Dynamic Training Elements in a Circuit Theory Course to Implement a Self-Directed Learning Process

ERIC Educational Resources Information Center

Krouk, B. I.; Zhuravleva, O. B.

2009-01-01

This paper reports on the implementation of a self-directed learning process in a circuit theory course, incorporating dynamic training elements which were designed on the basis of a cybernetic model of cognitive process management. These elements are centrally linked in a dynamic learning frame, created on the monitor screen, which displays the…

Monolithically integrated bacteriorhodopsin/semiconductor opto-electronic integrated circuit for a bio-photoreceiver.

PubMed

Xu, J; Bhattacharya, P; Váró, G

2004-03-15

The light-sensitive protein, bacteriorhodopsin (BR), is monolithically integrated with an InP-based amplifier circuit to realize a novel opto-electronic integrated circuit (OEIC) which performs as a high-speed photoreceiver. The circuit is realized by epitaxial growth of the field-effect transistors, currently used semiconductor device and circuit fabrication techniques, and selective area BR electro-deposition. The integrated photoreceiver has a responsivity of 175 V/W and linear photoresponse, with a dynamic range of 16 dB, with 594 nm photoexcitation. The dynamics of the photochemical cycle of BR has also been modeled and a proposed equivalent circuit simulates the measured BR photoresponse with good agreement.

Systematic Computation of Nonlinear Cellular and Molecular Dynamics with Low-Power CytoMimetic Circuits: A Simulation Study

PubMed Central

Papadimitriou, Konstantinos I.; Stan, Guy-Bart V.; Drakakis, Emmanuel M.

2013-01-01

This paper presents a novel method for the systematic implementation of low-power microelectronic circuits aimed at computing nonlinear cellular and molecular dynamics. The method proposed is based on the Nonlinear Bernoulli Cell Formalism (NBCF), an advanced mathematical framework stemming from the Bernoulli Cell Formalism (BCF) originally exploited for the modular synthesis and analysis of linear, time-invariant, high dynamic range, logarithmic filters. Our approach identifies and exploits the striking similarities existing between the NBCF and coupled nonlinear ordinary differential equations (ODEs) typically appearing in models of naturally encountered biochemical systems. The resulting continuous-time, continuous-value, low-power CytoMimetic electronic circuits succeed in simulating fast and with good accuracy cellular and molecular dynamics. The application of the method is illustrated by synthesising for the first time microelectronic CytoMimetic topologies which simulate successfully: 1) a nonlinear intracellular calcium oscillations model for several Hill coefficient values and 2) a gene-protein regulatory system model. The dynamic behaviours generated by the proposed CytoMimetic circuits are compared and found to be in very good agreement with their biological counterparts. The circuits exploit the exponential law codifying the low-power subthreshold operation regime and have been simulated with realistic parameters from a commercially available CMOS process. They occupy an area of a fraction of a square-millimetre, while consuming between 1 and 12 microwatts of power. Simulations of fabrication-related variability results are also presented. PMID:23393550

Cortico-striatal language pathways dynamically adjust for syntactic complexity: A computational study.

PubMed

Szalisznyó, Krisztina; Silverstein, David; Teichmann, Marc; Duffau, Hugues; Smits, Anja

2017-01-01

A growing body of literature supports a key role of fronto-striatal circuits in language perception. It is now known that the striatum plays a role in engaging attentional resources and linguistic rule computation while also serving phonological short-term memory capabilities. The ventral semantic and the dorsal phonological stream dichotomy assumed for spoken language processing also seems to play a role in cortico-striatal perception. Based on recent studies that correlate deep Broca-striatal pathways with complex syntax performance, we used a previously developed computational model of frontal-striatal syntax circuits and hypothesized that different parallel language pathways may contribute to canonical and non-canonical sentence comprehension separately. We modified and further analyzed a thematic role assignment task and corresponding reservoir computing model of language circuits, as previously developed by Dominey and coworkers. We examined the models performance under various parameter regimes, by influencing how fast the presented language input decays and altering the temporal dynamics of activated word representations. This enabled us to quantify canonical and non-canonical sentence comprehension abilities. The modeling results suggest that separate cortico-cortical and cortico-striatal circuits may be recruited differently for processing syntactically more difficult and less complicated sentences. Alternatively, a single circuit would need to dynamically and adaptively adjust to syntactic complexity. Copyright © 2016. Published by Elsevier Inc.

Topology and Dynamics of the Zebrafish Segmentation Clock Core Circuit

PubMed Central

Schröter, Christian; Isakova, Alina; Hens, Korneel; Soroldoni, Daniele; Gajewski, Martin; Jülicher, Frank; Maerkl, Sebastian J.; Deplancke, Bart; Oates, Andrew C.

2012-01-01

During vertebrate embryogenesis, the rhythmic and sequential segmentation of the body axis is regulated by an oscillating genetic network termed the segmentation clock. We describe a new dynamic model for the core pace-making circuit of the zebrafish segmentation clock based on a systematic biochemical investigation of the network's topology and precise measurements of somitogenesis dynamics in novel genetic mutants. We show that the core pace-making circuit consists of two distinct negative feedback loops, one with Her1 homodimers and the other with Her7:Hes6 heterodimers, operating in parallel. To explain the observed single and double mutant phenotypes of her1, her7, and hes6 mutant embryos in our dynamic model, we postulate that the availability and effective stability of the dimers with DNA binding activity is controlled in a “dimer cloud” that contains all possible dimeric combinations between the three factors. This feature of our model predicts that Hes6 protein levels should oscillate despite constant hes6 mRNA production, which we confirm experimentally using novel Hes6 antibodies. The control of the circuit's dynamics by a population of dimers with and without DNA binding activity is a new principle for the segmentation clock and may be relevant to other biological clocks and transcriptional regulatory networks. PMID:22911291

Hidden attractors in dynamical models of phase-locked loop circuits: Limitations of simulation in MATLAB and SPICE

NASA Astrophysics Data System (ADS)

Kuznetsov, N. V.; Leonov, G. A.; Yuldashev, M. V.; Yuldashev, R. V.

2017-10-01

During recent years it has been shown that hidden oscillations, whose basin of attraction does not overlap with small neighborhoods of equilibria, may significantly complicate simulation of dynamical models, lead to unreliable results and wrong conclusions, and cause serious damage in drilling systems, aircrafts control systems, electromechanical systems, and other applications. This article provides a survey of various phase-locked loop based circuits (used in satellite navigation systems, optical, and digital communication), where such difficulties take place in MATLAB and SPICE. Considered examples can be used for testing other phase-locked loop based circuits and simulation tools, and motivate the development and application of rigorous analytical methods for the global analysis of phase-locked loop based circuits.

Calculation and Analysis of Dynamic Characteristics of Multilink Permanent Magnetic Actuator in Vacuum Circuit Breaker

NASA Astrophysics Data System (ADS)

Liu, Yingyi; Yuan, Haiwen; Zhang, Qingjie; Chen, Degui; Yuan, Haibin

The dynamic characteristics are the key issues in the optimum design of a permanent magnetic actuator (PMA). A new approach to forecast the dynamic characteristics of the multilink PMA is proposed. By carrying out further developments of ADAMS and ANSOFT, a mathematic calculation model describing the coupling of mechanical movement, electric circuit and magnetic field considering eddy current effect, is constructed. With this model, the dynamic characteristics of the multilink PMA are calculated and compared with the experimental results. Factors that affect the opening time of the multilink PMA are analyzed with the model as well. The method is capable of providing a reference for the design of the PMA.

Lithium-ion battery cell-level control using constrained model predictive control and equivalent circuit models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xavier, MA; Trimboli, MS

This paper introduces a novel application of model predictive control (MPC) to cell-level charging of a lithium-ion battery utilizing an equivalent circuit model of battery dynamics. The approach employs a modified form of the MPC algorithm that caters for direct feed-though signals in order to model near-instantaneous battery ohmic resistance. The implementation utilizes a 2nd-order equivalent circuit discrete-time state-space model based on actual cell parameters; the control methodology is used to compute a fast charging profile that respects input, output, and state constraints. Results show that MPC is well-suited to the dynamics of the battery control problem and further suggestmore » significant performance improvements might be achieved by extending the result to electrochemical models. (C) 2015 Elsevier B.V. All rights reserved.« less

Dynamic balance of excitation and inhibition rapidly modulates spike probability and precision in feed-forward hippocampal circuits

PubMed Central

Wahlstrom-Helgren, Sarah

2016-01-01

Feed-forward inhibitory (FFI) circuits are important for many information-processing functions. FFI circuit operations critically depend on the balance and timing between the excitatory and inhibitory components, which undergo rapid dynamic changes during neural activity due to short-term plasticity (STP) of both components. How dynamic changes in excitation/inhibition (E/I) balance during spike trains influence FFI circuit operations remains poorly understood. In the current study we examined the role of STP in the FFI circuit functions in the mouse hippocampus. Using a coincidence detection paradigm with simultaneous activation of two Schaffer collateral inputs, we found that the spiking probability in the target CA1 neuron was increased while spike precision concomitantly decreased during high-frequency bursts compared with a single spike. Blocking inhibitory synaptic transmission revealed that dynamics of inhibition predominately modulates the spike precision but not the changes in spiking probability, whereas the latter is modulated by the dynamics of excitation. Further analyses combining whole cell recordings and simulations of the FFI circuit suggested that dynamics of the inhibitory circuit component may influence spiking behavior during bursts by broadening the width of excitatory postsynaptic responses and that the strength of this modulation depends on the basal E/I ratio. We verified these predictions using a mouse model of fragile X syndrome, which has an elevated E/I ratio, and found a strongly reduced modulation of postsynaptic response width during bursts. Our results suggest that changes in the dynamics of excitatory and inhibitory circuit components due to STP play important yet distinct roles in modulating the properties of FFI circuits. PMID:27605532

Two-dimensional lattice gauge theories with superconducting quantum circuits

PubMed Central

Marcos, D.; Widmer, P.; Rico, E.; Hafezi, M.; Rabl, P.; Wiese, U.-J.; Zoller, P.

2014-01-01

A quantum simulator of U(1) lattice gauge theories can be implemented with superconducting circuits. This allows the investigation of confined and deconfined phases in quantum link models, and of valence bond solid and spin liquid phases in quantum dimer models. Fractionalized confining strings and the real-time dynamics of quantum phase transitions are accessible as well. Here we show how state-of-the-art superconducting technology allows us to simulate these phenomena in relatively small circuit lattices. By exploiting the strong non-linear couplings between quantized excitations emerging when superconducting qubits are coupled, we show how to engineer gauge invariant Hamiltonians, including ring-exchange and four-body Ising interactions. We demonstrate that, despite decoherence and disorder effects, minimal circuit instances allow us to investigate properties such as the dynamics of electric flux strings, signaling confinement in gauge invariant field theories. The experimental realization of these models in larger superconducting circuits could address open questions beyond current computational capability. PMID:25512676

Dynamical foundations of the neural circuit for bayesian decision making.

PubMed

Morita, Kenji

2009-07-01

On the basis of accumulating behavioral and neural evidences, it has recently been proposed that the brain neural circuits of humans and animals are equipped with several specific properties, which ensure that perceptual decision making implemented by the circuits can be nearly optimal in terms of Bayesian inference. Here, I introduce the basic ideas of such a proposal and discuss its implications from the standpoint of biophysical modeling developed in the framework of dynamical systems.

From Contextual Fear to a Dynamic View of Memory Systems

PubMed Central

Fanselow, Michael S

2009-01-01

The brain does not learn and remember in a unitary fashion. Rather, different circuits specialize in certain classes of problems and encode different types of information. Damage to one of these systems typically results in amnesia only for the form of memory that is the affected region's specialty. How does the brain allocate a specific category of memory to a particular circuit? This question has received little attention. The currently dominant view, Multiple Memory Systems Theory, assumes that such abilities are hard-wired. Using fear conditioning as a paradigmatic case, I propose an alternative model in which mnemonic processing is allocated to specific circuits through a dynamic process. Potential circuits compete to form memories with the most efficient circuits emerging as winners. However, alternate circuits compensate when these “primary” circuits are compromised. PMID:19939724

The Hindmarsh-Rose neuron model: bifurcation analysis and piecewise-linear approximations.

PubMed

Storace, Marco; Linaro, Daniele; de Lange, Enno

2008-09-01

This paper provides a global picture of the bifurcation scenario of the Hindmarsh-Rose model. A combination between simulations and numerical continuations is used to unfold the complex bifurcation structure. The bifurcation analysis is carried out by varying two bifurcation parameters and evidence is given that the structure that is found is universal and appears for all combinations of bifurcation parameters. The information about the organizing principles and bifurcation diagrams are then used to compare the dynamics of the model with that of a piecewise-linear approximation, customized for circuit implementation. A good match between the dynamical behaviors of the models is found. These results can be used both to design a circuit implementation of the Hindmarsh-Rose model mimicking the diversity of neural response and as guidelines to predict the behavior of the model as well as its circuit implementation as a function of parameters. (c) 2008 American Institute of Physics.

Using Movies to Analyse Gene Circuit Dynamics in Single Cells

PubMed Central

Locke, James CW; Elowitz, Michael B

2010-01-01

Preface Many bacterial systems rely on dynamic genetic circuits to control critical processes. A major goal of systems biology is to understand these behaviours in terms of individual genes and their interactions. However, traditional techniques based on population averages wash out critical dynamics that are either unsynchronized between cells or driven by fluctuations, or ‘noise,’ in cellular components. Recently, the combination of time-lapse microscopy, quantitative image analysis, and fluorescent protein reporters has enabled direct observation of multiple cellular components over time in individual cells. In conjunction with mathematical modelling, these techniques are now providing powerful insights into genetic circuit behaviour in diverse microbial systems. PMID:19369953

Dynamical Systems in Circuit Designer's Eyes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Odyniec, M.

Examples of nonlinear circuit design are given. Focus of the design process is on theory and engineering methods (as opposed to numerical analysis). Modeling is related to measurements It is seen that the phase plane is still very useful with proper models Harmonic balance/describing function offers powerful insight (via the combination of simulation with circuit and ODE theory). Measurement and simulation capabilities increased, especially harmonics measurements (since sinusoids are easy to generate)

Deconstructing the core dynamics from a complex time-lagged regulatory biological circuit.

PubMed

Eriksson, O; Brinne, B; Zhou, Y; Björkegren, J; Tegnér, J

2009-03-01

Complex regulatory dynamics is ubiquitous in molecular networks composed of genes and proteins. Recent progress in computational biology and its application to molecular data generate a growing number of complex networks. Yet, it has been difficult to understand the governing principles of these networks beyond graphical analysis or extensive numerical simulations. Here the authors exploit several simplifying biological circumstances which thereby enable to directly detect the underlying dynamical regularities driving periodic oscillations in a dynamical nonlinear computational model of a protein-protein network. System analysis is performed using the cell cycle, a mathematically well-described complex regulatory circuit driven by external signals. By introducing an explicit time delay and using a 'tearing-and-zooming' approach the authors reduce the system to a piecewise linear system with two variables that capture the dynamics of this complex network. A key step in the analysis is the identification of functional subsystems by identifying the relations between state-variables within the model. These functional subsystems are referred to as dynamical modules operating as sensitive switches in the original complex model. By using reduced mathematical representations of the subsystems the authors derive explicit conditions on how the cell cycle dynamics depends on system parameters, and can, for the first time, analyse and prove global conditions for system stability. The approach which includes utilising biological simplifying conditions, identification of dynamical modules and mathematical reduction of the model complexity may be applicable to other well-characterised biological regulatory circuits. [Includes supplementary material].

Compartmental and Data-Based Modeling of Cerebral Hemodynamics: Linear Analysis.

PubMed

Henley, B C; Shin, D C; Zhang, R; Marmarelis, V Z

Compartmental and data-based modeling of cerebral hemodynamics are alternative approaches that utilize distinct model forms and have been employed in the quantitative study of cerebral hemodynamics. This paper examines the relation between a compartmental equivalent-circuit and a data-based input-output model of dynamic cerebral autoregulation (DCA) and CO2-vasomotor reactivity (DVR). The compartmental model is constructed as an equivalent-circuit utilizing putative first principles and previously proposed hypothesis-based models. The linear input-output dynamics of this compartmental model are compared with data-based estimates of the DCA-DVR process. This comparative study indicates that there are some qualitative similarities between the two-input compartmental model and experimental results.

Structure theorems and the dynamics of nitrogen catabolite repression in yeast

PubMed Central

Boczko, Erik M.; Cooper, Terrance G.; Gedeon, Tomas; Mischaikow, Konstantin; Murdock, Deborah G.; Pratap, Siddharth; Wells, K. Sam

2005-01-01

By using current biological understanding, a conceptually simple, but mathematically complex, model is proposed for the dynamics of the gene circuit responsible for regulating nitrogen catabolite repression (NCR) in yeast. A variety of mathematical “structure” theorems are described that allow one to determine the asymptotic dynamics of complicated systems under very weak hypotheses. It is shown that these theorems apply to several subcircuits of the full NCR circuit, most importantly to the URE2–GLN3 subcircuit that is independent of the other constituents but governs the switching behavior of the full NCR circuit under changes in nitrogen source. Under hypotheses that are fully consistent with biological data, it is proven that the dynamics of this subcircuit is simple periodic behavior in synchrony with the cell cycle. Although the current mathematical structure theorems do not apply to the full NCR circuit, extensive simulations suggest that the dynamics is constrained in much the same way as that of the URE2–GLN3 subcircuit. This finding leads to the proposal that mathematicians study genetic circuits to find new geometries for which structure theorems may exist. PMID:15814615

Engineering Consideration for the Self-Energizing Magnetoplasmadynamic (MPD) - Type Fusion Plasma Thruster

DTIC Science & Technology

1993-02-01

currents can be reached by optimizing the electrode geometry and the charging circuit voltage and that the equivalent circuit modelling provides a realistic basis for analyzing plasma focus pinch dynamics.

Interrogating the topological robustness of gene regulatory circuits by randomization

PubMed Central

Levine, Herbert; Onuchic, Jose N.

2017-01-01

One of the most important roles of cells is performing their cellular tasks properly for survival. Cells usually achieve robust functionality, for example, cell-fate decision-making and signal transduction, through multiple layers of regulation involving many genes. Despite the combinatorial complexity of gene regulation, its quantitative behavior has been typically studied on the basis of experimentally verified core gene regulatory circuitry, composed of a small set of important elements. It is still unclear how such a core circuit operates in the presence of many other regulatory molecules and in a crowded and noisy cellular environment. Here we report a new computational method, named random circuit perturbation (RACIPE), for interrogating the robust dynamical behavior of a gene regulatory circuit even without accurate measurements of circuit kinetic parameters. RACIPE generates an ensemble of random kinetic models corresponding to a fixed circuit topology, and utilizes statistical tools to identify generic properties of the circuit. By applying RACIPE to simple toggle-switch-like motifs, we observed that the stable states of all models converge to experimentally observed gene state clusters even when the parameters are strongly perturbed. RACIPE was further applied to a proposed 22-gene network of the Epithelial-to-Mesenchymal Transition (EMT), from which we identified four experimentally observed gene states, including the states that are associated with two different types of hybrid Epithelial/Mesenchymal phenotypes. Our results suggest that dynamics of a gene circuit is mainly determined by its topology, not by detailed circuit parameters. Our work provides a theoretical foundation for circuit-based systems biology modeling. We anticipate RACIPE to be a powerful tool to predict and decode circuit design principles in an unbiased manner, and to quantitatively evaluate the robustness and heterogeneity of gene expression. PMID:28362798

Experimental study of complex mixed-mode oscillations generated in a Bonhoeffer-van der Pol oscillator under weak periodic perturbation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shimizu, Kuniyasu, E-mail: kuniyasu.shimizu@it-chiba.ac.jp; Sekikawa, Munehisa; Inaba, Naohiko

2015-02-15

Bifurcations of complex mixed-mode oscillations denoted as mixed-mode oscillation-incrementing bifurcations (MMOIBs) have frequently been observed in chemical experiments. In a previous study [K. Shimizu et al., Physica D 241, 1518 (2012)], we discovered an extremely simple dynamical circuit that exhibits MMOIBs. Our model was represented by a slow/fast Bonhoeffer-van der Pol circuit under weak periodic perturbation near a subcritical Andronov-Hopf bifurcation point. In this study, we experimentally and numerically verify that our dynamical circuit captures the essence of the underlying mechanism causing MMOIBs, and we observe MMOIBs and chaos with distinctive waveforms in real circuit experiments.

Complex dynamics of memristive circuits: Analytical results and universal slow relaxation

NASA Astrophysics Data System (ADS)

Caravelli, F.; Traversa, F. L.; Di Ventra, M.

2017-02-01

Networks with memristive elements (resistors with memory) are being explored for a variety of applications ranging from unconventional computing to models of the brain. However, analytical results that highlight the role of the graph connectivity on the memory dynamics are still few, thus limiting our understanding of these important dynamical systems. In this paper, we derive an exact matrix equation of motion that takes into account all the network constraints of a purely memristive circuit, and we employ it to derive analytical results regarding its relaxation properties. We are able to describe the memory evolution in terms of orthogonal projection operators onto the subspace of fundamental loop space of the underlying circuit. This orthogonal projection explicitly reveals the coupling between the spatial and temporal sectors of the memristive circuits and compactly describes the circuit topology. For the case of disordered graphs, we are able to explain the emergence of a power-law relaxation as a superposition of exponential relaxation times with a broad range of scales using random matrices. This power law is also universal, namely independent of the topology of the underlying graph but dependent only on the density of loops. In the case of circuits subject to alternating voltage instead, we are able to obtain an approximate solution of the dynamics, which is tested against a specific network topology. These results suggest a much richer dynamics of memristive networks than previously considered.

Filopodial dynamics and growth cone stabilization in Drosophila visual circuit development

PubMed Central

Özel, Mehmet Neset; Langen, Marion; Hassan, Bassem A; Hiesinger, P Robin

2015-01-01

Filopodial dynamics are thought to control growth cone guidance, but the types and roles of growth cone dynamics underlying neural circuit assembly in a living brain are largely unknown. To address this issue, we have developed long-term, continuous, fast and high-resolution imaging of growth cone dynamics from axon growth to synapse formation in cultured Drosophila brains. Using R7 photoreceptor neurons as a model we show that >90% of the growth cone filopodia exhibit fast, stochastic dynamics that persist despite ongoing stepwise layer formation. Correspondingly, R7 growth cones stabilize early and change their final position by passive dislocation. N-Cadherin controls both fast filopodial dynamics and growth cone stabilization. Surprisingly, loss of N-Cadherin causes no primary targeting defects, but destabilizes R7 growth cones to jump between correct and incorrect layers. Hence, growth cone dynamics can influence wiring specificity without a direct role in target recognition and implement simple rules during circuit assembly. DOI: http://dx.doi.org/10.7554/eLife.10721.001 PMID:26512889

Implementation of an integrated op-amp based chaotic neuron model and observation of its chaotic dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jung, Jinwoo; Lee, Jewon; Song, Hanjung

2011-03-15

This paper presents a fully integrated circuit implementation of an operational amplifier (op-amp) based chaotic neuron model with a bipolar output function, experimental measurements, and analyses of its chaotic behavior. The proposed chaotic neuron model integrated circuit consists of several op-amps, sample and hold circuits, a nonlinear function block for chaotic signal generation, a clock generator, a nonlinear output function, etc. Based on the HSPICE (circuit program) simulation results, approximated empirical equations for analyses were formulated. Then, the chaotic dynamical responses such as bifurcation diagrams, time series, and Lyapunov exponent were calculated using these empirical equations. In addition, we performedmore » simulations about two chaotic neuron systems with four synapses to confirm neural network connections and got normal behavior of the chaotic neuron such as internal state bifurcation diagram according to the synaptic weight variation. The proposed circuit was fabricated using a 0.8-{mu}m single poly complementary metal-oxide semiconductor technology. Measurements of the fabricated single chaotic neuron with {+-}2.5 V power supplies and a 10 kHz sampling clock frequency were carried out and compared with the simulated results.« less

Aging analysis of high performance FinFET flip-flop under Dynamic NBTI simulation configuration

NASA Astrophysics Data System (ADS)

Zainudin, M. F.; Hussin, H.; Halim, A. K.; Karim, J.

2018-03-01

A mechanism known as Negative-bias Temperature Instability (NBTI) degrades a main electrical parameters of a circuit especially in terms of performance. So far, the circuit design available at present are only focussed on high performance circuit without considering the circuit reliability and robustness. In this paper, the main circuit performances of high performance FinFET flip-flop such as delay time, and power were studied with the presence of the NBTI degradation. The aging analysis was verified using a 16nm High Performance Predictive Technology Model (PTM) based on different commands available at Synopsys HSPICE. The results shown that the circuit under the longer dynamic NBTI simulation produces the highest impact in the increasing of gate delay and decrease in the average power reduction from a fresh simulation until the aged stress time under a nominal condition. In addition, the circuit performance under a varied stress condition such as temperature and negative stress gate bias were also studied.

Quantitative Investigation of the Role of Intra-/Intercellular Dynamics in Bacterial Quorum Sensing.

PubMed

Leaman, Eric J; Geuther, Brian Q; Behkam, Bahareh

2018-04-20

Bacteria utilize diffusible signals to regulate population density-dependent coordinated gene expression in a process called quorum sensing (QS). While the intracellular regulatory mechanisms of QS are well-understood, the effect of spatiotemporal changes in the population configuration on the sensitivity and robustness of the QS response remains largely unexplored. Using a microfluidic device, we quantitatively characterized the emergent behavior of a population of swimming E. coli bacteria engineered with the lux QS system and a GFP reporter. We show that the QS activation time follows a power law with respect to bacterial population density, but this trend is disrupted significantly by microscale variations in population configuration and genetic circuit noise. We then developed a computational model that integrates population dynamics with genetic circuit dynamics to enable accurate (less than 7% error) quantitation of the bacterial QS activation time. Through modeling and experimental analyses, we show that changes in spatial configuration of swimming bacteria can drastically alter the QS activation time, by up to 22%. The integrative model developed herein also enables examination of the performance robustness of synthetic circuits with respect to growth rate, circuit sensitivity, and the population's initial size and spatial structure. Our framework facilitates quantitative tuning of microbial systems performance through rational engineering of synthetic ribosomal binding sites. We have demonstrated this through modulation of QS activation time over an order of magnitude. Altogether, we conclude that predictive engineering of QS-based bacterial systems requires not only the precise temporal modulation of gene expression (intracellular dynamics) but also accounting for the spatiotemporal changes in population configuration (intercellular dynamics).

Scaling of Topologically Similar Functional Modules Defines Mouse Primary Auditory and Somatosensory Microcircuitry

PubMed Central

Sadovsky, Alexander J.

2013-01-01

Mapping the flow of activity through neocortical microcircuits provides key insights into the underlying circuit architecture. Using a comparative analysis we determined the extent to which the dynamics of microcircuits in mouse primary somatosensory barrel field (S1BF) and auditory (A1) neocortex generalize. We imaged the simultaneous dynamics of up to 1126 neurons spanning multiple columns and layers using high-speed multiphoton imaging. The temporal progression and reliability of reactivation of circuit events in both regions suggested common underlying cortical design features. We used circuit activity flow to generate functional connectivity maps, or graphs, to test the microcircuit hypothesis within a functional framework. S1BF and A1 present a useful test of the postulate as both regions map sensory input anatomically, but each area appears organized according to different design principles. We projected the functional topologies into anatomical space and found benchmarks of organization that had been previously described using physiology and anatomical methods, consistent with a close mapping between anatomy and functional dynamics. By comparing graphs representing activity flow we found that each region is similarly organized as highlighted by hallmarks of small world, scale free, and hierarchical modular topologies. Models of prototypical functional circuits from each area of cortex were sufficient to recapitulate experimentally observed circuit activity. Convergence to common behavior by these models was accomplished using preferential attachment to scale from an auditory up to a somatosensory circuit. These functional data imply that the microcircuit hypothesis be framed as scalable principles of neocortical circuit design. PMID:23986241

Enhanced charging kinetics of porous electrodes: surface conduction as a short-circuit mechanism.

PubMed

Mirzadeh, Mohammad; Gibou, Frederic; Squires, Todd M

2014-08-29

We use direct numerical simulations of the Poisson-Nernst-Planck equations to study the charging kinetics of porous electrodes and to evaluate the predictive capabilities of effective circuit models, both linear and nonlinear. The classic transmission line theory of de Levie holds for general electrode morphologies, but only at low applied potentials. Charging dynamics are slowed appreciably at high potentials, yet not as significantly as predicted by the nonlinear transmission line model of Biesheuvel and Bazant. We identify surface conduction as a mechanism which can effectively "short circuit" the high-resistance electrolyte in the bulk of the pores, thus accelerating the charging dynamics and boosting power densities. Notably, the boost in power density holds only for electrode morphologies with continuous conducting surfaces in the charging direction.

Dissipation in microwave quantum circuits with hybrid nanowire Josephson elements

NASA Astrophysics Data System (ADS)

Mugnai, D.; Ranfagni, A.; Agresti, A.

2017-04-01

Recent experiments on hybrid Josephson junctions have made the argument a topical subject. However, a quantity which remains still unknown is the tunneling (or response) time, which is strictly connected to the role that dissipation plays in the dynamics of the complete system. A simple way for evaluating dissipation in microwave circuits, previously developed for describing the dynamics of conventional Josephson junctions, is now presented as suitable for application even to non-conventional junctions. The method is based on a stochastic model, as derived from the telegrapher's equation, and is particularly devoted to the case of junctions loaded by real transmission lines. When the load is constituted by lumped-constant circuits, a connection with the stochastic model is also maintained. The theoretical model demonstrated its ability to analyze both classically-allowed and forbidden processes, and has found a wide field of applicability, namely in all cases in which dissipative effects cannot be ignored.

Development of single cell lithium ion battery model using Scilab/Xcos

NASA Astrophysics Data System (ADS)

Arianto, Sigit; Yunaningsih, Rietje Y.; Astuti, Edi Tri; Hafiz, Samsul

2016-02-01

In this research, a lithium battery model, as a component in a simulation environment, was developed and implemented using Scicos/Xcos graphical language programming. Scicos used in this research was actually Xcos that is a variant of Scicos which is embedded in Scilab. The equivalent circuit model used in modeling the battery was Double Polarization (DP) model. DP model consists of one open circuit voltage (VOC), one internal resistance (Ri), and two parallel RC circuits. The parameters of the battery were extracted using Hybrid Power Pulse Characterization (HPPC) testing. In this experiment, the Double Polarization (DP) electrical circuit model was used to describe the lithium battery dynamic behavior. The results of simulation of the model were validated with the experimental results. Using simple error analysis, it was found out that the biggest error was 0.275 Volt. It was occurred mostly at the low end of the state of charge (SOC).

Chaotic Motions in the Real Fuzzy Electronic Circuits

DTIC Science & Technology

2012-12-30

field of secure communications, the original source should be blended with other complex signals. Chaotic signals are one of the good sources to be...Takagi-Sugeno (T-S) fuzzy chaotic systems on electronic circuit. In the research field of secure communications, the original source should be blended ...model. The overall fuzzy model of the system is achieved by fuzzy blending of the linear system models. Consider a continuous-time nonlinear dynamic

Logic circuits based on molecular spider systems.

PubMed

Mo, Dandan; Lakin, Matthew R; Stefanovic, Darko

2016-08-01

Spatial locality brings the advantages of computation speed-up and sequence reuse to molecular computing. In particular, molecular walkers that undergo localized reactions are of interest for implementing logic computations at the nanoscale. We use molecular spider walkers to implement logic circuits. We develop an extended multi-spider model with a dynamic environment wherein signal transmission is triggered via localized reactions, and use this model to implement three basic gates (AND, OR, NOT) and a cascading mechanism. We develop an algorithm to automatically generate the layout of the circuit. We use a kinetic Monte Carlo algorithm to simulate circuit computations, and we analyze circuit complexity: our design scales linearly with formula size and has a logarithmic time complexity. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Nucleic acids for the rational design of reaction circuits.

PubMed

Padirac, Adrien; Fujii, Teruo; Rondelez, Yannick

2013-08-01

Nucleic acid-based circuits are rationally designed in vitro assemblies that can perform complex preencoded programs. They can be used to mimic in silico computations. Recent works emphasized the modularity and robustness of these circuits, which allow their scaling-up. Another new development has led to dynamic, time-responsive systems that can display emergent behaviors like oscillations. These are closely related to biological architectures and provide an in vitro model of in vivo information processing. Nucleic acid circuits have already been used to handle various processes for technological or biotechnological purposes. Future applications of these chemical smart systems will benefit from the rapidly growing ability to design, construct, and model nucleic acid circuits of increasing size. Copyright © 2012 Elsevier Ltd. All rights reserved.

SpikingLab: modelling agents controlled by Spiking Neural Networks in Netlogo.

PubMed

Jimenez-Romero, Cristian; Johnson, Jeffrey

2017-01-01

The scientific interest attracted by Spiking Neural Networks (SNN) has lead to the development of tools for the simulation and study of neuronal dynamics ranging from phenomenological models to the more sophisticated and biologically accurate Hodgkin-and-Huxley-based and multi-compartmental models. However, despite the multiple features offered by neural modelling tools, their integration with environments for the simulation of robots and agents can be challenging and time consuming. The implementation of artificial neural circuits to control robots generally involves the following tasks: (1) understanding the simulation tools, (2) creating the neural circuit in the neural simulator, (3) linking the simulated neural circuit with the environment of the agent and (4) programming the appropriate interface in the robot or agent to use the neural controller. The accomplishment of the above-mentioned tasks can be challenging, especially for undergraduate students or novice researchers. This paper presents an alternative tool which facilitates the simulation of simple SNN circuits using the multi-agent simulation and the programming environment Netlogo (educational software that simplifies the study and experimentation of complex systems). The engine proposed and implemented in Netlogo for the simulation of a functional model of SNN is a simplification of integrate and fire (I&F) models. The characteristics of the engine (including neuronal dynamics, STDP learning and synaptic delay) are demonstrated through the implementation of an agent representing an artificial insect controlled by a simple neural circuit. The setup of the experiment and its outcomes are described in this work.

A large-scale circuit mechanism for hierarchical dynamical processing in the primate cortex

PubMed Central

Chaudhuri, Rishidev; Knoblauch, Kenneth; Gariel, Marie-Alice; Kennedy, Henry; Wang, Xiao-Jing

2015-01-01

We developed a large-scale dynamical model of the macaque neocortex, which is based on recently acquired directed- and weighted-connectivity data from tract-tracing experiments, and which incorporates heterogeneity across areas. A hierarchy of timescales naturally emerges from this system: sensory areas show brief, transient responses to input (appropriate for sensory processing), whereas association areas integrate inputs over time and exhibit persistent activity (suitable for decision-making and working memory). The model displays multiple temporal hierarchies, as evidenced by contrasting responses to visual versus somatosensory stimulation. Moreover, slower prefrontal and temporal areas have a disproportionate impact on global brain dynamics. These findings establish a circuit mechanism for “temporal receptive windows” that are progressively enlarged along the cortical hierarchy, suggest an extension of time integration in decision-making from local to large circuits, and should prompt a re-evaluation of the analysis of functional connectivity (measured by fMRI or EEG/MEG) by taking into account inter-areal heterogeneity. PMID:26439530

Multistability in Chua's circuit with two stable node-foci

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bao, B. C.; Wang, N.; Xu, Q.

2016-04-15

Only using one-stage op-amp based negative impedance converter realization, a simplified Chua's diode with positive outer segment slope is introduced, based on which an improved Chua's circuit realization with more simpler circuit structure is designed. The improved Chua's circuit has identical mathematical model but completely different nonlinearity to the classical Chua's circuit, from which multiple attractors including coexisting point attractors, limit cycle, double-scroll chaotic attractor, or coexisting chaotic spiral attractors are numerically simulated and experimentally captured. Furthermore, with dimensionless Chua's equations, the dynamical properties of the Chua's system are studied including equilibrium and stability, phase portrait, bifurcation diagram, Lyapunov exponentmore » spectrum, and attraction basin. The results indicate that the system has two symmetric stable nonzero node-foci in global adjusting parameter regions and exhibits the unusual and striking dynamical behavior of multiple attractors with multistability.« less

GPS synchronized power system phase angle measurements

NASA Astrophysics Data System (ADS)

Wilson, Robert E.; Sterlina, Patrick S.

1994-09-01

This paper discusses the use of Global Positioning System (GPS) synchronized equipment for the measurement and analysis of key power system quantities. Two GPS synchronized phasor measurement units (PMU) were installed before testing. It was indicated that PMUs recorded the dynamic response of the power system phase angles when the northern California power grid was excited by the artificial short circuits. Power system planning engineers perform detailed computer generated simulations of the dynamic response of the power system to naturally occurring short circuits. The computer simulations use models of transmission lines, transformers, circuit breakers, and other high voltage components. This work will compare computer simulations of the same event with field measurement.

Dynamic Discharge Arc Driver. [computerized simulation

NASA Technical Reports Server (NTRS)

Dannenberg, R. E.; Slapnicar, P. I.

1975-01-01

A computer program using nonlinear RLC circuit analysis was developed to accurately model the electrical discharge performance of the Ames 1-MJ energy storage and arc-driver system. Solutions of circuit parameters are compared with experimental circuit data and related to shock speed measurements. Computer analysis led to the concept of a Dynamic Discharge Arc Driver (DDAD) capable of increasing the range of operation of shock-driven facilities. Utilization of mass addition of the driver gas offers a unique means of improving driver performance. Mass addition acts to increase the arc resistance, which results in better electrical circuit damping with more efficient Joule heating, producing stronger shock waves. Preliminary tests resulted in an increase in shock Mach number from 34 to 39 in air at an initial pressure of 2.5 torr.

A subthreshold aVLSI implementation of the Izhikevich simple neuron model.

PubMed

Rangan, Venkat; Ghosh, Abhishek; Aparin, Vladimir; Cauwenberghs, Gert

2010-01-01

We present a circuit architecture for compact analog VLSI implementation of the Izhikevich neuron model, which efficiently describes a wide variety of neuron spiking and bursting dynamics using two state variables and four adjustable parameters. Log-domain circuit design utilizing MOS transistors in subthreshold results in high energy efficiency, with less than 1pJ of energy consumed per spike. We also discuss the effects of parameter variations on the dynamics of the equations, and present simulation results that replicate several types of neural dynamics. The low power operation and compact analog VLSI realization make the architecture suitable for human-machine interface applications in neural prostheses and implantable bioelectronics, as well as large-scale neural emulation tools for computational neuroscience.

Programmed coherent coupling in a synthetic DNA-based excitonic circuit

NASA Astrophysics Data System (ADS)

Boulais, Étienne; Sawaya, Nicolas P. D.; Veneziano, Rémi; Andreoni, Alessio; Banal, James L.; Kondo, Toru; Mandal, Sarthak; Lin, Su; Schlau-Cohen, Gabriela S.; Woodbury, Neal W.; Yan, Hao; Aspuru-Guzik, Alán; Bathe, Mark

2018-02-01

Natural light-harvesting systems spatially organize densely packed chromophore aggregates using rigid protein scaffolds to achieve highly efficient, directed energy transfer. Here, we report a synthetic strategy using rigid DNA scaffolds to similarly program the spatial organization of densely packed, discrete clusters of cyanine dye aggregates with tunable absorption spectra and strongly coupled exciton dynamics present in natural light-harvesting systems. We first characterize the range of dye-aggregate sizes that can be templated spatially by A-tracts of B-form DNA while retaining coherent energy transfer. We then use structure-based modelling and quantum dynamics to guide the rational design of higher-order synthetic circuits consisting of multiple discrete dye aggregates within a DX-tile. These programmed circuits exhibit excitonic transport properties with prominent circular dichroism, superradiance, and fast delocalized exciton transfer, consistent with our quantum dynamics predictions. This bottom-up strategy offers a versatile approach to the rational design of strongly coupled excitonic circuits using spatially organized dye aggregates for use in coherent nanoscale energy transport, artificial light-harvesting, and nanophotonics.

Engineering a robust DNA split proximity circuit with minimized circuit leakage

PubMed Central

Ang, Yan Shan; Tong, Rachel; Yung, Lin-Yue Lanry

2016-01-01

DNA circuit is a versatile and highly-programmable toolbox which can potentially be used for the autonomous sensing of dynamic events, such as biomolecular interactions. However, the experimental implementation of in silico circuit designs has been hindered by the problem of circuit leakage. Here, we systematically analyzed the sources and characteristics of various types of leakage in a split proximity circuit which was engineered to spatially probe for target sites held within close proximity. Direct evidence that 3′-truncated oligonucleotides were the major impurity contributing to circuit leakage was presented. More importantly, a unique strategy of translocating a single nucleotide between domains, termed ‘inter-domain bridging’, was introduced to eliminate toehold-independent leakages while enhancing the strand displacement kinetics across a three-way junction. We also analyzed the dynamics of intermediate complexes involved in the circuit computation in order to define the working range of domain lengths for the reporter toehold and association region respectively. The final circuit design was successfully implemented on a model streptavidin-biotin system and demonstrated to be robust against both circuit leakage and biological interferences. We anticipate that this simple signal transduction strategy can be used to probe for diverse biomolecular interactions when used in conjunction with specific target recognition moieties. PMID:27207880

In vitro large-scale experimental and theoretical studies for the realization of bi-directional brain-prostheses.

PubMed

Bonifazi, Paolo; Difato, Francesco; Massobrio, Paolo; Breschi, Gian L; Pasquale, Valentina; Levi, Timothée; Goldin, Miri; Bornat, Yannick; Tedesco, Mariateresa; Bisio, Marta; Kanner, Sivan; Galron, Ronit; Tessadori, Jacopo; Taverna, Stefano; Chiappalone, Michela

2013-01-01

Brain-machine interfaces (BMI) were born to control "actions from thoughts" in order to recover motor capability of patients with impaired functional connectivity between the central and peripheral nervous system. The final goal of our studies is the development of a new proof-of-concept BMI-a neuromorphic chip for brain repair-to reproduce the functional organization of a damaged part of the central nervous system. To reach this ambitious goal, we implemented a multidisciplinary "bottom-up" approach in which in vitro networks are the paradigm for the development of an in silico model to be incorporated into a neuromorphic device. In this paper we present the overall strategy and focus on the different building blocks of our studies: (i) the experimental characterization and modeling of "finite size networks" which represent the smallest and most general self-organized circuits capable of generating spontaneous collective dynamics; (ii) the induction of lesions in neuronal networks and the whole brain preparation with special attention on the impact on the functional organization of the circuits; (iii) the first production of a neuromorphic chip able to implement a real-time model of neuronal networks. A dynamical characterization of the finite size circuits with single cell resolution is provided. A neural network model based on Izhikevich neurons was able to replicate the experimental observations. Changes in the dynamics of the neuronal circuits induced by optical and ischemic lesions are presented respectively for in vitro neuronal networks and for a whole brain preparation. Finally the implementation of a neuromorphic chip reproducing the network dynamics in quasi-real time (10 ns precision) is presented.

Equivalent circuit-level model of quantum cascade lasers with integrated hot-electron and hot-phonon effects

NASA Astrophysics Data System (ADS)

Yousefvand, H. R.

2017-12-01

We report a study of the effects of hot-electron and hot-phonon dynamics on the output characteristics of quantum cascade lasers (QCLs) using an equivalent circuit-level model. The model is developed from the energy balance equation to adopt the electron temperature in the active region levels, the heat transfer equation to include the lattice temperature, the nonequilibrium phonon rate to account for the hot phonon dynamics and simplified two-level rate equations to incorporate the carrier and photon dynamics in the active region. This technique simplifies the description of the electron-phonon interaction in QCLs far from the equilibrium condition. Using the presented model, the steady and transient responses of the QCLs for a wide range of sink temperatures (80 to 320 K) are investigated and analysed. The model enables us to explain the operating characteristics found in QCLs. This predictive model is expected to be applicable to all QCL material systems operating in pulsed and cw regimes.

Reduced-order modeling of piezoelectric energy harvesters with nonlinear circuits under complex conditions

NASA Astrophysics Data System (ADS)

Xiang, Hong-Jun; Zhang, Zhi-Wei; Shi, Zhi-Fei; Li, Hong

2018-04-01

A fully coupled modeling approach is developed for piezoelectric energy harvesters in this work based on the use of available robust finite element packages and efficient reducing order modeling techniques. At first, the harvester is modeled using finite element packages. The dynamic equilibrium equations of harvesters are rebuilt by extracting system matrices from the finite element model using built-in commands without any additional tools. A Krylov subspace-based scheme is then applied to obtain a reduced-order model for improving simulation efficiency but preserving the key features of harvesters. Co-simulation of the reduced-order model with nonlinear energy harvesting circuits is achieved in a system level. Several examples in both cases of harmonic response and transient response analysis are conducted to validate the present approach. The proposed approach allows to improve the simulation efficiency by several orders of magnitude. Moreover, the parameters used in the equivalent circuit model can be conveniently obtained by the proposed eigenvector-based model order reduction technique. More importantly, this work establishes a methodology for modeling of piezoelectric energy harvesters with any complicated mechanical geometries and nonlinear circuits. The input load may be more complex also. The method can be employed by harvester designers to optimal mechanical structures or by circuit designers to develop novel energy harvesting circuits.

Memcapacitor model and its application in chaotic oscillator with memristor.

PubMed

Wang, Guangyi; Zang, Shouchi; Wang, Xiaoyuan; Yuan, Fang; Iu, Herbert Ho-Ching

2017-01-01

Memristors and memcapacitors are two new nonlinear elements with memory. In this paper, we present a Hewlett-Packard memristor model and a charge-controlled memcapacitor model and design a new chaotic oscillator based on the two models for exploring the characteristics of memristors and memcapacitors in nonlinear circuits. Furthermore, many basic dynamical behaviors of the oscillator, including equilibrium sets, Lyapunov exponent spectrums, and bifurcations with various circuit parameters, are investigated theoretically and numerically. Our analysis results show that the proposed oscillator possesses complex dynamics such as an infinite number of equilibria, coexistence oscillation, and multi-stability. Finally, a discrete model of the chaotic oscillator is given and the main statistical properties of this oscillator are verified via Digital Signal Processing chip experiments and National Institute of Standards and Technology tests.

COMPENSATION FOR VARIABLE INTRINSIC NEURONAL EXCITABILITY BY CIRCUIT-SYNAPTIC INTERACTIONS

PubMed Central

Grashow, Rachel; Brookings, Ted; Marder, Eve

2010-01-01

Recent theoretical and experimental work indicates that neurons tune themselves to maintain target levels of excitation by modulating ion channel expression and synaptic strengths. As a result, functionally equivalent circuits can produce similar activity despite disparate underlying network and cellular properties. To experimentally test the extent to which synaptic and intrinsic conductances can produce target activity in the presence of variability in neuronal intrinsic properties, we used the dynamic clamp to create hybrid two-cell circuits built from four types of stomatogastric (STG) neurons coupled to the same model Morris-Lecar neuron by reciprocal inhibition. We measured six intrinsic properties (input resistance, minimum membrane potential, firing rate in response to +1nA of injected current, slope of the FI curve, spike height and spike voltage threshold) of Dorsal Gastric (DG), Gastric Mill (GM), Lateral Pyloric (LP) and Pyloric Dilator (PD) neurons from male crabs, Cancer borealis. The intrinsic properties varied two to seven-fold in each cell type. We coupled each biological neuron to the Morris-Lecar model with seven different values of inhibitory synaptic conductance, and also used the dynamic clamp to add seven different values of an artificial h-conductance, thus creating 49 different circuits for each biological neuron. Despite the variability in intrinsic excitability, networks formed from each neuron produced similar circuit performance at some values of synaptic and h-conductances. This work experimentally confirms results from previous modeling studies; tuning synaptic and intrinsic conductances can yield similar circuit output from neurons with variable intrinsic excitability. PMID:20610748

On the origin of reproducible sequential activity in neural circuits

NASA Astrophysics Data System (ADS)

Afraimovich, V. S.; Zhigulin, V. P.; Rabinovich, M. I.

2004-12-01

Robustness and reproducibility of sequential spatio-temporal responses is an essential feature of many neural circuits in sensory and motor systems of animals. The most common mathematical images of dynamical regimes in neural systems are fixed points, limit cycles, chaotic attractors, and continuous attractors (attractive manifolds of neutrally stable fixed points). These are not suitable for the description of reproducible transient sequential neural dynamics. In this paper we present the concept of a stable heteroclinic sequence (SHS), which is not an attractor. SHS opens the way for understanding and modeling of transient sequential activity in neural circuits. We show that this new mathematical object can be used to describe robust and reproducible sequential neural dynamics. Using the framework of a generalized high-dimensional Lotka-Volterra model, that describes the dynamics of firing rates in an inhibitory network, we present analytical results on the existence of the SHS in the phase space of the network. With the help of numerical simulations we confirm its robustness in presence of noise in spite of the transient nature of the corresponding trajectories. Finally, by referring to several recent neurobiological experiments, we discuss possible applications of this new concept to several problems in neuroscience.

On the origin of reproducible sequential activity in neural circuits.

PubMed

Afraimovich, V S; Zhigulin, V P; Rabinovich, M I

2004-12-01

Robustness and reproducibility of sequential spatio-temporal responses is an essential feature of many neural circuits in sensory and motor systems of animals. The most common mathematical images of dynamical regimes in neural systems are fixed points, limit cycles, chaotic attractors, and continuous attractors (attractive manifolds of neutrally stable fixed points). These are not suitable for the description of reproducible transient sequential neural dynamics. In this paper we present the concept of a stable heteroclinic sequence (SHS), which is not an attractor. SHS opens the way for understanding and modeling of transient sequential activity in neural circuits. We show that this new mathematical object can be used to describe robust and reproducible sequential neural dynamics. Using the framework of a generalized high-dimensional Lotka-Volterra model, that describes the dynamics of firing rates in an inhibitory network, we present analytical results on the existence of the SHS in the phase space of the network. With the help of numerical simulations we confirm its robustness in presence of noise in spite of the transient nature of the corresponding trajectories. Finally, by referring to several recent neurobiological experiments, we discuss possible applications of this new concept to several problems in neuroscience.

Tools for assessing mitochondrial dynamics in mouse tissues and neurodegenerative models

NASA Astrophysics Data System (ADS)

Pham, Anh H.

Mitochondria are dynamic organelles that undergo membrane fusion and fission and transport. The dynamic properties of mitochondria are important for regulating mitochondrial function. Defects in mitochondrial dynamics are linked neurodegenerative diseases and affect the development of many tissues. To investigate the role of mitochondrial dynamics in diseases, versatile tools are needed to explore the physiology of these dynamic organelles in multiple tissues. Current tools for monitoring mitochondrial dynamics have been limited to studies in cell culture, which may be inadequate model systems for exploring the network of tissues. Here, we have generated mouse models for monitoring mitochondrial dynamics in a broad spectrum of tissues and cell types. The Photo-Activatable Mitochondrial (PhAM floxed) line enables Cre-inducible expression of a mitochondrial targeted photoconvertible protein, Dendra2 (mito-Dendra2). In the PhAMexcised line, mito-Dendra2 is ubiquitously expressed to facilitate broad analysis of mitochondria at various developmental processes. We have utilized these models to study mitochondrial dynamics in the nigrostriatal circuit of Parkinson's disease (PD) and in the development of skeletal muscles. Increasing evidences implicate aberrant regulation of mitochondrial fusion and fission in models of PD. To assess the function of mitochondrial dynamics in the nigrostriatal circuit, we utilized transgenic techniques to abrogate mitochondrial fusion. We show that deletion of the Mfn2 leads to the degeneration of dopaminergic neurons and Parkinson's-like features in mice. To elucidate the dynamic properties of mitochondria during muscle development, we established a platform for examining mitochondrial compartmentalization in skeletal muscles. This model system may yield clues to the role of mitochondrial dynamics in mitochondrial myopathies.

Continuous system modeling

NASA Technical Reports Server (NTRS)

Cellier, Francois E.

1991-01-01

A comprehensive and systematic introduction is presented for the concepts associated with 'modeling', involving the transition from a physical system down to an abstract description of that system in the form of a set of differential and/or difference equations, and basing its treatment of modeling on the mathematics of dynamical systems. Attention is given to the principles of passive electrical circuit modeling, planar mechanical systems modeling, hierarchical modular modeling of continuous systems, and bond-graph modeling. Also discussed are modeling in equilibrium thermodynamics, population dynamics, and system dynamics, inductive reasoning, artificial neural networks, and automated model synthesis.

Sensory integration dynamics in a hierarchical network explains choice probabilities in cortical area MT

PubMed Central

Wimmer, Klaus; Compte, Albert; Roxin, Alex; Peixoto, Diogo; Renart, Alfonso; de la Rocha, Jaime

2015-01-01

Neuronal variability in sensory cortex predicts perceptual decisions. This relationship, termed choice probability (CP), can arise from sensory variability biasing behaviour and from top-down signals reflecting behaviour. To investigate the interaction of these mechanisms during the decision-making process, we use a hierarchical network model composed of reciprocally connected sensory and integration circuits. Consistent with monkey behaviour in a fixed-duration motion discrimination task, the model integrates sensory evidence transiently, giving rise to a decaying bottom-up CP component. However, the dynamics of the hierarchical loop recruits a concurrently rising top-down component, resulting in sustained CP. We compute the CP time-course of neurons in the medial temporal area (MT) and find an early transient component and a separate late contribution reflecting decision build-up. The stability of individual CPs and the dynamics of noise correlations further support this decomposition. Our model provides a unified understanding of the circuit dynamics linking neural and behavioural variability. PMID:25649611

Growth-rate-dependent dynamics of a bacterial genetic oscillator

NASA Astrophysics Data System (ADS)

Osella, Matteo; Lagomarsino, Marco Cosentino

2013-01-01

Gene networks exhibiting oscillatory dynamics are widespread in biology. The minimal regulatory designs giving rise to oscillations have been implemented synthetically and studied by mathematical modeling. However, most of the available analyses generally neglect the coupling of regulatory circuits with the cellular “chassis” in which the circuits are embedded. For example, the intracellular macromolecular composition of fast-growing bacteria changes with growth rate. As a consequence, important parameters of gene expression, such as ribosome concentration or cell volume, are growth-rate dependent, ultimately coupling the dynamics of genetic circuits with cell physiology. This work addresses the effects of growth rate on the dynamics of a paradigmatic example of genetic oscillator, the repressilator. Making use of empirical growth-rate dependencies of parameters in bacteria, we show that the repressilator dynamics can switch between oscillations and convergence to a fixed point depending on the cellular state of growth, and thus on the nutrients it is fed. The physical support of the circuit (type of plasmid or gene positions on the chromosome) also plays an important role in determining the oscillation stability and the growth-rate dependence of period and amplitude. This analysis has potential application in the field of synthetic biology, and suggests that the coupling between endogenous genetic oscillators and cell physiology can have substantial consequences for their functionality.

Machine Vision Within The Framework Of Collective Neural Assemblies

NASA Astrophysics Data System (ADS)

Gupta, Madan M.; Knopf, George K.

1990-03-01

The proposed mechanism for designing a robust machine vision system is based on the dynamic activity generated by the various neural populations embedded in nervous tissue. It is postulated that a hierarchy of anatomically distinct tissue regions are involved in visual sensory information processing. Each region may be represented as a planar sheet of densely interconnected neural circuits. Spatially localized aggregates of these circuits represent collective neural assemblies. Four dynamically coupled neural populations are assumed to exist within each assembly. In this paper we present a state-variable model for a tissue sheet derived from empirical studies of population dynamics. Each population is modelled as a nonlinear second-order system. It is possible to emulate certain observed physiological and psychophysiological phenomena of biological vision by properly programming the interconnective gains . Important early visual phenomena such as temporal and spatial noise insensitivity, contrast sensitivity and edge enhancement will be discussed for a one-dimensional tissue model.

Analysis and design of a genetic circuit for dynamic metabolic engineering.

PubMed

Anesiadis, Nikolaos; Kobayashi, Hideki; Cluett, William R; Mahadevan, Radhakrishnan

2013-08-16

Recent advances in synthetic biology have equipped us with new tools for bioprocess optimization at the genetic level. Previously, we have presented an integrated in silico design for the dynamic control of gene expression based on a density-sensing unit and a genetic toggle switch. In the present paper, analysis of a serine-producing Escherichia coli mutant shows that an instantaneous ON-OFF switch leads to a maximum theoretical productivity improvement of 29.6% compared to the mutant. To further the design, global sensitivity analysis is applied here to a mathematical model of serine production in E. coli coupled with a genetic circuit. The model of the quorum sensing and the toggle switch involves 13 parameters of which 3 are identified as having a significant effect on serine concentration. Simulations conducted in this reduced parameter space further identified the optimal ranges for these 3 key parameters to achieve productivity values close to the maximum theoretical values. This analysis can now be used to guide the experimental implementation of a dynamic metabolic engineering strategy and reduce the time required to design the genetic circuit components.

Dynamical Consequences of Bandpass Feedback Loops in a Bacterial Phosphorelay

PubMed Central

Sen, Shaunak; Garcia-Ojalvo, Jordi; Elowitz, Michael B.

2011-01-01

Under conditions of nutrient limitation, Bacillus subtilis cells terminally differentiate into a dormant spore state. Progression to sporulation is controlled by a genetic circuit consisting of a phosphorelay embedded in multiple transcriptional feedback loops, which is used to activate the master regulator Spo0A by phosphorylation. These transcriptional regulatory interactions are “bandpass”-like, in the sense that activation occurs within a limited band of Spo0A∼P concentrations. Additionally, recent results show that the phosphorelay activation occurs in pulses, in a cell-cycle dependent fashion. However, the impact of these pulsed bandpass interactions on the circuit dynamics preceding sporulation remains unclear. In order to address this question, we measured key features of the bandpass interactions at the single-cell level and analyzed them in the context of a simple mathematical model. The model predicted the emergence of a delayed phase shift between the pulsing activity of the different sporulation genes, as well as the existence of a stable state, with elevated Spo0A activity but no sporulation, embedded within the dynamical structure of the system. To test the model, we used time-lapse fluorescence microscopy to measure dynamics of single cells initiating sporulation. We observed the delayed phase shift emerging during the progression to sporulation, while a re-engineering of the sporulation circuit revealed behavior resembling the predicted additional state. These results show that periodically-driven bandpass feedback loops can give rise to complex dynamics in the progression towards sporulation. PMID:21980382

Multi-piecewise quadratic nonlinearity memristor and its 2N-scroll and 2N + 1-scroll chaotic attractors system.

PubMed

Wang, Chunhua; Liu, Xiaoming; Xia, Hu

2017-03-01

In this paper, two kinds of novel ideal active flux-controlled smooth multi-piecewise quadratic nonlinearity memristors with multi-piecewise continuous memductance function are presented. The pinched hysteresis loop characteristics of the two memristor models are verified by building a memristor emulator circuit. Using the two memristor models establish a new memristive multi-scroll Chua's circuit, which can generate 2N-scroll and 2N+1-scroll chaotic attractors without any other ordinary nonlinear function. Furthermore, coexisting multi-scroll chaotic attractors are found in the proposed memristive multi-scroll Chua's circuit. Phase portraits, Lyapunov exponents, bifurcation diagrams, and equilibrium point analysis have been used to research the basic dynamics of the memristive multi-scroll Chua's circuit. The consistency of circuit implementation and numerical simulation verifies the effectiveness of the system design.

Experimental Chaos - Proceedings of the 3rd Conference

NASA Astrophysics Data System (ADS)

Harrison, Robert G.; Lu, Weiping; Ditto, William; Pecora, Lou; Spano, Mark; Vohra, Sandeep

1996-10-01

The Table of Contents for the full book PDF is as follows: * Preface * Spatiotemporal Chaos and Patterns * Scale Segregation via Formation of Domains in a Nonlinear Optical System * Laser Dynamics as Hydrodynamics * Spatiotemporal Dynamics of Human Epileptic Seizures * Experimental Transition to Chaos in a Quasi 1D Chain of Oscillators * Measuring Coupling in Spatiotemporal Dynamical Systems * Chaos in Vortex Breakdown * Dynamical Analysis * Radial Basis Function Modelling and Prediction of Time Series * Nonlinear Phenomena in Polyrhythmic Hand Movements * Using Models to Diagnose, Test and Control Chaotic Systems * New Real-Time Analysis of Time Series Data with Physical Wavelets * Control and Synchronization * Measuring and Controlling Chaotic Dynamics in a Slugging Fluidized Bed * Control of Chaos in a Laser with Feedback * Synchronization and Chaotic Diode Resonators * Control of Chaos by Continuous-time Feedback with Delay * A Framework for Communication using Chaos Sychronization * Control of Chaos in Switching Circuits * Astrophysics, Meteorology and Oceanography * Solar-Wind-Magnetospheric Dynamics via Satellite Data * Nonlinear Dynamics of the Solar Atmosphere * Fractal Dimension of Scalar and Vector Variables from Turbulence Measurements in the Atmospheric Surface Layer * Mechanics * Escape and Overturning: Subtle Transient Behavior in Nonlinear Mechanical Models * Organising Centres in the Dynamics of Parametrically Excited Double Pendulums * Intermittent Behaviour in a Heating System Driven by Phase Transitions * Hydrodynamics * Size Segregation in Couette Flow of Granular Material * Routes to Chaos in Rotational Taylor-Couette Flow * Experimental Study of the Laminar-Turbulent Transition in an Open Flow System * Chemistry * Order and Chaos in Excitable Media under External Forcing * A Chemical Wave Propagation with Accelerating Speed Accompanied by Hydrodynamic Flow * Optics * Instabilities in Semiconductor Lasers with Optical Injection * Spatio-Temporal Dynamics of a Bimode CO2 Laser with Saturable Absorber * Chaotic Homoclinic Phenomena in Opto-Thermal Devices * Observation and Characterisation of Low-Frequency Chaos in Semiconductor Lasers with External Feedback * Condensed Matter * The Application of Nonlinear Dynamics in the Study of Ferroelectric Materials * Cellular Convection in a Small Aspect Ratio Liquid Crystal Device * Driven Spin-Wave Dynamics in YIG Films * Quantum Chaology in Quartz * Small Signal Amplification Caused by Nonlinear Properties of Ferroelectrics * Composite Materials Evolved from Chaos * Electronics and Circuits * Controlling a Chaotic Array of Pulse-Coupled Fitzhugh-Nagumo Circuits * Experimental Observation of On-Off Intermittency * Phase Lock-In of Chaotic Relaxation Oscillators * Biology and Medicine * Singular Value Decomposition and Circuit Structure in Invertebrate Ganglia * Nonlinear Forecasting of Spike Trains from Neurons of a Mollusc * Ultradian Rhythm in the Sensitive Plants: Chaos or Coloured Noise? * Chaos and the Crayfish Sixth Ganglion * Hardware Coupled Nonlinear Oscillators as a Model of Retina

Simplifications in modelling of dynamical response of coupled electro-mechanical system

NASA Astrophysics Data System (ADS)

Darula, Radoslav; Sorokin, Sergey

2016-12-01

The choice of a most suitable model of an electro-mechanical system depends on many variables, such as a scale of the system, type and frequency range of its operation, or power requirements. The article focuses on the model of the electromagnetic element used in passive regime (no feedback loops are assumed) and a general lumped parameter model (a conventional mass-spring-damper system coupled to an electric circuit consisting of a resistance, an inductance and a capacitance) is compared with its simplified version, where the full RLC circuit is replaced with its RL simplification, i.e. the capacitance of the electric system is neglected and just its inductance and the resistance are considered. From the comparison of dynamical responses of these systems, the range of applicability of a simplified model is assessed for free as well as forced vibration.

Photovoltaic Pixels for Neural Stimulation: Circuit Models and Performance.

PubMed

Boinagrov, David; Lei, Xin; Goetz, Georges; Kamins, Theodore I; Mathieson, Keith; Galambos, Ludwig; Harris, James S; Palanker, Daniel

2016-02-01

Photovoltaic conversion of pulsed light into pulsed electric current enables optically-activated neural stimulation with miniature wireless implants. In photovoltaic retinal prostheses, patterns of near-infrared light projected from video goggles onto subretinal arrays of photovoltaic pixels are converted into patterns of current to stimulate the inner retinal neurons. We describe a model of these devices and evaluate the performance of photovoltaic circuits, including the electrode-electrolyte interface. Characteristics of the electrodes measured in saline with various voltages, pulse durations, and polarities were modeled as voltage-dependent capacitances and Faradaic resistances. The resulting mathematical model of the circuit yielded dynamics of the electric current generated by the photovoltaic pixels illuminated by pulsed light. Voltages measured in saline with a pipette electrode above the pixel closely matched results of the model. Using the circuit model, our pixel design was optimized for maximum charge injection under various lighting conditions and for different stimulation thresholds. To speed discharge of the electrodes between the pulses of light, a shunt resistor was introduced and optimized for high frequency stimulation.

A plastic corticostriatal circuit model of adaptation in perceptual decision making

PubMed Central

Hsiao, Pao-Yueh; Lo, Chung-Chuan

2013-01-01

The ability to optimize decisions and adapt them to changing environments is a crucial brain function that increase survivability. Although much has been learned about the neuronal activity in various brain regions that are associated with decision making, and about how the nervous systems may learn to achieve optimization, the underlying neuronal mechanisms of how the nervous systems optimize decision strategies with preference given to speed or accuracy, and how the systems adapt to changes in the environment, remain unclear. Based on extensive empirical observations, we addressed the question by extending a previously described cortico-basal ganglia circuit model of perceptual decisions with the inclusion of a dynamic dopamine (DA) system that modulates spike-timing dependent plasticity (STDP). We found that, once an optimal model setting that maximized the reward rate was selected, the same setting automatically optimized decisions across different task environments through dynamic balancing between the facilitating and depressing components of the DA dynamics. Interestingly, other model parameters were also optimal if we considered the reward rate that was weighted by the subject's preferences for speed or accuracy. Specifically, the circuit model favored speed if we increased the phasic DA response to the reward prediction error, whereas the model favored accuracy if we reduced the tonic DA activity or the phasic DA responses to the estimated reward probability. The proposed model provides insight into the roles of different components of DA responses in decision adaptation and optimization in a changing environment. PMID:24339814

Modelling social interaction as perceptual crossing: an investigation into the dynamics of the interaction process

NASA Astrophysics Data System (ADS)

Froese, Tom; Di Paolo, Ezequiel A.

2010-03-01

This paper continues efforts to establish a mutually informative dialogue between psychology and evolutionary robotics in order to investigate the dynamics of social interaction. We replicate a recent simulation model of a minimalist experiment in perceptual crossing and confirm the results with significantly simpler artificial agents. A series of psycho-physical tests of their behaviour informs a hypothetical circuit model of their internal operation. However, a detailed study of the actual internal dynamics reveals this circuit model to be unfounded, thereby offering a tale of caution for those hypothesising about sub-personal processes in terms of behavioural observations. In particular, it is shown that the behaviour of the agents largely emerges out of the interaction process itself rather than being an individual achievement alone. We also extend the original simulation model in two novel directions in order to test further the extent to which perceptual crossing between agents can self-organise in a robust manner. These modelling results suggest new hypotheses that can become the basis for further psychological experiments.

Vibration analysis of printed circuit boards: Effect of boundary condition

NASA Astrophysics Data System (ADS)

Prashanth, M. D.

