Search NASA⌕ Search

SEARCH · Search NASA

Results for “SIGNAL DISCRIMINATOR”

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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Classification image analysis: estimation and statistical inference for two-alternative forced-choice experiments

We consider estimation and statistical hypothesis testing on classification images obtained from the two-alternative forced-choice experimental paradigm. We begin with a probabilistic model of task performance for simple forced-choice detection and discrimination tasks. Particular attention is paid to general linear filter models because these models lead to a direct interpretation of the classification image as an estimate of the filter weights. We then describe an estimation procedure for obtaining classification images from observer data. A number of statistical tests are presented for testing various hypotheses from classification images based on some more compact set of features derived from them. As an example of how the methods we describe can be used, we present a case study investigating detection of a Gaussian bump profile.

Non-NASA Center↗
NASA NTRS1988

North America-Pacific plate boundary, an elastic-plastic megashear - Evidence from very long baseline interferometry

Data obtained by Mark III VLBI measurements of radio signals from permanent and mobile VLBI sites for 5.5 years of observations, starting in October 1982, were used to derive a picture of the earth crust deformation near the North America-Pacific plate boundary. The data, which included the vector positions of the VLBI sites and their rate of change, were used for comparison with a number of lithospheric deformation models based upon the concept that the motions of points near the North America-Pacific plate boundary are a linear combination of North America and Pacific velocities. The best of these models were found to fit 95 percent of the variance in 139 VLBI length and transverse velocity observations. Instantaneous shear deformation associated with plate tectonics is apparently developing in a zone 450 km wide paralleling the San Andreas Fault; some of this deformation will be recovered through elastic rebound, while the rest will be permanently set through plastic processes. Because the VLBI data have not been collected for a significant fraction of the earthquake cycle, they cannot discriminate between elastic and plastic behaviors.

Ward, Steven N.↗
NASA NTRS1999

Plasma membrane ordering agent pluronic F-68 (PF-68) reduces neurotransmitter uptake and release and produces learning and memory deficits in rats

A substantial body of evidence indicates that aged-related changes in the fluidity and lipid composition of the plasma membrane contribute to cellular dysfunction in humans and other mammalian species. In the CNS, reductions in neuronal plasma membrane order (PMO) (i.e., increased plasma membrane fluidity) have been attributed to age as well as the presence of the beta-amyloid peptide-25-35, known to play an important role in the neuropathology of Alzheimer's disease (AD). These PMO increases may influence neurotransmitter synthesis, receptor binding, and second messenger systems as well as signal transduction pathways. The effects of neuronal PMO on learning and memory processes have not been adequately investigated, however. Based on the hypothesis that an increase in PMO may alter a number of aspects of synaptic transmission, we investigated several neurochemical and behavioral effects of the membrane ordering agent, PF-68. In cell culture, PF-68 (nmoles/mg SDS extractable protein) reduced [3H]norepinephrine (NE) uptake into differentiated PC-12 cells as well as reduced nicotine stimulated [3H]NE release. The compound (800-2400 microg/kg, i.p., resulting in nmoles/mg SDS extractable protein in the brain) decreased step-through latencies and increased the frequencies of crossing into the unsafe side of the chamber in inhibitory avoidance training. In the Morris water maze, PF-68 increased the latencies and swim distances required to locate a hidden platform and reduced the time spent and distance swam in the previous target quadrant during transfer (probe) trials. PF-68 did not impair performance of a well-learned working memory task, the rat delayed stimulus discrimination task (DSDT), however. Studies with 14C-labeled PF-68 indicated that significant (pmoles/mg wet tissue) levels of the compound entered the brain from peripheral (i.p.) injection. No PF-68 related changes were observed in swim speeds or in visual acuity tests in water maze experiments, rotorod performance, or in tests of general locomotor activity. Furthermore, latencies to select a lever in the DSDT were not affected. These results suggest that PF-68 induced deficits in learning and memory without confounding peripheral motor, sensory, or motivational effects at the tested doses. Furthermore, none of the doses induced a conditioned taste aversion to a novel 0.1% saccharin solution indicating a lack of nausea or gastrointestinal malaise induced by the compound. The data indicate that increases in neuronal plasma membrane order may have significant effects on neurotransmitter function as well as learning and memory processes. Furthermore, compounds such as PF-68 may also offer novel tools for studying the role of neuronal PMO in mnemonic processes and changes in PMO resulting from age-related disorders such as AD.

