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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.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Chicken (Gallus domesticus) inner ear afferents

Neurons from the vestibular (VG) and the statoacoustic (SAG) ganglion of the chick (Gallus domesticus) were evaluated histologically and morphometrically. Embryos at stages 34 (E8 days), 39 (E13 days) and 44 (E18 days) were sacrificed and temporal bones microdissected. Specimens were embedded in JB-4 methacrylate plastic, and stained with a mixture of 0.2% toluidine blue (TB) and 0.1% basic Fuschin in 25% ethanol or with a mixture of 2% TB and 1% paraphenylenediamine (PDA) for axon and myelin measurement study. Images of the VIIIth nerve were produced by a V150 (R) color imaging system and the contour of 200-300 neuronal bodies (perikarya) was traced directly on a video screen with a mouse in real time. The cross-sectional area of VG perikarya was 67.29 micrometers2 at stage 34 (E8), 128.46 micrometers2 at stage 39 (E13) and 275.85 micrometers2 at stage 44 (E18). The cross-sectional area of SAG perikarya was 62.44 micrometers2 at stage 34 (E8), 102.05 micrometers2 at stage 39 (E13) and 165.02 micrometers2 at stage 44 (E18). A significant cross-sectional area increase of the VG perikarya between stage 39 (E13) and stage 44 (E18) was determined. We randomly measured the cross-sectional area of myelin and axoplasm of hatchling afferent nerves, and found a correspondence between axoplasmic and myelin cross-sectional area in the utricular, saccular and semicircular canal nerve branches of the nerve. The results suggest that the period between stage 34 (E8) and 39 (E13) is a critical period for afferent neuronal development. Physiological and behavioral vestibular properties of developing and maturing hatchlings may change accordingly. The results compliment previous work by other investigators and provide valuable anatomical measures useful to correlate physiological data obtained from stimulation of the whole nerve or its parts.

NASA Discipline Neuroscience↗
DOE OSTI2025

ON-OFF neuromorphic ISING machines using Fowler-Nordheim annealers

We introduce NeuroSA, a neuromorphic architecture specifically designed to ensure asymptotic convergence to the ground state of an Ising problem using a Fowler-Nordheim quantum mechanical tunneling based threshold-annealing process. The core component of NeuroSA consists of a pair of asynchronous ON-OFF neurons, which effectively map classical simulated annealing dynamics onto a network of integrate-and-fire neurons. The threshold of each ON-OFF neuron pair is adaptively adjusted by an FN annealer and the resulting spiking dynamics replicates the optimal escape mechanism and convergence of SA, particularly at low-temperatures. To validate the effectiveness of our neuromorphic Ising machine, we systematically solved benchmark combinatorial optimization problems such as MAX-CUT and Max Independent Set. Across multiple runs, NeuroSA consistently generates distribution of solutions that are concentrated around the state-of-the-art results (within 99%) or surpass the current state-of-the-art solutions for Max Independent Set benchmarks. Furthermore, NeuroSA is able to achieve these superior distributions without any graph-specific hyperparameter tuning. For practical illustration, we present results from an implementation of NeuroSA on the SpiNNaker2 platform, highlighting the feasibility of mapping our proposed architecture onto a standard neuromorphic accelerator platform.

42 ENGINEERING↗
DOE OSTI2025

Quantum optical classifier with superexponential speedup

Abstract Classification is a central task in deep learning algorithms. Usually, images are first captured and then processed by a sequence of operations, of which the artificial neuron represents one of the fundamental units. This paradigm requires significant resources that scale (at least) linearly in the image resolution, both in terms of photons and computational operations. Here, we present a quantum optical pattern recognition method for binary classification tasks. It classifies objects without reconstructing their images, using the rate of two-photon coincidences at the output of a Hong-Ou-Mandel interferometer, where both the input and the classifier parameters are encoded into single-photon states. Our method exhibits the behaviour of a classical neuron of unit depth. Once trained, it shows a constant $${{\mathcal{O}}}(1)$$ O ( 1 ) complexity in the number of computational operations and photons required by a single classification. This is a superexponential advantage over a classical artificial neuron.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

A conserved molecular logic for neurogenesis to gliogenesis switch in the cerebral cortex

