Search NASA⌕ Search

SEARCH · Search NASA

Results for “Neural Conduction”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

Binaural speech discrimination under noise in hearing-impaired listeners

This paper presents the results of an assessment of speech discrimination by hearing-impaired listeners (sensori-neural, conductive, and mixed groups) under binaural free-field listening in the presence of background noise. Subjects with pure-tone thresholds greater than 20 dB in 0.5, 1.0 and 2.0 kHz were presented with a version of the W-22 list of phonetically balanced words under three conditions: (1) 'quiet', with the chamber noise below 28 dB and speech at 60 dB; (2) at a constant S/N ratio of +10 dB, and with a background white noise at 70 dB; and (3) same as condition (2), but with the background noise at 80 dB. The mean speech discrimination scores decreased significantly with noise in all groups. However, the decrease in binaural speech discrimination scores with an increase in hearing impairment was less for material presented under the noise conditions than for the material presented in quiet.

Kumar, K. V.↗

The effects of deuterium on static posture control

A significant operational problem impacting upon the Space Shuttle program involves the astronaut's ability to safely egress from the Orbiter during an emergency situation. Following space flight, astronauts display significant movement problems. One variable which may contribute to increased movement ataxia is deuterium (D2O). Deuterium is present in low levels within the Orbiter's water supply but may accumulate to significant physiological levels during lengthy missions. Deuterium was linked to a number of negative physiological responses, including motion sickness, decreased metabolism, and slowing of neural conduction velocity. The effects of D2O on static postural control in response to a range of dosage levels were investigated. Nine sugjects were divided into three groups of three subjects each. The groups were divided into a low, medium, and a high D2O dosage group. The subjects static posture was assessed with the use of the EquiTest systems, a commercially available postural control evaluation system featuring movable force plates and a visual surround that can be servoed to the subject's sway. In addition to the force plate information, data about the degree of subject sway about the hips and shoulders was obtained. Additionally, surface electromyographic (EMG) data from the selected lower limb muscles were collected along with saliva samples used to determine the amount of deuterium enrichment following D2O ingestion. Two baseline testing sessions were performed using the EquiTest testing protocol prior to ingestion of the D2O. Thirty minutes after dosing, subjects again performed the tests. Two more post-dosing tests were run with an interest interval of one hour. Preliminary data anlaysis indicates that only subjects in the igh dose group displayed any significant static postural problems. Future analyses of the sway and EMG is expected to reveal significant variations in the subject's postural control strategy following D2O dosing. While functionally significant static postural problems were not commonly observed, subjects in both the medium and high dosage groups displayed significant, and in some cases, severe voluntary movement problems.

Layne, Charles S.↗

Neuroscience Investigations: An Overview of Studies Conducted

The neural processes that mediate human spatial orientation and adaptive changes occurring in response to the sensory rearrangement encountered during orbital flight are primarily studied through second and third order responses. In the Extended Duration Orbiter Medical Project (EDOMP) neuroscience investigations, the following were measured: (1) eye movements during acquisition of either static or moving visual targets, (2) postural and locomotor responses provoked by unexpected movement of the support surface, changes in the interaction of visual, proprioceptive, and vestibular information, changes in the major postural muscles via descending pathways, or changes in locomotor pathways, and (3) verbal reports of perceived self-orientation and self-motion which enhance and complement conclusions drawn from the analysis of oculomotor, postural, and locomotor responses. In spaceflight operations, spatial orientation can be defined as situational awareness, where crew member perception of attitude, position, or motion of the spacecraft or other objects in three-dimensional space, including orientation of one's own body, is congruent with actual physical events. Perception of spatial orientation is determined by integrating information from several sensory modalities. This involves higher levels of processing within the central nervous system that control eye movements, locomotion, and stable posture. Spaceflight operational problems occur when responses to the incorrectly perceived spatial orientation are compensatory in nature. Neuroscience investigations were conducted in conjunction with U. S. Space Shuttle flights to evaluate possible changes in the ability of an astronaut to land the Shuttle or effectively perform an emergency post-landing egress following microgravity adaptation during space flights of variable length. While the results of various sensory motor and spatial orientation tests could have an impact on future space flights, our knowledge of sensorimotor adaptation to spaceflight is limited, and the future application of effective countermeasures depends, in large part, on the results from appropriate neuroscience investigations. Therefore, the objective of the neuroscience investigations could have a negative effect on mission success. The Neuroscience Laboratory, Johnson Space Center (JSC), implemented three integrated Detailed Supplementary Objectives (DSO) designed to investigate spatial orientation and the associated compensatory responses as a part of the EDOMP. The four primary goals were (1) to establish a normative database of vestibular and associated sensory changes in response to spaceflight, (2) to determine the underlying etiology of neurovestibular and sensory motor changes associated with exposure to microgravity and the subsequent return to Earth, (3) to provide immediate feedback to spaceflight crews regarding potential countermeasures that could improve performance and safety during and after flight, and (4) to take under consideration appropriate designs for preflight, in-flight, and postflight countermeasures that could be implemented for future flights.

