalation. The principal limitations of the study were the relatively small number of subjects and the limited duration (96 completed the entire 6-month exposure program).

The minimum interval for confident spike sorting: A sequential decision method.

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. When the threshold is exceeded, the clustering model with the highest model evidence is accepted. We first develop a testing procedure for a single recording interval, and then extend the method to multi-interval recording by using both Bayesian priors from previous recording intervals and recently developed cluster tracking procedure. Lastly, a more advanced tracker is implemented and initials results are presented. This later procedure is useful for real time applications such as brain machine interfaces and autonomous recording electrodes. We test our theory on recordings from Macaque parietal cortex, showing that the method does reach the desired confidence level.

A Bayesian clustering method for tracking neural signals over successive intervals.

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. We also develop techniques to use prior data to appropriately seed the clustering algorithm and select the model class. We present results in a principal components space; however, the algorithm may be applied in any feature space where the distribution of a neuron's spikes may be modeled as Gaussian. Applications of this signal classification method to recordings from macaque parietal cortex show that it provides significantly more consistent clustering and tracking results than traditional methods based on expectation-maximization optimization of mixture models. This consistent tracking ability is crucial for intended applications of the method.

Recovery of control of posture and locomotion after a spinal cord injury: solutions staring us in the face.

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. Advances in multiple areas have provided tools for pursuing effective combination of strategies for recovering stepping and standing after a severe spinal cord injury. Muscle physiology research has provided insight into how to maintain functional muscle properties after a spinal cord injury. Understanding the role of the spinal networks in processing sensory information that is important for the generation of motor functions has focused research on developing treatments that sharpen the sensitivity of the locomotor circuitry and that carefully manage the presentation of proprioceptive and cutaneous stimuli to favor recovery. Pharmacological facilitation or inhibition of neurotransmitter systems, spinal cord stimulation, and rehabilitative motor training, which all function by modulating the physiological state of the spinal circuitry, have emerged as promising approaches. Early technological developments, such as robotic training systems and high-density electrode arrays for stimulating the spinal cord, can significantly enhance the precision and minimize the invasiveness of treatment after an injury. Strategies that seek out the complementary effects of combination treatments and that efficiently integrate relevant technical advances in bioengineering represent an untapped potential and are likely to have an immediate impact. Herein, we review key findings in each of these areas of research and present a unified vision for moving forward. Much work remains, but we already have the capability, and more importantly, the responsibility, to help spinal cord injury patients now.

Wing and body motion during flight initiation in Drosophila revealed by automated visual tracking.

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. An accurate geometric fly model is designed using unit quaternions to capture complex body and wing rotations, which are automatically fitted to the images in each time frame. Our approach works across a range of flight behaviors, while also being robust to common environmental clutter. The tracking system is used in this paper to compare wing and body motion during both voluntary and escape take-offs. Using our automated algorithms, we are able to measure stroke amplitude, geometric angle of attack and other parameters important to a mechanistic understanding of flapping flight. When compared with manual tracking methods, the algorithm estimates body position within 4.4+/-1.3% of the body length, while body orientation is measured within 6.5+/-1.9 deg. (roll), 3.2+/-1.3 deg. (pitch) and 3.4+/-1.6 deg. (yaw) on average across six videos. Similarly, stroke amplitude and deviation are estimated within 3.3 deg. and 2.1 deg., while angle of attack is typically measured within 8.8 deg. comparing against a human digitizer. Using our automated tracker, we analyzed a total of eight voluntary and two escape take-offs. These sequences show that Drosophila melanogaster do not utilize clap and fling during take-off and are able to modify their wing kinematics from one wingstroke to the next. Our approach should enable biomechanists and ethologists to process much larger datasets than possible at present and, therefore, accelerate insight into the mechanisms of free-flight maneuvers of flying insects.

Automated visual tracking for studying the ontogeny of zebrafish swimming.

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. An accurate geometric fish model is automatically designed and fit to the images at each time frame. Our approach works across a range of fish shapes and sizes and is therefore well suited for studying the ontogeny of fish swimming, while also being robust to common environmental occlusions. Our current analysis focuses on measuring the influence of vertebra development on the swimming capabilities of zebrafish. We examine wild-type zebrafish and mutants with stiff vertebrae (stocksteif) and quantify their body kinematics as a function of their development from larvae to adult (mutants made available by the Hubrecht laboratory, The Netherlands). By tracking the fish, we are able to measure the curvature and net acceleration along the body that result from the fish's body wave. Here, we demonstrate the capabilities of the tracking system for the escape response of wild-type zebrafish and stocksteif mutant zebrafish. The response was filmed with a digital high-speed camera at 1500 frames s(-1). Our approach enables biomechanists and ethologists to process much larger datasets than possible at present. Our automated tracking scheme can therefore accelerate insight in the swimming behavior of many species of (developing) fish.

Training locomotor networks.