Poloxamer/pharmacology↗
NASA NTRS2004

Using AVIRIS Data to Map and Characterize Subaerially and Subaqueously Erupted BasalticVolcanic Tephras: The Challenge of Mapping Low-Albedo Materials

Increases in the signal-to-noise ratio (SNR) in AVIRIS has enabled the mapping and characterization of low albedo materials. Low albedo materials of interest include certain soils, man-made materials (asphalt, certain building materials, tires, etc.), and basaltic lava flows and ashes. Early in its history, the response of the AVIRIS sensor was not sensitive enough so that these low albedo materials could be reliably mapped. However, as indicated by Green and Pavri (2002) the noise equivalent delta radiance (NEdL) of AVIRIS in the 2001 flight season was below 0.010 in all but the shortest wavelength channels. This is approximately a ten-fold improvement from the 1989 flight season when NEdL was closer to 0.1 (Green et al., 1990). In the current investigation, AVIRIS data from the 2002 flight season collected over the Pavant Butte tuff cone, Tabernacle Hill tuff ring, and an associated lava flow in the Black Rock Desert of west central Utah were examined to determine how well these generally low albedo volcanic lavas and tephras could be discriminated from background materials. The Pavant Butte tuff cone was examined by the author in an earlier study with a 1989 AVIRIS dataset (Farrand and Singer,

Farrand, William H.↗
NASA NTRS2014

A Comparison of Potential IM-CW Lidar Modulation Techniques for ASCENDS CO2 Column Measurements From Space

Global atmospheric carbon dioxide (CO2) measurements through the Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) Decadal Survey recommended space mission are critical for improving our understanding of CO2 sources and sinks. IM-CW (Intensity Modulated Continuous Wave) lidar techniques are investigated as a means of facilitating CO2 measurements from space to meet the ASCENDS science requirements. In previous laboratory and flight experiments we have successfully used linear swept frequency modulation to discriminate surface lidar returns from intermediate aerosol and cloud contamination. Furthermore, high accuracy and precision ranging to the surface as well as to the top of intermediate clouds, which is a requirement for the inversion of the CO2 column-mixing ratio from the instrument optical depth measurements, has been demonstrated with the linear swept frequency modulation technique. We are concurrently investigating advanced techniques to help improve the auto-correlation properties of the transmitted waveform implemented through physical hardware to make cloud rejection more robust in special restricted scenarios. Several different carrier based modulation techniques are compared including orthogonal linear swept, orthogonal non-linear swept, and Binary Phase Shift Keying (BPSK). Techniques are investigated that reduce or eliminate sidelobes. These techniques have excellent auto-correlation properties while possessing a finite bandwidth (by way of a new cyclic digital filter), which will reduce bias error in the presence of multiple scatterers. Our analyses show that the studied modulation techniques can increase the accuracy of CO2 column measurements from space. A comparison of various properties such as signal to noise ratio (SNR) and time-bandwidth product are discussed.

Campbell, Joel F.↗
NASA NTRS2002

The footprints of visual attention in the Posner cueing paradigm revealed by classification images

In the Posner cueing paradigm, observers' performance in detecting a target is typically better in trials in which the target is present at the cued location than in trials in which the target appears at the uncued location. This effect can be explained in terms of a Bayesian observer where visual attention simply weights the information differently at the cued (attended) and uncued (unattended) locations without a change in the quality of processing at each location. Alternatively, it could also be explained in terms of visual attention changing the shape of the perceptual filter at the cued location. In this study, we use the classification image technique to compare the human perceptual filters at the cued and uncued locations in a contrast discrimination task. We did not find statistically significant differences between the shapes of the inferred perceptual filters across the two locations, nor did the observed differences account for the measured cueing effects in human observers. Instead, we found a difference in the magnitude of the classification images, supporting the idea that visual attention changes the weighting of information at the cued and uncued location, but does not change the quality of processing at each individual location.

