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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 163 records · Page 9

Modelling the firing pattern of bullfrog vestibular neurons responding to naturalistic stimuli

We have developed a neural system identification method for fitting models to stimulus-response data, where the response is a spike train. The method involves using a general nonlinear optimisation procedure to fit models in the time domain. We have applied the method to model bullfrog semicircular canal afferent neuron responses during naturalistic, broad-band head rotations. These neurons respond in diverse ways, but a simple four parameter class of models elegantly accounts for the various types of responses observed. c1999 Elsevier Science B.V. All rights reserved.

Non-NASA Center↗

Molecular and structural basis of olfactory sensory neuron axon coalescence by Kirrel receptors

Projections from sensory neurons of olfactory systems coalesce into glomeruli in the brain. The Kirrel receptors are believed to homodimerize via their ectodomains and help separate sensory neuron axons into Kirrel2- or Kirrel3-expressing glomeruli. Here, we present the crystal structures of homodimeric Kirrel receptors and show that the closely related Kirrel2 and Kirrel3 have evolved specific sets of polar and hydrophobic interactions, respectively, disallowing heterodimerization while preserving homodimerization, likely resulting in proper segregation and coalescence of Kirrel-expressing axons into glomeruli. We show that the dimerization interface at the N-terminal immunoglobulin (IG) domains is necessary and sufficient to create homodimers and fail to find evidence for a secondary interaction site in Kirrel ectodomains. Furthermore, we show that abolishing dimerization of Kirrel3 in vivo leads to improper formation of glomeruli in the mouse accessory olfactory bulb as observed in Kirrel3 –/– animals. Our results provide evidence for Kirrel3 homodimerization controlling axonal coalescence.

59 BASIC BIOLOGICAL SCIENCES↗

Two-dimensional materials for bio-realistic neuronal computing networks

Two-dimensional (2D) van der Waals materials have found broad utility in a diverse range of applications including electronics, optoelectronics, renewable energy, and quantum information technologies. Meanwhile, exponentially growing digital data coupled with the ubiquity of artificial intelligence algorithms have generated significant interest in edge neuromorphic computing as an alternative to centralized cloud computing. The drive to incorporate neuroscience principles into computing hardware is motivated by the low power consumption, parallel processing, and reconfigurability of the human brain. The diverse library of 2D materials with atomic-level thicknesses, exceptional electrostatic tunability, and integration versatility is particularly well-suited for realizing bio-realistic synaptic and neuronal functionality. Here, we summarize past and present work in this field and outline the frontier challenges that have not yet been overcome. Here we also delineate potential solutions and suggest that the neuroscience principles of criticality and synchrony have the potential to inspire breakthrough applications of 2D materials in neuronal computing networks.

36 MATERIALS SCIENCE↗

Wireless Optogenetic Modulation of Cortical Neurons Enabled by Radioluminescent Nanoparticles

While offering high precision control of neural circuits, optogenetics is hampered by the necessity to implant fiber-optic waveguides in order to deliver photons to genetically engineered light-gated neurons in the brain. Unlike laser light, X-rays freely pass biological barriers. In this work, we show that radioluminescent Gd 2 (WO 4 ) 3 :Eu nanoparticles, which absorb an external X-rays energy and then down-converter it into optical photons with wavelengths of ~610 nm, can be used for the transcranial stimulation of cortical neurons expressing red-shifted, ~590-630 nm, channelrhodopsin ReaChR, thereby promoting optogenetic neural control to the practical implementation of minimally-invasive wireless deep brain stimulation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A NWB-based dataset and processing pipeline of human single-neuron activity during a declarative memory task

A challenge for data sharing in systems neuroscience is the multitude of different data formats used. Neurodata Without Borders: Neurophysiology 2.0 (NWB:N) has emerged as a standardized data format for the storage of cellular-level data together with meta-data, stimulus information, and behavior. A key next step to facilitate NWB:N adoption is to provide easy to use processing pipelines to import/export data from/to NWB:N. Here, we present a NWB-formatted dataset of 1863 single neurons recorded from the medial temporal lobes of 59 human subjects undergoing intracranial monitoring while they performed a recognition memory task. We provide code to analyze and export/import stimuli, behavior, and electrophysiological recordings to/from NWB in both MATLAB and Python. The data files are NWB:N compliant, which affords interoperability between programming languages and operating systems. This combined data and code release is a case study for how to utilize NWB:N for human single-neuron recordings and enables easy re-use of this hard-to-obtain data for both teaching and research on the mechanisms of human memory.