During development, neural stem cells in the cerebral cortex, also known as radial glial cells (RGCs), generate excitatory neurons, followed by production of cortical macroglia and inhibitory neurons that migrate to the olfactory bulb (OB). Understanding the mechanisms for this lineage switch is fundamental for unraveling how proper numbers of diverse neuronal and glial cell types are controlled. We and others recently showed that Sonic Hedgehog (Shh) signaling promotes the cortical RGC lineage switch to generate cortical oligodendrocytes and OB interneurons. During this process, cortical RGCs generate intermediate progenitor cells that express critical gliogenesis genes Ascl1, Egfr, and Olig2. The increased Ascl1 expression and appearance of Egfr + and Olig2 + cortical progenitors are concurrent with the switch from excitatory neurogenesis to gliogenesis and OB interneuron neurogenesis in the cortex. While Shh signaling promotes Olig2 expression in the developing spinal cord, the exact mechanism for this transcriptional regulation is not known. Furthermore, the transcriptional regulation of Olig2 and Egfr has not been explored. Here, we show that in cortical progenitor cells, multiple regulatory programs, including Pax6 and Gli3, prevent precocious expression of Olig2, a gene essential for production of cortical oligodendrocytes and astrocytes. We identify multiple enhancers that control Olig2 expression in cortical progenitors and show that the mechanisms for regulating Olig2 expression are conserved between the mouse and human. Our study reveals evolutionarily conserved regulatory logic controlling the lineage switch of cortical neural stem cells.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1972

Effects of endotoxin on monoamine metabolism in the rat.

Examination of effects of administered endotoxin on catecholamine metabolism in the rat brain, sympathetic neurons, and adrenal medulla. It is found that endotoxin, administered intraperitoneally, lowers the norepinephrine content in peripheral sympathetic neurons and the brain, and the catecholamine content in the adrenal medulla. It also accelerates the disappearance of H3-norepinephrine from all these tissues. It is therefore suggested that the effects of endotoxin on body temperature may be mediated in part by central non-adrenergic neurons.

Pohorecky, L. A.↗
NASA NTRS1973

Simulated weightlessness in fish and neurophysiological studies on memory storage

Simulated weightlessness was used to study the different types of gravity responses in blind fish. It was found that a shift in the direction of low magnitude acceleration in weightlessness causes a rapid 180 deg turn in the blind fish, while a shift in the direction of the applied acceleration in the earth's gravitational field is not significant because of a higher acceleration magnitude threshold than during the zero g condition. This increased responsiveness seems to be explained by a combination of directional sensitivity with a Weber-Fechner relationship of increased receptor sensitivity at diminished levels of background stimulation. Neurophysical studies of the statocyst nerve of the gastropod Mollusc Pleurobranchaea Californica were undertaken in order to understand how complex otolith systems operate. Information storage was investigated on relatively simple neuronal networks in the mollusc Aplysia. Intracellular electrical stimulation of isolated neurons show that a manipulation of autoditonous rhymicity is possible. It was also found that glycolysis and oxidative phosphorylation are involved in inherent rhymicity of Aplysis neurons.

Vonbaumgarten, R. J.↗
NASA NTRS1979

Loudness of steady sounds - A new theory

A new mathematical theory for calculating the loudness of steady sounds from power summation and frequency interaction, based on psychoacoustic and physiological information, assuems that loudness is a subjective measure of the electrical energy transmitted along the auditory nerve to the central nervous system. The auditory system consists of the mechanical part modeled by a bandpass filter with a transfer function dependent on the sound pressure, and the electrical part where the signal is transformed into a half-wave reproduction represented by the electrical power in impulsive discharges transmitted along neurons comprising the auditory nerve. In the electrical part the neurons are distributed among artificial parallel channels with frequency bandwidths equal to 'critical bandwidths for loudness', within which loudness is constant for constant sound pressure. The total energy transmitted to the central nervous system is the sum of the energy transmitted in all channels, and the loudness is proportional to the square root of the total filtered sound energy distributed over all channels. The theory explains many psychoacoustic phenomena such as audible beats resulting from closely spaced tones, interaction of sound stimuli which affect the same neurons affecting loudness, and of individually subliminal sounds becoming audible if they lie within the same critical band.

Howes, W. L.↗
NASA NTRS1980

Topochemical differences in the amount of RNA in the motoneurons of the spinal chord in hypoxia and hypokinesia

Reactions to hypoxia and hypoknesia were compared by measuring charges in the amount of ribonucleic acid (RNA) in the cytoplasm of neurons of the intumescentia cervicalis and lumbalis. Animals were subjected to hypoxia, hypokinesia and both combined and a control group to neither. A total of two groups of motoneurons were compared, one innervating the respiratory musculature, the other the musculature of the lower extremities, so that hypoxic hypoxia would probably affect the first group primarily and hypokinesia the second. Results indicate that neither affect the amount of RNA in the neurons of the first group but a significant increase is noted in neurons of the second group. Other significant results are reported.

Brumberg, V. A.↗
NASA NTRS1988

Electronic Neural-Network Simulator

Experimental circuits faster than simulation programs run on digital computers. Serial shift register routes clock pulses C1 to neurons in sequence. Clock pulses C2 interrogate neurons. Neuron interconnection information stored in simulated synapses. Can be expanded to greater complexity.

