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Sample records for mcculloch-pitts artificial neurons

  1. A Neuron- and a Synapse Chip for Artificial Neural Networks

    DEFF Research Database (Denmark)

    Lansner, John; Lehmann, Torsten

    1992-01-01

    A cascadable, analog, CMOS chip set has been developed for hardware implementations of artificial neural networks (ANN's):I) a neuron chip containing an array of neurons with hyperbolic tangent activation functions and adjustable gains, and II) a synapse chip (or a matrix-vector multiplier) where...

  2. Artificial spatiotemporal touch inputs reveal complementary decoding in neocortical neurons.

    Science.gov (United States)

    Oddo, Calogero M; Mazzoni, Alberto; Spanne, Anton; Enander, Jonas M D; Mogensen, Hannes; Bengtsson, Fredrik; Camboni, Domenico; Micera, Silvestro; Jörntell, Henrik

    2017-04-04

    Investigations of the mechanisms of touch perception and decoding has been hampered by difficulties in achieving invariant patterns of skin sensor activation. To obtain reproducible spatiotemporal patterns of activation of sensory afferents, we used an artificial fingertip equipped with an array of neuromorphic sensors. The artificial fingertip was used to transduce real-world haptic stimuli into spatiotemporal patterns of spikes. These spike patterns were delivered to the skin afferents of the second digit of rats via an array of stimulation electrodes. Combined with low-noise intra- and extracellular recordings from neocortical neurons in vivo, this approach provided a previously inaccessible high resolution analysis of the representation of tactile information in the neocortical neuronal circuitry. The results indicate high information content in individual neurons and reveal multiple novel neuronal tactile coding features such as heterogeneous and complementary spatiotemporal input selectivity also between neighboring neurons. Such neuronal heterogeneity and complementariness can potentially support a very high decoding capacity in a limited population of neurons. Our results also indicate a potential neuroprosthetic approach to communicate with the brain at a very high resolution and provide a potential novel solution for evaluating the degree or state of neurological disease in animal models.

  3. Performance of networks of artificial neurons: The role of clustering

    International Nuclear Information System (INIS)

    Kim, Beom Jun

    2004-01-01

    The performance of the Hopfield neural network model is numerically studied on various complex networks, such as the Watts-Strogatz network, the Barabasi-Albert network, and the neuronal network of Caenorhabditis elegans. Through the use of a systematic way of controlling the clustering coefficient, with the degree of each neuron kept unchanged, we find that the networks with the lower clustering exhibit much better performance. The results are discussed in the practical viewpoint of application, and the biological implications are also suggested

  4. Rapid Integration of Artificial Sensory Feedback during Operant Conditioning of Motor Cortex Neurons.

    Science.gov (United States)

    Prsa, Mario; Galiñanes, Gregorio L; Huber, Daniel

    2017-02-22

    Neuronal motor commands, whether generating real or neuroprosthetic movements, are shaped by ongoing sensory feedback from the displacement being produced. Here we asked if cortical stimulation could provide artificial feedback during operant conditioning of cortical neurons. Simultaneous two-photon imaging and real-time optogenetic stimulation were used to train mice to activate a single neuron in motor cortex (M1), while continuous feedback of its activity level was provided by proportionally stimulating somatosensory cortex. This artificial signal was necessary to rapidly learn to increase the conditioned activity, detect correct performance, and maintain the learned behavior. Population imaging in M1 revealed that learning-related activity changes are observed in the conditioned cell only, which highlights the functional potential of individual neurons in the neocortex. Our findings demonstrate the capacity of animals to use an artificially induced cortical channel in a behaviorally relevant way and reveal the remarkable speed and specificity at which this can occur. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  5. Artificial neuron-glia networks learning approach based on cooperative coevolution.

    Science.gov (United States)

    Mesejo, Pablo; Ibáñez, Oscar; Fernández-Blanco, Enrique; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana B

    2015-06-01

    Artificial Neuron-Glia Networks (ANGNs) are a novel bio-inspired machine learning approach. They extend classical Artificial Neural Networks (ANNs) by incorporating recent findings and suppositions about the way information is processed by neural and astrocytic networks in the most evolved living organisms. Although ANGNs are not a consolidated method, their performance against the traditional approach, i.e. without artificial astrocytes, was already demonstrated on classification problems. However, the corresponding learning algorithms developed so far strongly depends on a set of glial parameters which are manually tuned for each specific problem. As a consequence, previous experimental tests have to be done in order to determine an adequate set of values, making such manual parameter configuration time-consuming, error-prone, biased and problem dependent. Thus, in this paper, we propose a novel learning approach for ANGNs that fully automates the learning process, and gives the possibility of testing any kind of reasonable parameter configuration for each specific problem. This new learning algorithm, based on coevolutionary genetic algorithms, is able to properly learn all the ANGNs parameters. Its performance is tested on five classification problems achieving significantly better results than ANGN and competitive results with ANN approaches.

  6. Artificial Induction of Associative Olfactory Memory by Optogenetic and Thermogenetic Activation of Olfactory Sensory Neurons and Octopaminergic Neurons in Drosophila Larvae.

    Science.gov (United States)

    Honda, Takato; Lee, Chi-Yu; Honjo, Ken; Furukubo-Tokunaga, Katsuo

    2016-01-01

    The larval brain of Drosophila melanogaster provides an excellent system for the study of the neurocircuitry mechanism of memory. Recent development of neurogenetic techniques in fruit flies enables manipulations of neuronal activities in freely behaving animals. This protocol describes detailed steps for artificial induction of olfactory associative memory in Drosophila larvae. In this protocol, the natural reward signal is substituted by thermogenetic activation of octopaminergic neurons in the brain. In parallel, the odor signal is substituted by optogenetic activation of a specific class of olfactory receptor neurons. Association of reward and odor stimuli is achieved with the concomitant application of blue light and heat that leads to activation of both sets of neurons in living transgenic larvae. Given its operational simplicity and robustness, this method could be utilized to further our knowledge on the neurocircuitry mechanism of memory in the fly brain.

  7. COMPUTER DYNAMICS SIMULATION OF DRUG DEPENDENCE THROUGH ARTIFICIAL NEURONAL NETWORK: PEDAGOGICAL AND CLINICAL IMPLICATIONS

    Directory of Open Access Journals (Sweden)

    G. SANTOS

    2008-05-01

    Full Text Available To develop and to evaluate the efficiency of a software able to simulate a virtual patient at different stages of addition was the main goal and challenge of this work. We developed the software in Borland™ Delphi  5®  programming language. Techniques of artificial intelligence, neuronal networks and expert systems, were responsible for modeling the neurobiological structures and mechanisms of the interaction with the drugs used. Dynamical simulation and  hypermedia were designed to increase the software’s interactivity which was able to show graphical information from virtual instrumentation and from realistic functional magnetic resonance imaging display. Early, the program was designed to be used by undergraduate students to improve their neurophysiologic learn, based not only in an interaction of membrane receptors with drugs, but in such a large behavioral simulation. The experimental manipulation of the software was accomplished by: i creating a virtual patient from a normal mood to a behavioral addiction, increasing gradatively: alcohol, opiate or cocaine doses. ii designing an approach to treat the patient, to get total or partial remission of behavioral disorder by combining psychopharmacology and psychotherapy. Integration of dynamic simulation with hypermedia and artificial intelligence has been able to point out behavioral details as tolerance, sensitization and level of addiction to drugs of abuse and so on, turned into a potentially useful tool in the development of teaching activities on several ways, such as education as well clinical skills, in which it could assist patients, families and health care to improve and test their knowledge and skills about different faces supported by drugs dependency. Those features are currently under investigation.

  8. A Hybrid Fuzzy Time Series Approach Based on Fuzzy Clustering and Artificial Neural Network with Single Multiplicative Neuron Model

    Directory of Open Access Journals (Sweden)

    Ozge Cagcag Yolcu

    2013-01-01

    Full Text Available Particularly in recent years, artificial intelligence optimization techniques have been used to make fuzzy time series approaches more systematic and improve forecasting performance. Besides, some fuzzy clustering methods and artificial neural networks with different structures are used in the fuzzification of observations and determination of fuzzy relationships, respectively. In approaches considering the membership values, the membership values are determined subjectively or fuzzy outputs of the system are obtained by considering that there is a relation between membership values in identification of relation. This necessitates defuzzification step and increases the model error. In this study, membership values were obtained more systematically by using Gustafson-Kessel fuzzy clustering technique. The use of artificial neural network with single multiplicative neuron model in identification of fuzzy relation eliminated the architecture selection problem as well as the necessity for defuzzification step by constituting target values from real observations of time series. The training of artificial neural network with single multiplicative neuron model which is used for identification of fuzzy relation step is carried out with particle swarm optimization. The proposed method is implemented using various time series and the results are compared with those of previous studies to demonstrate the performance of the proposed method.

  9. Artificial neuron operations and spike-timing-dependent plasticity using memristive devices for brain-inspired computing

    Science.gov (United States)

    Marukame, Takao; Nishi, Yoshifumi; Yasuda, Shin-ichi; Tanamoto, Tetsufumi

    2018-04-01

    The use of memristive devices for creating artificial neurons is promising for brain-inspired computing from the viewpoints of computation architecture and learning protocol. We present an energy-efficient multiplier accumulator based on a memristive array architecture incorporating both analog and digital circuitries. The analog circuitry is used to full advantage for neural networks, as demonstrated by the spike-timing-dependent plasticity (STDP) in fabricated AlO x /TiO x -based metal-oxide memristive devices. STDP protocols for controlling periodic analog resistance with long-range stability were experimentally verified using a variety of voltage amplitudes and spike timings.

  10. The characteristic patterns of neuronal avalanches in mice under anesthesia and at rest: An investigation using constrained artificial neural networks

    Science.gov (United States)

    Knöpfel, Thomas; Leech, Robert

    2018-01-01

    Local perturbations within complex dynamical systems can trigger cascade-like events that spread across significant portions of the system. Cascades of this type have been observed across a broad range of scales in the brain. Studies of these cascades, known as neuronal avalanches, usually report the statistics of large numbers of avalanches, without probing the characteristic patterns produced by the avalanches themselves. This is partly due to limitations in the extent or spatiotemporal resolution of commonly used neuroimaging techniques. In this study, we overcome these limitations by using optical voltage (genetically encoded voltage indicators) imaging. This allows us to record cortical activity in vivo across an entire cortical hemisphere, at both high spatial (~30um) and temporal (~20ms) resolution in mice that are either in an anesthetized or awake state. We then use artificial neural networks to identify the characteristic patterns created by neuronal avalanches in our data. The avalanches in the anesthetized cortex are most accurately classified by an artificial neural network architecture that simultaneously connects spatial and temporal information. This is in contrast with the awake cortex, in which avalanches are most accurately classified by an architecture that treats spatial and temporal information separately, due to the increased levels of spatiotemporal complexity. This is in keeping with reports of higher levels of spatiotemporal complexity in the awake brain coinciding with features of a dynamical system operating close to criticality. PMID:29795654

  11. Operant Conditioning: A Minimal Components Requirement in Artificial Spiking Neurons Designed for Bio-Inspired Robot’s Controller

    Directory of Open Access Journals (Sweden)

    André eCyr

    2014-07-01

    Full Text Available We demonstrate the operant conditioning (OC learning process within a basic bio-inspired robot controller paradigm, using an artificial spiking neural network (ASNN with minimal component count as artificial brain. In biological agents, OC results in behavioral changes that are learned from the consequences of previous actions, using progressive prediction adjustment triggered by reinforcers. In a robotics context, virtual and physical robots may benefit from a similar learning skill when facing unknown environments with no supervision. In this work, we demonstrate that a simple ASNN can efficiently realise many OC scenarios. The elementary learning kernel that we describe relies on a few critical neurons, synaptic links and the integration of habituation and spike-timing dependent plasticity (STDP as learning rules. Using four tasks of incremental complexity, our experimental results show that such minimal neural component set may be sufficient to implement many OC procedures. Hence, with the described bio-inspired module, OC can be implemented in a wide range of robot controllers, including those with limited computational resources.

  12. Artificial brains. A million spiking-neuron integrated circuit with a scalable communication network and interface.

    Science.gov (United States)

    Merolla, Paul A; Arthur, John V; Alvarez-Icaza, Rodrigo; Cassidy, Andrew S; Sawada, Jun; Akopyan, Filipp; Jackson, Bryan L; Imam, Nabil; Guo, Chen; Nakamura, Yutaka; Brezzo, Bernard; Vo, Ivan; Esser, Steven K; Appuswamy, Rathinakumar; Taba, Brian; Amir, Arnon; Flickner, Myron D; Risk, William P; Manohar, Rajit; Modha, Dharmendra S

    2014-08-08

    Inspired by the brain's structure, we have developed an efficient, scalable, and flexible non-von Neumann architecture that leverages contemporary silicon technology. To demonstrate, we built a 5.4-billion-transistor chip with 4096 neurosynaptic cores interconnected via an intrachip network that integrates 1 million programmable spiking neurons and 256 million configurable synapses. Chips can be tiled in two dimensions via an interchip communication interface, seamlessly scaling the architecture to a cortexlike sheet of arbitrary size. The architecture is well suited to many applications that use complex neural networks in real time, for example, multiobject detection and classification. With 400-pixel-by-240-pixel video input at 30 frames per second, the chip consumes 63 milliwatts. Copyright © 2014, American Association for the Advancement of Science.

  13. A Spray-On Carbon Nanotube Artificial Neuron Strain Sensor for Composite Structural Health Monitoring

    Directory of Open Access Journals (Sweden)

    Gyeongrak Choi

    2016-07-01

    Full Text Available We present a nanocomposite strain sensor (NCSS to develop a novel structural health monitoring (SHM sensor that can be easily installed in a composite structure. An NCSS made of a multi-walled carbon nanotubes (MWCNT/epoxy composite was installed on a target structure with facile processing. We attempted to evaluate the NCSS sensing characteristics and benchmark compared to those of a conventional foil strain gauge. The response of the NCSS was fairly good and the result was nearly identical to the strain gauge. A neuron, which is a biomimetic long continuous NCSS, was also developed, and its vibration response was investigated for structural damage detection of a composite cantilever. The vibration response for damage detection was measured by tracking the first natural frequency, which demonstrated good result that matched the finite element (FE analysis.