2018-04-01

A spacecraft consists of a number of electronic packages to meet the functional requirements. An electronic package is generally an assembly of printed circuit boards placed in a mechanical housing. A number of electronic components are mounted on the printed circuit board (PCB). A spacecraft experiences various types of loads during its launch such as vibration, acoustic and shock loads. Prediction of response for printed circuit boards due to vibration loads is important for mechanical design and reliability of electronic packages. The modeling and analysis of printed circuit boards is required for accurate prediction of response due to vibration loads. The response of PCB is highly dependent on the mounting configuration of PCB. In addition, anti-vibration mounts or stiffeners are used to reduce the PCB response. Vibration analysis of printed circuit boards is carried out using finite element method. The objective of this paper is to determine the dynamic characteristics of a printed circuit board. Modeling and analysis of PCB shall be carried out to study the effect of boundary conditions on the vibration response. The modeling of stiffeners or ribs shall also be considered in detail. The analysis results shall be validated using vibration tests of PCB.

Digital MOS integrated circuits

NASA Astrophysics Data System (ADS)

Elmasry, M. I.

MOS in digital circuit design is considered along with aspects of digital VLSI, taking into account a comparison of MOSFET logic circuits, 1-micrometer MOSFET VLSI technology, a generalized guide for MOSFET miniaturization, processing technologies, novel circuit structures for VLSI, and questions of circuit and system design for VLSI. MOS memory cells and circuits are discussed, giving attention to a survey of high-density dynamic RAM cell concepts, one-device cells for dynamic random-access memories, variable resistance polysilicon for high density CMOS Ram, high performance MOS EPROMs using a stacked-gate cell, and the optimization of the latching pulse for dynamic flip-flop sensors. Programmable logic arrays are considered along with digital signal processors, microprocessors, static RAMs, and dynamic RAMs.

Experimental verification of a thermal equivalent circuit dynamic model on an extended range electric vehicle battery pack

NASA Astrophysics Data System (ADS)

Ramotar, Lokendra; Rohrauer, Greg L.; Filion, Ryan; MacDonald, Kathryn

2017-03-01

The development of a dynamic thermal battery model for hybrid and electric vehicles is realized. A thermal equivalent circuit model is created which aims to capture and understand the heat propagation from the cells through the entire pack and to the environment using a production vehicle battery pack for model validation. The inclusion of production hardware and the liquid battery thermal management system components into the model considers physical and geometric properties to calculate thermal resistances of components (conduction, convection and radiation) along with their associated heat capacity. Various heat sources/sinks comprise the remaining model elements. Analog equivalent circuit simulations using PSpice are compared to experimental results to validate internal temperature nodes and heat rates measured through various elements, which are then employed to refine the model further. Agreement with experimental results indicates the proposed method allows for a comprehensive real-time battery pack analysis at little computational expense when compared to other types of computer based simulations. Elevated road and ambient conditions in Mesa, Arizona are simulated on a parked vehicle with varying quiescent cooling rates to examine the effect on the diurnal battery temperature for longer term static exposure. A typical daily driving schedule is also simulated and examined.

Model annotation for synthetic biology: automating model to nucleotide sequence conversion

PubMed Central

Misirli, Goksel; Hallinan, Jennifer S.; Yu, Tommy; Lawson, James R.; Wimalaratne, Sarala M.; Cooling, Michael T.; Wipat, Anil

2011-01-01

Motivation: The need for the automated computational design of genetic circuits is becoming increasingly apparent with the advent of ever more complex and ambitious synthetic biology projects. Currently, most circuits are designed through the assembly of models of individual parts such as promoters, ribosome binding sites and coding sequences. These low level models are combined to produce a dynamic model of a larger device that exhibits a desired behaviour. The larger model then acts as a blueprint for physical implementation at the DNA level. However, the conversion of models of complex genetic circuits into DNA sequences is a non-trivial undertaking due to the complexity of mapping the model parts to their physical manifestation. Automating this process is further hampered by the lack of computationally tractable information in most models. Results: We describe a method for automatically generating DNA sequences from dynamic models implemented in CellML and Systems Biology Markup Language (SBML). We also identify the metadata needed to annotate models to facilitate automated conversion, and propose and demonstrate a method for the markup of these models using RDF. Our algorithm has been implemented in a software tool called MoSeC. Availability: The software is available from the authors' web site http://research.ncl.ac.uk/synthetic_biology/downloads.html. Contact: anil.wipat@ncl.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21296753

Photonic integrated circuits unveil crisis-induced intermittency.

PubMed

Karsaklian Dal Bosco, Andreas; Akizawa, Yasuhiro; Kanno, Kazutaka; Uchida, Atsushi; Harayama, Takahisa; Yoshimura, Kazuyuki

2016-09-19

We experimentally investigate an intermittent route to chaos in a photonic integrated circuit consisting of a semiconductor laser with time-delayed optical feedback from a short external cavity. The transition from a period-doubling dynamics to a fully-developed chaos reveals a stage intermittently exhibiting these two dynamics. We unveil the bifurcation mechanism underlying this route to chaos by using the Lang-Kobayashi model and demonstrate that the process is based on a phenomenon of attractor expansion initiated by a particular distribution of the local Lyapunov exponents. We emphasize on the crucial importance of the distribution of the steady-state solutions introduced by the time-delayed feedback on the existence of this intermittent dynamics.

Synthetic analog computation in living cells.

PubMed

Daniel, Ramiz; Rubens, Jacob R; Sarpeshkar, Rahul; Lu, Timothy K

2013-05-30

A central goal of synthetic biology is to achieve multi-signal integration and processing in living cells for diagnostic, therapeutic and biotechnology applications. Digital logic has been used to build small-scale circuits, but other frameworks may be needed for efficient computation in the resource-limited environments of cells. Here we demonstrate that synthetic analog gene circuits can be engineered to execute sophisticated computational functions in living cells using just three transcription factors. Such synthetic analog gene circuits exploit feedback to implement logarithmically linear sensing, addition, ratiometric and power-law computations. The circuits exhibit Weber's law behaviour as in natural biological systems, operate over a wide dynamic range of up to four orders of magnitude and can be designed to have tunable transfer functions. Our circuits can be composed to implement higher-order functions that are well described by both intricate biochemical models and simple mathematical functions. By exploiting analog building-block functions that are already naturally present in cells, this approach efficiently implements arithmetic operations and complex functions in the logarithmic domain. Such circuits may lead to new applications for synthetic biology and biotechnology that require complex computations with limited parts, need wide-dynamic-range biosensing or would benefit from the fine control of gene expression.

Experimentally simulating the dynamics of quantum light and matter at ultrastrong coupling using circuit QED (1) - implementation and matter dynamics -

NASA Astrophysics Data System (ADS)

Kounalakis, M.; Langford, N. K.; Sagastizabal, R.; Dickel, C.; Bruno, A.; Luthi, F.; Thoen, D. J.; Endo, A.; Dicarlo, L.

The field dipole coupling of quantum light and matter, described by the quantum Rabi model, leads to exotic phenomena when the coupling strength g becomes comparable or larger than the atom and photon frequencies ωq , r. In this ultra-strong coupling regime, excitations are not conserved, leading to collapse-revival dynamics in atom and photon parity and Schrödinger-cat-like atom-photon entanglement. We realize a quantum simulation of the Rabi model using a transmon qubit coupled to a resonator. In this first part, we describe our analog-digital approach to implement up to 90 symmetric Trotter steps, combining single-qubit gates with the Jaynes-Cummings interaction naturally present in our circuit QED system. Controlling the phase of microwave pulses defines a rotating frame and enables simulation of arbitrary parameter regimes of the Rabi model. We demonstrate measurements of qubit parity dynamics showing revivals at g /ωr > 0 . 8 for ωq = 0 and characteristic dynamics for nondegenerate ωq from g / 4 to g. Funding from the EU FP7 Project ScaleQIT, an ERC Grant, the Dutch Research Organization NWO, and Microsoft Research.

Towards a whole-cell modeling approach for synthetic biology

NASA Astrophysics Data System (ADS)

Purcell, Oliver; Jain, Bonny; Karr, Jonathan R.; Covert, Markus W.; Lu, Timothy K.

2013-06-01

Despite rapid advances over the last decade, synthetic biology lacks the predictive tools needed to enable rational design. Unlike established engineering disciplines, the engineering of synthetic gene circuits still relies heavily on experimental trial-and-error, a time-consuming and inefficient process that slows down the biological design cycle. This reliance on experimental tuning is because current modeling approaches are unable to make reliable predictions about the in vivo behavior of synthetic circuits. A major reason for this lack of predictability is that current models view circuits in isolation, ignoring the vast number of complex cellular processes that impinge on the dynamics of the synthetic circuit and vice versa. To address this problem, we present a modeling approach for the design of synthetic circuits in the context of cellular networks. Using the recently published whole-cell model of Mycoplasma genitalium, we examined the effect of adding genes into the host genome. We also investigated how codon usage correlates with gene expression and find agreement with existing experimental results. Finally, we successfully implemented a synthetic Goodwin oscillator in the whole-cell model. We provide an updated software framework for the whole-cell model that lays the foundation for the integration of whole-cell models with synthetic gene circuit models. This software framework is made freely available to the community to enable future extensions. We envision that this approach will be critical to transforming the field of synthetic biology into a rational and predictive engineering discipline.

Monolithic amplifier with stable, high resistance feedback element and method for fabricating the same

DOEpatents

O'Connor, Paul

1998-08-11

A monolithic amplifier includes a stable, high resistance feedback circuit and a dynamic bias circuit. The dynamic bias circuit is formed with active elements matched to those in the amplifier and feedback circuit to compensate for variations in the operating and threshold voltages thereby maintaining a stable resistance in the feedback circuit.

A fully dynamic model of a multi-layer piezoelectric actuator incorporating the power amplifier

NASA Astrophysics Data System (ADS)

Zhu, Wei; Yang, Fufeng; Rui, Xiaoting

2017-12-01

The dynamic input-output characteristics of the multi-layer piezoelectric actuator (PA) are intrinsically rate-dependent and hysteresis. Meanwhile, aiming at the strong capacitive impedance of multi-layer PA, the power amplifier of the actuator can greatly affect the dynamic performances of the actuator. In this paper, a novel dynamic model that includes a model of the electric circuit providing voltage to the actuator, an inverse piezoelectric effect model describing the hysteresis and creep behavior of the actuator, and a mechanical model, in which the vibration characteristics of the multi-layer PA is described, is put forward. Validation experimental tests are conducted. Experimental results show that the proposed dynamic model can accurately predict the fully dynamic behavior of the multi-layer PA with different driving power.

Successful Reconstruction of a Physiological Circuit with Known Connectivity from Spiking Activity Alone

PubMed Central

Gerhard, Felipe; Kispersky, Tilman; Gutierrez, Gabrielle J.; Marder, Eve; Kramer, Mark; Eden, Uri

2013-01-01

Identifying the structure and dynamics of synaptic interactions between neurons is the first step to understanding neural network dynamics. The presence of synaptic connections is traditionally inferred through the use of targeted stimulation and paired recordings or by post-hoc histology. More recently, causal network inference algorithms have been proposed to deduce connectivity directly from electrophysiological signals, such as extracellularly recorded spiking activity. Usually, these algorithms have not been validated on a neurophysiological data set for which the actual circuitry is known. Recent work has shown that traditional network inference algorithms based on linear models typically fail to identify the correct coupling of a small central pattern generating circuit in the stomatogastric ganglion of the crab Cancer borealis. In this work, we show that point process models of observed spike trains can guide inference of relative connectivity estimates that match the known physiological connectivity of the central pattern generator up to a choice of threshold. We elucidate the necessary steps to derive faithful connectivity estimates from a model that incorporates the spike train nature of the data. We then apply the model to measure changes in the effective connectivity pattern in response to two pharmacological interventions, which affect both intrinsic neural dynamics and synaptic transmission. Our results provide the first successful application of a network inference algorithm to a circuit for which the actual physiological synapses between neurons are known. The point process methodology presented here generalizes well to larger networks and can describe the statistics of neural populations. In general we show that advanced statistical models allow for the characterization of effective network structure, deciphering underlying network dynamics and estimating information-processing capabilities. PMID:23874181

Self-consistent radiation-based simulation of electric arcs: II. Application to gas circuit breakers

NASA Astrophysics Data System (ADS)

Iordanidis, A. A.; Franck, C. M.

2008-07-01

An accurate and robust method for radiative heat transfer simulation for arc applications was presented in the previous paper (part I). In this paper a self-consistent mathematical model based on computational fluid dynamics and a rigorous radiative heat transfer model is described. The model is applied to simulate switching arcs in high voltage gas circuit breakers. The accuracy of the model is proven by comparison with experimental data for all arc modes. The ablation-controlled arc model is used to simulate high current PTFE arcs burning in cylindrical tubes. Model accuracy for the lower current arcs is evaluated using experimental data on the axially blown SF6 arc in steady state and arc resistance measurements close to current zero. The complete switching process with the arc going through all three phases is also simulated and compared with the experimental data from an industrial circuit breaker switching test.

A framework for scalable parameter estimation of gene circuit models using structural information.

PubMed

Kuwahara, Hiroyuki; Fan, Ming; Wang, Suojin; Gao, Xin

2013-07-01

Systematic and scalable parameter estimation is a key to construct complex gene regulatory models and to ultimately facilitate an integrative systems biology approach to quantitatively understand the molecular mechanisms underpinning gene regulation. Here, we report a novel framework for efficient and scalable parameter estimation that focuses specifically on modeling of gene circuits. Exploiting the structure commonly found in gene circuit models, this framework decomposes a system of coupled rate equations into individual ones and efficiently integrates them separately to reconstruct the mean time evolution of the gene products. The accuracy of the parameter estimates is refined by iteratively increasing the accuracy of numerical integration using the model structure. As a case study, we applied our framework to four gene circuit models with complex dynamics based on three synthetic datasets and one time series microarray data set. We compared our framework to three state-of-the-art parameter estimation methods and found that our approach consistently generated higher quality parameter solutions efficiently. Although many general-purpose parameter estimation methods have been applied for modeling of gene circuits, our results suggest that the use of more tailored approaches to use domain-specific information may be a key to reverse engineering of complex biological systems. http://sfb.kaust.edu.sa/Pages/Software.aspx. Supplementary data are available at Bioinformatics online.

Transistor analogs of emergent iono-neuronal dynamics.

PubMed

Rachmuth, Guy; Poon, Chi-Sang

2008-06-01

Neuromorphic analog metal-oxide-silicon (MOS) transistor circuits promise compact, low-power, and high-speed emulations of iono-neuronal dynamics orders-of-magnitude faster than digital simulation. However, their inherently limited input voltage dynamic range vs power consumption and silicon die area tradeoffs makes them highly sensitive to transistor mismatch due to fabrication inaccuracy, device noise, and other nonidealities. This limitation precludes robust analog very-large-scale-integration (aVLSI) circuits implementation of emergent iono-neuronal dynamics computations beyond simple spiking with limited ion channel dynamics. Here we present versatile neuromorphic analog building-block circuits that afford near-maximum voltage dynamic range operating within the low-power MOS transistor weak-inversion regime which is ideal for aVLSI implementation or implantable biomimetic device applications. The fabricated microchip allowed robust realization of dynamic iono-neuronal computations such as coincidence detection of presynaptic spikes or pre- and postsynaptic activities. As a critical performance benchmark, the high-speed and highly interactive iono-neuronal simulation capability on-chip enabled our prompt discovery of a minimal model of chaotic pacemaker bursting, an emergent iono-neuronal behavior of fundamental biological significance which has hitherto defied experimental testing or computational exploration via conventional digital or analog simulations. These compact and power-efficient transistor analogs of emergent iono-neuronal dynamics open new avenues for next-generation neuromorphic, neuroprosthetic, and brain-machine interface applications.

Monolithic amplifier with stable, high resistance feedback element and method for fabricating the same

DOEpatents

O`Connor, P.

1998-08-11

A monolithic amplifier includes a stable, high resistance feedback circuit and a dynamic bias circuit. The dynamic bias circuit is formed with active elements matched to those in the amplifier and feedback circuit to compensate for variations in the operating and threshold voltages thereby maintaining a stable resistance in the feedback circuit. 11 figs.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wong, Melissa; Bolovan-Fritts, Cynthia; Dar, Roy D.

Signal transduction circuits have long been known to differentiate between signals by amplifying inputs to different levels. Here, we describe a novel transcriptional circuitry that dynamically converts greater input levels into faster rates, without increasing the final equilibrium level (i.e. a rate amplifier). We utilize time-lapse microscopy to study human herpesvirus (cytomegalovirus) infection of live cells in real time. Strikingly, our results show that transcriptional activators accelerate viral gene expression in single cells without amplifying the steady-state levels of gene products in these cells. Experiment and modeling show that rate amplification operates by dynamically manipulating the traditional gain-bandwidth feedback relationshipmore » from electrical circuit theory to convert greater input levels into faster rates, and is driven by highly self-cooperative transcriptional feedback encoded by the virus s essential transactivator, IE2. This transcriptional rate-amplifier provides a significant fitness advantage for the virus and for minimal synthetic circuits. In general, rate-amplifiers may provide a mechanism for signal-transduction circuits to respond quickly to external signals without increasing steady-state levels of potentially cytotoxic molecules.« less

Analysis of a homemade Edison tinfoil phonograph.

PubMed

Sagers, Jason D; McNeese, Andrew R; Lenhart, Richard D; Wilson, Preston S

2012-10-01

Thomas Edison's phonograph was a landmark acoustic invention. In this paper, the phonograph is presented as a tool for education in acoustics. A brief history of the phonograph is outlined and an analogous circuit model that describes its dynamic response is discussed. Microphone and scanning laser Doppler vibrometer (SLDV) measurements were made on a homemade phonograph for model validation and inversion for unknown model parameters. SLDV measurements also conclusively illustrate where model assumptions are violated. The model elements which dominate the dynamic response are discussed.

Gene Circuit Analysis of the Terminal Gap Gene huckebein

PubMed Central

Ashyraliyev, Maksat; Siggens, Ken; Janssens, Hilde; Blom, Joke; Akam, Michael; Jaeger, Johannes

2009-01-01

The early embryo of Drosophila melanogaster provides a powerful model system to study the role of genes in pattern formation. The gap gene network constitutes the first zygotic regulatory tier in the hierarchy of the segmentation genes involved in specifying the position of body segments. Here, we use an integrative, systems-level approach to investigate the regulatory effect of the terminal gap gene huckebein (hkb) on gap gene expression. We present quantitative expression data for the Hkb protein, which enable us to include hkb in gap gene circuit models. Gap gene circuits are mathematical models of gene networks used as computational tools to extract regulatory information from spatial expression data. This is achieved by fitting the model to gap gene expression patterns, in order to obtain estimates for regulatory parameters which predict a specific network topology. We show how considering variability in the data combined with analysis of parameter determinability significantly improves the biological relevance and consistency of the approach. Our models are in agreement with earlier results, which they extend in two important respects: First, we show that Hkb is involved in the regulation of the posterior hunchback (hb) domain, but does not have any other essential function. Specifically, Hkb is required for the anterior shift in the posterior border of this domain, which is now reproduced correctly in our models. Second, gap gene circuits presented here are able to reproduce mutants of terminal gap genes, while previously published models were unable to reproduce any null mutants correctly. As a consequence, our models now capture the expression dynamics of all posterior gap genes and some variational properties of the system correctly. This is an important step towards a better, quantitative understanding of the developmental and evolutionary dynamics of the gap gene network. PMID:19876378

Gene circuit analysis of the terminal gap gene huckebein.

PubMed

Ashyraliyev, Maksat; Siggens, Ken; Janssens, Hilde; Blom, Joke; Akam, Michael; Jaeger, Johannes

2009-10-01

The early embryo of Drosophila melanogaster provides a powerful model system to study the role of genes in pattern formation. The gap gene network constitutes the first zygotic regulatory tier in the hierarchy of the segmentation genes involved in specifying the position of body segments. Here, we use an integrative, systems-level approach to investigate the regulatory effect of the terminal gap gene huckebein (hkb) on gap gene expression. We present quantitative expression data for the Hkb protein, which enable us to include hkb in gap gene circuit models. Gap gene circuits are mathematical models of gene networks used as computational tools to extract regulatory information from spatial expression data. This is achieved by fitting the model to gap gene expression patterns, in order to obtain estimates for regulatory parameters which predict a specific network topology. We show how considering variability in the data combined with analysis of parameter determinability significantly improves the biological relevance and consistency of the approach. Our models are in agreement with earlier results, which they extend in two important respects: First, we show that Hkb is involved in the regulation of the posterior hunchback (hb) domain, but does not have any other essential function. Specifically, Hkb is required for the anterior shift in the posterior border of this domain, which is now reproduced correctly in our models. Second, gap gene circuits presented here are able to reproduce mutants of terminal gap genes, while previously published models were unable to reproduce any null mutants correctly. As a consequence, our models now capture the expression dynamics of all posterior gap genes and some variational properties of the system correctly. This is an important step towards a better, quantitative understanding of the developmental and evolutionary dynamics of the gap gene network.

Modelling, analyses and design of switching converters

NASA Technical Reports Server (NTRS)

Cuk, S. M.; Middlebrook, R. D.

1978-01-01

A state-space averaging method for modelling switching dc-to-dc converters for both continuous and discontinuous conduction mode is developed. In each case the starting point is the unified state-space representation, and the end result is a complete linear circuit model, for each conduction mode, which correctly represents all essential features, namely, the input, output, and transfer properties (static dc as well as dynamic ac small-signal). While the method is generally applicable to any switching converter, it is extensively illustrated for the three common power stages (buck, boost, and buck-boost). The results for these converters are then easily tabulated owing to the fixed equivalent circuit topology of their canonical circuit model. The insights that emerge from the general state-space modelling approach lead to the design of new converter topologies through the study of generic properties of the cascade connection of basic buck and boost converters.

Quantitative Biofractal Feedback Part II ’Devices, Scalability & Robust Control’

DTIC Science & Technology

2008-05-01

in the modelling of proton exchange membrane fuel cells ( PEMFC ) may work as a powerful tool in the development and widespread testing of alternative...energy sources in the next decade [9], where biofractal controllers will be used to control these complex systems. The dynamic model of PEMFC , is...dynamic response of the PEMFC . In the Iftukhar model, the fuel cell is represented by an equivalent circuit, whose components are identified with

Equivalent circuit modeling of a piezo-patch energy harvester on a thin plate with AC-DC conversion

NASA Astrophysics Data System (ADS)

Bayik, B.; Aghakhani, A.; Basdogan, I.; Erturk, A.

2016-05-01

As an alternative to beam-like structures, piezoelectric patch-based energy harvesters attached to thin plates can be readily integrated to plate-like structures in automotive, marine, and aerospace applications, in order to directly exploit structural vibration modes of the host system without mass loading and volumetric occupancy of cantilever attachments. In this paper, a multi-mode equivalent circuit model of a piezo-patch energy harvester integrated to a thin plate is developed and coupled with a standard AC-DC conversion circuit. Equivalent circuit parameters are obtained in two different ways: (1) from the modal analysis solution of a distributed-parameter analytical model and (2) from the finite-element numerical model of the harvester by accounting for two-way coupling. After the analytical modeling effort, multi-mode equivalent circuit representation of the harvester is obtained via electronic circuit simulation software SPICE. Using the SPICE software, electromechanical response of the piezoelectric energy harvester connected to linear and nonlinear circuit elements are computed. Simulation results are validated for the standard AC-AC and AC-DC configurations. For the AC input-AC output problem, voltage frequency response functions are calculated for various resistive loads, and they show excellent agreement with modal analysis-based analytical closed-form solution and with the finite-element model. For the standard ideal AC input-DC output case, a full-wave rectifier and a smoothing capacitor are added to the harvester circuit for conversion of the AC voltage to a stable DC voltage, which is also validated against an existing solution by treating the single-mode plate dynamics as a single-degree-of-freedom system.

SiC-VJFETs power switching devices: an improved model and parameter optimization technique

NASA Astrophysics Data System (ADS)

Ben Salah, T.; Lahbib, Y.; Morel, H.

2009-12-01

Silicon carbide junction field effect transistor (SiC-JFETs) is a mature power switch newly applied in several industrial applications. SiC-JFETs are often simulated by Spice model in order to predict their electrical behaviour. Although such a model provides sufficient accuracy for some applications, this paper shows that it presents serious shortcomings in terms of the neglect of the body diode model, among many others in circuit model topology. Simulation correction is then mandatory and a new model should be proposed. Moreover, this paper gives an enhanced model based on experimental dc and ac data. New devices are added to the conventional circuit model giving accurate static and dynamic behaviour, an effect not accounted in the Spice model. The improved model is implemented into VHDL-AMS language and steady-state dynamic and transient responses are simulated for many SiC-VJFETs samples. Very simple and reliable optimization algorithm based on the optimization of a cost function is proposed to extract the JFET model parameters. The obtained parameters are verified by comparing errors between simulations results and experimental data.

System Modeling of a MEMS Vibratory Gyroscope and Integration to Circuit Simulation.

PubMed

Kwon, Hyukjin J; Seok, Seyeong; Lim, Geunbae

2017-11-18

Recently, consumer applications have dramatically created the demand for low-cost and compact gyroscopes. Therefore, on the basis of microelectromechanical systems (MEMS) technology, many gyroscopes have been developed and successfully commercialized. A MEMS gyroscope consists of a MEMS device and an electrical circuit for self-oscillation and angular-rate detection. Since the MEMS device and circuit are interactively related, the entire system should be analyzed together to design or test the gyroscope. In this study, a MEMS vibratory gyroscope is analyzed based on the system dynamic modeling; thus, it can be mathematically expressed and integrated into a circuit simulator. A behavioral simulation of the entire system was conducted to prove the self-oscillation and angular-rate detection and to determine the circuit parameters to be optimized. From the simulation, the operating characteristic according to the vacuum pressure and scale factor was obtained, which indicated similar trends compared with those of the experimental results. The simulation method presented in this paper can be generalized to a wide range of MEMS devices.

Equivalent circuit-based analysis of CMUT cell dynamics in arrays.

PubMed

Oguz, H K; Atalar, Abdullah; Köymen, Hayrettin

2013-05-01

Capacitive micromachined ultrasonic transducers (CMUTs) are usually composed of large arrays of closely packed cells. In this work, we use an equivalent circuit model to analyze CMUT arrays with multiple cells. We study the effects of mutual acoustic interactions through the immersion medium caused by the pressure field generated by each cell acting upon the others. To do this, all the cells in the array are coupled through a radiation impedance matrix at their acoustic terminals. An accurate approximation for the mutual radiation impedance is defined between two circular cells, which can be used in large arrays to reduce computational complexity. Hence, a performance analysis of CMUT arrays can be accurately done with a circuit simulator. By using the proposed model, one can very rapidly obtain the linear frequency and nonlinear transient responses of arrays with an arbitrary number of CMUT cells. We performed several finite element method (FEM) simulations for arrays with small numbers of cells and showed that the results are very similar to those obtained by the equivalent circuit model.

In situ determination of the static inductance and resistance of a plasma focus capacitor bank.

PubMed

Saw, S H; Lee, S; Roy, F; Chong, P L; Vengadeswaran, V; Sidik, A S M; Leong, Y W; Singh, A

2010-05-01

The static (unloaded) electrical parameters of a capacitor bank are of utmost importance for the purpose of modeling the system as a whole when the capacitor bank is discharged into its dynamic electromagnetic load. Using a physical short circuit across the electromagnetic load is usually technically difficult and is unnecessary. The discharge can be operated at the highest pressure permissible in order to minimize current sheet motion, thus simulating zero dynamic load, to enable bank parameters, static inductance L(0), and resistance r(0) to be obtained using lightly damped sinusoid equations given the bank capacitance C(0). However, for a plasma focus, even at the highest permissible pressure it is found that there is significant residual motion, so that the assumption of a zero dynamic load introduces unacceptable errors into the determination of the circuit parameters. To overcome this problem, the Lee model code is used to fit the computed current trace to the measured current waveform. Hence the dynamics is incorporated into the solution and the capacitor bank parameters are computed using the Lee model code, and more accurate static bank parameters are obtained.

In situ determination of the static inductance and resistance of a plasma focus capacitor bank

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saw, S. H.; Institute for Plasma Focus Studies, 32 Oakpark Drive, Chadstone, Victoria 3148; Lee, S.

2010-05-15

The static (unloaded) electrical parameters of a capacitor bank are of utmost importance for the purpose of modeling the system as a whole when the capacitor bank is discharged into its dynamic electromagnetic load. Using a physical short circuit across the electromagnetic load is usually technically difficult and is unnecessary. The discharge can be operated at the highest pressure permissible in order to minimize current sheet motion, thus simulating zero dynamic load, to enable bank parameters, static inductance L{sub 0}, and resistance r{sub 0} to be obtained using lightly damped sinusoid equations given the bank capacitance C{sub 0}. However, formore » a plasma focus, even at the highest permissible pressure it is found that there is significant residual motion, so that the assumption of a zero dynamic load introduces unacceptable errors into the determination of the circuit parameters. To overcome this problem, the Lee model code is used to fit the computed current trace to the measured current waveform. Hence the dynamics is incorporated into the solution and the capacitor bank parameters are computed using the Lee model code, and more accurate static bank parameters are obtained.« less

Application of the GRC Stirling Convertor System Dynamic Model

NASA Technical Reports Server (NTRS)

Regan, Timothy F.; Lewandowski, Edward J.; Schreiber, Jeffrey G. (Technical Monitor)

2004-01-01

The GRC Stirling Convertor System Dynamic Model (SDM) has been developed to simulate dynamic performance of power systems incorporating free-piston Stirling convertors. This paper discusses its use in evaluating system dynamics and other systems concerns. Detailed examples are provided showing the use of the model in evaluation of off-nominal operating conditions. The many degrees of freedom in both the mechanical and electrical domains inherent in the Stirling convertor and the nonlinear dynamics make simulation an attractive analysis tool in conjunction with classical analysis. Application of SDM in studying the relationship of the size of the resonant circuit quality factor (commonly referred to as Q) in the various resonant mechanical and electrical sub-systems is discussed.

Redefinition of the self-bias voltage in a dielectrically shielded thin sheath RF discharge

NASA Astrophysics Data System (ADS)

Ho, Teck Seng; Charles, Christine; Boswell, Rod

2018-05-01

In a geometrically asymmetric capacitively coupled discharge where the powered electrode is shielded from the plasma by a layer of dielectric material, the self-bias manifests as a nonuniform negative charging in the dielectric rather than on the blocking capacitor. In the thin sheath regime where the ion transit time across the powered sheath is on the order of or less than the Radiofrequency (RF) period, the plasma potential is observed to respond asymmetrically to extraneous impedances in the RF circuit. Consequently, the RF waveform on the plasma-facing surface of the dielectric is unknown, and the behaviour of the powered sheath is not easily predictable. Sheath circuit models become inadequate for describing this class of discharges, and a comprehensive fluid, electrical, and plasma numerical model is employed to accurately quantify this behaviour. The traditional definition of the self-bias voltage as the mean of the RF waveform is shown to be erroneous in this regime. Instead, using the maxima of the RF waveform provides a more rigorous definition given its correlation with the ion dynamics in the powered sheath. This is supported by a RF circuit model derived from the computational fluid dynamics and plasma simulations.

Model parameter estimation approach based on incremental analysis for lithium-ion batteries without using open circuit voltage

NASA Astrophysics Data System (ADS)

Wu, Hongjie; Yuan, Shifei; Zhang, Xi; Yin, Chengliang; Ma, Xuerui

2015-08-01

To improve the suitability of lithium-ion battery model under varying scenarios, such as fluctuating temperature and SoC variation, dynamic model with parameters updated realtime should be developed. In this paper, an incremental analysis-based auto regressive exogenous (I-ARX) modeling method is proposed to eliminate the modeling error caused by the OCV effect and improve the accuracy of parameter estimation. Then, its numerical stability, modeling error, and parametric sensitivity are analyzed at different sampling rates (0.02, 0.1, 0.5 and 1 s). To identify the model parameters recursively, a bias-correction recursive least squares (CRLS) algorithm is applied. Finally, the pseudo random binary sequence (PRBS) and urban dynamic driving sequences (UDDSs) profiles are performed to verify the realtime performance and robustness of the newly proposed model and algorithm. Different sampling rates (1 Hz and 10 Hz) and multiple temperature points (5, 25, and 45 °C) are covered in our experiments. The experimental and simulation results indicate that the proposed I-ARX model can present high accuracy and suitability for parameter identification without using open circuit voltage.

Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns

PubMed Central

Cruchet, Steeve; Gustafson, Kyle; Benton, Richard; Floreano, Dario

2015-01-01

The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs—locomotor bouts—matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior. PMID:26600381

New modeling method for the dielectric relaxation of a DRAM cell capacitor

NASA Astrophysics Data System (ADS)

Choi, Sujin; Sun, Wookyung; Shin, Hyungsoon

2018-02-01

This study proposes a new method for automatically synthesizing the equivalent circuit of the dielectric relaxation (DR) characteristic in dynamic random access memory (DRAM) without frequency dependent capacitance measurement. Charge loss due to DR can be observed by a voltage drop at the storage node and this phenomenon can be analyzed by an equivalent circuit. The Havariliak-Negami model is used to accurately determine the electrical characteristic parameters of an equivalent circuit. The DRAM sensing operation is performed in HSPICE simulations to verify this new method. The simulation demonstrates that the storage node voltage drop resulting from DR and the reduction in the sensing voltage margin, which has a critical impact on DRAM read operation, can be accurately estimated using this new method.

Resilience of the quantum Rabi model in circuit QED

NASA Astrophysics Data System (ADS)

E Manucharyan, Vladimir; Baksic, Alexandre; Ciuti, Cristiano

2017-07-01

In circuit quantum electrodynamics (circuit QED), an artificial ‘circuit atom’ can couple to a quantized microwave radiation much stronger than its real atomic counterpart. The celebrated quantum Rabi model describes the simplest interaction of a two-level system with a single-mode boson field. When the coupling is large enough, the bare multilevel structure of a realistic circuit atom cannot be ignored even if the circuit is strongly anharmonic. We explored this situation theoretically for flux (fluxonium) and charge (Cooper pair box) type multi-level circuits tuned to their respective flux/charge degeneracy points. We identified which spectral features of the quantum Rabi model survive and which are renormalized for large coupling. Despite significant renormalization of the low-energy spectrum in the fluxonium case, the key quantum Rabi feature—nearly-degenerate vacuum consisting of an atomic state entangled with a multi-photon field—appears in both types of circuits when the coupling is sufficiently large. Like in the quantum Rabi model, for very large couplings the entanglement spectrum is dominated by only two, nearly equal eigenvalues, in spite of the fact that a large number of bare atomic states are actually involved in the atom-resonator ground state. We interpret the emergence of the two-fold degeneracy of the vacuum of both circuits as an environmental suppression of flux/charge tunneling due to their dressing by virtual low-/high-impedance photons in the resonator. For flux tunneling, the dressing is nothing else than the shunting of a Josephson atom with a large capacitance of the resonator. Suppression of charge tunneling is a manifestation of the dynamical Coulomb blockade of transport in tunnel junctions connected to resistive leads.

A two-layered diffusion model traces the dynamics of information processing in the valuation-and-choice circuit of decision making.

PubMed

Piu, Pietro; Fargnoli, Francesco; Innocenti, Alessandro; Rufa, Alessandra

2014-01-01

A circuit of evaluation and selection of the alternatives is considered a reliable model in neurobiology. The prominent contributions of the literature to this topic are reported. In this study, valuation and choice of a decisional process during Two-Alternative Forced-Choice (TAFC) task are represented as a two-layered network of computational cells, where information accrual and processing progress in nonlinear diffusion dynamics. The evolution of the response-to-stimulus map is thus modeled by two linked diffusive modules (2LDM) representing the neuronal populations involved in the valuation-and-decision circuit of decision making. Diffusion models are naturally appropriate for describing accumulation of evidence over the time. This allows the computation of the response times (RTs) in valuation and choice, under the hypothesis of ex-Wald distribution. A nonlinear transfer function integrates the activities of the two layers. The input-output map based on the infomax principle makes the 2LDM consistent with the reinforcement learning approach. Results from simulated likelihood time series indicate that 2LDM may account for the activity-dependent modulatory component of effective connectivity between the neuronal populations. Rhythmic fluctuations of the estimate gain functions in the delta-beta bands also support the compatibility of 2LDM with the neurobiology of DM.

Full analogue electronic realisation of the Hodgkin-Huxley neuronal dynamics in weak-inversion CMOS.

PubMed

Lazaridis, E; Drakakis, E M; Barahona, M

2007-01-01

This paper presents a non-linear analog synthesis path towards the modeling and full implementation of the Hodgkin-Huxley neuronal dynamics in silicon. The proposed circuits have been realized in weak-inversion CMOS technology and take advantage of both log-domain and translinear transistor-level techniques.

A Linear Electromagnetic Piston Pump

NASA Astrophysics Data System (ADS)

Hogan, Paul H.

Advancements in mobile hydraulics for human-scale applications have increased demand for a compact hydraulic power supply. Conventional designs couple a rotating electric motor to a hydraulic pump, which increases the package volume and requires several energy conversions. This thesis investigates the use of a free piston as the moving element in a linear motor to eliminate multiple energy conversions and decrease the overall package volume. A coupled model used a quasi-static magnetic equivalent circuit to calculate the motor inductance and the electromagnetic force acting on the piston. The force was an input to a time domain model to evaluate the mechanical and pressure dynamics. The magnetic circuit model was validated with finite element analysis and an experimental prototype linear motor. The coupled model was optimized using a multi-objective genetic algorithm to explore the parameter space and maximize power density and efficiency. An experimental prototype linear pump coupled pistons to an off-the-shelf linear motor to validate the mechanical and pressure dynamics models. The magnetic circuit force calculation agreed within 3% of finite element analysis, and within 8% of experimental data from the unoptimized prototype linear motor. The optimized motor geometry also had good agreement with FEA; at zero piston displacement, the magnetic circuit calculates optimized motor force within 10% of FEA in less than 1/1000 the computational time. This makes it well suited to genetic optimization algorithms. The mechanical model agrees very well with the experimental piston pump position data when tuned for additional unmodeled mechanical friction. Optimized results suggest that an improvement of 400% of the state of the art power density is attainable with as high as 85% net efficiency. This demonstrates that a linear electromagnetic piston pump has potential to serve as a more compact and efficient supply of fluid power for the human scale.

Implementing a Bayes Filter in a Neural Circuit: The Case of Unknown Stimulus Dynamics.

PubMed

Sokoloski, Sacha

2017-09-01

In order to interact intelligently with objects in the world, animals must first transform neural population responses into estimates of the dynamic, unknown stimuli that caused them. The Bayesian solution to this problem is known as a Bayes filter, which applies Bayes' rule to combine population responses with the predictions of an internal model. The internal model of the Bayes filter is based on the true stimulus dynamics, and in this note, we present a method for training a theoretical neural circuit to approximately implement a Bayes filter when the stimulus dynamics are unknown. To do this we use the inferential properties of linear probabilistic population codes to compute Bayes' rule and train a neural network to compute approximate predictions by the method of maximum likelihood. In particular, we perform stochastic gradient descent on the negative log-likelihood of the neural network parameters with a novel approximation of the gradient. We demonstrate our methods on a finite-state, a linear, and a nonlinear filtering problem and show how the hidden layer of the neural network develops tuning curves consistent with findings in experimental neuroscience.

Corticostriatal circuit mechanisms of value-based action selection: Implementation of reinforcement learning algorithms and beyond.

PubMed

Morita, Kenji; Jitsev, Jenia; Morrison, Abigail

2016-09-15

Value-based action selection has been suggested to be realized in the corticostriatal local circuits through competition among neural populations. In this article, we review theoretical and experimental studies that have constructed and verified this notion, and provide new perspectives on how the local-circuit selection mechanisms implement reinforcement learning (RL) algorithms and computations beyond them. The striatal neurons are mostly inhibitory, and lateral inhibition among them has been classically proposed to realize "Winner-Take-All (WTA)" selection of the maximum-valued action (i.e., 'max' operation). Although this view has been challenged by the revealed weakness, sparseness, and asymmetry of lateral inhibition, which suggest more complex dynamics, WTA-like competition could still occur on short time scales. Unlike the striatal circuit, the cortical circuit contains recurrent excitation, which may enable retention or temporal integration of information and probabilistic "soft-max" selection. The striatal "max" circuit and the cortical "soft-max" circuit might co-implement an RL algorithm called Q-learning; the cortical circuit might also similarly serve for other algorithms such as SARSA. In these implementations, the cortical circuit presumably sustains activity representing the executed action, which negatively impacts dopamine neurons so that they can calculate reward-prediction-error. Regarding the suggested more complex dynamics of striatal, as well as cortical, circuits on long time scales, which could be viewed as a sequence of short WTA fragments, computational roles remain open: such a sequence might represent (1) sequential state-action-state transitions, constituting replay or simulation of the internal model, (2) a single state/action by the whole trajectory, or (3) probabilistic sampling of state/action. Copyright © 2016. Published by Elsevier B.V.

Discrete Time-Crystalline Order in Cavity and Circuit QED Systems

NASA Astrophysics Data System (ADS)

Gong, Zongping; Hamazaki, Ryusuke; Ueda, Masahito

2018-01-01

Discrete time crystals are a recently proposed and experimentally observed out-of-equilibrium dynamical phase of Floquet systems, where the stroboscopic dynamics of a local observable repeats itself at an integer multiple of the driving period. We address this issue in a driven-dissipative setup, focusing on the modulated open Dicke model, which can be implemented by cavity or circuit QED systems. In the thermodynamic limit, we employ semiclassical approaches and find rich dynamical phases on top of the discrete time-crystalline order. In a deep quantum regime with few qubits, we find clear signatures of a transient discrete time-crystalline behavior, which is absent in the isolated counterpart. We establish a phenomenology of dissipative discrete time crystals by generalizing the Landau theory of phase transitions to Floquet open systems.

Closed-Loop and Activity-Guided Optogenetic Control

PubMed Central

Grosenick, Logan; Marshel, James H.; Deisseroth, Karl

2016-01-01

Advances in optical manipulation and observation of neural activity have set the stage for widespread implementation of closed-loop and activity-guided optical control of neural circuit dynamics. Closing the loop optogenetically (i.e., basing optogenetic stimulation on simultaneously observed dynamics in a principled way) is a powerful strategy for causal investigation of neural circuitry. In particular, observing and feeding back the effects of circuit interventions on physiologically relevant timescales is valuable for directly testing whether inferred models of dynamics, connectivity, and causation are accurate in vivo. Here we highlight technical and theoretical foundations as well as recent advances and opportunities in this area, and we review in detail the known caveats and limitations of optogenetic experimentation in the context of addressing these challenges with closed-loop optogenetic control in behaving animals. PMID:25856490

Phase Difference between Model Cortical Areas Determines Level of Information Transfer

PubMed Central

ter Wal, Marije; Tiesinga, Paul H.

2017-01-01

Communication between cortical sites is mediated by long-range synaptic connections. However, these connections are relatively static, while everyday cognitive tasks demand a fast and flexible routing of information in the brain. Synchronization of activity between distant cortical sites has been proposed as the mechanism underlying such a dynamic communication structure. Here, we study how oscillatory activity affects the excitability and input-output relation of local cortical circuits and how it alters the transmission of information between cortical circuits. To this end, we develop model circuits showing fast oscillations by the PING mechanism, of which the oscillatory characteristics can be altered. We identify conditions for synchronization between two brain circuits and show that the level of intercircuit coherence and the phase difference is set by the frequency difference between the intrinsic oscillations. We show that the susceptibility of the circuits to inputs, i.e., the degree of change in circuit output following input pulses, is not uniform throughout the oscillation period and that both firing rate, frequency and power are differentially modulated by inputs arriving at different phases. As a result, an appropriate phase difference between the circuits is critical for the susceptibility windows of the circuits in the network to align and for information to be efficiently transferred. We demonstrate that changes in synchrony and phase difference can be used to set up or abolish information transfer in a network of cortical circuits. PMID:28232796

Chaos and multi-scroll attractors in RCL-shunted junction coupled Jerk circuit connected by memristor

PubMed Central

Zhou, Ping; Ahmad, Bashir; Ren, Guodong; Wang, Chunni

2018-01-01

In this paper, a new four-variable dynamical system is proposed to set chaotic circuit composed of memristor and Josephson junction, and the dependence of chaotic behaviors on nonlinearity is investigated. A magnetic flux-controlled memristor is used to couple with the RCL-shunted junction circuit, and the dynamical behaviors can be modulated by changing the coupling intensity between the memristor and the RCL-shunted junction. Bifurcation diagram and Lyapunov exponent are calculated to confirm the emergence of chaos in the improved dynamical system. The outputs and dynamical behaviors can be controlled by the initial setting and external stimulus as well. As a result, chaos can be suppressed and spiking occurs in the sampled outputs under negative feedback, while applying positive feedback type via memristor can be effective to trigger chaos. Furthermore, it is found that the number of multi-attractors in the Jerk circuit can be modulated when memristor coupling is applied on the circuit. These results indicate that memristor coupling can be effective to control chaotic circuits and it is also useful to reproduce dynamical behaviors for neuronal activities. PMID:29342178

Chaos and multi-scroll attractors in RCL-shunted junction coupled Jerk circuit connected by memristor.

PubMed

Ma, Jun; Zhou, Ping; Ahmad, Bashir; Ren, Guodong; Wang, Chunni

2018-01-01

In this paper, a new four-variable dynamical system is proposed to set chaotic circuit composed of memristor and Josephson junction, and the dependence of chaotic behaviors on nonlinearity is investigated. A magnetic flux-controlled memristor is used to couple with the RCL-shunted junction circuit, and the dynamical behaviors can be modulated by changing the coupling intensity between the memristor and the RCL-shunted junction. Bifurcation diagram and Lyapunov exponent are calculated to confirm the emergence of chaos in the improved dynamical system. The outputs and dynamical behaviors can be controlled by the initial setting and external stimulus as well. As a result, chaos can be suppressed and spiking occurs in the sampled outputs under negative feedback, while applying positive feedback type via memristor can be effective to trigger chaos. Furthermore, it is found that the number of multi-attractors in the Jerk circuit can be modulated when memristor coupling is applied on the circuit. These results indicate that memristor coupling can be effective to control chaotic circuits and it is also useful to reproduce dynamical behaviors for neuronal activities.

Transition to Chaos in Random Neuronal Networks

NASA Astrophysics Data System (ADS)

Kadmon, Jonathan; Sompolinsky, Haim

2015-10-01

Firing patterns in the central nervous system often exhibit strong temporal irregularity and considerable heterogeneity in time-averaged response properties. Previous studies suggested that these properties are the outcome of the intrinsic chaotic dynamics of the neural circuits. Indeed, simplified rate-based neuronal networks with synaptic connections drawn from Gaussian distribution and sigmoidal nonlinearity are known to exhibit chaotic dynamics when the synaptic gain (i.e., connection variance) is sufficiently large. In the limit of an infinitely large network, there is a sharp transition from a fixed point to chaos, as the synaptic gain reaches a critical value. Near the onset, chaotic fluctuations are slow, analogous to the ubiquitous, slow irregular fluctuations observed in the firing rates of many cortical circuits. However, the existence of a transition from a fixed point to chaos in neuronal circuit models with more realistic architectures and firing dynamics has not been established. In this work, we investigate rate-based dynamics of neuronal circuits composed of several subpopulations with randomly diluted connections. Nonzero connections are either positive for excitatory neurons or negative for inhibitory ones, while single neuron output is strictly positive with output rates rising as a power law above threshold, in line with known constraints in many biological systems. Using dynamic mean field theory, we find the phase diagram depicting the regimes of stable fixed-point, unstable-dynamic, and chaotic-rate fluctuations. We focus on the latter and characterize the properties of systems near this transition. We show that dilute excitatory-inhibitory architectures exhibit the same onset to chaos as the single population with Gaussian connectivity. In these architectures, the large mean excitatory and inhibitory inputs dynamically balance each other, amplifying the effect of the residual fluctuations. Importantly, the existence of a transition to chaos and its critical properties depend on the shape of the single-neuron nonlinear input-output transfer function, near firing threshold. In particular, for nonlinear transfer functions with a sharp rise near threshold, the transition to chaos disappears in the limit of a large network; instead, the system exhibits chaotic fluctuations even for small synaptic gain. Finally, we investigate transition to chaos in network models with spiking dynamics. We show that when synaptic time constants are slow relative to the mean inverse firing rates, the network undergoes a transition from fast spiking fluctuations with constant rates to a state where the firing rates exhibit chaotic fluctuations, similar to the transition predicted by rate-based dynamics. Systems with finite synaptic time constants and firing rates exhibit a smooth transition from a regime dominated by stationary firing rates to a regime of slow rate fluctuations. This smooth crossover obeys scaling properties, similar to crossover phenomena in statistical mechanics. The theoretical results are supported by computer simulations of several neuronal architectures and dynamics. Consequences for cortical circuit dynamics are discussed. These results advance our understanding of the properties of intrinsic dynamics in realistic neuronal networks and their functional consequences.

Introduction to focus issue: quantitative approaches to genetic networks.

PubMed

Albert, Réka; Collins, James J; Glass, Leon

2013-06-01

All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks using field-programmable gate arrays. Mathematical analyses will be essential for understanding naturally occurring genetic networks in diverse organisms and for providing a foundation for the improved development of synthetic genetic networks.

Introduction to Focus Issue: Quantitative Approaches to Genetic Networks

NASA Astrophysics Data System (ADS)

Albert, Réka; Collins, James J.; Glass, Leon

2013-06-01

All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks using field-programmable gate arrays. Mathematical analyses will be essential for understanding naturally occurring genetic networks in diverse organisms and for providing a foundation for the improved development of synthetic genetic networks.

Piezoelectric self-sensing actuator for active vibration control of motorized spindle based on adaptive signal separation

NASA Astrophysics Data System (ADS)

He, Ye; Chen, Xiaoan; Liu, Zhi; Qin, Yi

2018-06-01

The motorized spindle is the core component of CNC machine tools, and the vibration of it reduces the machining precision and service life of the machine tools. Owing to the fast response, large output force, and displacement of the piezoelectric stack, it is often used as the actuator in the active vibration control of the spindle. A piezoelectric self-sensing actuator (SSA) can reduce the cost of the active vibration control system and simplify the structure by eliminating the use of a sensor, because a SSA can have both actuating and sensing functions at the same time. The signal separation method of a SSA based on a bridge circuit is widely applied because of its simple principle and easy implementation. However, it is difficult to maintain dynamic balance of the circuit. Prior research has used adaptive algorithm to balance of the bridge circuit on the flexible beam dynamically, but those algorithms need no correlation between sensing and control voltage, which limit the applications of SSA in the vibration control of the rotor-bearing system. Here, the electromechanical coupling model of the piezoelectric stack is established, followed by establishment of the dynamic model of the spindle system. Next, a new adaptive signal separation method based on the bridge circuit is proposed, which can separate relative small sensing voltage from related mixed voltage adaptively. The experimental results show that when the self-sensing signal obtained from the proposed method is used as a displacement signal, the vibration of the motorized spindle can be suppressed effectively through a linear quadratic Gaussian (LQG) algorithm.

Dynamic corticostriatal activity biases social bonding in monogamous female prairie voles

PubMed Central

Amadei, Elizabeth A.; Johnson, Zachary V.; Kwon, Yong Jun; Shpiner, Aaron C.; Saravanan, Varun; Mays, Wittney D.; Ryan, Steven J.; Walum, Hasse; Rainnie, Donald G.; Young, Larry J.; Liu, Robert C.

2017-01-01

Summary paragraph Adult pair bonding involves dramatic changes in the perception and valuation of another individual1. One key change is that partners come to reliably activate the brain's reward system2-6, though the precise neural mechanisms by which partners become rewarding during sociosexual interactions leading to a bond remain unclear. Using a prairie vole model of social bonding7, we show how a functional circuit from medial prefrontal cortex (mPFC) to nucleus accumbens (NAcc) is dynamically modulated to enhance females' affiliative behavior towards a partner. Individual variation in the strength of this functional connectivity, particularly after the first mating encounter, predicts how quickly animals begin affiliative huddling with their partner. Rhythmically activating this circuit in a social context without mating biases later preference towards a partner, indicating that this circuit's activity is not just correlated with how quickly animals become affiliative but causally accelerates it. These results provide the first dynamic view of corticostriatal activity during bond formation, revealing how social interactions can recruit brain reward systems to drive changes in affiliative behavior. PMID:28562592

Neural reuse of action perception circuits for language, concepts and communication.

PubMed

Pulvermüller, Friedemann

2018-01-01

Neurocognitive and neurolinguistics theories make explicit statements relating specialized cognitive and linguistic processes to specific brain loci. These linking hypotheses are in need of neurobiological justification and explanation. Recent mathematical models of human language mechanisms constrained by fundamental neuroscience principles and established knowledge about comparative neuroanatomy offer explanations for where, when and how language is processed in the human brain. In these models, network structure and connectivity along with action- and perception-induced correlation of neuronal activity co-determine neurocognitive mechanisms. Language learning leads to the formation of action perception circuits (APCs) with specific distributions across cortical areas. Cognitive and linguistic processes such as speech production, comprehension, verbal working memory and prediction are modelled by activity dynamics in these APCs, and combinatorial and communicative-interactive knowledge is organized in the dynamics within, and connections between APCs. The network models and, in particular, the concept of distributionally-specific circuits, can account for some previously not well understood facts about the cortical 'hubs' for semantic processing and the motor system's role in language understanding and speech sound recognition. A review of experimental data evaluates predictions of the APC model and alternative theories, also providing detailed discussion of some seemingly contradictory findings. Throughout, recent disputes about the role of mirror neurons and grounded cognition in language and communication are assessed critically. Copyright © 2017 The Author. Published by Elsevier Ltd.. All rights reserved.

Simulative method for determining the optimal operating conditions for a cooling plate for lithium-ion battery cell modules

NASA Astrophysics Data System (ADS)

Smith, Joshua; Hinterberger, Michael; Hable, Peter; Koehler, Juergen

2014-12-01

Extended battery system lifetime and reduced costs are essential to the success of electric vehicles. An effective thermal management strategy is one method of enhancing system lifetime increasing vehicle range. Vehicle-typical space restrictions favor the minimization of battery thermal management system (BTMS) size and weight, making their production and subsequent vehicle integration extremely difficult and complex. Due to these space requirements, a cooling plate as part of a water-glycerol cooling circuit is commonly implemented. This paper presents a computational fluid dynamics (CFD) model and multi-objective analysis technique for determining the thermal effect of coolant flow rate and inlet temperature in a cooling plate-at a range of vehicle operating conditions-on a battery system, thereby providing a dynamic input for one-dimensional models. Traditionally, one-dimensional vehicular thermal management system models assume a static heat input from components such as a battery system: as a result, the components are designed for a set coolant input (flow rate and inlet temperature). Such a design method is insufficient for dynamic thermal management models and control strategies, thereby compromising system efficiency. The presented approach allows for optimal BMTS design and integration in the vehicular coolant circuit.

Bit-systolic arithmetic arrays using dynamic differential gallium arsenide circuits

NASA Technical Reports Server (NTRS)

Beagles, Grant; Winters, Kel; Eldin, A. G.

1992-01-01

A new family of gallium arsenide circuits for fine grained bit-systolic arithmetic arrays is introduced. This scheme combines features of two recent techniques of dynamic gallium arsenide FET logic and differential dynamic single-clock CMOS logic. The resulting circuits are fast and compact, with tightly constrained series FET propagation paths, low fanout, no dc power dissipation, and depletion FET implementation without level shifting diodes.

Hacking DNA copy number for circuit engineering.

PubMed

Wu, Feilun; You, Lingchong

2017-07-27

DNA copy number represents an essential parameter in the dynamics of synthetic gene circuits but typically is not explicitly considered. A new study demonstrates how dynamic control of DNA copy number can serve as an effective strategy to program robust oscillations in gene expression circuits.

A hyperjerk memristive system with infinite equilibrium points

NASA Astrophysics Data System (ADS)

Prousalis, Dimitrios A.; Volos, Christos K.; Stouboulos, Ioannis N.; Kyprianidis, Ioannis M.

2017-09-01

A novel 4-D dynamical memristive system is presented in this work. The specificity of the model is that it develops a line of equilibrium points and it has hyperjerk dynamics in a particular range of the parameters space. The behavior of the suggested system is investigated through numerical simulations, by using phase portraits, Lyapunov exponents, bifurcation diagrams. Also, its circuital implementation confirms the memristive system's expected dynamics.

A 1.26 μW Cytomimetic IC Emulating Complex Nonlinear Mammalian Cell Cycle Dynamics: Synthesis, Simulation and Proof-of-Concept Measured Results.

PubMed

Houssein, Alexandros; Papadimitriou, Konstantinos I; Drakakis, Emmanuel M

2015-08-01

Cytomimetic circuits represent a novel, ultra low-power, continuous-time, continuous-value class of circuits, capable of mapping on silicon cellular and molecular dynamics modelled by means of nonlinear ordinary differential equations (ODEs). Such monolithic circuits are in principle able to emulate on chip, single or multiple cell operations in a highly parallel fashion. Cytomimetic topologies can be synthesized by adopting the Nonlinear Bernoulli Cell Formalism (NBCF), a mathematical framework that exploits the striking similarities between the equations describing weakly-inverted Metal-Oxide Semiconductor (MOS) devices and coupled nonlinear ODEs, typically appearing in models of naturally encountered biochemical systems. The NBCF maps biological state variables onto strictly positive subthreshold MOS circuit currents. This paper presents the synthesis, the simulation and proof-of-concept chip results corresponding to the emulation of a complex cellular network mechanism, the skeleton model for the network of Cyclin-dependent Kinases (CdKs) driving the mammalian cell cycle. This five variable nonlinear biological model, when appropriate model parameter values are assigned, can exhibit multiple oscillatory behaviors, varying from simple periodic oscillations, to complex oscillations such as quasi-periodicity and chaos. The validity of our approach is verified by simulated results with realistic process parameters from the commercially available AMS 0.35 μm technology and by chip measurements. The fabricated chip occupies an area of 2.27 mm2 and consumes a power of 1.26 μW from a power supply of 3 V. The presented cytomimetic topology follows closely the behavior of its biological counterpart, exhibiting similar time-dependent solutions of the Cdk complexes, the transcription factors and the proteins.

The Impact of Structural Heterogeneity on Excitation-Inhibition Balance in Cortical Networks.

PubMed

Landau, Itamar D; Egger, Robert; Dercksen, Vincent J; Oberlaender, Marcel; Sompolinsky, Haim

2016-12-07

Models of cortical dynamics often assume a homogeneous connectivity structure. However, we show that heterogeneous input connectivity can prevent the dynamic balance between excitation and inhibition, a hallmark of cortical dynamics, and yield unrealistically sparse and temporally regular firing. Anatomically based estimates of the connectivity of layer 4 (L4) rat barrel cortex and numerical simulations of this circuit indicate that the local network possesses substantial heterogeneity in input connectivity, sufficient to disrupt excitation-inhibition balance. We show that homeostatic plasticity in inhibitory synapses can align the functional connectivity to compensate for structural heterogeneity. Alternatively, spike-frequency adaptation can give rise to a novel state in which local firing rates adjust dynamically so that adaptation currents and synaptic inputs are balanced. This theory is supported by simulations of L4 barrel cortex during spontaneous and stimulus-evoked conditions. Our study shows how synaptic and cellular mechanisms yield fluctuation-driven dynamics despite structural heterogeneity in cortical circuits. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Temperature-Dependent Short-Circuit Capability of Silicon Carbide Power MOSFETs

DOE PAGES

Wang, Zhiqiang; Shi, Xiaojie; Tolbert, Leon M.; ...

2016-02-01

Our paper presents a comprehensive short-circuit ruggedness evaluation and numerical investigation of up-to-date commercial silicon carbide (SiC) MOSFETs. The short-circuit capability of three types of commercial 1200-V SiC MOSFETs is tested under various conditions, with case temperatures from 25 to 200 degrees C and dc bus voltages from 400 to 750 V. It is found that the commercial SiC MOSFETs can withstand short-circuit current for only several microseconds with a dc bus voltage of 750 V and case temperature of 200 degrees C. Moreover, the experimental short-circuit behaviors are compared, and analyzed through numerical thermal dynamic simulation. Specifically, an electrothermalmore » model is built to estimate the device internal temperature distribution, considering the temperature-dependent thermal properties of SiC material. Based on the temperature information, a leakage current model is derived to calculate the main leakage current components (i.e., thermal, diffusion, and avalanche generation currents). Finally, numerical results show that the short-circuit failure mechanisms of SiC MOSFETs can be thermal generation current induced thermal runaway or high-temperature-related gate oxide damage.« less

Multi-mode ultra-strong coupling (I): spectroscopic experiments using a vacuum-gap transmon circuit architecture

NASA Astrophysics Data System (ADS)

Bosman, Sal J.; Gely, Mario F.; Singh, Vibhor; Bruno, Alessandro; Bothner, Daniel; Steele, Gary A.

In circuit QED, multi-mode extensions of the quantum Rabi model suffer from divergence problems. Here, we spectroscopically study multi-mode ultra-strong coupling using a transmon circuit architecture, which provides no clear guidelines on how many modes play a role in the dynamics of the system. As our transmon qubit, we employ a suspended island above the voltage anti-node of a λ / 4 coplanar microwave resonator, thereby realising a circuit where 88% of the qubit capacitance is formed by a vacuum-gap capacitor with the center conductor of the resonator. We measure vacuum Rabi splitting over multiple modes up to 2 GHz, reaching coupling ratios of g / ω = 0 . 18 , well within the ultra-strong coupling regime. We observe a qubit-mediated mode coupling, measurable up to the fifth mode at 38 GHz. Using a novel analytical quantum circuit model of this architecture, which includes all modes without introducing divergencies, we are able to fit the full spectrum and extract a vacuum fluctuations induced Bloch-Siegert shift of up to 62 MHz. This circuit architecture expands the versatility of the transmon technology platform and opens many possibilities in multi-mode physics in the ultra-strong coupling regime.

Design and Implementation of a Biomolecular Concentration Tracker

PubMed Central

2015-01-01

As a field, synthetic biology strives to engineer increasingly complex artificial systems in living cells. Active feedback in closed loop systems offers a dynamic and adaptive way to ensure constant relative activity independent of intrinsic and extrinsic noise. In this work, we use synthetic protein scaffolds as a modular and tunable mechanism for concentration tracking through negative feedback. Input to the circuit initiates scaffold production, leading to colocalization of a two-component system and resulting in the production of an inhibitory antiscaffold protein. Using a combination of modeling and experimental work, we show that the biomolecular concentration tracker circuit achieves dynamic protein concentration tracking in Escherichia coli and that steady state outputs can be tuned. PMID:24847683

A systematic review of lumped-parameter equivalent circuit models for real-time estimation of lithium-ion battery states

NASA Astrophysics Data System (ADS)

Nejad, S.; Gladwin, D. T.; Stone, D. A.

2016-06-01

This paper presents a systematic review for the most commonly used lumped-parameter equivalent circuit model structures in lithium-ion battery energy storage applications. These models include the Combined model, Rint model, two hysteresis models, Randles' model, a modified Randles' model and two resistor-capacitor (RC) network models with and without hysteresis included. Two variations of the lithium-ion cell chemistry, namely the lithium-ion iron phosphate (LiFePO4) and lithium nickel-manganese-cobalt oxide (LiNMC) are used for testing purposes. The model parameters and states are recursively estimated using a nonlinear system identification technique based on the dual Extended Kalman Filter (dual-EKF) algorithm. The dynamic performance of the model structures are verified using the results obtained from a self-designed pulsed-current test and an electric vehicle (EV) drive cycle based on the New European Drive Cycle (NEDC) profile over a range of operating temperatures. Analysis on the ten model structures are conducted with respect to state-of-charge (SOC) and state-of-power (SOP) estimation with erroneous initial conditions. Comparatively, both RC model structures provide the best dynamic performance, with an outstanding SOC estimation accuracy. For those cell chemistries with large inherent hysteresis levels (e.g. LiFePO4), the RC model with only one time constant is combined with a dynamic hysteresis model to further enhance the performance of the SOC estimator.

Simulation of the Process of Arc Energy-Effect in High Voltage Auto-Expansion SF6 Circuit Breaker

NASA Astrophysics Data System (ADS)

Rong, Mingzhe; Yang, Qian; Fan, Chunduo

2005-12-01

A new magnetic hydro-dynamics (MHD) model of arc in H.V. auto-expansion SF6 circuit breaker that takes into consideration nozzle ablation due to both radiation and thermal conduction is presented in this paper. The effect of PTFE (polytetrafluorethylene) vapor is considered in the mass, momentum and energy conservation equations of the constructed model. Then, the gas flow fields with and without conduction considered are simulated. By comparing the aforementioned two results, it is indicated that the arc's maximal temperature with conduction considered is 90 percent of that without considering conduction.

High accuracy switched-current circuits using an improved dynamic mirror

NASA Technical Reports Server (NTRS)

Zweigle, G.; Fiez, T.

1991-01-01

The switched-current technique, a recently developed circuit approach to analog signal processing, has emerged as an alternative/compliment to the well established switched-capacitor circuit technique. High speed switched-current circuits offer potential cost and power savings over slower switched-capacitor circuits. Accuracy improvements are a primary concern at this stage in the development of the switched-current technique. Use of the dynamic current mirror has produced circuits that are insensitive to transistor matching errors. The dynamic current mirror has been limited by other sources of error including clock-feedthrough and voltage transient errors. In this paper we present an improved switched-current building block using the dynamic current mirror. Utilizing current feedback the errors due to current imbalance in the dynamic current mirror are reduced. Simulations indicate that this feedback can reduce total harmonic distortion by as much as 9 dB. Additionally, we have developed a clock-feedthrough reduction scheme for which simulations reveal a potential 10 dB total harmonic distortion improvement. The clock-feedthrough reduction scheme also significantly reduces offset errors and allows for cancellation with a constant current source. Experimental results confirm the simulated improvements.

SNDR Limits of Oscillator-Based Sensor Readout Circuits.

PubMed

Cardes, Fernando; Quintero, Andres; Gutierrez, Eric; Buffa, Cesare; Wiesbauer, Andreas; Hernandez, Luis

2018-02-03

This paper analyzes the influence of phase noise and distortion on the performance of oscillator-based sensor data acquisition systems. Circuit noise inherent to the oscillator circuit manifests as phase noise and limits the SNR. Moreover, oscillator nonlinearity generates distortion for large input signals. Phase noise analysis of oscillators is well known in the literature, but the relationship between phase noise and the SNR of an oscillator-based sensor is not straightforward. This paper proposes a model to estimate the influence of phase noise in the performance of an oscillator-based system by reflecting the phase noise to the oscillator input. The proposed model is based on periodic steady-state analysis tools to predict the SNR of the oscillator. The accuracy of this model has been validated by both simulation and experiment in a 130 nm CMOS prototype. We also propose a method to estimate the SNDR and the dynamic range of an oscillator-based readout circuit that improves by more than one order of magnitude the simulation time compared to standard time domain simulations. This speed up enables the optimization and verification of this kind of systems with iterative algorithms.

Digital-analog quantum simulation of generalized Dicke models with superconducting circuits

NASA Astrophysics Data System (ADS)

Lamata, Lucas

2017-03-01

We propose a digital-analog quantum simulation of generalized Dicke models with superconducting circuits, including Fermi- Bose condensates, biased and pulsed Dicke models, for all regimes of light-matter coupling. We encode these classes of problems in a set of superconducting qubits coupled with a bosonic mode implemented by a transmission line resonator. Via digital-analog techniques, an efficient quantum simulation can be performed in state-of-the-art circuit quantum electrodynamics platforms, by suitable decomposition into analog qubit-bosonic blocks and collective single-qubit pulses through digital steps. Moreover, just a single global analog block would be needed during the whole protocol in most of the cases, superimposed with fast periodic pulses to rotate and detune the qubits. Therefore, a large number of digital steps may be attained with this approach, providing a reduced digital error. Additionally, the number of gates per digital step does not grow with the number of qubits, rendering the simulation efficient. This strategy paves the way for the scalable digital-analog quantum simulation of many-body dynamics involving bosonic modes and spin degrees of freedom with superconducting circuits.