Moopenn, Alex W.↗
NASA NTRS1989

Anatomical study of the final common pathway for vocalization in the cat

Results are presented of an anatomical study of the neuronal pathways in the cat, via which the periaqueductal gray (PAG) produces excitation of motoneurons involved in vocalization. It is shown that a specific cell group in the lateral part of the caudal PAG and in the tegmentum just lateral to it projects bilaterally to the nucleus retroambiguus (NRA) in the caudal medulla oblongata. Neurons in the NRA in turn project, via a contralateral pathway through the ventral funiculus of the spinal cord, to the motoneuronal cell groups innervating intercostal and abdominal muscles. In the brainstem, the NRA neurons project to the motoneuronal cell groups innervating mouth-opening and perioral muscles as well as to motoneurons innervating the pharynx, soft palate, and tongue. These results indicate that the projections from PAG via NRA to vocalization motoneurons form the final common pathway in vocalization.

Holstege, Gert↗
NASA NTRS1991

On the capacity of ternary Hebbian networks

Networks of ternary neurons storing random vectors over the set -1,0,1 by the so-called Hebbian rule are considered. It is shown that the maximal number of stored patterns that are equilibrium states of the network with probability tending to one as N tends to infinity is at least on the order of (N exp 2-1/alpha)/K, where N is the number of neurons, K is the number of nonzero elements in a pattern, and t = alpha x K, alpha between 1/2 and 1, is the threshold in the neuron function. While, for small K, this bound is similar to that obtained for fully connected binary networks, the number of interneural connections required in the ternary case is considerably smaller. Similar bounds, incorporating error probabilities, are shown to guarantee, in the same probabilistic sense, the correction of errors in the nonzero elements and in the location of these elements.

Baram, Yoram↗
NASA NTRS1989

Intelligent Network Management and Functional Cerebellum Synthesis

Transdisciplinary modeling of the cerebellum across histology, physiology, and network engineering provides preliminary results at three organization levels: input/output links to central nervous system networks; links between the six neuron populations in the cerebellum; and computation among the neurons of the populations. Older models probably underestimated the importance and role of climbing fiber input which seems to supply write as well as read signals, not just to Purkinje but also to basket and stellate neurons. The well-known mossy fiber-granule cell-Golgi cell system should also respond to inputs originating from climbing fibers. Corticonuclear microcomplexing might be aided by stellate and basket computation and associate processing. Technological and scientific implications of the proposed cerebellum model are discussed.

Loebner, Egon E.↗
NASA NTRS1992

Fast temporal neural learning using teacher forcing

A neural network is trained to output a time dependent target vector defined over a predetermined time interval in response to a time dependent input vector defined over the same time interval by applying corresponding elements of the error vector, or difference between the target vector and the actual neuron output vector, to the inputs of corresponding output neurons of the network as corrective feedback. This feedback decreases the error and quickens the learning process, so that a much smaller number of training cycles are required to complete the learning process. A conventional gradient descent algorithm is employed to update the neural network parameters at the end of the predetermined time interval. The foregoing process is repeated in repetitive cycles until the actual output vector corresponds to the target vector. In the preferred embodiment, as the overall error of the neural network output decreasing during successive training cycles, the portion of the error fed back to the output neurons is decreased accordingly, allowing the network to learn with greater freedom from teacher forcing as the network parameters converge to their optimum values. The invention may also be used to train a neural network with stationary training and target vectors.

Toomarian, Nikzad↗
NASA NTRS1992

Analysis of fault-tolerant neurocontrol architectures

The fault-tolerance of analog parallel distributed implementations of a multivariable aircraft neurocontroller is analyzed by simulating weight and neuron failures in a simplified scheme of analog processing based on the functional architecture of the ETANN chip (Electrically Trainable Artificial Neural Network). The neural information processing is found to be only partially distributed throughout the set of weights of the neurocontroller synthesized with the backpropagation algorithm. Although the degree of distribution of the neural processing, and consequently the fault-tolerance of the neurocontroller, could be enhanced using Locally Distributed Weight and Neuron Approaches, a satisfactory level of fault-tolerance could only be obtained by retraining the degrated VLSI neurocontroller. The possibility of maintaining neurocontrol performance and stability in the presence of single weight of neuron failures was demonstrated through an automated retraining procedure of the neurocontroller based on a pre-programmed choice and sequence of the training parameters.

Troudet, T.↗
NASA NTRS1992

Adding dynamic rules to self-organizing fuzzy systems

This paper develops a Dynamic Self-Organizing Fuzzy System (DSOFS) capable of adding, removing, and/or adapting the fuzzy rules and the fuzzy reference sets. The DSOFS background consists of a self-organizing neural structure with neuron relocation features which will develop a map of the input-output behavior. The relocation algorithm extends the topological ordering concept. Fuzzy rules (neurons) are dynamically added or released while the neural structure learns the pattern. The DSOFS advantages are the automatic synthesis and the possibility of parallel implementation. A high adaptation speed and a reduced number of neurons is needed in order to keep errors under some limits. The computer simulation results are presented in a nonlinear systems modelling application.