Non-NASA Center↗
NASA NTRS2006

A Preliminary Analysis of Calcifying Particles in the Serum and Prostates of Patients with Prostatic Inflammation

Chronic diseases of the prostate such as benign prostatic hyperplasia (BPH) & chronic pelvic pain syndrome (CPPS) have associated findings of chronic inflammation, despite a lack of causal relationship. Numerous attempts to define an infectious agent responsible for the clinical findings have been inconsistent. The possibility of an infectious agent, that has not been uncovered with routine culturing methods, forms the basis for this study. Serum from 940 healthy Finnish men were compared with serum from 40 Crohn's, 40 path dx prostatitis, & 40 with path dx carcinoma, using an enzyme-linked immunosorbant assay (ELISA), to detect antigens specific to Nanobacteria(NB) utilizing monoclonal antibodies (Ab) 5/3 and 8D10. This ELISA has not been validated for detecting NB-associated with clinical prostatic disease, yet cross-reactivity with other bacterial species is low. Immunohistochemistry was performed on de-paraffinized prostatic tissue slides, de-calcified with EDTA and stained with the DAKO Catalyzed Signal Amplification kit, employing 8D10 as the primary (target/antigen-detecting) Ab. The mean (plus or minus SD) & median concentrations of NB antigen (U/50 L) were 379.59 (plus or minus 219.28) & 640.00 for patients with prostatitis (BPH) vs 3.31 (plus or minus 3.55) & 2.94 for prostate adenocarcinoma, 1.88 (plus or minus 2.94) & 0.80 for Crohn's disease, & 7.43 (plus or minus 25.57) & 0.00 for patients with no clinical prostatic disease. Unpaired t-tests revealed statistically significant differences between the prostatitis (BPH) sera & each of the other groups with p less than 0.005, but no differences between the other groups themselves. Preliminary studies with immunohistochemistry & 3-D confocal microscopy reveal 16/24 tissue sections + for NB Ag in BPH vs. only 2/22 tissue sections with prostate cancer. The preliminary findings of this serum screening study suggest that NB antigen may be commonly found in the serum of patients with the pathological diagnosis of prostatitis. Preliminary immunohistologic studies, suggest that NB may be found within the gland itself at a higher rate in patients with BPH relative to patients with adenocarcinoma, however confirmatory studies with a more specific ELISA technique, primary cultures, & with larger numbers of patients in a prospective design are required to determine if 1) NB are a causative organism for clinical hyperplastic and inflammatory disease, & if 2) serological testing can be used to discriminate patients with nanobacterial-associated prostatic disease.

Jones, Jeffrey A.↗
NASA NTRS1987

An electric current associated with gravity sensing in maize roots

The study of gravisensing would be greatly enhanced if physiological events associated with gravity sensing could be detected separately from subsequent growth processes. This report presents a means to discriminate sensing from the growth processes. By using a vibrating probe, we have found an electric current generated by the gravity sensing region of the root cap of maize (Zea mays cv Merit) in response to gravistimulation. On the upper surface of the root cap, the change from the endogenous current has a density of 0.55 microampere per square centimeter away from gravity. The onset of the current shift has a characteristic of lag of three to four minutes after gravistimulation, which corresponds to the presentation time for gravity sensing in this tissue. A description of the current provides some information about the sensing mechanism, as well as being a valuable means to detect gravity sensing independently of differential growth.

NASA Discipline Number 40-10↗
NASA NTRS1993

Parametric motion control of robotic arms: A biologically based approach using neural networks

A neural network based system is presented which is able to generate point-to-point movements of robotic manipulators. The foundation of this approach is the use of prototypical control torque signals which are defined by a set of parameters. The parameter set is used for scaling and shaping of these prototypical torque signals to effect a desired outcome of the system. This approach is based on neurophysiological findings that the central nervous system stores generalized cognitive representations of movements called synergies, schemas, or motor programs. It has been proposed that these motor programs may be stored as torque-time functions in central pattern generators which can be scaled with appropriate time and magnitude parameters. The central pattern generators use these parameters to generate stereotypical torque-time profiles, which are then sent to the joint actuators. Hence, only a small number of parameters need to be determined for each point-to-point movement instead of the entire torque-time trajectory. This same principle is implemented for controlling the joint torques of robotic manipulators where a neural network is used to identify the relationship between the task requirements and the torque parameters. Movements are specified by the initial robot position in joint coordinates and the desired final end-effector position in Cartesian coordinates. This information is provided to the neural network which calculates six torque parameters for a two-link system. The prototypical torque profiles (one per joint) are then scaled by those parameters. After appropriate training of the network, our parametric control design allowed the reproduction of a trained set of movements with relatively high accuracy, and the production of previously untrained movements with comparable accuracy. We conclude that our approach was successful in discriminating between trained movements and in generalizing to untrained movements.