  14. Modern drug design: the implication of using artificial neuronal networks and multiple molecular dynamic simulations

    Science.gov (United States)

    Yakovenko, Oleksandr; Jones, Steven J. M.

    2018-01-01

    We report the implementation of molecular modeling approaches developed as a part of the 2016 Grand Challenge 2, the blinded competition of computer aided drug design technologies held by the D3R Drug Design Data Resource (https://drugdesigndata.org/). The challenge was focused on the ligands of the farnesoid X receptor (FXR), a highly flexible nuclear receptor of the cholesterol derivative chenodeoxycholic acid. FXR is considered an important therapeutic target for metabolic, inflammatory, bowel and obesity related diseases (Expert Opin Drug Metab Toxicol 4:523-532, 2015), but in the context of this competition it is also interesting due to the significant ligand-induced conformational changes displayed by the protein. To deal with these conformational changes we employed multiple simulations of molecular dynamics (MD). Our MD-based protocols were top-ranked in estimating the free energy of binding of the ligands and FXR protein. Our approach was ranked second in the prediction of the binding poses where we also combined MD with molecular docking and artificial neural networks. Our approach showed mediocre results for high-throughput scoring of interactions.

  15. Genetic algorithms used to optimize an artificial neural network design used in neutron spectrometry; Algoritmos geneticos utilizados para optimizar un diseno de red neuronal artificial usado en espectrometria de neutrones

    Energy Technology Data Exchange (ETDEWEB)

    Arteaga A, T.; Ortiz R, J. M.; Vega C, H. R., E-mail: tarcicio70@yahoo.co.uk [Universidad Autonoma de Zacatecas, Av. Lopez Velarde 117, 98600 Zacatecas, Zac. (Mexico)

    2016-10-15

    Artificial neural networks (Ann) are widely used; it which consist of an input layer, one or more hidden layers and an output layer; these layers contain neurons and each has connections called weights, where the knowledge are allowed and let to Ann solve problems proposed. These Ann is used to reconstruction of the energy spectrum of neutrons from count rates and develop Bonner sphere neutron dosimetry. Currently, we have developed Ann with high performance and generalization ability. Determine your optimal architecture is usually a difficult task, an exhaustive search of all possible combinations of parameters is rarely possible further training of the neural network with random initial weights can cause two major drawbacks: it can stuck in local minima or converge very slowly. In this project it will be used Genetic Algorithms (Ga); which are based on the principle or analogy of evolution through natural selection and has shown to be very effective in optimizing complex search functions and large spaces or to find a near optimal overall efficiency. The aim is to decrease the architecture in number of hidden neurons and therefore the total number of connections is reducing. The benefits obtained by optimizing the network are that the number of connections would be considerably smaller and thus the computational complexity, hardware integration, resources will be lower such that will allow to be even more viable implemented. To use the Ga three problems must be solve: 1) coding the problem into chromosomes. 2) Construct a fitness function. 3) Proper selection of genetic operators; crossover, selection, mutation. As a result, the scientific knowledge obtained can to be applied to similar problems having a reference parameters used and their impact on the optimization would to be generated. It concluded that the input layer and output are subject to the problem; the Ga propose the optimal number of neurons in the hidden layer without losing the quality of the

  16. Use of artificial neuronal networks for prediction of the control parameters in the process of anaerobic digestion with thermal pretreatment.

    Science.gov (United States)

    Flores-Asis, Rita; Méndez-Contreras, Juan M; Juárez-Martínez, Ulises; Alvarado-Lassman, Alejandro; Villanueva-Vásquez, Daniel; Aguilar-Lasserre, Alberto A

    2018-04-19

    This article focuses on the analysis of the behavior patterns of the variables involved in the anaerobic digestion process. The objective is to predict the impact factor and the behavior pattern of the variables, i.e., temperature, pH, volatile solids (VS), total solids, volumetric load, and hydraulic residence time, considering that these are the control variables for the conservation of the different groups of anaerobic microorganisms. To conduct the research, samples of physicochemical sludge were taken from a water treatment plant in a poultry processing factory, and, then, the substrate was characterized, and a thermal pretreatment was used to accelerate the hydrolysis process. The anaerobic digestion process was analyzed in order to obtain experimental data of the control variables and observe their impact on the production of biogas. The results showed that the thermal pre-hydrolysis applied at 90°C for 90 min accelerated the hydrolysis phase, allowing a significant 52% increase in the volume of methane produced. An artificial neural network was developed, and it was trained with the database obtained by monitoring the anaerobic digestion process. The results obtained from the artificial neural network showed that there is an adjustment between the real values and the prediction of validation based on 60 samples with a 96.4% coefficient of determination, and it was observed that the variables with the major impact on the process were the loading rate and VS, with impact factors of 36% and 23%, respectively.

  17. EXPERIMENTOS CON UNA PROTECCION BASADA EN REDES DE NEURONAS ARTIFICIALES;EXPERIMENTS WITH A PROTECTION BASED ON ARTIFICIALS NEURONS NETWORKS

    Directory of Open Access Journals (Sweden)

    Orlys Ernesto - Torres Breffe y otros

    2011-11-01

    Full Text Available En este trabajo se muestran los resultados de los experimentos físicos realizados con una protección basadatotalmente en Redes de Neuronas Artificiales para un transformador eléctrico a escala de laboratorio. Se demuestraque unas Redes de Neuronas Artificiales entrenadas, con datos provenientes de regímenes simuladosmatemáticamente, opera correctamente con señales de regímenes provenientes de casos reales, al menos a escalade laboratorio y con niveles reducidos de intensidad. Se describe la instalación experimental, tanto desde el puntode vista de hardware como software utilizando la tecnología de National Instrument. Se entrenan diferentes tipos deRedes Neuronales y todas aprendieron a proteger correctamente. Estos experimentos establecen las pautas para eldesarrollo de Relés Electrónicos Inteligentes que no se ajustarían, al menos con datos y valores de difícilcomprensión como los actuales relés, sino que se entrenarían una vez mediante la simulación matemática y laexperiencia práctica los haría cada vez mejores.In this work is shown the results of the physical experiments done with a protection totally based in Artificial NeuralNetworks for an electric transformer of the laboratory scale. Its demonstrated that some Artificial Neural Networkstrained with data coming from a mathematically simulated regimens, it operates correctly with signals coming fromreal cases, at least to laboratory scale and with reduced levels of intensity. The experimental installation is described,so much from the hardware and software point of view, using the technology of National Instrument. Different typesof Artificial Neural Nets are trained and all learned how to protect correctly. These experiments establish the rules forthe development of Intelligent Electronic Relays that would not be adjusted, at least with complex data and valueslike the current relays, they will be trained once from the mathematically simulation and the practical

  18. Introduction to Concepts in Artificial Neural Networks

    Science.gov (United States)

    Niebur, Dagmar

    1995-01-01

    This introduction to artificial neural networks summarizes some basic concepts of computational neuroscience and the resulting models of artificial neurons. The terminology of biological and artificial neurons, biological and machine learning and neural processing is introduced. The concepts of supervised and unsupervised learning are explained with examples from the power system area. Finally, a taxonomy of different types of neurons and different classes of artificial neural networks is presented.

  19. Design of an artificial neural network, with the topology oriented to the reconstruction of neutron spectra; Diseno de una red neuronal artificial, con la topologia orientada a la reconstruccion del espectro de neutrones

    Energy Technology Data Exchange (ETDEWEB)

    Arteaga A, T.; Ortiz R, J.M.; Vega C, H.R.; Hernandez D, V.M.; Manzanares A, E.; Mercado S, G.A. [Unidades Academicas de Estudios Nucleares, Ingenieria Electrica y Matematicas, Universidad de Zacatecas, A.P. 336, 98000 Zacatecas (Mexico)]. e-mail: tarcicio70@yahoo.co.uk

    2006-07-01

    People that live in high places respect to the sea level, in latitudes far from the equator or that they travel by plane, they are exposed to atmospheres of high radiation generated by the cosmic rays. Another atmosphere with radiation is the medical equipment, particle accelerators and nuclear reactors. The evaluation of the biological risk for neutron radiation requires an appropriate and sure dosimetry. A commonly used system is the Bonner Sphere Spectrometer (EEB) with the purpose of reconstructing the spectrum that is important because the equivalent dose for neutrons depends strongly on its energy. The count rates obtained in each sphere are treated, in most of the cases, for iterative methods, Monte Carlo or Maximum Entropy. Each one of them has difficulties that it motivates to the development of complementary procedures. Recently it has been used Artificial Neural Networks, ANN) and not yet conclusive results have been obtained. In this work it was designed an ANN to obtain the neutron energy spectrum neutrons starting from the counting rate of count of an EEB. The ANN was trained with 129 reference spectra obtained of the IAEA (1990, 2001), 24 were built as defined energy, including isotopic sources of neutrons of reference and operational, of accelerators, reactors, mathematical functions, and of defined energy with several peaks. The spectrum was transformed from lethargy units to energy and were reaccommodated in 31 energies using the Monte Carlo code 4C. The reaccommodated spectra and the response matrix UTA4 were used to calculate the prospective count rates in the EEB. These rates were used as entrance and its respective spectrum was used as output during the net training. The net design is Retropropagation type with 5 layers of 7, 140, 140, 140 and 31 neurons, transfer function logsig, tansig, logsig, logsig, logsig respectively. Training algorithm, traingdx. After the training, the net was proven with a group of training spectra and others that

  20. A program for assisting automatic generation control of the ELETRONORTE using artificial neural network; Um programa para assistencia ao controle automatico de geracao da Eletronorte usando rede neuronal artificial

    Energy Technology Data Exchange (ETDEWEB)

    Brito Filho, Pedro Rodrigues de; Nascimento Garcez, Jurandyr do [Para Univ., Belem, PA (Brazil). Centro Tecnologico; Charone, Junior, Wady [Centrais Eletricas do Nordeste do Brasil S.A. (ELETRONORTE), Belem, PA (Brazil)

    1994-12-31

    This work presents an application of artificial neural network as a support to decision making in the automatic generation control (AGC) of the ELETRONORTE. It uses a software to auxiliary in the decisions in real time of the AGC. (author) 2 refs., 6 figs., 1 tab.

  1. Single neuron computation

    CERN Document Server

    McKenna, Thomas M; Zornetzer, Steven F

    1992-01-01

    This book contains twenty-two original contributions that provide a comprehensive overview of computational approaches to understanding a single neuron structure. The focus on cellular-level processes is twofold. From a computational neuroscience perspective, a thorough understanding of the information processing performed by single neurons leads to an understanding of circuit- and systems-level activity. From the standpoint of artificial neural networks (ANNs), a single real neuron is as complex an operational unit as an entire ANN, and formalizing the complex computations performed by real n

  2. Artificial Astrocytes Improve Neural Network Performance

    Science.gov (United States)

    Porto-Pazos, Ana B.; Veiguela, Noha; Mesejo, Pablo; Navarrete, Marta; Alvarellos, Alberto; Ibáñez, Oscar; Pazos, Alejandro; Araque, Alfonso

    2011-01-01

    Compelling evidence indicates the existence of bidirectional communication between astrocytes and neurons. Astrocytes, a type of glial cells classically considered to be passive supportive cells, have been recently demonstrated to be actively involved in the processing and regulation of synaptic information, suggesting that brain function arises from the activity of neuron-glia networks. However, the actual impact of astrocytes in neural network function is largely unknown and its application in artificial intelligence remains untested. We have investigated the consequences of including artificial astrocytes, which present the biologically defined properties involved in astrocyte-neuron communication, on artificial neural network performance. Using connectionist systems and evolutionary algorithms, we have compared the performance of artificial neural networks (NN) and artificial neuron-glia networks (NGN) to solve classification problems. We show that the degree of success of NGN is superior to NN. Analysis of performances of NN with different number of neurons or different architectures indicate that the effects of NGN cannot be accounted for an increased number of network elements, but rather they are specifically due to astrocytes. Furthermore, the relative efficacy of NGN vs. NN increases as the complexity of the network increases. These results indicate that artificial astrocytes improve neural network performance, and established the concept of Artificial Neuron-Glia Networks, which represents a novel concept in Artificial Intelligence with implications in computational science as well as in the understanding of brain function. PMID:21526157

  3. Artificial astrocytes improve neural network performance.

    Directory of Open Access Journals (Sweden)

    Ana B Porto-Pazos

    Full Text Available Compelling evidence indicates the existence of bidirectional communication between astrocytes and neurons. Astrocytes, a type of glial cells classically considered to be passive supportive cells, have been recently demonstrated to be actively involved in the processing and regulation of synaptic information, suggesting that brain function arises from the activity of neuron-glia networks. However, the actual impact of astrocytes in neural network function is largely unknown and its application in artificial intelligence remains untested. We have investigated the consequences of including artificial astrocytes, which present the biologically defined properties involved in astrocyte-neuron communication, on artificial neural network performance. Using connectionist systems and evolutionary algorithms, we have compared the performance of artificial neural networks (NN and artificial neuron-glia networks (NGN to solve classification problems. We show that the degree of success of NGN is superior to NN. Analysis of performances of NN with different number of neurons or different architectures indicate that the effects of NGN cannot be accounted for an increased number of network elements, but rather they are specifically due to astrocytes. Furthermore, the relative efficacy of NGN vs. NN increases as the complexity of the network increases. These results indicate that artificial astrocytes improve neural network performance, and established the concept of Artificial Neuron-Glia Networks, which represents a novel concept in Artificial Intelligence with implications in computational science as well as in the understanding of brain function.