Reschke, Millard F.↗

Monte Carlo Tree Search Methods for the Earth-Observing Satellite Scheduling Problem

This work explores on-board planning for the single spacecraft, multiple ground station Earth-observing satellite scheduling problem through artificial neural network function approximation of state–action value estimates generated by Monte Carlo tree search (MCTS). An extensive hyperparameter search is conducted for MCTS on the basis of performance, safety, and downlink opportunity utilization to determine the best hyperparameter combination for data generation. A hyperparameter search is also conducted on neural network architectures. The learned behavior of each network is explored, and each network architecture’s robustness to orbits and epochs outside of the training distributions is investigated. Furthermore, each algorithm is compared with a genetic algorithm, which serves to provide a baseline for optimality. MCTS is shown to compute near-optimal solutions in comparison to the genetic algorithm. The state–action value networks are shown to match or exceed the performance of MCTS in six orders of magnitude less execution time, showing promise for execution on board spacecraft.

Adam P. Herrmann↗

Changes in nerve conduction and Pi/PCr ratio during denervation-reinnervation of the gastrocsoleus muscles of rats

The purpose of this investigation was to study the changes in nerve conduction and phosphate metabolites of the gastrocsoleus muscles of rats during denervation-reinnervation. Sixteen male Sprague-Dawley rats underwent unilateral crush-denervation of the left sciatic nerves at the sciatic notch. Six rats were used for measurement of motor conduction latency and action potential amplitude of the gastrocsoleus muscle by stimulating the sciatic nerve at one, two and eight weeks after nerve crush. The other ten rats were designated for evaluation of the ratio of inorganic phosphorous (Pi) to phosphocreatine (PCr) by a 31P-phosphoenergetic spectrometer at two weeks and eight weeks after nerve crush. None of the sciatic nerves showed conduction to the gastrocsoleus at one or two weeks after nerve crush. At eight weeks postcrush, the motor conduction latency returned to within normal limits, whereas the action potential amplitude was only 55% of the normal. For the eight-week period of study, the Pi/PCr ratio of the normal control muscles ranged between 0.09 +/- 0.02 and 0.11 +/- 0.02 (mean +/- SD). The denervated muscles showed an increase of Pi/PCr ratio by 54% at two weeks postcrush, compared to the respective contralateral control sides. The ratios returned to the normal value by eight weeks postcrush. In summary, these data suggested that the metabolic recovery of the crush-denervated muscle followed the same pattern as the parameters of nerve conduction.

NASA Center JSC↗

Subacute diabetic proximal neuropathy

OBJECTIVE: To evaluate the clinical, electrophysiologic, autonomic, and neuropathologic characteristics and the natural history of subacute diabetic proximal neuropathy and its response to immunotherapy. MATERIAL AND METHODS: For the 12-year period from 1983 to 1995, we conducted a retrospective review of medical records of Mayo Clinic patients with diabetes who had subacute onset and progression of proximal weakness. The responses of treated versus untreated patients were compared statistically. RESULTS: During the designated study period, 44 patients with subacute diabetic proximal neuropathy were encountered. Most patients were middle-aged or elderly, and no sex preponderance was noted. The proximal muscle weakness often was associated with reduced or absent lower extremity reflexes. Associated weight loss was a common finding. Frequently, patients had some evidence of demyelination on nerve conduction studies, but it invariably was accompanied by concomitant axonal degeneration. The cerebrospinal fluid protein concentration was usually increased. Diffuse and substantial autonomic failure was generally present. In most cases, a sural nerve biopsy specimen suggested demyelination, although evidence of an inflammatory infiltrate was less common. Of 12 patients who received treatment (with prednisone, intravenous immune globulin, or plasma exchange), 9 had improvement of their conditions, but 17 of 29 untreated patients (59%) with follow-up also eventually had improvement, albeit at a much slower rate. Improvement was usually incomplete. CONCLUSION: We suggest that the entity of subacute diabetic proximal neuropathy is an extensive and severe variant of bilateral lumbosacral radiculoplexopathy, with some features suggestive of an immune-mediated cause. It differs from chronic inflammatory demyelinating polyradiculoneuropathy in that most cases have a more restricted distribution and seem to be monophasic and self-limiting. The efficacy of immunotherapy is unproved, but such intervention may be considered in the severe and progressive cases or ones associated with severe neuropathic pain.