Bock, O.↗
NASA NTRS1995

Cationic influences upon synaptic transmission at the hair cell-afferent fiber synapse of the frog

The concentrations of inorganic cations (K+, Na+, and Ca2+) bathing the isolated frog labyrinth were varied in order to assess their role in influencing and mediating synaptic transmission at the hair cell-afferent fiber synapse. Experiments employed intracellular recordings of synaptic activity from VIIIth nerve afferents. Recordings were digitized continuously at 50 kHz, and excitatory postsynaptic potentials were detected and parameters quantified by computer algorithms. Particular attention was focused on cationic effects upon excitatory postsynaptic potential frequency of occurrence and excitatory postsynaptic potential amplitude, in order to discriminate between pre- and postsynaptic actions. Because the small size of afferents preclude long term stable recordings, alterations in cationic concentrations were applied transiently and their peak effects on synaptic activity were assessed. Increases in extracellular K+ concentration of a few millimolar produced a large increase in the frequency of occurrence of excitatory postsynaptic potentials with little change in amplitude, indicating that release of transmitter from the hair cell is tightly coupled to its membrane potential. Increasing extracellular Na+ concentration resulted in an increase in excitatory postsynaptic potential amplitude with no significant change in excitatory postsynaptic potential frequency of occurrence, suggesting that the transmitter-gated subsynaptic channel conducts Na+ ions. Decreases in extracellular Ca2+ concentration had little effect upon excitatory postsynaptic potential frequency, but increased excitatory postsynaptic potential frequency and amplitude. These findings suggest that at higher concentrations Ca2+ act presynaptically to prevent transmitter release and postsynaptically to prevent Na+ influx during the generation of the excitatory postsynaptic potential. The influences of these ions on synaptic activity at this synapse are remarkably similar to those reported at the vertebrate neuromuscular junction. The major differences between these two synapses are the neurotransmitters and the higher resting release rate and higher sensitivity of release to increased K+ concentrations of the hair cells over that of motor nerve terminals. These differences reflect the functional roles of the two synapses: the motor nerve terminal response in an all-or-nothing signal consequent from action potential invasion, while the hair cell releases transmitter in a graded fashion, proportionate to the extent of stereocilial deflection. Despite these differences between the two junctions, the similar actions of these elemental cations upon synaptic function at each implies that these ions may participate similarly in the operations of other synapses, independent of the neurotransmitter type.(ABSTRACT TRUNCATED AT 400 WORDS).

NASA Discipline Neuroscience↗
NASA NTRSDate not supplied

Transcriptomics-based Machine Learning (ML) Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗
NASA NTRSDate not supplied

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% was shown on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗
NASA NTRSDate not supplied

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% was shown on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗
NASA NTRS2000

Spatiotemporal processing of linear acceleration: primary afferent and central vestibular neuron responses