  4. Artificial astrocytes improve neural network performance.

    Science.gov (United States)

    Porto-Pazos, Ana B; Veiguela, Noha; Mesejo, Pablo; Navarrete, Marta; Alvarellos, Alberto; Ibáñez, Oscar; Pazos, Alejandro; Araque, Alfonso

    2011-04-19

    Compelling evidence indicates the existence of bidirectional communication between astrocytes and neurons. Astrocytes, a type of glial cells classically considered to be passive supportive cells, have been recently demonstrated to be actively involved in the processing and regulation of synaptic information, suggesting that brain function arises from the activity of neuron-glia networks. However, the actual impact of astrocytes in neural network function is largely unknown and its application in artificial intelligence remains untested. We have investigated the consequences of including artificial astrocytes, which present the biologically defined properties involved in astrocyte-neuron communication, on artificial neural network performance. Using connectionist systems and evolutionary algorithms, we have compared the performance of artificial neural networks (NN) and artificial neuron-glia networks (NGN) to solve classification problems. We show that the degree of success of NGN is superior to NN. Analysis of performances of NN with different number of neurons or different architectures indicate that the effects of NGN cannot be accounted for an increased number of network elements, but rather they are specifically due to astrocytes. Furthermore, the relative efficacy of NGN vs. NN increases as the complexity of the network increases. These results indicate that artificial astrocytes improve neural network performance, and established the concept of Artificial Neuron-Glia Networks, which represents a novel concept in Artificial Intelligence with implications in computational science as well as in the understanding of brain function.

  5. Simulation of lung motions using an artificial neural network; Utilisation d'un reseau de neurones artificiels pour la simulation des mouvements pulmonaires

    Energy Technology Data Exchange (ETDEWEB)

    Laurent, R.; Henriet, J.; Sauget, M.; Gschwind, R.; Makovicka, L. [IRMA/ENISYS/FEMTO-ST, UMR 6174 CNRS, pole universitaire des Portes du Jura, BP 71427, 25211 Montbeliard cedex (France); Salomon, M. [AND/LIFC, universite de Franche-Comte, BP 527, rue Engel-Gros, 90016 Belfort cedex (France); Nguyen, F. [Service de radiotherapie, CHU Jean-Minjoz, 3, boulevard Fleming, 25030 Besancon cedex (France)

    2011-04-15

    Purpose. A way to improve the accuracy of lung radiotherapy for a patient is to get a better understanding of its lung motion. Indeed, thanks to this knowledge it becomes possible to follow the displacements of the clinical target volume (CTV) induced by the lung breathing. This paper presents a feasibility study of an original method to simulate the positions of points in patient's lung at all breathing phases. Patients and methods. This method, based on an artificial neural network, allowed learning the lung motion on real cases and then to simulate it for new patients for which only the beginning and the end breathing data are known. The neural network learning set is made up of more than 600 points. These points, shared out on three patients and gathered on a specific lung area, were plotted by a MD. Results. - The first results are promising: an average accuracy of 1 mm is obtained for a spatial resolution of 1 x 1 x 2.5 mm{sup 3}. Conclusion. We have demonstrated that it is possible to simulate lung motion with accuracy using an artificial neural network. As future work we plan to improve the accuracy of our method with the addition of new patient data and a coverage of the whole lungs. (authors)

  6. The principles of artificial neural network information processing

    International Nuclear Information System (INIS)

    Dai, Ru-Wei

    1993-01-01

    In this article, the basic structure of an artificial neuron is first introduced. In addition, principles of artificial neural network as well as several important artificial neural models such as perception, back propagation model, Hopfield net, and ART model are briefly discussed and analyzed. Finally the application of artificial neural network for Chinese character recognition is also given. (author)

  7. The principles of artificial neural network information processing

    International Nuclear Information System (INIS)

    Dai, Ru-Wei

    1993-01-01

    In this article, the basic structure of an artificial neuron is first introduced. In addition, principles of artificial neural network as well as several important artificial neural models such as Perceptron, Back propagation model, Hopfield net, and ART model are briefly discussed and analyzed. Finally, the application of artificial neural network for Chinese Character Recognition is also given. (author)

  8. Artificial intelligence

    CERN Document Server

    Hunt, Earl B

    1975-01-01

    Artificial Intelligence provides information pertinent to the fundamental aspects of artificial intelligence. This book presents the basic mathematical and computational approaches to problems in the artificial intelligence field.Organized into four parts encompassing 16 chapters, this book begins with an overview of the various fields of artificial intelligence. This text then attempts to connect artificial intelligence problems to some of the notions of computability and abstract computing devices. Other chapters consider the general notion of computability, with focus on the interaction bet

  9. Reconstruction of the neutron spectrum using an artificial neural network in CPU and GPU; Reconstruccion del espectro de neutrones usando una red neuronal artificial (RNA) en CPU y GPU

    Energy Technology Data Exchange (ETDEWEB)

    Hernandez D, V. M.; Moreno M, A.; Ortiz L, M. A. [Universidad de Cordoba, 14002 Cordoba (Spain); Vega C, H. R.; Alonso M, O. E., E-mail: vic.mc68010@gmail.com [Universidad Autonoma de Zacatecas, 98000 Zacatecas, Zac. (Mexico)

    2016-10-15

    The increase in computing power in personal computers has been increasing, computers now have several processors in the CPU and in addition multiple CUDA cores in the graphics processing unit (GPU); both systems can be used individually or combined to perform scientific computation without resorting to processor or supercomputing arrangements. The Bonner sphere spectrometer is the most commonly used multi-element system for neutron detection purposes and its associated spectrum. Each sphere-detector combination gives a particular response that depends on the energy of the neutrons, and the total set of these responses is known like the responses matrix Rφ(E). Thus, the counting rates obtained with each sphere and the neutron spectrum is related to the Fredholm equation in its discrete version. For the reconstruction of the spectrum has a system of poorly conditioned equations with an infinite number of solutions and to find the appropriate solution, it has been proposed the use of artificial intelligence through neural networks with different platforms CPU and GPU. (Author)

  10. Recognition of faults patterns in electric generators using artificial neurons networks; Reconocimiento de patrones de fallas en generadores electricos empleando redes neuronales artificiales

    Energy Technology Data Exchange (ETDEWEB)

    Rocha Sanchez, Martha Alicia

    1999-03-01

    This work present the development of a reprocessing method to reduce the information of the original data and to maintain the essential information of the data that enter the reduction process. The obtaining of these data is performed with the aid of the ICM ++ (ICMsystems), from which vectors or n-uplos of elements are obtained. This investigation allowed to analyze an evaluation of the paradigms of artificial neural networks, with the intention of detecting which of these paradigms would evolve better with the problem of fault diagnosis in electric generators. From this a prototype system was developed called diagnosis of faults in electrical generators, which automatically will recognize faults in electrical generators by means of the interpretation of the recording of partial discharges. [Spanish] El presente trabajo presenta el desarrollo de un metodo de reprocesamiento para reducir informacion de los datos originales y mantener la informacion esencial de los datos que entran al proceso de reduccion. La obtencion de estos datos se realiza con la ayuda del ICM ++ (ICMsystems), de los cuales se obtienen vectores o n-uplos de elementos. Esta investigacion permitio analizar una evaluacion de los paradigmas de redes neuronales artificiales, con el objeto de detectar cual de estos paradigmas se desempenaria mejor con el problema de diagnostico de fallas en generadores electricos. A partir de esto se desarrollo un sistema prototipo llamado diagnostico de fallas en generadores electricos, el cual automaticamente reconocera fallas en los generadores electricos mediante la interpretacion de registro de descargas parciales.

  11. Artificial Intelligence and brain.

    Science.gov (United States)

    Shapshak, Paul

    2018-01-01

    From the start, Kurt Godel observed that computer and brain paradigms were considered on a par by researchers and that researchers had misunderstood his theorems. He hailed with displeasure that the brain transcends computers. In this brief article, we point out that Artificial Intelligence (AI) comprises multitudes of human-made methodologies, systems, and languages, and implemented with computer technology. These advances enhance development in the electron and quantum realms. In the biological realm, animal neurons function, also utilizing electron flow, and are products of evolution. Mirror neurons are an important paradigm in neuroscience research. Moreover, the paradigm shift proposed here - 'hall of mirror neurons' - is a potentially further productive research tactic. These concepts further expand AI and brain research.

  12. Neural Network Molecule: a Solution of the Inverse Biometry Problem through Software Support of Quantum Superposition on Outputs of the Network of Artificial Neurons

    Directory of Open Access Journals (Sweden)

    Vladimir I. Volchikhin

    2017-12-01

    Full Text Available Introduction: The aim of the study is to accelerate the solution of neural network biometrics inverse problem on an ordinary desktop computer. Materials and Methods: To speed up the calculations, the artificial neural network is introduced into the dynamic mode of “jittering” of the states of all 256 output bits. At the same time, too many output states of the neural network are logarithmically folded by transitioning to the Hamming distance space between the code of the image “Own” and the codes of the images “Alien”. From the database of images of “Alien” 2.5 % of the most similar images are selected. In the next generation, 97.5 % of the discarded images are restored with GOST R 52633.2-2010 procedures by crossing parent images and obtaining descendant images from them. Results: Over a period of about 10 minutes, 60 generations of directed search for the solution of the inverse problem can be realized that allows inversing matrices of neural network functionals of dimension 416 inputs to 256 outputs with restoration of up to 97 % information on unknown biometric parameters of the image “Own”. Discussion and Conclusions: Supporting for 10 minutes of computer time the 256 qubit quantum superposition allows on a conventional computer to bypass the actual infinity of analyzed states in 5050 (50 to 50 times more than the same computer could process realizing the usual calculations. The increase in the length of the supported quantum superposition by 40 qubits is equivalent to increasing the processor clock speed by about a billion times. It is for this reason that it is more profitable to increase the number of quantum superpositions supported by the software emulator in comparison with the creation of a more powerful processor.

  13. Artificial Intelligence.

    Science.gov (United States)

    Information Technology Quarterly, 1985

    1985-01-01

    This issue of "Information Technology Quarterly" is devoted to the theme of "Artificial Intelligence." It contains two major articles: (1) Artificial Intelligence and Law" (D. Peter O'Neill and George D. Wood); (2) "Artificial Intelligence: A Long and Winding Road" (John J. Simon, Jr.). In addition, it contains two sidebars: (1) "Calculating and…

  14. Artificial Consciousness or Artificial Intelligence

    OpenAIRE

    Spanache Florin

    2017-01-01

    Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus a...

  15. [Artificial organs].

    Science.gov (United States)

    Raguin, Thibaut; Dupret-Bories, Agnès; Debry, Christian

    2017-01-01

    Research has been fighting against organ failure and shortage of donations by supplying artificial organs for many years. With the raise of new technologies, tissue engineering and regenerative medicine, many organs can benefit of an artificial equivalent: thanks to retinal implants some blind people can visualize stimuli, an artificial heart can be proposed in case of cardiac failure while awaiting for a heart transplant, artificial larynx enables laryngectomy patients to an almost normal life, while the diabetic can get a glycemic self-regulation controlled by smartphones with an artificial device. Dialysis devices become portable, as well as the oxygenation systems for terminal respiratory failure. Bright prospects are being explored or might emerge in a near future. However, the retrospective assessment of putative side effects is not yet sufficient. Finally, the cost of these new devices is significant even if the advent of three dimensional printers may reduce it. © 2017 médecine/sciences – Inserm.

  16. Parvalbumin+ Neurons and Npas1+ Neurons Are Distinct Neuron Classes in the Mouse External Globus Pallidus.

    Science.gov (United States)

    Hernández, Vivian M; Hegeman, Daniel J; Cui, Qiaoling; Kelver, Daniel A; Fiske, Michael P; Glajch, Kelly E; Pitt, Jason E; Huang, Tina Y; Justice, Nicholas J; Chan, C Savio

    2015-08-26

    Compelling evidence suggests that pathological activity of the external globus pallidus (GPe), a nucleus in the basal ganglia, contributes to the motor symptoms of a variety of movement disorders such as Parkinson's disease. Recent studies have challenged the idea that the GPe comprises a single, homogenous population of neurons that serves as a simple relay in the indirect pathway. However, we still lack a full understanding of the diversity of the neurons that make up the GPe. Specifically, a more precise classification scheme is needed to better describe the fundamental biology and function of different GPe neuron classes. To this end, we generated a novel multicistronic BAC (bacterial artificial chromosome) transgenic mouse line under the regulatory elements of the Npas1 gene. Using a combinatorial transgenic and immunohistochemical approach, we discovered that parvalbumin-expressing neurons and Npas1-expressing neurons in the GPe represent two nonoverlapping cell classes, amounting to 55% and 27% of the total GPe neuron population, respectively. These two genetically identified cell classes projected primarily to the subthalamic nucleus and to the striatum, respectively. Additionally, parvalbumin-expressing neurons and Npas1-expressing neurons were distinct in their autonomous and driven firing characteristics, their expression of intrinsic ion conductances, and their responsiveness to chronic 6-hydroxydopamine lesion. In summary, our data argue that parvalbumin-expressing neurons and Npas1-expressing neurons are two distinct functional classes of GPe neurons. This work revises our understanding of the GPe, and provides the foundation for future studies of its function and dysfunction. Until recently, the heterogeneity of the constituent neurons within the external globus pallidus (GPe) was not fully appreciated. We addressed this knowledge gap by discovering two principal GPe neuron classes, which were identified by their nonoverlapping expression of the

  17. Parvalbumin+ Neurons and Npas1+ Neurons Are Distinct Neuron Classes in the Mouse External Globus Pallidus

    Science.gov (United States)

    Hernández, Vivian M.; Hegeman, Daniel J.; Cui, Qiaoling; Kelver, Daniel A.; Fiske, Michael P.; Glajch, Kelly E.; Pitt, Jason E.; Huang, Tina Y.; Justice, Nicholas J.

