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At least 163 records · Page 9

Behavioral and Physiological Effects of Hindlimb Unloading in Rats

The overarching objective of this project was to identify changes in neural and biochemical systems of the central and peripheral nervous systems (the CNS and PNS) that are related to disruptions of functional motor responses, or motor control. The identification of neural and biochemical changes that are related to sensory-motor adaptation elicited as animals react to changes in the gravitational field was of particular interest. Thus, the major objective of this work was to study disruptions of motor responses that arise after (sic. due to) chronic exposure to altered gravity (G). To do this, parallel studies investigating changes in neural, sensory, and neuromuscular systems were conducted after animals (rats) experienced chronic exposure to conditions of altered-G. Conditions of altered-G included hyper-G produced by centrifugation, micro-G produced by orbital flight, and simulated micro-G produced by hind limb suspension. A second major interest was to examine the contribution of putative changes in sensory systems to disruptions of motor responses. To do this, motor responses and reflexes of rats were studied following chronic treatment with streptomycin sulfate (STP, an ototoxic chemical) to damage the vestibular hair cells.

Fox, Robert A.↗

The Effects of Long Duration Bed Rest as a Spaceflight Analogue on Resting State Sensorimotor Network Functional Connectivity and Neurocognitive Performance

Long duration spaceflight has been associated with detrimental alterations in human sensorimotor systems and neurocognitive performance. Prolonged exposure to a head-down tilt position during long duration bed rest can resemble several effects of the microgravity environment such as reduced sensory inputs, body unloading and increased cephalic fluid distribution. The question of whether microgravity affects other central nervous system functions such as brain functional connectivity and its relationship with neurocognitive performance is largely unknown, but of potential importance to the health and performance of astronauts both during and post-flight. The aims of the present study are 1) to identify changes in sensorimotor resting state functional connectivity that occur with extended bed rest exposure, and to characterize their recovery time course; 2) to evaluate how these neural changes correlate with neurocognitive performance. Resting-state functional magnetic resonance imaging (rsfMRI) data were collected from 17 male participants. The data were acquired through the NASA bed rest facility, located at the University of Texas Medical Branch (Galveston, TX). Participants remained in bed with their heads tilted down six degrees below their feet for 70 consecutive days. RsfMRI data were obtained at seven time points: 7 and 12 days before bed rest; 7, 50, and 65 days during bed rest; and 7 and 12 days after bed rest. Functional connectivity magnetic resonance imaging (fcMRI) analysis was performed to measure the connectivity of sensorimotor networks in the brain before, during, and post-bed rest. We found a decrease in left putamen connectivity with the pre- and post-central gyri from pre bed rest to the last day in bed rest. In addition, vestibular cortex connectivity with the posterior cingulate cortex decreased from pre to post bed rest. Furthermore, connectivity between cerebellar right superior posterior fissure and other cerebellar regions decreased from pre bed rest to the last day in bed rest. In contrast, connectivity within the default mode network remained stable over the course of bed rest. We also utilized a battery of behavioral measures including spatial working memory tasks and measures of functional mobility and balance. These behavioral measurements were collected before, during, and after bed rest. We will report the preliminary findings of correlations observed between brain functional connectivity and behavioral performance changes. Our results suggest that sensorimotor brain networks exhibit decoupling with extended periods of reduced usage. The findings from this study could aid in the understanding and future design of targeted countermeasures to alleviate the detrimental health and neurocognitive effects of long-duration spaceflight.

Cassady, K.↗

Toward modeling a dynamic biological neural network

The organization of a mammalian macular endorgan is interpreted on physical and engineering principles. Having accomplished this task, it is possible to mathematically and symbolically model information processing by the macular neural network. A complex symbolic model is produced through use of mathematical notations that describe the functioning system. The model, consisting of six tiers, is constructed to mimic the neural system. On the basis of initial simulations, it is concluded that the network functions best when some of the detecting elements (i.e., type I hair cells) are weakly inhibitory. The simulations also illustrate the importance of disinhibition of receptors located in the third tier in shaping nerve discharge patterns at the sixth tier in the model system.