Non-NASA Center↗

Signal dispersion within a hippocampal neural network

A model network is described, representing two neural populations coupled so that one population is inhibited by activity it excites in the other. Parameters and operations within the model represent EPSPs, IPSPs, neural thresholds, conduction delays, background activity and spatial and temporal dispersion of signals passing from one population to the other. Simulations of single-shock and pulse-train driving of the network are presented for various parameter values. Neuronal events from 100 to 300 msec following stimulation are given special consideration in model calculations.

Horowitz, J. M.↗

Hoffmann-reflex is delayed during 6 degree head-down tilt with balanced traction

BACKGROUND: Increased spinal height due to the lack of of axial compression on spinal structures in microgravity may stretch the spinal cord, cauda equina, nerve roots, and paraspinal tissues. HYPOTHESIS: Exposure to simulated microgravity causes dysfunction of nerve roots so that the synaptic portion of the Achilles tendon reflex is delayed. METHODS: Six healthy male subjects were randomly divided into two groups with three in each group. The subjects in the first group underwent horizontal bed rest (HBR) for three days. After a two week interval they underwent bed rest in a position of head-down tilt with balanced traction (HDT). So that each subject could serve as his own control, the second group was treated identically but in opposite order. Bilateral F waves and H-reflexes were measured daily (18:30-20:30) on all subjects placed in a prone position. RESULTS: By means of ANOVA, differences between HDT and HBR were observed only in M-latency and F-ratio, not in F-latency, central latency, and H-latency. Differences during the course of the bed rest were observed in M-latency and H-latency only. Tibial H latency was significantly lengthened in HDT group on day 2 and 3, although no significant difference between HDT and HBR was observed. CONCLUSION: The monosynaptic reflex assessed by H-reflex was delayed during 6 degree HDT with traction. The exact mechanism of this delay and whether the change was due to lengthening of the lower part of the vertebrae remain to be clarified.

Randomized Controlled Trial↗

Pilot Workload Rating Predictions Using Image Data and Recurrent Neural Networks

In this work, we augmented existing methods for estimating pilot workload ratings with deep neural networks trained using data from simulated flight tests in the Vertical Motion Simulator (VMS). We used an existing method, Spare Capacity Operations Estimator (SCOPE), along with a recurrent neural network and conducted comparison studies between the two methods individually, and when used together. We found that using both methods together can improve the result over using either approach alone. In our first test case, we achieved an improved linear correlation coefficient of 0.409 over that of SCOPE alone at 0.352 on the training dataset. Through cross validation, we also found that the results may be dependent on the split of training vs. validation data, and that further investigation should be conducted to understand what additional inputs to the neural network model should be made.

Image Data↗

Spaceflight Effects on Neurocognitive Performance: Extent, Longevity and Neural Bases

We are conducting ongoing experiments in which we are performing structural and functional magnetic resonance brain imaging to identify the relationships between changes in neurocognitive function and neural structural alterations following a six month International Space Station mission. Our central hypothesis is that measures of brain structure, function, and network integrity will change from pre to post spaceflight. Moreover, we predict that these changes will correlate with indices of cognitive, sensory, and motor function in a neuroanatomically selective fashion. Our interdisciplinary approach utilizes cutting edge neuroimaging techniques and a broad ranging battery of sensory, motor, and cognitive assessments that are conducted pre flight, during flight, and post flight to investigate potential neuroplastic and maladaptive brain changes in crewmembers following long-duration spaceflight. Success in this endeavor would 1) result in identification of the underlying neural mechanisms and operational risks of spaceflight-induced changes in behavior, and 2) identify whether a return to normative behavioral function following re-adaptation to Earth's gravitational environment is associated with a restitution of brain structure and function or instead is supported by substitution with compensatory brain processes. We have collected data on several crewmembers and preliminary findings will be presented. Eventual comparison to results from our parallel bed rest study will enable us to parse out the multiple mechanisms contributing to any spaceflight-induced neural structural and behavioral changes that we observe.