    2015-01-01

    Compelling evidence suggests that pathological activity of the external globus pallidus (GPe), a nucleus in the basal ganglia, contributes to the motor symptoms of a variety of movement disorders such as Parkinson's disease. Recent studies have challenged the idea that the GPe comprises a single, homogenous population of neurons that serves as a simple relay in the indirect pathway. However, we still lack a full understanding of the diversity of the neurons that make up the GPe. Specifically, a more precise classification scheme is needed to better describe the fundamental biology and function of different GPe neuron classes. To this end, we generated a novel multicistronic BAC (bacterial artificial chromosome) transgenic mouse line under the regulatory elements of the Npas1 gene. Using a combinatorial transgenic and immunohistochemical approach, we discovered that parvalbumin-expressing neurons and Npas1-expressing neurons in the GPe represent two nonoverlapping cell classes, amounting to 55% and 27% of the total GPe neuron population, respectively. These two genetically identified cell classes projected primarily to the subthalamic nucleus and to the striatum, respectively. Additionally, parvalbumin-expressing neurons and Npas1-expressing neurons were distinct in their autonomous and driven firing characteristics, their expression of intrinsic ion conductances, and their responsiveness to chronic 6-hydroxydopamine lesion. In summary, our data argue that parvalbumin-expressing neurons and Npas1-expressing neurons are two distinct functional classes of GPe neurons. This work revises our understanding of the GPe, and provides the foundation for future studies of its function and dysfunction. SIGNIFICANCE STATEMENT Until recently, the heterogeneity of the constituent neurons within the external globus pallidus (GPe) was not fully appreciated. We addressed this knowledge gap by discovering two principal GPe neuron classes, which were identified by their nonoverlapping

  18. Artificial intelligence

    CERN Document Server

    Ennals, J R

    1987-01-01

    Artificial Intelligence: State of the Art Report is a two-part report consisting of the invited papers and the analysis. The editor first gives an introduction to the invited papers before presenting each paper and the analysis, and then concludes with the list of references related to the study. The invited papers explore the various aspects of artificial intelligence. The analysis part assesses the major advances in artificial intelligence and provides a balanced analysis of the state of the art in this field. The Bibliography compiles the most important published material on the subject of

  19. Artificial Reefs

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — An artificial reef is a human-made underwater structure, typically built to promote marine life in areas with a generally featureless bottom, control erosion, block...

  20. Natural - synthetic - artificial!

    DEFF Research Database (Denmark)

    Nielsen, Peter E

    2010-01-01

    The terms "natural," "synthetic" and "artificial" are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life.......The terms "natural," "synthetic" and "artificial" are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life....

  1. Artificial sweeteners

    DEFF Research Database (Denmark)

    Raben, Anne Birgitte; Richelsen, Bjørn

    2012-01-01

    Artificial sweeteners can be a helpful tool to reduce energy intake and body weight and thereby risk for diabetes and cardiovascular diseases (CVD). Considering the prevailing diabesity (obesity and diabetes) epidemic, this can, therefore, be an important alternative to natural, calorie-containin......Artificial sweeteners can be a helpful tool to reduce energy intake and body weight and thereby risk for diabetes and cardiovascular diseases (CVD). Considering the prevailing diabesity (obesity and diabetes) epidemic, this can, therefore, be an important alternative to natural, calorie......-containing sweeteners. The purpose of this review is to summarize the current evidence on the effect of artificial sweeteners on body weight, appetite, and risk markers for diabetes and CVD in humans....

  2. The straintronic spin-neuron

    International Nuclear Information System (INIS)

    Biswas, Ayan K; Bandyopadhyay, Supriyo; Atulasimha, Jayasimha

    2015-01-01

    In artificial neural networks, neurons are usually implemented with highly dissipative CMOS-based operational amplifiers. A more energy-efficient implementation is a ‘spin-neuron’ realized with a magneto-tunneling junction (MTJ) that is switched with a spin-polarized current (representing weighted sum of input currents) that either delivers a spin transfer torque or induces domain wall motion in the soft layer of the MTJ to mimic neuron firing. Here, we propose and analyze a different type of spin-neuron in which the soft layer of the MTJ is switched with mechanical strain generated by a voltage (representing weighted sum of input voltages) and term it straintronic spin-neuron. It dissipates orders of magnitude less energy in threshold operations than the traditional current-driven spin neuron at 0 K temperature and may even be faster. We have also studied the room-temperature firing behaviors of both types of spin neurons and find that thermal noise degrades the performance of both types, but the current-driven type is degraded much more than the straintronic type if both are optimized for maximum energy-efficiency. On the other hand, if both are designed to have the same level of thermal degradation, then the current-driven version will dissipate orders of magnitude more energy than the straintronic version. Thus, the straintronic spin-neuron is superior to current-driven spin neurons. (paper)

  3. Artificial Intelligence

    CERN Document Server

    Warwick, Kevin

    2011-01-01

    if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory

  4. Artificial intelligence

    International Nuclear Information System (INIS)

    Perret-Galix, D.

    1992-01-01

    A vivid example of the growing need for frontier physics experiments to make use of frontier technology is in the field of artificial intelligence and related themes. This was reflected in the second international workshop on 'Software Engineering, Artificial Intelligence and Expert Systems in High Energy and Nuclear Physics' which took place from 13-18 January at France Telecom's Agelonde site at La Londe des Maures, Provence. It was the second in a series, the first having been held at Lyon in 1990

  5. Spiking Neurons for Analysis of Patterns

    Science.gov (United States)

    Huntsberger, Terrance

    2008-01-01

    Artificial neural networks comprising spiking neurons of a novel type have been conceived as improved pattern-analysis and pattern-recognition computational systems. These neurons are represented by a mathematical model denoted the state-variable model (SVM), which among other things, exploits a computational parallelism inherent in spiking-neuron geometry. Networks of SVM neurons offer advantages of speed and computational efficiency, relative to traditional artificial neural networks. The SVM also overcomes some of the limitations of prior spiking-neuron models. There are numerous potential pattern-recognition, tracking, and data-reduction (data preprocessing) applications for these SVM neural networks on Earth and in exploration of remote planets. Spiking neurons imitate biological neurons more closely than do the neurons of traditional artificial neural networks. A spiking neuron includes a central cell body (soma) surrounded by a tree-like interconnection network (dendrites). Spiking neurons are so named because they generate trains of output pulses (spikes) in response to inputs received from sensors or from other neurons. They gain their speed advantage over traditional neural networks by using the timing of individual spikes for computation, whereas traditional artificial neurons use averages of activity levels over time. Moreover, spiking neurons use the delays inherent in dendritic processing in order to efficiently encode the information content of incoming signals. Because traditional artificial neurons fail to capture this encoding, they have less processing capability, and so it is necessary to use more gates when implementing traditional artificial neurons in electronic circuitry. Such higher-order functions as dynamic tasking are effected by use of pools (collections) of spiking neurons interconnected by spike-transmitting fibers. The SVM includes adaptive thresholds and submodels of transport of ions (in imitation of such transport in biological

  6. Artificial Intelligence.

    Science.gov (United States)

    Wash, Darrel Patrick

    1989-01-01

    Making a machine seem intelligent is not easy. As a consequence, demand has been rising for computer professionals skilled in artificial intelligence and is likely to continue to go up. These workers develop expert systems and solve the mysteries of machine vision, natural language processing, and neural networks. (Editor)

  7. Doubly stochastic Poisson processes in artificial neural learning.

    Science.gov (United States)

    Card, H C

    1998-01-01

    This paper investigates neuron activation statistics in artificial neural networks employing stochastic arithmetic. It is shown that a doubly stochastic Poisson process is an appropriate model for the signals in these circuits.

  8. Artificial Consciousness or Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Spanache Florin

    2017-05-01

    Full Text Available Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus automatic. But conscience is above these differences because it is neither conditioned by the self-preservation of autonomy, because a conscience is something that you use to help your neighbor, nor automatic, because one’s conscience is tested by situations which are not similar or subject to routine. So, artificial intelligence is only in science-fiction literature similar to an autonomous conscience-endowed being. In real life, religion with its notions of redemption, sin, expiation, confession and communion will not have any meaning for a machine which cannot make a mistake on its own.

  9. Artificial Intelligence.

    Science.gov (United States)

    Lawrence, David R; Palacios-González, César; Harris, John

    2016-04-01

    It seems natural to think that the same prudential and ethical reasons for mutual respect and tolerance that one has vis-à-vis other human persons would hold toward newly encountered paradigmatic but nonhuman biological persons. One also tends to think that they would have similar reasons for treating we humans as creatures that count morally in our own right. This line of thought transcends biological boundaries-namely, with regard to artificially (super)intelligent persons-but is this a safe assumption? The issue concerns ultimate moral significance: the significance possessed by human persons, persons from other planets, and hypothetical nonorganic persons in the form of artificial intelligence (AI). This article investigates why our possible relations to AI persons could be more complicated than they first might appear, given that they might possess a radically different nature to us, to the point that civilized or peaceful coexistence in a determinate geographical space could be impossible to achieve.

  10. Artificial intelligence

    OpenAIRE

    Duda, Antonín

    2009-01-01

    Abstract : Issue of this work is to acquaint the reader with the history of artificial inteligence, esspecialy branch of chess computing. Main attention is given to progress from fifties to the present. The work also deals with fighting chess programs against each other, and against human opponents. The greatest attention is focused on 1997 and duel Garry Kasparov against chess program Deep Blue. The work is divided into chapters according to chronological order.

  11. Artificial heart

    Energy Technology Data Exchange (ETDEWEB)

    1984-10-18

    Super-pure plutonium-238 could use heat produced during fission to power an implanted artificial heart. Three model hearts have worked for some time. Concern that excess heat would make the procedure unsafe for humans has broadened the search for another energy source, such as electrohydraulic drive or an external power battery. A back pack approach may provide an interim solution until materials are developed which can withstand heart activity and be small enough for implantation.

  12. Artificial intelligence in hematology.

    Science.gov (United States)

    Zini, Gina

    2005-10-01

    Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.

  13. Motor Neurons

    DEFF Research Database (Denmark)

    Hounsgaard, Jorn

    2017-01-01

    Motor neurons translate synaptic input from widely distributed premotor networks into patterns of action potentials that orchestrate motor unit force and motor behavior. Intercalated between the CNS and muscles, motor neurons add to and adjust the final motor command. The identity and functional...... in in vitro preparations is far from complete. Nevertheless, a foundation has been provided for pursuing functional significance of intrinsic response properties in motoneurons in vivo during motor behavior at levels from molecules to systems....

  14. Artificial graphites

    International Nuclear Information System (INIS)

    Maire, J.

    1984-01-01

    Artificial graphites are obtained by agglomeration of carbon powders with an organic binder, then by carbonisation at 1000 0 C and graphitization at 2800 0 C. After description of the processes and products, we show how the properties of the various materials lead to the various uses. Using graphite enables us to solve some problems, but it is not sufficient to satisfy all the need of the application. New carbonaceous material open application range. Finally, if some products are becoming obsolete, other ones are being developed in new applications [fr

  15. [Mirror neurons].

    Science.gov (United States)

    Rubia Vila, Francisco José

    2011-01-01

    Mirror neurons were recently discovered in frontal brain areas of the monkey. They are activated when the animal makes a specific movement, but also when the animal observes the same movement in another animal. Some of them also respond to the emotional expression of other animals of the same species. These mirror neurons have also been found in humans. They respond to or "reflect" actions of other individuals in the brain and are thought to represent the basis for imitation and empathy and hence the neurobiological substrate for "theory of mind", the potential origin of language and the so-called moral instinct.

  16. Behavioral plasticity through the modulation of switch neurons.

    Science.gov (United States)

    Vassiliades, Vassilis; Christodoulou, Chris

    2016-02-01

    A central question in artificial intelligence is how to design agents capable of switching between different behaviors in response to environmental changes. Taking inspiration from neuroscience, we address this problem by utilizing artificial neural networks (NNs) as agent controllers, and mechanisms such as neuromodulation and synaptic gating. The novel aspect of this work is the introduction of a type of artificial neuron we call "switch neuron". A switch neuron regulates the flow of information in NNs by selectively gating all but one of its incoming synaptic connections, effectively allowing only one signal to propagate forward. The allowed connection is determined by the switch neuron's level of modulatory activation which is affected by modulatory signals, such as signals that encode some information about the reward received by the agent. An important aspect of the switch neuron is that it can be used in appropriate "switch modules" in order to modulate other switch neurons. As we show, the introduction of the switch modules enables the creation of sequences of gating events. This is achieved through the design of a modulatory pathway capable of exploring in a principled manner all permutations of the connections arriving on the switch neurons. We test the model by presenting appropriate architectures in nonstationary binary association problems and T-maze tasks. The results show that for all tasks, the switch neuron architectures generate optimal adaptive behaviors, providing evidence that the switch neuron model could be a valuable tool in simulations where behavioral plasticity is required. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Computational Models of Neuron-Astrocyte Interactions Lead to Improved Efficacy in the Performance of Neural Networks

    Science.gov (United States)

    Alvarellos-González, Alberto; Pazos, Alejandro; Porto-Pazos, Ana B.

    2012-01-01

    The importance of astrocytes, one part of the glial system, for information processing in the brain has recently been demonstrated. Regarding information processing in multilayer connectionist systems, it has been shown that systems which include artificial neurons and astrocytes (Artificial Neuron-Glia Networks) have well-known advantages over identical systems including only artificial neurons. Since the actual impact of astrocytes in neural network function is unknown, we have investigated, using computational models, different astrocyte-neuron interactions for information processing; different neuron-glia algorithms have been implemented for training and validation of multilayer Artificial Neuron-Glia Networks oriented toward classification problem resolution. The results of the tests performed suggest that all the algorithms modelling astrocyte-induced synaptic potentiation improved artificial neural network performance, but their efficacy depended on the complexity of the problem. PMID:22649480

  18. [Artificial intelligence in psychiatry-an overview].

    Science.gov (United States)

    Meyer-Lindenberg, A

    2018-06-18

    Artificial intelligence and the underlying methods of machine learning and neuronal networks (NN) have made dramatic progress in recent years and have allowed computers to reach superhuman performance in domains that used to be thought of as uniquely human. In this overview, the underlying methodological developments that made this possible are briefly delineated and then the applications to psychiatry in three domains are discussed: precision medicine and biomarkers, natural language processing and artificial intelligence-based psychotherapeutic interventions. In conclusion, some of the risks of this new technology are mentioned.