Digital-analog quantum simulation of generalized Dicke models with superconducting circuits

PubMed Central

Lamata, Lucas

2017-01-01

We propose a digital-analog quantum simulation of generalized Dicke models with superconducting circuits, including Fermi- Bose condensates, biased and pulsed Dicke models, for all regimes of light-matter coupling. We encode these classes of problems in a set of superconducting qubits coupled with a bosonic mode implemented by a transmission line resonator. Via digital-analog techniques, an efficient quantum simulation can be performed in state-of-the-art circuit quantum electrodynamics platforms, by suitable decomposition into analog qubit-bosonic blocks and collective single-qubit pulses through digital steps. Moreover, just a single global analog block would be needed during the whole protocol in most of the cases, superimposed with fast periodic pulses to rotate and detune the qubits. Therefore, a large number of digital steps may be attained with this approach, providing a reduced digital error. Additionally, the number of gates per digital step does not grow with the number of qubits, rendering the simulation efficient. This strategy paves the way for the scalable digital-analog quantum simulation of many-body dynamics involving bosonic modes and spin degrees of freedom with superconducting circuits. PMID:28256559

Cholinergic modulation of cognitive processing: insights drawn from computational models

PubMed Central

Newman, Ehren L.; Gupta, Kishan; Climer, Jason R.; Monaghan, Caitlin K.; Hasselmo, Michael E.

2012-01-01

Acetylcholine plays an important role in cognitive function, as shown by pharmacological manipulations that impact working memory, attention, episodic memory, and spatial memory function. Acetylcholine also shows striking modulatory influences on the cellular physiology of hippocampal and cortical neurons. Modeling of neural circuits provides a framework for understanding how the cognitive functions may arise from the influence of acetylcholine on neural and network dynamics. We review the influences of cholinergic manipulations on behavioral performance in working memory, attention, episodic memory, and spatial memory tasks, the physiological effects of acetylcholine on neural and circuit dynamics, and the computational models that provide insight into the functional relationships between the physiology and behavior. Specifically, we discuss the important role of acetylcholine in governing mechanisms of active maintenance in working memory tasks and in regulating network dynamics important for effective processing of stimuli in attention and episodic memory tasks. We also propose that theta rhythm plays a crucial role as an intermediary between the physiological influences of acetylcholine and behavior in episodic and spatial memory tasks. We conclude with a synthesis of the existing modeling work and highlight future directions that are likely to be rewarding given the existing state of the literature for both empiricists and modelers. PMID:22707936

Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex.

PubMed

Mejias, Jorge F; Murray, John D; Kennedy, Henry; Wang, Xiao-Jing

2016-11-01

Interactions between top-down and bottom-up processes in the cerebral cortex hold the key to understanding attentional processes, predictive coding, executive control, and a gamut of other brain functions. However, the underlying circuit mechanism remains poorly understood and represents a major challenge in neuroscience. We approached this problem using a large-scale computational model of the primate cortex constrained by new directed and weighted connectivity data. In our model, the interplay between feedforward and feedback signaling depends on the cortical laminar structure and involves complex dynamics across multiple (intralaminar, interlaminar, interareal, and whole cortex) scales. The model was tested by reproducing, as well as providing insights into, a wide range of neurophysiological findings about frequency-dependent interactions between visual cortical areas, including the observation that feedforward pathways are associated with enhanced gamma (30 to 70 Hz) oscillations, whereas feedback projections selectively modulate alpha/low-beta (8 to 15 Hz) oscillations. Furthermore, the model reproduces a functional hierarchy based on frequency-dependent Granger causality analysis of interareal signaling, as reported in recent monkey and human experiments, and suggests a mechanism for the observed context-dependent hierarchy dynamics. Together, this work highlights the necessity of multiscale approaches and provides a modeling platform for studies of large-scale brain circuit dynamics and functions.

Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex

PubMed Central

Mejias, Jorge F.; Murray, John D.; Kennedy, Henry; Wang, Xiao-Jing

2016-01-01

Interactions between top-down and bottom-up processes in the cerebral cortex hold the key to understanding attentional processes, predictive coding, executive control, and a gamut of other brain functions. However, the underlying circuit mechanism remains poorly understood and represents a major challenge in neuroscience. We approached this problem using a large-scale computational model of the primate cortex constrained by new directed and weighted connectivity data. In our model, the interplay between feedforward and feedback signaling depends on the cortical laminar structure and involves complex dynamics across multiple (intralaminar, interlaminar, interareal, and whole cortex) scales. The model was tested by reproducing, as well as providing insights into, a wide range of neurophysiological findings about frequency-dependent interactions between visual cortical areas, including the observation that feedforward pathways are associated with enhanced gamma (30 to 70 Hz) oscillations, whereas feedback projections selectively modulate alpha/low-beta (8 to 15 Hz) oscillations. Furthermore, the model reproduces a functional hierarchy based on frequency-dependent Granger causality analysis of interareal signaling, as reported in recent monkey and human experiments, and suggests a mechanism for the observed context-dependent hierarchy dynamics. Together, this work highlights the necessity of multiscale approaches and provides a modeling platform for studies of large-scale brain circuit dynamics and functions. PMID:28138530

Complex computation in the retina

NASA Astrophysics Data System (ADS)

Deshmukh, Nikhil Rajiv

Elucidating the general principles of computation in neural circuits is a difficult problem requiring both a tractable model circuit as well as sophisticated measurement tools. This thesis advances our understanding of complex computation in the salamander retina and its underlying circuitry and furthers the development of advanced tools to enable detailed study of neural circuits. The retina provides an ideal model system for neural circuits in general because it is capable of producing complex representations of the visual scene, and both its inputs and outputs are accessible to the experimenter. Chapter 2 describes the biophysical mechanisms that give rise to the omitted stimulus response in retinal ganglion cells described in Schwartz et al., (2007) and Schwartz and Berry, (2008). The extra response to omitted flashes is generated at the input to bipolar cells, and is separable from the characteristic latency shift of the OSR apparent in ganglion cells, which must occur downstream in the circuit. Chapter 3 characterizes the nonlinearities at the first synapse of the ON pathway in response to high contrast flashes and develops a phenomenological model that captures the effect of synaptic activation and intracellular signaling dynamics on flash responses. This work is the first attempt to model the dynamics of the poorly characterized mGluR6 transduction cascade unique to ON bipolar cells, and explains the second lobe of the biphasic flash response. Complementary to the study of neural circuits, recent advances in wafer-scale photolithography have made possible new devices to measure the electrical and mechanical properties of neurons. Chapter 4 reports a novel piezoelectric sensor that facilitates the simultaneous measurement of electrical and mechanical signals in neural tissue. This technology could reveal the relationship between the electrical activity of neurons and their local mechanical environment, which is critical to the study of mechanoreceptors, neural development, and traumatic brain injury. Chapter 5 describes advances in the development, fabrication, and testing of a prototype silicon micropipette for patch clamp physiology. Nanoscale photolithography addresses some of the limitations of traditional glass patch electrodes, such as the rapid dialysis of the cell with internal solution, and provides a platform for integration of microfluidics and electronics into the device, which can enable novel experimental methodology.

Nonequilibrium Quantum Simulation in Circuit QED

NASA Astrophysics Data System (ADS)

Raftery, James John

Superconducting circuits have become a leading architecture for quantum computing and quantum simulation. In particular, the circuit QED framework leverages high coherence qubits and microwave resonators to construct systems realizing quantum optics models with exquisite precision. For example, the Jaynes-Cummings model has been the focus of significant theoretical interest as a means of generating photon-photon interactions. Lattices of such strongly correlated photons are an exciting new test bed for exploring non-equilibrium condensed matter physics such as dissipative phase transitions of light. This thesis covers a series of experiments which establish circuit QED as a powerful tool for exploring condensed matter physics with photons. The first experiment explores the use of ultra high speed arbitrary waveform generators for the direct digital synthesis of complex microwave waveforms. This new technique dramatically simplifies the classical control chain for quantum experiments and enables high bandwidth driving schemes expected to be essential for generating interesting steady-states and dynamical behavior. The last two experiments explore the rich physics of interacting photons, with an emphasis on small systems where a high degree of control is possible. The first experiment realizes a two-site system called the Jaynes-Cummings dimer, which undergoes a self-trapping transition where the strong photon-photon interactions block photon hopping between sites. The observation of this dynamical phase transition and the related dissipation-induced transition are key results of this thesis. The final experiment augments the Jaynes-Cummings dimer by redesigning the circuit to include in-situ control over photon hopping between sites using a tunable coupler. This enables the study of the dimer's localization transition in the steady-state regime.

Neuronal correlates of decisions to speak and act: Spontaneous emergence and dynamic topographies in a computational model of frontal and temporal areas

PubMed Central

Garagnani, Max; Pulvermüller, Friedemann

2013-01-01

The neural mechanisms underlying the spontaneous, stimulus-independent emergence of intentions and decisions to act are poorly understood. Using a neurobiologically realistic model of frontal and temporal areas of the brain, we simulated the learning of perception–action circuits for speech and hand-related actions and subsequently observed their spontaneous behaviour. Noise-driven accumulation of reverberant activity in these circuits leads to their spontaneous ignition and partial-to-full activation, which we interpret, respectively, as model correlates of action intention emergence and action decision-and-execution. Importantly, activity emerged first in higher-association prefrontal and temporal cortices, subsequently spreading to secondary and finally primary sensorimotor model-areas, hence reproducing the dynamics of cortical correlates of voluntary action revealed by readiness-potential and verb-generation experiments. This model for the first time explains the cortical origins and topography of endogenous action decisions, and the natural emergence of functional specialisation in the cortex, as mechanistic consequences of neurobiological principles, anatomical structure and sensorimotor experience. PMID:23489583

Neural dynamics in Parkinsonian brain: The boundary between synchronized and nonsynchronized dynamics

NASA Astrophysics Data System (ADS)

Park, Choongseok; Worth, Robert M.; Rubchinsky, Leonid L.

2011-04-01

Synchronous oscillatory dynamics is frequently observed in the human brain. We analyze the fine temporal structure of phase-locking in a realistic network model and match it with the experimental data from Parkinsonian patients. We show that the experimentally observed intermittent synchrony can be generated just by moderately increased coupling strength in the basal ganglia circuits due to the lack of dopamine. Comparison of the experimental and modeling data suggest that brain activity in Parkinson's disease resides in the large boundary region between synchronized and nonsynchronized dynamics. Being on the edge of synchrony may allow for easy formation of transient neuronal assemblies.

Quantum networks in divergence-free circuit QED

NASA Astrophysics Data System (ADS)

Parra-Rodriguez, A.; Rico, E.; Solano, E.; Egusquiza, I. L.

2018-04-01

Superconducting circuits are one of the leading quantum platforms for quantum technologies. With growing system complexity, it is of crucial importance to develop scalable circuit models that contain the minimum information required to predict the behaviour of the physical system. Based on microwave engineering methods, divergent and non-divergent Hamiltonian models in circuit quantum electrodynamics have been proposed to explain the dynamics of superconducting quantum networks coupled to infinite-dimensional systems, such as transmission lines and general impedance environments. Here, we study systematically common linear coupling configurations between networks and infinite-dimensional systems. The main result is that the simple Lagrangian models for these configurations present an intrinsic natural length that provides a natural ultraviolet cutoff. This length is due to the unavoidable dressing of the environment modes by the network. In this manner, the coupling parameters between their components correctly manifest their natural decoupling at high frequencies. Furthermore, we show the requirements to correctly separate infinite-dimensional coupled systems in local bases. We also compare our analytical results with other analytical and approximate methods available in the literature. Finally, we propose several applications of these general methods to analogue quantum simulation of multi-spin-boson models in non-perturbative coupling regimes.

Combining a Toggle Switch and a Repressilator within the AC-DC Circuit Generates Distinct Dynamical Behaviors.

PubMed

Perez-Carrasco, Ruben; Barnes, Chris P; Schaerli, Yolanda; Isalan, Mark; Briscoe, James; Page, Karen M

2018-04-25

Although the structure of a genetically encoded regulatory circuit is an important determinant of its function, the relationship between circuit topology and the dynamical behaviors it can exhibit is not well understood. Here, we explore the range of behaviors available to the AC-DC circuit. This circuit consists of three genes connected as a combination of a toggle switch and a repressilator. Using dynamical systems theory, we show that the AC-DC circuit exhibits both oscillations and bistability within the same region of parameter space; this generates emergent behaviors not available to either the toggle switch or the repressilator alone. The AC-DC circuit can switch on oscillations via two distinct mechanisms, one of which induces coherence into ensembles of oscillators. In addition, we show that in the presence of noise, the AC-DC circuit can behave as an excitable system capable of spatial signal propagation or coherence resonance. Together, these results demonstrate how combinations of simple motifs can exhibit multiple complex behaviors. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Comparison of in-situ delay monitors for use in Adaptive Voltage Scaling

NASA Astrophysics Data System (ADS)

Pour Aryan, N.; Heiß, L.; Schmitt-Landsiedel, D.; Georgakos, G.; Wirnshofer, M.

2012-09-01

In Adaptive Voltage Scaling (AVS) the supply voltage of digital circuits is tuned according to the circuit's actual operating condition, which enables dynamic compensation to PVTA variations. By exploiting the excessive safety margins added in state-of-the-art worst-case designs considerable power saving is achieved. In our approach, the operating condition of the circuit is monitored by in-situ delay monitors. This paper presents different designs to implement the in-situ delay monitors capable of detecting late but still non-erroneous transitions, called Pre-Errors. The developed Pre-Error monitors are integrated in a 16 bit multiplier test circuit and the resulting Pre-Error AVS system is modeled by a Markov chain in order to determine the power saving potential of each Pre-Error detection approach.

A tweaking principle for executive control: neuronal circuit mechanism for rule-based task switching and conflict resolution.

PubMed

Ardid, Salva; Wang, Xiao-Jing

2013-12-11

A hallmark of executive control is the brain's agility to shift between different tasks depending on the behavioral rule currently in play. In this work, we propose a "tweaking hypothesis" for task switching: a weak rule signal provides a small bias that is dramatically amplified by reverberating attractor dynamics in neural circuits for stimulus categorization and action selection, leading to an all-or-none reconfiguration of sensory-motor mapping. Based on this principle, we developed a biologically realistic model with multiple modules for task switching. We found that the model quantitatively accounts for complex task switching behavior: switch cost, congruency effect, and task-response interaction; as well as monkey's single-neuron activity associated with task switching. The model yields several testable predictions, in particular, that category-selective neurons play a key role in resolving sensory-motor conflict. This work represents a neural circuit model for task switching and sheds insights in the brain mechanism of a fundamental cognitive capability.

Design of a biochemical circuit motif for learning linear functions

PubMed Central

Lakin, Matthew R.; Minnich, Amanda; Lane, Terran; Stefanovic, Darko

2014-01-01

Learning and adaptive behaviour are fundamental biological processes. A key goal in the field of bioengineering is to develop biochemical circuit architectures with the ability to adapt to dynamic chemical environments. Here, we present a novel design for a biomolecular circuit capable of supervised learning of linear functions, using a model based on chemical reactions catalysed by DNAzymes. To achieve this, we propose a novel mechanism of maintaining and modifying internal state in biochemical systems, thereby advancing the state of the art in biomolecular circuit architecture. We use simulations to demonstrate that the circuit is capable of learning behaviour and assess its asymptotic learning performance, scalability and robustness to noise. Such circuits show great potential for building autonomous in vivo nanomedical devices. While such a biochemical system can tell us a great deal about the fundamentals of learning in living systems and may have broad applications in biomedicine (e.g. autonomous and adaptive drugs), it also offers some intriguing challenges and surprising behaviours from a machine learning perspective. PMID:25401175

Design of a biochemical circuit motif for learning linear functions.

PubMed

Lakin, Matthew R; Minnich, Amanda; Lane, Terran; Stefanovic, Darko

2014-12-06

Learning and adaptive behaviour are fundamental biological processes. A key goal in the field of bioengineering is to develop biochemical circuit architectures with the ability to adapt to dynamic chemical environments. Here, we present a novel design for a biomolecular circuit capable of supervised learning of linear functions, using a model based on chemical reactions catalysed by DNAzymes. To achieve this, we propose a novel mechanism of maintaining and modifying internal state in biochemical systems, thereby advancing the state of the art in biomolecular circuit architecture. We use simulations to demonstrate that the circuit is capable of learning behaviour and assess its asymptotic learning performance, scalability and robustness to noise. Such circuits show great potential for building autonomous in vivo nanomedical devices. While such a biochemical system can tell us a great deal about the fundamentals of learning in living systems and may have broad applications in biomedicine (e.g. autonomous and adaptive drugs), it also offers some intriguing challenges and surprising behaviours from a machine learning perspective.

Overbias light emission due to higher-order quantum noise in a tunnel junction.

PubMed

Xu, F; Holmqvist, C; Belzig, W

2014-08-08

Understanding tunneling from an atomically sharp tip to a metallic surface requires us to account for interactions on a nanoscopic scale. Inelastic tunneling of electrons generates emission of photons, whose energies intuitively should be limited by the applied bias voltage. However, experiments [G. Schull et al., Phys. Rev. Lett. 102, 057401 (2009) indicate that more complex processes involving the interaction of electrons with plasmon polaritons lead to photon emission characterized by overbias energies. We propose a model of this observation in analogy to the dynamical Coulomb blockade, originally developed for treating the electronic environment in mesoscopic circuits. We explain the experimental finding quantitatively by the correlated tunneling of two electrons interacting with a LRC circuit modeling the local plasmon-polariton mode. To explain the overbias emission, the non-Gaussian statistics of the tunneling dynamics of the electrons is essential.

Classical analogs for Rabi-oscillations, Ramsey-fringes, and spin-echo in Josephson junctions

NASA Astrophysics Data System (ADS)

Marchese, J. E.; Cirillo, M.; Grønbech-Jensen, N.

2007-08-01

We investigate the results of recently published experiments on the quantum behavior of Josephson circuits in terms of the classical modeling based on the resistively and capacitively-shunted (RCSJ) junction model. Our analysis shows evidence for a close analogy between the nonlinear behavior of a pulsed microwave-driven Josephson junction at low temperature and low dissipation and the experimental observations reported for the Josephson circuits. Specifically, we demonstrate that Rabi-oscillations, Ramsey-fringes, and spin-echo observations are not phenomena with a unique quantum interpretation. In fact, they are natural consequences of transients to phase-locking in classical nonlinear dynamics and can be observed in a purely classical model of a Josephson junction when the experimental recipe for the application of microwaves is followed and the experimental detection scheme followed. We therefore conclude that classical nonlinear dynamics can contribute to the understanding of relevant experimental observations of Josephson response to various microwave perturbations at very low temperature and low dissipation.

Computer simulations of stimulus dependent state switching in basic circuits of bursting neurons

NASA Astrophysics Data System (ADS)

Rabinovich, Mikhail; Huerta, Ramón; Bazhenov, Maxim; Kozlov, Alexander K.; Abarbanel, Henry D. I.

1998-11-01

We investigate the ability of oscillating neural circuits to switch between different states of oscillation in two basic neural circuits. We model two quite distinct small neural circuits. The first circuit is based on invertebrate central pattern generator (CPG) studies [A. I. Selverston and M. Moulins, The Crustacean Stomatogastric System (Springer-Verlag, Berlin, 1987)] and is composed of two neurons coupled via both gap junction and inhibitory synapses. The second consists of coupled pairs of interconnected thalamocortical relay and thalamic reticular neurons with both inhibitory and excitatory synaptic coupling. The latter is an elementary unit of the thalamic networks passing sensory information to the cerebral cortex [M. Steriade, D. A. McCormick, and T. J. Sejnowski, Science 262, 679 (1993)]. Both circuits have contradictory coupling between symmetric parts. The thalamocortical model has excitatory and inhibitory connections and the CPG has reciprocal inhibitory and electrical coupling. We describe the dynamics of the individual neurons in these circuits by conductance based ordinary differential equations of Hodgkin-Huxley type [J. Physiol. (London) 117, 500 (1952)]. Both model circuits exhibit bistability and hysteresis in a wide region of coupling strengths. The two main modes of behavior are in-phase and out-of-phase oscillations of the symmetric parts of the network. We investigate the response of these circuits, while they are operating in bistable regimes, to externally imposed excitatory spike trains with varying interspike timing and small amplitude pulses. These are meant to represent spike trains received by the basic circuits from sensory neurons. Circuits operating in a bistable region are sensitive to the frequency of these excitatory inputs. Frequency variations lead to changes from in-phase to out-of-phase coordination or vice versa. The signaling information contained in a spike train driving the network can place the circuit into one or another state depending on the interspike interval and this happens within a few spikes. These states are maintained by the basic circuit after the input signal is ended. When a new signal of the correct frequency enters the circuit, it can be switched to another state with the same ease.

Digital Quantum Simulation of Minimal AdS/CFT.

PubMed

García-Álvarez, L; Egusquiza, I L; Lamata, L; Del Campo, A; Sonner, J; Solano, E

2017-07-28

We propose the digital quantum simulation of a minimal AdS/CFT model in controllable quantum platforms. We consider the Sachdev-Ye-Kitaev model describing interacting Majorana fermions with randomly distributed all-to-all couplings, encoding nonlocal fermionic operators onto qubits to efficiently implement their dynamics via digital techniques. Moreover, we also give a method for probing nonequilibrium dynamics and the scrambling of information. Finally, our approach serves as a protocol for reproducing a simplified low-dimensional model of quantum gravity in advanced quantum platforms as trapped ions and superconducting circuits.

Digital Quantum Simulation of Minimal AdS /CFT

NASA Astrophysics Data System (ADS)

García-Álvarez, L.; Egusquiza, I. L.; Lamata, L.; del Campo, A.; Sonner, J.; Solano, E.

2017-07-01

We propose the digital quantum simulation of a minimal AdS /CFT model in controllable quantum platforms. We consider the Sachdev-Ye-Kitaev model describing interacting Majorana fermions with randomly distributed all-to-all couplings, encoding nonlocal fermionic operators onto qubits to efficiently implement their dynamics via digital techniques. Moreover, we also give a method for probing nonequilibrium dynamics and the scrambling of information. Finally, our approach serves as a protocol for reproducing a simplified low-dimensional model of quantum gravity in advanced quantum platforms as trapped ions and superconducting circuits.

A neural circuit transforming temporal periodicity information into a rate-based representation in the mammalian auditory system.

PubMed

Dicke, Ulrike; Ewert, Stephan D; Dau, Torsten; Kollmeier, Birger

2007-01-01

Periodic amplitude modulations (AMs) of an acoustic stimulus are presumed to be encoded in temporal activity patterns of neurons in the cochlear nucleus. Physiological recordings indicate that this temporal AM code is transformed into a rate-based periodicity code along the ascending auditory pathway. The present study suggests a neural circuit for the transformation from the temporal to the rate-based code. Due to the neural connectivity of the circuit, bandpass shaped rate modulation transfer functions are obtained that correspond to recorded functions of inferior colliculus (IC) neurons. In contrast to previous modeling studies, the present circuit does not employ a continuously changing temporal parameter to obtain different best modulation frequencies (BMFs) of the IC bandpass units. Instead, different BMFs are yielded from varying the number of input units projecting onto different bandpass units. In order to investigate the compatibility of the neural circuit with a linear modulation filterbank analysis as proposed in psychophysical studies, complex stimuli such as tones modulated by the sum of two sinusoids, narrowband noise, and iterated rippled noise were processed by the model. The model accounts for the encoding of AM depth over a large dynamic range and for modulation frequency selective processing of complex sounds.

Cycle-averaged dynamics of a periodically driven, closed-loop circulation model

NASA Technical Reports Server (NTRS)

Heldt, T.; Chang, J. L.; Chen, J. J. S.; Verghese, G. C.; Mark, R. G.

2005-01-01

Time-varying elastance models have been used extensively in the past to simulate the pulsatile nature of cardiovascular waveforms. Frequently, however, one is interested in dynamics that occur over longer time scales, in which case a detailed simulation of each cardiac contraction becomes computationally burdensome. In this paper, we apply circuit-averaging techniques to a periodically driven, closed-loop, three-compartment recirculation model. The resultant cycle-averaged model is linear and time invariant, and greatly reduces the computational burden. It is also amenable to systematic order reduction methods that lead to further efficiencies. Despite its simplicity, the averaged model captures the dynamics relevant to the representation of a range of cardiovascular reflex mechanisms. c2004 Elsevier Ltd. All rights reserved.

Validation of computational fluid dynamics-based analysis to evaluate hemodynamic significance of access stenosis.

PubMed

Hoganson, David M; Hinkel, Cameron J; Chen, Xiaomin; Agarwal, Ramesh K; Shenoy, Surendra

2014-01-01

Stenosis in a vascular access circuit is the predominant cause of access dysfunction. Hemodynamic significance of a stenosis identified by angiography in an access circuit is uncertain. This study utilizes computational fluid dynamics (CFD) to model flow through arteriovenous fistula to predict the functional significance of stenosis in vascular access circuits. Three-dimensional models of fistulas were created with a range of clinically relevant stenoses using SolidWorks. Stenoses diameters ranged from 1.0 to 3.0 mm and lengths from 5 to 60 mm within a fistula diameter of 7 mm. CFD analyses were performed using a blood model over a range of blood pressures. Eight patient-specific stenoses were also modeled and analyzed with CFD and the resulting blood flow calculations were validated by comparison with brachial artery flow measured by duplex ultrasound. Predicted flow rates were derived from CFD analysis of a range of stenoses. These stenoses were modeled by CFD and correlated with the ultrasound measured flow rate through the fistula of eight patients. The calculated flow rate using CFD correlated within 20% of ultrasound measured flow for five of eight patients. The mean difference was 17.2% (ranged from 1.3% to 30.1%). CFD analysis-generated flow rate tables provide valuable information to assess the functional significance of stenosis detected during imaging studies. The CFD study can help in determining the clinical relevance of a stenosis in access dysfunction and guide the need for intervention.

On the Influence of the Coupling Strength among Chua’s Circuits on the Structure of Their Hyper-Chaotic Attractors

NASA Astrophysics Data System (ADS)

Freud, Sven; Plaga, Rainer; Breithaupt, Ralph

2016-06-01

The hyper-chaotic strange attractor of systems of four Chua’s circuits that are mutually coupled by three strong and three weak couplings is studied, both experimentally and via simulation. A new metric to compare strange attractors is presented. It is found that the strength of the couplings between circuits have a complex and determining influence on the probability for the presence of a trajectory within their attractors. This influence is strictly local, i.e. the probability of the presence of the trajectories is determined by the coupling strength to the directly adjacent circuits and independent of the coupling strengths among other circuits. Fluctuations in the properties of Chua’s circuits due to random fluctuations during the production of its components have a significant influence on the probability of presence of the attractor’s trajectories that could be qualitatively, but not quantitatively, modeled by our simulation. The consequences of these results for the possibility to construct “physical unclonable functions” as networks of Chua’s circuits with a hyper-chaotic dynamics are discussed.

Social Status-Dependent Shift in Neural Circuit Activation Affects Decision Making.

PubMed

Miller, Thomas H; Clements, Katie; Ahn, Sungwoo; Park, Choongseok; Hye Ji, Eoon; Issa, Fadi A

2017-02-22

In a social group, animals make behavioral decisions that fit their social ranks. These behavioral choices are dependent on the various social cues experienced during social interactions. In vertebrates, little is known of how social status affects the underlying neural mechanisms regulating decision-making circuits that drive competing behaviors. Here, we demonstrate that social status in zebrafish ( Danio rerio ) influences behavioral decisions by shifting the balance in neural circuit activation between two competing networks (escape and swim). We show that socially dominant animals enhance activation of the swim circuit. Conversely, social subordinates display a decreased activation of the swim circuit, but an enhanced activation of the escape circuit. In an effort to understand how social status mediates these effects, we constructed a neurocomputational model of the escape and swim circuits. The model replicates our findings and suggests that social status-related shift in circuit dynamics could be mediated by changes in the relative excitability of the escape and swim networks. Together, our results reveal that changes in the excitabilities of the Mauthner command neuron for escape and the inhibitory interneurons that regulate swimming provide a cellular mechanism for the nervous system to adapt to changes in social conditions by permitting the animal to select a socially appropriate behavioral response. SIGNIFICANCE STATEMENT Understanding how social factors influence nervous system function is of great importance. Using zebrafish as a model system, we demonstrate how social experience affects decision making to enable animals to produce socially appropriate behavior. Based on experimental evidence and computational modeling, we show that behavioral decisions reflect the interplay between competing neural circuits whose activation thresholds shift in accordance with social status. We demonstrate this through analysis of the behavior and neural circuit responses that drive escape and swim behaviors in fish. We show that socially subordinate animals favor escape over swimming, while socially dominants favor swimming over escape. We propose that these differences are mediated by shifts in relative circuit excitability. Copyright © 2017 the authors 0270-6474/17/372137-12$15.00/0.

Dynamic Modeling of Yield and Particle Size Distribution in Continuous Bayer Precipitation

NASA Astrophysics Data System (ADS)

Stephenson, Jerry L.; Kapraun, Chris

Process engineers at Alcoa's Point Comfort refinery are using a dynamic model of the Bayer precipitation area to evaluate options in operating strategies. The dynamic model, a joint development effort between Point Comfort and the Alcoa Technical Center, predicts process yields, particle size distributions and occluded soda levels for various flowsheet configurations of the precipitation and classification circuit. In addition to rigorous heat, material and particle population balances, the model includes mechanistic kinetic expressions for particle growth and agglomeration and semi-empirical kinetics for nucleation and attrition. The kinetic parameters have been tuned to Point Comfort's operating data, with excellent matches between the model results and plant data. The model is written for the ACSL dynamic simulation program with specifically developed input/output graphical user interfaces to provide a user-friendly tool. Features such as a seed charge controller enhance the model's usefulness for evaluating operating conditions and process control approaches.

D-VASim: an interactive virtual laboratory environment for the simulation and analysis of genetic circuits.

PubMed

Baig, Hasan; Madsen, Jan

2017-01-15

Simulation and behavioral analysis of genetic circuits is a standard approach of functional verification prior to their physical implementation. Many software tools have been developed to perform in silico analysis for this purpose, but none of them allow users to interact with the model during runtime. The runtime interaction gives the user a feeling of being in the lab performing a real world experiment. In this work, we present a user-friendly software tool named D-VASim (Dynamic Virtual Analyzer and Simulator), which provides a virtual laboratory environment to simulate and analyze the behavior of genetic logic circuit models represented in an SBML (Systems Biology Markup Language). Hence, SBML models developed in other software environments can be analyzed and simulated in D-VASim. D-VASim offers deterministic as well as stochastic simulation; and differs from other software tools by being able to extract and validate the Boolean logic from the SBML model. D-VASim is also capable of analyzing the threshold value and propagation delay of a genetic circuit model. D-VASim is available for Windows and Mac OS and can be downloaded from bda.compute.dtu.dk/downloads/. haba@dtu.dk, jama@dtu.dk. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Spatial gradients and multidimensional dynamics in a neural integrator circuit

PubMed Central

Miri, Andrew; Daie, Kayvon; Arrenberg, Aristides B.; Baier, Herwig; Aksay, Emre; Tank, David W.

2011-01-01

In a neural integrator, the variability and topographical organization of neuronal firing rate persistence can provide information about the circuit’s functional architecture. Here we use optical recording to measure the time constant of decay of persistent firing (“persistence time”) across a population of neurons comprising the larval zebrafish oculomotor velocity-to-position neural integrator. We find extensive persistence time variation (10-fold; coefficients of variation 0.58–1.20) across cells within individual larvae. We also find that the similarity in firing between two neurons decreased as the distance between them increased and that a gradient in persistence time was mapped along the rostrocaudal and dorsoventral axes. This topography is consistent with the emergence of persistence time heterogeneity from a circuit architecture in which nearby neurons are more strongly interconnected than distant ones. Collectively, our results can be accounted for by integrator circuit models characterized by multiple dimensions of slow firing rate dynamics. PMID:21857656

The circuit parameters measurement of the SABALAN-I plasma focus facility and comparison with Lee Model

NASA Astrophysics Data System (ADS)

Karimi, F. S.; Saviz, S.; Ghoranneviss, M.; Salem, M. K.; Aghamir, F. M.

The circuit parameters are investigated in a Mather-type plasma focus device. The experiments are performed in the SABALAN-I plasma focus facility (2 kJ, 20 kV, 10 μF). A 12-turn Rogowski coil is built and used to measure the time derivative of discharge current (dI/dt). The high pressure test has been performed in this work, as alternative technique to short circuit test to determine the machine circuit parameters and calibration factor of the Rogowski coil. The operating parameters are calculated by two methods and the results show that the relative error of determined parameters by method I, are very low in comparison to method II. Thus the method I produces more accurate results than method II. The high pressure test is operated with this assumption that no plasma motion and the circuit parameters may be estimated using R-L-C theory given that C0 is known. However, for a plasma focus, even at highest permissible pressure it is found that there is significant motion, so that estimated circuit parameters not accurate. So the Lee Model code is used in short circuit mode to generate the computed current trace for fitting to the current waveform was integrated from current derivative signal taken with Rogowski coil. Hence, the dynamics of plasma is accounted for into the estimation and the static bank parameters are determined accurately.

Functional identification of spike-processing neural circuits.

PubMed

Lazar, Aurel A; Slutskiy, Yevgeniy B

2014-02-01

We introduce a novel approach for a complete functional identification of biophysical spike-processing neural circuits. The circuits considered accept multidimensional spike trains as their input and comprise a multitude of temporal receptive fields and conductance-based models of action potential generation. Each temporal receptive field describes the spatiotemporal contribution of all synapses between any two neurons and incorporates the (passive) processing carried out by the dendritic tree. The aggregate dendritic current produced by a multitude of temporal receptive fields is encoded into a sequence of action potentials by a spike generator modeled as a nonlinear dynamical system. Our approach builds on the observation that during any experiment, an entire neural circuit, including its receptive fields and biophysical spike generators, is projected onto the space of stimuli used to identify the circuit. Employing the reproducing kernel Hilbert space (RKHS) of trigonometric polynomials to describe input stimuli, we quantitatively describe the relationship between underlying circuit parameters and their projections. We also derive experimental conditions under which these projections converge to the true parameters. In doing so, we achieve the mathematical tractability needed to characterize the biophysical spike generator and identify the multitude of receptive fields. The algorithms obviate the need to repeat experiments in order to compute the neurons' rate of response, rendering our methodology of interest to both experimental and theoretical neuroscientists.

A new 4-D chaotic hyperjerk system, its synchronization, circuit design and applications in RNG, image encryption and chaos-based steganography

NASA Astrophysics Data System (ADS)

Vaidyanathan, S.; Akgul, A.; Kaçar, S.; Çavuşoğlu, U.

2018-02-01

Hyperjerk systems have received significant interest in the literature because of their simple structure and complex dynamical properties. This work presents a new chaotic hyperjerk system having two exponential nonlinearities. Dynamical properties of the chaotic hyperjerk system are discovered through equilibrium point analysis, bifurcation diagram, dissipativity and Lyapunov exponents. Moreover, an adaptive backstepping controller is designed for the synchronization of the chaotic hyperjerk system. Also, a real circuit of the chaotic hyperjerk system has been carried out to show the feasibility of the theoretical hyperjerk model. The chaotic hyperjerk system can also be useful in scientific fields such as Random Number Generators (RNGs), data security, data hiding, etc. In this work, three implementations of the chaotic hyperjerk system, viz. RNG, image encryption and sound steganography have been performed by using complex dynamics characteristics of the system.

Combining dynamical decoupling with fault-tolerant quantum computation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ng, Hui Khoon; Preskill, John; Lidar, Daniel A.

2011-07-15

We study how dynamical decoupling (DD) pulse sequences can improve the reliability of quantum computers. We prove upper bounds on the accuracy of DD-protected quantum gates and derive sufficient conditions for DD-protected gates to outperform unprotected gates. Under suitable conditions, fault-tolerant quantum circuits constructed from DD-protected gates can tolerate stronger noise and have a lower overhead cost than fault-tolerant circuits constructed from unprotected gates. Our accuracy estimates depend on the dynamics of the bath that couples to the quantum computer and can be expressed either in terms of the operator norm of the bath's Hamiltonian or in terms of themore » power spectrum of bath correlations; we explain in particular how the performance of recursively generated concatenated pulse sequences can be analyzed from either viewpoint. Our results apply to Hamiltonian noise models with limited spatial correlations.« less

Mixed Signal Learning by Spike Correlation Propagation in Feedback Inhibitory Circuits

PubMed Central

Hiratani, Naoki; Fukai, Tomoki

2015-01-01

The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP) is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits; however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning algorithm such circuits achieve. We derive analytical conditions at which neurons detect minor signals with STDP, and show that depending on the origin of the noise, different correlation timescales are useful for learning. In particular, we show that non-precise spike correlation is beneficial for learning in the presence of cross-talk noise. We also show that by considering excitatory and inhibitory STDP at lateral connections, the circuit can acquire a lateral structure optimal for signal detection. In addition, we demonstrate that the model performs blind source separation in a manner similar to the sequential sampling approximation of the Bayesian independent component analysis algorithm. Our results provide a basic understanding of STDP learning in feedback circuits by integrating analyses from both dynamical systems and information theory. PMID:25910189

Measuring circuit

DOEpatents

Sun, Shan C.; Chaprnka, Anthony G.

1977-01-11

An automatic gain control circuit functions to adjust the magnitude of an input signal supplied to a measuring circuit to a level within the dynamic range of the measuring circuit while a log-ratio circuit adjusts the magnitude of the output signal from the measuring circuit to the level of the input signal and optimizes the signal-to-noise ratio performance of the measuring circuit.

Comparative study of diastolic filling under varying left ventricular wall stiffness

NASA Astrophysics Data System (ADS)

Mekala, Pritam; Santhanakrishnan, Arvind

2014-11-01

Pathological remodeling of the human cardiac left ventricle (LV) is observed in hypertensive heart failure as a result of pressure overload. Myocardial stiffening occurs in these patients prior to chronic maladaptive changes, resulting in increased LV wall stiffness. The goal of this study was to investigate the change in intraventricular filling fluid dynamics inside a physical model of the LV as a function of wall stiffness. Three LV models of varying wall stiffness were incorporated into an in vitro flow circuit driven by a programmable piston pump. Windkessel elements were used to tune the inflow and systemic pressure in the model with least stiffness to match healthy conditions. Models with stiffer walls were comparatively tested maintaining circuit compliance, resistance and pump amplitude constant. 2D phase-locked PIV measurements along the central plane showed that with increase in wall stiffness, the peak velocity and cardiac output inside the LV decreased. Further, inflow vortex ring propagation toward the LV apex was reduced with increasing stiffness. The above findings indicate the importance of considering LV wall relaxation characteristics in pathological studies of filling fluid dynamics.

Circuit models and three-dimensional electromagnetic simulations of a 1-MA linear transformer driver stage

NASA Astrophysics Data System (ADS)

Rose, D. V.; Miller, C. L.; Welch, D. R.; Clark, R. E.; Madrid, E. A.; Mostrom, C. B.; Stygar, W. A.; Lechien, K. R.; Mazarakis, M. A.; Langston, W. L.; Porter, J. L.; Woodworth, J. R.

2010-09-01

A 3D fully electromagnetic (EM) model of the principal pulsed-power components of a high-current linear transformer driver (LTD) has been developed. LTD systems are a relatively new modular and compact pulsed-power technology based on high-energy density capacitors and low-inductance switches located within a linear-induction cavity. We model 1-MA, 100-kV, 100-ns rise-time LTD cavities [A. A. Kim , Phys. Rev. ST Accel. Beams 12, 050402 (2009)PRABFM1098-440210.1103/PhysRevSTAB.12.050402] which can be used to drive z-pinch and material dynamics experiments. The model simulates the generation and propagation of electromagnetic power from individual capacitors and triggered gas switches to a radially symmetric output line. Multiple cavities, combined to provide voltage addition, drive a water-filled coaxial transmission line. A 3D fully EM model of a single 1-MA 100-kV LTD cavity driving a simple resistive load is presented and compared to electrical measurements. A new model of the current loss through the ferromagnetic cores is developed for use both in circuit representations of an LTD cavity and in the 3D EM simulations. Good agreement between the measured core current, a simple circuit model, and the 3D simulation model is obtained. A 3D EM model of an idealized ten-cavity LTD accelerator is also developed. The model results demonstrate efficient voltage addition when driving a matched impedance load, in good agreement with an idealized circuit model.

Generation of electromagnetic energy in a magnetic cumulation generator with the use of inductively coupled circuits with a variable coupling coefficient

NASA Astrophysics Data System (ADS)

Gilev, S. D.; Prokopiev, V. S.

2017-07-01

A method of generation of electromagnetic energy and magnetic flux in a magnetic cumulation generator is proposed. The method is based on dynamic variation of the circuit coupling coefficient. This circuit is compared with other available circuits of magnetic energy generation with the help of magnetic cumulation (classical magnetic cumulation generator, generator with transformer coupling, and generator with a dynamic transformer). It is demonstrated that the proposed method allows obtaining high values of magnetic energy. The proposed circuit is found to be more effective than the known transformer circuit. Experiments on electromagnetic energy generation are performed, which demonstrate the efficiency of the proposed method.

Experimentally simulating the dynamics of quantum light and matter at ultrastrong coupling using circuit QED (2) - light dynamics and light-matter entanglement -

NASA Astrophysics Data System (ADS)

Sagastizabal, R.; Langford, N. K.; Kounalakis, M.; Dickel, C.; Bruno, A.; Luthi, F.; Thoen, D. J.; Endo, A.; Dicarlo, L.

Light-matter interaction can lead to large photon build-up and hybrid atom-photon entanglement in the ultrastrong coupling (USC) regime, where the coupling strength becomes comparable to the eigenenergies of the system. Accessing the cavity degree of freedom, however, is an outstanding challenge in natural USC systems. In this talk, we directly probe light field dynamics in the USC regime using a digital simulation of the quantum Rabi model in a planar circuit QED chip with a transmon moderately coupled to a resonator. We produce high-accuracy USC light-matter dynamics, using second-order Trotterisation and up to 90 Trotter steps. We probe the average photon number, photon parity and perform Wigner tomography of the simulated field. Finally, we combine tomography of the resonator with qubit measurements to evidence the Schrödinger-cat-like atom-photon entanglement which is a key signature of light-matter dynamics in the USC regime. Funding from the EU FP7 Project ScaleQIT, the ERC Synergy Grant QC-lab, the Netherlands Organization of Scientic Research (NWO), and Microsoft Research.

A low cost, modular, and physiologically inspired electronic neuron

NASA Astrophysics Data System (ADS)

Sitt, J. D.; Campetella, F.; Aliaga, J.

2010-12-01

We describe a low cost design of an electronic neuron, which is designed to represent the dynamical properties of the membrane potential of biological neurons by modeling the states of the membrane channels. This electronic neuron can be used to study the nonlinear properties of the membrane voltage dynamics and to develop and analyze small neuronal circuits using electronic neurons as building blocks.

Design and use of multisine signals for Li-ion battery equivalent circuit modelling. Part 1: Signal design

NASA Astrophysics Data System (ADS)

Widanage, W. D.; Barai, A.; Chouchelamane, G. H.; Uddin, K.; McGordon, A.; Marco, J.; Jennings, P.

2016-08-01

The Pulse Power Current (PPC) profile is often the signal of choice for obtaining the parameters of a Lithium-ion (Li-ion) battery Equivalent Circuit Model (ECM). Subsequently, a drive-cycle current profile is used as a validation signal. Such a profile, in contrast to a PPC, is more dynamic in both the amplitude and frequency bandwidth. Modelling errors can occur when using PPC data for parametrisation since the model is optimised over a narrower bandwidth than the validation profile. A signal more representative of a drive-cycle, while maintaining a degree of generality, is needed to reduce such modelling errors. In Part 1 of this 2-part paper a signal design technique defined as a pulse-multisine is presented. This superimposes a signal known as a multisine to a discharge, rest and charge base signal to achieve a profile more dynamic in amplitude and frequency bandwidth, and thus more similar to a drive-cycle. The signal improves modelling accuracy and reduces the experimentation time, per state-of-charge (SoC) and temperature, to several minutes compared to several hours for an PPC experiment.

Computational Validation of a Two-Dimensional Semi-Empirical Model for Inductive Coupling in a Conical Pulsed Inductive Plasma Thruster

NASA Technical Reports Server (NTRS)

Hallock, Ashley K.; Polzin, Kurt A.

2011-01-01

A two-dimensional semi-empirical model of pulsed inductive thrust efficiency is developed to predict the effect of such a geometry on thrust efficiency. The model includes electromagnetic and gas-dynamic forces but excludes energy conversion from radial motion to axial motion, with the intention of characterizing thrust efficiency loss mechanisms that result from a conical versus a at inductive coil geometry. The range of conical pulsed inductive thruster geometries to which this model can be applied is explored with the use of finite element analysis. A semi-empirical relation for inductance as a function of current sheet radial and axial position is the limiting feature of the model, restricting the applicability as a function of half cone angle to a range from ten degrees to about 60 degrees. The model is nondimensionalized, yielding a set of dimensionless performance scaling parameters. Results of the model indicate that radial current sheet motion changes the axial dynamic impedance parameter at which thrust efficiency is maximized. This shift indicates that when radial current sheet motion is permitted in the model longer characteristic circuit timescales are more efficient, which can be attributed to a lower current sheet axial velocity as the plasma more rapidly decouples from the coil through radial motion. Thrust efficiency is shown to increase monotonically for decreasing values of the radial dynamic impedance parameter. This trend indicates that to maximize the radial decoupling timescale should be long compared to the characteristic circuit timescale.

Periodicity, chaos, and multiple attractors in a memristor-based Shinriki's circuit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kengne, J.; Njitacke Tabekoueng, Z.; Kamdoum Tamba, V.

2015-10-15

In this contribution, a novel memristor-based oscillator, obtained from Shinriki's circuit by substituting the nonlinear positive conductance with a first order memristive diode bridge, is introduced. The model is described by a continuous time four-dimensional autonomous system with smooth nonlinearities. The basic dynamical properties of the system are investigated including equilibria and stability, phase portraits, frequency spectra, bifurcation diagrams, and Lyapunov exponents' spectrum. It is found that in addition to the classical period-doubling and symmetry restoring crisis scenarios reported in the original circuit, the memristor-based oscillator experiences the unusual and striking feature of multiple attractors (i.e., coexistence of a pairmore » of asymmetric periodic attractors with a pair of asymmetric chaotic ones) over a broad range of circuit parameters. Results of theoretical analyses are verified by laboratory experimental measurements.« less

Synthetic gene circuits for metabolic control: design trade-offs and constraints

PubMed Central

Oyarzún, Diego A.; Stan, Guy-Bart V.

2013-01-01

A grand challenge in synthetic biology is to push the design of biomolecular circuits from purely genetic constructs towards systems that interface different levels of the cellular machinery, including signalling networks and metabolic pathways. In this paper, we focus on a genetic circuit for feedback regulation of unbranched metabolic pathways. The objective of this feedback system is to dampen the effect of flux perturbations caused by changes in cellular demands or by engineered pathways consuming metabolic intermediates. We consider a mathematical model for a control circuit with an operon architecture, whereby the expression of all pathway enzymes is transcriptionally repressed by the metabolic product. We address the existence and stability of the steady state, the dynamic response of the network under perturbations, and their dependence on common tuneable knobs such as the promoter characteristic and ribosome binding site (RBS) strengths. Our analysis reveals trade-offs between the steady state of the enzymes and the intermediates, together with a separation principle between promoter and RBS design. We show that enzymatic saturation imposes limits on the parameter design space, which must be satisfied to prevent metabolite accumulation and guarantee the stability of the network. The use of promoters with a broad dynamic range and a small leaky expression enlarges the design space. Simulation results with realistic parameter values also suggest that the control circuit can effectively upregulate enzyme production to compensate flux perturbations. PMID:23054953

A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses.

PubMed

Qiao, Ning; Mostafa, Hesham; Corradi, Federico; Osswald, Marc; Stefanini, Fabio; Sumislawska, Dora; Indiveri, Giacomo

2015-01-01

Implementing compact, low-power artificial neural processing systems with real-time on-line learning abilities is still an open challenge. In this paper we present a full-custom mixed-signal VLSI device with neuromorphic learning circuits that emulate the biophysics of real spiking neurons and dynamic synapses for exploring the properties of computational neuroscience models and for building brain-inspired computing systems. The proposed architecture allows the on-chip configuration of a wide range of network connectivities, including recurrent and deep networks, with short-term and long-term plasticity. The device comprises 128 K analog synapse and 256 neuron circuits with biologically plausible dynamics and bi-stable spike-based plasticity mechanisms that endow it with on-line learning abilities. In addition to the analog circuits, the device comprises also asynchronous digital logic circuits for setting different synapse and neuron properties as well as different network configurations. This prototype device, fabricated using a 180 nm 1P6M CMOS process, occupies an area of 51.4 mm(2), and consumes approximately 4 mW for typical experiments, for example involving attractor networks. Here we describe the details of the overall architecture and of the individual circuits and present experimental results that showcase its potential. By supporting a wide range of cortical-like computational modules comprising plasticity mechanisms, this device will enable the realization of intelligent autonomous systems with on-line learning capabilities.

A Role of Phase-Resetting in Coordinating Large Scale Neural Networks During Attention and Goal-Directed Behavior

PubMed Central

Voloh, Benjamin; Womelsdorf, Thilo

2016-01-01

Short periods of oscillatory activation are ubiquitous signatures of neural circuits. A broad range of studies documents not only their circuit origins, but also a fundamental role for oscillatory activity in coordinating information transfer during goal directed behavior. Recent studies suggest that resetting the phase of ongoing oscillatory activity to endogenous or exogenous cues facilitates coordinated information transfer within circuits and between distributed brain areas. Here, we review evidence that pinpoints phase resetting as a critical marker of dynamic state changes of functional networks. Phase resets: (1) set a “neural context” in terms of narrow band frequencies that uniquely characterizes the activated circuits; (2) impose coherent low frequency phases to which high frequency activations can synchronize, identifiable as cross-frequency correlations across large anatomical distances; (3) are critical for neural coding models that depend on phase, increasing the informational content of neural representations; and (4) likely originate from the dynamics of canonical E-I circuits that are anatomically ubiquitous. These multiple signatures of phase resets are directly linked to enhanced information transfer and behavioral success. We survey how phase resets re-organize oscillations in diverse task contexts, including sensory perception, attentional stimulus selection, cross-modal integration, Pavlovian conditioning, and spatial navigation. The evidence we consider suggests that phase-resets can drive changes in neural excitability, ensemble organization, functional networks, and ultimately, overt behavior. PMID:27013986

Design and Dynamic Model of a Frog-inspired Swimming Robot Powered by Pneumatic Muscles

NASA Astrophysics Data System (ADS)

Fan, Ji-Zhuang; Zhang, Wei; Kong, Peng-Cheng; Cai, He-Gao; Liu, Gang-Feng

2017-09-01

Pneumatic muscles with similar characteristics to biological muscles have been widely used in robots, and thus are promising drivers for frog inspired robots. However, the application and nonlinearity of the pneumatic system limit the advance. On the basis of the swimming mechanism of the frog, a frog-inspired robot based on pneumatic muscles is developed. To realize the independent tasks by the robot, a pneumatic system with internal chambers, micro air pump, and valves is implemented. The micro pump is used to maintain the pressure difference between the source and exhaust chambers. The pneumatic muscles are controlled by high-speed switch valves which can reduce the robot cost, volume, and mass. A dynamic model of the pneumatic system is established for the simulation to estimate the system, including the chamber, muscle, and pneumatic circuit models. The robot design is verified by the robot swimming experiments and the dynamic model is verified through the experiments and simulations of the pneumatic system. The simulation results are compared to analyze the functions of the source pressure, internal volume of the muscle, and circuit flow rate which is proved the main factor that limits the response of muscle pressure. The proposed research provides the application of the pneumatic muscles in the frog inspired robot and the pneumatic model to study muscle controller.

Investigating habits: strategies, technologies and models

PubMed Central

Smith, Kyle S.; Graybiel, Ann M.

2014-01-01

Understanding habits at a biological level requires a combination of behavioral observations and measures of ongoing neural activity. Theoretical frameworks as well as definitions of habitual behaviors emerging from classic behavioral research have been enriched by new approaches taking account of the identification of brain regions and circuits related to habitual behavior. Together, this combination of experimental and theoretical work has provided key insights into how brain circuits underlying action-learning and action-selection are organized, and how a balance between behavioral flexibility and fixity is achieved. New methods to monitor and manipulate neural activity in real time are allowing us to have a first look “under the hood” of a habit as it is formed and expressed. Here we discuss ideas emerging from such approaches. We pay special attention to the unexpected findings that have arisen from our own experiments suggesting that habitual behaviors likely require the simultaneous activity of multiple distinct components, or operators, seen as responsible for the contrasting dynamics of neural activity in both cortico-limbic and sensorimotor circuits recorded concurrently during different stages of habit learning. The neural dynamics identified thus far do not fully meet expectations derived from traditional models of the structure of habits, and the behavioral measures of habits that we have made also are not fully aligned with these models. We explore these new clues as opportunities to refine an understanding of habits. PMID:24574988

SNDR Limits of Oscillator-Based Sensor Readout Circuits

PubMed Central

Buffa, Cesare; Wiesbauer, Andreas; Hernandez, Luis

2018-01-01

This paper analyzes the influence of phase noise and distortion on the performance of oscillator-based sensor data acquisition systems. Circuit noise inherent to the oscillator circuit manifests as phase noise and limits the SNR. Moreover, oscillator nonlinearity generates distortion for large input signals. Phase noise analysis of oscillators is well known in the literature, but the relationship between phase noise and the SNR of an oscillator-based sensor is not straightforward. This paper proposes a model to estimate the influence of phase noise in the performance of an oscillator-based system by reflecting the phase noise to the oscillator input. The proposed model is based on periodic steady-state analysis tools to predict the SNR of the oscillator. The accuracy of this model has been validated by both simulation and experiment in a 130 nm CMOS prototype. We also propose a method to estimate the SNDR and the dynamic range of an oscillator-based readout circuit that improves by more than one order of magnitude the simulation time compared to standard time domain simulations. This speed up enables the optimization and verification of this kind of systems with iterative algorithms. PMID:29401646

Modeling the Transitions between Collective and Solitary Migration Phenotypes in Cancer Metastasis

PubMed Central

Huang, Bin; Jolly, Mohit Kumar; Lu, Mingyang; Tsarfaty, Ilan; Ben-Jacob, Eshel; Onuchic, Jose’ N

2015-01-01

Cellular plasticity during cancer metastasis is a major clinical challenge. Two key cellular plasticity mechanisms —Epithelial-to-Mesenchymal Transition (EMT) and Mesenchymal-to-Amoeboid Transition (MAT) – have been carefully investigated individually, yet a comprehensive understanding of their interconnections remains elusive. Previously, we have modeled the dynamics of the core regulatory circuits for both EMT (miR-200/ZEB/miR-34/SNAIL) and MAT (Rac1/RhoA). We now extend our previous work to study the coupling between these two core circuits by considering the two microRNAs (miR-200 and miR-34) as external signals to the core MAT circuit. We show that this coupled circuit enables four different stable steady states (phenotypes) that correspond to hybrid epithelial/mesenchymal (E/M), mesenchymal (M), amoeboid (A) and hybrid amoeboid/mesenchymal (A/M) phenotypes. Our model recapitulates the metastasis-suppressing role of the microRNAs even in the presence of EMT-inducing signals like Hepatocyte Growth Factor (HGF). It also enables mapping the microRNA levels to the transitions among various cell migration phenotypes. Finally, it offers a mechanistic understanding for the observed phenotypic transitions among different cell migration phenotypes, specifically the Collective-to-Amoeboid Transition (CAT). PMID:26627083

A portable expression resource for engineering cross-species genetic circuits and pathways

PubMed Central

Kushwaha, Manish; Salis, Howard M.

2015-01-01

Genetic circuits and metabolic pathways can be reengineered to allow organisms to process signals and manufacture useful chemicals. However, their functions currently rely on organism-specific regulatory parts, fragmenting synthetic biology and metabolic engineering into host-specific domains. To unify efforts, here we have engineered a cross-species expression resource that enables circuits and pathways to reuse the same genetic parts, while functioning similarly across diverse organisms. Our engineered system combines mixed feedback control loops and cross-species translation signals to autonomously self-regulate expression of an orthogonal polymerase without host-specific promoters, achieving nontoxic and tuneable gene expression in diverse Gram-positive and Gram-negative bacteria. Combining 50 characterized system variants with mechanistic modelling, we show how the cross-species expression resource's dynamics, capacity and toxicity are controlled by the control loops' architecture and feedback strengths. We also demonstrate one application of the resource by reusing the same genetic parts to express a biosynthesis pathway in both model and non-model hosts. PMID:26184393

Inhibitory Control in the Cortico-Basal Ganglia-Thalamocortical Loop: Complex Regulation and Interplay with Memory and Decision Processes.

PubMed

Wei, Wei; Wang, Xiao-Jing

2016-12-07

We developed a circuit model of spiking neurons that includes multiple pathways in the basal ganglia (BG) and is endowed with feedback mechanisms at three levels: cortical microcircuit, corticothalamic loop, and cortico-BG-thalamocortical system. We focused on executive control in a stop signal task, which is known to depend on BG across species. The model reproduces a range of experimental observations and shows that the newly discovered feedback projection from external globus pallidus to striatum is crucial for inhibitory control. Moreover, stopping process is enhanced by the cortico-subcortical reverberatory dynamics underlying persistent activity, establishing interdependence between working memory and inhibitory control. Surprisingly, the stop signal reaction time (SSRT) can be adjusted by weights of certain connections but is insensitive to other connections in this complex circuit, suggesting novel circuit-based intervention for inhibitory control deficits associated with mental illness. Our model provides a unified framework for inhibitory control, decision making, and working memory. Copyright © 2016 Elsevier Inc. All rights reserved.

Clinically Anxious Individuals Show Disrupted Feedback between Inferior Frontal Gyrus and Prefrontal-Limbic Control Circuit.

PubMed

Cha, Jiook; DeDora, Daniel; Nedic, Sanja; Ide, Jaime; Greenberg, Tsafrir; Hajcak, Greg; Mujica-Parodi, Lilianne Rivka

2016-04-27

Clinical anxiety is associated with generalization of conditioned fear, in which innocuous stimuli elicit alarm. Using Pavlovian fear conditioning (electric shock), we quantify generalization as the degree to which subjects' neurobiological responses track perceptual similarity gradients to a conditioned stimulus. Previous studies show that the ventromedial prefrontal cortex (vmPFC) inversely and ventral tegmental area directly track the gradient of perceptual similarity to the conditioned stimulus in healthy individuals, whereas clinically anxious individuals fail to discriminate. Here, we extend this work by identifying specific functional roles within the prefrontal-limbic circuit. We analyzed fMRI time-series acquired from 57 human subjects during a fear generalization task using entropic measures of circuit-wide regulation and feedback (power spectrum scale invariance/autocorrelation), in combination with structural (diffusion MRI-probabilistic tractography) and functional (stochastic dynamic causal modeling) measures of prefrontal-limbic connectivity within the circuit. Group comparison and correlations with anxiety severity across 57 subjects revealed dysregulatory dynamic signatures within the inferior frontal gyrus (IFG), which our prior work has linked to impaired feedback within the circuit. Bayesian model selection then identified a fully connected prefrontal-limbic model comprising the IFG, vmPFC, and amygdala. Dysregulatory IFG dynamics were associated with weaker reciprocal excitatory connectivity between the IFG and the vmPFC. The vmPFC exhibited inhibitory influence on the amygdala. Our current results, combined with our previous work across a threat-perception spectrum of 137 subjects and a meta-analysis of 366 fMRI studies, dissociate distinct roles for three prefrontal-limbic regions, wherein the IFG provides evaluation of stimulus meaning, which then informs the vmPFC in inhibiting the amygdala. Affective neuroscience has generally treated prefrontal regions (orbitofrontal cortex, dorsolateral prefrontal cortex, inferior frontal gyrus, ventromedial prefrontal cortex) equivalently as inhibitory components of the prefrontal-limbic system. Yet research across the anxiety spectrum suggests that the inferior frontal gyrus may have a more complex role in emotion regulation, as this region shows abnormal function in disorders of both hyperarousal and hypoarousal. Using entropic measures of circuit-wide regulation and feedback, in combination with measures of structural and functional connectivity, we dissociate distinct roles for three prefrontal-limbic regions, wherein the inferior frontal gyrus provides evaluation of stimulus meaning, which then informs the ventromedial prefrontal cortex in inhibiting the amygdala. This reconfiguration coheres with studies of conceptual disambiguation also implicating the inferior frontal gyrus. Copyright © 2016 the authors 0270-6474/16/364708-11$15.00/0.

Recurrent connectivity can account for the dynamics of disparity processing in V1

PubMed Central

Samonds, Jason M.; Potetz, Brian R.; Tyler, Christopher W.; Lee, Tai Sing

2013-01-01

Disparity tuning measured in the primary visual cortex (V1) is described well by the disparity energy model, but not all aspects of disparity tuning are fully explained by the model. Such deviations from the disparity energy model provide us with insight into how network interactions may play a role in disparity processing and help to solve the stereo correspondence problem. Here, we propose a neuronal circuit model with recurrent connections that provides a simple account of the observed deviations. The model is based on recurrent connections inferred from neurophysiological observations on spike timing correlations, and is in good accord with existing data on disparity tuning dynamics. We further performed two additional experiments to test predictions of the model. First, we increased the size of stimuli to drive more neurons and provide a stronger recurrent input. Our model predicted sharper disparity tuning for larger stimuli. Second, we displayed anti-correlated stereograms, where dots of opposite luminance polarity are matched between the left- and right-eye images and result in inverted disparity tuning in the disparity energy model. In this case, our model predicted reduced sharpening and strength of inverted disparity tuning. For both experiments, the dynamics of disparity tuning observed from the neurophysiological recordings in macaque V1 matched model simulation predictions. Overall, the results of this study support the notion that, while the disparity energy model provides a primary account of disparity tuning in V1 neurons, neural disparity processing in V1 neurons is refined by recurrent interactions among elements in the neural circuit. PMID:23407952

A Simulation Framework for Battery Cell Impact Safety Modeling Using LS-DYNA

DOE PAGES

Marcicki, James; Zhu, Min; Bartlett, Alexander; ...

2017-02-04

The development process of electrified vehicles can benefit significantly from computer-aided engineering tools that predict themultiphysics response of batteries during abusive events. A coupled structural, electrical, electrochemical, and thermal model framework has been developed within the commercially available LS-DYNA software. The finite element model leverages a three-dimensional mesh structure that fully resolves the unit cell components. The mechanical solver predicts the distributed stress and strain response with failure thresholds leading to the onset of an internal short circuit. In this implementation, an arbitrary compressive strain criterion is applied locally to each unit cell. A spatially distributed equivalent circuit model providesmore » an empirical representation of the electrochemical responsewith minimal computational complexity.The thermalmodel provides state information to index the electrical model parameters, while simultaneously accepting irreversible and reversible sources of heat generation. The spatially distributed models of the electrical and thermal dynamics allow for the localization of current density and corresponding temperature response. The ability to predict the distributed thermal response of the cell as its stored energy is completely discharged through the short circuit enables an engineering safety assessment. A parametric analysis of an exemplary model is used to demonstrate the simulation capabilities.« less

Phase Control in Nonlinear Systems

NASA Astrophysics Data System (ADS)

Zambrano, Samuel; Seoane, Jesús M.; Mariño, Inés P.; Sanjuán, Miguel A. F.; Meucci, Riccardo

The following sections are included: * Introduction * Phase Control of Chaos * Description of the model * Numerical exploration of phase control of chaos * Experimental evidence of phase control of chaos * Phase Control of Intermittency in Dynamical Systems * Crisis-induced intermittency and its control * Experimental setup and implementation of the phase control scheme * Phase control of the laser in the pre-crisis regime * Phase control of the intermittency after the crisis * Phase control of the intermittency in the quadratic map * Phase Control of Escapes in Open Dynamical Systems * Control of open dynamical systems * Model description * Numerical simulations and heuristic arguments * Experimental implementation in an electronic circuit * Conclusions and Discussions * Acknowledgments * References

Ring Attractor Dynamics Emerge from a Spiking Model of the Entire Protocerebral Bridge.

PubMed

Kakaria, Kyobi S; de Bivort, Benjamin L

2017-01-01

Animal navigation is accomplished by a combination of landmark-following and dead reckoning based on estimates of self motion. Both of these approaches require the encoding of heading information, which can be represented as an allocentric or egocentric azimuthal angle. Recently, Ca 2+ correlates of landmark position and heading direction, in egocentric coordinates, were observed in the ellipsoid body (EB), a ring-shaped processing unit in the fly central complex (CX; Seelig and Jayaraman, 2015). These correlates displayed key dynamics of so-called ring attractors, namely: (1) responsiveness to the position of external stimuli; (2) persistence in the absence of external stimuli; (3) locking onto a single external stimulus when presented with two competitors; (4) stochastically switching between competitors with low probability; and (5) sliding or jumping between positions when an external stimulus moves. We hypothesized that ring attractor-like activity in the EB arises from reciprocal neuronal connections to a related structure, the protocerebral bridge (PB). Using recent light-microscopy resolution catalogs of neuronal cell types in the PB (Lin et al., 2013; Wolff et al., 2015), we determined a connectivity matrix for the PB-EB circuit. When activity in this network was simulated using a leaky-integrate-and-fire model, we observed patterns of activity that closely resemble the reported Ca 2+ phenomena. All qualitative ring attractor behaviors were recapitulated in our model, allowing us to predict failure modes of the putative PB-EB ring attractor and the circuit dynamics phenotypes of thermogenetic or optogenetic manipulations. Ring attractor dynamics emerged under a wide variety of parameter configurations, even including non-spiking leaky-integrator implementations. This suggests that the ring-attractor computation is a robust output of this circuit, apparently arising from its high-level network properties (topological configuration, local excitation and long-range inhibition) rather than fine-scale biological detail.

Fault-tolerant, high-level quantum circuits: form, compilation and description

NASA Astrophysics Data System (ADS)

Paler, Alexandru; Polian, Ilia; Nemoto, Kae; Devitt, Simon J.

2017-06-01

Fault-tolerant quantum error correction is a necessity for any quantum architecture destined to tackle interesting, large-scale problems. Its theoretical formalism has been well founded for nearly two decades. However, we still do not have an appropriate compiler to produce a fault-tolerant, error-corrected description from a higher-level quantum circuit for state-of the-art hardware models. There are many technical hurdles, including dynamic circuit constructions that occur when constructing fault-tolerant circuits with commonly used error correcting codes. We introduce a package that converts high-level quantum circuits consisting of commonly used gates into a form employing all decompositions and ancillary protocols needed for fault-tolerant error correction. We call this form the (I)initialisation, (C)NOT, (M)measurement form (ICM) and consists of an initialisation layer of qubits into one of four distinct states, a massive, deterministic array of CNOT operations and a series of time-ordered X- or Z-basis measurements. The form allows a more flexible approach towards circuit optimisation. At the same time, the package outputs a standard circuit or a canonical geometric description which is a necessity for operating current state-of-the-art hardware architectures using topological quantum codes.

