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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Quantitative Reflection Imaging for the Morphology and Dynamics of Live Aplysia californica Pedal Ganglion Neurons Cultured on Nanostructured Plasmonic Crystals

We describe a reflection imaging system that consists of a plasmonic crystal, a common laboratory microscope, and band-pass filters for use in the quantitative imaging and in situ monitoring of live cells and their substrate interactions. Surface plasmon resonance (SPR) provides a highly sensitive method to monitor changes in physicochemical properties occurring at metal-dielectric interfaces. Polyelectrolyte thin films deposited using the layer-by-layer (LBL) self-assembly method provide a reference system for calibrating the reflection contrast changes that occur when the polyelectrolyte film thickness changes and provide insight into the optical responses that originate from the multiple plasmonic features supported by this imaging system. Finitedifference time-domain (FDTD) simulations of the optical responses measured experimentally from the polyelectrolyte reference system are used to provide a calibration of the optical system for subsequent use in quantitative studies investigating live cell dynamics in cultures supported on a plasmonic crystal substrate. Live Aplysia californica pedal ganglion neurons cultured in artificial seawater were used as a model system through which to explore the utility of this plasmonic imaging technique. Here, the morphology of cellular peripheral structures ≲80 nm in thickness were quantitatively analyzed, and the dynamics of their trypsin-induced surface detachment were visualized. These results illustrate the capacities of this system for use in investigations of the dynamics of ultrathin cellular structures within complex bioanalytical environments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Impaired neuron differentiation in GBA-associated Parkinson’s disease is linked to cell cycle defects in organoids

The mechanisms underlying Parkinson’s disease (PD) etiology are only partially understood despite intensive research conducted in the field. Recent evidence suggests that early neurodevelopmental defects might play a role in cellular susceptibility to neurodegeneration. To study the early developmental contribution of GBA mutations in PD we used patient-derived iPSCs carrying a heterozygous N370S mutation in the GBA gene. Patient-specific midbrain organoids displayed GBA-PD relevant phenotypes such as reduction of GCase activity, autophagy impairment, and mitochondrial dysfunction. Genome-scale metabolic (GEM) modeling predicted changes in lipid metabolism which were validated with lipidomics analysis, showing significant differences in the lipidome of GBA-PD. In addition, patient-specific midbrain organoids exhibited a decrease in the number and complexity of dopaminergic neurons. This was accompanied by an increase in the neural progenitor population showing signs of oxidative stress-induced damage and premature cellular senescence. These results provide insights into how GBA mutations may lead to neurodevelopmental defects thereby predisposing to PD pathology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

An artificial spiking quantum neuron

Abstract Artificial spiking neural networks have found applications in areas where the temporal nature of activation offers an advantage, such as time series prediction and signal processing. To improve their efficiency, spiking architectures often run on custom-designed neuromorphic hardware, but, despite their attractive properties, these implementations have been limited to digital systems. We describe an artificial quantum spiking neuron that relies on the dynamical evolution of two easy to implement Hamiltonians and subsequent local measurements. The architecture allows exploiting complex amplitudes and back-action from measurements to influence the input. This approach to learning protocols is advantageous in the case where the input and output of the system are both quantum states. We demonstrate this through the classification of Bell pairs which can be seen as a certification protocol. Stacking the introduced elementary building blocks into larger networks combines the spatiotemporal features of a spiking neural network with the non-local quantum correlations across the graph.

Kristensen, Lasse Bjørn (ORCID:0000000239398170)↗
DOE OSTI2014

Quantitation and localization of intracellular redox active metals by X-ray fluorescence microscopy in cortical neurons derived from APP and APLP2 knockout tissue

The amyloid precursor protein (APP) gene family includes APP and the amyloid precursor-like proteins, APLP1 and APLP2. These proteins contain metal binding sites for copper, zinc and iron and are known to have physiological roles in modulating the metal homeostasis in brain cells. Here we report the application of X-ray fluorescence microscopy (XFM) to investigate the subcellular distribution patterns of the metal ions Cu, Zn, Fe, and Ca in individual neurons derived from APP and APLP2 knockout mice brains to further define their role in metal homeostasis. These studies add to the growing body of data that the APP family of proteins are metalloproteins that have shared as well as distinct effects on metals. As we continue to delineate the cellular effects of the APP family of proteins it is important to consider how metals are involved in their actions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Optical control of neuronal activity using a light-operated GIRK channel opener (LOGO)