Buhusi, Catalin V.↗
NASA NTRS1990

Hair cell tufts and afferent innervation of the bullfrog crista ampullaris

Within the bullfrog semicircular canal crista, hair cell tuft types were defined and mapped with the aid of scanning electron microscopy. Dye-filled planar afferent axons had mean distal axonal diameters of 1.6-4.9 microns, highly branched arbors, and contacted 11-24 hair cells. Dye-filled isthmus afferent axons had mean distal axonal diameters of 1.8-7.9 microns, with either small or large field arbors contacting 4-9 or 25-31 hair cells. The estimated mean number of contacts per innervated hair cell was 2.2 for planar and 1.3 for isthmus afferent neurons. Data on evoked afferent responses were available only for isthmus units that were observed to respond to our microrotational stimuli. Of 21 such afferent neurons, eight were successfully dye-filled. Within this sample, high-gain units had large field arbors and lower-gain units had small field arbors. The sensitivity of each afferent neuron was analyzed in terms of noise equivalent input (NEI), the stimulus amplitude for which the afferent response amplitude is just equivalent to the rms deviation of the instantaneous spike rate. NEI for isthmus units varied from 0.63 to 8.2 deg/s; the mean was 3.2 deg/s.

Myers, Steven F.↗
NASA NTRS1987

Gamma-aminobutyric acid (GABA) and neuropeptides in neural areas mediating motion-induced emesis

Immunocytochemical methods were employed to localize the neurotransmitter amino acid gamma-aminobutyric acid and the neuropeptides substance P and Met-enkephalin in the area postrema (AP), area subpostrema (ASP), nucleus of the tractus solitarius (NTS), dorsal motor nucleus of the vagus nerve (DMNV), and lateral vestibular nucleus (LVN). Glutamic acid decarboxylase immunoreactive (GAD-IR) terminals and fibers were observed in the AP and particularly in the ASP. A gradual decrease in the density of terminals was seen towards the solitary complex. The DMNV revealed irregularly scattered GAD-IR terminals within the neuropil or closely surrounding neuronal cell bodies. The LVN, particularly the dorsal division, showed numerous axon terminals which were mostly localize around large neurons and their proximal dendrites. Substance P immunoreactive (SP-IR) terminals and fibers showed high density in the solitary complex, in particular within the lateral division. The ASP showed medium to low density of SP-IR fibers and terminals. The AP exhibited a small number of fibers and terminals irregularly distributed. The DMNV revealed a high density of SP-IR terminals and fibers that were mainly concentrated in the periphery. Very few terminals were detected in the LVN. Met-enkephalin immunoreactive (Met-Enk-IR) fibers and terminals showed high density and uniform distribution in the DMNV. Scattered terminals and fibers were observed in the AP, ASP, and NTS (particularly the lateral division). The very few fibers were observed in the LVN surrounded the neuronal cell bodies. The present report is part of a study designed to investigate the interaction between neuropeptides and conventional neurotransmitters under conditions producing motion sickness and in the process of sensory-motor adaptation.

F Damelio↗
NASA NTRS1994

Innovation and application of ANN in Europe demonstrated by Kohonen maps

One of the most important contributions to neural networks comes from Kohonen, Helsinki/Espoo, Finland, who had the idea of self-organizating maps in 1981. He verified his idea by an algorithm of which many applications make use of. The impetus for this idea came from biology, a field where the Europeans have always been very active at several research laboratories. The challenge was to model the self-organization found in the brain. Today one goal is the development of more sophisticated neurons which model the biological neurons more exactly. They should come to a better performance of neural nets with only a few complex neurons instead of many simple ones. A lot of application concepts arise from this idea: Kohonen himself applied it to speech recognition, but the project did not overcome much more than the recognition of the numerals one to ten at that time. A more promising application for self-organizing maps is process control and process monitoring. Several proposals were made which concern parameter classification of semiconductor technologies, design of integrated circuits, and control of chemical processes. Self-organizing maps were applied to robotics. The neural concept was introduced into electric power systems. At Dortmund we are working on a system which has to monitor the quality and the reliability of gears and electrical motors in equipment installed in coal mines. The results are promising and the probability to apply the system in the field is very high. A special feature of the system is that linguistic rules which are embedded in a fuzzy controller analyze the data of the self-organizing map in regard to life expectation of the gears. It seems that the fuzzy technique will introduce the technology of neural networks in a tandem mode. These technologies together with the genetic algorithms start to form the attractive field of computational intelligence.

Goser, Karl↗