Seidler, R. D.↗

The Effects of Spaceflight and a Spaceflight Analog on Neurocognitive Perfonnance: Extent, Longevity, and Neural Bases

We are conducting ongoing experiments in which we are performing structural and functional magnetic resonance brain imaging to identify the relationships between changes in neurocognitive function and neural structural alterations following a six month International Space Station mission and following 70 days exposure to a spaceflight analog, head down tilt bedrest. Our central hypothesis is that measures of brain structure, function, and network integrity will change from pre to post intervention (spaceflight, bedrest). Moreover, we predict that these changes will correlate with indices of cognitive, sensory, and motor function in a neuroanatomically selective fashion. Our interdisciplinary approach utilizes cutting edge neuroimaging techniques and a broad ranging battery of sensory, motor, and cognitive assessments that will be conducted pre flight, during flight, and post flight to investigate potential neuroplastic and maladaptive brain changes in crewmembers following long-duration spaceflight. Success in this endeavor would 1) result in identification of the underlying neural mechanisms and operational risks of spaceflight-induced changes in behavior, and 2) identify whether a return to normative behavioral function following re-adaptation to Earth's gravitational environment is associated with a restitution of brain structure and function or instead is supported by substitution with compensatory brain processes. With the bedrest study, we will be able to determine the neural and neurocognitive effects of extended duration unloading, reduced sensory inputs, and increased cephalic fluid distribution. This will enable us to parse out the multiple mechanisms contributing to any spaceflight-induced neural structural and behavioral changes that we observe in the flight study. In this presentation I will discuss preliminary results from six participants who have undergone the bed rest protocol. These individuals show decrements in balance and functional mobility, and alterations in brain structure and function, in association with extended bed rest.

Seidler, R. D.↗

Radiation Behavior of Analog Neural Network Chip

A neural network experiment conducted for the Space Technology Research Vehicle (STRV-1) 1-b launched in June 1994. Identical sets of analog feed-forward neural network chips was used to study and compare the effects of space and ground radiation on the chips. Three failure mechanisms are noted.

neural networks radiation hardening graceful degra↗

Neural networks analysis on SSME vibration simulation data

The neural networks method is applied to investigate the feasibility in detecting anomalies in turbopump vibration of SSME to supplement the statistical method utilized in the prototype system. The investigation of neural networks analysis is conducted using SSME vibration data from a NASA developed numerical simulator. The limited application of neural networks to the HPFTP has also shown the effectiveness in diagnosing the anomalies of turbopump vibrations.

Lo, Ching F.↗

Neural network architectures to analyze OPAD data

A prototype Optical Plume Anomaly Detection (OPAD) system is now installed on the space shuttle main engine (SSME) Technology Test Bed (TTB) at MSFC. The OPAD system requirements dictate the need for fast, efficient data processing techniques. To address this need of the OPAD system, a study was conducted into how artificial neural networks could be used to assist in the analysis of plume spectral data.

Whitaker, Kevin W.↗

On-line, adaptive state estimator for active noise control

Dynamic characteristics of airframe structures are expected to vary as aircraft flight conditions change. Accurate knowledge of the changing dynamic characteristics is crucial to enhancing the performance of the active noise control system using feedback control. This research investigates the development of an adaptive, on-line state estimator using a neural network concept to conduct active noise control. In this research, an algorithm has been developed that can be used to estimate displacement and velocity responses at any locations on the structure from a limited number of acceleration measurements and input force information. The algorithm employs band-pass filters to extract from the measurement signal the frequency contents corresponding to a desired mode. The filtered signal is then used to train a neural network which consists of a linear neuron with three weights. The structure of the neural network is designed as simple as possible to increase the sampling frequency as much as possible. The weights obtained through neural network training are then used to construct the transfer function of a mode in z-domain and to identify modal properties of each mode. By using the identified transfer function and interpolating the mode shape obtained at sensor locations, the displacement and velocity responses are estimated with reasonable accuracy at any locations on the structure. The accuracy of the response estimates depends on the number of modes incorporated in the estimates and the number of sensors employed to conduct mode shape interpolation. Computer simulation demonstrates that the algorithm is capable of adapting to the varying dynamic characteristics of structural properties. Experimental implementation of the algorithm on a DSP (digital signal processing) board for a plate structure is underway. The algorithm is expected to reach the sampling frequency range of about 10 kHz to 20 kHz which needs to be maintained for a typical active noise control application.