Spatiotemporal convergence and two-dimensional (2-D) neural tuning have been proposed as a major neural mechanism in the signal processing of linear acceleration. To examine this hypothesis, we studied the firing properties of primary otolith afferents and central otolith neurons that respond exclusively to horizontal linear accelerations of the head (0.16-10 Hz) in alert rhesus monkeys. Unlike primary afferents, the majority of central otolith neurons exhibited 2-D spatial tuning to linear acceleration. As a result, central otolith dynamics vary as a function of movement direction. During movement along the maximum sensitivity direction, the dynamics of all central otolith neurons differed significantly from those observed for the primary afferent population. Specifically at low frequencies (</=0.5 Hz), the firing rate of the majority of central otolith neurons peaked in phase with linear velocity, in contrast to primary afferents that peaked in phase with linear acceleration. At least three different groups of central response dynamics were described according to the properties observed for motion along the maximum sensitivity direction. "High-pass" neurons exhibited increasing gains and phase values as a function of frequency. "Flat" neurons were characterized by relatively flat gains and constant phase lags (approximately 20-55 degrees ). A few neurons ("low-pass") were characterized by decreasing gain and phase as a function of frequency. The response dynamics of central otolith neurons suggest that the approximately 90 degrees phase lags observed at low frequencies are not the result of a neural integration but rather the effect of nonminimum phase behavior, which could arise at least partly through spatiotemporal convergence. Neither afferent nor central otolith neurons discriminated between gravitational and inertial components of linear acceleration. Thus response sensitivity was indistinguishable during 0.5-Hz pitch oscillations and fore-aft movements. The fact that otolith-only central neurons with "high-pass" filter properties exhibit semicircular canal-like dynamics during head tilts might have important consequences for the conclusions of previous studies of sensory convergence and sensorimotor transformations in central vestibular neurons.

NASA Discipline Neuroscience↗
NASA NTRS2014

Constraints On the Emission Geometries and Spin Evolution Of Gamma-Ray Millisecond Pulsars

Millisecond pulsars (MSPs) are a growing class of gamma-ray emitters. Pulsed gamma-ray signals have been detected from more than 40 MSPs with the Fermi Large Area Telescope (LAT). The wider radio beams and more compact magnetospheres of MSPs enable studies of emission geometries over a broader range of phase space than non-recycled radio-loud gamma-ray pulsars. We have modeled the gamma-ray light curves of 40 LAT-detected MSPs using geometric emission models assuming a vacuum retarded-dipole magnetic field. We modeled the radio profiles using a single-altitude hollow-cone beam, with a core component when indicated by polarimetry; however, for MSPs with gamma-ray and radio light curve peaks occurring at nearly the same rotational phase, we assume that the radio emission is co-located with the gamma rays and caustic in nature. The best-fit parameters and confidence intervals are determined using amaximum likelihood technique.We divide the light curves into three model classes, with gamma-ray peaks trailing (Class I), aligned (Class II), or leading (Class III) the radio peaks. Outer gap and slot gap (two-pole caustic) models best fit roughly equal numbers of Class I and II, while Class III are exclusively fit with pair-starved polar cap models. Distinguishing between the model classes based on typical derived parameters is difficult. We explore the evolution of the magnetic inclination angle with period and spin-down power, finding possible correlations. While the presence of significant off-peak emission can often be used as a discriminator between outer gap and slot gap models, a hybrid model may be needed.

pulsars: general↗
NASA NTRS2002

Interocular velocity difference contributes to stereomotion speed perception

Two experiments are presented assessing the contributions of the rate of change of disparity (CD) and interocular velocity difference (IOVD) cues to stereomotion speed perception. Using a two-interval forced-choice paradigm, the perceived speed of directly approaching and receding stereomotion and of monocular lateral motion in random dot stereogram (RDS) targets was measured. Prior adaptation using dysjunctively moving random dot stimuli induced a velocity aftereffect (VAE). The degree of interocular correlation in the adapting images was manipulated to assess the effectiveness of each cue. While correlated adaptation involved a conventional RDS stimulus, containing both IOVD and CD cues, uncorrelated adaptation featured an independent dot array in each monocular half-image, and hence lacked a coherent disparity signal. Adaptation produced a larger VAE for stereomotion than for monocular lateral motion, implying effects at neural sites beyond that of binocular combination. For motion passing through the horopter, correlated and uncorrelated adaptation stimuli produced equivalent stereomotion VAEs. The possibility that these results were due to the adaptation of a CD mechanism through random matches in the uncorrelated stimulus was discounted in a control experiment. Here both simultaneous and sequential adaptation of left and right eyes produced similar stereomotion VAEs. Motion at uncrossed disparities was also affected by both correlated and uncorrelated adaptation stimuli, but showed a significantly greater VAE in response to the former. These results show that (1) there are two separate, specialised mechanisms for encoding stereomotion: one through IOVD, the other through CD; (2) the IOVD cue dominates the perception of stereomotion speed for stimuli passing through the horopter; and (3) at a disparity pedestal both the IOVD and the CD cues have a significant influence.