Ross, M. D.↗

A neural fuzzy controller learning by fuzzy error propagation

In this paper, we describe a procedure to integrate techniques for the adaptation of membership functions in a linguistic variable based fuzzy control environment by using neural network learning principles. This is an extension to our work. We solve this problem by defining a fuzzy error that is propagated back through the architecture of our fuzzy controller. According to this fuzzy error and the strength of its antecedent each fuzzy rule determines its amount of error. Depending on the current state of the controlled system and the control action derived from the conclusion, each rule tunes the membership functions of its antecedent and its conclusion. By this we get an unsupervised learning technique that enables a fuzzy controller to adapt to a control task by knowing just about the global state and the fuzzy error.

Nauck, Detlef↗

Neural network based automatic limit prediction and avoidance system and method

A method for performance envelope boundary cueing for a vehicle control system comprises the steps of formulating a prediction system for a neural network and training the neural network to predict values of limited parameters as a function of current control positions and current vehicle operating conditions. The method further comprises the steps of applying the neural network to the control system of the vehicle, where the vehicle has capability for measuring current control positions and current vehicle operating conditions. The neural network generates a map of current control positions and vehicle operating conditions versus the limited parameters in a pre-determined vehicle operating condition. The method estimates critical control deflections from the current control positions required to drive the vehicle to a performance envelope boundary. Finally, the method comprises the steps of communicating the critical control deflection to the vehicle control system; and driving the vehicle control system to provide a tactile cue to an operator of the vehicle as the control positions approach the critical control deflections.

Calise, Anthony J.↗

Cardiovascular function in space flight

Changes in orthostatic heart rate have been noted universally in Soviet and U.S. crewmembers post space flight. The magnitude of these changes appears to be influenced by mission duration, with increasing orthostatic intolerance for the first 7-10 days of flight and then a partial recovery in the orthostatic heart rate response. Fluid loading has been used as a countermeasure to this postflight orthostatic intolerance. Previous reports have documented the effectiveness of this technique, but it has also been noted that the effectiveness of volume expansion diminishes as flight duration exceeds one week. The response of carotid baroreceptor function was investigated utilizing a commercially available neck collar which could apply positive and negative pressure to effect receptor stimulation. Bedrest studies had validated the usefulness and validity of the device. In these studies it was shown that carotid baroreceptor function curves demonstrated less responsiveness to orthostatic stimulation than control individuals. Twelve Space Shuttle crewmembers were examined pre- and postflight from flights lasting from 4-5 days. Plots of baroreceptor function were constructed and plotted as change in R-R interval vs. carotid distending pressure (an orthostatic stimulus). Typical sigmoidal curves were obtained. Postflight the resting heart rate was higher (smaller R-R interval) and the range of R-R value and the slope of the carotid sigmoidal response were both depressed. These changes were not significant immediately postflight (L + O), but did become significant by the second day postflight (L + 2), and remained suppressed for several days thereafter. It is hypothesized that the early adaptation to space flight involves a central fluid shift during the initial days of flight, but subsequent alterations in neural controlling mechanisms (such as carotid baroreceptor function) contribute to orthostatic intolerance.

Review↗

Objective and automated measurement of dynamic vision functions

A phoria stimulus array and electro-oculographic (EOG) arrangements for measuring motor and sensory responses of subjects subjected to stress or drug conditions are described, along with experimental procedures. Heterophoria (as oculomotor function) and glare recovery time (time required for photochemical and neural recovery after exposure to a flash stimulus) are measured, in research aimed at developing automated objective measurement of dynamic vision functions. Onset of involuntary optokinetic nystagmus in subjects attempting to track moving stripes (while viewing through head-mounted binocular eyepieces) after exposure to glare serves as an objective measure of glare recovery time.