Nonlinear Contact Effects in Staggered Thin-Film Transistors

NASA Astrophysics Data System (ADS)

Fischer, Axel; Zündorf, Hilke; Kaschura, Felix; Widmer, Johannes; Leo, Karl; Kraft, Ulrike; Klauk, Hagen

2017-11-01

The static and dynamic electrical characteristics of thin-film transistors (TFTs) are often limited by the parasitic contact resistances, especially for TFTs with a small channel length. For the smallest possible contact resistance, the staggered device architecture has a general advantage over the coplanar architecture of a larger injection area. Since the charge transport occurs over an extended area, it is inherently more difficult to develop an accurate analytical device model for staggered TFTs. Most analytical models for staggered TFTs, therefore, assume that the contact resistance is linear, even though this is commonly accepted not to be the case. Here, we introduce a semiphenomenological approach to accurately fit experimental data based on a highly discretized equivalent network circuit explicitly taking into account the inherent nonlinearity of the contact resistance. The model allows us to investigate the influence of nonlinear contact resistances on the static and dynamic performance of staggered TFTs for different contact layouts with a relatively short computation time. The precise extraction of device parameters enables us to calculate the transistor behavior as well as the potential for optimization in real circuits.

High-resolution mapping of bifurcations in nonlinear biochemical circuits

NASA Astrophysics Data System (ADS)

Genot, A. J.; Baccouche, A.; Sieskind, R.; Aubert-Kato, N.; Bredeche, N.; Bartolo, J. F.; Taly, V.; Fujii, T.; Rondelez, Y.

2016-08-01

Analog molecular circuits can exploit the nonlinear nature of biochemical reaction networks to compute low-precision outputs with fewer resources than digital circuits. This analog computation is similar to that employed by gene-regulation networks. Although digital systems have a tractable link between structure and function, the nonlinear and continuous nature of analog circuits yields an intricate functional landscape, which makes their design counter-intuitive, their characterization laborious and their analysis delicate. Here, using droplet-based microfluidics, we map with high resolution and dimensionality the bifurcation diagrams of two synthetic, out-of-equilibrium and nonlinear programs: a bistable DNA switch and a predator-prey DNA oscillator. The diagrams delineate where function is optimal, dynamics bifurcates and models fail. Inverse problem solving on these large-scale data sets indicates interference from enzymatic coupling. Additionally, data mining exposes the presence of rare, stochastically bursting oscillators near deterministic bifurcations.

Research on laser detonation pulse circuit with low-power based on super capacitor

NASA Astrophysics Data System (ADS)

Wang, Hao-yu; Hong, Jin; He, Aifeng; Jing, Bo; Cao, Chun-qiang; Ma, Yue; Chu, En-yi; Hu, Ya-dong

2018-03-01

According to the demand of laser initiating device miniaturization and low power consumption of weapon system, research on the low power pulse laser detonation circuit with super capacitor. Established a dynamic model of laser output based on super capacitance storage capacity, discharge voltage and programmable output pulse width. The output performance of the super capacitor under different energy storage capacity and discharge voltage is obtained by simulation. The experimental test system was set up, and the laser diode of low power pulsed laser detonation circuit was tested and the laser output waveform of laser diode in different energy storage capacity and discharge voltage was collected. Experiments show that low power pulse laser detonation based on super capacitor energy storage circuit discharge with high efficiency, good transient performance, for a low power consumption requirement, for laser detonation system and low power consumption and provide reference light miniaturization of engineering practice.

Optimization of the Switch Mechanism in a Circuit Breaker Using MBD Based Simulation

PubMed Central

Jang, Jin-Seok; Yoon, Chang-Gyu; Ryu, Chi-Young; Kim, Hyun-Woo; Bae, Byung-Tae; Yoo, Wan-Suk

2015-01-01

A circuit breaker is widely used to protect electric power system from fault currents or system errors; in particular, the opening mechanism in a circuit breaker is important to protect current overflow in the electric system. In this paper, multibody dynamic model of a circuit breaker including switch mechanism was developed including the electromagnetic actuator system. Since the opening mechanism operates sequentially, optimization of the switch mechanism was carried out to improve the current breaking time. In the optimization process, design parameters were selected from length and shape of each latch, which changes pivot points of bearings to shorten the breaking time. To validate optimization results, computational results were compared to physical tests with a high speed camera. Opening time of the optimized mechanism was decreased by 2.3 ms, which was proved by experiments. Switch mechanism design process can be improved including contact-latch system by using this process. PMID:25918740

Foundations and Emerging Paradigms for Computing in Living Cells.

PubMed

Ma, Kevin C; Perli, Samuel D; Lu, Timothy K

2016-02-27

Genetic circuits, composed of complex networks of interacting molecular machines, enable living systems to sense their dynamic environments, perform computation on the inputs, and formulate appropriate outputs. By rewiring and expanding these circuits with novel parts and modules, synthetic biologists have adapted living systems into vibrant substrates for engineering. Diverse paradigms have emerged for designing, modeling, constructing, and characterizing such artificial genetic systems. In this paper, we first provide an overview of recent advances in the development of genetic parts and highlight key engineering approaches. We then review the assembly of these parts into synthetic circuits from the perspectives of digital and analog logic, systems biology, and metabolic engineering, three areas of particular theoretical and practical interest. Finally, we discuss notable challenges that the field of synthetic biology still faces in achieving reliable and predictable forward-engineering of artificial biological circuits. Copyright © 2016. Published by Elsevier Ltd.

Multilevel Resistance Programming in Conductive Bridge Resistive Memory

NASA Astrophysics Data System (ADS)

Mahalanabis, Debayan

This work focuses on the existence of multiple resistance states in a type of emerging non-volatile resistive memory device known commonly as Programmable Metallization Cell (PMC) or Conductive Bridge Random Access Memory (CBRAM), which can be important for applications such as multi-bit memory as well as non-volatile logic and neuromorphic computing. First, experimental data from small signal, quasi-static and pulsed mode electrical characterization of such devices are presented which clearly demonstrate the inherent multi-level resistance programmability property in CBRAM devices. A physics based analytical CBRAM compact model is then presented which simulates the ion-transport dynamics and filamentary growth mechanism that causes resistance change in such devices. Simulation results from the model are fitted to experimental dynamic resistance switching characteristics. The model designed using Verilog-a language is computation-efficient and can be integrated with industry standard circuit simulation tools for design and analysis of hybrid circuits involving both CMOS and CBRAM devices. Three main circuit applications for CBRAM devices are explored in this work. Firstly, the susceptibility of CBRAM memory arrays to single event induced upsets is analyzed via compact model simulation and experimental heavy ion testing data that show possibility of both high resistance to low resistance and low resistance to high resistance transitions due to ion strikes. Next, a non-volatile sense amplifier based flip-flop architecture is proposed which can help make leakage power consumption negligible by allowing complete shutdown of power supply while retaining its output data in CBRAM devices. Reliability and energy consumption of the flip-flop circuit for different CBRAM low resistance levels and supply voltage values are analyzed and compared to CMOS designs. Possible extension of this architecture for threshold logic function computation using the CBRAM devices as re-configurable resistive weights is also discussed. Lastly, Spike timing dependent plasticity (STDP) based gradual resistance change behavior in CBRAM device fabricated in back-end-of-line on a CMOS die containing integrate and fire CMOS neuron circuits is demonstrated for the first time which indicates the feasibility of using CBRAM devices as electronic synapses in spiking neural network hardware implementations for non-Boolean neuromorphic computing.

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning.

PubMed

Kappel, David; Legenstein, Robert; Habenschuss, Stefan; Hsieh, Michael; Maass, Wolfgang

2018-01-01

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is at least as large as the component that depends on the history of pre- and postsynaptic neural activity. These data are inconsistent with common models for network plasticity and raise the following questions: how can neural circuits maintain a stable computational function in spite of these continuously ongoing processes, and what could be functional uses of these ongoing processes? Here, we present a rigorous theoretical framework for these seemingly stochastic spine dynamics and rewiring processes in the context of reward-based learning tasks. We show that spontaneous synapse-autonomous processes, in combination with reward signals such as dopamine, can explain the capability of networks of neurons in the brain to configure themselves for specific computational tasks, and to compensate automatically for later changes in the network or task. Furthermore, we show theoretically and through computer simulations that stable computational performance is compatible with continuously ongoing synapse-autonomous changes. After reaching good computational performance it causes primarily a slow drift of network architecture and dynamics in task-irrelevant dimensions, as observed for neural activity in motor cortex and other areas. On the more abstract level of reinforcement learning the resulting model gives rise to an understanding of reward-driven network plasticity as continuous sampling of network configurations.

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning

PubMed Central

Habenschuss, Stefan; Hsieh, Michael

2018-01-01

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is at least as large as the component that depends on the history of pre- and postsynaptic neural activity. These data are inconsistent with common models for network plasticity and raise the following questions: how can neural circuits maintain a stable computational function in spite of these continuously ongoing processes, and what could be functional uses of these ongoing processes? Here, we present a rigorous theoretical framework for these seemingly stochastic spine dynamics and rewiring processes in the context of reward-based learning tasks. We show that spontaneous synapse-autonomous processes, in combination with reward signals such as dopamine, can explain the capability of networks of neurons in the brain to configure themselves for specific computational tasks, and to compensate automatically for later changes in the network or task. Furthermore, we show theoretically and through computer simulations that stable computational performance is compatible with continuously ongoing synapse-autonomous changes. After reaching good computational performance it causes primarily a slow drift of network architecture and dynamics in task-irrelevant dimensions, as observed for neural activity in motor cortex and other areas. On the more abstract level of reinforcement learning the resulting model gives rise to an understanding of reward-driven network plasticity as continuous sampling of network configurations. PMID:29696150

Dynamics of Permanent-Magnet Biased Active Magnetic Bearings

NASA Technical Reports Server (NTRS)

Fukata, Satoru; Yutani, Kazuyuki

1996-01-01

Active magnetic radial bearings are constructed with a combination of permanent magnets to provide bias forces and electromagnets to generate control forces for the reduction of cost and the operating energy consumption. Ring-shaped permanent magnets with axial magnetization are attached to a shaft and share their magnet stators with the electromagnets. The magnet cores are made of solid iron for simplicity. A simplified magnetic circuit of the combined magnet system is analyzed with linear circuit theory by approximating the characteristics of permanent magnets with a linear relation. A linearized dynamical model of the control force is presented with the first-order approximation of the effects of eddy currents. Frequency responses of the rotor motion to disturbance inputs and the motion for impulsive forces are tested in the non-rotating state. The frequency responses are compared with numerical results. The decay of rotor speed due to magnetic braking is examined. The experimental results and the presented linearized model are similar to those of the all-electromagnetic design.

A Brain-wide Circuit Model of Heat-Evoked Swimming Behavior in Larval Zebrafish.

PubMed

Haesemeyer, Martin; Robson, Drew N; Li, Jennifer M; Schier, Alexander F; Engert, Florian

2018-05-16

Thermosensation provides crucial information, but how temperature representation is transformed from sensation to behavior is poorly understood. Here, we report a preparation that allows control of heat delivery to zebrafish larvae while monitoring motor output and imaging whole-brain calcium signals, thereby uncovering algorithmic and computational rules that couple dynamics of heat modulation, neural activity and swimming behavior. This approach identifies a critical step in the transformation of temperature representation between the sensory trigeminal ganglia and the hindbrain: A simple sustained trigeminal stimulus representation is transformed into a representation of absolute temperature as well as temperature changes in the hindbrain that explains the observed motor output. An activity constrained dynamic circuit model captures the most prominent aspects of these sensori-motor transformations and predicts both behavior and neural activity in response to novel heat stimuli. These findings provide the first algorithmic description of heat processing from sensory input to behavioral output. Copyright © 2018 Elsevier Inc. All rights reserved.

The neural circuit and synaptic dynamics underlying perceptual decision-making

NASA Astrophysics Data System (ADS)

Liu, Feng

2015-03-01

Decision-making with several choice options is central to cognition. To elucidate the neural mechanisms of multiple-choice motion discrimination, we built a continuous recurrent network model to represent a local circuit in the lateral intraparietal area (LIP). The network is composed of pyramidal cells and interneurons, which are directionally tuned. All neurons are reciprocally connected, and the synaptic connectivity strength is heterogeneous. Specifically, we assume two types of inhibitory connectivity to pyramidal cells: opposite-feature and similar-feature inhibition. The model accounted for both physiological and behavioral data from monkey experiments. The network is endowed with slow excitatory reverberation, which subserves the buildup and maintenance of persistent neural activity, and predominant feedback inhibition, which underlies the winner-take-all competition and attractor dynamics. The opposite-feature and opposite-feature inhibition have different effects on decision-making, and only their combination allows for a categorical choice among 12 alternatives. Together, our work highlights the importance of structured synaptic inhibition in multiple-choice decision-making processes.

Cerebellar supervised learning revisited: biophysical modeling and degrees-of-freedom control.

PubMed

Kawato, Mitsuo; Kuroda, Shinya; Schweighofer, Nicolas

2011-10-01

The biophysical models of spike-timing-dependent plasticity have explored dynamics with molecular basis for such computational concepts as coincidence detection, synaptic eligibility trace, and Hebbian learning. They overall support different learning algorithms in different brain areas, especially supervised learning in the cerebellum. Because a single spine is physically very small, chemical reactions at it are essentially stochastic, and thus sensitivity-longevity dilemma exists in the synaptic memory. Here, the cascade of excitable and bistable dynamics is proposed to overcome this difficulty. All kinds of learning algorithms in different brain regions confront with difficult generalization problems. For resolution of this issue, the control of the degrees-of-freedom can be realized by changing synchronicity of neural firing. Especially, for cerebellar supervised learning, the triangle closed-loop circuit consisting of Purkinje cells, the inferior olive nucleus, and the cerebellar nucleus is proposed as a circuit to optimally control synchronous firing and degrees-of-freedom in learning. Copyright © 2011 Elsevier Ltd. All rights reserved.

Flux qubit interaction with rapid single-flux quantum logic circuits: Control and readout

NASA Astrophysics Data System (ADS)

Klenov, N. V.; Kuznetsov, A. V.; Soloviev, I. I.; Bakurskiy, S. V.; Denisenko, M. V.; Satanin, A. M.

2017-07-01

We present the results of an analytical study and numerical simulation of the dynamics of a superconducting three-Josephson-junction (3JJ) flux qubit magnetically coupled with rapid single-flux quantum (RSFQ) logic circuit, which demonstrate the fundamental possibility of implementing the simplest logic operations at picosecond times, as well as rapid non-destructive readout. It is shown that when solving optimization problems, the qubit dynamics can be conveniently interpreted as a precession of the magnetic moment vector around the direction of the magnetic field. In this case, the role of magnetic field components is played by combinations of the Hamiltonian matrix elements, and the role of the magnetic moment is played by the Bloch vector. Features of the 3JJ qubit model are discussed during the analysis of how the qubit is affected by exposure to a short control pulse, as are the similarities between the Bloch and Landau-Lifshitz-Gilbert equations. An analysis of solutions to the Bloch equations made it possible to develop recommendations for the use of readout RSFQ circuits in implementing an optimal interface between the classical and quantum parts of the computer system, as well as to justify the use of single-quantum logic in order to control superconducting quantum circuits on a chip.

An Overview of Dynamic Contact Resistance Measurement of HV Circuit Breakers

NASA Astrophysics Data System (ADS)

Bhole, A. A.; Gandhare, W. Z.

2016-06-01

With the deregulation of the electrical power industry, utilities and service companies are operating in a changing business environment. High voltage circuit breakers are extremely important for the function of modern electric power supply systems. The need to predict the proper function of circuit breaker grew over the years as the transmission networks expanded. The maintenance of circuit breakers deserves special consideration because of their importance for routine switching and for protection of other equipments. Electric transmission system breakups and equipment destruction can occur if a circuit breaker fails to operate because of a lack of preventive maintenance. Dynamic Contact Resistance Measurement (DCRM) is known as an effective technique for assessing the condition of power circuit breakers contacts and operating mechanism. This paper gives a general review about DCRM. It discusses the practical case studies on use of DCRM for condition assessment of high voltage circuit breakers.

A transfer function type of simplified electrochemical model with modified boundary conditions and Padé approximation for Li-ion battery: Part 2. Modeling and parameter estimation

NASA Astrophysics Data System (ADS)

Yuan, Shifei; Jiang, Lei; Yin, Chengliang; Wu, Hongjie; Zhang, Xi

2017-06-01

The electrochemistry-based battery model can provide physics-meaningful knowledge about the lithium-ion battery system with extensive computation burdens. To motivate the development of reduced order battery model, three major contributions have been made throughout this paper: (1) the transfer function type of simplified electrochemical model is proposed to address the current-voltage relationship with Padé approximation method and modified boundary conditions for electrolyte diffusion equations. The model performance has been verified under pulse charge/discharge and dynamic stress test (DST) profiles with the standard derivation less than 0.021 V and the runtime 50 times faster. (2) the parametric relationship between the equivalent circuit model and simplified electrochemical model has been established, which will enhance the comprehension level of two models with more in-depth physical significance and provide new methods for electrochemical model parameter estimation. (3) four simplified electrochemical model parameters: equivalent resistance Req, effective diffusion coefficient in electrolyte phase Deeff, electrolyte phase volume fraction ε and open circuit voltage (OCV), have been identified by the recursive least square (RLS) algorithm with the modified DST profiles under 45, 25 and 0 °C. The simulation results indicate that the proposed model coupled with RLS algorithm can achieve high accuracy for electrochemical parameter identification in dynamic scenarios.

Dynamic analysis and electronic circuit implementation of a novel 3D autonomous system without linear terms

NASA Astrophysics Data System (ADS)

Kengne, J.; Jafari, S.; Njitacke, Z. T.; Yousefi Azar Khanian, M.; Cheukem, A.

2017-11-01

Mathematical models (ODEs) describing the dynamics of almost all continuous time chaotic nonlinear systems (e.g. Lorenz, Rossler, Chua, or Chen system) involve at least a nonlinear term in addition to linear terms. In this contribution, a novel (and singular) 3D autonomous chaotic system without linear terms is introduced. This system has an especial feature of having two twin strange attractors: one ordinary and one symmetric strange attractor when the time is reversed. The complex behavior of the model is investigated in terms of equilibria and stability, bifurcation diagrams, Lyapunov exponent plots, time series and Poincaré sections. Some interesting phenomena are found including for instance, period-doubling bifurcation, antimonotonicity (i.e. the concurrent creation and annihilation of periodic orbits) and chaos while monitoring the system parameters. Compared to the (unique) case previously reported by Xu and Wang (2014) [31], the system considered in this work displays a more 'elegant' mathematical expression and experiences richer dynamical behaviors. A suitable electronic circuit (i.e. the analog simulator) is designed and used for the investigations. Pspice based simulation results show a very good agreement with the theoretical analysis.

Synchrony dynamics underlying effective connectivity reconstruction of neuronal circuits

NASA Astrophysics Data System (ADS)

Yu, Haitao; Guo, Xinmeng; Qin, Qing; Deng, Yun; Wang, Jiang; Liu, Jing; Cao, Yibin

2017-04-01

Reconstruction of effective connectivity between neurons is essential for neural systems with function-related significance, characterizing directionally causal influences among neurons. In this work, causal interactions between neurons in spinal dorsal root ganglion, activated by manual acupuncture at Zusanli acupoint of experimental rats, are estimated using Granger causality (GC) method. Different patterns of effective connectivity are obtained for different frequencies and types of acupuncture. Combined with synchrony analysis between neurons, we show a dependence of effective connection on the synchronization dynamics. Based on the experimental findings, a neuronal circuit model with synaptic connections is constructed. The variation of neuronal effective connectivity with respect to its structural connectivity and synchronization dynamics is further explored. Simulation results show that reciprocally causal interactions with statistically significant are formed between well-synchronized neurons. The effective connectivity may be not necessarily equivalent to synaptic connections, but rather depend on the synchrony relationship. Furthermore, transitions of effective interaction between neurons are observed following the synchronization transitions induced by conduction delay and synaptic conductance. These findings are helpful to further investigate the dynamical mechanisms underlying the reconstruction of effective connectivity of neuronal population.

A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses

PubMed Central

Qiao, Ning; Mostafa, Hesham; Corradi, Federico; Osswald, Marc; Stefanini, Fabio; Sumislawska, Dora; Indiveri, Giacomo

2015-01-01

Implementing compact, low-power artificial neural processing systems with real-time on-line learning abilities is still an open challenge. In this paper we present a full-custom mixed-signal VLSI device with neuromorphic learning circuits that emulate the biophysics of real spiking neurons and dynamic synapses for exploring the properties of computational neuroscience models and for building brain-inspired computing systems. The proposed architecture allows the on-chip configuration of a wide range of network connectivities, including recurrent and deep networks, with short-term and long-term plasticity. The device comprises 128 K analog synapse and 256 neuron circuits with biologically plausible dynamics and bi-stable spike-based plasticity mechanisms that endow it with on-line learning abilities. In addition to the analog circuits, the device comprises also asynchronous digital logic circuits for setting different synapse and neuron properties as well as different network configurations. This prototype device, fabricated using a 180 nm 1P6M CMOS process, occupies an area of 51.4 mm2, and consumes approximately 4 mW for typical experiments, for example involving attractor networks. Here we describe the details of the overall architecture and of the individual circuits and present experimental results that showcase its potential. By supporting a wide range of cortical-like computational modules comprising plasticity mechanisms, this device will enable the realization of intelligent autonomous systems with on-line learning capabilities. PMID:25972778

Local changes in neocortical circuit dynamics coincide with the spread of seizures to thalamus in a model of epilepsy.

PubMed

Neubauer, Florian B; Sederberg, Audrey; MacLean, Jason N

2014-01-01

During the generalization of epileptic seizures, pathological activity in one brain area recruits distant brain structures into joint synchronous discharges. However, it remains unknown whether specific changes in local circuit activity are related to the aberrant recruitment of anatomically distant structures into epileptiform discharges. Further, it is not known whether aberrant areas recruit or entrain healthy ones into pathological activity. Here we study the dynamics of local circuit activity during the spread of epileptiform discharges in the zero-magnesium in vitro model of epilepsy. We employ high-speed multi-photon imaging in combination with dual whole-cell recordings in acute thalamocortical (TC) slices of the juvenile mouse to characterize the generalization of epileptic activity between neocortex and thalamus. We find that, although both structures are exposed to zero-magnesium, the initial onset of focal epileptiform discharge occurs in cortex. This suggests that local recurrent connectivity that is particularly prevalent in cortex is important for the initiation of seizure activity. Subsequent recruitment of thalamus into joint, generalized discharges is coincident with an increase in the coherence of local cortical circuit activity that itself does not depend on thalamus. Finally, the intensity of population discharges is positively correlated between both brain areas. This suggests that during and after seizure generalization not only the timing but also the amplitude of epileptiform discharges in thalamus is entrained by cortex. Together these results suggest a central role of neocortical activity for the onset and the structure of pathological recruitment of thalamus into joint synchronous epileptiform discharges.

Local changes in neocortical circuit dynamics coincide with the spread of seizures to thalamus in a model of epilepsy

PubMed Central

Neubauer, Florian B.; Sederberg, Audrey; MacLean, Jason N.

2014-01-01

During the generalization of epileptic seizures, pathological activity in one brain area recruits distant brain structures into joint synchronous discharges. However, it remains unknown whether specific changes in local circuit activity are related to the aberrant recruitment of anatomically distant structures into epileptiform discharges. Further, it is not known whether aberrant areas recruit or entrain healthy ones into pathological activity. Here we study the dynamics of local circuit activity during the spread of epileptiform discharges in the zero-magnesium in vitro model of epilepsy. We employ high-speed multi-photon imaging in combination with dual whole-cell recordings in acute thalamocortical (TC) slices of the juvenile mouse to characterize the generalization of epileptic activity between neocortex and thalamus. We find that, although both structures are exposed to zero-magnesium, the initial onset of focal epileptiform discharge occurs in cortex. This suggests that local recurrent connectivity that is particularly prevalent in cortex is important for the initiation of seizure activity. Subsequent recruitment of thalamus into joint, generalized discharges is coincident with an increase in the coherence of local cortical circuit activity that itself does not depend on thalamus. Finally, the intensity of population discharges is positively correlated between both brain areas. This suggests that during and after seizure generalization not only the timing but also the amplitude of epileptiform discharges in thalamus is entrained by cortex. Together these results suggest a central role of neocortical activity for the onset and the structure of pathological recruitment of thalamus into joint synchronous epileptiform discharges. PMID:25232306

Comparative methods to assess harmonic response of nonlinear piezoelectric energy harvesters interfaced with AC and DC circuits

NASA Astrophysics Data System (ADS)

Lan, Chunbo; Tang, Lihua; Harne, Ryan L.

2018-05-01

Nonlinear piezoelectric energy harvester (PEH) has been widely investigated during the past few years. Among the majority of these researches, a pure resistive load is used to evaluate power output. To power conventional electronics in practical application, the alternating current (AC) generated by nonlinear PEH needs to be transformed into a direct current (DC) and rectifying circuits are required to interface the device and electronic load. This paper aims at exploring the critical influences of AC and DC interface circuits on nonlinear PEH. As a representative nonlinear PEH, we fabricate and evaluate a monostable PEH in terms of generated power and useful operating bandwidth when it is connected to AC and DC interface circuits. Firstly, the harmonic balance analysis and equivalent circuit representation method are utilized to tackle the modeling of nonlinear energy harvesters connected to AC and DC interface circuits. The performances of the monostable PEH connected to these interface circuits are then analyzed and compared, focusing on the influences of the varying load, excitation and electromechanical coupling strength on the nonlinear dynamics, bandwidth and harvested power. Subsequently, the behaviors of the monostable PEH with AC and DC interface circuits are verified by experiment. Results indicate that both AC and DC interface circuits have a peculiar influence on the power peak shifting and operational bandwidth of the monostable PEH, which is quite different from that on the linear PEH.

Exploring the entanglement of personal epistemologies and emotions in students' thinking

NASA Astrophysics Data System (ADS)

Gupta, Ayush; Elby, Andrew; Danielak, Brian A.

2018-06-01

Evidence from psychology, cognitive science, and neuroscience suggests that cognition and emotions are coupled. Education researchers have also documented correlations between emotions (such as joy, anxiety, fear, curiosity, boredom) and academic performance. Nonetheless, most research on students' reasoning and conceptual change within the learning sciences and physics and science education research has not attended to the role of learners' emotions in describing or modeling the fine timescale dynamics of their conceptual reasoning. The few studies that integrate emotions into models of learners' cognition have mostly done so at a coarse grain size. In this study, toward the long-term goal of incorporating emotions into models of in-the-moment cognitive dynamics, we present a case study of Judy, an undergraduate electrical engineering and physics major. We show that shifts in the intensity of a fine-grained aspect of Judy's emotions, her annoyance at conceptual homework problems, co-occur with shifts in her epistemological stance toward differentiating knowledge about and the practical utility of real circuits and idealized circuit models. We then argue for the plausibility of a cognitive model in which Judy's emotions and epistemological stances mutually affect each other. We end with discussions on how models of learners' cognition that incorporate their emotions are generative for instructional purposes and research on learning.

Analog quantum simulation of the Rabi model in the ultra-strong coupling regime.

PubMed

Braumüller, Jochen; Marthaler, Michael; Schneider, Andre; Stehli, Alexander; Rotzinger, Hannes; Weides, Martin; Ustinov, Alexey V

2017-10-03

The quantum Rabi model describes the fundamental mechanism of light-matter interaction. It consists of a two-level atom or qubit coupled to a quantized harmonic mode via a transversal interaction. In the weak coupling regime, it reduces to the well-known Jaynes-Cummings model by applying a rotating wave approximation. The rotating wave approximation breaks down in the ultra-strong coupling regime, where the effective coupling strength g is comparable to the energy ω of the bosonic mode, and remarkable features in the system dynamics are revealed. Here we demonstrate an analog quantum simulation of an effective quantum Rabi model in the ultra-strong coupling regime, achieving a relative coupling ratio of g/ω ~ 0.6. The quantum hardware of the simulator is a superconducting circuit embedded in a cQED setup. We observe fast and periodic quantum state collapses and revivals of the initial qubit state, being the most distinct signature of the synthesized model.An analog quantum simulation scheme has been explored with a quantum hardware based on a superconducting circuit. Here the authors investigate the time evolution of the quantum Rabi model at ultra-strong coupling conditions, which is synthesized by slowing down the system dynamics in an effective frame.

Quantum simulation of the spin-boson model with a microwave circuit

NASA Astrophysics Data System (ADS)

Leppäkangas, Juha; Braumüller, Jochen; Hauck, Melanie; Reiner, Jan-Michael; Schwenk, Iris; Zanker, Sebastian; Fritz, Lukas; Ustinov, Alexey V.; Weides, Martin; Marthaler, Michael

2018-05-01

We consider superconducting circuits for the purpose of simulating the spin-boson model. The spin-boson model consists of a single two-level system coupled to bosonic modes. In most cases, the model is considered in a limit where the bosonic modes are sufficiently dense to form a continuous spectral bath. A very well known case is the Ohmic bath, where the density of states grows linearly with the frequency. In the limit of weak coupling or large temperature, this problem can be solved numerically. If the coupling is strong, the bosonic modes can become sufficiently excited to make a classical simulation impossible. Here we discuss how a quantum simulation of this problem can be performed by coupling a superconducting qubit to a set of microwave resonators. We demonstrate a possible implementation of a continuous spectral bath with individual bath resonators coupling strongly to the qubit. Applying a microwave drive scheme potentially allows us to access the strong-coupling regime of the spin-boson model. We discuss how the resulting spin relaxation dynamics with different initialization conditions can be probed by standard qubit-readout techniques from circuit quantum electrodynamics.

Measuring single-cell gene expression dynamics in bacteria using fluorescence time-lapse microscopy

PubMed Central

Young, Jonathan W; Locke, James C W; Altinok, Alphan; Rosenfeld, Nitzan; Bacarian, Tigran; Swain, Peter S; Mjolsness, Eric; Elowitz, Michael B

2014-01-01

Quantitative single-cell time-lapse microscopy is a powerful method for analyzing gene circuit dynamics and heterogeneous cell behavior. We describe the application of this method to imaging bacteria by using an automated microscopy system. This protocol has been used to analyze sporulation and competence differentiation in Bacillus subtilis, and to quantify gene regulation and its fluctuations in individual Escherichia coli cells. The protocol involves seeding and growing bacteria on small agarose pads and imaging the resulting microcolonies. Images are then reviewed and analyzed using our laboratory's custom MATLAB analysis code, which segments and tracks cells in a frame-to-frame method. This process yields quantitative expression data on cell lineages, which can illustrate dynamic expression profiles and facilitate mathematical models of gene circuits. With fast-growing bacteria, such as E. coli or B. subtilis, image acquisition can be completed in 1 d, with an additional 1–2 d for progressing through the analysis procedure. PMID:22179594

3-Dimensional Modeling of Capacitively and Inductively Coupled Plasma Etching Systems

NASA Astrophysics Data System (ADS)

Rauf, Shahid

2008-10-01

Low temperature plasmas are widely used for thin film etching during micro and nano-electronic device fabrication. Fluid and hybrid plasma models were developed 15-20 years ago to understand the fundamentals of these plasmas and plasma etching. These models have significantly evolved since then, and are now a major tool used for new plasma hardware design and problem resolution. Plasma etching is a complex physical phenomenon, where inter-coupled plasma, electromagnetic, fluid dynamics, and thermal effects all have a major influence. The next frontier in the evolution of fluid-based plasma models is where these models are able to self-consistently treat the inter-coupling of plasma physics with fluid dynamics, electromagnetics, heat transfer and magnetostatics. We describe one such model in this paper and illustrate its use in solving engineering problems of interest for next generation plasma etcher design. Our 3-dimensional plasma model includes the full set of Maxwell equations, transport equations for all charged and neutral species in the plasma, the Navier-Stokes equation for fluid flow, and Kirchhoff's equations for the lumped external circuit. This model also includes Monte Carlo based kinetic models for secondary electrons and stochastic heating, and can take account of plasma chemistry. This modeling formalism allows us to self-consistently treat the dynamics in commercial inductively and capacitively coupled plasma etching reactors with realistic plasma chemistries, magnetic fields, and reactor geometries. We are also able to investigate the influence of the distributed electromagnetic circuit at very high frequencies (VHF) on the plasma dynamics. The model is used to assess the impact of azimuthal asymmetries in plasma reactor design (e.g., off-center pump, 3D magnetic field, slit valve, flow restrictor) on plasma characteristics at frequencies from 2 -- 180 MHz. With Jason Kenney, Ankur Agarwal, Ajit Balakrishna, Kallol Bera, and Ken Collins.

Chua's Circuit and the Qualitative Theory of Dynamical Systems

NASA Astrophysics Data System (ADS)

Mira, Christian

Simple electronic oscillators were at the origin of many studies related to the qualitative theory of dynamical systems. Chua's circuit ([Chua, 1992; Madan, 1993; Chua, 1993; Chua & Pivka, 1995; Wu & Chua, 1996; Pivka et al., 1996]) is now playing an equivalent role for the generation and understanding of complex dynamics. In honour of my friend Leon Chua on his 60th birthday.

Engineering dynamical control of cell fate switching using synthetic phospho-regulons

PubMed Central

Gordley, Russell M.; Williams, Reid E.; Bashor, Caleb J.; Toettcher, Jared E.; Yan, Shude; Lim, Wendell A.

2016-01-01

Many cells can sense and respond to time-varying stimuli, selectively triggering changes in cell fate only in response to inputs of a particular duration or frequency. A common motif in dynamically controlled cells is a dual-timescale regulatory network: although long-term fate decisions are ultimately controlled by a slow-timescale switch (e.g., gene expression), input signals are first processed by a fast-timescale signaling layer, which is hypothesized to filter what dynamic information is efficiently relayed downstream. Directly testing the design principles of how dual-timescale circuits control dynamic sensing, however, has been challenging, because most synthetic biology methods have focused solely on rewiring transcriptional circuits, which operate at a single slow timescale. Here, we report the development of a modular approach for flexibly engineering phosphorylation circuits using designed phospho-regulon motifs. By then linking rapid phospho-feedback with slower downstream transcription-based bistable switches, we can construct synthetic dual-timescale circuits in yeast in which the triggering dynamics and the end-state properties of the ON state can be selectively tuned. These phospho-regulon tools thus open up the possibility to engineer cells with customized dynamical control. PMID:27821768

Developmental metaplasticity in neural circuit codes of firing and structure.

PubMed

Baram, Yoram

2017-01-01

Firing-rate dynamics have been hypothesized to mediate inter-neural information transfer in the brain. While the Hebbian paradigm, relating learning and memory to firing activity, has put synaptic efficacy variation at the center of cortical plasticity, we suggest that the external expression of plasticity by changes in the firing-rate dynamics represents a more general notion of plasticity. Hypothesizing that time constants of plasticity and firing dynamics increase with age, and employing the filtering property of the neuron, we obtain the elementary code of global attractors associated with the firing-rate dynamics in each developmental stage. We define a neural circuit connectivity code as an indivisible set of circuit structures generated by membrane and synapse activation and silencing. Synchronous firing patterns under parameter uniformity, and asynchronous circuit firing are shown to be driven, respectively, by membrane and synapse silencing and reactivation, and maintained by the neuronal filtering property. Analytic, graphical and simulation representation of the discrete iteration maps and of the global attractor codes of neural firing rate are found to be consistent with previous empirical neurobiological findings, which have lacked, however, a specific correspondence between firing modes, time constants, circuit connectivity and cortical developmental stages. Copyright © 2016 Elsevier Ltd. All rights reserved.

Josephson junction in the quantum mesoscopic electric circuits with charge discreteness

NASA Astrophysics Data System (ADS)

Pahlavani, H.

2018-04-01

A quantum mesoscopic electrical LC-circuit with charge discreteness including a Josephson junction is considered and a nonlinear Hamiltonian that describing the dynamic of such circuit is introduced. The quantum dynamical behavior (persistent current probability) is studied in the charge and phase regimes by numerical solution approaches. The time evolution of charge and current, number-difference and the bosonic phase and also the energy spectrum of a quantum mesoscopic electric LC-circuit with charge discreteness that coupled with a Josephson junction device are investigated. We show the role of the coupling energy and the electrostatic Coulomb energy of the Josephson junction in description of the quantum behavior and the spectral properties of a quantum mesoscopic electrical LC-circuits with charge discreteness.

CMOS Amperometric ADC With High Sensitivity, Dynamic Range and Power Efficiency for Air Quality Monitoring.

PubMed

Li, Haitao; Boling, C Sam; Mason, Andrew J

2016-08-01

Airborne pollutants are a leading cause of illness and mortality globally. Electrochemical gas sensors show great promise for personal air quality monitoring to address this worldwide health crisis. However, implementing miniaturized arrays of such sensors demands high performance instrumentation circuits that simultaneously meet challenging power, area, sensitivity, noise and dynamic range goals. This paper presents a new multi-channel CMOS amperometric ADC featuring pixel-level architecture for gas sensor arrays. The circuit combines digital modulation of input currents and an incremental Σ∆ ADC to achieve wide dynamic range and high sensitivity with very high power efficiency and compact size. Fabricated in 0.5 [Formula: see text] CMOS, the circuit was measured to have 164 dB cross-scale dynamic range, 100 fA sensitivity while consuming only 241 [Formula: see text] and 0.157 [Formula: see text] active area per channel. Electrochemical experiments with liquid and gas targets demonstrate the circuit's real-time response to a wide range of analyte concentrations.

Analysis and Control of Pulse-Width Modulated AC to DC Voltage Source Converters.

NASA Astrophysics Data System (ADS)

Wu, Rusong

The pulse width modulated AC to DC voltage source converter is comprehensively analyzed in the thesis. A general mathematical model of the converter is first established, which is discontinuous, time-variant and non-linear. The following three techniques are used to obtain closed form solutions: Fourier analysis, transformation of reference frame and small signal linearization. Three models, namely, a steady-state DC model, a low frequency small signal AC model and a high frequency model, are consequently developed. Finally, three solution sets, namely, the steady-state solution, various dynamic transfer functions and the high frequency harmonic components, are obtained from the three models. Two control strategies, the Phase and Amplitude Control (PAC) and a new proposed strategy, Predicted Current Control with a Fixed Switching Frequency (PCFF), are investigated. Based on the transfer functions derived from the above mentioned analysis, regulators for a closed-loop control are designed. A prototype circuit is built to experimentally verify the theoretical predictions. The analysis and experimental results show that both strategies produce nearly sinusoidal line current with unity power factor on the utility side in both rectifying and regenerating operations and concurrently provide a regulated DC output voltage on the load side. However the proposed PCFF control has a faster and improved dynamic response over the PAC control. Moreover it is also easier to be implemented. Therefore, the PCFF control is preferable to the PAC control. As an example of application, a configuration of variable DC supply under PCFF control is proposed. The quasi-optimal dynamic response obtained shows that the PWM AC to DC converter lays the foundation for building a four-quadrant, fast-dynamic system, and the PCFF control is an effective strategy for improving dynamic performances not only as applied to the AC to DC converter, but also as applied to the DC to DC chopper or other circuits.

Dynamic Divisive Normalization Predicts Time-Varying Value Coding in Decision-Related Circuits

PubMed Central

LoFaro, Thomas; Webb, Ryan; Glimcher, Paul W.

2014-01-01

Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. PMID:25429145

Bio-Inspired Neural Model for Learning Dynamic Models

NASA Technical Reports Server (NTRS)

Duong, Tuan; Duong, Vu; Suri, Ronald

2009-01-01

A neural-network mathematical model that, relative to prior such models, places greater emphasis on some of the temporal aspects of real neural physical processes, has been proposed as a basis for massively parallel, distributed algorithms that learn dynamic models of possibly complex external processes by means of learning rules that are local in space and time. The algorithms could be made to perform such functions as recognition and prediction of words in speech and of objects depicted in video images. The approach embodied in this model is said to be "hardware-friendly" in the following sense: The algorithms would be amenable to execution by special-purpose computers implemented as very-large-scale integrated (VLSI) circuits that would operate at relatively high speeds and low power demands.

An equivalent circuit model for terahertz quantum cascade lasers: Modeling and experiments

NASA Astrophysics Data System (ADS)

Yao, Chen; Xu, Tian-Hong; Wan, Wen-Jian; Zhu, Yong-Hao; Cao, Jun-Cheng

2015-09-01

Terahertz quantum cascade lasers (THz QCLs) emitted at 4.4 THz are fabricated and characterized. An equivalent circuit model is established based on the five-level rate equations to describe their characteristics. In order to illustrate the capability of the model, the steady and dynamic performances of the fabricated THz QCLs are simulated by the model. Compared to the sophisticated numerical methods, the presented model has advantages of fast calculation and good compatibility with circuit simulation for system-level designs and optimizations. The validity of the model is verified by the experimental and numerical results. Project supported by the National Basic Research Program of China (Grant No. 2014CB339803), the National High Technology Research and Development Program of China (Grant No. 2011AA010205), the National Natural Science Foundation of China (Grant Nos. 61131006, 61321492, and 61404149), the Major National Development Project of Scientific Instrument and Equipment, China (Grant No. 2011YQ150021), the National Science and Technology Major Project, China (Grant No. 2011ZX02707), the Major Project, China (Grant No. YYYJ-1123-1), the International Collaboration and Innovation Program on High Mobility Materials Engineering of the Chinese Academy of Sciences, and the Shanghai Municipal Commission of Science and Technology, China (Grant Nos. 14530711300).

Laminar circuit organization and response modulation in mouse visual cortex

PubMed Central

Olivas, Nicholas D.; Quintanar-Zilinskas, Victor; Nenadic, Zoran; Xu, Xiangmin

2012-01-01

The mouse has become an increasingly important animal model for visual system studies, but few studies have investigated local functional circuit organization of mouse visual cortex. Here we used our newly developed mapping technique combining laser scanning photostimulation (LSPS) with fast voltage-sensitive dye (VSD) imaging to examine the spatial organization and temporal dynamics of laminar circuit responses in living slice preparations of mouse primary visual cortex (V1). During experiments, LSPS using caged glutamate provided spatially restricted neuronal activation in a specific cortical layer, and evoked responses from the stimulated layer to its functionally connected regions were detected by VSD imaging. In this study, we first provided a detailed analysis of spatiotemporal activation patterns at specific V1 laminar locations and measured local circuit connectivity. Then we examined the role of cortical inhibition in the propagation of evoked cortical responses by comparing circuit activity patterns in control and in the presence of GABAa receptor antagonists. We found that GABAergic inhibition was critical in restricting layer-specific excitatory activity spread and maintaining topographical projections. In addition, we investigated how AMPA and NMDA receptors influenced cortical responses and found that blocking AMPA receptors abolished interlaminar functional projections, and the NMDA receptor activity was important in controlling visual cortical circuit excitability and modulating activity propagation. The NMDA receptor antagonist reduced neuronal population activity in time-dependent and laminar-specific manners. Finally, we used the quantitative information derived from the mapping experiments and presented computational modeling analysis of V1 circuit organization. Taken together, the present study has provided important new information about mouse V1 circuit organization and response modulation. PMID:23060751

Manipulating Models and Grasping the Ideas They Represent

ERIC Educational Resources Information Center

Bryce, T. G.; Blown, E. J.

2016-01-01

This article notes the convergence of recent thinking in neuroscience and grounded cognition regarding the way we understand mental representation and recollection: ideas are dynamic and multi-modal, actively created at the point of recall. Also, neurophysiologically, re-entrant signalling among cortical circuits allows non-conscious processing to…

Dynamic characteristics of motor-gear system under load saltations and voltage transients

NASA Astrophysics Data System (ADS)

Bai, Wenyu; Qin, Datong; Wang, Yawen; Lim, Teik C.

2018-02-01

In this paper, a dynamic model of a motor-gear system is proposed. The model combines a nonlinear permeance network model (PNM) of a squirrel-cage induction motor and a coupled lateral-torsional dynamic model of a planetary geared rotor system. The external excitations including voltage transients and load saltations, as well as the internal excitations such as spatial effects, magnetic circuits topology and material nonlinearity in the motor, and time-varying mesh stiffness and damping in the planetary gear system are considered in the proposed model. Then, the simulation results are compared with those predicted by the electromechanical model containing a dynamic motor model with constant inductances. The comparison showed that the electromechanical system model with the PNM motor model yields more reasonable results than the electromechanical system model with the lumped-parameter electric machine. It is observed that electromechanical coupling effect can induce additional and severe gear vibrations. In addition, the external conditions, especially the voltage transients, will dramatically affect the dynamic characteristics of the electromechanical system. Finally, some suggestions are offered based on this analysis for improving the performance and reliability of the electromechanical system.

Engineering self-contained DNA circuit for proximity recognition and localized signal amplification of target biomolecules

PubMed Central

Ang, Yan Shan; Yung, Lin-Yue Lanry

2014-01-01

Biomolecular interactions have important cellular implications, however, a simple method for the sensing of such proximal events is lacking in the current molecular toolbox. We designed a dynamic DNA circuit capable of recognizing targets in close proximity to initiate a pre-programmed signal transduction process resulting in localized signal amplification. The entire circuit was engineered to be self-contained, i.e. it can self-assemble onto individual target molecules autonomously and form localized signal with minimal cross-talk. α-thrombin was used as a model protein to evaluate the performance of the individual modules and the overall circuit for proximity interaction under physiologically relevant buffer condition. The circuit achieved good selectivity in presence of non-specific protein and interfering serum matrix and successfully detected for physiologically relevant α-thrombin concentration (50 nM–5 μM) in a single mixing step without any further washing. The formation of localized signal at the interaction site can be enhanced kinetically through the control of temperature and probe concentration. This work provides a basic general framework from which other circuit modules can be adapted for the sensing of other biomolecular or cellular interaction of interest. PMID:25056307

On the Synchronization of EEG Spindle Waves

NASA Astrophysics Data System (ADS)

Long, Wen; Zhang, ChengFu; Zhao, SiLan; Shi, RuiHong

2000-06-01

Based on recently sleeping cellular substrates, a network model synaptically coupled by N three-cell circuits is provided. Simulation results show that: (i) the dynamic behavior of every circuit is chaotic; (ii) the synchronization of the network is incomplete; (iii) the incomplete synchronization can integrate burst firings of cortical cells into waxing-and-wanning EEG spindle waves. These results enlighten us that this kind of incomplete synchronization may integrate microscopic, electrical activities of neurons in billions into macroscopic, functional states in human brain. In addition, the effects of coupling strength, connectional mode and noise to the synchronization are discussed.

Experimental Measurements and Mathematical Modeling of Static and Dynamic Characteristics of Water Flow in a Long Pipe

NASA Astrophysics Data System (ADS)

Jablonska, J.; Kozubkova, M.

2017-08-01

Static and dynamic characteristics of flow in technical practice are very important and serious problem and can be solved by experimental measurement or mathematical modeling. Unsteady flow presents time changes of the flow and water hammer can be an example of this phenomenon. Water hammer is caused by rapid changes in the water flow by means the closure or opening of the control valve. The authors deal with by hydraulic hammer at the multiphase flow (water and air), its one-dimensional modeling (Matlab SimHydraulics) and modeling with the use of the finite volume method (Ansys Fluent) in article. The circuit elements are defined by static and dynamic characteristics. The results are verified with measurements. The article evaluates different approaches, their advantages, disadvantages and specifics in solving of water hammer.

Biologically based neural circuit modelling for the study of fear learning and extinction

NASA Astrophysics Data System (ADS)

Nair, Satish S.; Paré, Denis; Vicentic, Aleksandra

2016-11-01

The neuronal systems that promote protective defensive behaviours have been studied extensively using Pavlovian conditioning. In this paradigm, an initially neutral-conditioned stimulus is paired with an aversive unconditioned stimulus leading the subjects to display behavioural signs of fear. Decades of research into the neural bases of this simple behavioural paradigm uncovered that the amygdala, a complex structure comprised of several interconnected nuclei, is an essential part of the neural circuits required for the acquisition, consolidation and expression of fear memory. However, emerging evidence from the confluence of electrophysiological, tract tracing, imaging, molecular, optogenetic and chemogenetic methodologies, reveals that fear learning is mediated by multiple connections between several amygdala nuclei and their distributed targets, dynamical changes in plasticity in local circuit elements as well as neuromodulatory mechanisms that promote synaptic plasticity. To uncover these complex relations and analyse multi-modal data sets acquired from these studies, we argue that biologically realistic computational modelling, in conjunction with experiments, offers an opportunity to advance our understanding of the neural circuit mechanisms of fear learning and to address how their dysfunction may lead to maladaptive fear responses in mental disorders.

Assimilation of Biophysical Neuronal Dynamics in Neuromorphic VLSI.

PubMed

Wang, Jun; Breen, Daniel; Akinin, Abraham; Broccard, Frederic; Abarbanel, Henry D I; Cauwenberghs, Gert

2017-12-01

Representing the biophysics of neuronal dynamics and behavior offers a principled analysis-by-synthesis approach toward understanding mechanisms of nervous system functions. We report on a set of procedures assimilating and emulating neurobiological data on a neuromorphic very large scale integrated (VLSI) circuit. The analog VLSI chip, NeuroDyn, features 384 digitally programmable parameters specifying for 4 generalized Hodgkin-Huxley neurons coupled through 12 conductance-based chemical synapses. The parameters also describe reversal potentials, maximal conductances, and spline regressed kinetic functions for ion channel gating variables. In one set of experiments, we assimilated membrane potential recorded from one of the neurons on the chip to the model structure upon which NeuroDyn was designed using the known current input sequence. We arrived at the programmed parameters except for model errors due to analog imperfections in the chip fabrication. In a related set of experiments, we replicated songbird individual neuron dynamics on NeuroDyn by estimating and configuring parameters extracted using data assimilation from intracellular neural recordings. Faithful emulation of detailed biophysical neural dynamics will enable the use of NeuroDyn as a tool to probe electrical and molecular properties of functional neural circuits. Neuroscience applications include studying the relationship between molecular properties of neurons and the emergence of different spike patterns or different brain behaviors. Clinical applications include studying and predicting effects of neuromodulators or neurodegenerative diseases on ion channel kinetics.

How to turn a genetic circuit into a synthetic tunable oscillator, or a bistable switch.

PubMed

Marucci, Lucia; Barton, David A W; Cantone, Irene; Ricci, Maria Aurelia; Cosma, Maria Pia; Santini, Stefania; di Bernardo, Diego; di Bernardo, Mario

2009-12-07

Systems and Synthetic Biology use computational models of biological pathways in order to study in silico the behaviour of biological pathways. Mathematical models allow to verify biological hypotheses and to predict new possible dynamical behaviours. Here we use the tools of non-linear analysis to understand how to change the dynamics of the genes composing a novel synthetic network recently constructed in the yeast Saccharomyces cerevisiae for In-vivo Reverse-engineering and Modelling Assessment (IRMA). Guided by previous theoretical results that make the dynamics of a biological network depend on its topological properties, through the use of simulation and continuation techniques, we found that the network can be easily turned into a robust and tunable synthetic oscillator or a bistable switch. Our results provide guidelines to properly re-engineering in vivo the network in order to tune its dynamics.

Dynamic simulation of perturbation responses in a closed-loop virtual arm model.

PubMed

Du, Yu-Fan; He, Xin; Lan, Ning

2010-01-01

A closed-loop virtual arm (VA) model has been developed in SIMULINK environment by adding spinal reflex circuits and propriospinal neural networks to the open-loop VA model developed in early study [1]. An improved virtual muscle model (VM4.0) is used to speed up simulation and to generate more precise recruitment of muscle force at low levels of muscle activation. Time delays in the reflex loops are determined by their synaptic connections and afferent transmission back to the spinal cord. Reflex gains are properly selected so that closed-loop responses are stable. With the closed-loop VA model, we are developing an approach to evaluate system behaviors by dynamic simulation of perturbation responses. Joint stiffness is calculated based on simulated perturbation responses by a least-squares algorithm in MATLAB. This method of dynamic simulation will be essential for further evaluation of feedforward and reflex control of arm movement and position.

Architecture-Dependent Robustness and Bistability in a Class of Genetic Circuits

PubMed Central

Zhang, Jiajun; Yuan, Zhanjiang; Li, Han-Xiong; Zhou, Tianshou

2010-01-01

Understanding the relationship between genotype and phenotype is a challenge in systems biology. An interesting yet related issue is why a particular circuit topology is present in a cell when the same function can supposedly be obtained from an alternative architecture. Here we analyzed two topologically equivalent genetic circuits of coupled positive and negative feedback loops, named NAT and ALT circuits, respectively. The computational search for the oscillation volume of the entire biologically reasonable parameter region through large-scale random samplings shows that the NAT circuit exhibits a distinctly larger fraction of the oscillatory region than the ALT circuit. Such a global robustness difference between two circuits is supplemented by analyzing local robustness, including robustness to parameter perturbations and to molecular noise. In addition, detailed dynamical analysis shows that the molecular noise of both circuits can induce transient switching of the different mechanism between a stable steady state and a stable limit cycle. Our investigation on robustness and dynamics through examples provides insights into the relationship between network architecture and its function. PMID:20712986

Control model design to limit DC-link voltage during grid fault in a dfig variable speed wind turbine

NASA Astrophysics Data System (ADS)

Nwosu, Cajethan M.; Ogbuka, Cosmas U.; Oti, Stephen E.

2017-08-01

This paper presents a control model design capable of inhibiting the phenomenal rise in the DC-link voltage during grid- fault condition in a variable speed wind turbine. Against the use of power circuit protection strategies with inherent limitations in fault ride-through capability, a control circuit algorithm capable of limiting the DC-link voltage rise which in turn bears dynamics that has direct influence on the characteristics of the rotor voltage especially during grid faults is here proposed. The model results so obtained compare favorably with the simulation results as obtained in a MATLAB/SIMULINK environment. The generated model may therefore be used to predict near accurately the nature of DC-link voltage variations during fault given some factors which include speed and speed mode of operation, the value of damping resistor relative to half the product of inner loop current control bandwidth and the filter inductance.

Memristive Model of the Barnacle Giant Muscle Fibers

NASA Astrophysics Data System (ADS)

Sah, Maheshwar Pd.; Kim, Hyongsuk; Eroglu, Abdullah; Chua, Leon

The generation of action potentials (oscillations) in biological systems is a complex, yet poorly understood nonlinear dynamical phenomenon involving ions. This paper reveals that the time-varying calcium ion and the time-varying potassium ion, which are essential for generating action potentials in Barnacle giant muscle fibers are in fact generic memristors in the perspective of electrical circuit theory. We will show that these two ions exhibit all the fingerprints of memristors from the equations of the Morris-Lecar model of the Barnacle giant muscle fibers. This paper also gives a textbook reference to understand the difference between memristor and nonlinear resistor via analysis of the potassium ion-channel memristor and calcium ion-channel nonlinear resistor. We will also present a comprehensive in-depth analysis of the generation of action potentials (oscillations) in memristive Morris-Lecar model using small-signal circuit model and the Hopf bifurcation theorem.

Study on the Mathematical Model of Dielectric Recovery Characteristics in High Voltage SF6 Circuit Breaker

NASA Astrophysics Data System (ADS)

Lin, Xin; Wang, Feiming; Xu, Jianyuan; Xia, Yalong; Liu, Weidong

2016-03-01

According to the stream theory, this paper proposes a mathematical model of the dielectric recovery characteristic based on the two-temperature ionization equilibrium equation. Taking the dynamic variation of charged particle's ionization and attachment into account, this model can be used in collaboration with the Coulomb collision model, which gives the relationship of the heavy particle temperature and electron temperature to calculate the electron density and temperature under different pressure and electric field conditions, so as to deliver the breakdown electric field strength under different pressure conditions. Meanwhile an experiment loop of the circuit breaker has been built to measure the breakdown voltage. It is shown that calculated results are in conformity with experiment results on the whole while results based on the stream criterion are larger than experiment results. This indicates that the mathematical model proposed here is more accurate for calculating the dielectric recovery characteristic, it is derived from the stream model with some improvement and refinement and has great significance for increasing the simulation accuracy of circuit breaker's interruption characteristic. supported by Science and Technology Project of State Grid Corporation of China (No. GY17201200063), National Natural Science Foundation of China (No. 51277123), Basic Research Project of Liaoning Key Laboratory of Education Department (LZ2015055)

Genetic programs constructed from layered logic gates in single cells

PubMed Central

Moon, Tae Seok; Lou, Chunbo; Tamsir, Alvin; Stanton, Brynne C.; Voigt, Christopher A.

2014-01-01

Genetic programs function to integrate environmental sensors, implement signal processing algorithms and control expression dynamics1. These programs consist of integrated genetic circuits that individually implement operations ranging from digital logic to dynamic circuits2–6, and they have been used in various cellular engineering applications, including the implementation of process control in metabolic networks and the coordination of spatial differentiation in artificial tissues. A key limitation is that the circuits are based on biochemical interactions occurring in the confined volume of the cell, so the size of programs has been limited to a few circuits1,7. Here we apply part mining and directed evolution to build a set of transcriptional AND gates in Escherichia coli. Each AND gate integrates two promoter inputs and controls one promoter output. This allows the gates to be layered by having the output promoter of an upstream circuit serve as the input promoter for a downstream circuit. Each gate consists of a transcription factor that requires a second chaperone protein to activate the output promoter. Multiple activator–chaperone pairs are identified from type III secretion pathways in different strains of bacteria. Directed evolution is applied to increase the dynamic range and orthogonality of the circuits. These gates are connected in different permutations to form programs, the largest of which is a 4-input AND gate that consists of 3 circuits that integrate 4 inducible systems, thus requiring 11 regulatory proteins. Measuring the performance of individual gates is sufficient to capture the behaviour of the complete program. Errors in the output due to delays (faults), a common problem for layered circuits, are not observed. This work demonstrates the successful layering of orthogonal logic gates, a design strategy that could enable the construction of large, integrated circuits in single cells. PMID:23041931

Effect of Sensors on the Reliability and Control Performance of Power Circuits in the Web of Things (WoT)

PubMed Central

Bae, Sungwoo; Kim, Myungchin

2016-01-01

In order to realize a true WoT environment, a reliable power circuit is required to ensure interconnections among a range of WoT devices. This paper presents research on sensors and their effects on the reliability and response characteristics of power circuits in WoT devices. The presented research can be used in various power circuit applications, such as energy harvesting interfaces, photovoltaic systems, and battery management systems for the WoT devices. As power circuits rely on the feedback from voltage/current sensors, the system performance is likely to be affected by the sensor failure rates, sensor dynamic characteristics, and their interface circuits. This study investigated how the operational availability of the power circuits is affected by the sensor failure rates by performing a quantitative reliability analysis. In the analysis process, this paper also includes the effects of various reconstruction and estimation techniques used in power processing circuits (e.g., energy harvesting circuits and photovoltaic systems). This paper also reports how the transient control performance of power circuits is affected by sensor interface circuits. With the frequency domain stability analysis and circuit simulation, it was verified that the interface circuit dynamics may affect the transient response characteristics of power circuits. The verification results in this paper showed that the reliability and control performance of the power circuits can be affected by the sensor types, fault tolerant approaches against sensor failures, and the response characteristics of the sensor interfaces. The analysis results were also verified by experiments using a power circuit prototype. PMID:27608020

Nonlinear dynamics based digital logic and circuits.

PubMed

Kia, Behnam; Lindner, John F; Ditto, William L

2015-01-01

We discuss the role and importance of dynamics in the brain and biological neural networks and argue that dynamics is one of the main missing elements in conventional Boolean logic and circuits. We summarize a simple dynamics based computing method, and categorize different techniques that we have introduced to realize logic, functionality, and programmability. We discuss the role and importance of coupled dynamics in networks of biological excitable cells, and then review our simple coupled dynamics based method for computing. In this paper, for the first time, we show how dynamics can be used and programmed to implement computation in any given base, including but not limited to base two.

Coherent quantum dynamics launched by incoherent relaxation in a quantum circuit simulator of a light-harvesting complex

NASA Astrophysics Data System (ADS)

Chin, A. W.; Mangaud, E.; Atabek, O.; Desouter-Lecomte, M.

2018-06-01

Engineering and harnessing coherent excitonic transport in organic nanostructures has recently been suggested as a promising way towards improving manmade light-harvesting materials. However, realizing and testing the dissipative system-environment models underlying these proposals is presently very challenging in supramolecular materials. A promising alternative is to use simpler and highly tunable "quantum simulators" built from programmable qubits, as recently achieved in a superconducting circuit by Potočnik et al. [A. Potočnik et al., Nat. Commun. 9, 904 (2018), 10.1038/s41467-018-03312-x]. We simulate the real-time dynamics of an exciton coupled to a quantum bath as it moves through a network based on the quantum circuit of Potočnik et al. Using the numerically exact hierarchical equations of motion to capture the open quantum system dynamics, we find that an ultrafast but completely incoherent relaxation from a high-lying "bright" exciton into a doublet of closely spaced "dark" excitons can spontaneously generate electronic coherences and oscillatory real-space motion across the network (quantum beats). Importantly, we show that this behavior also survives when the environmental noise is classically stochastic (effectively high temperature), as in present experiments. These predictions highlight the possibilities of designing matched electronic and spectral noise structures for robust coherence generation that do not require coherent excitation or cold environments.

Dynamic impedance compensation for wireless power transfer using conjugate power

NASA Astrophysics Data System (ADS)

Liu, Suqi; Tan, Jianping; Wen, Xue

2018-02-01

Wireless power transfer (WPT) via coupled magnetic resonances has been in development for over a decade. However, the frequency splitting phenomenon occurs in the over-coupled region. Thus, the output power of the two-coil system achieves the maximum output power at the two splitting angular frequencies, and not at the natural resonant angular frequency. According to the maximum power transfer theorem, the impedance compensation method was adopted in many WPT projects. However, it remains a challenge to achieve the maximum output power and transmission efficiency in a fixed-frequency mode. In this study, dynamic impedance compensation for WPT was presented by utilizing the compensator within a virtual three-coil WPT system. First, the circuit model was established and transfer characteristics of a system were studied by utilizing circuit theories. Second, the power superposition of the WPT system was carefully researched. When a pair of compensating coils was inserted into the transmitter loop, the conjugate power of the compensator loop was created via magnetic coupling of the two compensating coils that insert into the transmitter loop. The mechanism for dynamic impedance compensation for wireless power transfer was then provided by investigating a virtual three-coil WPT system. Finally, the experimental circuit of a virtual three-coil WPT system was designed, and experimental results are consistent with the theoretical analysis, which achieves the maximum output power and transmission efficiency.

Sheath expansion and plasma dynamics in the presence of electrode evaporation: Application to a vacuum circuit breaker

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sarrailh, P.; LAPLACE, CNRS, F-31062 Toulouse; Schneider Electric, Centre de Recherche 38 TEC, 38050 Grenoble Cedex 09

2009-09-01

During the postarc dielectric recovery phase in a vacuum circuit breaker, a cathode sheath forms and expels the plasma from the electrode gap. The success or failure of current breaking depends on how efficiently the plasma is expelled from the electrode gap. The sheath expansion in the postarc phase can be compared to sheath expansion in plasma immersion ion implantation except that collisions between charged particles and atoms generated by electrode evaporation may become important in a vacuum circuit breaker. In this paper, we show that electrode evaporation plays a significant role in the dynamics of the sheath expansion inmore » this context not only because charged particle transport is no longer collisionless but also because the neutral flow due to evaporation and temperature gradients may push the plasma toward one of the electrodes. Using a hybrid model of the nonequilibrium postarc plasma and cathode sheath coupled with a direct simulation Monte Carlo method to describe collisions between heavy species, we present a parametric study of the sheath and plasma dynamics and of the time needed for the sheath to expel the plasma from the gap for different values of plasma density and electrode temperatures at the beginning of the postarc phase. This work constitutes a preliminary step toward understanding and quantifying the risk of current breaking failure of a vacuum arc.« less

Sheath expansion and plasma dynamics in the presence of electrode evaporation: Application to a vacuum circuit breaker

NASA Astrophysics Data System (ADS)

Sarrailh, P.; Garrigues, L.; Hagelaar, G. J. M.; Boeuf, J. P.; Sandolache, G.; Rowe, S.

2009-09-01

During the postarc dielectric recovery phase in a vacuum circuit breaker, a cathode sheath forms and expels the plasma from the electrode gap. The success or failure of current breaking depends on how efficiently the plasma is expelled from the electrode gap. The sheath expansion in the postarc phase can be compared to sheath expansion in plasma immersion ion implantation except that collisions between charged particles and atoms generated by electrode evaporation may become important in a vacuum circuit breaker. In this paper, we show that electrode evaporation plays a significant role in the dynamics of the sheath expansion in this context not only because charged particle transport is no longer collisionless but also because the neutral flow due to evaporation and temperature gradients may push the plasma toward one of the electrodes. Using a hybrid model of the nonequilibrium postarc plasma and cathode sheath coupled with a direct simulation Monte Carlo method to describe collisions between heavy species, we present a parametric study of the sheath and plasma dynamics and of the time needed for the sheath to expel the plasma from the gap for different values of plasma density and electrode temperatures at the beginning of the postarc phase. This work constitutes a preliminary step toward understanding and quantifying the risk of current breaking failure of a vacuum arc.

Optimization,Modeling, and Control: Applications to Klystron Designing and Hepatitis C Virus Dynamics

NASA Astrophysics Data System (ADS)

Lankford, George Bernard

In this dissertation, we address applying mathematical and numerical techniques in the fields of high energy physics and biomedical sciences. The first portion of this thesis presents a method for optimizing the design of klystron circuits. A klystron is an electron beam tube lined with cavities that emit resonant frequencies to velocity modulate electrons that pass through the tube. Radio frequencies (RF) inserted in the klystron are amplified due to the velocity modulation of the electrons. The routine described in this work automates the selection of cavity positions, resonant frequencies, quality factors, and other circuit parameters to maximize the efficiency with required gain. The method is based on deterministic sampling methods. We will describe the procedure and give several examples for both narrow and wide band klystrons, using the klystron codes AJDISK (Java) and TESLA (Python). The rest of the dissertation is dedicated to developing, calibrating and using a mathematical model for hepatitis C dynamics with triple drug combination therapy. Groundbreaking new drugs, called direct acting antivirals, have been introduced recently to fight off chronic hepatitis C virus infection. The model we introduce is for hepatitis C dynamics treated with the direct acting antiviral drug, telaprevir, along with traditional interferon and ribavirin treatments to understand how this therapy affects the viral load of patients exhibiting different types of response. We use sensitivity and identifiability techniques to determine which parameters can be best estimated from viral load data. We use these estimations to give patient-specific fits of the model to partial viral response, end-of-treatment response, and breakthrough patients. We will then revise the model to incorporate an immune response dynamic to more accurately describe the dynamics. Finally, we will implement a suboptimal control to acquire a drug treatment regimen that will alleviate the systemic cost associated with constant drug treatment.

Modeling and Analysis of a Fractional-Order Generalized Memristor-Based Chaotic System and Circuit Implementation

NASA Astrophysics Data System (ADS)

Yang, Ningning; Xu, Cheng; Wu, Chaojun; Jia, Rong; Liu, Chongxin

2017-12-01

Memristor is a nonlinear “missing circuit element”, that can easily achieve chaotic oscillation. Memristor-based chaotic systems have received more and more attention. Research shows that fractional-order systems are more close to real systems. As an important parameter, the order can increase the flexibility and degree of freedom of the system. In this paper, a fractional-order generalized memristor, which consists of a diode bridge and a parallel circuit with an equivalent unit circuit and a linear resistance, is proposed. Frequency and electrical characteristics of the fractional-order memristor are analyzed. A chain structure circuit is used to implement the fractional-order unit circuit. Then replacing the conventional Chua’s diode by the fractional-order generalized memristor, a fractional-order memristor-based chaotic circuit is proposed. A large amount of research work has been done to investigate the influence of the order on the dynamical behaviors of the fractional-order memristor-based chaotic circuit. Varying with the order, the system enters the chaotic state from the periodic state through the Hopf bifurcation and period-doubling bifurcation. The chaotic state of the system has two types of attractors: single-scroll and double-scroll attractor. The stability theory of fractional-order systems is used to determine the minimum order occurring Hopf bifurcation. And the influence of the initial value on the system is analyzed. Circuit simulations are designed to verify the results of theoretical analysis and numerical simulation.