Vision, Binocular/physiology↗
NASA NTRS1998

The Effect of Set Size on the Relation Between Saccadic and Perceptual Decisions During Search

We have shown that when searching for a disk in noise at one of 10 locations, the accuracy of the I st saccade is similar to that of the perceptual decision at the time of saccadic programming. The present study has two goals: 1) to test whether this linden - extends to a contrast-discrimination task without noise, and 2) to measure the effect of set size on the relation between saccadic and perceptual decisions. Methods: Three observers searched over a grey background (34.5 cd/sq m) for a bright disk (63.2 cd/sq m) among dim disks (54.1 cd/sq m) along the circumference of a circle (r = 5.9 deg.) centered on a fixation cress. Four set sizes (2, 4, 6, 12) were used. In the 1st condition, stimuli were presented for 1 sec. and observers used natural eye movements. We then measured the accuracy of the first saccade (% correct using a shortest-distance criterion). In the 2nd condition, observers fixated a central cross at all times and the stimulus duration was approx. 70 as less than the median latency of the first saccade in the 1st condition (saccadic programming time). We then recorded perceptual performance and discarded trials in which observers broke fixation. Results: For set sizes of 2, 4, 8, and 12, the mean d' across observers for the perceptual decision was 2.03, 1.96, 1.94, 1.71, respectively, while the mean d' of the first saccade was only 0.73, 1.40, 1.23, 1.17. Conclusions: Unlike detection of a disk in noise, for all observers and set-sizes, the perceptual accuracy at the time of saccadic programming is better than that of the lst saccade. For set-sizes of 4, 6, and 12, the amount of information available to the perceptual system relative to that available to the saccadic system is approximately constant (fixed do ratio). For these higher set sizes, the constancy in do across set size for both perception and saccadic decisions is consistent with a simple signal detection theory (SDT) model that processes noisy signals in parallel. However, for 2 observers, at a set-size of 2, saccadic targeting appears to be worse than the SDT model prediction, perhaps due to speed-accuracy trade-off.

Eckstein, M. P.↗
NASA NTRS2002

Differential half-maximal effects of human insulin and its analogs for in situ glucose transport and protein synthesis in rat soleus muscle

Analogs of human insulin have been used to discriminate between responses of metabolic and mitogenic (growth-related) pathways. This study compared the stimulatory effects of human insulin (HI) and 2 analogs (X2, B-Asp(9), B-Glu(27) and H2, A-His(8),B-His(4),B-Glu(10), B-His(27)) on glucose uptake and protein synthesis in rat soleus muscle in situ. Glucose uptake, estimated by intramuscular (IM) injection of 2-deoxy[1,2-3H]glucose with or without insulin, was maximally increased at 10(-6) mol/L for HI and X2 and 10(-7) mol/L for H2. HI had a larger effect (318%) than either X2 (156%) or H2 (124%). The half-maximal effect (ED(50)) values for HI, X2, and H2 were 3.3 x10(-8) mol/L, 1.7 x 10(-7) mol/L, and 1.6 x 10(-9) mol/L, respectively. Protein synthesis, estimated by protein incorporation of [(3)H]phenylalanine injected into muscles with or without insulin, was maximally increased at 10(-5) mol/L for HI and 10(-6) for X2 and H2. HI had a larger effect in stimulating protein synthesis (34%) than either X2 (25%) or H2 (19.8%). The ED(50) values for HI, X2, and H2 were 3.0 x 10(-7) mol/L, 3.2 x 10(-7) mol/L, and 1.0 x 10(-9) mol/L, respectively. The biological potency of each analog (ED(50)insulin/ED(50)analog) showed X2 to be less potent than HI for both glucose uptake (0.2) and protein synthesis (0.9), whereas H2 is more potent than HI with ratios of 20 and 300, respectively. These data suggest that this approach for studying insulin responsiveness in a single muscle in situ may be a useful tool for investigating insulin signaling in muscle in vivo. Copyright 2002, Elsevier Science (USA). All rights reserved.

NASA Discipline Developmental Biology↗