Flom, M. C.↗

Neural Network and Response Surface Methodology for Rocket Engine Component Optimization

The goal of this work is to compare the performance of response surface methodology (RSM) and two types of neural networks (NN) to aid preliminary design of two rocket engine components. A data set of 45 training points and 20 test points obtained from a semi-empirical model based on three design variables is used for a shear coaxial injector element. Data for supersonic turbine design is based on six design variables, 76 training, data and 18 test data obtained from simplified aerodynamic analysis. Several RS and NN are first constructed using the training data. The test data are then employed to select the best RS or NN. Quadratic and cubic response surfaces. radial basis neural network (RBNN) and back-propagation neural network (BPNN) are compared. Two-layered RBNN are generated using two different training algorithms, namely solverbe and solverb. A two layered BPNN is generated with Tan-Sigmoid transfer function. Various issues related to the training of the neural networks are addressed including number of neurons, error goals, spread constants and the accuracy of different models in representing the design space. A search for the optimum design is carried out using a standard gradient-based optimization algorithm over the response surfaces represented by the polynomials and trained neural networks. Usually a cubic polynominal performs better than the quadratic polynomial but exceptions have been noticed. Among the NN choices, the RBNN designed using solverb yields more consistent performance for both engine components considered. The training of RBNN is easier as it requires linear regression. This coupled with the consistency in performance promise the possibility of it being used as an optimization strategy for engineering design problems.

Vaidyanathan, Rajkumar↗

Nonvolatile Ionic Two-Terminal Memory Device

Conceptual solid-state memory device nonvolatile and erasable and has only two terminals. Proposed device based on two effects: thermal phase transition and reversible intercalation of ions. Transfer of sodium ions between source of ions and electrical switching element increases or decreases electrical conductance of element, turning switch "on" or "off". Used in digital computers and neural-network computers. In neural networks, many small, densely packed switches function as erasable, nonvolatile synaptic elements.

Williams, Roger M.↗

Expert networks in CLIPS

Rule-based expert systems may be structurally and functionally mapped onto a special class of neural networks called expert networks. This mapping lends itself to adaptation of connectionist learning strategies for the expert networks. A parsing algorithm to translate C Language Integrated Production System (CLIPS) rules into a network of interconnected assertion and operation nodes has been developed. The translation of CLIPS rules to an expert network and back again is illustrated. Measures of uncertainty similar to those rules in MYCIN-like systems are introduced into the CLIPS system and techniques for combining and hiring nodes in the network based on rule-firing with these certainty factors in the expert system are presented. Several learning algorithms are under study which automate the process of attaching certainty factors to rules.

Hruska, S. I.↗

Program Aids Analysis And Optimization Of Design

NETS/ PROSSS (NETS Coupled With Programming System for Structural Synthesis) computer program developed to provide system for combining NETS (MSC-21588), neural-network application program and CONMIN (Constrained Function Minimization, ARC-10836), optimization program. Enables user to reach nearly optimal design. Design then used as starting point in normal optimization process, possibly enabling user to converge to optimal solution in significantly fewer iterations. NEWT/PROSSS written in C language and FORTRAN 77.

Rogers, James L., Jr.↗

The effects of area postrema lesions and selective vagotomy on motion-induced conditioned taste aversion

Conditioned taste aversion (CTA) is one of several behaviors which was suggested as a putative measure of motion sickness in rats. A review is made of studies which used surgical disruption of area postrema or the vagus nerve to investigate whether CTA and vomiting induced by motion may depend on common neural pathways or structures. When the chemoreceptive function of the area postrema (AP) is destroyed by complete ablation, rats develop CTA and cats and monkeys develop CTA and vomit. Thus the AP is not crucially involved in either CTA or vomiting induced by motion. However, after complete denervation of the stomach or after labyrinthectomy rats do not develop CTA when motion is used as the unconditioned stimulus. Studies of brainstem projections of the vagus nerve, the area postrema, the periaqueductal grey, and the vestibular system are used as the basis for speculation about regions which could mediate both motion-induced vomiting and behavioral food aversion.

conditioned taste aversion↗

Design of Neural Networks for Fast Convergence and Accuracy: Dynamics and Control