G-protein coupled inwardly rectifying potassium (GIRK) channels are expressed throughout the human body and are an integral part of inhibitory signal transduction pathways. Upon binding of G βγ subunits released from G-protein coupled receptors (GPCRs), GIRK channels open and reduce the activity of excitable cells via hyperpolarization. As such, they play a role in cardiac output, the coordination of movement and cognition. Due to their involvement in a multitude of pathways, the precision control of GIRK channels is an important endeavour. Here, we describe the development of the photoswitchable agonist LOGO (the Light-Operated GIRK channel Opener), which activates GIRK channels in the dark and is rapidly deactivated upon exposure to long wavelength UV irradiation. LOGO is the first photochromic K+ channel opener and selectively targets channels that contain the GIRK1 subunit. It can be used to optically silence action potential firing in dissociated hippocampal neurons and LOGO exhibits activity in vivo, controlling the motility of zebrafish larvae in a light-dependent fashion. We envisage that LOGO will be a valuable research tool to dissect the function of GIRK channels from other GPCR dependent signalling pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Spin switches for compact implementation of neuron and synapse

Nanomagnets driven by spin currents provide a natural implementation for a neuron and a synapse: currents allow convenient summation of multiple inputs, while the magnet provides the threshold function. The objective of this paper is to explore the possibility of a hardware neural network implementation using a spin switch (SS) as its basic building block. SS is a recently proposed device based on established technology with a transistor-like gain and input-output isolation. This allows neural networks to be constructed with purely passive interconnections without intervening clocks or amplifiers. The weights for the neural network are conveniently adjusted through analog voltages that can be stored in a non-volatile manner in an underlying CMOS layer using a floating gate low dropout voltage regulator. The operation of a multi-layer SS neural network designed for character recognition is demonstrated using a standard simulation model based on coupled Landau-Lifshitz-Gilbert equations, one for each magnet in the network.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Macro- and micro-chaotic structures in the Hindmarsh-Rose model of bursting neurons

We study a plethora of chaotic phenomena in the Hindmarsh-Rose neuron model with the use of several computational techniques including the bifurcation parameter continuation, spike-quantification, and evaluation of Lyapunov exponents in bi-parameter diagrams. Such an aggregated approach allows for detecting regions of simple and chaotic dynamics, and demarcating borderlines—exact bifurcation curves. We demonstrate how the organizing centers—points corresponding to codimension-two homoclinic bifurcations—along with fold and period-doubling bifurcation curves structure the biparametric plane, thus forming macro-chaotic regions of onion bulb shapes and revealing spike-adding cascades that generate micro-chaotic structures due to the hysteresis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Impact of weak excitatory synapses on chaotic transients in a diffusively coupled Morris-Lecar neuronal network

Spatiotemporal chaos collapses to either a rest state or a propagating pulse solution in a ring network of diffusively coupled, excitable Morris-Lecar neurons. Weak excitatory synapses can increase the Lyapunov exponent, expedite the collapse, and promote the collapse to the rest state rather than the pulse state. A single traveling pulse solution may no longer be asymptotic for certain combinations of network topology and (weak) coupling strengths, and initiate spatiotemporal chaos. Multiple pulses can cause chaos initiation due to diffusive and synaptic pulse-pulse interaction. In the presence of chaos initiation, intermittent spatiotemporal chaos exists until typically a collapse to the rest state.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

An integrated analog O/E/O link for multi-channel laser neurons

We demonstrate an analog O/E/O electronic link to allow integrated laser neurons to accept many distinguishable, high bandwidth input signals simultaneously. This device utilizes wavelength division multiplexing to achieve multi-channel fan-in, a photodetector to sum signals together, and a laser cavity to perform a nonlinear operation. Its speed outpaces accelerated-time neuromorphic electronics, and it represents a viable direction towards scalable networking approaches.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Synapse-specific catecholaminergic modulation of neuronal glutamate release

Norepinephrine in vertebrates and its invertebrate analog, octopamine, regulate the activity of neural circuits. We find that, when hungry,Drosophilalarvae switch activity in type II octopaminergic motor neurons (MNs) to high-frequency bursts, which coincide with locomotion-driving bursts in type I glutamatergic MNs that converge on the same muscles. Optical quantal analysis across hundreds of synapses simultaneously reveals that octopamine potentiates glutamate release by tonic type Ib MNs, but not phasic type Is MNs, and occurs via the G q -coupled octopamine receptor (OAMB). OAMB is more abundant in type Ib terminals and acts through diacylglycerol and its target Unc13A, a key component of the glutamate release machinery. Potentiation varies significantly—by up to 1,000%—across synapses of a single Ib axon, with synaptic Unc13A levels determining both release probability and potentiation. We propose that a dual molecular mechanism—an upstream neuromodulator receptor and a downstream transmitter release controller—fine-tunes catecholaminergic modulation so that strong tonic synapses exhibit large potentiation, while weaker tonic and all phasic synapses maintain consistency, yielding a sophisticated regulation of locomotor behavior.