  19. Neurons other than motor neurons in motor neuron disease.

    Science.gov (United States)

    Ruffoli, Riccardo; Biagioni, Francesca; Busceti, Carla L; Gaglione, Anderson; Ryskalin, Larisa; Gambardella, Stefano; Frati, Alessandro; Fornai, Francesco

    2017-11-01

    Amyotrophic lateral sclerosis (ALS) is typically defined by a loss of motor neurons in the central nervous system. Accordingly, morphological analysis for decades considered motor neurons (in the cortex, brainstem and spinal cord) as the neuronal population selectively involved in ALS. Similarly, this was considered the pathological marker to score disease severity ex vivo both in patients and experimental models. However, the concept of non-autonomous motor neuron death was used recently to indicate the need for additional cell types to produce motor neuron death in ALS. This means that motor neuron loss occurs only when they are connected with other cell types. This concept originally emphasized the need for resident glia as well as non-resident inflammatory cells. Nowadays, the additional role of neurons other than motor neurons emerged in the scenario to induce non-autonomous motor neuron death. In fact, in ALS neurons diverse from motor neurons are involved. These cells play multiple roles in ALS: (i) they participate in the chain of events to produce motor neuron loss; (ii) they may even degenerate more than and before motor neurons. In the present manuscript evidence about multi-neuronal involvement in ALS patients and experimental models is discussed. Specific sub-classes of neurons in the whole spinal cord are reported either to degenerate or to trigger neuronal degeneration, thus portraying ALS as a whole spinal cord disorder rather than a disease affecting motor neurons solely. This is associated with a novel concept in motor neuron disease which recruits abnormal mechanisms of cell to cell communication.

  20. Integrated neuron circuit for implementing neuromorphic system with synaptic device

    Science.gov (United States)

    Lee, Jeong-Jun; Park, Jungjin; Kwon, Min-Woo; Hwang, Sungmin; Kim, Hyungjin; Park, Byung-Gook

    2018-02-01

    In this paper, we propose and fabricate Integrate & Fire neuron circuit for implementing neuromorphic system. Overall operation of the circuit is verified by measuring discrete devices and the output characteristics of the circuit. Since the neuron circuit shows asymmetric output characteristic that can drive synaptic device with Spike-Timing-Dependent-Plasticity (STDP) characteristic, the autonomous weight update process is also verified by connecting the synaptic device and the neuron circuit. The timing difference of the pre-neuron and the post-neuron induce autonomous weight change of the synaptic device. Unlike 2-terminal devices, which is frequently used to implement neuromorphic system, proposed scheme of the system enables autonomous weight update and simple configuration by using 4-terminal synapse device and appropriate neuron circuit. Weight update process in the multi-layer neuron-synapse connection ensures implementation of the hardware-based artificial intelligence, based on Spiking-Neural- Network (SNN).

  1. Modeling by artificial neural networks. Application to the management of fuel in a nuclear power plant; Modelisation par reseaux de neurones. Application a la gestion du combustible dans un reacteur

    Energy Technology Data Exchange (ETDEWEB)

    Gaudier, F

    1999-07-01

    The determination of the family of optimum core loading patterns for Pressurized Water Reactors (PWRs) involves the assessment of the core attributes, such as the power peaking factor for thousands of candidate loading patterns. Despite the rapid advances in computer architecture, the direct calculation of these attributes by a neutronic code needs a lot of of time and memory. With the goal of reducing the calculation time and optimizing the loading pattern, we propose in this thesis a method based on ideas of neural and statistical learning to provide a feed forward neural network capable of calculating the power peaking corresponding to an eighth core PWR. We use statistical methods to deduct judicious inputs (reduction of the input space dimension) and neural methods to train the model (learning capabilities). Indeed, on one hand, a principal component analysis allows us to characterize more efficiently the fuel assemblies (neural model inputs) and the other hand, the introduction of the a priori knowledge allows us to reducing the number of freedom parameters in the neural network. The model was built using a multi layered perceptron trained with the standard back propagation algorithm. We introduced our neural network in the automatic optimization code FORMOSA, and on EDF real problems we showed an important saving in time. Finally, we propose an hybrid method which combining the best characteristics of the linear local approximator GPT (Generalized Perturbation Theory) and the artificial neural network. (author)

  2. A neuron-astrocyte transistor-like model for neuromorphic dressed neurons.

    Science.gov (United States)

    Valenza, G; Pioggia, G; Armato, A; Ferro, M; Scilingo, E P; De Rossi, D

    2011-09-01

    Experimental evidences on the role of the synaptic glia as an active partner together with the bold synapse in neuronal signaling and dynamics of neural tissue strongly suggest to investigate on a more realistic neuron-glia model for better understanding human brain processing. Among the glial cells, the astrocytes play a crucial role in the tripartite synapsis, i.e. the dressed neuron. A well-known two-way astrocyte-neuron interaction can be found in the literature, completely revising the purely supportive role for the glia. The aim of this study is to provide a computationally efficient model for neuron-glia interaction. The neuron-glia interactions were simulated by implementing the Li-Rinzel model for an astrocyte and the Izhikevich model for a neuron. Assuming the dressed neuron dynamics similar to the nonlinear input-output characteristics of a bipolar junction transistor, we derived our computationally efficient model. This model may represent the fundamental computational unit for the development of real-time artificial neuron-glia networks opening new perspectives in pattern recognition systems and in brain neurophysiology. Copyright © 2011 Elsevier Ltd. All rights reserved.

  3. Artificial Hydration and Nutrition

    Science.gov (United States)

    ... Crisis Situations Pets and Animals myhealthfinder Food and Nutrition Healthy Food Choices Weight Loss and Diet Plans ... Your Health Resources Healthcare Management Artificial Hydration and Nutrition Artificial Hydration and Nutrition Share Print Patients who ...

  4. Artificial Disc Replacement

    Science.gov (United States)

    ... Spondylolisthesis BLOG FIND A SPECIALIST Treatments Artificial Disc Replacement (ADR) Patient Education Committee Jamie Baisden The disc ... Disc An artificial disc (also called a disc replacement, disc prosthesis or spine arthroplasty device) is a ...

  5. Application of artificial intelligence to the management of urological cancer.

    Science.gov (United States)

    Abbod, Maysam F; Catto, James W F; Linkens, Derek A; Hamdy, Freddie C

    2007-10-01

    Artificial intelligence techniques, such as artificial neural networks, Bayesian belief networks and neuro-fuzzy modeling systems, are complex mathematical models based on the human neuronal structure and thinking. Such tools are capable of generating data driven models of biological systems without making assumptions based on statistical distributions. A large amount of study has been reported of the use of artificial intelligence in urology. We reviewed the basic concepts behind artificial intelligence techniques and explored the applications of this new dynamic technology in various aspects of urological cancer management. A detailed and systematic review of the literature was performed using the MEDLINE and Inspec databases to discover reports using artificial intelligence in urological cancer. The characteristics of machine learning and their implementation were described and reports of artificial intelligence use in urological cancer were reviewed. While most researchers in this field were found to focus on artificial neural networks to improve the diagnosis, staging and prognostic prediction of urological cancers, some groups are exploring other techniques, such as expert systems and neuro-fuzzy modeling systems. Compared to traditional regression statistics artificial intelligence methods appear to be accurate and more explorative for analyzing large data cohorts. Furthermore, they allow individualized prediction of disease behavior. Each artificial intelligence method has characteristics that make it suitable for different tasks. The lack of transparency of artificial neural networks hinders global scientific community acceptance of this method but this can be overcome by neuro-fuzzy modeling systems.

  6. Spin orbit torque based electronic neuron

    Energy Technology Data Exchange (ETDEWEB)

    Sengupta, Abhronil, E-mail: asengup@purdue.edu; Choday, Sri Harsha; Kim, Yusung; Roy, Kaushik [School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907 (United States)

    2015-04-06

    A device based on current-induced spin-orbit torque (SOT) that functions as an electronic neuron is proposed in this work. The SOT device implements an artificial neuron's thresholding (transfer) function. In the first step of a two-step switching scheme, a charge current places the magnetization of a nano-magnet along the hard-axis, i.e., an unstable point for the magnet. In the second step, the SOT device (neuron) receives a current (from the synapses) which moves the magnetization from the unstable point to one of the two stable states. The polarity of the synaptic current encodes the excitatory and inhibitory nature of the neuron input and determines the final orientation of the magnetization. A resistive crossbar array, functioning as synapses, generates a bipolar current that is a weighted sum of the inputs. The simulation of a two layer feed-forward artificial neural network based on the SOT electronic neuron shows that it consumes ∼3× lower power than a 45 nm digital CMOS implementation, while reaching ∼80% accuracy in the classification of 100 images of handwritten digits from the MNIST dataset.

  7. Spin orbit torque based electronic neuron

    International Nuclear Information System (INIS)

    Sengupta, Abhronil; Choday, Sri Harsha; Kim, Yusung; Roy, Kaushik

    2015-01-01

    A device based on current-induced spin-orbit torque (SOT) that functions as an electronic neuron is proposed in this work. The SOT device implements an artificial neuron's thresholding (transfer) function. In the first step of a two-step switching scheme, a charge current places the magnetization of a nano-magnet along the hard-axis, i.e., an unstable point for the magnet. In the second step, the SOT device (neuron) receives a current (from the synapses) which moves the magnetization from the unstable point to one of the two stable states. The polarity of the synaptic current encodes the excitatory and inhibitory nature of the neuron input and determines the final orientation of the magnetization. A resistive crossbar array, functioning as synapses, generates a bipolar current that is a weighted sum of the inputs. The simulation of a two layer feed-forward artificial neural network based on the SOT electronic neuron shows that it consumes ∼3× lower power than a 45 nm digital CMOS implementation, while reaching ∼80% accuracy in the classification of 100 images of handwritten digits from the MNIST dataset

  8. Artificial life and Piaget.

    Science.gov (United States)

    Mueller, Ulrich; Grobman, K H.

    2003-04-01

    Artificial life provides important theoretical and methodological tools for the investigation of Piaget's developmental theory. This new method uses artificial neural networks to simulate living phenomena in a computer. A recent study by Parisi and Schlesinger suggests that artificial life might reinvigorate the Piagetian framework. We contrast artificial life with traditional cognitivist approaches, discuss the role of innateness in development, and examine the relation between physiological and psychological explanations of intelligent behaviour.

  9. Study of the thermo-mechanical behavior of medium carbon microalloyed steel during hot forming process using an artificial neural network; Estudio del comportamiento termo-mecanico de un acero microaleado de medio carbono durante un proceso de conformado en caliente usando una red neuronal artificial

    Energy Technology Data Exchange (ETDEWEB)

    Alcelay, I.; Pena, E.; Al Omar, A.

    2016-10-01

    The thermo-mechanical behavior of medium carbon microalloyed steel has been analyzed by an Artificial Neural Network (ANN). The flow curves for training the ANN have been obtained from the hot compression tests, carried out over a temperature range varying from 900 to 1150 degree centigrade and at different true strain rates ranging from 10{sup -}4 to 10 s{sup -}1. It has been found that the ANN model developed in this study is capable to predict accurately and efficiently the flow behavior of the studied steel and there is a good agreement between the experimental results and the ANN results. To analyze the formability of the studied steel, processing maps have been constructed on the basis of the Dynamic Materials Model (DMM), using the ANN values of the flow stress. The study of maps reveals the different domains of the flow behavior of the studied steel and shows the great similarity between the experimental results and the theoretical results, so the use of the ANN can constitute an interesting alternative for design and study of hot forming processes. (Author)

  10. Building functional networks of spiking model neurons.

    Science.gov (United States)

    Abbott, L F; DePasquale, Brian; Memmesheimer, Raoul-Martin

    2016-03-01

    Most of the networks used by computer scientists and many of those studied by modelers in neuroscience represent unit activities as continuous variables. Neurons, however, communicate primarily through discontinuous spiking. We review methods for transferring our ability to construct interesting networks that perform relevant tasks from the artificial continuous domain to more realistic spiking network models. These methods raise a number of issues that warrant further theoretical and experimental study.

  11. An experimental biomimetic platform for artificial olfaction.

    Directory of Open Access Journals (Sweden)

    Corrado Di Natale

    Full Text Available Artificial olfactory systems have been studied for the last two decades mainly from the point of view of the features of olfactory neuron receptor fields. Other fundamental olfaction properties have only been episodically considered in artificial systems. As a result, current artificial olfactory systems are mostly intended as instruments and are of poor benefit for biologists who may need tools to model and test olfactory models. Herewith, we show how a simple experimental approach can be used to account for several phenomena observed in olfaction. An artificial epithelium is formed as a disordered distributed layer of broadly selective color indicators dispersed in a transparent polymer layer. The whole epithelium is probed with colored light, imaged with a digital camera and the olfactory response upon exposure to an odor is the change of the multispectral image. The pixels are treated as olfactory receptor neurons, whose optical properties are used to build a convergence classifier into a number of mathematically defined artificial glomeruli. A non-homogenous exposure of the test structure to the odours gives rise to a time and spatial dependence of the response of the different glomeruli strikingly similar to patterns observed in the olfactory bulb. The model seems to mimic both the formation of glomeruli, the zonal nature of olfactory epithelium, and the spatio-temporal signal patterns at the glomeruli level. This platform is able to provide a readily available test vehicle for chemists developing optical indicators for chemical sensing purposes and for biologists to test models of olfactory system organization.

  12. Applications of artificial intelligence technology to wastewater treatment fields in China

    Institute of Scientific and Technical Information of China (English)

    QING Xiao-xia; WANG Bo; MENG De-tao

    2005-01-01

    Current applications of artificial intelligence technology to wastewater treatment in China are summarized. Wastewater treatment plants use expert system mainly in the operation decision-making and fault diagnosis of system operation, use artificial neuron network for system modeling, water quality forecast and soft measure, and use fuzzy control technology for the intelligence control of wastewater treatment process. Finally, the main problems in applying artificial intelligence technology to wastewater treatment in China are analyzed.