A procedure for the design and training of artificial neural networks, used for rapid and efficient controls and dynamics design and analysis for flexible space systems, has been developed. Artificial neural networks are employed, such that once properly trained, they provide a means of evaluating the impact of design changes rapidly. Specifically, two-layer feedforward neural networks are designed to approximate the functional relationship between the component/spacecraft design changes and measures of its performance or nonlinear dynamics of the system/components. A training algorithm, based on statistical sampling theory, is presented, which guarantees that the trained networks provide a designer-specified degree of accuracy in mapping the functional relationship. Within each iteration of this statistical-based algorithm, a sequential design algorithm is used for the design and training of the feedforward network to provide rapid convergence to the network goals. Here, at each sequence a new network is trained to minimize the error of previous network. The proposed method should work for applications wherein an arbitrary large source of training data can be generated. Two numerical examples are performed on a spacecraft application in order to demonstrate the feasibility of the proposed approach.

Maghami, Peiman G.↗

Design of Neural Networks for Fast Convergence and Accuracy

A novel procedure for the design and training of artificial neural networks, used for rapid and efficient controls and dynamics design and analysis for flexible space systems, has been developed. Artificial neural networks are employed to provide a means of evaluating the impact of design changes rapidly. Specifically, two-layer feedforward neural networks are designed to approximate the functional relationship between the component spacecraft design changes and measures of its performance. A training algorithm, based on statistical sampling theory, is presented, which guarantees that the trained networks provide a designer-specified degree of accuracy in mapping the functional relationship. Within each iteration of this statistical-based algorithm, a sequential design algorithm is used for the design and training of the feedforward network to provide rapid convergence to the network goals. Here, at each sequence a new network is trained to minimize the error of previous network. The design algorithm attempts to avoid the local minima phenomenon that hampers the traditional network training. A numerical example is performed on a spacecraft application in order to demonstrate the feasibility of the proposed approach.

Maghami, Peiman G.↗

Space Vehicle Pose Estimation via Optical Correlation and Nonlinear Estimation

A technique for 6-degree-of-freedom (6DOF) pose estimation of space vehicles is being developed. This technique draws upon recent developments in implementing optical correlation measurements in a nonlinear estimator, which relates the optical correlation measurements to the pose states (orientation and position). For the optical correlator, the use of both conjugate filters and binary, phase-only filters in the design of synthetic discriminant function (SDF) filters is explored. A static neural network is trained a priori and used as the nonlinear estimator. New commercial animation and image rendering software is exploited to design the SDF filters and to generate a large filter set with which to train the neural network. The technique is applied to pose estimation for rendezvous and docking of free-flying spacecraft and to terrestrial surface mobility systems for NASA's Vision for Space Exploration. Quantitative pose estimation performance will be reported. Advantages and disadvantages of the implementation of this technique are discussed.

Rakoczy, John↗

Space Vehicle Pose Estimation via Optical Correlation and Nonlinear Estimation

A technique for 6-degree-of-freedom (6DOF) pose estimation of space vehicles is being developed. This technique draws upon recent developments in implementing optical correlation measurements in a nonlinear estimator, which relates the optical correlation measurements to the pose states (orientation and position). For the optical correlator, the use of both conjugate filters and binary, phase-only filters in the design of synthetic discriminant function (SDF) filters is explored. A static neural network is trained a priori and used as the nonlinear estimator. New commercial animation and image rendering software is exploited to design the SDF filters and to generate a large filter set with which to train the neural network. The technique is applied to pose estimation for rendezvous and docking of free-flying spacecraft and to terrestrial surface mobility systems for NASA's Vision for Space Exploration. Quantitative pose estimation performance will be reported. Advantages and disadvantages of the implementation of this technique are discussed.