Science & Technology - Other Topics↗

Neuronally-derived tau is increased in experienced breachers and is associated with neurobehavioral symptoms

Military and law enforcement breachers are exposed to many low-level blasts during their training and occupational experiences in which they detonate explosives to force entry into secured structures. There is a concern that exposure to these repetitive blast events in career breachers could result in cumulative neurological effects. This study aimed to determine concentrations of neurofilament light (NF-L), tau, and amyloid-beta 42 (Aβ42) in serum and in neuronal-derived extracellular vesicles (EVs) in an experienced breacher population, and to examine biomarker associations with neurobehavioral symptoms. Thirty-four participants enrolled in the study: 20 experienced breachers and 14 matched military or civilian law enforcement controls. EV tau concentrations were significantly elevated in experienced breachers (0.3301 ± 0.5225) compared to controls (–0.4279 ± 0.7557; F = 10.43, p = 0.003). No statistically significant changes were observed in EV levels of NF-L or Aβ42 or in serum levels of NF-L, tau, or Aβ42 (p’s > 0.05). Elevated EV tau concentrations correlated with increased Neurobehavioral Symptom Inventory (NSI) score in experienced breachers (r = 0.596, p = 0.015) and predicted higher NSI score (F(1,14) = 7.702, p = 0.015, R 2 = 0.355). These findings show that neuronal-derived EV concentrations of tau are significantly elevated and associated with neurobehavioral symptoms in this sample of experienced breachers who have a history of many low-level blast exposures.

59 BASIC BIOLOGICAL SCIENCES↗

An electro-optical Mott neuron based on niobium dioxide

Various applications—including brain-like computing and on-chip artificial vision—increasingly demand a combination of electronic and photonic techniques. However, integrating both approaches on a single chip is challenging, and solutions typically rely on disparate components with power-hungry signal conversions. Here, in this paper, we report electro-optical Mott neurons that combine visible light emission with electrical threshold switching, as well as neuron-like oscillations. The devices are based on thin films of sputtered niobium dioxide (NbO 2 ), a Mott insulator–metal transition material, operating at room temperature and emitting light that peaks around 810 nm. Operando measurements reveal an electronic origin to the light emission: charge carrier relaxation initiated by high-field transport in the NbO 2 . Our devices combine electrical and optical functions within a single material, thereby expanding the options available for future artificial intelligence hardware.

electrical engineering↗

Viability of perturbative expansion for quantum field theories on neurons

Neural Network (NN) architectures that break statistical independence of parameters have been proposed as a new approach for simulating local quantum field theories (QFTs) [1]. In the infinite neuron number limit, single-layer NNs can exactly reproduce QFT results. This paper examines the viability of this architecture for perturbative calculations of local QFTs for finite neuron number N using scalar ϕ 4 theory in d Euclidean dimensions as an example. We find that the renormalized O(1/N ) corrections to two-and four-point correlators yield perturbative series which are sensitive to the UV cut-off and therefore have a weak convergence. We propose a modification to the architecture to improve this convergence and discuss constraints on the parameters of the theory and the scaling of N which allow us to extract accurate field theory results.

Sen, Srimoyee [Iowa State University, Ames, IA (Un↗

Modeling the Impacts of Material Properties on Oscillatory Neuron Behavior

In this study, neuromorphic computing, which mimics the functions of biological brains, offers improvements in both latency and energy efficiency over typical von Neumann computing architectures. Spiking neural networks can be especially power-efficient because they encode information temporally and can use more sparse electrical inputs. Here, we study the design of volatile memristors (variable resistors with memory) for neuronal devices, with particular consideration toward the feasibility of all-on-chip oscillation using built-in capacitance. We use circuit simulations to model the behavior of oscillator neurons with a range of realistic material properties. We find that energy inputs increase with insulating-phase resistivity, thermal conductivity, and device aspect ratio. However, we also find that the minimum capacitance needed for oscillation decreases with increasing insulating-phase resistivity, which opposes the constraints for power efficiency. Based on published data on NbO 2 , VO 2 , and EuNiO 3 , we find that existing materials can be engineered for all-on-chip spiking using their parasitic capacitance.

36 MATERIALS SCIENCE↗

Association of AK4 Protein From Stem Cell–Derived Neurons With Cognitive Reserve

Background and Objectives: Identifying protein targets that provide cognitive reserve is a strategy to prevent and treat Alzheimer disease and Alzheimer disease related dementias (AD/ADRD). Previous studies using bulk human brain tissue reported 12 proteins associated with cognitive reserve. This study examined whether the same proteins from induced neurons (iNs) are associated with cognitive reserve of their human donors. Methods: Here, induced pluripotent stem cell (iPSC) lines were generated from cryopreserved peripheral blood mononuclear cells of older adults who were autopsied as part of the Religious Orders Study or Rush Memory and Aging Project. Neurons were induced from iPSCs using a standard neurogenin2 protocol. Tandem mass tag proteomics analyses were conducted on iNs day 21. Cognitive reserve of their human donors was measured as person-specific slopes of cognitive change not accounted for by common neuropathologies. Results: The 53 human donors died at a mean age of 91 years, all were non-Latino White, and 36 (67.9%) were female. Eighteen were diagnosed with Alzheimer dementia proximate to death, and 34 had pathologic AD diagnosis at autopsy. Approximately 60% of the donors had above-average cognitive reserve such that their cognition declined slower than an average person with comparable burdens of neuropathologies. Eight of the 12 candidate proteins were quantified in iNs proteomics analyses. Higher adenylate kinase 4 (AK4) expression in iNs was associated with lower cognitive reserve, consistent with the previous report for brain AK4 expression. Discussion: By replicating cortical protein associations with cognitive reserve in human iNs, these data provide a valuable molecular readout for studying complex clinical phenotypes such as cognitive reserve in a dish.