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. This level of modulation is sustained from supraspinal input in intact, but not spinal, rats. In a series of experiments with complete spinal rats, we have shown that an appropriate level of excitability of the spinal circuitry can be achieved using widely different means. For example, this modulation level can be acquired pharmacologically, via epidural electrical stimulation over specific lumbosacral spinal cord segments, and/or by use-dependent mechanisms such as step or stand training. Evidence as to how each of these treatments can "tune" the spinal circuitry to a "physiological state" that enables it to respond appropriately to proprioceptive input will be presented. We have found that each of these interventions can enable the proprioceptive input to actually control extensive details that define the dynamics of stepping over a range of speeds, loads, and directions. A series of experiments will be described that illustrate sensory control of stepping and standing after a spinal cord injury and the necessity for the "physiological state" of the spinal circuitry to be modulated within a critical window of excitability for this control to be manifested. The present findings have important consequences not only for our understanding of how the motor pattern for stepping is formed, but also for the design of rehabilitation intervention to restore lumbosacral circuit function in humans following a spinal cord injury.

Omnidirectional sensory and motor volumes in electric fish.

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. We find that the motor volume has a similar omnidirectional shape, which can be attributed to the fish's backward-swimming capabilities and body dynamics. We assessed the electrosensory space for prey detection by analyzing simulated changes in spiking activity of primary electrosensory afferents during empirically measured and synthetic prey capture trials. The animal's motor volume was reconstructed from video recordings of body motion during prey capture behavior. Our results suggest that in weakly electric fish, there is a close connection between the shape of the sensory and motor volumes. We consider three general spatial relationships between 3-D sensory and motor volumes in active and passive-sensing animals, and we examine hypotheses about these relationships in the context of the volumes we quantify for weakly electric fish. We propose that the ratio of the sensory volume to the motor volume provides insight into behavioral control strategies across all animals.

Implications of assist-as-needed robotic step training after a complete spinal cord injury on intrinsic strategies of motor learning.

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. To test the efficacy of these robotic control strategies to teach spinal mice to step, we divided 27 adult female Swiss-Webster mice randomly into three groups. Each group was trained robotically by using one of three control strategies: a fixed training trajectory (Fixed group), an AAN training paradigm without interlimb coordination (Band group), and an AAN training paradigm with bilateral hindlimb coordination (Window group). Beginning at 14 d after a complete midthoracic spinal cord transection, the mice were trained daily (10 min/d, 5 d/week) to step on a treadmill 10 min after the administration of quipazine (0.5 mg/kg), a serotonin agonist, for a period of 6 weeks. During weekly performance evaluations, the mice trained with the AAN window paradigm generally showed the highest level of recovery as measured by the number, consistency, and periodicity of steps during the testing sessions. In all three measurements there were no significant differences between the Band and the Fixed training groups. These results indicate that the window training approach, which includes loose alternating interlimb coordination, is more effective than a fixed trajectory paradigm with rigid alternating interlimb coordination or an AAN paradigm without any interlimb constraints in promoting robust postinjury stepping behavior.

Exposure data for personal care products: hairspray, spray perfume, liquid foundation, shampoo, body wash, and solid antiperspirant.

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. Six widely used personal care product types were included in the studies. Five of the products were cosmetics (spray perfume, hairspray, liquid foundation, shampoo, body wash) and one product was a cosmetic/over-the-counter drug product (solid antiperspirant). Three hundred and sixty women, ages 19-65 years, who regularly use the products of interest, were recruited at 10 different geographical locations within the US. The number of recruits was chosen to ensure a minimum of three hundred completed responses per product type. Subjects were provided with a new container of the brand of product they normally use and kept diaries and recorded detailed daily usage information over a two week period. Products were weighed at the start and completion of the study in order to determine the total amount of product used. Statistical analyses of the data were conducted to derive summary distributions of use patterns. The geometric mean and median usage per application, respectively, for the six product types were: spray perfume, 0.33 g and 0.23 g; hairspray, 2.58 g and 1.83 g (aerosol); 3.64 g and 2.66 g (pump); liquid foundation, 0.54 g and 0.36 g; shampoo, 11.76 g and 9.56 g; body wash, 11.3g and 9.5 g; and solid antiperspirant, 0.61 g and 0.45 g. The mean and median usage per day for the six product types were: spray perfume, 0.53 g and 0.34 g; hairspray, 3.57 g and 2.71 g (aerosol); 5.18 g and 3.74 g (pump); liquid foundation, 0.67 g and 0.45 g; shampoo, 12.80 g and 10.75 g; body wash, 14.5 g and 12.9 g; and solid antiperspirant, 0.79 g and 0.59 g. The mean number of applications per day for spray perfume, hairspray, liquid foundation, shampoo, body wash, and solid antiperspirant was 1.67, 1.49 (aerosol) and 1.51 (pump), 1.24, 1.11, 1.37, and 1.3, respectively. This study provides current exposure information for commonly used products which will be useful for risk assessment purposes.

A control algorithm for autonomous optimization of extracellular recordings.

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. The application of the algorithm to acute neurophysiological recording experiments and its potential implications to chronic recording electrode arrays are discussed.

Automated tracking of multiple C. Elegans.

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). The filter can naturally be expanded to estimate the locations of multiple worms and determine when they are occluding each other. The predicted location of the models at each iteration allows for an efficient method to determine the regions that are undergoing occlusions. Experiments on actual C. Elegans mating sequence data demonstrate the quality of the proposed method.