  13. Artificial cognition architectures

    CERN Document Server

    Crowder, James A; Friess, Shelli A

    2013-01-01

    The goal of this book is to establish the foundation, principles, theory, and concepts that are the backbone of real, autonomous Artificial Intelligence. Presented here are some basic human intelligence concepts framed for Artificial Intelligence systems. These include concepts like Metacognition and Metamemory, along with architectural constructs for Artificial Intelligence versions of human brain functions like the prefrontal cortex. Also presented are possible hardware and software architectures that lend themselves to learning, reasoning, and self-evolution

  14. Artificial Intelligence Study (AIS).

    Science.gov (United States)

    1987-02-01

    ARTIFICIAL INTELLIGNECE HARDWARE ....... 2-50 AI Architecture ................................... 2-49 AI Hardware ....................................... 2...ftf1 829 ARTIFICIAL INTELLIGENCE STUDY (RIS)(U) MAY CONCEPTS 1/3 A~NLYSIS AGENCY BETHESA RD R B NOJESKI FED 6? CM-RP-97-1 NCASIFIED /01/6 M |K 1.0...p/ - - ., e -- CAA- RP- 87-1 SAOFŔ)11 I ARTIFICIAL INTELLIGENCE STUDY (AIS) tNo DTICFEBRUARY 1987 LECT 00 I PREPARED BY RESEARCH AND ANALYSIS

  15. Artificial Intelligence in Astronomy

    Science.gov (United States)

    Devinney, E. J.; Prša, A.; Guinan, E. F.; Degeorge, M.

    2010-12-01

    From the perspective (and bias) as Eclipsing Binary researchers, we give a brief overview of the development of Artificial Intelligence (AI) applications, describe major application areas of AI in astronomy, and illustrate the power of an AI approach in an application developed under the EBAI (Eclipsing Binaries via Artificial Intelligence) project, which employs Artificial Neural Network technology for estimating light curve solution parameters of eclipsing binary systems.

  16. Quo Vadis, Artificial Intelligence?

    OpenAIRE

    Berrar, Daniel; Sato, Naoyuki; Schuster, Alfons

    2010-01-01

    Since its conception in the mid 1950s, artificial intelligence with its great ambition to understand and emulate intelligence in natural and artificial environments alike is now a truly multidisciplinary field that reaches out and is inspired by a great diversity of other fields. Rapid advances in research and technology in various fields have created environments into which artificial intelligence could embed itself naturally and comfortably. Neuroscience with its desire to understand nervou...

  17. Inteligencia artificial en vehiculo

    OpenAIRE

    Amador Díaz, Pedro

    2012-01-01

    Desarrollo de un robot seguidor de líneas, en el que se implementan diversas soluciones de las áreas de sistemas embebidos e inteligencia artificial. Desenvolupament d'un robot seguidor de línies, en el qual s'implementen diverses solucions de les àrees de sistemes encastats i intel·ligència artificial. Follower robot development of lines, in which various solutions are implemented in the areas of artificial intelligence embedded systems.

  18. STANFORD ARTIFICIAL INTELLIGENCE PROJECT.

    Science.gov (United States)

    ARTIFICIAL INTELLIGENCE , GAME THEORY, DECISION MAKING, BIONICS, AUTOMATA, SPEECH RECOGNITION, GEOMETRIC FORMS, LEARNING MACHINES, MATHEMATICAL MODELS, PATTERN RECOGNITION, SERVOMECHANISMS, SIMULATION, BIBLIOGRAPHIES.

  19. Artificial life and life artificialization in Tron

    Directory of Open Access Journals (Sweden)

    Carolina Dantas Figueiredo

    2012-12-01

    Full Text Available Cinema constantly shows the struggle between the men and artificial intelligences. Fiction, and more specifically fiction films, lends itself to explore possibilities asking “what if?”. “What if”, in this case, is related to the eventual rebellion of artificial intelligences, theme explored in the movies Tron (1982 and Tron Legacy (2010 trat portray the conflict between programs and users. The present paper examines these films, observing particularly the possibility programs empowering. Finally, is briefly mentioned the concept of cyborg as a possibility of response to human concerns.

  20. Dynamic artificial neural networks with affective systems.

    Directory of Open Access Journals (Sweden)

    Catherine D Schuman

    Full Text Available Artificial neural networks (ANNs are processors that are trained to perform particular tasks. We couple a computational ANN with a simulated affective system in order to explore the interaction between the two. In particular, we design a simple affective system that adjusts the threshold values in the neurons of our ANN. The aim of this paper is to demonstrate that this simple affective system can control the firing rate of the ensemble of neurons in the ANN, as well as to explore the coupling between the affective system and the processes of long term potentiation (LTP and long term depression (LTD, and the effect of the parameters of the affective system on its performance. We apply our networks with affective systems to a simple pole balancing example and briefly discuss the effect of affective systems on network performance.

  1. Neuronal Migration Disorders

    Science.gov (United States)

    ... Understanding Sleep The Life and Death of a Neuron Genes At Work In The Brain Order Publications ... birth defects caused by the abnormal migration of neurons in the developing brain and nervous system. In ...

  2. Motor Neuron Diseases

    Science.gov (United States)

    ... and other neurodegenerative diseases to better understand the function of neurons and other support cells and identify candidate therapeutic ... and other neurodegenerative diseases to better understand the function of neurons and other support cells and identify candidate therapeutic ...

  3. [Total artificial heart].

    Science.gov (United States)

    Antretter, H; Dumfarth, J; Höfer, D

    2015-09-01

    To date the CardioWest™ total artificial heart is the only clinically available implantable biventricular mechanical replacement for irreversible cardiac failure. This article presents the indications, contraindications, implantation procedere and postoperative treatment. In addition to a overview of the applications of the total artificial heart this article gives a brief presentation of the two patients treated in our department with the CardioWest™. The clinical course, postoperative rehabilitation, device-related complications and control mechanisms are presented. The total artificial heart is a reliable implant for treating critically ill patients with irreversible cardiogenic shock. A bridge to transplantation is feasible with excellent results.

  4. Signals and Circuits in the Purkinje Neuron

    Directory of Open Access Journals (Sweden)

    Ze'ev R Abrams

    2011-09-01

    Full Text Available Purkinje neurons 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 Purkinje neuron 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 Purkinje neuron and define 3 unique frequency ranges associated with the cells’ output. Comparing the Purkinje neuron 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 Purkinje neuron can act as a multivibrator circuit.

  5. Bibliography: Artificial Intelligence.

    Science.gov (United States)

    Smith, Richard L.

    1986-01-01

    Annotates reference material on artificial intelligence, mostly at an introductory level, with applications to education and learning. Topics include: (1) programing languages; (2) expert systems; (3) language instruction; (4) tutoring systems; and (5) problem solving and reasoning. (JM)

  6. Artificial intelligence in medicine.

    OpenAIRE

    Ramesh, A. N.; Kambhampati, C.; Monson, J. R. T.; Drew, P. J.

    2004-01-01

    INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of ...

  7. Minimally Naturalistic Artificial Intelligence

    OpenAIRE

    Hansen, Steven Stenberg

    2017-01-01

    The rapid advancement of machine learning techniques has re-energized research into general artificial intelligence. While the idea of domain-agnostic meta-learning is appealing, this emerging field must come to terms with its relationship to human cognition and the statistics and structure of the tasks humans perform. The position of this article is that only by aligning our agents' abilities and environments with those of humans do we stand a chance at developing general artificial intellig...

  8. Artificial Intelligence Project

    Science.gov (United States)

    1990-01-01

    Symposium on Aritificial Intelligence and Software Engineering Working Notes, March 1989. Blumenthal, Brad, "An Architecture for Automating...Artificial Intelligence Project Final Technical Report ARO Contract: DAAG29-84-K-OGO Artificial Intelligence LaboratO"ry The University of Texas at...Austin N>.. ~ ~ JA 1/I 1991 n~~~ Austin, Texas 78712 ________k A,.tificial Intelligence Project i Final Technical Report ARO Contract: DAAG29-84-K-0060

  9. Artificial intelligence in cardiology

    OpenAIRE

    Bonderman, Diana

    2017-01-01

    Summary Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiol...

  10. Principles of artificial intelligence

    CERN Document Server

    Nilsson, Nils J

    1980-01-01

    A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of th

  11. Intelligence: Real or artificial?

    OpenAIRE

    Schlinger, Henry D.

    1992-01-01

    Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally r...

  12. Training Spiking Neural Models Using Artificial Bee Colony

    Science.gov (United States)

    Vazquez, Roberto A.; Garro, Beatriz A.

    2015-01-01

    Spiking neurons are models designed to simulate, in a realistic manner, the behavior of biological neurons. Recently, it has been proven that this type of neurons can be applied to solve pattern recognition problems with great efficiency. However, the lack of learning strategies for training these models do not allow to use them in several pattern recognition problems. On the other hand, several bioinspired algorithms have been proposed in the last years for solving a broad range of optimization problems, including those related to the field of artificial neural networks (ANNs). Artificial bee colony (ABC) is a novel algorithm based on the behavior of bees in the task of exploring their environment to find a food source. In this paper, we describe how the ABC algorithm can be used as a learning strategy to train a spiking neuron aiming to solve pattern recognition problems. Finally, the proposed approach is tested on several pattern recognition problems. It is important to remark that to realize the powerfulness of this type of model only one neuron will be used. In addition, we analyze how the performance of these models is improved using this kind of learning strategy. PMID:25709644

  13. Modeling the Development of Goal-Specificity in Mirror Neurons.

    Science.gov (United States)

    Thill, Serge; Svensson, Henrik; Ziemke, Tom

    2011-12-01

    Neurophysiological studies have shown that parietal mirror neurons encode not only actions but also the goal of these actions. Although some mirror neurons will fire whenever a certain action is perceived (goal-independently), most will only fire if the motion is perceived as part of an action with a specific goal. This result is important for the action-understanding hypothesis as it provides a potential neurological basis for such a cognitive ability. It is also relevant for the design of artificial cognitive systems, in particular robotic systems that rely on computational models of the mirror system in their interaction with other agents. Yet, to date, no computational model has explicitly addressed the mechanisms that give rise to both goal-specific and goal-independent parietal mirror neurons. In the present paper, we present a computational model based on a self-organizing map, which receives artificial inputs representing information about both the observed or executed actions and the context in which they were executed. We show that the map develops a biologically plausible organization in which goal-specific mirror neurons emerge. We further show that the fundamental cause for both the appearance and the number of goal-specific neurons can be found in geometric relationships between the different inputs to the map. The results are important to the action-understanding hypothesis as they provide a mechanism for the emergence of goal-specific parietal mirror neurons and lead to a number of predictions: (1) Learning of new goals may mostly reassign existing goal-specific neurons rather than recruit new ones; (2) input differences between executed and observed actions can explain observed corresponding differences in the number of goal-specific neurons; and (3) the percentage of goal-specific neurons may differ between motion primitives.

  14. Encoding of natural and artificial stimuli in the auditory midbrain

    Science.gov (United States)

    Lyzwa, Dominika

    How complex acoustic stimuli are encoded in the main center of convergence in the auditory midbrain is not clear. Here, the representation of neural spiking responses to natural and artificial sounds across this subcortical structure is investigated based on neurophysiological recordings from the mammalian midbrain. Neural and stimulus correlations of neuronal pairs are analyzed with respect to the neurons' distance, and responses to different natural communication sounds are discriminated. A model which includes linear and nonlinear neural response properties of this nucleus is presented and employed to predict temporal spiking responses to new sounds. Supported by BMBF Grant 01GQ0811.

  15. Microfluidic Neurons, a New Way in Neuromorphic Engineering?

    Directory of Open Access Journals (Sweden)

    Timothée Levi

    2016-08-01

    Full Text Available This article describes a new way to explore neuromorphic engineering, the biomimetic artificial neuron using microfluidic techniques. This new device could replace silicon neurons and solve the issues of biocompatibility and power consumption. The biological neuron transmits electrical signals based on ion flow through their plasma membrane. Action potentials are propagated along axons and represent the fundamental electrical signals by which information are transmitted from one place to another in the nervous system. Based on this physiological behavior, we propose a microfluidic structure composed of chambers representing the intra and extracellular environments, connected by channels actuated by Quake valves. These channels are equipped with selective ion permeable membranes to mimic the exchange of chemical species found in the biological neuron. A thick polydimethylsiloxane (PDMS membrane is used to create the Quake valve membrane. Integrated electrodes are used to measure the potential difference between the intracellular and extracellular environments: the membrane potential.

  16. Artificial intelligence in nanotechnology.

    Science.gov (United States)

    Sacha, G M; Varona, P

    2013-11-15

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

  17. Artificial organ engineering

    CERN Document Server

    Annesini, Maria Cristina; Piemonte, Vincenzo; Turchetti, Luca

    2017-01-01

    Artificial organs may be considered as small-scale process plants, in which heat, mass and momentum transfer operations and, possibly, chemical transformations are carried out. This book proposes a novel analysis of artificial organs based on the typical bottom-up approach used in process engineering. Starting from a description of the fundamental physico-chemical phenomena involved in the process, the whole system is rebuilt as an interconnected ensemble of elemental unit operations. Each artificial organ is presented with a short introduction provided by expert clinicians. Devices commonly used in clinical practice are reviewed and their performance is assessed and compared by using a mathematical model based approach. Whilst mathematical modelling is a fundamental tool for quantitative descriptions of clinical devices, models are kept simple to remain focused on the essential features of each process. Postgraduate students and researchers in the field of chemical and biomedical engineering will find that t...

  18. Artificial intelligence in nanotechnology

    Science.gov (United States)

    Sacha, G. M.; Varona, P.

    2013-11-01

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

  19. Artificial organs and transplantation.

    Science.gov (United States)

    Splendiani, G; Cipriani, S; Vega, A; Casciani, C U

    2003-05-01

    Nowadays artificial devices are not able to totally and undefinitely replace the loss of function of all vital organs and artificial organs can be used only to bridge the time to transplantation, which must be considered the first choice in the therapeutical approach for many chronic diseases. Since general population aging process is leading to an increase of organ demand, the gap between performed and requested transplantation is hard to fill. Xenotransplantation is nowadays only an experimental alternative solution and we have to do our best using available artificial organs to increase and improve the survival of patients waiting for transplantation. In this meeting we particularly dealt about organ function replacing therapy, especially regarding the kidney, heart, liver, pancreas and ear.

  20. Charlas sobre inteligencia artificial

    OpenAIRE

    Álvarez Sánchez, José Ramón; Ferrández Vicente, José Manuel; Paz López, Félix de la

    2014-01-01

    Serie: Informática en Radio 3 La Inteligencia Artificial es una de las ciencias que causa mayor impacto en la sociedad, mucho más si tenemos en cuenta que cambiará el futuro de la humanidad. En España existen actualmente un nutrido grupo de equipos de investigación relacionados con las tecnologías de computación natural-artificial que aúnan sus esfuerzos a través de la RTNAC la Red Temática en Tecnologías de Computación Natural-Artificial . La UNED participa en todas sus actividades desde ...