Science & Technology - Other Topics↗
DOE OSTI2018

Anticonvulsant drug polytherapy stops status epilepticus and prevents neuronal loss in soman‐exposed rats

Introduction When treatment of status epilepticus (SE) is delayed, seizures become self‐sustaining and refractory to benzodiazepine therapy. Chemical warfare nerve agents (CWNAs), such as soman(GD), increase acetylcholine through inhibition of acetylcholine sterase and can lead to SE if seizures are not treated quickly and controlled. Prolonged seizures may lead to extensive neuropathology, spontaneous recurrent seizures and long‐term performance deficits. To identify a better treatment against pharmacoresistant seizures caused by GD exposure, we are using combinations of drugs aimed at reversing the effects of maladaptive receptor trafficking that follows CWNA exposure. Methods Rats were implanted with telemetry transmitters for continuous monitoring of EEG, body temperature and activity. After surgical recovery, rats were exposed to 1.2 LD 50 GD and treated 1 min later with atropine sulfate and the oxime HI‐6 and then 40 min after seizure onset with the anticonvulsant phenobarbital with or without the NMDA antagonist ketamine (PHE/KET), the benzodiazepine midazolam (PHE/MDZ) or a combination of all three drugs (PHE/KET/MDZ).Two weeks after exposure, rat brains were sectioned and stained for neuropathology assessments. Results Triple therapy with PHE/KET/MDZ reduced total time spent in seizures (SE +early recurrent seizures) in the first 72 h and reduced the number of spontaneous recurrent seizures compared to midazolam monotherapy. Tripletherapy also reduced the duration of toxic signs in the hours following GD‐exposure and prevented the development of hyperactivity that occurs in the weeks following exposure compared to GD/MDZ monotherapy. In addition, tripletherapy reduced loss of neurons in the piriform cortex and thalamus compared to GD/MDZ monotherapy. Conclusion Triple therapy with PHE/KET/MDZ hadanticonvulsant, antiepileptic, and neuroprotective effects compared with midazolammonotherapy in GD‐exposed rats. Triple therapy may be a highly effective approach against pharmacoresistant seizures, such as those caused by GD exposure, and may allow for administration of lower doses, resulting in fewer side effects than are often seen with large doses of individual drug therapies. Disclaimer: The views expressed in this abstract are those of the authors and do not reflect the official policy of the Department of the Army, Department of Defense, or the U.S. Government. The experimental protocol was approved by the Animal Care and Use Committee at the United States Army Medical Research Institute of Chemical Defense and all procedures were conducted in accordance with the principles stated in the Guide for the Care and Use of Laboratory Animals and the Animal Welfare Act of 1966 (P.L. 89‐544), as amended. Support or Funding Information KatieWalker, Erica Kundrick and Sean O'Brien were supported in part by an appointment to the Research Participation Program for the U.S. Army Medical Research and Materiel Command administered by the Oak Ridge Institute for Science and Education through an agreement between the U.S. Department of Energy and U.S. Army Medical Research and Materiel Command. This research was supported by the NIH U01 to Dr. Claude Wasterlain.

Stone, Michael↗
DOE OSTI2018

Relaxation of a Spiking Mott Artificial Neuron

We consider the phenomenon of electric Mott transition (EMT), which is an electrically induced insulator-to-metal transition. Experimentally, it is observed that depending on the magnitude of the electric excitation, the final state may show a short-lived or a long-lived resistance change. We extend a previous model for the EMT to include the effect of local structural distortions through an elastic energy term. We find that by strong electric pulsing, the induced metastable phase may become further stabilized by the electroelastic effect. We present a systematic study of the model by numerical simulations and compare the results to experiments in Mott insulators of the AM 4 Q 8 family. Our work significantly extends the scope of our recently introduced leaky-integrate-and-fire Mott neuron [P. Stoliar et al., Adv. Funct. Mat. 27, 1604740 (2017)] to provide a better insight into the physical mechanism of its relaxation. This is a key feature for future implementations of neuromorphic circuits.

bio-inspired↗
DOE OSTI2014

Associative memory in phasing neuron networks

We studied pattern formation in a network of coupled Hindmarsh-Rose model neurons and introduced a new model for associative memory retrieval using networks of Kuramoto oscillators. Hindmarsh-Rose Neural Networks can exhibit a rich set of collective dynamics that can be controlled by their connectivity. Specifically, we showed an instance of Hebb's rule where spiking was correlated with network topology. Based on this, we presented a simple model of associative memory in coupled phase oscillators.