Dynamic sensory cues shape song structure in Drosophila

NASA Astrophysics Data System (ADS)

Coen, Philip; Clemens, Jan; Weinstein, Andrew J.; Pacheco, Diego A.; Deng, Yi; Murthy, Mala

2014-03-01

The generation of acoustic communication signals is widespread across the animal kingdom, and males of many species, including Drosophilidae, produce patterned courtship songs to increase their chance of success with a female. For some animals, song structure can vary considerably from one rendition to the next; neural noise within pattern generating circuits is widely assumed to be the primary source of such variability, and statistical models that incorporate neural noise are successful at reproducing the full variation present in natural songs. In direct contrast, here we demonstrate that much of the pattern variability in Drosophila courtship song can be explained by taking into account the dynamic sensory experience of the male. In particular, using a quantitative behavioural assay combined with computational modelling, we find that males use fast modulations in visual and self-motion signals to pattern their songs, a relationship that we show is evolutionarily conserved. Using neural circuit manipulations, we also identify the pathways involved in song patterning choices and show that females are sensitive to song features. Our data not only demonstrate that Drosophila song production is not a fixed action pattern, but establish Drosophila as a valuable new model for studies of rapid decision-making under both social and naturalistic conditions.

Synaptic augmentation in a cortical circuit model reproduces serial dependence in visual working memory

PubMed Central

D’Esposito, Mark

2017-01-01

Recent work has established that visual working memory is subject to serial dependence: current information in memory blends with that from the recent past as a function of their similarity. This tuned temporal smoothing likely promotes the stability of memory in the face of noise and occlusion. Serial dependence accumulates over several seconds in memory and deteriorates with increased separation between trials. While this phenomenon has been extensively characterized in behavior, its neural mechanism is unknown. In the present study, we investigate the circuit-level origins of serial dependence in a biophysical model of cortex. We explore two distinct kinds of mechanisms: stable persistent activity during the memory delay period and dynamic “activity-silent” synaptic plasticity. We find that networks endowed with both strong reverberation to support persistent activity and dynamic synapses can closely reproduce behavioral serial dependence. Specifically, elevated activity drives synaptic augmentation, which biases activity on the subsequent trial, giving rise to a spatiotemporally tuned shift in the population response. Our hybrid neural model is a theoretical advance beyond abstract mathematical characterizations, offers testable hypotheses for physiological research, and demonstrates the power of biological insights to provide a quantitative explanation of human behavior. PMID:29244810

p53 activated by AND gate genetic circuit under radiation and hypoxia for targeted cancer gene therapy

PubMed Central

Ding, Miao; Li, Rong; He, Rong; Wang, Xingyong; Yi, Qijian; Wang, Weidong

2015-01-01

Radio-activated gene therapy has been developed as a novel therapeutic strategy against cancer; however, expression of therapeutic gene in peritumoral tissues will result in unacceptable toxicity to normal cells. To restrict gene expression in targeted tumor mass, we used hypoxia and radiation tolerance features of tumor cells to develop a synthetic AND gate genetic circuit through connecting radiation sensitivity promoter cArG6, heat shock response elements SNF1, HSF1 and HSE4 with retroviral vector plxsn. Their construction and dynamic activity process were identified through downstream enhanced green fluorescent protein and wtp53 expression in non-small cell lung cancer A549 cells and in a nude mice model. The result showed that AND gate genetic circuit could be activated by lower required radiation dose (6 Gy) and after activated, AND gate could induce significant apoptosis effects and growth inhibition of cancer cells in vitro and in vivo. The radiation- and hypoxia-activated AND gate genetic circuit, which could lead to more powerful target tumoricidal activity represented a promising strategy for both targeted and effective gene therapy of human lung adenocarcinoma and low dose activation character of the AND gate genetic circuit implied that this model could be further exploited to decrease side-effects of clinical radiation therapy. PMID:26177264

Programming mRNA decay to modulate synthetic circuit resource allocation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Venturelli, Ophelia S.; Tei, Mika; Bauer, Stefan

Synthetic circuits embedded in host cells compete with cellular processes for limited intracellular resources. Here we show how funnelling of cellular resources, after global transcriptome degradation by the sequence-dependent endoribonuclease MazF, to a synthetic circuit can increase production. Target genes are protected from MazF activity by recoding the gene sequence to eliminate recognition sites, while preserving the amino acid sequence. The expression of a protected fluorescent reporter and flux of a high-value metabolite are significantly enhanced using this genome-scale control strategy. Proteomics measurements discover a host factor in need of protection to improve resource redistribution activity. A computational model demonstratesmore » that the MazF mRNA-decay feedback loop enables proportional control of MazF in an optimal operating regime. Transcriptional profiling of MazF-induced cells elucidates the dynamic shifts in transcript abundance and discovers regulatory design elements. Altogether, our results suggest that manipulation of cellular resource allocation is a key control parameter for synthetic circuit design.« less

Programming mRNA decay to modulate synthetic circuit resource allocation

DOE PAGES

Venturelli, Ophelia S.; Tei, Mika; Bauer, Stefan; ...

2017-04-26

Synthetic circuits embedded in host cells compete with cellular processes for limited intracellular resources. Here we show how funnelling of cellular resources, after global transcriptome degradation by the sequence-dependent endoribonuclease MazF, to a synthetic circuit can increase production. Target genes are protected from MazF activity by recoding the gene sequence to eliminate recognition sites, while preserving the amino acid sequence. The expression of a protected fluorescent reporter and flux of a high-value metabolite are significantly enhanced using this genome-scale control strategy. Proteomics measurements discover a host factor in need of protection to improve resource redistribution activity. A computational model demonstratesmore » that the MazF mRNA-decay feedback loop enables proportional control of MazF in an optimal operating regime. Transcriptional profiling of MazF-induced cells elucidates the dynamic shifts in transcript abundance and discovers regulatory design elements. Altogether, our results suggest that manipulation of cellular resource allocation is a key control parameter for synthetic circuit design.« less

Biophysical Neural Spiking, Bursting, and Excitability Dynamics in Reconfigurable Analog VLSI.

PubMed

Yu, T; Sejnowski, T J; Cauwenberghs, G

2011-10-01

We study a range of neural dynamics under variations in biophysical parameters underlying extended Morris-Lecar and Hodgkin-Huxley models in three gating variables. The extended models are implemented in NeuroDyn, a four neuron, twelve synapse continuous-time analog VLSI programmable neural emulation platform with generalized channel kinetics and biophysical membrane dynamics. The dynamics exhibit a wide range of time scales extending beyond 100 ms neglected in typical silicon models of tonic spiking neurons. Circuit simulations and measurements show transition from tonic spiking to tonic bursting dynamics through variation of a single conductance parameter governing calcium recovery. We similarly demonstrate transition from graded to all-or-none neural excitability in the onset of spiking dynamics through the variation of channel kinetic parameters governing the speed of potassium activation. Other combinations of variations in conductance and channel kinetic parameters give rise to phasic spiking and spike frequency adaptation dynamics. The NeuroDyn chip consumes 1.29 mW and occupies 3 mm × 3 mm in 0.5 μm CMOS, supporting emerging developments in neuromorphic silicon-neuron interfaces.

Causal Role of Thalamic Interneurons in Brain State Transitions: A Study Using a Neural Mass Model Implementing Synaptic Kinetics

PubMed Central

Bhattacharya, Basabdatta Sen; Bond, Thomas P.; O'Hare, Louise; Turner, Daniel; Durrant, Simon J.

2016-01-01

Experimental studies on the Lateral Geniculate Nucleus (LGN) of mammals and rodents show that the inhibitory interneurons (IN) receive around 47.1% of their afferents from the retinal spiking neurons, and constitute around 20–25% of the LGN cell population. However, there is a definite gap in knowledge about the role and impact of IN on thalamocortical dynamics in both experimental and model-based research. We use a neural mass computational model of the LGN with three neural populations viz. IN, thalamocortical relay (TCR), thalamic reticular nucleus (TRN), to study the causality of IN on LGN oscillations and state-transitions. The synaptic information transmission in the model is implemented with kinetic modeling, facilitating the linking of low-level cellular attributes with high-level population dynamics. The model is parameterized and tuned to simulate alpha (8–13 Hz) rhythm that is dominant in both Local Field Potential (LFP) of LGN and electroencephalogram (EEG) of visual cortex in an awake resting state with eyes closed. The results show that: First, the response of the TRN is suppressed in the presence of IN in the circuit; disconnecting the IN from the circuit effects a dramatic change in the model output, displaying high amplitude synchronous oscillations within the alpha band in both TCR and TRN. These observations conform to experimental reports implicating the IN as the primary inhibitory modulator of LGN dynamics in a cognitive state, and that reduced cognition is achieved by suppressing the TRN response. Second, the model validates steady state visually evoked potential response in humans corresponding to periodic input stimuli; however, when the IN is disconnected from the circuit, the output power spectra do not reflect the input frequency. This agrees with experimental reports underpinning the role of IN in efficient retino-geniculate information transmission. Third, a smooth transition from alpha to theta band is observed by progressive decrease of neurotransmitter concentrations in the synaptic clefts; however, the transition is abrupt with removal of the IN circuitry in the model. The results imply a role of IN toward maintaining homeostasis in the LGN by suppressing any instability that may arise due to anomalous synaptic attributes. PMID:27899890

Microendophenotypes of psychiatric disorders: phenotypes of psychiatric disorders at the level of molecular dynamics, synapses, neurons, and neural circuits.

PubMed

Kida, S; Kato, T

2015-01-01

Psychiatric disorders are caused not only by genetic factors but also by complicated factors such as environmental ones. Moreover, environmental factors are rarely quantitated as biological and biochemical indicators, making it extremely difficult to understand the pathological conditions of psychiatric disorders as well as their underlying pathogenic mechanisms. Additionally, we have actually no other option but to perform biological studies on postmortem human brains that display features of psychiatric disorders, thereby resulting in a lack of experimental materials to characterize the basic biology of these disorders. From these backgrounds, animal, tissue, or cell models that can be used in basic research are indispensable to understand biologically the pathogenic mechanisms of psychiatric disorders. In this review, we discuss the importance of microendophenotypes of psychiatric disorders, i.e., phenotypes at the level of molecular dynamics, neurons, synapses, and neural circuits, as targets of basic research on these disorders.

Xyce

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomquist, Heidi K.; Fixel, Deborah A.; Fett, David Brian

The Xyce Parallel Electronic Simulator simulates electronic circuit behavior in DC, AC, HB, MPDE and transient mode using standard analog (DAE) and/or device (PDE) device models including several age and radiation aware devices. It supports a variety of computing platforms (both serial and parallel) computers. Lastly, it uses a variety of modern solution algorithms dynamic parallel load-balancing and iterative solvers.

Cannabinoids disrupt memory encoding by functionally isolating hippocampal CA1 from CA3.

PubMed

Sandler, Roman A; Fetterhoff, Dustin; Hampson, Robert E; Deadwyler, Sam A; Marmarelis, Vasilis Z

2017-07-01

Much of the research on cannabinoids (CBs) has focused on their effects at the molecular and synaptic level. However, the effects of CBs on the dynamics of neural circuits remains poorly understood. This study aims to disentangle the effects of CBs on the functional dynamics of the hippocampal Schaffer collateral synapse by using data-driven nonparametric modeling. Multi-unit activity was recorded from rats doing an working memory task in control sessions and under the influence of exogenously administered tetrahydrocannabinol (THC), the primary CB found in marijuana. It was found that THC left firing rate unaltered and only slightly reduced theta oscillations. Multivariate autoregressive models, estimated from spontaneous spiking activity, were then used to describe the dynamical transformation from CA3 to CA1. They revealed that THC served to functionally isolate CA1 from CA3 by reducing feedforward excitation and theta information flow. The functional isolation was compensated by increased feedback excitation within CA1, thus leading to unaltered firing rates. Finally, both of these effects were shown to be correlated with memory impairments in the working memory task. By elucidating the circuit mechanisms of CBs, these results help close the gap in knowledge between the cellular and behavioral effects of CBs.

Cannabinoids disrupt memory encoding by functionally isolating hippocampal CA1 from CA3

PubMed Central

Fetterhoff, Dustin; Hampson, Robert E.; Deadwyler, Sam A.; Marmarelis, Vasilis Z.

2017-01-01

Much of the research on cannabinoids (CBs) has focused on their effects at the molecular and synaptic level. However, the effects of CBs on the dynamics of neural circuits remains poorly understood. This study aims to disentangle the effects of CBs on the functional dynamics of the hippocampal Schaffer collateral synapse by using data-driven nonparametric modeling. Multi-unit activity was recorded from rats doing an working memory task in control sessions and under the influence of exogenously administered tetrahydrocannabinol (THC), the primary CB found in marijuana. It was found that THC left firing rate unaltered and only slightly reduced theta oscillations. Multivariate autoregressive models, estimated from spontaneous spiking activity, were then used to describe the dynamical transformation from CA3 to CA1. They revealed that THC served to functionally isolate CA1 from CA3 by reducing feedforward excitation and theta information flow. The functional isolation was compensated by increased feedback excitation within CA1, thus leading to unaltered firing rates. Finally, both of these effects were shown to be correlated with memory impairments in the working memory task. By elucidating the circuit mechanisms of CBs, these results help close the gap in knowledge between the cellular and behavioral effects of CBs. PMID:28686594

Interaction between telencephalic signals and respiratory dynamics in songbirds

PubMed Central

Méndez, Jorge M.; Mindlin, Gabriel B.

2012-01-01

The mechanisms by which telencephalic areas affect motor activities are largely unknown. They could either take over motor control from downstream motor circuits or interact with the intrinsic dynamics of these circuits. Both models have been proposed for telencephalic control of respiration during learned vocal behavior in birds. The interactive model postulates that simple signals from the telencephalic song control areas are sufficient to drive the nonlinear respiratory network into producing complex temporal sequences. We tested this basic assumption by electrically stimulating telencephalic song control areas and analyzing the resulting respiratory patterns in zebra finches and in canaries. We found strong evidence for interaction between the rhythm of stimulation and the intrinsic respiratory rhythm, including naturally emerging subharmonic behavior and integration of lateralized telencephalic input. The evidence for clear interaction in our experimental paradigm suggests that telencephalic vocal control also uses a similar mechanism. Furthermore, species differences in the response of the respiratory system to stimulation show parallels to differences in the respiratory patterns of song, suggesting that the interactive production of respiratory rhythms is manifested in species-specific specialization of the involved circuitry. PMID:22402649

Plasticity in single neuron and circuit computations

NASA Astrophysics Data System (ADS)

Destexhe, Alain; Marder, Eve

2004-10-01

Plasticity in neural circuits can result from alterations in synaptic strength or connectivity, as well as from changes in the excitability of the neurons themselves. To better understand the role of plasticity in the brain, we need to establish how brain circuits work and the kinds of computations that different circuit structures achieve. By linking theoretical and experimental studies, we are beginning to reveal the consequences of plasticity mechanisms for network dynamics, in both simple invertebrate circuits and the complex circuits of mammalian cerebral cortex.

Hybrid Cubature Kalman filtering for identifying nonlinear models from sampled recording: Estimation of neuronal dynamics.

PubMed

Madi, Mahmoud K; Karameh, Fadi N

2017-01-01

Kalman filtering methods have long been regarded as efficient adaptive Bayesian techniques for estimating hidden states in models of linear dynamical systems under Gaussian uncertainty. Recent advents of the Cubature Kalman filter (CKF) have extended this efficient estimation property to nonlinear systems, and also to hybrid nonlinear problems where by the processes are continuous and the observations are discrete (continuous-discrete CD-CKF). Employing CKF techniques, therefore, carries high promise for modeling many biological phenomena where the underlying processes exhibit inherently nonlinear, continuous, and noisy dynamics and the associated measurements are uncertain and time-sampled. This paper investigates the performance of cubature filtering (CKF and CD-CKF) in two flagship problems arising in the field of neuroscience upon relating brain functionality to aggregate neurophysiological recordings: (i) estimation of the firing dynamics and the neural circuit model parameters from electric potentials (EP) observations, and (ii) estimation of the hemodynamic model parameters and the underlying neural drive from BOLD (fMRI) signals. First, in simulated neural circuit models, estimation accuracy was investigated under varying levels of observation noise (SNR), process noise structures, and observation sampling intervals (dt). When compared to the CKF, the CD-CKF consistently exhibited better accuracy for a given SNR, sharp accuracy increase with higher SNR, and persistent error reduction with smaller dt. Remarkably, CD-CKF accuracy shows only a mild deterioration for non-Gaussian process noise, specifically with Poisson noise, a commonly assumed form of background fluctuations in neuronal systems. Second, in simulated hemodynamic models, parametric estimates were consistently improved under CD-CKF. Critically, time-localization of the underlying neural drive, a determinant factor in fMRI-based functional connectivity studies, was significantly more accurate under CD-CKF. In conclusion, and with the CKF recently benchmarked against other advanced Bayesian techniques, the CD-CKF framework could provide significant gains in robustness and accuracy when estimating a variety of biological phenomena models where the underlying process dynamics unfold at time scales faster than those seen in collected measurements.

Hybrid Cubature Kalman filtering for identifying nonlinear models from sampled recording: Estimation of neuronal dynamics

PubMed Central

2017-01-01

Kalman filtering methods have long been regarded as efficient adaptive Bayesian techniques for estimating hidden states in models of linear dynamical systems under Gaussian uncertainty. Recent advents of the Cubature Kalman filter (CKF) have extended this efficient estimation property to nonlinear systems, and also to hybrid nonlinear problems where by the processes are continuous and the observations are discrete (continuous-discrete CD-CKF). Employing CKF techniques, therefore, carries high promise for modeling many biological phenomena where the underlying processes exhibit inherently nonlinear, continuous, and noisy dynamics and the associated measurements are uncertain and time-sampled. This paper investigates the performance of cubature filtering (CKF and CD-CKF) in two flagship problems arising in the field of neuroscience upon relating brain functionality to aggregate neurophysiological recordings: (i) estimation of the firing dynamics and the neural circuit model parameters from electric potentials (EP) observations, and (ii) estimation of the hemodynamic model parameters and the underlying neural drive from BOLD (fMRI) signals. First, in simulated neural circuit models, estimation accuracy was investigated under varying levels of observation noise (SNR), process noise structures, and observation sampling intervals (dt). When compared to the CKF, the CD-CKF consistently exhibited better accuracy for a given SNR, sharp accuracy increase with higher SNR, and persistent error reduction with smaller dt. Remarkably, CD-CKF accuracy shows only a mild deterioration for non-Gaussian process noise, specifically with Poisson noise, a commonly assumed form of background fluctuations in neuronal systems. Second, in simulated hemodynamic models, parametric estimates were consistently improved under CD-CKF. Critically, time-localization of the underlying neural drive, a determinant factor in fMRI-based functional connectivity studies, was significantly more accurate under CD-CKF. In conclusion, and with the CKF recently benchmarked against other advanced Bayesian techniques, the CD-CKF framework could provide significant gains in robustness and accuracy when estimating a variety of biological phenomena models where the underlying process dynamics unfold at time scales faster than those seen in collected measurements. PMID:28727850

Chaotic behaviors of operational amplifiers.

PubMed

Yim, Geo-Su; Ryu, Jung-Wan; Park, Young-Jai; Rim, Sunghwan; Lee, Soo-Young; Kye, Won-Ho; Kim, Chil-Min

2004-04-01

We investigate nonlinear dynamical behaviors of operational amplifiers. When the output terminal of an operational amplifier is connected to the inverting input terminal, the circuit exhibits period-doubling bifurcation, chaos, and periodic windows, depending on the voltages of the positive and the negative power supplies. We study these nonlinear dynamical characteristics of this electronic circuit experimentally.

Laser dynamics: The system dynamics and network theory of optoelectronic integrated circuit design

NASA Astrophysics Data System (ADS)

Tarng, Tom Shinming-T. K.

Laser dynamics is the system dynamics, communication and network theory for the design of opto-electronic integrated circuit (OEIC). Combining the optical network theory and optical communication theory, the system analysis and design for the OEIC fundamental building blocks is considered. These building blocks include the direct current modulation, inject light modulation, wideband filter, super-gain optical amplifier, E/O and O/O optical bistability and current-controlled optical oscillator. Based on the rate equations, the phase diagram and phase portrait analysis is applied to the theoretical studies and numerical simulation. The OEIC system design methodologies are developed for the OEIC design. Stimulating-field-dependent rate equations are used to model the line-width narrowing/broadening mechanism for the CW mode and frequency chirp of semiconductor lasers. The momentary spectra are carrier-density-dependent. Furthermore, the phase portrait analysis and the nonlinear refractive index is used to simulate the single mode frequency chirp. The average spectra of chaos, period doubling, period pulsing, multi-loops and analog modulation are generated and analyzed. The bifurcation-chirp design chart with modulation depth and modulation frequency as parameters is provided for design purpose.

Observing Resonant Entanglement Dynamics in Circuit QED

NASA Astrophysics Data System (ADS)

Mlynek, J. A.; Abdumalikov, A. A.; Fink, J. M.; Steffen, L.; Lang, C.; van Loo, A. F.; Wallraff, A.

2012-02-01

We study the resonant interaction of up to three two-level systems and a single mode of an electromagnetic field in a circuit QED setup. Our investigation is focused on how a single excitation is dynamically shared in this fourpartite system. The underlying theory of the experiment is governed by the Tavis-Cummings-model, which on resonance predicts dynamics known as vacuum Rabi oscillations. The resonant situation has already been studied spectroscopically with three qubits [1] and time resolved measurements have been carried out in a tripartite system [2]. Here we are able to observe the coherent oscillations and their √N- enhancement by tracking the populations of all three qubits and the resonator. Full quantum state tomography is used to verify that the dynamics generates the maximally entangled 3-qubit W-state when the cavity state factorizes. The √N-speed-up offers the possibility to create W-states within a few ns with a fidelity of 75%. We compare the resonant collective method to an approach, which achieves entanglement by sequentially tuning qubits into resonance with the cavity.[4pt] [1] J. M. Fink, Physical Review Letters 103, 083601 (2009)[0pt] [2] F. Altomare, Nature Physics 6, 777--781 (2010)

Comparison of the measured and predicted response of the Earth Radiation Budget Experiment active cavity radiometer during solar observations

NASA Technical Reports Server (NTRS)

Mahan, J. R.; Tira, N. E.; Lee, Robert B., III; Keynton, R. J.

1989-01-01

The Earth Radiation Budget Experiment consists of an array of radiometric instruments placed in earth orbit by the National Aeronautics and Space Administration to monitor the longwave and visible components of the earth's radiation budget. Presented is a dynamic electrothermal model of the active cavity radiometer used to measure the earth's total radiative exitance. Radiative exchange is modeled using the Monte Carlo method and transient conduction is treated using the finite element method. Also included is the feedback circuit which controls electrical substitution heating of the cavity. The model is shown to accurately predict the dynamic response of the instrument during solar calibration.

Modelling of piezoelectric actuator dynamics for active structural control

NASA Technical Reports Server (NTRS)

Hagood, Nesbitt W.; Chung, Walter H.; Von Flotow, Andreas

1990-01-01

The paper models the effects of dynamic coupling between a structure and an electrical network through the piezoelectric effect. The coupled equations of motion of an arbitrary elastic structure with piezoelectric elements and passive electronics are derived. State space models are developed for three important cases: direct voltage driven electrodes, direct charge driven electrodes, and an indirect drive case where the piezoelectric electrodes are connected to an arbitrary electrical circuit with embedded voltage and current sources. The equations are applied to the case of a cantilevered beam with surface mounted piezoceramics and indirect voltage and current drive. The theoretical derivations are validated experimentally on an actively controlled cantilevered beam test article with indirect voltage drive.

The impact of neurotechnology on rehabilitation.

PubMed

Berger, Theodore W; Gerhardt, Greg; Liker, Mark A; Soussou, Walid

2008-01-01

This paper present results of a multi-disciplinary project that is developing a microchip-based neural prosthesis for the hippocampus, a region of the brain responsible for the formation of long-term memories. Damage to the hippocampus is frequently associated with epilepsy, stroke, and dementia (Alzheimer's disease) and is considered to underlie the memory deficits related to these neurological conditions. The essential goals of the multi-laboratory effort include: (1) experimental study of neuron and neural network function--how does the hippocampus encode information? (2) formulation of biologically realistic models of neural system dynamics--can that encoding process be described mathematically to realize a predictive model of how the hippocampus responds to any event? (3) microchip implementation of neural system models--can the mathematical model be realized as a set of electronic circuits to achieve parallel processing, rapid computational speed, and miniaturization? and (4) creation of hybrid neuron-silicon interfaces-can structural and functional connections between electronic devices and neural tissue be achieved for long-term, bi-directional communication with the brain? By integrating solutions to these component problems, we are realizing a microchip-based model of hippocampal nonlinear dynamics that can perform the same function as part of the hippocampus. Through bi-directional communication with other neural tissue that normally provides the inputs and outputs to/from a damaged hippocampal area, the biomimetic model could serve as a neural prosthesis. A proof-of-concept will be presented in which the CA3 region of the hippocampal slice is surgically removed and is replaced by a microchip model of CA3 nonlinear dynamics--the "hybrid" hippocampal circuit displays normal physiological properties. How the work in brain slices is being extended to behaving animals also will be described.

Modeling and Application of Piezoelectric Materials in Repair of Engineering Structures

NASA Astrophysics Data System (ADS)

Wu, Nan

The shear horizontal wave propagation and vibration of piezoelectric coupled structures under an open circuit electrical boundary condition are studied. Following the studies on the dynamic response of piezoelectric coupled structures, the repair of both crack/notch and delaminated structures using piezoelectric materials are conducted. The main contribution was the proposed the active structural repair design using piezoelectric materials for different structures. An accurate model for the piezoelectric effect on the shear wave propagation is first proposed to guide the application of piezoelectric materials as sensors and actuators in the repair of engineering structures. A vibration analysis of a circular steel substrate surface bonded by a piezoelectric layer with open circuit is presented. The mechanical models and solutions for the wave propagation and vibration analysis of piezoelectric coupled structures are established based on the Kirchhoff plate model and Maxwell equation. Following the studies of the dynamic response of piezoelectric coupled structures, a close-loop feedback control repair methodology is proposed for a vibrating delaminated beam structure by using piezoelectric patches. The electromechanical characteristic of the piezoelectric material is employed to induce a local shear force above the delamination area via an external actuation voltage, which is designed as a feedback of the deflection of a vibrating beam and a delaminated plate, to reduce the stress singularity around the delamination tips. Furthermore, an experimental realization of an effective repair of a notched cantilever beam structure subjected to a dynamic loading by use of piezoelectric patches is reported. A small piezoelectric patch used as a sensor is placed on the notch position to monitor the severity of the stress singularity around the notch area by measuring the charge output on the sensor, and a patch used as an actuator is located around the notch area to generate a required bending moment by employing an actuation voltage to reduce the stress singularity at the notch position. The actuation voltage on the actuator is designed from a feedback circuit process. Through the analytical model, FEM simulation and experimental studies, the active structural repair method using piezoelectric materials is realized and proved to be feasible and practical.

Role of inhibitory feedback for information processing in thalamocortical circuits

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayer, Joerg; Schuster, Heinz Georg; Claussen, Jens Christian

2006-03-15

The information transfer in the thalamus is blocked dynamically during sleep, in conjunction with the occurrence of spindle waves. In order to describe the dynamic mechanisms which control the sensory transfer of information, it is necessary to have a qualitative model for the response properties of thalamic neurons. As the theoretical understanding of the mechanism remains incomplete, we analyze two modeling approaches for a recent experiment by Le Masson et al. [Nature (London) 417, 854 (2002)] on the thalamocortical loop. We use a conductance based model in order to motivate an extension of the Hindmarsh-Rose model, which mimics experimental observationsmore » of Le Masson et al. Typically, thalamic neurons posses two different firing modes, depending on their membrane potential. At depolarized potentials, the cells fire in a single spike mode and relay synaptic inputs in a one-to-one manner to the cortex. If the cell gets hyperpolarized, T-type calcium currents generate burst-mode firing which leads to a decrease in the spike transfer. In thalamocortical circuits, the cell membrane gets hyperpolarized by recurrent inhibitory feedback loops. In the case of reciprocally coupled excitatory and inhibitory neurons, inhibitory feedback leads to metastable self-sustained oscillations, which mask the incoming input, and thereby reduce the information transfer significantly.« less

Digital-analog quantum simulation of generalized Dicke models with superconducting circuits

NASA Astrophysics Data System (ADS)

Lamata, Lucas

We propose a digital-analog quantum simulation of generalized Dicke models with superconducting circuits, including Fermi-Bose condensates, biased and pulsed Dicke models, for all regimes of light-matter coupling. We encode these classes of problems in a set of superconducting qubits coupled with a bosonic mode implemented by a transmission line resonator. Via digital-analog techniques, an efficient quantum simulation can be performed in state-of-the-art circuit quantum electrodynamics platforms, by suitable decomposition into analog qubit-bosonic blocks and collective single-qubit pulses through digital steps. Moreover, just a single global analog block would be needed during the whole protocol in most of the cases, superimposed with fast periodic pulses to rotate and detune the qubits. Therefore, a large number of digital steps may be attained with this approach, providing a reduced digital error. Additionally, the number of gates per digital step does not grow with the number of qubits, rendering the simulation efficient. This strategy paves the way for the scalable digital-analog quantum simulation of many-body dynamics involving bosonic modes and spin degrees of freedom with superconducting circuits. The author wishes to acknowledge discussions with I. Arrazola, A. Mezzacapo, J. S. Pedernales, and E. Solano, and support from Ramon y Cajal Grant RYC-2012-11391, Spanish MINECO/FEDER FIS2015-69983-P, UPV/EHU UFI 11/55 and Project EHUA14/04.

Modeling, Dynamics, Bifurcation Behavior and Stability Analysis of a DC-DC Boost Converter in Photovoltaic Systems

NASA Astrophysics Data System (ADS)

Zhioua, M.; El Aroudi, A.; Belghith, S.; Bosque-Moncusí, J. M.; Giral, R.; Al Hosani, K.; Al-Numay, M.

A study of a DC-DC boost converter fed by a photovoltaic (PV) generator and supplying a constant voltage load is presented. The input port of the converter is controlled using fixed frequency pulse width modulation (PWM) based on the loss-free resistor (LFR) concept whose parameter is selected with the aim to force the PV generator to work at its maximum power point. Under this control strategy, it is shown that the system can exhibit complex nonlinear behaviors for certain ranges of parameter values. First, using the nonlinear models of the converter and the PV source, the dynamics of the system are explored in terms of some of its parameters such as the proportional gain of the controller and the output DC bus voltage. To present a comprehensive approach to the overall system behavior under parameter changes, a series of bifurcation diagrams are computed from the circuit-level switched model and from a simplified model both implemented in PSIM© software showing a remarkable agreement. These diagrams show that the first instability that takes place in the system period-1 orbit when a primary parameter is varied is a smooth period-doubling bifurcation and that the nonlinearity of the PV generator is irrelevant for predicting this phenomenon. Different bifurcation scenarios can take place for the resulting period-2 subharmonic regime depending on a secondary bifurcation parameter. The boundary between the desired period-1 orbit and subharmonic oscillation resulting from period-doubling in the parameter space is obtained by calculating the eigenvalues of the monodromy matrix of the simplified model. The results from this model have been validated with time-domain numerical simulation using the circuit-level switched model and also experimentally from a laboratory prototype. This study can help in selecting the parameter values of the circuit in order to delimit the region of period-1 operation of the converter which is of practical interest in PV systems.

Stochastic modular analysis for gene circuits: interplay among retroactivity, nonlinearity, and stochasticity.

PubMed

Kim, Kyung Hyuk; Sauro, Herbert M

2015-01-01

This chapter introduces a computational analysis method for analyzing gene circuit dynamics in terms of modules while taking into account stochasticity, system nonlinearity, and retroactivity. (1) ANALOG ELECTRICAL CIRCUIT REPRESENTATION FOR GENE CIRCUITS: A connection between two gene circuit components is often mediated by a transcription factor (TF) and the connection signal is described by the TF concentration. The TF is sequestered to its specific binding site (promoter region) and regulates downstream transcription. This sequestration has been known to affect the dynamics of the TF by increasing its response time. The downstream effect-retroactivity-has been shown to be explicitly described in an electrical circuit representation, as an input capacitance increase. We provide a brief review on this topic. (2) MODULAR DESCRIPTION OF NOISE PROPAGATION: Gene circuit signals are noisy due to the random nature of biological reactions. The noisy fluctuations in TF concentrations affect downstream regulation. Thus, noise can propagate throughout the connected system components. This can cause different circuit components to behave in a statistically dependent manner, hampering a modular analysis. Here, we show that the modular analysis is still possible at the linear noise approximation level. (3) NOISE EFFECT ON MODULE INPUT-OUTPUT RESPONSE: We investigate how to deal with a module input-output response and its noise dependency. Noise-induced phenotypes are described as an interplay between system nonlinearity and signal noise. Lastly, we provide the comprehensive approach incorporating the above three analysis methods, which we call "stochastic modular analysis." This method can provide an analysis framework for gene circuit dynamics when the nontrivial effects of retroactivity, stochasticity, and nonlinearity need to be taken into account.

Modeling of a carbon nanotube ultracapacitor.

PubMed

Orphanou, Antonis; Yamada, Toshishige; Yang, Cary Y

2012-03-09

The modeling of carbon nanotube ultracapacitor (CNU) performance based on the simulation of electrolyte ion motion between the cathode and the anode is described. Using a molecular dynamics (MD) approach, the equilibrium positions of the electrode charges interacting through the Coulomb potential are determined, which in turn yield the equipotential surface and electric field associated with the capacitor. With an applied ac voltage, the current is computed based on the nanotube and electrolyte particle distribution and interaction, resulting in the frequency-dependent impedance Z(ω). From the current and impedance profiles, the Nyquist and cyclic voltammetry (CV) plots are then extracted. The results of these calculations compare well with existing experimental data. A lumped-element equivalent circuit for the CNU is proposed and the impedance computed from this circuit correlates well with the simulated and measured impedances.

Architecture, Voltage, and Components for a Turboelectric Distributed Propulsion Electric Grid (AVC-TeDP)

NASA Technical Reports Server (NTRS)

Gemin, Paul; Kupiszewski, Tom; Radun, Arthur; Pan, Yan; Lai, Rixin; Zhang, Di; Wang, Ruxi; Wu, Xinhui; Jiang, Yan; Galioto, Steve;

A new chaotic attractor with two quadratic nonlinearities, its synchronization and circuit implementation

NASA Astrophysics Data System (ADS)

Vaidyanathan, S.; Sambas, A.; Sukono; Mamat, M.; Gundara, G.; Mada Sanjaya, W. S.; Subiyanto

2018-03-01

A 3-D new chaotic attractor with two quadratic nonlinearities is proposed in this paper. The dynamical properties of the new chaotic system are described in terms of phase portraits, equilibrium points, Lyapunov exponents, Kaplan-Yorke dimension, dissipativity, etc. We show that the new chaotic system has three unstable equilibrium points. The new chaotic attractor is dissipative in nature. As an engineering application, adaptive synchronization of identical new chaotic attractors is designed via nonlinear control and Lyapunov stability theory. Furthermore, an electronic circuit realization of the new chaotic attractor is presented in detail to confirm the feasibility of the theoretical chaotic attractor model.

Dynamic divisive normalization predicts time-varying value coding in decision-related circuits.

PubMed

Louie, Kenway; LoFaro, Thomas; Webb, Ryan; Glimcher, Paul W

2014-11-26

Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. Copyright © 2014 the authors 0270-6474/14/3416046-12$15.00/0.

Mathematical modeling and simulation of a thermal system

NASA Astrophysics Data System (ADS)

Toropoc, Mirela; Gavrila, Camelia; Frunzulica, Rodica; Toma, Petrica D.

2016-12-01

The aim of the present paper is the conception of a mathematical model and simulation of a system formed by a heatexchanger for domestic hot water preparation, a storage tank for hot water and a radiator, starting from the mathematical equations describing this system and developed using Scilab-Xcos program. The model helps to determine the evolution in time for the hot water temperature, for the return temperature in the primary circuit of the heat exchanger, for the supply temperature in the secondary circuit, the thermal power for heating and for hot water preparation to the consumer respectively. In heating systems, heat-exchangers have an important role and their performances influence the energy efficiency of the systems. In the meantime, it is very important to follow the behavior of such systems in dynamic regimes. Scilab-Xcos program can be utilized to follow the important parameters of the systems in different functioning scenarios.

The modeling of a standalone solid-oxide fuel cell auxiliary power unit

NASA Astrophysics Data System (ADS)

Lu, N.; Li, Q.; Sun, X.; Khaleel, M. A.

In this research, a Simulink model of a standalone vehicular solid-oxide fuel cell (SOFC) auxiliary power unit (APU) is developed. The SOFC APU model consists of three major components: a controller model; a power electronics system model; and an SOFC plant model, including an SOFC stack module, two heat exchanger modules, and a combustor module. This paper discusses the development of the nonlinear dynamic models for the SOFC stacks, the heat exchangers and the combustors. When coupling with a controller model and a power electronic circuit model, the developed SOFC plant model is able to model the thermal dynamics and the electrochemical dynamics inside the SOFC APU components, as well as the transient responses to the electric loading changes. It has been shown that having such a model for the SOFC APU will help design engineers to adjust design parameters to optimize the performance. The modeling results of the SOFC APU heat-up stage and the output voltage response to a sudden load change are presented in this paper. The fuel flow regulation based on fuel utilization is also briefly discussed.

An IBM PC-based math model for space station solar array simulation

NASA Technical Reports Server (NTRS)

Emanuel, E. M.

1986-01-01

This report discusses and documents the design, development, and verification of a microcomputer-based solar cell math model for simulating the Space Station's solar array Initial Operational Capability (IOC) reference configuration. The array model is developed utilizing a linear solar cell dc math model requiring only five input parameters: short circuit current, open circuit voltage, maximum power voltage, maximum power current, and orbit inclination. The accuracy of this model is investigated using actual solar array on orbit electrical data derived from the Solar Array Flight Experiment/Dynamic Augmentation Experiment (SAFE/DAE), conducted during the STS-41D mission. This simulator provides real-time simulated performance data during the steady state portion of the Space Station orbit (i.e., array fully exposed to sunlight). Eclipse to sunlight transients and shadowing effects are not included in the analysis, but are discussed briefly. Integrating the Solar Array Simulator (SAS) into the Power Management and Distribution (PMAD) subsystem is also discussed.

Dynamic Excitatory and Inhibitory Gain Modulation Can Produce Flexible, Robust and Optimal Decision-making

PubMed Central

Niyogi, Ritwik K.; Wong-Lin, KongFatt

2013-01-01

Behavioural and neurophysiological studies in primates have increasingly shown the involvement of urgency signals during the temporal integration of sensory evidence in perceptual decision-making. Neuronal correlates of such signals have been found in the parietal cortex, and in separate studies, demonstrated attention-induced gain modulation of both excitatory and inhibitory neurons. Although previous computational models of decision-making have incorporated gain modulation, their abstract forms do not permit an understanding of the contribution of inhibitory gain modulation. Thus, the effects of co-modulating both excitatory and inhibitory neuronal gains on decision-making dynamics and behavioural performance remain unclear. In this work, we incorporate time-dependent co-modulation of the gains of both excitatory and inhibitory neurons into our previous biologically based decision circuit model. We base our computational study in the context of two classic motion-discrimination tasks performed in animals. Our model shows that by simultaneously increasing the gains of both excitatory and inhibitory neurons, a variety of the observed dynamic neuronal firing activities can be replicated. In particular, the model can exhibit winner-take-all decision-making behaviour with higher firing rates and within a significantly more robust model parameter range. It also exhibits short-tailed reaction time distributions even when operating near a dynamical bifurcation point. The model further shows that neuronal gain modulation can compensate for weaker recurrent excitation in a decision neural circuit, and support decision formation and storage. Higher neuronal gain is also suggested in the more cognitively demanding reaction time than in the fixed delay version of the task. Using the exact temporal delays from the animal experiments, fast recruitment of gain co-modulation is shown to maximize reward rate, with a timescale that is surprisingly near the experimentally fitted value. Our work provides insights into the simultaneous and rapid modulation of excitatory and inhibitory neuronal gains, which enables flexible, robust, and optimal decision-making. PMID:23825935

Emergence and analysis of Kuramoto-Sakaguchi-like models as an effective description for the dynamics of coupled Wien-bridge oscillators.

PubMed

English, L Q; Mertens, David; Abdoulkary, Saidou; Fritz, C B; Skowronski, K; Kevrekidis, P G

2016-12-01

We derive the Kuramoto-Sakaguchi model from the basic circuit equations governing two coupled Wien-bridge oscillators. A Wien-bridge oscillator is a particular realization of a tunable autonomous oscillator that makes use of frequency filtering (via an RC bandpass filter) and positive feedback (via an operational amplifier). In the past few years, such oscillators have started to be utilized in synchronization studies. We first show that the Wien-bridge circuit equations can be cast in the form of a coupled pair of van der Pol equations. Subsequently, by applying the method of multiple time scales, we derive the differential equations that govern the slow evolution of the oscillator phases and amplitudes. These equations are directly reminiscent of the Kuramoto-Sakaguchi-type models for the study of synchronization. We analyze the resulting system in terms of the existence and stability of various coupled oscillator solutions and explain on that basis how their synchronization emerges. The phase-amplitude equations are also compared numerically to the original circuit equations and good agreement is found. Finally, we report on experimental measurements of two coupled Wien-bridge oscillators and relate the results to the theoretical predictions.

Instrument For Simulation Of Piezoelectric Transducers

NASA Technical Reports Server (NTRS)

Mcnichol, Randal S.

1996-01-01

Electronic instrument designed to simulate dynamic output of integrated-circuit piezoelectric acceleration or pressure transducer. Operates in conjunction with external signal-conditioning circuit, generating square-wave signal of known amplitude for use in calibrating signal-conditioning circuit. Instrument also useful as special-purpose square-wave generator in other applications.

Locality of interactions for planar memristive circuits

DOE PAGES

Caravelli, Francesco

2017-11-08

The dynamics of purely memristive circuits has been shown to depend on a projection operator which expresses the Kirchhoff constraints, is naturally non-local in nature, and does represent the interaction between memristors. In the present paper we show that for the case of planar circuits, for which a meaningful Hamming distance can be defined, the elements of such projector can be bounded by exponentially decreasing functions of the distance. We provide a geometrical interpretation of the projector elements in terms of determinants of Dirichlet Laplacian of the dual circuit. For the case of linearized dynamics of the circuit for whichmore » a solution is known, this can be shown to provide a light cone bound for the interaction between memristors. Furthermore, this result establishes a finite speed of propagation of signals across the network, despite the non-local nature of the system.« less

Technique for extending the range of a signal measuring circuit

DOEpatents

Chaprnka, Anthony G.; Sun, Shan C.; Vercellotti, Leonard C.

1978-01-01

An input signal supplied to a signal measuring circuit is either amplified or attenuated as necessary to establish the magnitude of the input signal within the defined dynamic range of the measuring circuit and the output signal developed by the measuring circuit is subsequently readjusted through amplification or attenuation to develop an output signal which corresponds to the magnitude of the initial input signal.

Gated high speed optical detector

NASA Technical Reports Server (NTRS)

Green, S. I.; Carson, L. M.; Neal, G. W.

1973-01-01

The design, fabrication, and test of two gated, high speed optical detectors for use in high speed digital laser communication links are discussed. The optical detectors used a dynamic crossed field photomultiplier and electronics including dc bias and RF drive circuits, automatic remote synchronization circuits, automatic gain control circuits, and threshold detection circuits. The equipment is used to detect binary encoded signals from a mode locked neodynium laser.

Top-Down Modulation on Perceptual Decision with Balanced Inhibition through Feedforward and Feedback Inhibitory Neurons

PubMed Central

Wang, Cheng-Te; Lee, Chung-Ting; Wang, Xiao-Jing; Lo, Chung-Chuan

2013-01-01

Recent physiological studies have shown that neurons in various regions of the central nervous systems continuously receive noisy excitatory and inhibitory synaptic inputs in a balanced and covaried fashion. While this balanced synaptic input (BSI) is typically described in terms of maintaining the stability of neural circuits, a number of experimental and theoretical studies have suggested that BSI plays a proactive role in brain functions such as top-down modulation for executive control. Two issues have remained unclear in this picture. First, given the noisy nature of neuronal activities in neural circuits, how do the modulatory effects change if the top-down control implements BSI with different ratios between inhibition and excitation? Second, how is a top-down BSI realized via only excitatory long-range projections in the neocortex? To address the first issue, we systematically tested how the inhibition/excitation ratio affects the accuracy and reaction times of a spiking neural circuit model of perceptual decision. We defined an energy function to characterize the network dynamics, and found that different ratios modulate the energy function of the circuit differently and form two distinct functional modes. To address the second issue, we tested BSI with long-distance projection to inhibitory neurons that are either feedforward or feedback, depending on whether these inhibitory neurons do or do not receive inputs from local excitatory cells, respectively. We found that BSI occurs in both cases. Furthermore, when relying on feedback inhibitory neurons, through the recurrent interactions inside the circuit, BSI dynamically and automatically speeds up the decision by gradually reducing its inhibitory component in the course of a trial when a decision process takes too long. PMID:23626812

Top-down modulation on perceptual decision with balanced inhibition through feedforward and feedback inhibitory neurons.

PubMed

Wang, Cheng-Te; Lee, Chung-Ting; Wang, Xiao-Jing; Lo, Chung-Chuan

2013-01-01

Recent physiological studies have shown that neurons in various regions of the central nervous systems continuously receive noisy excitatory and inhibitory synaptic inputs in a balanced and covaried fashion. While this balanced synaptic input (BSI) is typically described in terms of maintaining the stability of neural circuits, a number of experimental and theoretical studies have suggested that BSI plays a proactive role in brain functions such as top-down modulation for executive control. Two issues have remained unclear in this picture. First, given the noisy nature of neuronal activities in neural circuits, how do the modulatory effects change if the top-down control implements BSI with different ratios between inhibition and excitation? Second, how is a top-down BSI realized via only excitatory long-range projections in the neocortex? To address the first issue, we systematically tested how the inhibition/excitation ratio affects the accuracy and reaction times of a spiking neural circuit model of perceptual decision. We defined an energy function to characterize the network dynamics, and found that different ratios modulate the energy function of the circuit differently and form two distinct functional modes. To address the second issue, we tested BSI with long-distance projection to inhibitory neurons that are either feedforward or feedback, depending on whether these inhibitory neurons do or do not receive inputs from local excitatory cells, respectively. We found that BSI occurs in both cases. Furthermore, when relying on feedback inhibitory neurons, through the recurrent interactions inside the circuit, BSI dynamically and automatically speeds up the decision by gradually reducing its inhibitory component in the course of a trial when a decision process takes too long.

A physics-based model of the electrical impedance of ionic polymer metal composites

NASA Astrophysics Data System (ADS)

Cha, Youngsu; Aureli, Matteo; Porfiri, Maurizio

2012-06-01

In this paper, we analyze the chemoelectrical behavior of ionic polymer metal composites (IPMCs) in the small voltage range with a novel hypothesis on the charge dynamics in proximity of the electrodes. In particular, we homogenize the microscopic properties of the interfacial region through a so-called composite layer which extends between the polymer membrane and the metal electrode. This layer accounts for the dissimilar properties of its constituents by describing the charge distribution via two species of charge carriers, that is, electrons and mobile counterions. We model the charge dynamics in the IPMC by adapting the multiphysics formulation based on the Poisson-Nernst-Planck (PNP) framework, which is enriched through an additional term to capture the electron transport in the composite layer. Under the hypothesis of small voltage input, we use the linearized PNP model to derive an equivalent IPMC circuit model with lumped elements. The equivalent model comprises a resistor connected in series with the parallel of a capacitor and a Warburg impedance element. These elements idealize the phenomena of charge build up in the double layer region and the faradaic impedance related to mass transfer, respectively. We validate the equivalent model through measurements on in-house fabricated samples addressing both IPMC step response and impedance, while assessing the influence of repeated plating cycles on the electrical properties of IPMCs. Experimental results are compared with theoretical findings to identify the equivalent circuit parameters. Findings from this study are compared with alternative impedance models proposed in the literature.

Nano- and micro-electromechanical switch dynamics

NASA Astrophysics Data System (ADS)

Pulskamp, Jeffrey S.; Proie, Robert M.; Polcawich, Ronald G.

2013-01-01

This paper reports theoretical analysis and experimental results on the dynamics of piezoelectric MEMS mechanical logic relays. The multiple degree of freedom analytical model, based on modal decomposition, utilizes modal parameters obtained from finite element analysis and an analytical model of piezoelectric actuation. The model accounts for exact device geometry, damping, drive waveform variables, and high electric field piezoelectric nonlinearity. The piezoelectrically excited modal force is calculated directly and provides insight into design optimization for switching speed. The model accurately predicts the propagation delay dependence on actuation voltage of mechanically distinct relay designs. The model explains the observed discrepancies in switching speed of these devices relative to single degree of freedom switching speed models and suggests the strong potential for improved switching speed performance in relays designed for mechanical logic and RF circuits through the exploitation of higher order vibrational modes.

A receptor and neuron that activate a circuit limiting sucrose consumption.

PubMed

Joseph, Ryan M; Sun, Jennifer S; Tam, Edric; Carlson, John R

2017-03-23

The neural control of sugar consumption is critical for normal metabolism. In contrast to sugar-sensing taste neurons that promote consumption, we identify a taste neuron that limits sucrose consumption in Drosophila . Silencing of the neuron increases sucrose feeding; optogenetic activation decreases it. The feeding inhibition depends on the IR60b receptor, as shown by behavioral analysis and Ca 2+ imaging of an IR60b mutant. The IR60b phenotype shows a high degree of chemical specificity when tested with a broad panel of tastants. An automated analysis of feeding behavior in freely moving flies shows that IR60b limits the duration of individual feeding bouts. This receptor and neuron provide the molecular and cellular underpinnings of a new element in the circuit logic of feeding regulation. We propose a dynamic model in which sucrose acts via IR60b to activate a circuit that inhibits feeding and prevents overconsumption.

High speed high dynamic range high accuracy measurement system

DOEpatents

Deibele, Craig E.; Curry, Douglas E.; Dickson, Richard W.; Xie, Zaipeng

2016-11-29

A measuring system includes an input that emulates a bandpass filter with no signal reflections. A directional coupler connected to the input passes the filtered input to electrically isolated measuring circuits. Each of the measuring circuits includes an amplifier that amplifies the signal through logarithmic functions. The output of the measuring system is an accurate high dynamic range measurement.

Exploring Alternative Conceptions from Newtonian Dynamics and Simple DC Circuits: Links between Item Difficulty and Item Confidence

ERIC Educational Resources Information Center

Planinic, Maja; Boone, William J.; Krsnik, Rudolf; Beilfuss, Meredith L.

2006-01-01

Croatian 1st-year and 3rd-year high-school students (N = 170) completed a conceptual physics test. Students were evaluated with regard to two physics topics: Newtonian dynamics and simple DC circuits. Students answered test items and also indicated their confidence in each answer. Rasch analysis facilitated the calculation of three linear…

p53 activated by AND gate genetic circuit under radiation and hypoxia for targeted cancer gene therapy.

PubMed

Ding, Miao; Li, Rong; He, Rong; Wang, Xingyong; Yi, Qijian; Wang, Weidong

2015-09-01

Radio-activated gene therapy has been developed as a novel therapeutic strategy against cancer; however, expression of therapeutic gene in peritumoral tissues will result in unacceptable toxicity to normal cells. To restrict gene expression in targeted tumor mass, we used hypoxia and radiation tolerance features of tumor cells to develop a synthetic AND gate genetic circuit through connecting radiation sensitivity promoter cArG6 , heat shock response elements SNF1, HSF1 and HSE4 with retroviral vector plxsn. Their construction and dynamic activity process were identified through downstream enhanced green fluorescent protein and wtp53 expression in non-small cell lung cancer A549 cells and in a nude mice model. The result showed that AND gate genetic circuit could be activated by lower required radiation dose (6 Gy) and after activated, AND gate could induce significant apoptosis effects and growth inhibition of cancer cells in vitro and in vivo. The radiation- and hypoxia-activated AND gate genetic circuit, which could lead to more powerful target tumoricidal activity represented a promising strategy for both targeted and effective gene therapy of human lung adenocarcinoma and low dose activation character of the AND gate genetic circuit implied that this model could be further exploited to decrease side-effects of clinical radiation therapy. © 2015 The Authors. Cancer Science published by Wiley Publishing Asia Pty Ltd on behalf of Japanese Cancer Association.

Mouse Visual Neocortex Supports Multiple Stereotyped Patterns of Microcircuit Activity

PubMed Central

Sadovsky, Alexander J.

2014-01-01

Spiking correlations between neocortical neurons provide insight into the underlying synaptic connectivity that defines cortical microcircuitry. Here, using two-photon calcium fluorescence imaging, we observed the simultaneous dynamics of hundreds of neurons in slices of mouse primary visual cortex (V1). Consistent with a balance of excitation and inhibition, V1 dynamics were characterized by a linear scaling between firing rate and circuit size. Using lagged firing correlations between neurons, we generated functional wiring diagrams to evaluate the topological features of V1 microcircuitry. We found that circuit connectivity exhibited both cyclic graph motifs, indicating recurrent wiring, and acyclic graph motifs, indicating feedforward wiring. After overlaying the functional wiring diagrams onto the imaged field of view, we found properties consistent with Rentian scaling: wiring diagrams were topologically efficient because they minimized wiring with a modular architecture. Within single imaged fields of view, V1 contained multiple discrete circuits that were overlapping and highly interdigitated but were still distinct from one another. The majority of neurons that were shared between circuits displayed peri-event spiking activity whose timing was specific to the active circuit, whereas spike times for a smaller percentage of neurons were invariant to circuit identity. These data provide evidence that V1 microcircuitry exhibits balanced dynamics, is efficiently arranged in anatomical space, and is capable of supporting a diversity of multineuron spike firing patterns from overlapping sets of neurons. PMID:24899701

Lattice dynamics approach to determine the dependence of the time-of-flight of transversal polarized acoustic waves on external stress

NASA Astrophysics Data System (ADS)

Tarar, K. S.; Pluta, M.; Amjad, U.; Grill, W.

2011-04-01

Based on the lattice dynamics approach the dependence of the time-of-flight (TOF) on stress has been modeled for transversal polarized acoustic waves. The relevant dispersion relation is derived from the appropriate mass-spring model together with the dependencies on the restoring forces including the effect of externally applied stress. The lattice dynamics approach can also be interpreted as a discrete and strictly periodic lumped circuit. In that case the modeling represents a finite element approach. In both cases the properties relevant for wavelengths large with respect to the periodic structure can be derived from the respective limit relating also to low frequencies. The model representing a linear chain with stiffness to shear and additional stiffness introduced by extensional stress is presented and compared to existing models, which so far represent each only one of the effects treated here in combination. For a string this effect is well known from musical instruments. The counteracting effects are discussed and compared to experimental results.

Bursting Transition Dynamics Within the Pre-Bötzinger Complex

NASA Astrophysics Data System (ADS)

Duan, Lixia; Chen, Xi; Tang, Xuhui; Su, Jianzhong

The pre-Bötzinger complex of the mammalian brain stem plays a crucial role in the respiratory rhythms generation. Neurons within the pre-Bötzinger complex have been found experimentally to yield different firing activities. In this paper, we study the spiking and bursting activities related to the respiratory rhythms in the pre-Bötzinger complex based on a mathematical model proposed by Butera. Using the one-dimensional first recurrence map induced by dynamics, we investigate the different bursting patterns and their transition of the pre-Bötzinger complex neurons based on the Butera model, after we derived a one-dimensional map from the dynamical characters of the differential equations, and we obtained conditions for the transition of different bursting patterns. These analytical results were verified through numerical simulations. We conclude that the one-dimensional map contains similar rhythmic patterns as the Butera model and can be used as a simpler modeling tool to study fast-slow models like pre-Bötzinger complex neural circuit.

Modeling and analysis of a resonant nanosystem

NASA Astrophysics Data System (ADS)

Calvert, Scott L.

The majority of investigations into nanoelectromechanical resonators focus on a single area of the resonator's function. This focus varies from the development of a model for a beam's vibration, to the modeling of electrostatic forces, to a qualitative explanation of experimentally-obtained currents. Despite these efforts, there remains a gap between these works, and the level of sophistication needed to truly design nanoresonant systems for efficient commercial use. Towards this end, a comprehensive system model for both a nanobeam resonator and its related experimental setup is proposed. Furthermore, a simulation arrangement is suggested as a method for facilitating the study of the system-level behavior of these devices in a variety of cases that could not be easily obtained experimentally or analytically. The dynamics driving the nanoresonator's motion, as well as the electrical interactions influencing the forcing and output of the system, are modeled, experimentally validated, and studied. The model seeks to develop both a simple circuit representation of the nanoresonator, and to create a mathematical system that can be used to predict and interpret the observed behavior. Due to the assumptions used to simplify the model to a point of reasonable comprehension, the model is most accurate for small beam deflections near the first eigenmode of the beam. The process and results of an experimental investigation are documented, and compared with a circuit simulation modeling the full test system. The comparison qualitatively proves the functionality of the model, while a numerical analysis serves to validate the functionality and setup of the circuit simulation. The use of the simulation enables a much broader investigation of both the electrical behavior and the physical device's dynamics. It is used to complement an assessment of the tuning behavior of the system's linear natural frequency by demonstrating the tuning behavior of the full nonlinear response. The simulation is used to demonstrate the difficulties with the contemporary mixing approach to experimental data collection and to complete a variety of case studies investigating the use of the nanoresonator systems in practical applications, such as signal filtering. Many of these case studies would be difficult to complete analytically, but results are quickly achieved through the use of the simulation.

Fully parameterized model of a voltage-driven capacitive coupled micromachined ohmic contact switch for RF applications

NASA Astrophysics Data System (ADS)

Heeb, Peter; Tschanun, Wolfgang; Buser, Rudolf

2012-03-01

A comprehensive and completely parameterized model is proposed to determine the related electrical and mechanical dynamic system response of a voltage-driven capacitive coupled micromechanical switch. As an advantage over existing parameterized models, the model presented in this paper returns within few seconds all relevant system quantities necessary to design the desired switching cycle. Moreover, a sophisticated and detailed guideline is given on how to engineer a MEMS switch. An analytical approach is used throughout the modelling, providing representative coefficients in a set of two coupled time-dependent differential equations. This paper uses an equivalent mass moving along the axis of acceleration and a momentum absorption coefficient. The model describes all the energies transferred: the energy dissipated in the series resistor that models the signal attenuation of the bias line, the energy dissipated in the squeezed film, the stored energy in the series capacitor that represents a fixed separation in the bias line and stops the dc power in the event of a short circuit between the RF and dc path, the energy stored in the spring mechanism, and the energy absorbed by mechanical interaction at the switch contacts. Further, the model determines the electrical power fed back to the bias line. The calculated switching dynamics are confirmed by the electrical characterization of the developed RF switch. The fabricated RF switch performs well, in good agreement with the modelled data, showing a transition time of 7 µs followed by a sequence of bounces. Moreover, the scattering parameters exhibit an isolation in the off-state of >8 dB and an insertion loss in the on-state of <0.6 dB up to frequencies of 50 GHz. The presented model is intended to be integrated into standard circuit simulation software, allowing circuit engineers to design the switch bias line, to minimize induced currents and cross actuation, as well as to find the mechanical structure dimensions necessary for the desired switching time and actuation voltage waveform. Moreover, process related design rules can be automatically verified.

A stochastic differential equation analysis of cerebrospinal fluid dynamics.

PubMed

Raman, Kalyan

2011-01-18

Clinical measurements of intracranial pressure (ICP) over time show fluctuations around the deterministic time path predicted by a classic mathematical model in hydrocephalus research. Thus an important issue in mathematical research on hydrocephalus remains unaddressed--modeling the effect of noise on CSF dynamics. Our objective is to mathematically model the noise in the data. The classic model relating the temporal evolution of ICP in pressure-volume studies to infusions is a nonlinear differential equation based on natural physical analogies between CSF dynamics and an electrical circuit. Brownian motion was incorporated into the differential equation describing CSF dynamics to obtain a nonlinear stochastic differential equation (SDE) that accommodates the fluctuations in ICP. The SDE is explicitly solved and the dynamic probabilities of exceeding critical levels of ICP under different clinical conditions are computed. A key finding is that the probabilities display strong threshold effects with respect to noise. Above the noise threshold, the probabilities are significantly influenced by the resistance to CSF outflow and the intensity of the noise. Fluctuations in the CSF formation rate increase fluctuations in the ICP and they should be minimized to lower the patient's risk. The nonlinear SDE provides a scientific methodology for dynamic risk management of patients. The dynamic output of the SDE matches the noisy ICP data generated by the actual intracranial dynamics of patients better than the classic model used in prior research.

Asymptotic Representation for the Eigenvalues of a Non-selfadjoint Operator Governing the Dynamics of an Energy Harvesting Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shubov, Marianna A., E-mail: marianna.shubov@gmail.com

2016-06-15

We consider a well known model of a piezoelectric energy harvester. The harvester is designed as a beam with a piezoceramic layer attached to its top face (unimorph configuration). A pair of thin perfectly conductive electrodes is covering the top and the bottom faces of the piezoceramic layer. These electrodes are connected to a resistive load. The model is governed by a system consisting of two equations. The first of them is the equation of the Euler–Bernoulli model for the transverse vibrations of the beam and the second one represents the Kirchhoff’s law for the electric circuit. Both equations aremore » coupled due to the direct and converse piezoelectric effects. The boundary conditions for the beam equations are of clamped-free type. We represent the system as a single operator evolution equation in a Hilbert space. The dynamics generator of this system is a non-selfadjoint operator with compact resolvent. Our main result is an explicit asymptotic formula for the eigenvalues of this generator, i.e., we perform the modal analysis for electrically loaded (not short-circuit) system. We show that the spectrum splits into an infinite sequence of stable eigenvalues that approaches a vertical line in the left half plane and possibly of a finite number of unstable eigenvalues. This paper is the first in a series of three works. In the second one we will prove that the generalized eigenvectors of the dynamics generator form a Riesz basis (and, moreover, a Bari basis) in the energy space. In the third paper we will apply the results of the first two to control problems for this model.« less

A Design Methodology for Optoelectronic VLSI

DTIC Science & Technology

2007-01-01

current gets converted to a CMOS voltage level through a transimpedance amplifier circuit called a receiver. The output of the receiver is then...change the current flowing from the diode to a voltage that the logic inputs can use. That circuit is called a receiver. It is a transimpedance amplifier ...incorpo- rate random access memory circuits, SRAM or dynamic RAM (DRAM). These circuits use weak internal analog signals that are amplified by sense

Coupling Spatial Segregation with Synthetic Circuits to Control Bacterial Survival (Open Access)

DTIC Science & Technology

2016-02-29

Subject Categories Synthetic Biology & Biotechnology; Quantitative Biology & Dynamical Systems DOI 10.15252/msb.20156567 | Received 9 September 2015...survival. Experimentally , we program collective survival using three different gene circuits, which allow us to evaluate the modularity of the...QS-CAT circuit depends on QS regulation. The QS-BlaM circuit depends on both QS regulation and enzyme release (by lysis and export). G–I Experimental

Synthesizing cognition in neuromorphic electronic systems

PubMed Central

Neftci, Emre; Binas, Jonathan; Rutishauser, Ueli; Chicca, Elisabetta; Indiveri, Giacomo; Douglas, Rodney J.

2013-01-01

The quest to implement intelligent processing in electronic neuromorphic systems lacks methods for achieving reliable behavioral dynamics on substrates of inherently imprecise and noisy neurons. Here we report a solution to this problem that involves first mapping an unreliable hardware layer of spiking silicon neurons into an abstract computational layer composed of generic reliable subnetworks of model neurons and then composing the target behavioral dynamics as a “soft state machine” running on these reliable subnets. In the first step, the neural networks of the abstract layer are realized on the hardware substrate by mapping the neuron circuit bias voltages to the model parameters. This mapping is obtained by an automatic method in which the electronic circuit biases are calibrated against the model parameters by a series of population activity measurements. The abstract computational layer is formed by configuring neural networks as generic soft winner-take-all subnetworks that provide reliable processing by virtue of their active gain, signal restoration, and multistability. The necessary states and transitions of the desired high-level behavior are then easily embedded in the computational layer by introducing only sparse connections between some neurons of the various subnets. We demonstrate this synthesis method for a neuromorphic sensory agent that performs real-time context-dependent classification of motion patterns observed by a silicon retina. PMID:23878215

Non-linear lumped model circuit of capacitively coupled plasmas at the intermediate radio-frequencies

NASA Astrophysics Data System (ADS)

Shihab, Mohammed

2018-06-01

The discharge dynamics in geometrically asymmetric capacitively coupled plasmas are investigated via a lumped model circuit. A realistic reactor configuration is assumed. A single and two separate RF voltage sources are considered. One of the driven frequencies (the higher frequency) has been adjusted to excite a plasma series resonance, while the second frequency (the lower frequency) is in the range of the ion plasma frequency. Increasing the plasma pressure in the low pressure regime (≤ 100mTorr) is found to diminish the amplitude of the self-excited harmonics of the discharge current, however, the net result is enhancing the plasma heating. The modulation of the ion density with the lower driving frequency affect the plasma heating considerably. The net effect depends on the amplitude and the phase of the ion modulation.

Research on hysteresis loop considering the prestress effect and electrical input dynamics for a giant magnetostrictive actuator

NASA Astrophysics Data System (ADS)

Zhu, Yuchuan; Yang, Xulei; Wereley, Norman M.

2016-08-01

In this paper, focusing on the application-oriented giant magnetostrictive material (GMM)-based electro-hydrostatic actuator, which features an applied magnetic field at high frequency and high amplitude, and concentrating on the static and dynamic characteristics of a giant magnetostrictive actuator (GMA) considering the prestress effect on the GMM rod and the electrical input dynamics involving the power amplifier and the inductive coil, a methodology for studying the static and dynamic characteristics of a GMA using the hysteresis loop as a tool is developed. A GMA that can display the preforce on the GMM rod in real-time is designed, and a magnetostrictive model dependent on the prestress on a GMM rod instead of the existing quadratic domain rotation model is proposed. Additionally, an electrical input dynamics model to excite GMA is developed according to the simplified circuit diagram, and the corresponding parameters are identified by the experimental data. A dynamic magnetization model with the eddy current effect is deduced according to the Jiles-Atherton model and the Maxwell equations. Next, all of the parameters, including the electrical input characteristics, the dynamic magnetization and the mechanical structure of GMA, are identified by the experimental data from the current response, magnetization response and displacement response, respectively. Finally, a comprehensive comparison between the model results and experimental data is performed, and the results show that the test data agree well with the presented model results. An analysis on the relation between the GMA displacement response and the parameters from the electrical input dynamics, magnetization dynamics and mechanical structural dynamics is performed.