  1. Artificial Intelligence in Cardiology.

    Science.gov (United States)

    Johnson, Kipp W; Torres Soto, Jessica; Glicksberg, Benjamin S; Shameer, Khader; Miotto, Riccardo; Ali, Mohsin; Ashley, Euan; Dudley, Joel T

    2018-06-12

    Artificial intelligence and machine learning are poised to influence nearly every aspect of the human condition, and cardiology is not an exception to this trend. This paper provides a guide for clinicians on relevant aspects of artificial intelligence and machine learning, reviews selected applications of these methods in cardiology to date, and identifies how cardiovascular medicine could incorporate artificial intelligence in the future. In particular, the paper first reviews predictive modeling concepts relevant to cardiology such as feature selection and frequent pitfalls such as improper dichotomization. Second, it discusses common algorithms used in supervised learning and reviews selected applications in cardiology and related disciplines. Third, it describes the advent of deep learning and related methods collectively called unsupervised learning, provides contextual examples both in general medicine and in cardiovascular medicine, and then explains how these methods could be applied to enable precision cardiology and improve patient outcomes. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  2. Artificial intelligence in nanotechnology

    International Nuclear Information System (INIS)

    Sacha, G M; Varona, P

    2013-01-01

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines. (topical review)

  3. Artificial intelligence executive summary

    International Nuclear Information System (INIS)

    Wamsley, S.J.; Purvis, E.E. III

    1984-01-01

    Artificial intelligence (AI) is a high technology field that can be used to provide problem solving diagnosis, guidance and for support resolution of problems. It is not a stand alone discipline, but can also be applied to develop data bases for retention of the expertise that is required for its own knowledge base. This provides a way to retain knowledge that otherwise may be lost. Artificial Intelligence Methodology can provide an automated construction management decision support system, thereby restoring the manager's emphasis to project management

  4. Artificial intelligence in cardiology.

    Science.gov (United States)

    Bonderman, Diana

    2017-12-01

    Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiology are reviewed. The text also touches on the ethical issues and speculates on the future roles of automated algorithms versus clinicians in cardiology and medicine in general.

  5. Spatially Resolved Artificial Chemistry

    DEFF Research Database (Denmark)

    Fellermann, Harold

    2009-01-01

    Although spatial structures can play a crucial role in chemical systems and can drastically alter the outcome of reactions, the traditional framework of artificial chemistry is a well-stirred tank reactor with no spatial representation in mind. Advanced method development in physical chemistry has...... made a class of models accessible to the realms of artificial chemistry that represent reacting molecules in a coarse-grained fashion in continuous space. This chapter introduces the mathematical models of Brownian dynamics (BD) and dissipative particle dynamics (DPD) for molecular motion and reaction...

  6. Bayesian artificial intelligence

    CERN Document Server

    Korb, Kevin B

    2003-01-01

    As the power of Bayesian techniques has become more fully realized, the field of artificial intelligence has embraced Bayesian methodology and integrated it to the point where an introduction to Bayesian techniques is now a core course in many computer science programs. Unlike other books on the subject, Bayesian Artificial Intelligence keeps mathematical detail to a minimum and covers a broad range of topics. The authors integrate all of Bayesian net technology and learning Bayesian net technology and apply them both to knowledge engineering. They emphasize understanding and intuition but also provide the algorithms and technical background needed for applications. Software, exercises, and solutions are available on the authors' website.

  7. Spatially Resolved Artificial Chemistry

    DEFF Research Database (Denmark)

    Fellermann, Harold

    2009-01-01

    made a class of models accessible to the realms of artificial chemistry that represent reacting molecules in a coarse-grained fashion in continuous space. This chapter introduces the mathematical models of Brownian dynamics (BD) and dissipative particle dynamics (DPD) for molecular motion and reaction......Although spatial structures can play a crucial role in chemical systems and can drastically alter the outcome of reactions, the traditional framework of artificial chemistry is a well-stirred tank reactor with no spatial representation in mind. Advanced method development in physical chemistry has...

  8. Kappe neurons, a novel population of olfactory sensory neurons

    OpenAIRE

    Ahuja, Gaurav; Nia, Shahrzad Bozorg; Zapilko, Veronika; Shiriagin, Vladimir; Kowatschew, Daniel; Oka, Yuichiro; Korsching, Sigrun I.

    2014-01-01

    Perception of olfactory stimuli is mediated by distinct populations of olfactory sensory neurons, each with a characteristic set of morphological as well as functional parameters. Beyond two large populations of ciliated and microvillous neurons, a third population, crypt neurons, has been identified in teleost and cartilaginous fishes. We report here a novel, fourth olfactory sensory neuron population in zebrafish, which we named kappe neurons for their characteristic shape. Kappe neurons ar...

  9. Prediction of Availability Indicator of Water Pipes Using Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Kutyłowska Małgorzata

    2017-01-01

    Full Text Available The paper presents the results of artificial neural networks application to the availability indicator prediction. The forecasted results indicate that artificial networks may be used to model the reliability level of the water supply systems. The network was trained using 147 and 173 operational data from one Polish medium-sized city (distribution pipes and house connections, respectively. 50% of all data was chosen for learning, 25% for testing and 25% for validation. In prognosis phase, the best created network used 100% of 114 and 133 values for testing. Following functions were used to activate neurons in hidden and output layers: linear, logistic, hyperbolic tangent, exponential. The learning of the artificial network was performed using following input parameters: material, total length, diameter. In the optimal models hyperbolic tangent was chosen to activate the hidden and output neurons in modeling the availability indicator of house connections during 68 epochs of training. Hidden and output neurons were activated (20 epochs of learning respectively by hyperbolic tangent and linear function during the prediction of availability indicator of distribution pipes. The maximum relative errors in learning and prognosis step were equal to 0.10% and 1.20% as well as 0.27% and 1.15% for distribution pipes and house connections, respectively.

  10. NEURON and Python.

    Science.gov (United States)

    Hines, Michael L; Davison, Andrew P; Muller, Eilif

    2009-01-01

    The NEURON simulation program now allows Python to be used, alone or in combination with NEURON's traditional Hoc interpreter. Adding Python to NEURON has the immediate benefit of making available a very extensive suite of analysis tools written for engineering and science. It also catalyzes NEURON software development by offering users a modern programming tool that is recognized for its flexibility and power to create and maintain complex programs. At the same time, nothing is lost because all existing models written in Hoc, including graphical user interface tools, continue to work without change and are also available within the Python context. An example of the benefits of Python availability is the use of the xml module in implementing NEURON's Import3D and CellBuild tools to read MorphML and NeuroML model specifications.

  11. Generality in Artificial Intelligence

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 19; Issue 3. Generality in Artificial Intelligence. John McCarthy. Classics Volume 19 Issue 3 March 2014 pp 283-296. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/019/03/0283-0296. Author Affiliations.

  12. Artificial molecular motors

    NARCIS (Netherlands)

    Kassem, Salma; van Leeuwen, Thomas; Lubbe, Anouk S.; Wilson, Miriam R.; Feringa, Ben L.; Leigh, David A.

    2017-01-01

    Motor proteins are nature's solution for directing movement at the molecular level. The field of artificial molecular motors takes inspiration from these tiny but powerful machines. Although directional motion on the nanoscale performed by synthetic molecular machines is a relatively new

  13. Artificial intelligence within AFSC

    Science.gov (United States)

    Gersh, Mark A.

    1990-01-01

    Information on artificial intelligence research in the Air Force Systems Command is given in viewgraph form. Specific research that is being conducted at the Rome Air Development Center, the Space Technology Center, the Human Resources Laboratory, the Armstrong Aerospace Medical Research Laboratory, the Armamant Laboratory, and the Wright Research and Development Center is noted.

  14. Database in Artificial Intelligence.

    Science.gov (United States)

    Wilkinson, Julia

    1986-01-01

    Describes a specialist bibliographic database of literature in the field of artificial intelligence created by the Turing Institute (Glasgow, Scotland) using the BRS/Search information retrieval software. The subscription method for end-users--i.e., annual fee entitles user to unlimited access to database, document provision, and printed awareness…

  15. Spinal cord: motor neuron diseases.

    Science.gov (United States)

    Rezania, Kourosh; Roos, Raymond P

    2013-02-01

    Spinal cord motor neuron diseases affect lower motor neurons in the ventral horn. This article focuses on the most common spinal cord motor neuron disease, amyotrophic lateral sclerosis, which also affects upper motor neurons. Also discussed are other motor neuron diseases that only affect the lower motor neurons. Despite the identification of several genes associated with familial amyotrophic lateral sclerosis, the pathogenesis of this complex disease remains elusive. Copyright © 2013 Elsevier Inc. All rights reserved.

  16. Artificial skin and patient simulator comprising the artificial skin

    NARCIS (Netherlands)

    2011-01-01

    The invention relates to an artificial skin (10, 12, 14), and relates to a patient simulator (100) comprising the artificial skin. The artificial skin is a layered structure comprising a translucent cover layer (20) configured for imitating human or animal skin, and comprising a light emitting layer

  17. [Hardware Implementation of Numerical Simulation Function of Hodgkin-Huxley Model Neurons Action Potential Based on Field Programmable Gate Array].

    Science.gov (United States)

    Wang, Jinlong; Lu, Mai; Hu, Yanwen; Chen, Xiaoqiang; Pan, Qiangqiang

    2015-12-01

    Neuron is the basic unit of the biological neural system. The Hodgkin-Huxley (HH) model is one of the most realistic neuron models on the electrophysiological characteristic description of neuron. Hardware implementation of neuron could provide new research ideas to clinical treatment of spinal cord injury, bionics and artificial intelligence. Based on the HH model neuron and the DSP Builder technology, in the present study, a single HH model neuron hardware implementation was completed in Field Programmable Gate Array (FPGA). The neuron implemented in FPGA was stimulated by different types of current, the action potential response characteristics were analyzed, and the correlation coefficient between numerical simulation result and hardware implementation result were calculated. The results showed that neuronal action potential response of FPGA was highly consistent with numerical simulation result. This work lays the foundation for hardware implementation of neural network.

  18. A Subset of Serotonergic Neurons Evokes Hunger in Adult Drosophila.

    Science.gov (United States)

    Albin, Stephanie D; Kaun, Karla R; Knapp, Jon-Michael; Chung, Phuong; Heberlein, Ulrike; Simpson, Julie H

    2015-09-21

    Hunger is a complex motivational state that drives multiple behaviors. The sensation of hunger is caused by an imbalance between energy intake and expenditure. One immediate response to hunger is increased food consumption. Hunger also modulates behaviors related to food seeking such as increased locomotion and enhanced sensory sensitivity in both insects and vertebrates. In addition, hunger can promote the expression of food-associated memory. Although progress is being made, how hunger is represented in the brain and how it coordinates these behavioral responses is not fully understood in any system. Here, we use Drosophila melanogaster to identify neurons encoding hunger. We found a small group of neurons that, when activated, induced a fed fly to eat as though it were starved, suggesting that these neurons are downstream of the metabolic regulation of hunger. Artificially activating these neurons also promotes appetitive memory performance in sated flies, indicating that these neurons are not simply feeding command neurons but likely play a more general role in encoding hunger. We determined that the neurons relevant for the feeding effect are serotonergic and project broadly within the brain, suggesting a possible mechanism for how various responses to hunger are coordinated. These findings extend our understanding of the neural circuitry that drives feeding and enable future exploration of how state influences neural activity within this circuit. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. Solving Constraint Satisfaction Problems with Networks of Spiking Neurons.

    Science.gov (United States)

    Jonke, Zeno; Habenschuss, Stefan; Maass, Wolfgang

    2016-01-01

    Network of neurons in the brain apply-unlike processors in our current generation of computer hardware-an event-based processing strategy, where short pulses (spikes) are emitted sparsely by neurons to signal the occurrence of an event at a particular point in time. Such spike-based computations promise to be substantially more power-efficient than traditional clocked processing schemes. However, it turns out to be surprisingly difficult to design networks of spiking neurons that can solve difficult computational problems on the level of single spikes, rather than rates of spikes. We present here a new method for designing networks of spiking neurons via an energy function. Furthermore, we show how the energy function of a network of stochastically firing neurons can be shaped in a transparent manner by composing the networks of simple stereotypical network motifs. We show that this design approach enables networks of spiking neurons to produce approximate solutions to difficult (NP-hard) constraint satisfaction problems from the domains of planning/optimization and verification/logical inference. The resulting networks employ noise as a computational resource. Nevertheless, the timing of spikes plays an essential role in their computations. Furthermore, networks of spiking neurons carry out for the Traveling Salesman Problem a more efficient stochastic search for good solutions compared with stochastic artificial neural networks (Boltzmann machines) and Gibbs sampling.

  20. Solving constraint satisfaction problems with networks of spiking neurons

    Directory of Open Access Journals (Sweden)

    Zeno eJonke

    2016-03-01

    Full Text Available Network of neurons in the brain apply – unlike processors in our current generation ofcomputer hardware – an event-based processing strategy, where short pulses (spikes areemitted sparsely by neurons to signal the occurrence of an event at a particular point intime. Such spike-based computations promise to be substantially more power-efficient thantraditional clocked processing schemes. However it turned out to be surprisingly difficult todesign networks of spiking neurons that can solve difficult computational problems on the levelof single spikes (rather than rates of spikes. We present here a new method for designingnetworks of spiking neurons via an energy function. Furthermore we show how the energyfunction of a network of stochastically firing neurons can be shaped in a quite transparentmanner by composing the networks of simple stereotypical network motifs. We show that thisdesign approach enables networks of spiking neurons to produce approximate solutions todifficult (NP-hard constraint satisfaction problems from the domains of planning/optimizationand verification/logical inference. The resulting networks employ noise as a computationalresource. Nevertheless the timing of spikes (rather than just spike rates plays an essential rolein their computations. Furthermore, networks of spiking neurons carry out for the Traveling Salesman Problem a more efficient stochastic search for good solutions compared with stochastic artificial neural networks (Boltzmann machines and Gibbs sampling.