Nair, Niketh↗
DOE OSTI2014

Power Consumption During Neuronal Computation

Maintaining the ability of the nervous system to perceive, remember, process, and react to the outside world necessitates a continuous energy supply. However, the overall power consumption is remarkably low, which has inspired engineers to mimic nervous systems in designing artificial cochlea, retinal implants, and brain–computer interfaces (BCIs) to improve the quality of life in patients. Such neuromorphic devices are both energy efficient and increasingly able to emulate many functions of the human nervous system. We explore the energy constraints of neuronal signaling within biology, review the quantitative tradeoff between energy use and information processing, and ask whether the biophysics and design of nerve cells minimizes energy consumption.

42 ENGINEERING↗
DOE OSTI2020

Heterotrimeric G‐protein, Gi1, is involved in the regulation of proliferation, neuronal migration, and dendrite morphology during cortical development in vivo

Abstract Heterotrimeric G‐proteins are composed of α, β, and γ subunits, and function as signal transducers. Critical roles of the α‐subunits of Gi/o family heterotrimeric G‐proteins, Gαi2, and Gαo1, have so far been reported in brain development and neurodevelopmental disorders. In this study, we tried to clarify the role of Gαi1, α‐subunit of another Gi/o family member Gi1, during corticogenesis, based on the recent identification of its gene abnormalities in neurodevelopmental disorders. In western blot analyses, Gαi1 was found to be expressed in mouse brain in a developmental stage‐dependent manner. Morphological analyses revealed that Gαi1 was broadly distributed in cerebral cortex with relatively high expression in the ventricular zone (VZ) at embryonic day (E) 14. Meanwhile, Gαi1 was enriched in membrane area of yet unidentified early mitotic cells in the VZ and the marginal zone at E14. Acute knockdown of Gαi1 with in utero electroporation in cerebral cortex caused cell cycle elongation of the neural progenitor cells and promoted their cell cycle exit. Gαi1‐deficient cortical neurons also exhibited delayed radial migration during corticogenesis, with abnormally elongated leading processes and hampered nucleokinesis. In addition, silencing of Gαi1 prevented basal dendrite development. The migration and dendritic phenotypes were at least partially rescued by an RNAi‐resistant version of Gαi1. Collectively, these results strongly suggest a crucial role of Gi1 in cortical development, and disturbance of its function may cause deficits in synaptic network formation, leading to neurodevelopmental disorders. image

Hamada, Nanako↗
DOE OSTI2018

The Probe Length Effect on the Cantilever of an Atomic Force Microscope in Measuring the Mechanical Properties of Living Neurons

Living sensory neurons were studied by atomic force microscopy in the PeakForce QNM mode under near-physiological conditions. The dependence of the measured apparent Young modulus of cells on the ratio of the probe height to the beam length on a used cantilever was revealed. A qualitative explanation based on the analysis of beam strains in two limit cases, in which the probe slides over a studied object and the probe sticks to the latter, was given to the obtained result. It was proposed to classify native cells by the character of their interaction with the probe (sliding or sticking).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Multimodal parameter spaces of a complex multi-channel neuron model

One of the most common types of models that helps us to understand neuron behavior is based on the Hodgkin–Huxley ion channel formulation (HH model). A major challenge with inferring parameters in HH models is non-uniqueness: many different sets of ion channel parameter values produce similar outputs for the same input stimulus. Such phenomena result in an objective function that exhibits multiple modes (i.e., multiple local minima). This non-uniqueness of local optimality poses challenges for parameter estimation with many algorithmic optimization techniques. HH models additionally have severe non-linearities resulting in further challenges for inferring parameters in an algorithmic fashion. To address these challenges with a tractable method in high-dimensional parameter spaces, we propose using a particular Markov chain Monte Carlo (MCMC) algorithm, which has the advantage of inferring parameters in a Bayesian framework. The Bayesian approach is designed to be suitable for multimodal solutions to inverse problems. We introduce and demonstrate the method using a three-channel HH model. We then focus on the inference of nine parameters in an eight-channel HH model, which we analyze in detail. We explore how the MCMC algorithm can uncover complex relationships between inferred parameters using five injected current levels. The MCMC method provides as a result a nine-dimensional posterior distribution, which we analyze visually with solution maps or landscapes of the possible parameter sets. The visualized solution maps show new complex structures of the multimodal posteriors, and they allow for selection of locally and globally optimal value sets, and they visually expose parameter sensitivities and regions of higher model robustness. We envision these solution maps as enabling experimentalists to improve the design of future experiments, increase scientific productivity and improve on model structure and ideation when the MCMC algorithm is applied to experimental data.

97 MATHEMATICS AND COMPUTING↗