Rakoczy, John M.↗

Automated Escape Guidance Algorithms for An Escape Vehicle

An escape vehicle was designed to provide an emergency evacuation for crew members living on a space station. For maximum escape capability, the escape vehicle needs to have the ability to safely evacuate a station in a contingency scenario such as an uncontrolled (e.g., tumbling) station. This emergency escape sequence will typically be divided into three events: The fust separation event (SEP1), the navigation reconstruction event, and the second separation event (SEP2). SEP1 is responsible for taking the spacecraft from its docking port to a distance greater than the maximum radius of the rotating station. The navigation reconstruction event takes place prior to the SEP2 event and establishes the orbital state to within the tolerance limits necessary for SEP2. The SEP2 event calculates and performs an avoidance burn to prevent station recontact during the next several orbits. This paper presents the tools and results for the whole separation sequence with an emphasis on the two separation events. The fust challenge includes collision avoidance during the escape sequence while the station is in an uncontrolled rotational state, with rotation rates of up to 2 degrees per second. The task of avoiding a collision may require the use of the Vehicle's de-orbit propulsion system for maximum thrust and minimum dwell time within the vicinity of the station vicinity. The thrust of the propulsion system is in a single direction, and can be controlled only by the attitude of the spacecraft. Escape algorithms based on a look-up table or analytical guidance can be implemented since the rotation rate and the angular momentum vector can be sensed onboard and a-priori knowledge of the position and relative orientation are available. In addition, crew intervention has been provided for in the event of unforeseen obstacles in the escape path. The purpose of the SEP2 burn is to avoid re-contact with the station over an extended period of time. Performing this maneuver properly requires knowledge of the orbital state, which is obtained during the navigation state reconstruction event. Since the direction of the delta-v of the SEPI maneuver is a random variable with respect to the Local Vertical Local Horizontal (LVLH) coordinate system, calculating the required SEP2 burn is a challenge. This problem was solved using a neural network as a model-free function approximation technique.

Flanary, Ronald↗

Functional Sensory-Motor Performance Following Long Term Space Flight: The First Results of "Field Test" Experiment

The effect that extended-duration space flights may have on human space travelers, including exploration missions, is widely discussed at the present time. Specifically, there is an increasing amount of evidence showing that the physical capacity of cosmonauts is significantly reduced after long-duration space flights. It is evident that the most impaired functions are those that rely on gravity, particularly up right posture and gait. Because of the sensorimotor disturbances manifested in the neurology of the posture and gait space flight and postflight changes may also be observed in debilitating motion sickness. While the severity of particular symptoms varies, disturbances in spatial orientation and alterations in the accuracy of voluntary movements are persistently observed after long-duration space flights. At this time most of the currently available data are primarily descriptive and not yet suitable for predicting operational impacts of most sensorimotor decrements observed upon landing on planetary surfaces or asteroids. In particular there are no existing data on the recovery dynamics or functionality of neurological, cardiovascular or muscle performance making it difficult to model or simulate the cosmonauts' activity after landing and develop the appropriate countermeasure that will ensure the rapid and safe recovery of crewmembers immediately after landing in what could be hostile environments. However and as a starting position, the videos we have acquired during recent data collection following the long duration flights of cosmonauts and astronauts walking and performing other tasks shortly after return from space flight speak volumes about their level of deconditioning. A joint Russian-American team has developed a new study specifically to address the changes in crewmembers performance and the recovery of performance with the intent of filling the missing data gaps. The first (pilot) phase of this study includes recording body kinematics and quantifying the coordination and timing of relatively simple basic movements - transition from seated and prone positions to standing, walking, stepping over obstacles, tandem walking, muscle compliance, as well as characteristics of postural sway and orthostatic tolerance. Testing for changes in these parameters have been initiated in the medical tent at the landing site. The first set of experiments showed that during the first hour after landing, cosmonauts and astronauts were able to execute (although slower and with more effort than preflight) simple movements such as egress from a seated or prone position and also to remain standing for 3.5 minutes without exhibiting pronounced cardiovascular changes. More challenging tests, however, demonstrated a prominent reduction in coordination - the obstacle task, for example, was performed at much slower speed and with a marked overestimation of the obstacle height and tandem walking was greatly degraded suggesting significant changes in proprioception, brainstem and vestibular function. There is some speculation that the neural changes, either from the bottom-up or top down may be long lasting; requiring compensatory responses that will modify or mask the adverse responses we have observed. Furthermore, these compensatory responses may actually be beneficial, helping achieve a more rapid adaptation to both weightlessness and a return to earth.

Tomilovskaya, E. S.↗