59 BASIC BIOLOGICAL SCIENCES↗

Cat vestibular neurons that exhibit different responses to active and passive yaw head rotations

Neurons in the vestibular nuclei were recorded in alert cats during voluntary yaw rotations of the head and during the same rotations delivered with a turntable driven from a record of previous voluntary movements. During both voluntary and passive rotations, 35 percent (6/17) of neurons tested responded at higher rates or for a larger part of the movement during voluntary movements than during the same rotations delivered with the turntable. Neck sensory input was evaluated separately in many of these cells and can account qualitatively for the extra firing present during active movement.

Robinson, F. R.↗

Expiratory muscle control during vomiting - Role of brain stem expiratory neurons

The neural mechanisms controlling the muscles involved during vomiting were examined using decerebrated cats. In one experiment, the activity of the ventral respiratory group (VRG) expiratory (E) neurons was recorded during induced 'fictive vomiting' (i.e., a series of bursts of coactivation of abdominal and phrenic nerves that would be expected to produce expulsion in unparalyzed animals) and vomiting. In a second, abdominal muscle electromyographic and nerve activity were compared before and after sectioning the axons of descending VRG E neurons as they cross the midline between C1 and the obex (the procedure that is known to abolish expiratory modulation of internal intercostal muscle activity). The results of the study indicate that the abdominal muscles are controlled differently during respiration and vomiting.

Miller, A. D.↗

Adaptive Neurons For Artificial Neural Networks

Training time decreases dramatically. In improved mathematical model of neural-network processor, temperature of neurons (in addition to connection strengths, also called weights, of synapses) varied during supervised-learning phase of operation according to mathematical formalism and not heuristic rule. Evidence that biological neural networks also process information at neuronal level.

Tawel, Raoul↗

Numbers And Gains Of Neurons In Winner-Take-All Networks

Report presents theoretical study of gains required in neurons to implement winner-take-all electronic neural network of given size and related question of maximum size of winner-take-all network in which neurons have specified sigmoid transfer or response function with specified gain.

Brown, Timothy X.↗

GaAs-based optoelectronic neurons

An integrated, optoelectronic, variable thresholding neuron implemented monolithically in GaAs integrated circuit and exhibiting high differential optical gain and low power consumption is presented. Two alternative embodiments each comprise an LED monolithically integrated with a detector and two transistors. One of the transistors is responsive to a bias voltage applied to its gate for varying the threshold of the neuron. One embodiment is implemented as an LED monolithically integrated with a double heterojunction bipolar phototransistor (detector) and two metal semiconductor field effect transistors (MESFET's) on a single GaAs substrate and another embodiment is implemented as an LED monolithically integrated with three MESFET's (one of which is an optical FET detector) on a single GaAs substrate. The first noted embodiment exhibits a differential optical gain of 6 and an optical switching energy of 10 pJ. The second embodiment has a differential optical gain of 80 and an optical switching energy of 38 pJ. Power consumption is 2.4 and 1.8 mW, respectively. Input 'light' power needed to turn on the LED is 2 micro-W and 54 nW, respectively. In both embodiments the detector is in series with a biasing MESFET and saturates the other MESFET upon detecting light above a threshold level. The saturated MESFET turns on the LED. Voltage applied to the biasing MESFET gate controls the threshold.

Lin, Steven H.↗

Nonlinear functional approximation with networks using adaptive neurons

A novel mathematical framework for the rapid learning of nonlinear mappings and topological transformations is presented. It is based on allowing the neuron's parameters to adapt as a function of learning. This fully recurrent adaptive neuron model (ANM) has been successfully applied to complex nonlinear function approximation problems such as the highly degenerate inverse kinematics problem in robotics.

Tawel, Raoul↗

Neural network with dynamically adaptable neurons

This invention is an adaptive neuron for use in neural network processors. The adaptive neuron participates in the supervised learning phase of operation on a co-equal basis with the synapse matrix elements by adaptively changing its gain in a similar manner to the change of weights in the synapse IO elements. In this manner, training time is decreased by as much as three orders of magnitude.

Tawel, Raoul↗