Lim, Tae W.↗

Neural Network Research on Tilt-Rotor Hover Performance

Results from a neural network study on XV-15 tilt-rotor hover performance are presented. Two XV-15 test data bases, acquired during separate tests conducted in the National Full-Scale Aerodynamics Complex at NASA Ames, were used in this study. The two XV-15 test data bases used were: the 1997 80- by 120-Foot Wind Tunnel test data base and the 1984 Outdoor Aerodynamic Research Facility (OARF) test data base. The objectives associated with the 80- by 120-Foot Wind Tunnel test data were to conduct data quality checks, obtain neural network representations, and demonstrate sensitivity to test conditions. The objectives associated with the OARF outdoor test data were to obtain a 'zero wind' neural network representation, and formulate and implement a neural network based wind correction procedure. An additional objective, common to both test data bases, was to conduct error comparisons. The conclusions from the present study were as follows: Compared to measured parameters (i.e., collective pitch angle), derived parameters (i.e., thrust coefficient) were found preferable as neural network inputs. For the 80- by 120-Foot Wind Tunnel test data base, the neural network based figure of merit representations did not extrapolate rotor stall. Using the OARF outdoor test database, a neural network based wind correction procedure was formulated and successfully implemented. Based on an error comparison, the present neural network based wind correction procedure was found to be more accurate compared to the existing, momentum-theory-based wind correction procedure. Also, a separate error comparison showed that the 80- by 120-Foot Wind Tunnel hover performance data were comparable to non-wind-corrected outdoor test data.

Kozapalli, S.↗

Optical Calibration Process Developed for Neural-Network-Based Optical Nondestructive Evaluation Method

A completely optical calibration process has been developed at Glenn for calibrating a neural-network-based nondestructive evaluation (NDE) method. The NDE method itself detects very small changes in the characteristic patterns or vibration mode shapes of vibrating structures as discussed in many references. The mode shapes or characteristic patterns are recorded using television or electronic holography and change when a structure experiences, for example, cracking, debonds, or variations in fastener properties. An artificial neural network can be trained to be very sensitive to changes in the mode shapes, but quantifying or calibrating that sensitivity in a consistent, meaningful, and deliverable manner has been challenging. The standard calibration approach has been difficult to implement, where the response to damage of the trained neural network is compared with the responses of vibration-measurement sensors. In particular, the vibration-measurement sensors are intrusive, insufficiently sensitive, and not numerous enough. In response to these difficulties, a completely optical alternative to the standard calibration approach was proposed and tested successfully. Specifically, the vibration mode to be monitored for structural damage was intentionally contaminated with known amounts of another mode, and the response of the trained neural network was measured as a function of the peak-to-peak amplitude of the contaminating mode. The neural network calibration technique essentially uses the vibration mode shapes of the undamaged structure as standards against which the changed mode shapes are compared. The published response of the network can be made nearly independent of the contaminating mode, if enough vibration modes are used to train the net. The sensitivity of the neural network can be adjusted for the environment in which the test is to be conducted. The response of a neural network trained with measured vibration patterns for use on a vibration isolation table in the presence of various sources of laboratory noise is shown. The output of the neural network is called the degradable classification index. The curve was generated by a simultaneous comparison of means, and it shows a peak-to-peak sensitivity of about 100 nm. The following graph uses model generated data from a compressor blade to show that much higher sensitivities are possible when the environment can be controlled better. The peak-to-peak sensitivity here is about 20 nm. The training procedure was modified for the second graph, and the data were subjected to an intensity-dependent transformation called folding. All the measurements for this approach to calibration were optical. The peak-to-peak amplitudes of the vibration modes were measured using heterodyne interferometry, and the modes themselves were recorded using television (electronic) holography.

Decker, Arthur J.↗

Porous-Floating-Gate Field-Effect Transistor

Porous-floating-gate, "vertical" field-effect transistor proposed as programmable analog memory device especially suitable for use in electronic neural networks. Analog value of electrical conductance of device represents synaptic weight (strength of synaptic connection) repeatedly modified by application of suitable writing or erasing voltage. Suited for hardware implementations of massively parallel neural-network architectures for two important reasons: vertical transistor structure requires only two external electrodes, and use of tailored amorphous semiconductors provides choice of very wide range of low conductivity values, dictated by overall power dissipation requirements in massively parallel neural-network circuits.

Thakoor, Anilkumar P.↗