Low temperature probe for dynamic nuclear polarization and multiple-pulse solid-state NMR.

PubMed

Cho, HyungJoon; Baugh, Jonathan; Ryan, Colm A; Cory, David G; Ramanathan, Chandrasekhar

2007-08-01

Here, we describe the design and performance characteristics of a low temperature probe for dynamic nuclear polarization (DNP) experiments, which is compatible with demanding multiple-pulse experiments. The competing goals of a high-Q microwave cavity to achieve large DNP enhancements and a high efficiency NMR circuit for multiple-pulse control lead to inevitable engineering tradeoffs. We have designed two probes-one with a single-resonance RF circuit and a horn-mirror cavity configuration for the microwaves and a second with a double-resonance RF circuit and a double-horn cavity configuration. The advantage of the design is that the sample is in vacuum, the RF circuits are locally tuned, and the microwave resonator has a large internal volume that is compatible with the use of RF and gradient coils.

Wiring Together Synthetic Bacterial Consortia to Create a Biological Integrated Circuit.

PubMed

Perry, Nicolas; Nelson, Edward M; Timp, Gregory

2016-12-16

The promise of adapting biology to information processing will not be realized until engineered gene circuits, operating in different cell populations, can be wired together to express a predictable function. Here, elementary biological integrated circuits (BICs), consisting of two sets of transmitter and receiver gene circuit modules with embedded memory placed in separate cell populations, were meticulously assembled using live cell lithography and wired together by the mass transport of quorum-sensing (QS) signal molecules to form two isolated communication links (comlinks). The comlink dynamics were tested by broadcasting "clock" pulses of inducers into the networks and measuring the responses of functionally linked fluorescent reporters, and then modeled through simulations that realistically captured the protein production and molecular transport. These results show that the comlinks were isolated and each mimicked aspects of the synchronous, sequential networks used in digital computing. The observations about the flow conditions, derived from numerical simulations, and the biofilm architectures that foster or silence cell-to-cell communications have implications for everything from decontamination of drinking water to bacterial virulence.

Interactions between Inhibitory Interneurons and Excitatory Associational Circuitry in Determining Spatio-Temporal Dynamics of Hippocampal Dentate Granule Cells: A Large-Scale Computational Study

PubMed Central

Hendrickson, Phillip J.; Yu, Gene J.; Song, Dong; Berger, Theodore W.

2015-01-01

This paper reports on findings from a million-cell granule cell model of the rat dentate gyrus that was used to explore the contributions of local interneuronal and associational circuits to network-level activity. The model contains experimentally derived morphological parameters for granule cells, which each contain approximately 200 compartments, and biophysical parameters for granule cells, basket cells, and mossy cells that were based both on electrophysiological data and previously published models. Synaptic input to cells in the model consisted of glutamatergic AMPA-like EPSPs and GABAergic-like IPSPs from excitatory and inhibitory neurons, respectively. The main source of input to the model was from layer II entorhinal cortical neurons. Network connectivity was constrained by the topography of the system, and was derived from axonal transport studies, which provided details about the spatial spread of axonal terminal fields, as well as how subregions of the medial and lateral entorhinal cortices project to subregions of the dentate gyrus. Results of this study show that strong feedback inhibition from the basket cell population can cause high-frequency rhythmicity in granule cells, while the strength of feedforward inhibition serves to scale the total amount of granule cell activity. Results furthermore show that the topography of local interneuronal circuits can have just as strong an impact on the development of spatio-temporal clusters in the granule cell population as the perforant path topography does, both sharpening existing clusters and introducing new ones with a greater spatial extent. Finally, results show that the interactions between the inhibitory and associational loops can cause high frequency oscillations that are modulated by a low-frequency oscillatory signal. These results serve to further illustrate the importance of topographical constraints on a global signal processing feature of a neural network, while also illustrating how rich spatio-temporal and oscillatory dynamics can evolve from a relatively small number of interacting local circuits. PMID:26635545

From Anxious to Reckless: A Control Systems Approach Unifies Prefrontal-Limbic Regulation Across the Spectrum of Threat Detection.

PubMed

Mujica-Parodi, Lilianne R; Cha, Jiook; Gao, Jonathan

2017-01-01

Here we provide an integrative review of basic control circuits, and introduce techniques by which their regulation can be quantitatively measured using human neuroimaging. We illustrate the utility of the control systems approach using four human neuroimaging threat detection studies ( N = 226), to which we applied circuit-wide analyses in order to identify the key mechanism underlying individual variation. In so doing, we build upon the canonical prefrontal-limbic control system to integrate circuit-wide influence from the inferior frontal gyrus (IFG). These were incorporated into a computational control systems model constrained by neuroanatomy and designed to replicate our experimental data. In this model, the IFG acts as an informational set point, gating signals between the primary prefrontal-limbic negative feedback loop and its cortical information-gathering loop. Along the cortical route, if the sensory cortex provides sufficient information to make a threat assessment, the signal passes to the ventromedial prefrontal cortex (vmPFC), whose threat-detection threshold subsequently modulates amygdala outputs. However, if signal outputs from the sensory cortex do not provide sufficient information during the first pass, the signal loops back to the sensory cortex, with each cycle providing increasingly fine-grained processing of sensory data. Simulations replicate IFG (chaotic) dynamics experimentally observed at both ends at the threat-detection spectrum. As such, they identify distinct types of IFG disconnection from the circuit, with associated clinical outcomes. If IFG thresholds are too high, the IFG and sensory cortex cycle for too long; in the meantime the coarse-grained (excitatory) pathway will dominate, biasing ambiguous stimuli as false positives. On the other hand, if cortical IFG thresholds are too low, the inhibitory pathway will suppress the amygdala without cycling back to the sensory cortex for much-needed fine-grained sensory cortical data, biasing ambiguous stimuli as false negatives. Thus, the control systems model provides a consistent mechanism for IFG regulation, capable of producing results consistent with our data for the full spectrum of threat-detection: from fearful to optimal to reckless. More generally, it illustrates how quantitative characterization of circuit dynamics can be used to unify a fundamental dimension across psychiatric affective symptoms, with implications for populations that range from anxiety disorders to addiction.

A Structural Model Decomposition Framework for Hybrid Systems Diagnosis

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Bregon, Anibal; Roychoudhury, Indranil

2015-01-01

Nowadays, a large number of practical systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete modes of behavior, each defined by a set of continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task very challenging. In this work, we present a new modeling and diagnosis framework for hybrid systems. Models are composed from sets of user-defined components using a compositional modeling approach. Submodels for residual generation are then generated for a given mode, and reconfigured efficiently when the mode changes. Efficient reconfiguration is established by exploiting causality information within the hybrid system models. The submodels can then be used for fault diagnosis based on residual generation and analysis. We demonstrate the efficient causality reassignment, submodel reconfiguration, and residual generation for fault diagnosis using an electrical circuit case study.

Dynamics, Analysis and Implementation of a Multiscroll Memristor-Based Chaotic Circuit

NASA Astrophysics Data System (ADS)

Alombah, N. Henry; Fotsin, Hilaire; Ngouonkadi, E. B. Megam; Nguazon, Tekou

This article introduces a novel four-dimensional autonomous multiscroll chaotic circuit which is derived from the actual simplest memristor-based chaotic circuit. A fourth circuit element — another inductor — is introduced to generate the complex behavior observed. A systematic study of the chaotic behavior is performed with the help of some nonlinear tools such as Lyapunov exponents, phase portraits, and bifurcation diagrams. Multiple scroll attractors are observed in Matlab, Pspice environments and also experimentally. We also observe the phenomenon of antimonotonicity, periodic and chaotic bubbles, multiple periodic-doubling bifurcations, Hopf bifurcations, crises and the phenomenon of intermittency. The chaotic dynamics of this circuit is realized by laboratory experiments, Pspice simulations, numerical and analytical investigations. It is observed that the results from the three environments agree to a great extent. This topology is likely convenient to be used to intentionally generate chaos in memristor-based chaotic circuit applications, given the fact that multiscroll chaotic systems have found important applications as broadband signal generators, pseudorandom number generators for communication engineering and also in biometric authentication.

Differential regulation of polarized synaptic vesicle trafficking and synapse stability in neural circuit rewiring in Caenorhabditis elegans

PubMed Central

Kurup, Naina; Kono, Karina

2017-01-01

Neural circuits are dynamic, with activity-dependent changes in synapse density and connectivity peaking during different phases of animal development. In C. elegans, young larvae form mature motor circuits through a dramatic switch in GABAergic neuron connectivity, by concomitant elimination of existing synapses and formation of new synapses that are maintained throughout adulthood. We have previously shown that an increase in microtubule dynamics during motor circuit rewiring facilitates new synapse formation. Here, we further investigate cellular control of circuit rewiring through the analysis of mutants obtained in a forward genetic screen. Using live imaging, we characterize novel mutations that alter cargo binding in the dynein motor complex and enhance anterograde synaptic vesicle movement during remodeling, providing in vivo evidence for the tug-of-war between kinesin and dynein in fast axonal transport. We also find that a casein kinase homolog, TTBK-3, inhibits stabilization of nascent synapses in their new locations, a previously unexplored facet of structural plasticity of synapses. Our study delineates temporally distinct signaling pathways that are required for effective neural circuit refinement. PMID:28636662

Preparation of Power Distribution System for High Penetration of Renewable Energy Part I. Dynamic Voltage Restorer for Voltage Regulation Pat II. Distribution Circuit Modeling and Validation

NASA Astrophysics Data System (ADS)

Khoshkbar Sadigh, Arash

Part I: Dynamic Voltage Restorer In the present power grids, voltage sags are recognized as a serious threat and a frequently occurring power-quality problem and have costly consequence such as sensitive loads tripping and production loss. Consequently, the demand for high power quality and voltage stability becomes a pressing issue. Dynamic voltage restorer (DVR), as a custom power device, is more effective and direct solutions for "restoring" the quality of voltage at its load-side terminals when the quality of voltage at its source-side terminals is disturbed. In the first part of this thesis, a DVR configuration with no need of bulky dc link capacitor or energy storage is proposed. This fact causes to reduce the size of the DVR and increase the reliability of the circuit. In addition, the proposed DVR topology is based on high-frequency isolation transformer resulting in the size reduction of transformer. The proposed DVR circuit, which is suitable for both low- and medium-voltage applications, is based on dc-ac converters connected in series to split the main dc link between the inputs of dc-ac converters. This feature makes it possible to use modular dc-ac converters and utilize low-voltage components in these converters whenever it is required to use DVR in medium-voltage application. The proposed configuration is tested under different conditions of load power factor and grid voltage harmonic. It has been shown that proposed DVR can compensate the voltage sag effectively and protect the sensitive loads. Following the proposition of the DVR topology, a fundamental voltage amplitude detection method which is applicable in both single/three-phase systems for DVR applications is proposed. The advantages of proposed method include application in distorted power grid with no need of any low-pass filter, precise and reliable detection, simple computation and implementation without using a phased locked loop and lookup table. The proposed method has been verified by simulation and experimental tests under various conditions considering all possible cases such as different amounts of voltage sag depth (VSD), different amounts of point-on-wave (POW) at which voltage sag occurs, harmonic distortion, line frequency variation, and phase jump (PJ). Furthermore, the ripple amount of fundamental voltage amplitude calculated by the proposed method and its error is analyzed considering the line frequency variation together with harmonic distortion. The best and worst detection time of proposed method were measured 1ms and 8.8ms, respectively. Finally, the proposed method has been compared with other voltage sag detection methods available in literature. Part 2: Power System Modeling for Renewable Energy Integration: As power distribution systems are evolving into more complex networks, electrical engineers have to rely on software tools to perform circuit analysis. There are dozens of powerful software tools available in the market to perform the power system studies. Although their main functions are similar, there are differences in features and formatting structures to suit specific applications. This creates challenges for transferring power system circuit models data (PSCMD) between different software and rebuilding the same circuit in the second software environment. The objective of this part of thesis is to develop a Unified Platform (UP) to facilitate transferring PSCMD among different software packages and relieve the challenges of the circuit model conversion process. UP uses a commonly available spreadsheet file with a defined format, for any home software to write data to and for any destination software to read data from, via a script-based application called PSCMD transfer application. The main considerations in developing the UP are to minimize manual intervention and import a one-line diagram into the destination software or export it from the source software, with all details to allow load flow, short circuit and other analyses. In this study, ETAP, OpenDSS, and GridLab-D are considered, and PSCMD transfer applications written in MATLAB have been developed for each of these to read the circuit model data provided in the UP spreadsheet. In order to test the developed PSCMD transfer applications, circuit model data of a test circuit and a power distribution circuit from Southern California Edison (SCE) - a utility company - both built in CYME, were exported into the spreadsheet file according to the UP format. Thereafter, circuit model data were imported successfully from the spreadsheet files into above mentioned software using the PSCMD transfer applications developed for each software. After the SCE studied circuit is transferred into OpenDSS software using the proposed UP scheme and developed application, it has been studied to investigate the impacts of large-scale solar energy penetration. The main challenge of solar energy integration into power grid is its intermittency (i.e., discontinuity of output power) nature due to cloud shading of photovoltaic panels which depends on weather conditions. In order to conduct this study, OpenDSS time-series simulation feature, which is required due to intermittency of solar energy, is utilized. In this study, the impacts of intermittency of solar energy penetration, especially high-variability points, on voltage fluctuation and operation of capacitor bank and voltage regulator is provided. In addition, the necessity to interpolate and resample unequally spaced time-series measurement data and convert them to equally spaced time-series data as well as the effect of resampling time-interval on the amount of error is discussed. Two applications are developed in Matlab to do interpolation and resampling as well as to calculate the amount of error for different resampling time-intervals to figure out the suitable resampling time-interval. Furthermore, an approach based on cumulative distribution, regarding the length for lines/cables types and the power rating for loads, is presented to prioritize which loads, lines and cables the meters should be installed at to have the most effect on model validation.

Periodic, Quasi-periodic and Chaotic Dynamics in Simple Gene Elements with Time Delays

PubMed Central

Suzuki, Yoko; Lu, Mingyang; Ben-Jacob, Eshel; Onuchic, José N.

2016-01-01

Regulatory gene circuit motifs play crucial roles in performing and maintaining vital cellular functions. Frequently, theoretical studies of gene circuits focus on steady-state behaviors and do not include time delays. In this study, the inclusion of time delays is shown to entirely change the time-dependent dynamics for even the simplest possible circuits with one and two gene elements with self and cross regulations. These elements can give rise to rich behaviors including periodic, quasi-periodic, weak chaotic, strong chaotic and intermittent dynamics. We introduce a special power-spectrum-based method to characterize and discriminate these dynamical modes quantitatively. Our simulation results suggest that, while a single negative feedback loop of either one- or two-gene element can only have periodic dynamics, the elements with two positive/negative feedback loops are the minimalist elements to have chaotic dynamics. These elements typically have one negative feedback loop that generates oscillations, and another unit that allows frequent switches among multiple steady states or between oscillatory and non-oscillatory dynamics. Possible dynamical features of several simple one- and two-gene elements are presented in details. Discussion is presented for possible roles of the chaotic behavior in the robustness of cellular functions and diseases, for example, in the context of cancer. PMID:26876008

Periodic, Quasi-periodic and Chaotic Dynamics in Simple Gene Elements with Time Delays

NASA Astrophysics Data System (ADS)

Suzuki, Yoko; Lu, Mingyang; Ben-Jacob, Eshel; Onuchic, José N.

2016-02-01

Regulatory gene circuit motifs play crucial roles in performing and maintaining vital cellular functions. Frequently, theoretical studies of gene circuits focus on steady-state behaviors and do not include time delays. In this study, the inclusion of time delays is shown to entirely change the time-dependent dynamics for even the simplest possible circuits with one and two gene elements with self and cross regulations. These elements can give rise to rich behaviors including periodic, quasi-periodic, weak chaotic, strong chaotic and intermittent dynamics. We introduce a special power-spectrum-based method to characterize and discriminate these dynamical modes quantitatively. Our simulation results suggest that, while a single negative feedback loop of either one- or two-gene element can only have periodic dynamics, the elements with two positive/negative feedback loops are the minimalist elements to have chaotic dynamics. These elements typically have one negative feedback loop that generates oscillations, and another unit that allows frequent switches among multiple steady states or between oscillatory and non-oscillatory dynamics. Possible dynamical features of several simple one- and two-gene elements are presented in details. Discussion is presented for possible roles of the chaotic behavior in the robustness of cellular functions and diseases, for example, in the context of cancer.

Development and Simulation of Increased Generation on a Secondary Circuit of a Microgrid

NASA Astrophysics Data System (ADS)

Reyes, Karina

As fossil fuels are depleted and their environmental impacts remain, other sources of energy must be considered to generate power. Renewable sources, for example, are emerging to play a major role in this regard. In parallel, electric vehicle (EV) charging is evolving as a major load demand. To meet reliability and resiliency goals demanded by the electricity market, interest in microgrids are growing as a distributed energy resource (DER). In this thesis, the effects of intermittent renewable power generation and random EV charging on secondary microgrid circuits are analyzed in the presence of a controllable battery in order to characterize and better understand the dynamics associated with intermittent power production and random load demands in the context of the microgrid paradigm. For two reasons, a secondary circuit on the University of California, Irvine (UCI) Microgrid serves as the case study. First, the secondary circuit (UC-9) is heavily loaded and an integral component of a highly characterized and metered microgrid. Second, a unique "next-generation" distributed energy resource has been deployed at the end of the circuit that integrates photovoltaic power generation, battery storage, and EV charging. In order to analyze this system and evaluate the impact of the DER on the secondary circuit, a model was developed to provide a real-time load flow analysis. The research develops a power management system applicable to similarly integrated systems. The model is verified by metered data obtained from a network of high resolution electric meters and estimated load data for the buildings that have unknown demand. An increase in voltage is observed when the amount of photovoltaic power generation is increased. To mitigate this effect, a constant power factor is set. Should the real power change dramatically, the reactive power is changed to mitigate voltage fluctuations.

A low-noise wide-dynamic-range event-driven detector using SOI pixel technology for high-energy particle imaging

NASA Astrophysics Data System (ADS)

Shrestha, Sumeet; Kamehama, Hiroki; Kawahito, Shoji; Yasutomi, Keita; Kagawa, Keiichiro; Takeda, Ayaki; Tsuru, Takeshi Go; Arai, Yasuo

2015-08-01

This paper presents a low-noise wide-dynamic-range pixel design for a high-energy particle detector in astronomical applications. A silicon on insulator (SOI) based detector is used for the detection of wide energy range of high energy particles (mainly for X-ray). The sensor has a thin layer of SOI CMOS readout circuitry and a thick layer of high-resistivity detector vertically stacked in a single chip. Pixel circuits are divided into two parts; signal sensing circuit and event detection circuit. The event detection circuit consisting of a comparator and logic circuits which detect the incidence of high energy particle categorizes the incident photon it into two energy groups using an appropriate energy threshold and generate a two-bit code for an event and energy level. The code for energy level is then used for selection of the gain of the in-pixel amplifier for the detected signal, providing a function of high-dynamic-range signal measurement. The two-bit code for the event and energy level is scanned in the event scanning block and the signals from the hit pixels only are read out. The variable-gain in-pixel amplifier uses a continuous integrator and integration-time control for the variable gain. The proposed design allows the small signal detection and wide dynamic range due to the adaptive gain technique and capability of correlated double sampling (CDS) technique of kTC noise canceling of the charge detector.

Progress in knowledge representation research

NASA Technical Reports Server (NTRS)

Lum, Henry

1985-01-01

Brief descriptions are given of research being carried out in the field of knowledge representation. Dynamic simulation and modelling of planning systems with real-time sensor inputs; development of domain-independent knowledge representation tools which can be used in the development of application-specific expert and planning systems; and development of a space-borne very high speed integrated circuit processor are among the projects discussed.

Critical phenomena at a first-order phase transition in a lattice of glow lamps: Experimental findings and analogy to neural activity

NASA Astrophysics Data System (ADS)

Minati, Ludovico; de Candia, Antonio; Scarpetta, Silvia

2016-07-01

Networks of non-linear electronic oscillators have shown potential as physical models of neural dynamics. However, two properties of brain activity, namely, criticality and metastability, remain under-investigated with this approach. Here, we present a simple circuit that exhibits both phenomena. The apparatus consists of a two-dimensional square lattice of capacitively coupled glow (neon) lamps. The dynamics of lamp breakdown (flash) events are controlled by a DC voltage globally connected to all nodes via fixed resistors. Depending on this parameter, two phases having distinct event rate and degree of spatiotemporal order are observed. The transition between them is hysteretic, thus a first-order one, and it is possible to enter a metastability region, wherein, approaching a spinodal point, critical phenomena emerge. Avalanches of events occur according to power-law distributions having exponents ≈3/2 for size and ≈2 for duration, and fractal structure is evident as power-law scaling of the Fano factor. These critical exponents overlap observations in biological neural networks; hence, this circuit may have value as building block to realize corresponding physical models.

Critical phenomena at a first-order phase transition in a lattice of glow lamps: Experimental findings and analogy to neural activity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Minati, Ludovico, E-mail: lminati@ieee.org, E-mail: ludovico.minati@unitn.it, E-mail: ludovico.minati@ifj.edu; Complex Systems Theory Department, Institute of Nuclear Physics, Polish Academy of Sciences, Kraków; Candia, Antonio de

2016-07-15

Networks of non-linear electronic oscillators have shown potential as physical models of neural dynamics. However, two properties of brain activity, namely, criticality and metastability, remain under-investigated with this approach. Here, we present a simple circuit that exhibits both phenomena. The apparatus consists of a two-dimensional square lattice of capacitively coupled glow (neon) lamps. The dynamics of lamp breakdown (flash) events are controlled by a DC voltage globally connected to all nodes via fixed resistors. Depending on this parameter, two phases having distinct event rate and degree of spatiotemporal order are observed. The transition between them is hysteretic, thus a first-ordermore » one, and it is possible to enter a metastability region, wherein, approaching a spinodal point, critical phenomena emerge. Avalanches of events occur according to power-law distributions having exponents ≈3/2 for size and ≈2 for duration, and fractal structure is evident as power-law scaling of the Fano factor. These critical exponents overlap observations in biological neural networks; hence, this circuit may have value as building block to realize corresponding physical models.« less

Multistability and metastability: understanding dynamic coordination in the brain

PubMed Central

Kelso, J. A. Scott

2012-01-01

Multistable coordination dynamics exists at many levels, from multifunctional neural circuits in vertebrates and invertebrates to large-scale neural circuitry in humans. Moreover, multistability spans (at least) the domains of action and perception, and has been found to place constraints upon, even dictating the nature of, intentional change and the skill-learning process. This paper reviews some of the key evidence for multistability in the aforementioned areas, and illustrates how it has been measured, modelled and theoretically understood. It then suggests how multistability—when combined with essential aspects of coordination dynamics such as instability, transitions and (especially) metastability—provides a platform for understanding coupling and the creative dynamics of complex goal-directed systems, including the brain and the brain–behaviour relation. PMID:22371613

A Digitally Programmable Cytomorphic Chip for Simulation of Arbitrary Biochemical Reaction Networks.

PubMed

Woo, Sung Sik; Kim, Jaewook; Sarpeshkar, Rahul

2018-04-01

Prior work has shown that compact analog circuits can faithfully represent and model fundamental biomolecular circuits via efficient log-domain cytomorphic transistor equivalents. Such circuits have emphasized basis functions that are dominant in genetic transcription and translation networks and deoxyribonucleic acid (DNA)-protein binding. Here, we report a system featuring digitally programmable 0.35 μm BiCMOS analog cytomorphic chips that enable arbitrary biochemical reaction networks to be exactly represented thus enabling compact and easy composition of protein networks as well. Since all biomolecular networks can be represented as chemical reaction networks, our protein networks also include the former genetic network circuits as a special case. The cytomorphic analog protein circuits use one fundamental association-dissociation-degradation building-block circuit that can be configured digitally to exactly represent any zeroth-, first-, and second-order reaction including loading, dynamics, nonlinearity, and interactions with other building-block circuits. To address a divergence issue caused by random variations in chip fabrication processes, we propose a unique way of performing computation based on total variables and conservation laws, which we instantiate at both the circuit and network levels. Thus, scalable systems that operate with finite error over infinite time can be built. We show how the building-block circuits can be composed to form various network topologies, such as cascade, fan-out, fan-in, loop, dimerization, or arbitrary networks using total variables. We demonstrate results from a system that combines interacting cytomorphic chips to simulate a cancer pathway and a glycolysis pathway. Both simulations are consistent with conventional software simulations. Our highly parallel digitally programmable analog cytomorphic systems can lead to a useful design, analysis, and simulation tool for studying arbitrary large-scale biological networks in systems and synthetic biology.

Impaired coupling of local and global functional feedbacks underlies abnormal synchronization and negative symptoms of schizophrenia.

PubMed

Noh, Kyungchul; Shin, Kyung Soon; Shin, Dongkwan; Hwang, Jae Yeon; Kim, June Sic; Jang, Joon Hwan; Chung, Chun Kee; Kwon, Jun Soo; Cho, Kwang-Hyun

2013-04-10

Abnormal synchronization of brain oscillations is found to be associated with various core symptoms of schizophrenia. However, the underlying mechanism of this association remains yet to be elucidated. In this study, we found that coupled local and global feedback (CLGF) circuits in the cortical functional network are related to the abnormal synchronization and also correlated to the negative symptom of schizophrenia. Analysis of the magnetoencephalography data obtained from patients with chronic schizophrenia during rest revealed an increase in beta band synchronization and a reduction in gamma band power compared to healthy controls. Using a feedback identification method based on non-causal impulse responses, we constructed functional feedback networks and found that CLGF circuits were significantly reduced in schizophrenia. From computational analysis on the basis of the Wilson-Cowan model, we unraveled that the CLGF circuits are critically involved in the abnormal synchronization and the dynamical switching between beta and gamma bands power in schizophrenia. Moreover, we found that the abundance of CLGF circuits was negatively correlated with the development of negative symptoms of schizophrenia, suggesting that the negative symptom is closely related to the impairment of this circuit. Our study implicates that patients with schizophrenia might have the impaired coupling of inter- and intra-regional functional feedbacks and that the CLGF circuit might serve as a critical bridge between abnormal synchronization and the negative symptoms of schizophrenia.

From structure to function, via dynamics

NASA Astrophysics Data System (ADS)

Stetter, O.; Soriano, J.; Geisel, T.; Battaglia, D.

2013-01-01

Neurons in the brain are wired into a synaptic network that spans multiple scales, from local circuits within cortical columns to fiber tracts interconnecting distant areas. However, brain function require the dynamic control of inter-circuit interactions on time-scales faster than synaptic changes. In particular, strength and direction of causal influences between neural populations (described by the so-called directed functional connectivity) must be reconfigurable even when the underlying structural connectivity is fixed. Such directed functional influences can be quantified resorting to causal analysis of time-series based on tools like Granger Causality or Transfer Entropy. The ability to quickly reorganize inter-areal interactions is a chief requirement for performance in a changing natural environment. But how can manifold functional networks stem "on demand" from an essentially fixed structure? We explore the hypothesis that the self-organization of neuronal synchronous activity underlies the control of brain functional connectivity. Based on simulated and real recordings of critical neuronal cultures in vitro, as well as on mean-field and spiking network models of interacting brain areas, we have found that "function follows dynamics", rather than structure. Different dynamic states of a same structural network, characterized by different synchronization properties, are indeed associated to different functional digraphs (functional multiplicity). We also highlight the crucial role of dynamics in establishing a structure-to-function link, by showing that whenever different structural topologies lead to similar dynamical states, than the associated functional connectivities are also very similar (structural degeneracy).

A portable monitor system for biology signal based on singlechip

NASA Astrophysics Data System (ADS)

Tu, Qiaoling; Guo, Jianhua; He, Li; Xu, Xia

2005-12-01

The objectives of the paper are to improve accuracy of the electrocardiogram and temperature signal, improve the system stability and the capability of dynamic response, and decrease power consumption and volume of the system. The basic method is making use of the inner resource of the singlechip, such as the exact constant-current source, hardware multiplier, ADC, etc. The model of singlechip is MSP430F449 of TI (Texas Instruments). A simple integral-coefficient band-rejection digital filter was designed for analyzing the electrocardiogram signal. The deviation of temperature coming from the degradation of battery voltage was compensated for. An automatic discharge access was designed in the circuit to improve the capability of dynamic response of circuit. The results indicate that the 50 Hz power frequency interfering and the baseline drift are filtered, the figure is clear, the accuracy of temperature is 0.03°C, and the consumption current is less than 1.3mA. The system can meet the requirement in ward monitor and surgery monitor.

Dynamically re-configurable CMOS imagers for an active vision system

NASA Technical Reports Server (NTRS)

Yang, Guang (Inventor); Pain, Bedabrata (Inventor)

2005-01-01

A vision system is disclosed. The system includes a pixel array, at least one multi-resolution window operation circuit, and a pixel averaging circuit. The pixel array has an array of pixels configured to receive light signals from an image having at least one tracking target. The multi-resolution window operation circuits are configured to process the image. Each of the multi-resolution window operation circuits processes each tracking target within a particular multi-resolution window. The pixel averaging circuit is configured to sample and average pixels within the particular multi-resolution window.

Low-noise pulse conditioner

DOEpatents

Bird, David A.

1983-01-01

A low-noise pulse conditioner is provided for driving electronic digital processing circuitry directly from differentially induced input pulses. The circuit uses a unique differential-to-peak detector circuit to generate a dynamic reference signal proportional to the input peak voltage. The input pulses are compared with the reference signal in an input network which operates in full differential mode with only a passive input filter. This reduces the introduction of circuit-induced noise, or jitter, generated in ground referenced input elements normally used in pulse conditioning circuits, especially speed transducer processing circuits.

Optogenetic interrogation of neural circuits: technology for probing mammalian brain structures

PubMed Central

Zhang, Feng; Gradinaru, Viviana; Adamantidis, Antoine R; Durand, Remy; Airan, Raag D; de Lecea, Luis; Deisseroth, Karl

2015-01-01

Elucidation of the neural substrates underlying complex animal behaviors depends on precise activity control tools, as well as compatible readout methods. Recent developments in optogenetics have addressed this need, opening up new possibilities for systems neuroscience. Interrogation of even deep neural circuits can be conducted by directly probing the necessity and sufficiency of defined circuit elements with millisecond-scale, cell type-specific optical perturbations, coupled with suitable readouts such as electrophysiology, optical circuit dynamics measures and freely moving behavior in mammals. Here we collect in detail our strategies for delivering microbial opsin genes to deep mammalian brain structures in vivo, along with protocols for integrating the resulting optical control with compatible readouts (electrophysiological, optical and behavioral). The procedures described here, from initial virus preparation to systems-level functional readout, can be completed within 4–5 weeks. Together, these methods may help in providing circuit-level insight into the dynamics underlying complex mammalian behaviors in health and disease. PMID:20203662

Computational fluid dynamics modelling of hydraulics and sedimentation in process reactors during aeration tank settling.

PubMed

Jensen, M D; Ingildsen, P; Rasmussen, M R; Laursen, J

2006-01-01

Aeration tank settling is a control method allowing settling in the process tank during high hydraulic load. The control method is patented. Aeration tank settling has been applied in several waste water treatment plants using the present design of the process tanks. Some process tank designs have shown to be more effective than others. To improve the design of less effective plants, computational fluid dynamics (CFD) modelling of hydraulics and sedimentation has been applied. This paper discusses the results at one particular plant experiencing problems with partly short-circuiting of the inlet and outlet causing a disruption of the sludge blanket at the outlet and thereby reducing the retention of sludge in the process tank. The model has allowed us to establish a clear picture of the problems arising at the plant during aeration tank settling. Secondly, several process tank design changes have been suggested and tested by means of computational fluid dynamics modelling. The most promising design changes have been found and reported.

Modeling of capacitor charging dynamics in an energy harvesting system considering accurate electromechanical coupling effects

NASA Astrophysics Data System (ADS)

Bagheri, Shahriar; Wu, Nan; Filizadeh, Shaahin

2018-06-01

This paper presents an iterative numerical method that accurately models an energy harvesting system charging a capacitor with piezoelectric patches. The constitutive relations of piezoelectric materials connected with an external charging circuit with a diode bridge and capacitors lead to the electromechanical coupling effect and the difficulty of deriving accurate transient mechanical response, as well as the charging progress. The proposed model is built upon the Euler-Bernoulli beam theory and takes into account the electromechanical coupling effects as well as the dynamic process of charging an external storage capacitor. The model is validated through experimental tests on a cantilever beam coated with piezoelectric patches. Several parametric studies are performed and the functionality of the model is verified. The efficiency of power harvesting system can be predicted and tuned considering variations in different design parameters. Such a model can be utilized to design robust and optimal energy harvesting system.

A Low-Power High-Dynamic-Range Receiver System for In-Probe 3-D Ultrasonic Imaging.

PubMed

Attarzadeh, Hourieh; Xu, Ye; Ytterdal, Trond

2017-10-01

In this paper, a dual-mode low-power, high dynamic-range receiver circuit is designed for the interface with a capacitive micromachined ultrasonic transducer. The proposed ultrasound receiver chip enables the development of an in-probe digital beamforming imaging system. The flexibility of having two operation modes offers a high dynamic range with minimum power sacrifice. A prototype of the chip containing one receive channel, with one variable transimpedance amplifier (TIA) and one analog to digital converter (ADC) circuit is implemented. Combining variable gain TIA functionality with ADC gain settings achieves an enhanced overall high dynamic range, while low power dissipation is maintained. The chip is designed and fabricated in a 65 nm standard CMOS process technology. The test chip occupies an area of 76[Formula: see text] 170 [Formula: see text]. A total average power range of 60-240 [Formula: see text] for a sampling frequency of 30 MHz, and a center frequency of 5 MHz is measured. An instantaneous dynamic range of 50.5 dB with an overall dynamic range of 72 dB is obtained from the receiver circuit.

Equivalent circuit simulation of HPEM-induced transient responses at nonlinear loads

NASA Astrophysics Data System (ADS)

Kotzev, Miroslav; Bi, Xiaotang; Kreitlow, Matthias; Gronwald, Frank

2017-09-01

In this paper the equivalent circuit modeling of a nonlinearly loaded loop antenna and its transient responses to HPEM field excitations are investigated. For the circuit modeling the general strategy to characterize the nonlinearly loaded antenna by a linear and a nonlinear circuit part is pursued. The linear circuit part can be determined by standard methods of antenna theory and numerical field computation. The modeling of the nonlinear circuit part requires realistic circuit models of the nonlinear loads that are given by Schottky diodes. Combining both parts, appropriate circuit models are obtained and analyzed by means of a standard SPICE circuit simulator. It is the main result that in this way full-wave simulation results can be reproduced. Furthermore it is clearly seen that the equivalent circuit modeling offers considerable advantages with respect to computation speed and also leads to improved physical insights regarding the coupling between HPEM field excitation and nonlinearly loaded loop antenna.

A Low-Power Wide Dynamic-Range Current Readout Circuit for Ion-Sensitive FET Sensors.

PubMed

Son, Hyunwoo; Cho, Hwasuk; Koo, Jahyun; Ji, Youngwoo; Kim, Byungsub; Park, Hong-June; Sim, Jae-Yoon

2017-06-01

This paper presents an amplifier-less and digital-intensive current-to-digital converter for ion-sensitive FET sensors. Capacitance on the input node is utilized as a residue accumulator, and a clocked comparator is followed for quantization. Without any continuous-time feedback circuit, the converter performs a first-order noise shaping of the quantization error. In order to minimize static power consumption, the proposed circuit employs a single-ended current-steering digital-to-analog converter which flows only the same current as the input. By adopting a switching noise averaging algorithm, our dynamic element matching not only mitigates mismatch of current sources in the current-steering DAC, but also makes the effect of dynamic switching noise become an input-independent constant. The implemented circuit in 0.35 μm CMOS converts the current input with a range of 2.8 μ A to 15 b digital output in about 4 ms, showing a DNL of +0.24/-0.25 LSB and an INL of + 1.98/-1.98 LSB while consuming 16.8 μW.

Chronic Stress Alters Striosome-Circuit Dynamics, Leading to Aberrant Decision-Making.

PubMed

Friedman, Alexander; Homma, Daigo; Bloem, Bernard; Gibb, Leif G; Amemori, Ken-Ichi; Hu, Dan; Delcasso, Sebastien; Truong, Timothy F; Yang, Joyce; Hood, Adam S; Mikofalvy, Katrina A; Beck, Dirk W; Nguyen, Norah; Nelson, Erik D; Toro Arana, Sebastian E; Vorder Bruegge, Ruth H; Goosens, Ki A; Graybiel, Ann M

2017-11-16

Effective evaluation of costs and benefits is a core survival capacity that in humans is considered as optimal, "rational" decision-making. This capacity is vulnerable in neuropsychiatric disorders and in the aftermath of chronic stress, in which aberrant choices and high-risk behaviors occur. We report that chronic stress exposure in rodents produces abnormal evaluation of costs and benefits resembling non-optimal decision-making in which choices of high-cost/high-reward options are sharply increased. Concomitantly, alterations in the task-related spike activity of medial prefrontal neurons correspond with increased activity of their striosome-predominant striatal projection neuron targets and with decreased and delayed striatal fast-firing interneuron activity. These effects of chronic stress on prefronto-striatal circuit dynamics could be blocked or be mimicked by selective optogenetic manipulation of these circuits. We suggest that altered excitation-inhibition dynamics of striosome-based circuit function could be an underlying mechanism by which chronic stress contributes to disorders characterized by aberrant decision-making under conflict. VIDEO ABSTRACT. Copyright © 2017 Elsevier Inc. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caravelli, Francesco

The dynamics of purely memristive circuits has been shown to depend on a projection operator which expresses the Kirchhoff constraints, is naturally non-local in nature, and does represent the interaction between memristors. In the present paper we show that for the case of planar circuits, for which a meaningful Hamming distance can be defined, the elements of such projector can be bounded by exponentially decreasing functions of the distance. We provide a geometrical interpretation of the projector elements in terms of determinants of Dirichlet Laplacian of the dual circuit. For the case of linearized dynamics of the circuit for whichmore » a solution is known, this can be shown to provide a light cone bound for the interaction between memristors. Furthermore, this result establishes a finite speed of propagation of signals across the network, despite the non-local nature of the system.« less

A new high dynamic range ROIC with smart light intensity control unit

NASA Astrophysics Data System (ADS)

Yazici, Melik; Ceylan, Omer; Shafique, Atia; Abbasi, Shahbaz; Galioglu, Arman; Gurbuz, Yasar

2017-05-01

This journal presents a new high dynamic range ROIC with smart pixel which consists of two pre-amplifiers that are controlled by a circuit inside the pixel. Each pixel automatically decides which pre-amplifier is used according to the incoming illumination level. Instead of using single pre-amplifier, two input pre-amplifiers, which are optimized for different signal levels, are placed inside each pixel. The smart circuit mechanism, which decides the best input circuit according to the incoming light level, is also designed for each pixel. In short, an individual pixel has the ability to select the best input amplifier circuit that performs the best/highest SNR for the incoming signal level. A 32 × 32 ROIC prototype chip is designed to demonstrate the concept in 0.18 μ m CMOS technology. The prototype is optimized for NIR and SWIR bands. Instead of a detector, process variation optimized current sources are placed inside the ROIC. The chip achieves minimum 8.6 e- input referred noise and 98.9 dB dynamic range. It has the highest dynamic range in the literature in terms of analog ROICs for SWIR band. It is operating in room temperature and power consumption is 2.8 μ W per pixel.

Vibration properties of and power harvested by a system of electromagnetic vibration energy harvesters that have electrical dynamics

NASA Astrophysics Data System (ADS)

Cooley, Christopher G.

2017-09-01

This study investigates the vibration and dynamic response of a system of coupled electromagnetic vibration energy harvesting devices that each consist of a proof mass, elastic structure, electromagnetic generator, and energy harvesting circuit with inductance, resistance, and capacitance. The governing equations for the coupled electromechanical system are derived using Newtonian mechanics and Kirchhoff circuit laws for an arbitrary number of these subsystems. The equations are cast in matrix operator form to expose the device's vibration properties. The device's complex-valued eigenvalues and eigenvectors are related to physical characteristics of its vibration. Because the electrical circuit has dynamics, these devices have more natural frequencies than typical electromagnetic vibration energy harvesters that have purely resistive circuits. Closed-form expressions for the steady state dynamic response and average power harvested are derived for devices with a single subsystem. Example numerical results for single and double subsystem devices show that the natural frequencies and vibration modes obtained from the eigenvalue problem agree with the resonance locations and response amplitudes obtained independently from forced response calculations. This agreement demonstrates the usefulness of solving eigenvalue problems for these devices. The average power harvested by the device differs substantially at each resonance. Devices with multiple subsystems have multiple modes where large amounts of power are harvested.

A CSMP Commutation Model for Design Study of a Brushless DC Motor Power Conditioner for a Cruise Missile Fin Control Actuator.

DTIC Science & Technology

1985-06-01

STUDY OF A BRUSHLESS DC MOTOR POWER CONDITIONER FOR A CRUISE MISSILE FIN CONTROL ACTUATOR CA. by Peter Norman MacMillan June 1985 Thesis Advisor: A...TYPE OF REPORT & PERIOD COVERED A CSMP Commutation Model for Design Master’s Thesis Study of a Brushless DC Motor Power June, 1985 Conditioner for a...tactical missiles. A dynamic equivalent circuit model for the analysis of a small four pole brushless DC motor fed ty a transistorized power conditioner

Enhanced electrostatic vibrational energy harvesting using integrated opposite-charged electrets

NASA Astrophysics Data System (ADS)

Tao, Kai; Wu, Jin; Tang, Lihua; Hu, Liangxing; Woh Lye, Sun; Miao, Jianmin

2017-04-01

This paper presents a sandwich-structured MEMS electret-based vibrational energy harvester (e-VEH) that has two opposite-charged electrets integrated into a single electrostatic device. Compared to the conventional two-plate configuration where the maximum charge can only be induced when the movable mass reaches its lowest position, the proposed harvester is capable of creating maximum charge induction at both the highest and the lowest extremes, leading to an enhanced output performance. As a proof of concept, an out-of-plane MEMS e-VEH device with an overall volume of about 0.24 cm3 is designed, modeled, fabricated and characterized. A holistic equivalent circuit model incorporating the mechanical dynamic model and two capacitive circuits has been established to study the charge circulations. With the fabricated prototype, the experimental analysis demonstrates the superior performance of the proposed sandwiched e-VEH: the output voltage increases by 80.9% and 18.6% at an acceleration of 5 m s-2 compared to the top electret alone and bottom electret alone configurations, respectively. The experimental results also confirm the waveform derivation with the increase of excitation, which is in good agreement with the circuit simulation results. The proposed sandwiched e-VEH topology provides an effective and convenient methodology for improving the performance of electrostatic energy harvesting devices.

Synthesis of a fully-integrated digital signal source for communications from chaotic dynamics-based oscillations

NASA Astrophysics Data System (ADS)

Glenn, Chance Michael, Sr.

This work is the conceptualization, derivation, analysis, and fabrication of a fully practical digital signal source designed from a chaotic oscillator. In it we show how a simple electronic circuit based upon the Colpitts oscillator, can be made to produce highly complex signals capable of carrying digital information. We show a direct relationship between the continuous-time chaotic oscillations produced by the circuit and the logistic map, which is discrete-time, one-dimensional map that is a fundamental paradigm for the study of chaotic systems. We demonstrate the direct encoding of binary information into the oscillations of the chaotic circuit. We demonstrate a new concept in power amplification, called syncrodyne amplification , which uses fundamental properties of chaotic oscillators to provide high-efficiency, high gain amplification of standard communication waveforms as well as typical chaotic oscillations. We show modeling results of this system providing nearly 60-dB power gain and 80% PAE for communications waveforms conforming to GMSK modulation. Finally we show results from a fabricated syncrodyne amplifier circuit operating at 2 MHz, providing over 40-dB power gain and 72% PAE, and propose design criteria for an 824--850 MHz circuit utilizing heterojunction bipolar transistors (HBTs), providing the basis for microwave frequency realization.

Signal transfer within a cultured asymmetric cortical neuron circuit

NASA Astrophysics Data System (ADS)

Isomura, Takuya; Shimba, Kenta; Takayama, Yuzo; Takeuchi, Akimasa; Kotani, Kiyoshi; Jimbo, Yasuhiko

2015-12-01

Objective. Simplified neuronal circuits are required for investigating information representation in nervous systems and for validating theoretical neural network models. Here, we developed patterned neuronal circuits using micro fabricated devices, comprising a micro-well array bonded to a microelectrode-array substrate. Approach. The micro-well array consisted of micrometre-scale wells connected by tunnels, all contained within a silicone slab called a micro-chamber. The design of the micro-chamber confined somata to the wells and allowed axons to grow through the tunnels bidirectionally but with a designed, unidirectional bias. We guided axons into the point of the arrow structure where one of the two tunnel entrances is located, making that the preferred direction. Main results. When rat cortical neurons were cultured in the wells, their axons grew through the tunnels and connected to neurons in adjoining wells. Unidirectional burst transfers and other asymmetric signal-propagation phenomena were observed via the substrate-embedded electrodes. Seventy-nine percent of burst transfers were in the forward direction. We also observed rapid propagation of activity from sites of local electrical stimulation, and significant effects of inhibitory synapse blockade on bursting activity. Significance. These results suggest that this simple, substrate-controlled neuronal circuit can be applied to develop in vitro models of the function of cortical microcircuits or deep neural networks, better to elucidate the laws governing the dynamics of neuronal networks.

Simulation of absolute amplitudes of ultrasound signals using equivalent circuits.

PubMed

Johansson, Jonny; Martinsson, Pär-Erik; Delsing, Jerker

2007-10-01

Equivalent circuits for piezoelectric devices and ultrasonic transmission media can be used to cosimulate electronics and ultrasound parts in simulators originally intended for electronics. To achieve efficient system-level optimization, it is important to simulate correct, absolute amplitude of the ultrasound signal in the system, as this determines the requirements on the electronics regarding dynamic range, circuit noise, and power consumption. This paper presents methods to achieve correct, absolute amplitude of an ultrasound signal in a simulation of a pulse-echo system using equivalent circuits. This is achieved by taking into consideration loss due to diffraction and the effect of the cable that connects the electronics and the piezoelectric transducer. The conductive loss in the transmission line that models the propagation media of the ultrasound pulse is used to model the loss due to diffraction. Results show that the simulated amplitude of the echo follows measured values well in both near and far fields, with an offset of about 10%. The use of a coaxial cable introduces inductance and capacitance that affect the amplitude of a received echo. Amplitude variations of 60% were observed when the cable length was varied between 0.07 m and 2.3 m, with simulations predicting similar variations. The high precision in the achieved results show that electronic design and system optimization can rely on system simulations alone. This will simplify the development of integrated electronics aimed at ultrasound systems.

Signal transfer within a cultured asymmetric cortical neuron circuit.

PubMed

Isomura, Takuya; Shimba, Kenta; Takayama, Yuzo; Takeuchi, Akimasa; Kotani, Kiyoshi; Jimbo, Yasuhiko

2015-12-01

Simplified neuronal circuits are required for investigating information representation in nervous systems and for validating theoretical neural network models. Here, we developed patterned neuronal circuits using micro fabricated devices, comprising a micro-well array bonded to a microelectrode-array substrate. The micro-well array consisted of micrometre-scale wells connected by tunnels, all contained within a silicone slab called a micro-chamber. The design of the micro-chamber confined somata to the wells and allowed axons to grow through the tunnels bidirectionally but with a designed, unidirectional bias. We guided axons into the point of the arrow structure where one of the two tunnel entrances is located, making that the preferred direction. When rat cortical neurons were cultured in the wells, their axons grew through the tunnels and connected to neurons in adjoining wells. Unidirectional burst transfers and other asymmetric signal-propagation phenomena were observed via the substrate-embedded electrodes. Seventy-nine percent of burst transfers were in the forward direction. We also observed rapid propagation of activity from sites of local electrical stimulation, and significant effects of inhibitory synapse blockade on bursting activity. These results suggest that this simple, substrate-controlled neuronal circuit can be applied to develop in vitro models of the function of cortical microcircuits or deep neural networks, better to elucidate the laws governing the dynamics of neuronal networks.

Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework

PubMed Central

Wang, Xiao-Jing

2016-01-01

The ability to simultaneously record from large numbers of neurons in behaving animals has ushered in a new era for the study of the neural circuit mechanisms underlying cognitive functions. One promising approach to uncovering the dynamical and computational principles governing population responses is to analyze model recurrent neural networks (RNNs) that have been optimized to perform the same tasks as behaving animals. Because the optimization of network parameters specifies the desired output but not the manner in which to achieve this output, “trained” networks serve as a source of mechanistic hypotheses and a testing ground for data analyses that link neural computation to behavior. Complete access to the activity and connectivity of the circuit, and the ability to manipulate them arbitrarily, make trained networks a convenient proxy for biological circuits and a valuable platform for theoretical investigation. However, existing RNNs lack basic biological features such as the distinction between excitatory and inhibitory units (Dale’s principle), which are essential if RNNs are to provide insights into the operation of biological circuits. Moreover, trained networks can achieve the same behavioral performance but differ substantially in their structure and dynamics, highlighting the need for a simple and flexible framework for the exploratory training of RNNs. Here, we describe a framework for gradient descent-based training of excitatory-inhibitory RNNs that can incorporate a variety of biological knowledge. We provide an implementation based on the machine learning library Theano, whose automatic differentiation capabilities facilitate modifications and extensions. We validate this framework by applying it to well-known experimental paradigms such as perceptual decision-making, context-dependent integration, multisensory integration, parametric working memory, and motor sequence generation. Our results demonstrate the wide range of neural activity patterns and behavior that can be modeled, and suggest a unified setting in which diverse cognitive computations and mechanisms can be studied. PMID:26928718

New dynamic FET logic and serial memory circuits for VLSI GaAs technology

NASA Technical Reports Server (NTRS)

Eldin, A. G.

1991-01-01

The complexity of GaAs field effect transistor (FET) very large scale integration (VLSI) circuits is limited by the maximum power dissipation while the uniformity of the device parameters determines the functional yield. In this work, digital GaAs FET circuits are presented that eliminate the DC power dissipation and reduce the area to 50% of that of the conventional static circuits. Its larger tolerance to device parameter variations results in higher functional yield.

Compact modeling of CRS devices based on ECM cells for memory, logic and neuromorphic applications.

PubMed

Linn, E; Menzel, S; Ferch, S; Waser, R

2013-09-27

Dynamic physics-based models of resistive switching devices are of great interest for the realization of complex circuits required for memory, logic and neuromorphic applications. Here, we apply such a model of an electrochemical metallization (ECM) cell to complementary resistive switches (CRSs), which are favorable devices to realize ultra-dense passive crossbar arrays. Since a CRS consists of two resistive switching devices, it is straightforward to apply the dynamic ECM model for CRS simulation with MATLAB and SPICE, enabling study of the device behavior in terms of sweep rate and series resistance variations. Furthermore, typical memory access operations as well as basic implication logic operations can be analyzed, revealing requirements for proper spike and level read operations. This basic understanding facilitates applications of massively parallel computing paradigms required for neuromorphic applications.

Miners' Misconceptions of Flow Distribution Within Circuits as a Factor Influencing Underground Mining Accidents.

NASA Astrophysics Data System (ADS)

Passaro, Perry David

Misconceptions can be thought of as naive approaches to problem solving that are perceptually appealing but incorrect and inconsistent with scientific evidence (Piaget, 1929). One type of misconception involves flow distributions within circuits. This concept is important because miners' conceptual errors about flow distribution changes within complex circuits may be in part responsible for fatal mine disasters. Based on the theory that misconceptions of flow distribution changes within circuits were responsible for underground mine disasters involving mine ventilation circuits, a series of studies was undertaken with mining engineering students, professional mining engineers, as well as mine foremen, mine supervisors, mine rescue members, mine maintenance personnel, mining researchers and working miners to identify these conceptual errors and errors in mine ventilation procedures. Results indicate that misconceptions of flow distribution changes within circuits exist in over 70 percent of the subjects sampled. It is assumed that these misconceptions of flow distribution changes within circuits result in errors of judgment when miners are faced with inferring and changing ventilation arrangements when two or more mine sections are connected. Furthermore, it is assumed that these misconceptions are pervasive in the mining industry and may be responsible for at least two mine ventilation disasters. The findings of this study are consistent with Piaget's (1929) model of figurative and operative knowledge. This model states that misconceptions are in part due to a lack of knowledge of dynamic transformations and how to apply content information. Recommendations for future research include the development of an interactive expert system for training miners with ventilation arrangements. Such a system would meet the educational recommendations made by Piaget (1973b) by involving a hands-on approach that allows discovery, interaction, the opportunity to make mistakes and to review the cognitive concepts on which the subject relied during his manipulation of the ventilation system.

Utilizing Dynamically Coupled Cores to Form a Resilient Chip Multiprocessor

DTIC Science & Technology

2007-06-01

requires a significant deviation from previous work. For instance, we find that using the relaxed input replication model from Reunion incurs a...Circuit Width Delay Count CRC-16 16 6.65 754 CRC- SDLC -16 16 6.10 888 CRC-32 16 7.28 2260 CRC-32 32 8.60 4240 Table 1. FO4 delay and transistor count for...the operation of our proposed system is the same in all other respects. 4.4 Compatibility Across Memory Consis- tency Models The memory consistency

Control of DNA strand displacement kinetics using toehold exchange.

PubMed

Zhang, David Yu; Winfree, Erik

2009-12-02

DNA is increasingly being used as the engineering material of choice for the construction of nanoscale circuits, structures, and motors. Many of these enzyme-free constructions function by DNA strand displacement reactions. The kinetics of strand displacement can be modulated by toeholds, short single-stranded segments of DNA that colocalize reactant DNA molecules. Recently, the toehold exchange process was introduced as a method for designing fast and reversible strand displacement reactions. Here, we characterize the kinetics of DNA toehold exchange and model it as a three-step process. This model is simple and quantitatively predicts the kinetics of 85 different strand displacement reactions from the DNA sequences. Furthermore, we use toehold exchange to construct a simple catalytic reaction. This work improves the understanding of the kinetics of nucleic acid reactions and will be useful in the rational design of dynamic DNA and RNA circuits and nanodevices.

The need for control of magnetic parameters for energy efficient performance of magnetic tunnel junctions

NASA Astrophysics Data System (ADS)

Farhat, I. A. H.; Gale, E.; Alpha, C.; Isakovic, A. F.

2017-07-01

Optimizing energy performance of Magnetic Tunnel Junctions (MTJs) is the key for embedding Spin Transfer Torque-Random Access Memory (STT-RAM) in low power circuits. Due to the complex interdependencies of the parameters and variables of the device operating energy, it is important to analyse parameters with most effective control of MTJ power. The impact of threshold current density, Jco , on the energy and the impact of HK on Jco are studied analytically, following the expressions that stem from Landau-Lifshitz-Gilbert-Slonczewski (LLGS-STT) model. In addition, the impact of other magnetic material parameters, such as Ms , and geometric parameters such as tfree and λ is discussed. Device modelling study was conducted to analyse the impact at the circuit level. Nano-magnetism simulation based on NMAGTM package was conducted to analyse the impact of controlling HK on the switching dynamics of the film.

Temperature control of fimbriation circuit switch in uropathogenic Escherichia coli: quantitative analysis via automated model abstraction.

PubMed

Kuwahara, Hiroyuki; Myers, Chris J; Samoilov, Michael S

2010-03-26

Uropathogenic Escherichia coli (UPEC) represent the predominant cause of urinary tract infections (UTIs). A key UPEC molecular virulence mechanism is type 1 fimbriae, whose expression is controlled by the orientation of an invertible chromosomal DNA element-the fim switch. Temperature has been shown to act as a major regulator of fim switching behavior and is overall an important indicator as well as functional feature of many urologic diseases, including UPEC host-pathogen interaction dynamics. Given this panoptic physiological role of temperature during UTI progression and notable empirical challenges to its direct in vivo studies, in silico modeling of corresponding biochemical and biophysical mechanisms essential to UPEC pathogenicity may significantly aid our understanding of the underlying disease processes. However, rigorous computational analysis of biological systems, such as fim switch temperature control circuit, has hereto presented a notoriously demanding problem due to both the substantial complexity of the gene regulatory networks involved as well as their often characteristically discrete and stochastic dynamics. To address these issues, we have developed an approach that enables automated multiscale abstraction of biological system descriptions based on reaction kinetics. Implemented as a computational tool, this method has allowed us to efficiently analyze the modular organization and behavior of the E. coli fimbriation switch circuit at different temperature settings, thus facilitating new insights into this mode of UPEC molecular virulence regulation. In particular, our results suggest that, with respect to its role in shutting down fimbriae expression, the primary function of FimB recombinase may be to effect a controlled down-regulation (rather than increase) of the ON-to-OFF fim switching rate via temperature-dependent suppression of competing dynamics mediated by recombinase FimE. Our computational analysis further implies that this down-regulation mechanism could be particularly significant inside the host environment, thus potentially contributing further understanding toward the development of novel therapeutic approaches to UPEC-caused UTIs.

Simulation model of an electrohydraulic-actuated double-clutch transmission vehicle: modelling and system design

NASA Astrophysics Data System (ADS)

Schoeftner, J.; Ebner, W.

2017-12-01

Automated and manual transmissions are the main link between engine and powertrain. The technical term when the transmission provides the desired torque during all possible driving conditions is denoted as powertrain matching. Recent developments in the last years show that double-clutch-transmissions (DCTs) are a reasonable compromise in terms of production costs, shifting quality, drivability and fuel efficiency. They have several advantages compared to other automatic transmissions (AT). Most DCTs nowadays consist of a hydraulic actuation control unit, which controls the clutches of the gearbox in order to induce a desired drivetrain torque into the driveline. The main functions of hydraulic systems are manifold: they initiate gear shifts, they provide sufficient oil for lubrication and they control the shift quality by suitably providing a desired oil flow or pressure for the clutch actuation. In this paper, a mathematical model of a passenger car equipped with a DCT is presented. The objective of this contribution is to get an increased understanding for the dynamics of the hydraulic circuit and its coupling to the vehicle drivetrain. The simulation model consists of a hydraulic and a mechanical domain: the hydraulic actuation circuit is described by nonlinear differential equations and includes the dynamics of the line pressure and the proportional valve, as well as the influence of the pressure reducing valve, pipe resistances and accumulator dynamics. The drivetrain with its gear ratios, moments of inertia, torsional stiffness of the rotating shafts and a simple longitudinal vehicle model represent the mechanical domain. The link between hydraulic and mechanical domain is given by the clutch, which combines hydraulic equations and Newton's laws. The presented mathematical model may not only be used as a simulation model for developing the transmission control software, it may also serve as a virtual layout for the design process phase. At the end of this contribution a parametric study shows the influence of the mechanical components, the accumulator and the temperature of the oil.

Useful properties of spinal circuits for learning and performing planar reaches

NASA Astrophysics Data System (ADS)

Tsianos, George A.; Goodner, Jared; Loeb, Gerald E.

2014-10-01

Objective. We developed a detailed model of the spinal circuitry plus musculoskeletal system (SC + MS) for the primate arm and investigated its role in sensorimotor control, learning and storing of movement repertoires. Approach. Recently developed models of spinal circuit connectivity, neurons and muscle force/energetics were integrated and in some cases refined to construct the most comprehensive model of the SC + MS to date. The SC + MS’s potential contributions to center-out reaching movement were assessed by employing an extremely simple model of the brain that issued only step commands. Main results. The SC + MS was able to generate physiological muscle dynamics underlying reaching across different directions, distances, speeds, and even in the midst of strong dynamic perturbations (i.e. viscous curl field). For each task, there were many different combinations of brain inputs that generated physiological performance. Natural patterns of recruitment and low metabolic cost emerged for about half of the learning trials when a purely kinematic cost function was used and for all of the trials when an estimate of metabolic energy consumption was added to the cost function. Solutions for different tasks could be interpolated to generate intermediate movement and the range over which interpolation was successful was consistent with experimental reports. Significance. This is the first demonstration that a realistic model of the SC + MS is capable of generating the required dynamics of center-out reaching. The interpolability observed is important for the feasibility of storing motor programs in memory rather than computing them from internal models of the musculoskeletal plant. Successful interpolation of command programs required them to have similar muscle recruitment patterns, which are thought by many to arise from hard-wired muscle synergies rather than learned as in our model system. These properties of the SC + MS along with its tendency to generate energetically efficient solutions might usefully be employed by motor cortex to generate voluntary behaviors such as reaching to targets.

A fractional calculus perspective of distributed propeller design

NASA Astrophysics Data System (ADS)

Tenreiro Machado, J.; Galhano, Alexandra M.

2018-02-01

A new generation of aircraft with distributed propellers leads to operational performances superior to those exhibited by standard designs. Computational simulations and experimental tests show a reduction of fuel consumption and noise. This paper proposes an analogy between aerodynamics and electrical circuits. The model reveals properties similar to those of fractional-order systems and gives a deeper insight into the dynamics of multi-propeller coupling.

Computational Models and Emergent Properties of Respiratory Neural Networks

PubMed Central

Lindsey, Bruce G.; Rybak, Ilya A.; Smith, Jeffrey C.

2012-01-01

Computational models of the neural control system for breathing in mammals provide a theoretical and computational framework bringing together experimental data obtained from different animal preparations under various experimental conditions. Many of these models were developed in parallel and iteratively with experimental studies and provided predictions guiding new experiments. This data-driven modeling approach has advanced our understanding of respiratory network architecture and neural mechanisms underlying generation of the respiratory rhythm and pattern, including their functional reorganization under different physiological conditions. Models reviewed here vary in neurobiological details and computational complexity and span multiple spatiotemporal scales of respiratory control mechanisms. Recent models describe interacting populations of respiratory neurons spatially distributed within the Bötzinger and pre-Bötzinger complexes and rostral ventrolateral medulla that contain core circuits of the respiratory central pattern generator (CPG). Network interactions within these circuits along with intrinsic rhythmogenic properties of neurons form a hierarchy of multiple rhythm generation mechanisms. The functional expression of these mechanisms is controlled by input drives from other brainstem components, including the retrotrapezoid nucleus and pons, which regulate the dynamic behavior of the core circuitry. The emerging view is that the brainstem respiratory network has rhythmogenic capabilities at multiple levels of circuit organization. This allows flexible, state-dependent expression of different neural pattern-generation mechanisms under various physiological conditions, enabling a wide repertoire of respiratory behaviors. Some models consider control of the respiratory CPG by pulmonary feedback and network reconfiguration during defensive behaviors such as cough. Future directions in modeling of the respiratory CPG are considered. PMID:23687564

Targeting circuits

PubMed Central

Rajasethupathy, Priyamvada; Ferenczi, Emily; Deisseroth, Karl

2017-01-01

Current optogenetic methodology enables precise inhibition or excitation of neural circuits, spanning timescales as needed from the acute (milliseconds) to the chronic (many days or more), for experimental modulation of network activity and animal behavior. Such broad temporal versatility, unique to optogenetic control, is particularly powerful when combined with brain activity measurements that span both acute and chronic timescales as well. This enables, for instance, the study of adaptive circuit dynamics across the intact brain, and tuning interventions to match activity patterns naturally observed during behavior in the same individual. Although the impact of this approach has been greater on basic research than on clinical translation, it is natural to ask if specific neural circuit activity patterns discovered to be involved in controlling adaptive or maladaptive behaviors could become targets for treatment of neuropsychiatric diseases. Here we consider the landscape of such ideas related to therapeutic targeting of circuit dynamics, taking note of developments not only in optical but also in ultrasonic, magnetic, and thermal methods. We note the recent emergence of first-in-kind optogenetically-guided clinical outcomes, as well as opportunities related to the integration of interventions and readouts spanning diverse circuit-physiology, molecular, and behavioral modalities. PMID:27104976

Neuromorphic log-domain silicon synapse circuits obey bernoulli dynamics: a unifying tutorial analysis

PubMed Central

Papadimitriou, Konstantinos I.; Liu, Shih-Chii; Indiveri, Giacomo; Drakakis, Emmanuel M.

2014-01-01

The field of neuromorphic silicon synapse circuits is revisited and a parsimonious mathematical framework able to describe the dynamics of this class of log-domain circuits in the aggregate and in a systematic manner is proposed. Starting from the Bernoulli Cell Formalism (BCF), originally formulated for the modular synthesis and analysis of externally linear, time-invariant logarithmic filters, and by means of the identification of new types of Bernoulli Cell (BC) operators presented here, a generalized formalism (GBCF) is established. The expanded formalism covers two new possible and practical combinations of a MOS transistor (MOST) and a linear capacitor. The corresponding mathematical relations codifying each case are presented and discussed through the tutorial treatment of three well-known transistor-level examples of log-domain neuromorphic silicon synapses. The proposed mathematical tool unifies past analysis approaches of the same circuits under a common theoretical framework. The speed advantage of the proposed mathematical framework as an analysis tool is also demonstrated by a compelling comparative circuit analysis example of high order, where the GBCF and another well-known log-domain circuit analysis method are used for the determination of the input-output transfer function of the high (4th) order topology. PMID:25653579

Neuromorphic log-domain silicon synapse circuits obey bernoulli dynamics: a unifying tutorial analysis.

PubMed

Papadimitriou, Konstantinos I; Liu, Shih-Chii; Indiveri, Giacomo; Drakakis, Emmanuel M

2014-01-01

The field of neuromorphic silicon synapse circuits is revisited and a parsimonious mathematical framework able to describe the dynamics of this class of log-domain circuits in the aggregate and in a systematic manner is proposed. Starting from the Bernoulli Cell Formalism (BCF), originally formulated for the modular synthesis and analysis of externally linear, time-invariant logarithmic filters, and by means of the identification of new types of Bernoulli Cell (BC) operators presented here, a generalized formalism (GBCF) is established. The expanded formalism covers two new possible and practical combinations of a MOS transistor (MOST) and a linear capacitor. The corresponding mathematical relations codifying each case are presented and discussed through the tutorial treatment of three well-known transistor-level examples of log-domain neuromorphic silicon synapses. The proposed mathematical tool unifies past analysis approaches of the same circuits under a common theoretical framework. The speed advantage of the proposed mathematical framework as an analysis tool is also demonstrated by a compelling comparative circuit analysis example of high order, where the GBCF and another well-known log-domain circuit analysis method are used for the determination of the input-output transfer function of the high (4(th)) order topology.

A hardware experimental platform for neural circuits in the auditory cortex

NASA Astrophysics Data System (ADS)

Rodellar-Biarge, Victoria; García-Dominguez, Pablo; Ruiz-Rizaldos, Yago; Gómez-Vilda, Pedro

2011-05-01

Speech processing in the human brain is a very complex process far from being fully understood although much progress has been done recently. Neuromorphic Speech Processing is a new research orientation in bio-inspired systems approach to find solutions to automatic treatment of specific problems (recognition, synthesis, segmentation, diarization, etc) which can not be adequately solved using classical algorithms. In this paper a neuromorphic speech processing architecture is presented. The systematic bottom-up synthesis of layered structures reproduce the dynamic feature detection of speech related to plausible neural circuits which work as interpretation centres located in the Auditory Cortex. The elementary model is based on Hebbian neuron-like units. For the computation of the architecture a flexible framework is proposed in the environment of Matlab®/Simulink®/HDL, which allows building models in different description styles, complexity and implementation levels. It provides a flexible platform for experimenting on the influence of the number of neurons and interconnections, in the precision of the results and in performance evaluation. The experimentation with different architecture configurations may help both in better understanding how neural circuits may work in the brain as well as in how speech processing can benefit from this understanding.

GaAs digital dynamic IC's for applications up to 10 GHz

NASA Astrophysics Data System (ADS)

Rocchi, M.; Gabillard, B.

1983-06-01

To evaluate the potentiality of GaAs MESFET's as transmitting gates, dynamic TT-bar flip-flops have been fabricated using a self-aligned planar process. The maximum operating frequency is 10.2 GHz, which is the best speed performance ever reported for a digital circuit. The performance of the transmitting gates within the circuits are discussed in detail. Speed improvement and topological simplification of fully static LSI subsystems are investigated.

Design of High Speed and Low Offset Dynamic Latch Comparator in 0.18 µm CMOS Process

PubMed Central

Rahman, Labonnah Farzana; Reaz, Mamun Bin Ibne; Yin, Chia Chieu; Ali, Mohammad Alauddin Mohammad; Marufuzzaman, Mohammad

2014-01-01

The cross-coupled circuit mechanism based dynamic latch comparator is presented in this research. The comparator is designed using differential input stages with regenerative S-R latch to achieve lower offset, lower power, higher speed and higher resolution. In order to decrease circuit complexity, a comparator should maintain power, speed, resolution and offset-voltage properly. Simulations show that this novel dynamic latch comparator designed in 0.18 µm CMOS technology achieves 3.44 mV resolution with 8 bit precision at a frequency of 50 MHz while dissipating 158.5 µW from 1.8 V supply and 88.05 µA average current. Moreover, the proposed design propagates as fast as 4.2 nS with energy efficiency of 0.7 fJ/conversion-step. Additionally, the core circuit layout only occupies 0.008 mm2. PMID:25299266

An improved low-voltage ride-through performance of DFIG based wind plant using stator dynamic composite fault current limiter.

PubMed

Gayen, P K; Chatterjee, D; Goswami, S K

2016-05-01

In this paper, an enhanced low-voltage ride-through (LVRT) performance of a grid connected doubly fed induction generator (DFIG) has been presented with the usage of stator dynamic composite fault current limiter (SDCFCL). This protection circuit comprises of a suitable series resistor-inductor combination and parallel bidirectional semiconductor switch. The SDCFCL facilitates double benefits such as reduction of rotor induced open circuit voltage due to increased value of stator total inductance and concurrent increase of rotor impedance. Both effects will limit rotor circuit over current and over voltage situation more secured way in comparison to the conventional scheme like the dynamic rotor current limiter (RCL) during any type of fault situation. The proposed concept is validated through the simulation study of the grid integrated 2.0MW DFIG. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

From the motor cortex to the movement and back again.

PubMed

Teka, Wondimu W; Hamade, Khaldoun C; Barnett, William H; Kim, Taegyo; Markin, Sergey N; Rybak, Ilya A; Molkov, Yaroslav I

2017-01-01

The motor cortex controls motor behaviors by generating movement-specific signals and transmitting them through spinal cord circuits and motoneurons to the muscles. Precise and well-coordinated muscle activation patterns are necessary for accurate movement execution. Therefore, the activity of cortical neurons should correlate with movement parameters. To investigate the specifics of such correlations among activities of the motor cortex, spinal cord network and muscles, we developed a model for neural control of goal-directed reaching movements that simulates the entire pathway from the motor cortex through spinal cord circuits to the muscles controlling arm movements. In this model, the arm consists of two joints (shoulder and elbow), whose movements are actuated by six muscles (4 single-joint and 2 double-joint flexors and extensors). The muscles provide afferent feedback to the spinal cord circuits. Cortical neurons are defined as cortical "controllers" that solve an inverse problem based on a proposed straight-line trajectory to a target position and a predefined bell-shaped velocity profile. Thus, the controller generates a motor program that produces a task-specific activation of low-level spinal circuits that in turn induce the muscle activation realizing the intended reaching movement. Using the model, we describe the mechanisms of correlation between cortical and motoneuronal activities and movement direction and other movement parameters. We show that the directional modulation of neuronal activity in the motor cortex and the spinal cord may result from direction-specific dynamics of muscle lengths. Our model suggests that directional modulation first emerges at the level of muscle forces, augments at the motoneuron level, and further increases at the level of the motor cortex due to the dependence of frictional forces in the joints, contractility of the muscles and afferent feedback on muscle lengths and/or velocities.

Electrical equivalent circuit for microstrip micro-plasma: control of EM propagation and numerical simulations.

PubMed

Mohamad, Almustafa; Tân-Hoa, Vuong; Jacques, David

2012-01-01

An approach to determine an equivalent electrical circuit of a micro planar discharge on a microstrip printed circuit is reported. The micro discharge is used to realize a dynamic microwave switching circuit. This approach is based on the measurement of the discharge current and the transmission coefficient for a given frequency 2.45 GHz. Numerical methods like FEM can be used to study the effect of plasma parameters on the propagation of electromagnetic waves through a microstrip printed circuit. Plasma behaves as flexible elements that can change its electrical proprieties such as conductivity.

Basic dynamics from a pulse-coupled network of autonomous integrate-and-fire chaotic circuits.

PubMed

Nakano, H; Saito, T

2002-01-01

This paper studies basic dynamics from a novel pulse-coupled network (PCN). The unit element of the PCN is an integrate-and-fire circuit (IFC) that exhibits chaos. We an give an iff condition for the chaos generation. Using two IFC, we construct a master-slave PCN. It exhibits interesting chaos synchronous phenomena and their breakdown phenomena. We give basic classification of the phenomena and their existence regions can be elucidated in the parameter space. We then construct a ring-type PCN and elucidate that the PCN exhibits interesting grouping phenomena based on the chaos synchronization patterns. Using a simple test circuit, some of typical phenomena can be verified in the laboratory.

Observation of the Topological Change Associated with the Dynamical Monodromy

NASA Astrophysics Data System (ADS)

Salmon, Daniel; Nerem, Matthew; Aubin, Seth; Delos, John

2017-04-01

Classical mechanics is an old theory and new phenomena do not often appear. A recently predicted phenomenon is called ``Dynamical Monodromy.'' Monodromy is the study of the behavior of a system as it evolves ``once around a closed circuit''. Systems that do not return to their original state after forming a closed circuit in some space are said to exhibit ``nontrivial monodromy.'' One such system is a collection of non-interacting particles moving in a ``champagne bottle'' potential. A loop of trajectories of this system exhibits a topological change when each of the particles traverse a monodromy circuit in Energy-Angular Momentum space (any closed path that encloses the singular point at the origin). This system has been realized using a rigid spherical pendulum, with a permanent magnet at its end. Magnetic fields generated by coils are used to create the champagne-bottle potential, as well as drive the pendulum through the monodromy circuit.

Carbon Nanotube Driver Circuit for 6 × 6 Organic Light Emitting Diode Display

NASA Astrophysics Data System (ADS)

Zou, Jianping; Zhang, Kang; Li, Jingqi; Zhao, Yongbiao; Wang, Yilei; Pillai, Suresh Kumar Raman; Volkan Demir, Hilmi; Sun, Xiaowei; Chan-Park, Mary B.; Zhang, Qing

2015-06-01

Single-walled carbon nanotube (SWNT) is expected to be a very promising material for flexible and transparent driver circuits for active matrix organic light emitting diode (AM OLED) displays due to its high field-effect mobility, excellent current carrying capacity, optical transparency and mechanical flexibility. Although there have been several publications about SWNT driver circuits, none of them have shown static and dynamic images with the AM OLED displays. Here we report on the first successful chemical vapor deposition (CVD)-grown SWNT network thin film transistor (TFT) driver circuits for static and dynamic AM OLED displays with 6 × 6 pixels. The high device mobility of ~45 cm2V-1s-1 and the high channel current on/off ratio of ~105 of the SWNT-TFTs fully guarantee the control capability to the OLED pixels. Our results suggest that SWNT-TFTs are promising backplane building blocks for future OLED displays.

Carbon Nanotube Driver Circuit for 6 × 6 Organic Light Emitting Diode Display.

PubMed

Zou, Jianping; Zhang, Kang; Li, Jingqi; Zhao, Yongbiao; Wang, Yilei; Pillai, Suresh Kumar Raman; Volkan Demir, Hilmi; Sun, Xiaowei; Chan-Park, Mary B; Zhang, Qing

2015-06-29

Single-walled carbon nanotube (SWNT) is expected to be a very promising material for flexible and transparent driver circuits for active matrix organic light emitting diode (AM OLED) displays due to its high field-effect mobility, excellent current carrying capacity, optical transparency and mechanical flexibility. Although there have been several publications about SWNT driver circuits, none of them have shown static and dynamic images with the AM OLED displays. Here we report on the first successful chemical vapor deposition (CVD)-grown SWNT network thin film transistor (TFT) driver circuits for static and dynamic AM OLED displays with 6 × 6 pixels. The high device mobility of ~45 cm(2)V(-1)s(-1) and the high channel current on/off ratio of ~10(5) of the SWNT-TFTs fully guarantee the control capability to the OLED pixels. Our results suggest that SWNT-TFTs are promising backplane building blocks for future OLED displays.

Tomonaga-Luttinger physics in electronic quantum circuits.

PubMed

Jezouin, S; Albert, M; Parmentier, F D; Anthore, A; Gennser, U; Cavanna, A; Safi, I; Pierre, F

2013-01-01

In one-dimensional conductors, interactions result in correlated electronic systems. At low energy, a hallmark signature of the so-called Tomonaga-Luttinger liquids is the universal conductance curve predicted in presence of an impurity. A seemingly different topic is the quantum laws of electricity, when distinct quantum conductors are assembled in a circuit. In particular, the conductances are suppressed at low energy, a phenomenon called dynamical Coulomb blockade. Here we investigate the conductance of mesoscopic circuits constituted by a short single-channel quantum conductor in series with a resistance, and demonstrate a proposed link to Tomonaga-Luttinger physics. We reformulate and establish experimentally a recently derived phenomenological expression for the conductance using a wide range of circuits, including carbon nanotube data obtained elsewhere. By confronting both conductance data and phenomenological expression with the universal Tomonaga-Luttinger conductance curve, we demonstrate experimentally the predicted mapping between dynamical Coulomb blockade and the transport across a Tomonaga-Luttinger liquid with an impurity.

Dynamic load simulator

NASA Technical Reports Server (NTRS)

Joncas, K. P.

1972-01-01

Concepts and techniques for identifying and simulating both the steady state and dynamic characteristics of electrical loads for use during integrated system test and evaluation are discussed. The investigations showed that it is feasible to design and develop interrogation and simulation equipment to perform the desired functions. During the evaluation, actual spacecraft loads were interrogated by stimulating the loads with their normal input voltage and measuring the resultant voltage and current time histories. Elements of the circuits were optimized by an iterative process of selecting element values and comparing the time-domain response of the model with those obtained from the real equipment during interrogation.

The effect of a gamma ray flare on Schumann resonances

NASA Astrophysics Data System (ADS)

Nickolaenko, A. P.; Kudintseva, I. G.; Pechony, O.; Hayakawa, M.; Hobara, Y.; Tanaka, Y. T.

2012-09-01

We describe the ionospheric modification by the SGR 1806-20 gamma flare (27 December 2004) seen in the global electromagnetic (Schumann) resonance. The gamma rays lowered the ionosphere over the dayside of the globe and modified the Schumann resonance spectra. We present the extremely low frequency (ELF) data monitored at the Moshiri observatory, Japan (44.365° N, 142.24° E). Records are compared with the expected modifications, which facilitate detection of the simultaneous abrupt change in the dynamic resonance pattern of the experimental record. The gamma flare modified the current of the global electric circuit and thus caused the "parametric" ELF transient. Model results are compared with observations enabling evaluation of changes in the global electric circuit.

A new two-scroll chaotic attractor with three quadratic nonlinearities, its adaptive control and circuit design

NASA Astrophysics Data System (ADS)

Lien, C.-H.; Vaidyanathan, S.; Sambas, A.; Sukono; Mamat, M.; Sanjaya, W. S. M.; Subiyanto

2018-03-01

A 3-D new two-scroll chaotic attractor with three quadratic nonlinearities is investigated in this paper. First, the qualitative and dynamical properties of the new two-scroll chaotic system are described in terms of phase portraits, equilibrium points, Lyapunov exponents, Kaplan-Yorke dimension, dissipativity, etc. We show that the new two-scroll dissipative chaotic system has three unstable equilibrium points. As an engineering application, global chaos control of the new two-scroll chaotic system with unknown system parameters is designed via adaptive feedback control and Lyapunov stability theory. Furthermore, an electronic circuit realization of the new chaotic attractor is presented in detail to confirm the feasibility of the theoretical chaotic two-scroll attractor model.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, R.; Lu, R.; Gong, S.

We demonstrate a room-temperature semiconductor-based photodetector where readout is achieved using a resonant radio-frequency (RF) circuit consisting of a microstrip split-ring resonator coupled to a microstrip busline, fabricated on a semiconductor substrate. The RF resonant circuits are characterized at RF frequencies as function of resonator geometry, as well as for their response to incident IR radiation. The detectors are modeled analytically and using commercial simulation software, with good agreement to our experimental results. Though the detector sensitivity is weak, the detector architecture offers the potential for multiplexing arrays of detectors on a single read-out line, in addition to high speedmore » response for either direct coupling of optical signals to RF circuitry, or alternatively, carrier dynamics characterization of semiconductor, or other, material systems.« less

Ion bipolar junction transistors

PubMed Central

Tybrandt, Klas; Larsson, Karin C.; Richter-Dahlfors, Agneta; Berggren, Magnus

2010-01-01

Dynamic control of chemical microenvironments is essential for continued development in numerous fields of life sciences. Such control could be achieved with active chemical circuits for delivery of ions and biomolecules. As the basis for such circuitry, we report a solid-state ion bipolar junction transistor (IBJT) based on conducting polymers and thin films of anion- and cation-selective membranes. The IBJT is the ionic analogue to the conventional semiconductor BJT and is manufactured using standard microfabrication techniques. Transistor characteristics along with a model describing the principle of operation, in which an anionic base current amplifies a cationic collector current, are presented. By employing the IBJT as a bioelectronic circuit element for delivery of the neurotransmitter acetylcholine, its efficacy in modulating neuronal cell signaling is demonstrated. PMID:20479274

Low-noise pulse conditioner

DOEpatents

Bird, D.A.

1981-06-16

A low-noise pulse conditioner is provided for driving electronic digital processing circuitry directly from differentially induced input pulses. The circuit uses a unique differential-to-peak detector circuit to generate a dynamic reference signal proportional to the input peak voltage. The input pulses are compared with the reference signal in an input network which operates in full differential mode with only a passive input filter. This reduces the introduction of circuit-induced noise, or jitter, generated in ground referenced input elements normally used in pulse conditioning circuits, especially speed transducer processing circuits. This circuit may be used for conditioning the sensor signal from the Fidler coil in a gas centrifuge for separation of isotopic gaseous mixtures.

Position sensor for a fuel injection element in an internal combustion engine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fulkerson, D.E.; Geske, M.L.

1987-08-18

This patent describes an electronic circuit for dynamically sensing and processing signals representative of changes in a magnet field, the circuit comprising: means for sensing a change in a magnetic field external to the circuit and providing an output representative of the change; circuit means electronically coupled with the output of the sensing means for providing an output indicating the presence of the magnetic field change; and a nulling circuit coupled with the output of the sensing means and across the indicating circuit means for nulling the electronic circuit responsive to the sensing means output, to thereby avoid ambient magneticmore » fields temperature and process variations, and wherein the nulling circuit comprises a capacitor coupled to the output of the nulling circuit, means for charging and discharging the capacitor responsive to any imbalance in the input to the nulling circuit, and circuit means coupling the capacitor with the output of the sensing means for nulling any imbalance during the charging or discharging of the capacitor.« less

Population clocks: motor timing with neural dynamics

PubMed Central

Buonomano, Dean V.; Laje, Rodrigo

2010-01-01

An understanding of sensory and motor processing will require elucidation of the mechanisms by which the brain tells time. Open questions relate to whether timing relies on dedicated or intrinsic mechanisms and whether distinct mechanisms underlie timing across scales and modalities. Although experimental and theoretical studies support the notion that neural circuits are intrinsically capable of sensory timing on short scales, few general models of motor timing have been proposed. For one class of models, population clocks, it is proposed that time is encoded in the time-varying patterns of activity of a population of neurons. We argue that population clocks emerge from the internal dynamics of recurrently connected networks, are biologically realistic and account for many aspects of motor timing. PMID:20889368

Sensitive detection of proteasomal activation using the Deg-On mammalian synthetic gene circuit.

PubMed

Zhao, Wenting; Bonem, Matthew; McWhite, Claire; Silberg, Jonathan J; Segatori, Laura

2014-04-08

The ubiquitin proteasome system (UPS) has emerged as a drug target for diverse diseases characterized by altered proteostasis, but pharmacological agents that enhance UPS activity have been challenging to establish. Here we report the Deg-On system, a genetic inverter that translates proteasomal degradation of the transcriptional regulator TetR into a fluorescent signal, thereby linking UPS activity to an easily detectable output, which can be tuned using tetracycline. We demonstrate that this circuit responds to modulation of UPS activity in cell culture arising from the inhibitor MG-132 and activator PA28γ. Guided by predictive modelling, we enhanced the circuit's signal sensitivity and dynamic range by introducing a feedback loop that enables self-amplification of TetR. By linking UPS activity to a simple and tunable fluorescence output, these genetic inverters will enable a variety of applications, including screening for UPS activating molecules and selecting for mammalian cells with different levels of proteasome activity.

Free-Standing Organic Transistors and Circuits with Sub-Micron Thicknesses

PubMed Central

Fukuda, Kenjiro; Sekine, Tomohito; Shiwaku, Rei; Morimoto, Takuya; Kumaki, Daisuke; Tokito, Shizuo

2016-01-01

The realization of wearable electronic devices with extremely thin and flexible form factors has been a major technological challenge. While substrates typically limit the thickness of thin-film electronic devices, they are usually necessary for their fabrication and functionality. Here we report on ultra-thin organic transistors and integrated circuits using device components whose substrates that have been removed. The fabricated organic circuits with total device thicknesses down to 350 nm have electrical performance levels close to those fabricated on conventional flexible substrates. Moreover, they exhibit excellent mechanical robustness, whereby their static and dynamic electrical characteristics do not change even under 50% compressive strain. Tests using systematically applied compressive strains reveal that these free-standing organic transistors possess anisotropic mechanical stability, and a strain model for a multilayer stack can be used to describe the strain in this sort of ultra-thin device. These results show the feasibility of ultimate-thin organic electronic devices using free-standing constructions. PMID:27278828

System theoretic models for high density VLSI structures

NASA Astrophysics Data System (ADS)

Dickinson, Bradley W.; Hopkins, William E., Jr.

This research project involved the development of mathematical models for analysis, synthesis, and simulation of large systems of interacting devices. The work was motivated by problems that may become important in high density VLSI chips with characteristic feature sizes less than 1 micron: it is anticipated that interactions of neighboring devices will play an important role in the determination of circuit properties. It is hoped that the combination of high device densities and such local interactions can somehow be exploited to increase circuit speed and to reduce power consumption. To address these issues from the point of view of system theory, research was pursued in the areas of nonlinear and stochastic systems and into neural network models. Statistical models were developed to characterize various features of the dynamic behavior of interacting systems. Random process models for studying the resulting asynchronous modes of operation were investigated. The local interactions themselves may be modeled as stochastic effects. The resulting behavior was investigated through the use of various scaling limits, and by a combination of other analytical and simulation techniques. Techniques arising in a variety of disciplines where models of interaction were formulated and explored were considered and adapted for use.

Atmospheric Turbulence Modeling for Aero Vehicles: Fractional Order Fits

NASA Technical Reports Server (NTRS)

Kopasakis, George

2015-01-01

Atmospheric turbulence models are necessary for the design of both inlet/engine and flight controls, as well as for studying coupling between the propulsion and the vehicle structural dynamics for supersonic vehicles. Models based on the Kolmogorov spectrum have been previously utilized to model atmospheric turbulence. In this paper, a more accurate model is developed in its representative fractional order form, typical of atmospheric disturbances. This is accomplished by first scaling the Kolmogorov spectral to convert them into finite energy von Karman forms and then by deriving an explicit fractional circuit-filter type analog for this model. This circuit model is utilized to develop a generalized formulation in frequency domain to approximate the fractional order with the products of first order transfer functions, which enables accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.

Atmospheric Turbulence Modeling for Aero Vehicles: Fractional Order Fits

NASA Technical Reports Server (NTRS)

Kopasakis, George

2010-01-01

Atmospheric turbulence models are necessary for the design of both inlet/engine and flight controls, as well as for studying coupling between the propulsion and the vehicle structural dynamics for supersonic vehicles. Models based on the Kolmogorov spectrum have been previously utilized to model atmospheric turbulence. In this paper, a more accurate model is developed in its representative fractional order form, typical of atmospheric disturbances. This is accomplished by first scaling the Kolmogorov spectral to convert them into finite energy von Karman forms and then by deriving an explicit fractional circuit-filter type analog for this model. This circuit model is utilized to develop a generalized formulation in frequency domain to approximate the fractional order with the products of first order transfer functions, which enables accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.

Auto-programmable impulse neural circuits

NASA Technical Reports Server (NTRS)

Watula, D.; Meador, J.

1990-01-01

Impulse neural networks use pulse trains to communicate neuron activation levels. Impulse neural circuits emulate natural neurons at a more detailed level than that typically employed by contemporary neural network implementation methods. An impulse neural circuit which realizes short term memory dynamics is presented. The operation of that circuit is then characterized in terms of pulse frequency modulated signals. Both fixed and programmable synapse circuits for realizing long term memory are also described. The implementation of a simple and useful unsupervised learning law is then presented. The implementation of a differential Hebbian learning rule for a specific mean-frequency signal interpretation is shown to have a straightforward implementation using digital combinational logic with a variation of a previously developed programmable synapse circuit. This circuit is expected to be exploited for simple and straightforward implementation of future auto-adaptive neural circuits.

Circuit variability interacts with excitatory-inhibitory diversity of interneurons to regulate network encoding capacity.

PubMed

Tsai, Kuo-Ting; Hu, Chin-Kun; Li, Kuan-Wei; Hwang, Wen-Liang; Chou, Ya-Hui

2018-05-23

Local interneurons (LNs) in the Drosophila olfactory system exhibit neuronal diversity and variability, yet it is still unknown how these features impact information encoding capacity and reliability in a complex LN network. We employed two strategies to construct a diverse excitatory-inhibitory neural network beginning with a ring network structure and then introduced distinct types of inhibitory interneurons and circuit variability to the simulated network. The continuity of activity within the node ensemble (oscillation pattern) was used as a readout to describe the temporal dynamics of network activity. We found that inhibitory interneurons enhance the encoding capacity by protecting the network from extremely short activation periods when the network wiring complexity is very high. In addition, distinct types of interneurons have differential effects on encoding capacity and reliability. Circuit variability may enhance the encoding reliability, with or without compromising encoding capacity. Therefore, we have described how circuit variability of interneurons may interact with excitatory-inhibitory diversity to enhance the encoding capacity and distinguishability of neural networks. In this work, we evaluate the effects of different types and degrees of connection diversity on a ring model, which may simulate interneuron networks in the Drosophila olfactory system or other biological systems.

A megahertz-frequency tunable piecewise-linear electromechanical resonator realized via nonlinear feedback

NASA Astrophysics Data System (ADS)

Bajaj, Nikhil; Chiu, George T.-C.; Rhoads, Jeffrey F.

2018-07-01

Vibration-based sensing modalities traditionally have relied upon monitoring small shifts in natural frequency in order to detect structural changes (such as those in mass or stiffness). In contrast, bifurcation-based sensing schemes rely on the detection of a qualitative change in the behavior of a system as a parameter is varied. This can produce easy-to-detect changes in response amplitude with high sensitivity to structural change, but requires resonant devices with specific dynamic behavior which is not always easily reproduced. Desirable behavior for such devices can be produced reliably via nonlinear feedback circuitry, but has in past efforts been largely limited to sub-MHz operation, partially due to the time delay limitations present in certain nonlinear feedback circuits, such as multipliers. This work demonstrates the design and implementation of a piecewise-linear resonator realized via diode- and integrated circuit-based feedback electronics and a quartz crystal resonator. The proposed system is fabricated and characterized, and the creation and selective placement of the bifurcation points of the overall electromechanical system is demonstrated by tuning the circuit gains. The demonstrated circuit operates at 16 MHz. Preliminary modeling and analysis is presented that qualitatively agrees with the experimentally-observed behavior.

Dynamic Recrystallization Model for Whisker and Hillock Growth

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vianco, Paul T.; Neilsen, Michael K.

2015-07-01

Tin (Sn) whiskers are not a recent development. Studies in the late 1930’s investigated thin filaments that grew spontaneously from Sn coatings used for the corrosion protection of electronic hardware. It was soon recognized that these Sn filaments,or whiskers, could create short circuits in the same electronic equipment. Figure 1a illustrates whisker growth in the hole of a printed circuit board having an immersion Sn surface finish. The engineering solution was to contaminate the Sn with > 3wt.% of lead (Pb). The result was that whisker growth was replaced with hillock formation (Fig. 1b) that posed a minimal reliability concerntomore » electrical circuits. Today, Pb-containing finishes are being replaced with pure Sn coatings to meet environmental restrictions on Pb use. The same short-circuit concerns have been raised, once again, with respect to Sn whiskers. The present authors have taken the approach that, in order to develop more widely applicable, first-principles strategies to mitigate Sn whisker formation, it is necessary to understand the fundamental mechanism(s) and rate kinetics underlying their development. Numerous mechanisms have been proposed by other authors to describe whisker growth, including static recrystallization by Boguslavsky and Bush.« less

Signals and circuits in the purkinje neuron.

PubMed

Abrams, Zéev R; Zhang, Xiang

2011-01-01

Purkinje neurons (PN) in the cerebellum have over 100,000 inputs organized in an orthogonal geometry, and a single output channel. As the sole output of the cerebellar cortex layer, their complex firing pattern has been associated with motor control and learning. As such they have been extensively modeled and measured using tools ranging from electrophysiology and neuroanatomy, to dynamic systems and artificial intelligence methods. However, there is an alternative approach to analyze and describe the neuronal output of these cells using concepts from electrical engineering, particularly signal processing and digital/analog circuits. By viewing the PN as an unknown circuit to be reverse-engineered, we can use the tools that provide the foundations of today's integrated circuits and communication systems to analyze the Purkinje system at the circuit level. We use Fourier transforms to analyze and isolate the inherent frequency modes in the PN and define three unique frequency ranges associated with the cells' output. Comparing the PN to a signal generator that can be externally modulated adds an entire level of complexity to the functional role of these neurons both in terms of data analysis and information processing, relying on Fourier analysis methods in place of statistical ones. We also re-describe some of the recent literature in the field, using the nomenclature of signal processing. Furthermore, by comparing the experimental data of the past decade with basic electronic circuitry, we can resolve the outstanding controversy in the field, by recognizing that the PN can act as a multivibrator circuit.

Input clustering in the normal and learned circuits of adult barn owls.

PubMed

McBride, Thomas J; DeBello, William M

2015-05-01

Experience-dependent formation of synaptic input clusters can occur in juvenile brains. Whether this also occurs in adults is largely unknown. We previously reconstructed the normal and learned circuits of prism-adapted barn owls and found that changes in clustering of axo-dendritic contacts (putative synapses) predicted functional circuit strength. Here we asked whether comparable changes occurred in normal and prism-removed adults. Across all anatomical zones, no systematic differences in the primary metrics for within-branch or between-branch clustering were observed: 95-99% of contacts resided within clusters (<10-20 μm from nearest neighbor) regardless of circuit strength. Bouton volumes, a proxy measure of synaptic strength, were on average larger in the functionally strong zones, indicating that changes in synaptic efficacy contributed to the differences in circuit strength. Bootstrap analysis showed that the distribution of inter-contact distances strongly deviated from random not in the functionally strong zones but in those that had been strong during the sensitive period (60-250 d), indicating that clusters formed early in life were preserved regardless of current value. While cluster formation in juveniles appeared to require the production of new synapses, cluster formation in adults did not. In total, these results support a model in which high cluster dynamics in juveniles sculpt a potential connectivity map that is refined in adulthood. We propose that preservation of clusters in functionally weak adult circuits provides a storage mechanism for disused but potentially useful pathways. Copyright © 2015 Elsevier Inc. All rights reserved.

Network motifs – recurring circuitry components in biological systems

EPA Science Inventory

Environmental perturbations, elicited by chemicals, dietary supplements, and drugs, can alter the dynamics of the molecular circuits and networks operating in cells, leading to multiple disease endpoints. Multi-component signal transduction pathways and gene regulatory circuits u...

Use of vacuum tubes in test instrumentation for measuring characteristics of fast high-voltage semiconductor devices

NASA Technical Reports Server (NTRS)

Berning, D.

1981-01-01

Circuits are described that permit measurement of fast events occurring in power semiconductors. These circuits were developed for the dynamic characterization of transistors used in inductive-load switching applications. Fast voltage clamping using vacuum diodes is discussed, and reference is made to a unique circuit that was built for performing nondestructive, reverse-bias, second-breakdown tests on transistors.

2.5 Gbit/s Optical Receiver Front-End Circuit with High Sensitivity and Wide Dynamic Range

NASA Astrophysics Data System (ADS)

Zhu, Tiezhu; Mo, Taishan; Ye, Tianchun

2017-12-01

An optical receiver front-end circuit is designed for passive optical network and fabricated in a 0.18 um CMOS technology. The whole circuit consists of a transimpedance amplifier (TIA), a single-ended to differential amplifier and an output driver. The TIA employs a cascode stage as the input stage and auxiliary amplifier to reduce the miller effect. Current injecting technique is employed to enlarge the input transistor's transconductance, optimize the noise performance and overcome the lack of voltage headroom. To achieve a wide dynamic range, an automatic gain control circuit with self-adaptive function is proposed. Experiment results show an optical sensitivity of -28 dBm for a bit error rate of 10-10 at 2.5 Gbit/s and a maxim input optical power of 2 dBm using an external photodiode. The chip occupies an area of 1×0.9 mm2 and consumes around 30 mW from single 1.8 V supply. The front-end circuit can be used in various optical receivers.

Modeling Zone-3 Protection with Generic Relay Models for Dynamic Contingency Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Qiuhua; Vyakaranam, Bharat GNVSR; Diao, Ruisheng

This paper presents a cohesive approach for calculating and coordinating the settings of multiple zone-3 protections for dynamic contingency analysis. The zone-3 protections are represented by generic distance relay models. A two-step approach for determining zone-3 relay settings is proposed. The first step is to calculate settings, particularly, the reach, of each zone-3 relay individually by iteratively running line open-end fault short circuit analysis; the blinder is also employed and properly set to meet the industry standard under extreme loading conditions. The second step is to systematically coordinate the protection settings of the zone-3 relays. The main objective of thismore » coordination step is to address the over-reaching issues. We have developed a tool to automate the proposed approach and generate the settings of all distance relays in a PSS/E dyr format file. The calculated zone-3 settings have been tested on a modified IEEE 300 system using a dynamic contingency analysis tool (DCAT).« less

A Scalable Multicore Architecture With Heterogeneous Memory Structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs).

PubMed

Moradi, Saber; Qiao, Ning; Stefanini, Fabio; Indiveri, Giacomo

2018-02-01

Neuromorphic computing systems comprise networks of neurons that use asynchronous events for both computation and communication. This type of representation offers several advantages in terms of bandwidth and power consumption in neuromorphic electronic systems. However, managing the traffic of asynchronous events in large scale systems is a daunting task, both in terms of circuit complexity and memory requirements. Here, we present a novel routing methodology that employs both hierarchical and mesh routing strategies and combines heterogeneous memory structures for minimizing both memory requirements and latency, while maximizing programming flexibility to support a wide range of event-based neural network architectures, through parameter configuration. We validated the proposed scheme in a prototype multicore neuromorphic processor chip that employs hybrid analog/digital circuits for emulating synapse and neuron dynamics together with asynchronous digital circuits for managing the address-event traffic. We present a theoretical analysis of the proposed connectivity scheme, describe the methods and circuits used to implement such scheme, and characterize the prototype chip. Finally, we demonstrate the use of the neuromorphic processor with a convolutional neural network for the real-time classification of visual symbols being flashed to a dynamic vision sensor (DVS) at high speed.

Digital model of a vacuum circuit breaker for the analysis of switching waveforms in electrical circuits

NASA Astrophysics Data System (ADS)

Budzisz, Joanna; Wróblewski, Zbigniew

2016-03-01

The article presents a method of modelling a vaccum circuit breaker in the ATP/EMTP package, the results of the verification of the correctness of the developed digital circuit breaker model operation and its practical usefulness for analysis of overvoltages and overcurrents occurring in commutated capacitive electrical circuits and also examples of digital simulations of overvoltages and overcurrents in selected electrical circuits.

Design and analysis of APD photoelectric detecting circuit

NASA Astrophysics Data System (ADS)

Fang, R.; Wang, C.

2015-11-01

In LADAR system, photoelectric detecting circuit is the key part in photoelectric conversion, which determines speed of respond, sensitivity and fidelity of the system. This paper presents the design of a matched APD Photoelectric detecting circuit. The circuit accomplishes low-noise readout and high-gain amplification of the weak photoelectric signal. The main performances, especially noise and transient response of the circuit are analyzed. In order to obtain large bandwidth, decompensated operational amplifiers are applied. Circuit simulations allow the architecture validation and the global performances to be predicted. The simulation results show that the gain of the detecting circuit is 630kΩ while the bandwidth is 100MHz, and 28dB dynamic range is achieved. Furthermore, the variation of the output pulse width is less than 0.9ns.

Temperature Distribution Within a Defect-Free Silicon Carbide Diode Predicted by a Computational Model

NASA Technical Reports Server (NTRS)

Kuczmarski, Maria A.; Neudeck, Philip G.

2000-01-01

Most solid-state electronic devices diodes, transistors, and integrated circuits are based on silicon. Although this material works well for many applications, its properties limit its ability to function under extreme high-temperature or high-power operating conditions. Silicon carbide (SiC), with its desirable physical properties, could someday replace silicon for these types of applications. A major roadblock to realizing this potential is the quality of SiC material that can currently be produced. Semiconductors require very uniform, high-quality material, and commercially available SiC tends to suffer from defects in the crystalline structure that have largely been eliminated in silicon. In some power circuits, these defects can focus energy into an extremely small area, leading to overheating that can damage the device. In an effort to better understand the way that these defects affect the electrical performance and reliability of an SiC device in a power circuit, the NASA Glenn Research Center at Lewis Field began an in-house three-dimensional computational modeling effort. The goal is to predict the temperature distributions within a SiC diode structure subjected to the various transient overvoltage breakdown stresses that occur in power management circuits. A commercial computational fluid dynamics computer program (FLUENT-Fluent, Inc., Lebanon, New Hampshire) was used to build a model of a defect-free SiC diode and generate a computational mesh. A typical breakdown power density was applied over 0.5 msec in a heated layer at the junction between the p-type SiC and n-type SiC, and the temperature distribution throughout the diode was then calculated. The peak temperature extracted from the computational model agreed well (within 6 percent) with previous first-order calculations of the maximum expected temperature at the end of the breakdown pulse. This level of agreement is excellent for a model of this type and indicates that three-dimensional computational modeling can provide useful predictions for this class of problem. The model is now being extended to include the effects of crystal defects. The model will provide unique insights into how high the temperature rises in the vicinity of the defects in a diode at various power densities and pulse durations. This information also will help researchers in understanding and designing SiC devices for safe and reliable operation in high-power circuits.

Modeling and control of fuel cell based distributed generation systems

NASA Astrophysics Data System (ADS)

Jung, Jin Woo

This dissertation presents circuit models and control algorithms of fuel cell based distributed generation systems (DGS) for two DGS topologies. In the first topology, each DGS unit utilizes a battery in parallel to the fuel cell in a standalone AC power plant and a grid-interconnection. In the second topology, a Z-source converter, which employs both the L and C passive components and shoot-through zero vectors instead of the conventional DC/DC boost power converter in order to step up the DC-link voltage, is adopted for a standalone AC power supply. In Topology 1, two applications are studied: a standalone power generation (Single DGS Unit and Two DGS Units) and a grid-interconnection. First, dynamic model of the fuel cell is given based on electrochemical process. Second, two full-bridge DC to DC converters are adopted and their controllers are designed: an unidirectional full-bridge DC to DC boost converter for the fuel cell and a bidirectional full-bridge DC to DC buck/boost converter for the battery. Third, for a three-phase DC to AC inverter without or with a Delta/Y transformer, a discrete-time state space circuit model is given and two discrete-time feedback controllers are designed: voltage controller in the outer loop and current controller in the inner loop. And last, for load sharing of two DGS units and power flow control of two DGS units or the DGS connected to the grid, real and reactive power controllers are proposed. Particularly, for the grid-connected DGS application, a synchronization issue between an islanding mode and a paralleling mode to the grid is investigated, and two case studies are performed. To demonstrate the proposed circuit models and control strategies, simulation test-beds using Matlab/Simulink are constructed for each configuration of the fuel cell based DGS with a three-phase AC 120 V (L-N)/60 Hz/50 kVA and various simulation results are presented. In Topology 2, this dissertation presents system modeling, modified space vector PWM implementation (MSVPWM) and design of a closed-loop controller of the Z-source converter which utilizes L and C components and shoot-through zero vectors for the standalone AC power generation. The fuel cell system is modeled by an electrical R-C circuit in order to include slow dynamics of the fuel cells and a voltage-current characteristic of a cell is also considered. A discrete-time state space model is derived to implement digital control and a space vector pulse-width modulation (SVPWM) technique is modified to realize the shoot-through zero vectors that boost the DC-link voltage. Also, three discrete-time feedback controllers are designed: a discrete-time optimal voltage controller, a discrete-time sliding mode current controller, and a discrete-time PI DC-link voltage controller. Furthermore, an asymptotic observer is used to reduce the number of sensors and enhance the reliability of the system. To demonstrate the analyzed circuit model and proposed control strategy, various simulation results using Matlab/Simulink are presented under both light/heavy loads and linear/nonlinear loads for a three-phase AC 208 V (L-L)/60 Hz/10 kVA.

A theory of neural dimensionality, dynamics, and measurement

NASA Astrophysics Data System (ADS)

Ganguli, Surya

In many experiments, neuroscientists tightly control behavior, record many trials, and obtain trial-averaged firing rates from hundreds of neurons in circuits containing millions of behaviorally relevant neurons. Dimensionality reduction has often shown that such datasets are strikingly simple; they can be described using a much smaller number of dimensions than the number of recorded neurons, and the resulting projections onto these dimensions yield a remarkably insightful dynamical portrait of circuit computation. This ubiquitous simplicity raises several profound and timely conceptual questions. What is the origin of this simplicity and its implications for the complexity of brain dynamics? Would neuronal datasets become more complex if we recorded more neurons? How and when can we trust dynamical portraits obtained from only hundreds of neurons in circuits containing millions of neurons? We present a theory that answers these questions, and test it using neural data recorded from reaching monkeys. Overall, this theory yields a picture of the neural measurement process as a random projection of neural dynamics, conceptual insights into how we can reliably recover dynamical portraits in such under-sampled measurement regimes, and quantitative guidelines for the design of future experiments. Moreover, it reveals the existence of phase transition boundaries in our ability to successfully decode cognition and behavior as a function of the number of recorded neurons, the complexity of the task, and the smoothness of neural dynamics. membership pending.

An undergraduate course, and new textbook, on ``Physical Models of Living Systems''

NASA Astrophysics Data System (ADS)

Nelson, Philip

2015-03-01

I'll describe an intermediate-level course on ``Physical Models of Living Systems.'' The only prerequisite is first-year university physics and calculus. The course is a response to rapidly growing interest among undergraduates in several science and engineering departments. Students acquire several research skills that are often not addressed in traditional courses, including: basic modeling skills, probabilistic modeling skills, data analysis methods, computer programming using a general-purpose platform like MATLAB or Python, dynamical systems, particularly feedback control. These basic skills, which are relevant to nearly any field of science or engineering, are presented in the context of case studies from living systems, including: virus dynamics; bacterial genetics and evolution of drug resistance; statistical inference; superresolution microscopy; synthetic biology; naturally evolved cellular circuits. Publication of a new textbook by WH Freeman and Co. is scheduled for December 2014. Supported in part by EF-0928048 and DMR-0832802.

Analyzing the dynamics of brain circuits with temperature: design and implementation of a miniature thermoelectric device.

PubMed

Aronov, Dmitriy; Fee, Michale S

2011-04-15

Traditional lesion or inactivation methods are useful for determining if a given brain area is involved in the generation of a behavior, but not for determining if circuit dynamics in that area control the timing of the behavior. In contrast, localized mild cooling or heating of a brain area alters the speed of neuronal and circuit dynamics and can reveal the role of that area in the control of timing. It has been shown that miniaturized solid-state heat pumps based on the Peltier effect can be useful for analyzing brain dynamics in small freely behaving animals (Long and Fee, 2008). Here we present a theoretical analysis of these devices and a procedure for optimizing their design. We describe the construction and implementation of one device for cooling surface brain areas, such as cortex, and another device for cooling deep brain regions. We also present measurements of the magnitude and localization of the brain temperature changes produced by these two devices. Copyright © 2011 Elsevier B.V. All rights reserved.

Study of the interrelation between the electrotechnical parameters of the plasma focus discharge circuit and the plasma compression dynamics on the PF-3 and PF-1000 facilities

NASA Astrophysics Data System (ADS)

Mitrofanov, K. N.; Krauz, V. I.; Grabovski, E. V.; Myalton, V. V.; Vinogradov, V. P.; Paduch, M.; Scholz, M.; Karpiński, L.

2015-05-01

The main stages of the plasma current sheath (PCS) dynamics on two plasma focus (PF) facilities with different geometries of the electrode system, PF-3 (Filippov type) and PF-1000 (Mather type), were studied by analyzing the results of the current and voltage measurements. Some dynamic characteristics, such as the PCS velocity in the acceleration phase in the Mather-type facility (PF-1000), the moment at which the PCS reaches the anode end, and the plasma velocity in the radial stage of plasma compression in the PF-3 Filippov-type facility, were determined from the time dependence of the inductance of the discharge circuit with a dynamic plasma load. The energy characteristics of the discharge circuit of the compressing PCS were studied for different working gases (deuterium, argon, and neon) at initial pressures of 1.5-3 Torr in discharges with energies of 0.3-0.6 MJ. In experiments with deuterium, correlation between the neutron yield and the electromagnetic energy deposited directly in the compressed PCS was investigated.

Dynamic thermal characteristics of heat pipe via segmented thermal resistance model for electric vehicle battery cooling

NASA Astrophysics Data System (ADS)

Liu, Feifei; Lan, Fengchong; Chen, Jiqing

2016-07-01

Heat pipe cooling for battery thermal management systems (BTMSs) in electric vehicles (EVs) is growing due to its advantages of high cooling efficiency, compact structure and flexible geometry. Considering the transient conduction, phase change and uncertain thermal conditions in a heat pipe, it is challenging to obtain the dynamic thermal characteristics accurately in such complex heat and mass transfer process. In this paper, a ;segmented; thermal resistance model of a heat pipe is proposed based on thermal circuit method. The equivalent conductivities of different segments, viz. the evaporator and condenser of pipe, are used to determine their own thermal parameters and conditions integrated into the thermal model of battery for a complete three-dimensional (3D) computational fluid dynamics (CFD) simulation. The proposed ;segmented; model shows more precise than the ;non-segmented; model by the comparison of simulated and experimental temperature distribution and variation of an ultra-thin micro heat pipe (UMHP) battery pack, and has less calculation error to obtain dynamic thermal behavior for exact thermal design, management and control of heat pipe BTMSs. Using the ;segmented; model, the cooling effect of the UMHP pack with different natural/forced convection and arrangements is predicted, and the results correspond well to the tests.

Quantum algorithm for solving some discrete mathematical problems by probing their energy spectra

NASA Astrophysics Data System (ADS)

Wang, Hefeng; Fan, Heng; Li, Fuli

2014-01-01

When a probe qubit is coupled to a quantum register that represents a physical system, the probe qubit will exhibit a dynamical response only when it is resonant with a transition in the system. Using this principle, we propose a quantum algorithm for solving discrete mathematical problems based on the circuit model. Our algorithm has favorable scaling properties in solving some discrete mathematical problems.

Impact of time delays on oscillatory dynamics of interlinked positive and negative feedback loops

NASA Astrophysics Data System (ADS)

Huang, Bo; Tian, Xinyu; Liu, Feng; Wang, Wei

2016-11-01

Interlinking a positive feedback loop (PFL) with a negative feedback loop (NFL) constitutes a typical motif in genetic networks, performing various functions in cell signaling. How time delay in feedback regulation affects the dynamics of such systems still remains unclear. Here, we investigate three systems of interlinked PFL and NFL with time delays: a synthetic genetic oscillator, a three-node circuit, and a simplified single-node model. The stability of steady states and the routes to oscillation in the single-node model are analyzed in detail. The amplitude and period of oscillations vary with a pointwise periodicity over a range of time delay. Larger-amplitude oscillations can be induced when the PFL has an appropriately long delay, in comparison with the PFL with no delay or short delay; this conclusion holds true for all the three systems. We unravel the underlying mechanism for the above effects via analytical derivation under a limiting condition. We also develop a stochastic algorithm for simulating a single reaction with two delays and show that robust oscillations can be maintained by the PFL with a properly long delay in the single-node system. This work presents an effective method for constructing robust large-amplitude oscillators and interprets why similar circuit architectures are engaged in timekeeping systems such as circadian clocks.

Quantum mechanical settings inspired by RLC circuits

NASA Astrophysics Data System (ADS)

Alicata, G.; Bagarello, F.; Gargano, F.; Spagnolo, S.

2018-04-01

In some recent papers, several authors used electronic circuits to construct loss and gain systems. This is particularly interesting in the context of PT-quantum mechanics, where this kind of effects appears quite naturally. The electronic circuits used so far are simple, but not so much. Surprisingly enough, a rather trivial RLC circuit can be analyzed with the same perspective and it produces a variety of unexpected results, both from a mathematical and on a physical side. In this paper, we show that this circuit produces two biorthogonal bases associated with the Liouville matrix L used in the treatment of its dynamics, with a biorthogonality which is linked to the value of the parameters of the circuit. We also show that the related loss RLC circuit is naturally associated with a gain RLC circuit and that the relation between the two is rather naturally encoded in L . We propose a pseudo-fermionic analysis of the circuit, and we introduce the notion of m-equivalence between electronic circuits.

Modeling and experimental validation of a Hybridized Energy Storage System for automotive applications

NASA Astrophysics Data System (ADS)

Fiorenti, Simone; Guanetti, Jacopo; Guezennec, Yann; Onori, Simona

2013-11-01

This paper presents the development and experimental validation of a dynamic model of a Hybridized Energy Storage System (HESS) consisting of a parallel connection of a lead acid (PbA) battery and double layer capacitors (DLCs), for automotive applications. The dynamic modeling of both the PbA battery and the DLC has been tackled via the equivalent electric circuit based approach. Experimental tests are designed for identification purposes. Parameters of the PbA battery model are identified as a function of state of charge and current direction, whereas parameters of the DLC model are identified for different temperatures. A physical HESS has been assembled at the Center for Automotive Research The Ohio State University and used as a test-bench to validate the model against a typical current profile generated for Start&Stop applications. The HESS model is then integrated into a vehicle simulator to assess the effects of the battery hybridization on the vehicle fuel economy and mitigation of the battery stress.

Computational Analysis of Static and Dynamic Behaviour of Magnetic Suspensions and Magnetic Bearings

NASA Technical Reports Server (NTRS)

Britcher, Colin P. (Editor); Groom, Nelson J.

1996-01-01

Static modelling of magnetic bearings is often carried out using magnetic circuit theory. This theory cannot easily include nonlinear effects such as magnetic saturation or the fringing of flux in air-gaps. Modern computational tools are able to accurately model complex magnetic bearing geometries, provided some care is exercised. In magnetic suspension applications, the magnetic fields are highly three-dimensional and require computational tools for the solution of most problems of interest. The dynamics of a magnetic bearing or magnetic suspension system can be strongly affected by eddy currents. Eddy currents are present whenever a time-varying magnetic flux penetrates a conducting medium. The direction of flow of the eddy current is such as to reduce the rate-of-change of flux. Analytic solutions for eddy currents are available for some simplified geometries, but complex geometries must be solved by computation. It is only in recent years that such computations have been considered truly practical. At NASA Langley Research Center, state-of-the-art finite-element computer codes, 'OPERA', 'TOSCA' and 'ELEKTRA' have recently been installed and applied to the magnetostatic and eddy current problems. This paper reviews results of theoretical analyses which suggest general forms of mathematical models for eddy currents, together with computational results. A simplified circuit-based eddy current model proposed appears to predict the observed trends in the case of large eddy current circuits in conducting non-magnetic material. A much more difficult case is seen to be that of eddy currents in magnetic material, or in non-magnetic material at higher frequencies, due to the lower skin depths. Even here, the dissipative behavior has been shown to yield at least somewhat to linear modelling. Magnetostatic and eddy current computations have been carried out relating to the Annular Suspension and Pointing System, a prototype for a space payload pointing and vibration isolation system, where the magnetic actuator geometry resembles a conventional magnetic bearing. Magnetostatic computations provide estimates of flux density within airgaps and the iron core material, fringing at the pole faces and the net force generated. Eddy current computations provide coil inductance, power dissipation and the phase lag in the magnetic field, all as functions of excitation frequency. Here, the dynamics of the magnetic bearings, notably the rise time of forces with changing currents, are found to be very strongly affected by eddy currents, even at quite low frequencies. Results are also compared to experimental measurements of the performance of a large-gap magnetic suspension system, the Large Angle Magnetic Suspension Test Fixture (LAMSTF). Eddy current effects are again shown to significantly affect the dynamics of the system. Some consideration is given to the ease and accuracy of computation, specifically relating to OPERA/TOSCA/ELEKTRA.

A Novel Offset Cancellation Based on Parasitic-Insensitive Switched-Capacitor Sensing Circuit for the Out-of-Plane Single-Gimbaled Decoupled CMOS-MEMS Gyroscope

PubMed Central

Chang, Ming-Hui; Huang, Han-Pang

2013-01-01

This paper presents a novel parasitic-insensitive switched-capacitor (PISC) sensing circuit design in order to obtain high sensitivity and ultra linearity and reduce the parasitic effect for the out-of-plane single-gimbaled decoupled CMOS-MEMS gyroscope (SGDG). According to the simulation results, the proposed PISC circuit has better sensitivity and high linearity in a wide dynamic range. Experimental results also show a better performance. In addition, the PISC circuit can use signal processing to cancel the offset and noise. Thus, this circuit is very suitable for gyroscope measurement. PMID:23493122

Modeling eye-head gaze shifts in multiple contexts without motor planning

PubMed Central

Haji-Abolhassani, Iman; Guitton, Daniel

2016-01-01

During gaze shifts, the eyes and head collaborate to rapidly capture a target (saccade) and fixate it. Accordingly, models of gaze shift control should embed both saccadic and fixation modes and a mechanism for switching between them. We demonstrate a model in which the eye and head platforms are driven by a shared gaze error signal. To limit the number of free parameters, we implement a model reduction approach in which steady-state cerebellar effects at each of their projection sites are lumped with the parameter of that site. The model topology is consistent with anatomy and neurophysiology, and can replicate eye-head responses observed in multiple experimental contexts: 1) observed gaze characteristics across species and subjects can emerge from this structure with minor parametric changes; 2) gaze can move to a goal while in the fixation mode; 3) ocular compensation for head perturbations during saccades could rely on vestibular-only cells in the vestibular nuclei with postulated projections to burst neurons; 4) two nonlinearities suffice, i.e., the experimentally-determined mapping of tectoreticular cells onto brain stem targets and the increased recruitment of the head for larger target eccentricities; 5) the effects of initial conditions on eye/head trajectories are due to neural circuit dynamics, not planning; and 6) “compensatory” ocular slow phases exist even after semicircular canal plugging, because of interconnections linking eye-head circuits. Our model structure also simulates classical vestibulo-ocular reflex and pursuit nystagmus, and provides novel neural circuit and behavioral predictions, notably that both eye-head coordination and segmental limb coordination are possible without trajectory planning. PMID:27440248

Cell-to-Cell Communication Circuits: Quantitative Analysis of Synthetic Logic Gates

PubMed Central

Hoffman-Sommer, Marta; Supady, Adriana; Klipp, Edda

2012-01-01

One of the goals in the field of synthetic biology is the construction of cellular computation devices that could function in a manner similar to electronic circuits. To this end, attempts are made to create biological systems that function as logic gates. In this work we present a theoretical quantitative analysis of a synthetic cellular logic-gates system, which has been implemented in cells of the yeast Saccharomyces cerevisiae (Regot et al., 2011). It exploits endogenous MAP kinase signaling pathways. The novelty of the system lies in the compartmentalization of the circuit where all basic logic gates are implemented in independent single cells that can then be cultured together to perform complex logic functions. We have constructed kinetic models of the multicellular IDENTITY, NOT, OR, and IMPLIES logic gates, using both deterministic and stochastic frameworks. All necessary model parameters are taken from literature or estimated based on published kinetic data, in such a way that the resulting models correctly capture important dynamic features of the included mitogen-activated protein kinase pathways. We analyze the models in terms of parameter sensitivity and we discuss possible ways of optimizing the system, e.g., by tuning the culture density. We apply a stochastic modeling approach, which simulates the behavior of whole populations of cells and allows us to investigate the noise generated in the system; we find that the gene expression units are the major sources of noise. Finally, the model is used for the design of system modifications: we show how the current system could be transformed to operate on three discrete values. PMID:22934039

The persistent current and energy spectrum on a driven mesoscopic LC-circuit with Josephson junction

NASA Astrophysics Data System (ADS)

Pahlavanias, Hassan

2018-03-01

The quantum theory for a mesoscopic electric circuit including a Josephson junction with charge discreteness is studied. By considering coupling energy of the mesoscopic capacitor in Josephson junction device, a Hamiltonian describing the dynamics of a quantum mesoscopic electric LC-circuit with charge discreteness is introduced. We first calculate the persistent current on a quantum driven ring including Josephson junction. Then we obtain the persistent current and energy spectrum of a quantum mesoscopic electrical circuit which includes capacitor, inductor, time-dependent external source and Josephson junction.

Gallium Arsenide Domino Circuit

NASA Technical Reports Server (NTRS)

Yang, Long; Long, Stephen I.

1990-01-01

Advantages include reduced power and high speed. Experimental gallium arsenide field-effect-transistor (FET) domino circuit replicated in large numbers for use in dynamic-logic systems. Name of circuit denotes mode of operation, which logic signals propagate from each stage to next when successive stages operated at slightly staggered clock cycles, in manner reminiscent of dominoes falling in a row. Building block of domino circuit includes input, inverter, and level-shifting substages. Combinational logic executed in input substage. During low half of clock cycle, result of logic operation transmitted to following stage.

ASDTIC control and standardized interface circuits applied to buck, parallel and buck-boost dc to dc power converters

NASA Technical Reports Server (NTRS)

Schoenfeld, A. D.; Yu, Y.

1973-01-01

Versatile standardized pulse modulation nondissipatively regulated control signal processing circuits were applied to three most commonly used dc to dc power converter configurations: (1) the series switching buck-regulator, (2) the pulse modulated parallel inverter, and (3) the buck-boost converter. The unique control concept and the commonality of control functions for all switching regulators have resulted in improved static and dynamic performance and control circuit standardization. New power-circuit technology was also applied to enhance reliability and to achieve optimum weight and efficiency.

Robust optimization with transiently chaotic dynamical systems

NASA Astrophysics Data System (ADS)

Sumi, R.; Molnár, B.; Ercsey-Ravasz, M.

2014-05-01

Efficiently solving hard optimization problems has been a strong motivation for progress in analog computing. In a recent study we presented a continuous-time dynamical system for solving the NP-complete Boolean satisfiability (SAT) problem, with a one-to-one correspondence between its stable attractors and the SAT solutions. While physical implementations could offer great efficiency, the transiently chaotic dynamics raises the question of operability in the presence of noise, unavoidable on analog devices. Here we show that the probability of finding solutions is robust to noise intensities well above those present on real hardware. We also developed a cellular neural network model realizable with analog circuits, which tolerates even larger noise intensities. These methods represent an opportunity for robust and efficient physical implementations.

Onboard calibration circuit for the DAMPE BGO calorimeter front-end electronics

NASA Astrophysics Data System (ADS)

Zhang, De-Liang; Feng, Chang-Qing; Zhang, Jun-Bin; Wang, Qi; Ma, Si-Yuan; Shen, Zhong-Tao; Jiang, Di; Gao, Shan-Shan; Zhang, Yun-Long; Guo, Jian-Hua; Liu, Shu-Bin; An, Qi

2016-05-01

DAMPE (DArk Matter Particle Explorer) is a scientific satellite which is mainly aimed at indirectly searching for dark matter in space. One critical sub-detector of the DAMPE payload is the BGO (bismuth germanium oxide) calorimeter, which contains 1848 PMT (photomultiplier tube) dynodes and 16 FEE (Front-End Electronics) boards. VA160 and VATA160, two 32-channel low power ASICs (Application Specific Integrated Circuits), are adopted as the key components on the FEEs to perform charge measurement for the PMT signals. In order to monitor the parameter drift which may be caused by temperature variation, aging, or other environmental factors, an onboard calibration circuit is designed for the VA160 and VATA160 ASICs. It is mainly composed of a 12-bit DAC (Digital to Analog Converter), an operational amplifier and an analog switch. Test results showed that a dynamic range of 0-30 pC with a precision of 5 fC (Root Meam Square, RMS) was achieved, which covers the VA160’s input range. It can be used to compensate for the temperature drift and test the trigger function of the FEEs. The calibration circuit has been implemented for the front-end electronics of the BGO Calorimeter and verified by all the environmental tests for both Qualification Model and Flight Model of DAMPE. The DAMPE satellite was launched at the end of 2015 and the calibration circuit will operate periodically in space. Supported by Strategic Priority Research Program on Space Science of Chinese Academy of Sciences (XDA04040202-4), and National Basic Research Program (973 Program) of China (2010CB833002) and National Natural Science Foundation of China (11273070)

Predictive representations can link model-based reinforcement learning to model-free mechanisms.

PubMed

Russek, Evan M; Momennejad, Ida; Botvinick, Matthew M; Gershman, Samuel J; Daw, Nathaniel D

2017-09-01

Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation.

Predictive representations can link model-based reinforcement learning to model-free mechanisms

PubMed Central

Botvinick, Matthew M.

2017-01-01

Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation. PMID:28945743

Seeing the whole picture: A comprehensive imaging approach to functional mapping of circuits in behaving zebrafish.

PubMed

Feierstein, C E; Portugues, R; Orger, M B

2015-06-18

In recent years, the zebrafish has emerged as an appealing model system to tackle questions relating to the neural circuit basis of behavior. This can be attributed not just to the growing use of genetically tractable model organisms, but also in large part to the rapid advances in optical techniques for neuroscience, which are ideally suited for application to the small, transparent brain of the larval fish. Many characteristic features of vertebrate brains, from gross anatomy down to particular circuit motifs and cell-types, as well as conserved behaviors, can be found in zebrafish even just a few days post fertilization, and, at this early stage, the physical size of the brain makes it possible to analyze neural activity in a comprehensive fashion. In a recent study, we used a systematic and unbiased imaging method to record the pattern of activity dynamics throughout the whole brain of larval zebrafish during a simple visual behavior, the optokinetic response (OKR). This approach revealed the broadly distributed network of neurons that were active during the behavior and provided insights into the fine-scale functional architecture in the brain, inter-individual variability, and the spatial distribution of behaviorally relevant signals. Combined with mapping anatomical and functional connectivity, targeted electrophysiological recordings, and genetic labeling of specific populations, this comprehensive approach in zebrafish provides an unparalleled opportunity to study complete circuits in a behaving vertebrate animal. Copyright © 2014. Published by Elsevier Ltd.

A Tribute to J. C. Sprott

NASA Astrophysics Data System (ADS)

Nazarimehr, Fahimeh; Jafari, Sajad; Chen, Guanrong; Kapitaniak, Tomasz; Kuznetsov, Nikolay V.; Leonov, Gennady A.; Li, Chunbiao; Wei, Zhouchao

2017-12-01

In honor of his 75th birthday, we review the prominent works of Professor Julien Clinton Sprott in chaos and nonlinear dynamics. We categorize his works into three important groups. The first and most important group is identifying new dynamical systems with special properties. He has proposed different chaotic maps, flows, complex variable systems, nonautonomous systems, partial differential equations, fractional-order systems, delay differential systems, spatiotemporal systems, artificial neural networks, and chaotic electrical circuits. He has also studied dynamical properties of complex systems such as bifurcations and basins of attraction. He has done work on generating fractal art. He has examined models of real-world systems that exhibit chaos. The second group of his works comprise control and synchronization of chaos. Finally, the third group is extracting dynamical properties of systems using time-series analysis. This paper highlights the impact of Sprott’s work on the promotion of nonlinear dynamics.

Experimental study of firing death in a network of chaotic FitzHugh-Nagumo neurons

NASA Astrophysics Data System (ADS)

Ciszak, Marzena; Euzzor, Stefano; Arecchi, F. Tito; Meucci, Riccardo

2013-02-01

The FitzHugh-Nagumo neurons driven by a periodic forcing undergo a period-doubling route to chaos and a transition to mixed-mode oscillations. When coupled, their dynamics tend to be synchronized. We show that the chaotically spiking neurons change their internal dynamics to subthreshold oscillations, the phenomenon referred to as firing death. These dynamical changes are observed below the critical coupling strength at which the transition to full chaotic synchronization occurs. Moreover, we find various dynamical regimes in the subthreshold oscillations, namely, regular, quasiperiodic, and chaotic states. We show numerically that these dynamical states may coexist with large-amplitude spiking regimes and that this coexistence is characterized by riddled basins of attraction. The reported results are obtained for neurons implemented in the electronic circuits as well as for the model equations. Finally, we comment on the possible scenarios where the coupling-induced firing death could play an important role in biological systems.

A thorough investigation of the progressive reset dynamics in HfO{sub 2}-based resistive switching structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lorenzi, P., E-mail: lorenzi@die.uniroma1.it; Rao, R.; Irrera, F.

2015-09-14

According to previous reports, filamentary electron transport in resistive switching HfO{sub 2}-based metal-insulator-metal structures can be modeled using a diode-like conduction mechanism with a series resistance. Taking the appropriate limits, the model allows simulating the high (HRS) and low (LRS) resistance states of the devices in terms of exponential and linear current-voltage relationships, respectively. In this letter, we show that this simple equivalent circuit approach can be extended to represent the progressive reset transition between the LRS and HRS if a generalized logistic growth model for the pre-exponential diode current factor is considered. In this regard, it is demonstrated heremore » that a Verhulst logistic model does not provide accurate results. The reset dynamics is interpreted as the sequential deactivation of multiple conduction channels spanning the dielectric film. Fitting results for the current-voltage characteristics indicate that the voltage sweep rate only affects the deactivation rate of the filaments without altering the main features of the switching dynamics.« less

Superconducting Microwave Multivibrator Produced by Coherent Feedback

NASA Astrophysics Data System (ADS)

Kerckhoff, Joseph; Lehnert, K. W.

2012-10-01

We investigate a nonlinear coherent feedback circuit constructed from preexisting superconducting microwave devices. The network exhibits emergent bistable and astable states, and we demonstrate its operation as a latch and the frequency locking of its oscillations. While the network is tedious to model by hand, our observations agree quite well with the semiclassical dynamical model produced by a new software package (N. Tezak , arXiv:1111.3081v1 [Phil. Trans. R. Soc. A (to be published)]) that systematically interpreted an idealized schematic of the system as a quantum optic feedback network.

A reassessment study of multi-material-shell gas puff z-pinches as a pulsed neutron source on the sandia ZR

NASA Astrophysics Data System (ADS)

Chong, Y. K.; Velikovich, A. L.; Thornhil, J. W.; Giuliani, J. L.; Knapp, P.; Jennings, C.

2013-10-01

Over the last few years, numerous 1D and 2D MHD simulation studies of deuterium (D) based double-shell gas-puff Z-pinch implosions driven by the Sandia ZR accelerator have been carried out to assess the Z-pinch as a pulsed thermal fusion neutron source. In these studies, an ad-hoc time-dependent shunt impedance model was used within the external driving circuit model in order to account for the unresolved current loss in the MITL and the load. In this study, we incorporate an improved ZR circuit model recently formulated based on the recent Sandia argon gas-puff experiment circuit data into the multi-material version of the Mach +DDTCRE RMHD code. We reinvestigate the effects of multidimensional structure and nonuniform gradients as well as the outer- and inner-shell material interaction on the implosion physics and dynamics of both D-on-D and argon-on-D Z-pinch loads using the model. Then, we characterize the neutron production performance of the Z-pinch loads as a function of total mass, mass ratio and/or radius toward their optimization as a pulsed thernonuclear neutron source. Work supported by DOE/NNSA. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. DOE's NNSA under contract DE-AC04-94AL85000.

The relative phases of basal ganglia activities dynamically shape effective connectivity in Parkinson's disease.

PubMed

Cagnan, Hayriye; Duff, Eugene Paul; Brown, Peter

2015-06-01

Optimal phase alignment between oscillatory neural circuits is hypothesized to optimize information flow and enhance system performance. This theory is known as communication-through-coherence. The basal ganglia motor circuit exhibits exaggerated oscillatory and coherent activity patterns in Parkinson's disease. Such activity patterns are linked to compromised motor system performance as evinced by bradykinesia, rigidity and tremor, suggesting that network function might actually deteriorate once a certain level of net synchrony is exceeded in the motor circuit. Here, we characterize the processes underscoring excessive synchronization and its termination. To this end, we analysed local field potential recordings from the subthalamic nucleus and globus pallidus of five patients with Parkinson's disease (four male and one female, aged 37-64 years). We observed that certain phase alignments between subthalamic nucleus and globus pallidus amplified local neural synchrony in the beta frequency band while others either suppressed it or did not induce any significant change with respect to surrogates. The increase in local beta synchrony directly correlated with how long the two nuclei locked to beta-amplifying phase alignments. Crucially, administration of the dopamine prodrug, levodopa, reduced the frequency and duration of periods during which subthalamic and pallidal populations were phase-locked to beta-amplifying alignments. Conversely ON dopamine, the total duration over which subthalamic and pallidal populations were aligned to phases that left beta-amplitude unchanged with respect to surrogates increased. Thus dopaminergic input shifted circuit dynamics from persistent periods of locking to amplifying phase alignments, associated with compromised motoric function, to more dynamic phase alignment and improved motoric function. This effect of dopamine on local circuit resonance suggests means by which novel electrical interventions might prevent resonance-related pathological circuit interactions. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain.

A novel prediction method about single components of analog circuits based on complex field modeling.

PubMed

Zhou, Jingyu; Tian, Shulin; Yang, Chenglin

2014-01-01

Few researches pay attention to prediction about analog circuits. The few methods lack the correlation with circuit analysis during extracting and calculating features so that FI (fault indicator) calculation often lack rationality, thus affecting prognostic performance. To solve the above problem, this paper proposes a novel prediction method about single components of analog circuits based on complex field modeling. Aiming at the feature that faults of single components hold the largest number in analog circuits, the method starts with circuit structure, analyzes transfer function of circuits, and implements complex field modeling. Then, by an established parameter scanning model related to complex field, it analyzes the relationship between parameter variation and degeneration of single components in the model in order to obtain a more reasonable FI feature set via calculation. According to the obtained FI feature set, it establishes a novel model about degeneration trend of analog circuits' single components. At last, it uses particle filter (PF) to update parameters for the model and predicts remaining useful performance (RUP) of analog circuits' single components. Since calculation about the FI feature set is more reasonable, accuracy of prediction is improved to some extent. Finally, the foregoing conclusions are verified by experiments.

High dynamic range infrared radiometry and imaging

NASA Technical Reports Server (NTRS)

Coon, Darryl D.; Karunasiri, R. P. G.; Bandara, K. M. S. V.

1988-01-01

The use is described of cryogenically cooled, extrinsic silicon infrared detectors in an unconventional mode of operation which offers an unusually large dynamic range. The system performs intensity-to-frequency conversion at the focal plane via simple circuits with very low power consumption. The incident IR intensity controls the repetition rate of short duration output pulses over a pulse rate dynamic range of about 10(6). Theory indicates the possibility of monotonic and approx. linear response over the full dynamic range. A comparison between the theoretical and the experimental results shows that the model provides a reasonably good description of experimental data. Some measurements of survivability with a very intense IR source were made on these devices and found to be very encouraging. Evidence continues to indicate that some variations in interpulse time intervals are deterministic rather than probabilistic.

Hebbian Wiring Plasticity Generates Efficient Network Structures for Robust Inference with Synaptic Weight Plasticity

PubMed Central

Hiratani, Naoki; Fukai, Tomoki

2016-01-01

In the adult mammalian cortex, a small fraction of spines are created and eliminated every day, and the resultant synaptic connection structure is highly nonrandom, even in local circuits. However, it remains unknown whether a particular synaptic connection structure is functionally advantageous in local circuits, and why creation and elimination of synaptic connections is necessary in addition to rich synaptic weight plasticity. To answer these questions, we studied an inference task model through theoretical and numerical analyses. We demonstrate that a robustly beneficial network structure naturally emerges by combining Hebbian-type synaptic weight plasticity and wiring plasticity. Especially in a sparsely connected network, wiring plasticity achieves reliable computation by enabling efficient information transmission. Furthermore, the proposed rule reproduces experimental observed correlation between spine dynamics and task performance. PMID:27303271

Programmable genetic circuits for pathway engineering.

PubMed

Hoynes-O'Connor, Allison; Moon, Tae Seok

2015-12-01

Synthetic biology has the potential to provide decisive advances in genetic control of metabolic pathways. However, there are several challenges that synthetic biologists must overcome before this vision becomes a reality. First, a library of diverse and well-characterized sensors, such as metabolite-sensing or condition-sensing promoters, must be constructed. Second, robust programmable circuits that link input conditions with a specific gene regulation response must be developed. Finally, multi-gene targeting strategies must be integrated with metabolically relevant sensors and complex, robust logic. Achievements in each of these areas, which employ the CRISPR/Cas system, in silico modeling, and dynamic sensor-regulators, among other tools, provide a strong basis for future research. Overall, the future for synthetic biology approaches in metabolic engineering holds immense promise. Copyright © 2015 Elsevier Ltd. All rights reserved.

Development of a two-dimensional skin friction balance nulling circuit using multivariable control theory

NASA Technical Reports Server (NTRS)

Tripp, John S.; Patek, Stephen D.

1988-01-01

Measurement of planar skin friction forces in aerodynamic testing currently requires installation of two perpendicularly mounted, single-axis balances; consequently, force components must be sensed at two distinct locations. A two-axis instrument developed at the Langley Research Center to overcome this disadvantage allows measurement of a two-dimensional force at one location. This paper describes a feedback-controlled nulling circuit developed for the NASA two-axis balance which, without external compensation, is inherently unstable because of its low friction mechanical design. Linear multivariable control theory is applied to an experimentally validated mathematical model of the balance to synthesize a state-variable feedback control law. Pole placement techniques and computer simulation studies are employed to select eigenvalues which provide ideal transient response with decoupled sensing dynamics.

Separating OR, SUM, and XOR Circuits.

PubMed

Find, Magnus; Göös, Mika; Järvisalo, Matti; Kaski, Petteri; Koivisto, Mikko; Korhonen, Janne H

2016-08-01

Given a boolean n × n matrix A we consider arithmetic circuits for computing the transformation x ↦ Ax over different semirings. Namely, we study three circuit models: monotone OR-circuits, monotone SUM-circuits (addition of non-negative integers), and non-monotone XOR-circuits (addition modulo 2). Our focus is on separating OR-circuits from the two other models in terms of circuit complexity: We show how to obtain matrices that admit OR-circuits of size O ( n ), but require SUM-circuits of size Ω( n 3/2 /log 2 n ).We consider the task of rewriting a given OR-circuit as a XOR-circuit and prove that any subquadratic-time algorithm for this task violates the strong exponential time hypothesis.

Circuit Motifs for Contrast-Adaptive Differentiation in Early Sensory Systems: The Role of Presynaptic Inhibition and Short-Term Plasticity

PubMed Central

Zhang, Danke; Wu, Si; Rasch, Malte J.

2015-01-01

In natural signals, such as the luminance value across of a visual scene, abrupt changes in intensity value are often more relevant to an organism than intensity values at other positions and times. Thus to reduce redundancy, sensory systems are specialized to detect the times and amplitudes of informative abrupt changes in the input stream rather than coding the intensity values at all times. In theory, a system that responds transiently to fast changes is called a differentiator. In principle, several different neural circuit mechanisms exist that are capable of responding transiently to abrupt input changes. However, it is unclear which circuit would be best suited for early sensory systems, where the dynamic range of the natural input signals can be very wide. We here compare the properties of different simple neural circuit motifs for implementing signal differentiation. We found that a circuit motif based on presynaptic inhibition (PI) is unique in a sense that the vesicle resources in the presynaptic site can be stably maintained over a wide range of stimulus intensities, making PI a biophysically plausible mechanism to implement a differentiator with a very wide dynamical range. Moreover, by additionally considering short-term plasticity (STP), differentiation becomes contrast adaptive in the PI-circuit but not in other potential neural circuit motifs. Numerical simulations show that the behavior of the adaptive PI-circuit is consistent with experimental observations suggesting that adaptive presynaptic inhibition might be a good candidate neural mechanism to achieve differentiation in early sensory systems. PMID:25723493

Circuit motifs for contrast-adaptive differentiation in early sensory systems: the role of presynaptic inhibition and short-term plasticity.

PubMed

Zhang, Danke; Wu, Si; Rasch, Malte J

2015-01-01

In natural signals, such as the luminance value across of a visual scene, abrupt changes in intensity value are often more relevant to an organism than intensity values at other positions and times. Thus to reduce redundancy, sensory systems are specialized to detect the times and amplitudes of informative abrupt changes in the input stream rather than coding the intensity values at all times. In theory, a system that responds transiently to fast changes is called a differentiator. In principle, several different neural circuit mechanisms exist that are capable of responding transiently to abrupt input changes. However, it is unclear which circuit would be best suited for early sensory systems, where the dynamic range of the natural input signals can be very wide. We here compare the properties of different simple neural circuit motifs for implementing signal differentiation. We found that a circuit motif based on presynaptic inhibition (PI) is unique in a sense that the vesicle resources in the presynaptic site can be stably maintained over a wide range of stimulus intensities, making PI a biophysically plausible mechanism to implement a differentiator with a very wide dynamical range. Moreover, by additionally considering short-term plasticity (STP), differentiation becomes contrast adaptive in the PI-circuit but not in other potential neural circuit motifs. Numerical simulations show that the behavior of the adaptive PI-circuit is consistent with experimental observations suggesting that adaptive presynaptic inhibition might be a good candidate neural mechanism to achieve differentiation in early sensory systems.

Quantum circuit dynamics via path integrals: Is there a classical action for discrete-time paths?

NASA Astrophysics Data System (ADS)

Penney, Mark D.; Enshan Koh, Dax; Spekkens, Robert W.

2017-07-01

It is straightforward to compute the transition amplitudes of a quantum circuit using the sum-over-paths methodology when the gates in the circuit are balanced, where a balanced gate is one for which all non-zero transition amplitudes are of equal magnitude. Here we consider the question of whether, for such circuits, the relative phases of different discrete-time paths through the configuration space can be defined in terms of a classical action, as they are for continuous-time paths. We show how to do so for certain kinds of quantum circuits, namely, Clifford circuits where the elementary systems are continuous-variable systems or discrete systems of odd-prime dimension. These types of circuit are distinguished by having phase-space representations that serve to define their classical counterparts. For discrete systems, the phase-space coordinates are also discrete variables. We show that for each gate in the generating set, one can associate a symplectomorphism on the phase-space and to each of these one can associate a generating function, defined on two copies of the configuration space. For discrete systems, the latter association is achieved using tools from algebraic geometry. Finally, we show that if the action functional for a discrete-time path through a sequence of gates is defined using the sum of the corresponding generating functions, then it yields the correct relative phases for the path-sum expression. These results are likely to be relevant for quantizing physical theories where time is fundamentally discrete, characterizing the classical limit of discrete-time quantum dynamics, and proving complexity results for quantum circuits.

Dynamics of Gut-Brain Communication Underlying Hunger.

PubMed

Beutler, Lisa R; Chen, Yiming; Ahn, Jamie S; Lin, Yen-Chu; Essner, Rachel A; Knight, Zachary A

2017-10-11

Communication between the gut and brain is critical for homeostasis, but how this communication is represented in the dynamics of feeding circuits is unknown. Here we describe nutritional regulation of key neurons that control hunger in vivo. We show that intragastric nutrient infusion rapidly and durably inhibits hunger-promoting AgRP neurons in awake, behaving mice. This inhibition is proportional to the number of calories infused but surprisingly independent of macronutrient identity or nutritional state. We show that three gastrointestinal signals-serotonin, CCK, and PYY-are necessary or sufficient for these effects. In contrast, the hormone leptin has no acute effect on dynamics of these circuits or their sensory regulation but instead induces a slow modulation that develops over hours and is required for inhibition of feeding. These findings reveal how layers of visceral signals operating on distinct timescales converge on hypothalamic feeding circuits to generate a central representation of energy balance. Copyright © 2017 Elsevier Inc. All rights reserved.

Propagating gene expression fronts in a one-dimensional coupled system of artificial cells

NASA Astrophysics Data System (ADS)

Tayar, Alexandra M.; Karzbrun, Eyal; Noireaux, Vincent; Bar-Ziv, Roy H.

2015-12-01

Living systems employ front propagation and spatiotemporal patterns encoded in biochemical reactions for communication, self-organization and computation. Emulating such dynamics in minimal systems is important for understanding physical principles in living cells and in vitro. Here, we report a one-dimensional array of DNA compartments in a silicon chip as a coupled system of artificial cells, offering the means to implement reaction-diffusion dynamics by integrated genetic circuits and chip geometry. Using a bistable circuit we programmed a front of protein synthesis propagating in the array as a cascade of signal amplification and short-range diffusion. The front velocity is maximal at a saddle-node bifurcation from a bistable regime with travelling fronts to a monostable regime that is spatially homogeneous. Near the bifurcation the system exhibits large variability between compartments, providing a possible mechanism for population diversity. This demonstrates that on-chip integrated gene circuits are dynamical systems driving spatiotemporal patterns, cellular variability and symmetry breaking.

Trading Speed and Accuracy by Coding Time: A Coupled-circuit Cortical Model

PubMed Central

Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C.

2013-01-01

Our actions take place in space and time, but despite the role of time in decision theory and the growing acknowledgement that the encoding of time is crucial to behaviour, few studies have considered the interactions between neural codes for objects in space and for elapsed time during perceptual decisions. The speed-accuracy trade-off (SAT) provides a window into spatiotemporal interactions. Our hypothesis is that temporal coding determines the rate at which spatial evidence is integrated, controlling the SAT by gain modulation. Here, we propose that local cortical circuits are inherently suited to the relevant spatial and temporal coding. In simulations of an interval estimation task, we use a generic local-circuit model to encode time by ‘climbing’ activity, seen in cortex during tasks with a timing requirement. The model is a network of simulated pyramidal cells and inhibitory interneurons, connected by conductance synapses. A simple learning rule enables the network to quickly produce new interval estimates, which show signature characteristics of estimates by experimental subjects. Analysis of network dynamics formally characterizes this generic, local-circuit timing mechanism. In simulations of a perceptual decision task, we couple two such networks. Network function is determined only by spatial selectivity and NMDA receptor conductance strength; all other parameters are identical. To trade speed and accuracy, the timing network simply learns longer or shorter intervals, driving the rate of downstream decision processing by spatially non-selective input, an established form of gain modulation. Like the timing network's interval estimates, decision times show signature characteristics of those by experimental subjects. Overall, we propose, demonstrate and analyse a generic mechanism for timing, a generic mechanism for modulation of decision processing by temporal codes, and we make predictions for experimental verification. PMID:23592967

Temporal Information of Directed Causal Connectivity in Multi-Trial ERP Data using Partial Granger Causality.

PubMed

Youssofzadeh, Vahab; Prasad, Girijesh; Naeem, Muhammad; Wong-Lin, KongFatt

2016-01-01

Partial Granger causality (PGC) has been applied to analyse causal functional neural connectivity after effectively mitigating confounding influences caused by endogenous latent variables and exogenous environmental inputs. However, it is not known how this connectivity obtained from PGC evolves over time. Furthermore, PGC has yet to be tested on realistic nonlinear neural circuit models and multi-trial event-related potentials (ERPs) data. In this work, we first applied a time-domain PGC technique to evaluate simulated neural circuit models, and demonstrated that the PGC measure is more accurate and robust in detecting connectivity patterns as compared to conditional Granger causality and partial directed coherence, especially when the circuit is intrinsically nonlinear. Moreover, the connectivity in PGC settles faster into a stable and correct configuration over time. After method verification, we applied PGC to reveal the causal connections of ERP trials of a mismatch negativity auditory oddball paradigm. The PGC analysis revealed a significant bilateral but asymmetrical localised activity in the temporal lobe close to the auditory cortex, and causal influences in the frontal, parietal and cingulate cortical areas, consistent with previous studies. Interestingly, the time to reach a stable connectivity configuration (~250–300 ms) coincides with the deviation of ensemble ERPs of oddball from standard tones. Finally, using a sliding time window, we showed higher resolution dynamics of causal connectivity within an ERP trial. In summary, time-domain PGC is promising in deciphering directed functional connectivity in nonlinear and ERP trials accurately, and at a sufficiently early stage. This data-driven approach can reduce computational time, and determine the key architecture for neural circuit modeling.

Measurement of the dynamic input impedance of a dc superconducting quantum interference device at audio frequencies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Falferi, P.; Mezzena, R.; Vitale, S.

1997-08-01

The coupling effects of a commercial dc superconducting quantum interference device (SQUID) to an electrical LC resonator which operates at audio frequencies ({approx}1kHz) with quality factors Q{approx}10{sup 6} are presented. The variations of the resonance frequency of the resonator as functions of the flux applied to the SQUID are due to the SQUID dynamic inductance in good agreement with the predictions of a model. The variations of the quality factor point to a feedback mechanism between the output of the SQUID and the input circuit. {copyright} {ital 1997 American Institute of Physics.}

Transgenic FingRs for Live Mapping of Synaptic Dynamics in Genetically-Defined Neurons

PubMed Central

Son, Jong-Hyun; Keefe, Matthew D.; Stevenson, Tamara J.; Barrios, Joshua P.; Anjewierden, Scott; Newton, James B.; Douglass, Adam D.; Bonkowsky, Joshua L.

2016-01-01

Tools for genetically-determined visualization of synaptic circuits and interactions are necessary to build connectomics of the vertebrate brain and to screen synaptic properties in neurological disease models. Here we develop a transgenic FingR (fibronectin intrabodies generated by mRNA display) technology for monitoring synapses in live zebrafish. We demonstrate FingR labeling of defined excitatory and inhibitory synapses, and show FingR applicability for dissecting synapse dynamics in normal and disease states. Using our system we show that chronic hypoxia, associated with neurological defects in preterm birth, affects dopaminergic neuron synapse number depending on the developmental timing of hypoxia. PMID:26728131

Tomonaga–Luttinger physics in electronic quantum circuits

PubMed Central

Jezouin, S.; Albert, M.; Parmentier, F. D.; Anthore, A.; Gennser, U.; Cavanna, A.; Safi, I.; Pierre, F.

2013-01-01

In one-dimensional conductors, interactions result in correlated electronic systems. At low energy, a hallmark signature of the so-called Tomonaga–Luttinger liquids is the universal conductance curve predicted in presence of an impurity. A seemingly different topic is the quantum laws of electricity, when distinct quantum conductors are assembled in a circuit. In particular, the conductances are suppressed at low energy, a phenomenon called dynamical Coulomb blockade. Here we investigate the conductance of mesoscopic circuits constituted by a short single-channel quantum conductor in series with a resistance, and demonstrate a proposed link to Tomonaga–Luttinger physics. We reformulate and establish experimentally a recently derived phenomenological expression for the conductance using a wide range of circuits, including carbon nanotube data obtained elsewhere. By confronting both conductance data and phenomenological expression with the universal Tomonaga–Luttinger conductance curve, we demonstrate experimentally the predicted mapping between dynamical Coulomb blockade and the transport across a Tomonaga–Luttinger liquid with an impurity. PMID:23653214

Carbon Nanotube Driver Circuit for 6 × 6 Organic Light Emitting Diode Display

PubMed Central

Zou, Jianping; Zhang, Kang; Li, Jingqi; Zhao, Yongbiao; Wang, Yilei; Pillai, Suresh Kumar Raman; Volkan Demir, Hilmi; Sun, Xiaowei; Chan-Park, Mary B.; Zhang, Qing

2015-01-01

Single-walled carbon nanotube (SWNT) is expected to be a very promising material for flexible and transparent driver circuits for active matrix organic light emitting diode (AM OLED) displays due to its high field-effect mobility, excellent current carrying capacity, optical transparency and mechanical flexibility. Although there have been several publications about SWNT driver circuits, none of them have shown static and dynamic images with the AM OLED displays. Here we report on the first successful chemical vapor deposition (CVD)-grown SWNT network thin film transistor (TFT) driver circuits for static and dynamic AM OLED displays with 6 × 6 pixels. The high device mobility of ~45 cm2V−1s−1 and the high channel current on/off ratio of ~105 of the SWNT-TFTs fully guarantee the control capability to the OLED pixels. Our results suggest that SWNT-TFTs are promising backplane building blocks for future OLED displays. PMID:26119218

Low-current traveling wave tube for use in the microwave power module

NASA Technical Reports Server (NTRS)

Palmer, Raymond W.; Ramins, Peter; Force, Dale A.; Dayton, James A.; Ebihara, Ben T.; Gruber, Robert P.

1993-01-01

The results of a traveling-wave-tube/multistage depressed-collector (TWT-MDC) design study in support of the Advanced Research Projects Agency/Department of Defense (ARPA/DOD) Microwave Power Module (MPM) Program are described. The study stressed the possible application of dynamic and other tapers to the RF output circuit of the MPM traveling wave tube as a means of increasing the RF and overall efficiencies and reducing the required beam current (perveance). The results indicate that a highly efficient, modified dynamic velocity taper (DVT) circuit can be designed for the broadband MPM application. The combination of reduced cathode current (lower perveance) and increased RF efficiency leads to (1) a substantially higher overall efficiency and reduction in the prime power to the MPM, and (2) substantially reduced levels of MDC and MPM heat dissipation, which simplify the cooling problems. However, the selected TWT circuit parameters need to be validated by cold test measurements on actual circuits.

Large Signal Modeling and Analysis of the GaAs MESFET.

DTIC Science & Technology

1986-07-09

various dimensions and physical parameters. A powerful computer aided design system can be developed by automating the circuit element and parameter...circuit model of the GaAs MESFET to aid in the designs of microwave MESFET circuits. The circuit elements of this model are obtained either directly...34. -. ’ Abstract The purpose of this work is to develop a large signal signal lumped circuit model of the GaAs MESFET to aid In the designs of microwave MESFET

Focal plane infrared readout circuit

NASA Technical Reports Server (NTRS)

Pain, Bedabrata (Inventor)

2002-01-01

An infrared imager, such as a spectrometer, includes multiple infrared photodetectors and readout circuits for reading out signals from the photodetectors. Each readout circuit includes a buffered direct injection input circuit including a differential amplifier with active feedback provided through an injection transistor. The differential amplifier includes a pair of input transistors, a pair of cascode transistors and a current mirror load. Photocurrent from a photodetector can be injected onto an integration capacitor in the readout circuit with high injection efficiency at high speed. A high speed, low noise, wide dynamic range linear infrared multiplexer array for reading out infrared detectors with large capacitances can be achieved even when short exposure times are used. The effect of image lag can be reduced.

Synaptic Scaling in Combination with Many Generic Plasticity Mechanisms Stabilizes Circuit Connectivity

PubMed Central

Tetzlaff, Christian; Kolodziejski, Christoph; Timme, Marc; Wörgötter, Florentin

2011-01-01

Synaptic scaling is a slow process that modifies synapses, keeping the firing rate of neural circuits in specific regimes. Together with other processes, such as conventional synaptic plasticity in the form of long term depression and potentiation, synaptic scaling changes the synaptic patterns in a network, ensuring diverse, functionally relevant, stable, and input-dependent connectivity. How synaptic patterns are generated and stabilized, however, is largely unknown. Here we formally describe and analyze synaptic scaling based on results from experimental studies and demonstrate that the combination of different conventional plasticity mechanisms and synaptic scaling provides a powerful general framework for regulating network connectivity. In addition, we design several simple models that reproduce experimentally observed synaptic distributions as well as the observed synaptic modifications during sustained activity changes. These models predict that the combination of plasticity with scaling generates globally stable, input-controlled synaptic patterns, also in recurrent networks. Thus, in combination with other forms of plasticity, synaptic scaling can robustly yield neuronal circuits with high synaptic diversity, which potentially enables robust dynamic storage of complex activation patterns. This mechanism is even more pronounced when considering networks with a realistic degree of inhibition. Synaptic scaling combined with plasticity could thus be the basis for learning structured behavior even in initially random networks. PMID:22203799

A new crank arm based load cell, with built-in conditioning circuit and strain gages, to measure the components of the force applied by a cyclist.

PubMed

Pigatto, Andre V; Moura, Karina O A; Favieiro, Gabriela W; Balbinot, Alexandre

2016-08-01

This report describes the development of a force platform based on instrumented load cells with built-in conditioning circuit and strain gages to measure and acquire the components of the force that is applied to the bike crank arm during pedaling in real conditions, and save them on a SD Card. To accomplish that, a complete new crank arm 3D solid model was developed in the SolidWorks, with dimensions equivalent to a commercial crank set and compatible with a conventional road bike, but with a compartment to support all the electronics necessary to measure 3 components of the force applied to the pedal during pedaling. After that, a 6082 T6 Aluminum Crankset based on the solid model was made and instrumented with three Wheatstone bridges each. The signals were conditioned on a printed circuit board, made on SMD technology, and acquired using a microcontroller with a DAC. Static deformation analysis showed a linearity error below 0.6% for all six channels. Dynamic analysis showed a natural frequency above 136Hz. A one-factor experiment design was performed with 5 amateur cyclists. ANOVA showed that the cyclist weight causes significant variation on the force applied to the bicycle pedal and its bilateral symmetry.

Coexistence of Multiple Attractors in an Active Diode Pair Based Chua’s Circuit

NASA Astrophysics Data System (ADS)

Bao, Bocheng; Wu, Huagan; Xu, Li; Chen, Mo; Hu, Wen

This paper focuses on the coexistence of multiple attractors in an active diode pair based Chua’s circuit with smooth nonlinearity. With dimensionless equations, dynamical properties, including boundness of system orbits and stability distributions of two nonzero equilibrium points, are investigated, and complex coexisting behaviors of multiple kinds of disconnected attractors of stable point attractors, limit cycles and chaotic attractors are numerically revealed. The results show that unlike the classical Chua’s circuit, the proposed circuit has two stable nonzero node-foci for the specified circuit parameters, thereby resulting in the emergence of multistability phenomenon. Based on two general impedance converters, the active diode pair based Chua’s circuit with an adjustable inductor and an adjustable capacitor is made in hardware, from which coexisting multiple attractors are conveniently captured.

Passively Shunted Piezoelectric Damping of Centrifugally-Loaded Plates

NASA Technical Reports Server (NTRS)

Duffy, Kirsten P.; Provenza, Andrew J.; Trudell, Jeffrey J.; Min, James B.

2009-01-01

Researchers at NASA Glenn Research Center have been investigating shunted piezoelectric circuits as potential damping treatments for turbomachinery rotor blades. This effort seeks to determine the effects of centrifugal loading on passively-shunted piezoelectric - damped plates. Passive shunt circuit parameters are optimized for the plate's third bending mode. Tests are performed both non-spinning and in the Dynamic Spin Facility to verify the analysis, and to determine the effectiveness of the damping under centrifugal loading. Results show that a resistive shunt circuit will reduce resonant vibration for this configuration. However, a tuned shunt circuit will be required to achieve the desired damping level. The analysis and testing address several issues with passive shunt circuit implementation in a rotating system, including piezoelectric material integrity under centrifugal loading, shunt circuit implementation, and tip mode damping.

[Study for portable dynamic ECG monitor and recorder].

PubMed

Yang, Pengcheng; Li, Yongqin; Chen, Bihua

2012-09-01

This Paper presents a portable dynamic ECG monitor system based on MSP430F149 microcontroller. The electrocardiogram detecting system consists of ECG detecting circuit, man-machine interaction module, MSP430F149 and upper computer software. The ECG detecting circuit including a preamplifier, second-order Butterworth low-pass filter, high-pass filter, and 50Hz trap circuit to detects electrocardiogram and depresses various kinds of interference effectively. A microcontroller is used to collect three channel analog signals which can be displayed on TFT LCD. A SD card is used to record real-time data continuously and implement the FTA16 file system. In the end, a host computer system interface is also designed to analyze the ECG signal and the analysis results can provide diagnosis references to clinical doctors.

Gain Modulation by an Urgency Signal Controls the Speed–Accuracy Trade-Off in a Network Model of a Cortical Decision Circuit

PubMed Central

Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C.

2011-01-01

The speed–accuracy trade-off (SAT) is ubiquitous in decision tasks. While the neural mechanisms underlying decisions are generally well characterized, the application of decision-theoretic methods to the SAT has been difficult to reconcile with experimental data suggesting that decision thresholds are inflexible. Using a network model of a cortical decision circuit, we demonstrate the SAT in a manner consistent with neural and behavioral data and with mathematical models that optimize speed and accuracy with respect to one another. In simulations of a reaction time task, we modulate the gain of the network with a signal encoding the urgency to respond. As the urgency signal builds up, the network progresses through a series of processing stages supporting noise filtering, integration of evidence, amplification of integrated evidence, and choice selection. Analysis of the network's dynamics formally characterizes this progression. Slower buildup of urgency increases accuracy by slowing down the progression. Faster buildup has the opposite effect. Because the network always progresses through the same stages, decision-selective firing rates are stereotyped at decision time. PMID:21415911

Gain modulation by an urgency signal controls the speed-accuracy trade-off in a network model of a cortical decision circuit.

PubMed

Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C

2011-01-01

The speed-accuracy trade-off (SAT) is ubiquitous in decision tasks. While the neural mechanisms underlying decisions are generally well characterized, the application of decision-theoretic methods to the SAT has been difficult to reconcile with experimental data suggesting that decision thresholds are inflexible. Using a network model of a cortical decision circuit, we demonstrate the SAT in a manner consistent with neural and behavioral data and with mathematical models that optimize speed and accuracy with respect to one another. In simulations of a reaction time task, we modulate the gain of the network with a signal encoding the urgency to respond. As the urgency signal builds up, the network progresses through a series of processing stages supporting noise filtering, integration of evidence, amplification of integrated evidence, and choice selection. Analysis of the network's dynamics formally characterizes this progression. Slower buildup of urgency increases accuracy by slowing down the progression. Faster buildup has the opposite effect. Because the network always progresses through the same stages, decision-selective firing rates are stereotyped at decision time.

Multiphysics Simulation of Welding-Arc and Nozzle-Arc System: Mathematical-Model, Solution-Methodology and Validation

NASA Astrophysics Data System (ADS)

Pawar, Sumedh; Sharma, Atul

2018-01-01

This work presents mathematical model and solution methodology for a multiphysics engineering problem on arc formation during welding and inside a nozzle. A general-purpose commercial CFD solver ANSYS FLUENT 13.0.0 is used in this work. Arc formation involves strongly coupled gas dynamics and electro-dynamics, simulated by solution of coupled Navier-Stoke equations, Maxwell's equations and radiation heat-transfer equation. Validation of the present numerical methodology is demonstrated with an excellent agreement with the published results. The developed mathematical model and the user defined functions (UDFs) are independent of the geometry and are applicable to any system that involves arc-formation, in 2D axisymmetric coordinates system. The high-pressure flow of SF6 gas in the nozzle-arc system resembles arc chamber of SF6 gas circuit breaker; thus, this methodology can be extended to simulate arcing phenomenon during current interruption.

Slow dynamics and regularization phenomena in ensembles of chaotic neurons

NASA Astrophysics Data System (ADS)

Rabinovich, M. I.; Varona, P.; Torres, J. J.; Huerta, R.; Abarbanel, H. D. I.

1999-02-01

We have explored the role of calcium concentration dynamics in the generation of chaos and in the regularization of the bursting oscillations using a minimal neural circuit of two coupled model neurons. In regions of the control parameter space where the slowest component, namely the calcium concentration in the endoplasmic reticulum, weakly depends on the other variables, this model is analogous to three dimensional systems as found in [1] or [2]. These are minimal models that describe the fundamental characteristics of the chaotic spiking-bursting behavior observed in real neurons. We have investigated different regimes of cooperative behavior in large assemblies of such units using lattice of non-identical Hindmarsh-Rose neurons electrically coupled with parameters chosen randomly inside the chaotic region. We study the regularization mechanisms in large assemblies and the development of several spatio-temporal patterns as a function of the interconnectivity among nearest neighbors.

Issues associated with modelling of proton exchange membrane fuel cell by computational fluid dynamics

NASA Astrophysics Data System (ADS)

Bednarek, Tomasz; Tsotridis, Georgios

2017-03-01

The objective of the current study is to highlight possible limitations and difficulties associated with Computational Fluid Dynamics in PEM single fuel cell modelling. It is shown that an appropriate convergence methodology should be applied for steady-state solutions, due to inherent numerical instabilities. A single channel fuel cell model has been taken as numerical example. Results are evaluated for quantitative as well qualitative points of view. The contribution to the polarization curve of the different fuel cell components such as bi-polar plates, gas diffusion layers, catalyst layers and membrane was investigated via their effects on the overpotentials. Furthermore, the potential losses corresponding to reaction kinetics, due to ohmic and mas transport limitations and the effect of the exchange current density and open circuit voltage, were also investigated. It is highlighted that the lack of reliable and robust input data is one of the issues for obtaining accurate results.

Sliding mode control based on Kalman filter dynamic estimation of battery SOC

NASA Astrophysics Data System (ADS)

He, Dongmeia; Hou, Enguang; Qiao, Xin; Liu, Guangmin

2018-06-01

Lithium-ion battery charge state of the accurate and rapid estimation of battery management system is the key technology. In this paper, an exponentially reaching law sliding-mode variable structure control algorithm based on Kalman filter is proposed to estimate the state of charge of Li-ion battery for the dynamic nonlinear system. The RC equivalent circuit model is established, and the model equation with specific structure is given. The proposed Kalman filter sliding mode structure is used to estimate the state of charge of the battery in the battery model, and the jitter effect can be avoided and the estimation performance can be improved. The simulation results show that the proposed Kalman filter sliding mode control has good accuracy in estimating the state of charge of the battery compared with the ordinary Kalman filter, and the error range is within 3%.

Maximum Temperature Detection System for Integrated Circuits

NASA Astrophysics Data System (ADS)

Frankiewicz, Maciej; Kos, Andrzej

2015-03-01

The paper describes structure and measurement results of the system detecting present maximum temperature on the surface of an integrated circuit. The system consists of the set of proportional to absolute temperature sensors, temperature processing path and a digital part designed in VHDL. Analogue parts of the circuit where designed with full-custom technique. The system is a part of temperature-controlled oscillator circuit - a power management system based on dynamic frequency scaling method. The oscillator cooperates with microprocessor dedicated for thermal experiments. The whole system is implemented in UMC CMOS 0.18 μm (1.8 V) technology.

Distinct Sources of Deterministic and Stochastic Components of Action Timing Decisions in Rodent Frontal Cortex.

PubMed

Murakami, Masayoshi; Shteingart, Hanan; Loewenstein, Yonatan; Mainen, Zachary F

2017-05-17

The selection and timing of actions are subject to determinate influences such as sensory cues and internal state as well as to effectively stochastic variability. Although stochastic choice mechanisms are assumed by many theoretical models, their origin and mechanisms remain poorly understood. Here we investigated this issue by studying how neural circuits in the frontal cortex determine action timing in rats performing a waiting task. Electrophysiological recordings from two regions necessary for this behavior, medial prefrontal cortex (mPFC) and secondary motor cortex (M2), revealed an unexpected functional dissociation. Both areas encoded deterministic biases in action timing, but only M2 neurons reflected stochastic trial-by-trial fluctuations. This differential coding was reflected in distinct timescales of neural dynamics in the two frontal cortical areas. These results suggest a two-stage model in which stochastic components of action timing decisions are injected by circuits downstream of those carrying deterministic bias signals. Copyright © 2017 Elsevier Inc. All rights reserved.

Analysis of Arc Characteristics and Flow Field in Arc Chamber of High-Voltage SF6 Auto-Expansion Circuit Breaker

NASA Astrophysics Data System (ADS)

Zhang, Junmin; Chen, Zhang

2008-10-01

A new magnetic hydro-dynamics model for nozzle arc emphasizing the interaction of arc with PTFE (polytetrafluorethylene) vapour is established based on the conservation equations. The interruption of auto-expansion circuit breaker is simulated numerically by finite element method and the influence of PTFE vapour on the arc is analysed with this model. The results reveal that the flow field inside the arc chamber is determined by the arc current, the arcing time, the nozzle arc and the clogging of its thermal boundary. The establishment of quenching pressure relies on both SF6 gas and PTFE vapour that absorbed arc energy in the nozzle. The PTFE vapour leads to an increase in the pressure of nozzle arc obviously, and a decrease in the temperature of arc. But it enhances the temperature of arc at zero current and slows down the decreasing rate of arc temperature as the current decreases.

Analysis of a minimal Rho-GTPase circuit regulating cell shape

NASA Astrophysics Data System (ADS)

Holmes, William R.; Edelstein-Keshet, Leah

2016-08-01

Networks of Rho-family GTPases regulate eukaryotic cell polarization and motility by controlling assembly and contraction of the cytoskeleton. The mutually inhibitory Rac-Rho circuit is emerging as a central, regulatory hub that can affect the shape and motility phenotype of eukaryotic cells. Recent experimental manipulation of the amounts of Rac and Rho or their regulators (guanine nucleotide-exchange factors, GTPase-activating proteins, guanine nucleotide dissociation inhibitors) have been shown to bias the prevalence of these different states and promote transitions between them. Here we show that part of this data can be understood in terms of inherent Rac-Rho mutually inhibitory dynamics. We analyze a spatio-temporal mathematical model of Rac-Rho dynamics to produce a detailed set of predictions of how parameters such as GTPase rates of activation and total amounts affect cell decisions (such as Rho-dominated contraction, Rac-dominated spreading, and spatially segregated Rac-Rho polarization). We find that in some parameter regimes, a cell can take on any of these three fates depending on its environment or stimuli. We also predict how experimental manipulations (corresponding to parameter variations) can affect cell shapes observed. Our methods are based on local perturbation analysis (a kind of nonlinear stability analysis), and an approximation of nonlinear feedback by sharp switches. We compare the Rac-Rho model to an even simpler single-GTPase (‘wave-pinning’) model and demonstrate that the overall behavior is inherent to GTPase properties, rather than stemming solely from network topology.

Optimization of return electrodes in neurostimulating arrays

NASA Astrophysics Data System (ADS)

Flores, Thomas; Goetz, Georges; Lei, Xin; Palanker, Daniel

2016-06-01

Objective. High resolution visual prostheses require dense stimulating arrays with localized inputs of individual electrodes. We study the electric field produced by multielectrode arrays in electrolyte to determine an optimal configuration of return electrodes and activation sequence. Approach. To determine the boundary conditions for computation of the electric field in electrolyte, we assessed current dynamics using an equivalent circuit of a multielectrode array with interleaved return electrodes. The electric field modeled with two different boundary conditions derived from the equivalent circuit was then compared to measurements of electric potential in electrolyte. To assess the effect of return electrode configuration on retinal stimulation, we transformed the computed electric fields into retinal response using a model of neural network-mediated stimulation. Main results. Electric currents at the capacitive electrode-electrolyte interface redistribute over time, so that boundary conditions transition from equipotential surfaces at the beginning of the pulse to uniform current density in steady state. Experimental measurements confirmed that, in steady state, the boundary condition corresponds to a uniform current density on electrode surfaces. Arrays with local return electrodes exhibit improved field confinement and can elicit stronger network-mediated retinal response compared to those with a common remote return. Connecting local return electrodes enhances the field penetration depth and allows reducing the return electrode area. Sequential activation of the pixels in large monopolar arrays reduces electrical cross-talk and improves the contrast in pattern stimulation. Significance. Accurate modeling of multielectrode arrays helps optimize the electrode configuration to maximize the spatial resolution, contrast and dynamic range of retinal prostheses.

A CSMP commutation model for design study of a brushless dc motor power conditioner for a cruise missile fin control actuator

NASA Astrophysics Data System (ADS)

MacMillan, P. N.

1985-06-01

Recent improvements in rare earth magnets have made it possible to construct strong, lightweight, high horsepower dc motors. This has occasioned a reassessment of electromechanical actuators as alternatives to comparable pneumatic and hydraulic systems for use as flight control actuators for tactical missiles. A dynamic equivalent circuit model for the analysis of a small four pole brushless dc motor fed by a transistorized power conditioner utilizing high speed switching power transistors as final elements is presented. The influence of electronic commutation on instantaneous dynamic motor performance is particularly demonstrated and good correlation between computer simulation and typical experimentally obtained performance data is achieved. The model is implemented in CSMP language and features more accurate air gap flux representation over previous work. Hall effect sensor rotor position feedback is simulated. Both constant and variable air gap flux is modeled and the variable flux model treats the flux as a fundamental and one harmonic.

A Novel Prediction Method about Single Components of Analog Circuits Based on Complex Field Modeling

PubMed Central

Tian, Shulin; Yang, Chenglin

2014-01-01

Few researches pay attention to prediction about analog circuits. The few methods lack the correlation with circuit analysis during extracting and calculating features so that FI (fault indicator) calculation often lack rationality, thus affecting prognostic performance. To solve the above problem, this paper proposes a novel prediction method about single components of analog circuits based on complex field modeling. Aiming at the feature that faults of single components hold the largest number in analog circuits, the method starts with circuit structure, analyzes transfer function of circuits, and implements complex field modeling. Then, by an established parameter scanning model related to complex field, it analyzes the relationship between parameter variation and degeneration of single components in the model in order to obtain a more reasonable FI feature set via calculation. According to the obtained FI feature set, it establishes a novel model about degeneration trend of analog circuits' single components. At last, it uses particle filter (PF) to update parameters for the model and predicts remaining useful performance (RUP) of analog circuits' single components. Since calculation about the FI feature set is more reasonable, accuracy of prediction is improved to some extent. Finally, the foregoing conclusions are verified by experiments. PMID:25147853

Study of the interrelation between the electrotechnical parameters of the plasma focus discharge circuit and the plasma compression dynamics on the PF-3 and PF-1000 facilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mitrofanov, K. N., E-mail: mitrkn@inbox.ru; Krauz, V. I., E-mail: krauz-vi@nrcki.ru, E-mail: vkrauz@yandex.ru; Grabovski, E. V.

The main stages of the plasma current sheath (PCS) dynamics on two plasma focus (PF) facilities with different geometries of the electrode system, PF-3 (Filippov type) and PF-1000 (Mather type), were studied by analyzing the results of the current and voltage measurements. Some dynamic characteristics, such as the PCS velocity in the acceleration phase in the Mather-type facility (PF-1000), the moment at which the PCS reaches the anode end, and the plasma velocity in the radial stage of plasma compression in the PF-3 Filippov-type facility, were determined from the time dependence of the inductance of the discharge circuit with amore » dynamic plasma load. The energy characteristics of the discharge circuit of the compressing PCS were studied for different working gases (deuterium, argon, and neon) at initial pressures of 1.5–3 Torr in discharges with energies of 0.3–0.6 MJ. In experiments with deuterium, correlation between the neutron yield and the electromagnetic energy deposited directly in the compressed PCS was investigated.« less

The coupled dynamics of fluids and spacecraft in low gravity and low gravity fluid measurement

NASA Technical Reports Server (NTRS)

Hansman, R. John; Peterson, Lee D.; Crawley, Edward F.

1987-01-01

The very large mass fraction of liquids stored on broad current and future generation spacecraft has made critical the technologies of describing the fluid-spacecraft dynamics and measuring or gauging the fluid. Combined efforts in these areas are described, and preliminary results are presented. The coupled dynamics of fluids and spacecraft in low gravity study is characterizing the parametric behavior of fluid-spacecraft systems in which interaction between the fluid and spacecraft dynamics is encountered. Particular emphasis is given to the importance of nonlinear fluid free surface phenomena to the coupled dynamics. An experimental apparatus has been developed for demonstrating a coupled fluid-spacecraft system. In these experiments, slosh force signals are fed back to a model tank actuator through a tunable analog second order integration circuit. In this manner, the tank motion is coupled to the resulting slosh force. Results are being obtained in 1-g and in low-g (on the NASA KC-135) using dynamic systems nondimensionally identical except for the Bond numbers.

Charge-sensitive front-end electronics with operational amplifiers for CdZnTe detectors

NASA Astrophysics Data System (ADS)

Födisch, P.; Berthel, M.; Lange, B.; Kirschke, T.; Enghardt, W.; Kaever, P.

2016-09-01

Cadmium zinc telluride (CdZnTe, CZT) radiation detectors are suitable for a variety of applications, due to their high spatial resolution and spectroscopic energy performance at room temperature. However, state-of-the-art detector systems require high-performance readout electronics. Though an application-specific integrated circuit (ASIC) is an adequate solution for the readout, requirements of high dynamic range and high throughput are not available in any commercial circuit. Consequently, the present study develops the analog front-end electronics with operational amplifiers for an 8×8 pixelated CZT detector. For this purpose, we modeled an electrical equivalent circuit of the CZT detector with the associated charge-sensitive amplifier (CSA). Based on a detailed network analysis, the circuit design is completed by numerical values for various features such as ballistic deficit, charge-to-voltage gain, rise time, and noise level. A verification of the performance is carried out by synthetic detector signals and a pixel detector. The experimental results with the pixel detector assembly and a 22Na radioactive source emphasize the depth dependence of the measured energy. After pulse processing with depth correction based on the fit of the weighting potential, the energy resolution is 2.2% (FWHM) for the 511 keV photopeak.

Derivation and calibration of a gas metal arc welding (GMAW) dynamic droplet model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reutzel, E.W.; Einerson, C.J.; Johnson, J.A.

1996-12-31

A rudimentary, existing dynamic model for droplet growth and detachment in gas metal arc welding (GMAW) was improved and calibrated to match experimental data. The model simulates droplets growing at the end of an imaginary spring. Mass is added to the drop as the electrode melts, the droplet grows, and the spring is displaced. Detachment occurs when one of two criteria is met, and the amount of mass that is detached is a function of the droplet velocity at the time of detachment. Improvements to the model include the addition of a second criterion for drop detachment, a more sophisticatedmore » model of the power supply and secondary electric circuit, and the incorporation of a variable electrode resistance. Relevant physical parameters in the model were adjusted during model calibration. The average current, droplet frequency, and parameter-space location of globular-to-streaming mode transition were used as criteria for tuning the model. The average current predicted by the calibrated model matched the experimental average current to within 5% over a wide range of operating conditions.« less

Minimizing the total harmonic distortion for a 3 kW, 20 kHz ac to dc converter using SPICE

NASA Technical Reports Server (NTRS)

Lollar, Louis F.; Kapustka, Robert E.

1988-01-01

This paper describes the SPICE model of a transformer-rectified-filter (TRF) circuit and the Micro-CAP (Microcomputer Circuit Analysis Program) model and their application. The models were used to develop an actual circuit with reduced input current THD. The SPICE analysis consistently predicted the THD improvements in actual circuits as various designs were attempted. In an effort to predict and verify load regulation, the incorporation of saturable inductor models significantly improved the fidelity of the TRF circuit output voltage.

Research on the equivalent circuit model of a circular flexural-vibration-research on the equivalent circuit model of a circular flexural-vibration-mode piezoelectric transformer with moderate thickness.

PubMed

Huang, Yihua; Huang, Wenjin; Wang, Qinglei; Su, Xujian

2013-07-01

The equivalent circuit model of a piezoelectric transformer is useful in designing and optimizing the related driving circuits. Based on previous work, an equivalent circuit model for a circular flexural-vibration-mode piezoelectric transformer with moderate thickness is proposed and validated by finite element analysis. The input impedance, voltage gain, and efficiency of the transformer are determined through computation. The basic behaviors of the transformer are shown by numerical results.

Column-parallel correlated multiple sampling circuits for CMOS image sensors and their noise reduction effects.

PubMed

Suh, Sungho; Itoh, Shinya; Aoyama, Satoshi; Kawahito, Shoji

2010-01-01

For low-noise complementary metal-oxide-semiconductor (CMOS) image sensors, the reduction of pixel source follower noises is becoming very important. Column-parallel high-gain readout circuits are useful for low-noise CMOS image sensors. This paper presents column-parallel high-gain signal readout circuits, correlated multiple sampling (CMS) circuits and their noise reduction effects. In the CMS, the gain of the noise cancelling is controlled by the number of samplings. It has a similar effect to that of an amplified CDS for the thermal noise but is a little more effective for 1/f and RTS noises. Two types of the CMS with simple integration and folding integration are proposed. In the folding integration, the output signal swing is suppressed by a negative feedback using a comparator and one-bit D-to-A converter. The CMS circuit using the folding integration technique allows to realize a very low-noise level while maintaining a wide dynamic range. The noise reduction effects of their circuits have been investigated with a noise analysis and an implementation of a 1Mpixel pinned photodiode CMOS image sensor. Using 16 samplings, dynamic range of 59.4 dB and noise level of 1.9 e(-) for the simple integration CMS and 75 dB and 2.2 e(-) for the folding integration CMS, respectively, are obtained.

Digital transmitter for data bus communications system

NASA Technical Reports Server (NTRS)

Proch, G. E.

1974-01-01

Digital transmitter designed for Manchester coded signals (and all signals with ac waveforms) generated at a rate of one megabit per second includes efficient output isolation circuit. Transmitter consists of logic control section, amplifier, and output isolation section. Output isolation circuit provides dynamic impedance at terminals as function of amplifier output level.

Separating OR, SUM, and XOR Circuits☆

PubMed Central

Find, Magnus; Göös, Mika; Järvisalo, Matti; Kaski, Petteri; Koivisto, Mikko; Korhonen, Janne H.

2017-01-01

Given a boolean n × n matrix A we consider arithmetic circuits for computing the transformation x ↦ Ax over different semirings. Namely, we study three circuit models: monotone OR-circuits, monotone SUM-circuits (addition of non-negative integers), and non-monotone XOR-circuits (addition modulo 2). Our focus is on separating OR-circuits from the two other models in terms of circuit complexity: We show how to obtain matrices that admit OR-circuits of size O(n), but require SUM-circuits of size Ω(n3/2/log2n).We consider the task of rewriting a given OR-circuit as a XOR-circuit and prove that any subquadratic-time algorithm for this task violates the strong exponential time hypothesis. PMID:28529379

VHDL-AMS modelling and simulation of a planar electrostatic micromotor

NASA Astrophysics Data System (ADS)

Endemaño, A.; Fourniols, J. Y.; Camon, H.; Marchese, A.; Muratet, S.; Bony, F.; Dunnigan, M.; Desmulliez, M. P. Y.; Overton, G.

2003-09-01

System level simulation results of a planar electrostatic micromotor, based on analytical models of the static and dynamic torque behaviours, are presented. A planar variable capacitance (VC) electrostatic micromotor designed, fabricated and tested at LAAS (Toulouse) in 1995 is simulated using the high level language VHDL-AMS (VHSIC (very high speed integrated circuits) hardware description language-analog mixed signal). The analytical torque model is obtained by first calculating the overlaps and capacitances between different electrodes based on a conformal mapping transformation. Capacitance values in the order of 10-16 F and torque values in the order of 10-11 N m have been calculated in agreement with previous measurements and simulations from this type of motor. A dynamic model has been developed for the motor by calculating the inertia coefficient and estimating the friction-coefficient-based values calculated previously for other similar devices. Starting voltage results obtained from experimental measurement are in good agreement with our proposed simulation model. Simulation results of starting voltage values, step response, switching response and continuous operation of the micromotor, based on the dynamic model of the torque, are also presented. Four VHDL-AMS blocks were created, validated and simulated for power supply, excitation control, micromotor torque creation and micromotor dynamics. These blocks can be considered as the initial phase towards the creation of intellectual property (IP) blocks for microsystems in general and electrostatic micromotors in particular.

Elevated CaMKIIα and hyperphosphorylation of Homer mediate circuit dysfunction in a Fragile X Syndrome mouse model

PubMed Central

Guo, Weirui; Ceolin, Laura; Collins, Katie; Perroy, Julie; Huber, Kimberly M.

2015-01-01

Summary Abnormal metabotropic glutamate receptor 5 (mGluR5) function, as a result of disrupted scaffolding with its binding partner Homer, contributes to the pathophysiology of Fragile X Syndrome, a common inherited from of intellectual disability and autism caused by mutations in Fmr1. How loss of Fmr1 disrupts mGluR5-Homer scaffolds is unknown, and little is known about the dynamic regulation of mGluR5-Homer scaffolds in wildtype neurons. Here we demonstrate that brief (minutes) elevations in neural activity cause CaMKIIα-mediated phosphorylation of long Homer proteins and dissociation from mGluR5 at synapses. In Fmr1 knockout cortex, Homers are hyperphosphorylated as a result of elevated CaMKIIα protein. Genetic or pharmacological inhibition of CaMKIIα or replacement of Homers with dephosphomimetics restores mGluR5-Homer scaffolds and multiple Fmr1 KO phenotypes, including circuit hyperexcitability and/or seizures. This work links translational control of an FMRP target mRNA, CaMKIIα, to the molecular, cellular and circuit level brain dysfunction in a complex neurodevelopmental disorder. PMID:26670047

Fault Detection, Isolation and Recovery (FDIR) Portable Liquid Oxygen Hardware Demonstrator

NASA Technical Reports Server (NTRS)

Oostdyk, Rebecca L.; Perotti, Jose M.

2011-01-01

The Fault Detection, Isolation and Recovery (FDIR) hardware demonstration will highlight the effort being conducted by Constellation's Ground Operations (GO) to provide the Launch Control System (LCS) with system-level health management during vehicle processing and countdown activities. A proof-of-concept demonstration of the FDIR prototype established the capability of the software to provide real-time fault detection and isolation using generated Liquid Hydrogen data. The FDIR portable testbed unit (presented here) aims to enhance FDIR by providing a dynamic simulation of Constellation subsystems that feed the FDIR software live data based on Liquid Oxygen system properties. The LO2 cryogenic ground system has key properties that are analogous to the properties of an electronic circuit. The LO2 system is modeled using electrical components and an equivalent circuit is designed on a printed circuit board to simulate the live data. The portable testbed is also be equipped with data acquisition and communication hardware to relay the measurements to the FDIR application running on a PC. This portable testbed is an ideal capability to perform FDIR software testing, troubleshooting, training among others.

An optimization based study of equivalent circuit models for representing recordings at the neuron-electrode interface

PubMed Central

Thakore, Vaibhav; Molnar, Peter; Hickman, James J.

2014-01-01

Extracellular neuroelectronic interfacing is an emerging field with important applications in the fields of neural prosthetics, biological computation and biosensors. Traditionally, neuron-electrode interfaces have been modeled as linear point or area contact equivalent circuits but it is now being increasingly realized that such models cannot explain the shapes and magnitudes of the observed extracellular signals. Here, results were compared and contrasted from an unprecedented optimization based study of the point contact models for an extracellular ‘on-cell’ neuron-patch electrode and a planar neuron-microelectrode interface. Concurrent electrophysiological recordings from a single neuron simultaneously interfaced to three distinct electrodes (intracellular, ‘on-cell’ patch and planar microelectrode) allowed novel insights into the mechanism of signal transduction at the neuron-electrode interface. After a systematic isolation of the nonlinear neuronal contribution to the extracellular signal, a consistent underestimation of the simulated supra-threshold extracellular signals compared to the experimentally recorded signals was observed. This conclusively demonstrated that the dynamics of the interfacial medium contribute nonlinearly to the process of signal transduction at the neuron-electrode interface. Further, an examination of the optimized model parameters for the experimental extracellular recordings from sub- and supra-threshold stimulations of the neuron-electrode junctions revealed that ionic transport at the ‘on-cell’ neuron-patch electrode is dominated by diffusion whereas at the neuron-microelectrode interface the electric double layer (EDL) effects dominate. Based on this study, the limitations of the equivalent circuit models in their failure to account for the nonlinear EDL and ionic electrodiffusion effects occurring during signal transduction at the neuron-electrode interfaces are discussed. PMID:22695342

Synthetic Biology: A Unifying View and Review Using Analog Circuits.

PubMed

Teo, Jonathan J Y; Woo, Sung Sik; Sarpeshkar, Rahul

2015-08-01

We review the field of synthetic biology from an analog circuits and analog computation perspective, focusing on circuits that have been built in living cells. This perspective is well suited to pictorially, symbolically, and quantitatively representing the nonlinear, dynamic, and stochastic (noisy) ordinary and partial differential equations that rigorously describe the molecular circuits of synthetic biology. This perspective enables us to construct a canonical analog circuit schematic that helps unify and review the operation of many fundamental circuits that have been built in synthetic biology at the DNA, RNA, protein, and small-molecule levels over nearly two decades. We review 17 circuits in the literature as particular examples of feedforward and feedback analog circuits that arise from special topological cases of the canonical analog circuit schematic. Digital circuit operation of these circuits represents a special case of saturated analog circuit behavior and is automatically incorporated as well. Many issues that have prevented synthetic biology from scaling are naturally represented in analog circuit schematics. Furthermore, the deep similarity between the Boltzmann thermodynamic equations that describe noisy electronic current flow in subthreshold transistors and noisy molecular flux in biochemical reactions has helped map analog circuit motifs in electronics to analog circuit motifs in cells and vice versa via a `cytomorphic' approach. Thus, a body of knowledge in analog electronic circuit design, analysis, simulation, and implementation may also be useful in the robust and efficient design of molecular circuits in synthetic biology, helping it to scale to more complex circuits in the future.

Ultrasound transducer modeling-received voltage signals and the use of half-wavelength window layers with acoustic coupling layers.

PubMed

Willatzen, M

1999-01-01

A general set of modeling equations for lossless one-dimensional multilayer ultrasound transducers is presented based on first principles. In particular, a direct relationship between ultrasound transducer results and the underlying physical principles of electroacoustics is given. As such, the model may provide better physical understanding for designers not fully versed in electrical circuits theory or in linear system analyses. The model is suitable for time-domain analysis and monofrequency design. Special attention is given to the determination of the time-dependent voltage across the receiver electrodes subject to a general voltage input, but information on any (dynamic) variable of interest is provided. The basic equations governing the dynamics of the multilayer structure acting as transmitter as well as receiver are solved by Fourier analysis and by imposing continuity of velocity and pressure between layers. Sound transmission between the two piezoelectric circuits is assumed to take place in a water bath such that the Rayleigh equation can be used to obtain the incoming pressure at the receiver aperture from the acceleration of the opposing transmitter aperture. Comparison with experimental results is possible by allowing coupling to external electric impedances. A numerical test case using a multilayered 1-MHz transducer for flow meter applications was considered and good agreement with experiments was obtained in terms of voltage signals. The transducer contains a half-wavelength stainless steel layer needed to resist corrosion, the ability to operate at temperatures in a wide range from 20 to 150 degrees Celsius, resistance to impact from flowing particles in the medium, high pressure or vacuum, and pH values up to 10 in some locations. The influence of epoxy glue and grease acoustic coupling layers-between the piezoceramics and the stainless steel layer-in the range from 1 to 70 mum was examined. It was shown that, for the same layer thickness, epoxy glue is preferred as compared with grease, both in terms of signal shapes and amplitudes. Finally, inclusion of appropriate electric impedances in the transmitter and receiver circuits is found to affect signal pulses strongly.

Optogenetic perturbations reveal the dynamics of an oculomotor integrator

PubMed Central

Gonçalves, Pedro J.; Arrenberg, Aristides B.; Hablitzel, Bastian; Baier, Herwig; Machens, Christian K.

2014-01-01

Many neural systems can store short-term information in persistently firing neurons. Such persistent activity is believed to be maintained by recurrent feedback among neurons. This hypothesis has been fleshed out in detail for the oculomotor integrator (OI) for which the so-called “line attractor” network model can explain a large set of observations. Here we show that there is a plethora of such models, distinguished by the relative strength of recurrent excitation and inhibition. In each model, the firing rates of the neurons relax toward the persistent activity states. The dynamics of relaxation can be quite different, however, and depend on the levels of recurrent excitation and inhibition. To identify the correct model, we directly measure these relaxation dynamics by performing optogenetic perturbations in the OI of zebrafish expressing halorhodopsin or channelrhodopsin. We show that instantaneous, inhibitory stimulations of the OI lead to persistent, centripetal eye position changes ipsilateral to the stimulation. Excitatory stimulations similarly cause centripetal eye position changes, yet only contralateral to the stimulation. These results show that the dynamics of the OI are organized around a central attractor state—the null position of the eyes—which stabilizes the system against random perturbations. Our results pose new constraints on the circuit connectivity of the system and provide new insights into the mechanisms underlying persistent activity. PMID:24616666

Millimeter-wave interconnects for microwave-frequency quantum machines

NASA Astrophysics Data System (ADS)

Pechal, Marek; Safavi-Naeini, Amir H.

2017-10-01

Superconducting microwave circuits form a versatile platform for storing and manipulating quantum information. A major challenge to further scalability is to find approaches for connecting these systems over long distances and at high rates. One approach is to convert the quantum state of a microwave circuit to optical photons that can be transmitted over kilometers at room temperature with little loss. Many proposals for electro-optic conversion between microwave and optics use optical driving of a weak three-wave mixing nonlinearity to convert the frequency of an excitation. Residual absorption of this optical pump leads to heating, which is problematic at cryogenic temperatures. Here we propose an alternative approach where a nonlinear superconducting circuit is driven to interconvert between microwave-frequency (7 ×109 Hz) and millimeter-wave-frequency photons (3 ×1011 Hz). To understand the potential for quantum state conversion between microwave and millimeter-wave photons, we consider the driven four-wave mixing quantum dynamics of nonlinear circuits. In contrast to the linear dynamics of the driven three-wave mixing converters, the proposed four-wave mixing converter has nonlinear decoherence channels that lead to a more complex parameter space of couplings and pump powers that we map out. We consider physical realizations of such converter circuits by deriving theoretically the upper bound on the maximum obtainable nonlinear coupling between any two modes in a lossless circuit, and synthesizing an optimal circuit based on realistic materials that saturates this bound. Our proposed circuit dissipates less than 10-9 times the energy of current electro-optic converters per qubit. Finally, we outline the quantum link budget for optical, microwave, and millimeter-wave connections, showing that our approach is viable for realizing interconnected quantum processors for intracity or quantum data center environments.

Three-Loop Automatic of Control System the Landfill of Household Solid Waste

NASA Astrophysics Data System (ADS)

Sereda, T. G.; Kostarev, S. N.

2017-05-01

The analysis of models of governance ground municipal solid waste (MSW). Considered a distributed circuit (spatio-temporal) ground control model. Developed a dynamic model of multicontour control landfill. Adjustable parameters are defined (the ratio of CH4 CO2 emission/fluxes, concentrations of heavy metals ions) and control (purging array, irrigation, adding reagents). Based on laboratory studies carried out with the analysis of equity flows and procedures developed by the transferring matrix that takes into account the relationship control loops. A system of differential equations in the frequency and time domains. Given the numerical approaches solving systems of differential equations in finite differential form.

Electronic Model of a Ferroelectric Field Effect Transistor

NASA Technical Reports Server (NTRS)

MacLeod, Todd C.; Ho, Fat Duen; Russell, Larry (Technical Monitor)

2001-01-01

A pair of electronic models has been developed of a Ferroelectric Field Effect transistor. These models can be used in standard electrical circuit simulation programs to simulate the main characteristics of the FFET. The models use the Schmitt trigger circuit as a basis for their design. One model uses bipolar junction transistors and one uses MOSFET's. Each model has the main characteristics of the FFET, which are the current hysterisis with different gate voltages and decay of the drain current when the gate voltage is off. The drain current from each model has similar values to an actual FFET that was measured experimentally. T'he input and o Output resistance in the models are also similar to that of the FFET. The models are valid for all frequencies below RF levels. No attempt was made to model the high frequency characteristics of the FFET. Each model can be used to design circuits using FFET's with standard electrical simulation packages. These circuits can be used in designing non-volatile memory circuits and logic circuits and is compatible with all SPICE based circuit analysis programs. The models consist of only standard electrical components, such as BJT's, MOSFET's, diodes, resistors, and capacitors. Each model is compared to the experimental data measured from an actual FFET.

New Magneto-Inductive DC Magnetometer for Space Missions

NASA Astrophysics Data System (ADS)

Moldwin, M.; Bronner, B.; Regoli, L.; Thoma, J.; Shen, A.; Jenkins, G.; Cutler, J.

2017-12-01

A new magneto-inductive DC magnetometer is being developed at the University of Michigan that provides fluxgate quality measurements in a low mass, volume, power and cost package. The magnetometer enables constellation-class missions not only due to its low-resource requirements, but also its potential for commercial integrated circuit fabrication. The magneto-inductive operating principle is based on a simple resistance-inductor (RL) circuit and involves measurement of the time it takes to charge and discharge the inductor between an upper and lower threshold by means of a Schmitt trigger oscillator. This time is proportional to the inductance that in turn is proportional to the field strength. We have modeled the operating principle in the circuit simulator SPICE and have built a proto-type using modified commercial sensors. The performance specifications include a dynamic range over the full-Earth's field, sampling rates up to 80 Hz, sensor and electronics mass of about 30 g, circuit board and sensor housing volume of < 100 cm3, and power consumption of about 5 mW. This system's noise levels are predicted to be about 100 pT /√Hz @ 1 Hz with a precision of about 100 pT. Due to the simple circuit design, lack of an analog-to-digital converter, and choice of oscillator, we anticipate that it will be extremely temperature stable and radiation tolerant. This presentation will describe the constellation mission enabling design, the development status and the testing results of this new magnetometer.

Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity

PubMed Central

Bennett, James E. M.; Bair, Wyeth

2015-01-01

Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli. PMID:26308406

Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity.

PubMed

Bennett, James E M; Bair, Wyeth

2015-08-01

Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli.

Readout circuit with novel background suppression for long wavelength infrared focal plane arrays

NASA Astrophysics Data System (ADS)

Xie, L.; Xia, X. J.; Zhou, Y. F.; Wen, Y.; Sun, W. F.; Shi, L. X.

2011-02-01

In this article, a novel pixel readout circuit using a switched-capacitor integrator mode background suppression technique is presented for long wavelength infrared focal plane arrays. This circuit can improve dynamic range and signal-to-noise ratio by suppressing the large background current during integration. Compared with other background suppression techniques, the new background suppression technique is less sensitive to the process mismatch and has no additional shot noise. The proposed circuit is theoretically analysed and simulated while taking into account the non-ideal characteristics. The result shows that the background suppression non-uniformity is ultra-low even for a large process mismatch. The background suppression non-uniformity of the proposed circuit can also remain very small with technology scaling.

Transition dynamics of generalized multiple epileptic seizures associated with thalamic reticular nucleus excitability: A computational study

NASA Astrophysics Data System (ADS)

Liu, Suyu; Wang, Qingyun

2017-11-01

Presently, we improve a computational framework of thalamocortical circuits related to the Taylor's model to investigate the relationship between thalamic reticular nucleus (RE) excitability and epilepsy. By using bifurcation analysis, we explore the RE's excitability dynamics mechanism in the processes of seizure generation, development and transition. Results show that the seizure-free state, absence seizures, clonic seizures and tonic seizures can be formed as the RE excitability is changed in this established model. Importantly, it is verified that physiological changing GABAA inhibition in RE can elicit absence seizures and clonic seizures and the pathological transitions between these two seizures. Furthermore, when the level of AMPA connection is decreased or increased, this proposed model embraces absence seizures and clonic seizures, and tonic seizures, respectively. Except that, bifurcation mechanisms of dynamical transition of different seizures are analyzed in detail. In addition, hybrid regulations of the reticular nucleus excitability for epileptic seizures are proven to be valid within the suitable levels of AMPA and GABAA connection. Hopefully, the obtained results could be helpful for effective control of epileptic activities with additional pharmacological interference.

Analysis of complex neural circuits with nonlinear multidimensional hidden state models

PubMed Central

Friedman, Alexander; Slocum, Joshua F.; Tyulmankov, Danil; Gibb, Leif G.; Altshuler, Alex; Ruangwises, Suthee; Shi, Qinru; Toro Arana, Sebastian E.; Beck, Dirk W.; Sholes, Jacquelyn E. C.; Graybiel, Ann M.

2016-01-01

A universal need in understanding complex networks is the identification of individual information channels and their mutual interactions under different conditions. In neuroscience, our premier example, networks made up of billions of nodes dynamically interact to bring about thought and action. Granger causality is a powerful tool for identifying linear interactions, but handling nonlinear interactions remains an unmet challenge. We present a nonlinear multidimensional hidden state (NMHS) approach that achieves interaction strength analysis and decoding of networks with nonlinear interactions by including latent state variables for each node in the network. We compare NMHS to Granger causality in analyzing neural circuit recordings and simulations, improvised music, and sociodemographic data. We conclude that NMHS significantly extends the scope of analyses of multidimensional, nonlinear networks, notably in coping with the complexity of the brain. PMID:27222584

A dynamical systems approach for estimating phase interactions between rhythms of different frequencies from experimental data.

PubMed

Onojima, Takayuki; Goto, Takahiro; Mizuhara, Hiroaki; Aoyagi, Toshio

2018-01-01

Synchronization of neural oscillations as a mechanism of brain function is attracting increasing attention. Neural oscillation is a rhythmic neural activity that can be easily observed by noninvasive electroencephalography (EEG). Neural oscillations show the same frequency and cross-frequency synchronization for various cognitive and perceptual functions. However, it is unclear how this neural synchronization is achieved by a dynamical system. If neural oscillations are weakly coupled oscillators, the dynamics of neural synchronization can be described theoretically using a phase oscillator model. We propose an estimation method to identify the phase oscillator model from real data of cross-frequency synchronized activities. The proposed method can estimate the coupling function governing the properties of synchronization. Furthermore, we examine the reliability of the proposed method using time-series data obtained from numerical simulation and an electronic circuit experiment, and show that our method can estimate the coupling function correctly. Finally, we estimate the coupling function between EEG oscillation and the speech sound envelope, and discuss the validity of these results.