  1. Introduction to Artificial Neural Networks

    DEFF Research Database (Denmark)

    Larsen, Jan

    1999-01-01

    The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks.......The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks....

  2. Neuronal-glial trafficking

    International Nuclear Information System (INIS)

    Bachelard, H.S.

    2001-01-01

    Full text: The name 'glia' originates from the Greek word for glue, because astro glia (or astrocytes) were thought only to provide an anatomical framework for the electrically-excitable neurones. However, awareness that astrocytes perform vital roles in protecting the neurones, which they surround, emerged from evidence that they act as neuroprotective K + -sinks, and that they remove potentially toxic extracellular glutamate from the vicinity of the neurones. The astrocytes convert the glutamate to non-toxic glutamine which is returned to the neurones and used to replenish transmitter glutamate. This 'glutamate-glutamine cycle' (established in the 1960s by Berl and his colleagues) also contributes to protecting the neurones against a build-up of toxic ammonia. Glial cells also supply the neurones with components for free-radical scavenging glutathione. Recent studies have revealed that glial cells play a more positive interactive role in furnishing the neurones with fuels. Studies using radioactive 14 C, 13 C-MRS and 15 N-GCMS have revealed that glia produce alanine, lactate and proline for consumption by neurones, with increased formation of neurotransmitter glutamate. On neuronal activation the release of NH 4 + and glutamate from the neurones stimulates glucose uptake and glycolysis in the glia to produce more alanine, which can be regarded as an 'alanine-glutamate cycle' Use of 14 C-labelled precursors provided early evidence that neurotransmitter GABA may be partly derived from glial glutamine, and this has been confirmed recently in vivo by MRS isotopomer analysis of the GABA and glutamine labelled from 13 C-acetate. Relative rates of intermediary metabolism in glia and neurones can be calculated using a combination of [1- 13 C] glucose and [1,2- 13 C] acetate. When glutamate is released by neurones there is a net neuronal loss of TCA intermediates which have to be replenished. Part of this is derived from carboxylation of pyruvate, (pyruvate carboxylase

  3. Criminal Aspects of Artificial Abortion

    OpenAIRE

    Hartmanová, Leona

    2016-01-01

    Criminal Aspects of Artificial Abortion This diploma thesis deals with the issue of artificial abortion, especially its criminal aspects. Legal aspects are not the most important aspects of artificial abortion. Social, ethical or ideological aspects are of the same importance but this diploma thesis cannot analyse all of them. The main issue with artificial abortion is whether it is possible to force a pregnant woman to carry a child and give birth to a child when she cannot or does not want ...

  4. Mesmerising mirror neurons.

    Science.gov (United States)

    Heyes, Cecilia

    2010-06-01

    Mirror neurons have been hailed as the key to understanding social cognition. I argue that three currents of thought-relating to evolution, atomism and telepathy-have magnified the perceived importance of mirror neurons. When they are understood to be a product of associative learning, rather than an adaptation for social cognition, mirror neurons are no longer mesmerising, but they continue to raise important questions about both the psychology of science and the neural bases of social cognition. Copyright 2010 Elsevier Inc. All rights reserved.

  5. The mirror neuron system.

    Science.gov (United States)

    Cattaneo, Luigi; Rizzolatti, Giacomo

    2009-05-01

    Mirror neurons are a class of neurons, originally discovered in the premotor cortex of monkeys, that discharge both when individuals perform a given motor act and when they observe others perform that same motor act. Ample evidence demonstrates the existence of a cortical network with the properties of mirror neurons (mirror system) in humans. The human mirror system is involved in understanding others' actions and their intentions behind them, and it underlies mechanisms of observational learning. Herein, we will discuss the clinical implications of the mirror system.

  6. Application of ANNS in tube CHF prediction: effect on neuron number in hidden layer

    International Nuclear Information System (INIS)

    Han, L.; Shan, J.; Zhang, B.

    2004-01-01

    Prediction of the Critical Heat Flux (CHF) for upward flow of water in uniformly heated vertical round tube is studied with Artificial Neuron Networks (ANNs) method utilizing different neuron number in hidden layers. This study is based on thermal equilibrium conditions. The neuron number in hidden layers is chosen to vary from 5 to 30 with the step of 5. The effect due to the variety of the neuron number in hidden layers is analyzed. The analysis shows that the neuron number in hidden layers should be appropriate, too less will affect the prediction accuracy and too much may result in abnormal parametric trends. It is concluded that the appropriate neuron number in two hidden layers should be [15 15]. (authors)

  7. Label-free visualization of ultrastructural features of artificial synapses via cryo-EM.

    Science.gov (United States)

    Gopalakrishnan, Gopakumar; Yam, Patricia T; Madwar, Carolin; Bostina, Mihnea; Rouiller, Isabelle; Colman, David R; Lennox, R Bruce

    2011-12-21

    The ultrastructural details of presynapses formed between artificial substrates of submicrometer silica beads and hippocampal neurons are visualized via cryo-electron microscopy (cryo-EM). The silica beads are derivatized by poly-d-lysine or lipid bilayers. Molecular features known to exist at presynapses are clearly present at these artificial synapses, as visualized by cryo-EM. Key synaptic features such as the membrane contact area at synaptic junctions, the presynaptic bouton containing presynaptic vesicles, as well as microtubular structures can be identified. This is the first report of the direct, label-free observation of ultrastructural details of artificial synapses.

  8. On the Construction of Artificial Brains

    CERN Document Server

    Ramacher, Ulrich

    2009-01-01

    This book presents a first generation of artificial brains, using vision as sample application. An object recognition system is built, using neurons and synapses as exclusive building elements. The system contains a feature pyramid with 8 orientations and 5 resolution levels for 1000 objects and networks for binding of features into objects. This vision system can recognize objects robustly in the presence of changes in illumination, deformation, distance and pose (as long as object components remain visible). The neuro-synaptic network owes its functional power to the introduction of rapidly modifiable dynamic synapses. These give a network greater pattern recognition capabilities than are achievable with fixed connections. The spatio-temporal correlation structure of patterns is captured by a single synaptic differential equation in a universal way. The correlation can appear as synchronous neural firing, which signals the presence of a feature in a robust way, or binds features into objects. Although in th...

  9. Biomaterials for artificial organs

    CERN Document Server

    Lysaght, Michael J

    2010-01-01

    The worldwide demand for organ transplants far exceeds available donor organs. Consequently some patients die whilst waiting for a transplant. Synthetic alternatives are therefore imperative to improve the quality of, and in some cases, save people's lives. Advances in biomaterials have generated a range of materials and devices for use either outside the body or through implantation to replace or assist functions which may have been lost through disease or injury. Biomaterials for artificial organs reviews the latest developments in biomaterials and investigates how they can be used to improve the quality and efficiency of artificial organs. Part one discusses commodity biomaterials including membranes for oxygenators and plasmafilters, titanium and cobalt chromium alloys for hips and knees, polymeric joint-bearing surfaces for total joint replacements, biomaterials for pacemakers, defibrillators and neurostimulators and mechanical and bioprosthetic heart valves. Part two goes on to investigate advanced and ...

  10. Artificial structures on Mars

    Science.gov (United States)

    Van Flandern, T.

    2002-05-01

    Approximately 70,000 images of the surface of Mars at a resolution of up to 1.4 meters per pixel, taken by the Mars Global Surveyor spacecraft, are now in public archives. Approximately 1% of those images show features that can be broadly described as `special shapes', `tracks, trails, and possible vegetation', `spots, stripes, and tubes', `artistic imagery', and `patterns and symbols'. Rather than optical illusions and tricks of light and shadow, most of these have the character that, if photographed on Earth, no one would doubt that they were the products of large biology and intelligence. In a few cases, relationships, context, and fulfillment of a priori predictions provide objective evidence of artificiality that is exempt from the influence of experimenter biases. Only controlled test results can be trusted because biases are strong and operate both for and against artificiality.

  11. Artificial intelligence in medicine

    OpenAIRE

    Scerri, Mariella; Grech, Victor E.

    2016-01-01

    Various types of artificial intelligence programs are already available as consultants to physicians, and these help in medical diagnostics and treatment. At the time of writing, extant programs constitute “weak” AI—lacking in consciousness and intentionality. With AI currently making rapid progress in all domains, including those of healthcare, physicians face possible competitors—or worse, claims that doctors may become obsolete. We will explore the development of AI and robotics in medicin...

  12. Essentials of artificial intelligence

    CERN Document Server

    Ginsberg, Matt

    1993-01-01

    Since its publication, Essentials of Artificial Intelligence has beenadopted at numerous universities and colleges offering introductory AIcourses at the graduate and undergraduate levels. Based on the author'scourse at Stanford University, the book is an integrated, cohesiveintroduction to the field. The author has a fresh, entertaining writingstyle that combines clear presentations with humor and AI anecdotes. At thesame time, as an active AI researcher, he presents the materialauthoritatively and with insight that reflects a contemporary, first hand

  13. Intelligible Artificial Intelligence

    OpenAIRE

    Weld, Daniel S.; Bansal, Gagan

    2018-01-01

    Since Artificial Intelligence (AI) software uses techniques like deep lookahead search and stochastic optimization of huge neural networks to fit mammoth datasets, it often results in complex behavior that is difficult for people to understand. Yet organizations are deploying AI algorithms in many mission-critical settings. In order to trust their behavior, we must make it intelligible --- either by using inherently interpretable models or by developing methods for explaining otherwise overwh...

  14. Intelligence in Artificial Intelligence

    OpenAIRE

    Datta, Shoumen Palit Austin

    2016-01-01

    The elusive quest for intelligence in artificial intelligence prompts us to consider that instituting human-level intelligence in systems may be (still) in the realm of utopia. In about a quarter century, we have witnessed the winter of AI (1990) being transformed and transported to the zenith of tabloid fodder about AI (2015). The discussion at hand is about the elements that constitute the canonical idea of intelligence. The delivery of intelligence as a pay-per-use-service, popping out of ...

  15. Artificial neural network modelling

    CERN Document Server

    Samarasinghe, Sandhya

    2016-01-01

    This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .

  16. Neuromorphic Silicon Neuron Circuits

    Science.gov (United States)

    Indiveri, Giacomo; Linares-Barranco, Bernabé; Hamilton, Tara Julia; van Schaik, André; Etienne-Cummings, Ralph; Delbruck, Tobi; Liu, Shih-Chii; Dudek, Piotr; Häfliger, Philipp; Renaud, Sylvie; Schemmel, Johannes; Cauwenberghs, Gert; Arthur, John; Hynna, Kai; Folowosele, Fopefolu; Saighi, Sylvain; Serrano-Gotarredona, Teresa; Wijekoon, Jayawan; Wang, Yingxue; Boahen, Kwabena

    2011-01-01

    Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems, to bidirectional brain–machine interfaces. The specific circuit solutions used to implement silicon neurons depend on the application requirements. In this paper we describe the most common building blocks and techniques used to implement these circuits, and present an overview of a wide range of neuromorphic silicon neurons, which implement different computational models, ranging from biophysically realistic and conductance-based Hodgkin–Huxley models to bi-dimensional generalized adaptive integrate and fire models. We compare the different design methodologies used for each silicon neuron design described, and demonstrate their features with experimental results, measured from a wide range of fabricated VLSI chips. PMID:21747754

  17. Neuromorphic silicon neuron circuits

    Directory of Open Access Journals (Sweden)

    Giacomo eIndiveri

    2011-05-01

    Full Text Available Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems, to bidirectional brain-machine interfaces. The specific circuit solutions used to implement silicon neurons depend on the application requirements. In this paper we describe the most common building blocks and techniques used to implement these circuits, and present an overview of a wide range of neuromorphic silicon neurons, which implement different computational models, ranging from biophysically realistic and conductance based Hodgkin-Huxley models to bi-dimensional generalized adaptive Integrate and Fire models. We compare the different design methodologies used for each silicon neuron design described, and demonstrate their features with experimental results, measured from a wide range of fabricated VLSI chips.

  18. Leaky Integrate-and-Fire Neuron Circuit Based on Floating-Gate Integrator

    Science.gov (United States)

    Kornijcuk, Vladimir; Lim, Hyungkwang; Seok, Jun Yeong; Kim, Guhyun; Kim, Seong Keun; Kim, Inho; Choi, Byung Joon; Jeong, Doo Seok

    2016-01-01

    The artificial spiking neural network (SNN) is promising and has been brought to the notice of the theoretical neuroscience and neuromorphic engineering research communities. In this light, we propose a new type of artificial spiking neuron based on leaky integrate-and-fire (LIF) behavior. A distinctive feature of the proposed FG-LIF neuron is the use of a floating-gate (FG) integrator rather than a capacitor-based one. The relaxation time of the charge on the FG relies mainly on the tunnel barrier profile, e.g., barrier height and thickness (rather than the area). This opens up the possibility of large-scale integration of neurons. The circuit simulation results offered biologically plausible spiking activity (circuit was subject to possible types of noise, e.g., thermal noise and burst noise. The simulation results indicated remarkable distributional features of interspike intervals that are fitted to Gamma distribution functions, similar to biological neurons in the neocortex. PMID:27242416

  19. Artificial sweetener; Jinko kanmiryo

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1999-08-01

    The patents related to the artificial sweetener that it is introduced to the public in 3 years from 1996 until 1998 are 115 cases. The sugar quality which makes an oligosaccharide and sugar alcohol the subject is greatly over 28 cases of the non-sugar quality in the one by the kind as a general tendency of these patents at 73 cases in such cases as the Aspartame. The method of manufacture patent, which included new material around other peptides, the oligosaccharide and sugar alcohol isn`t inferior to 56 cases of the formation thing patent at 43 cases, and pays attention to the thing, which is many by the method of manufacture, formation. There is most improvement of the quality of sweetness with 31 cases in badness of the aftertaste which is characteristic of the artificial sweetener and so on, and much stability including the improvement in the flavor of food by the artificial sweetener, a long time and dissolution, fluid nature and productivity and improvement of the economy such as a cost are seen with effect on a purpose. (NEDO)

  20. Antithrombotic artificial organs

    Energy Technology Data Exchange (ETDEWEB)

    Takamatsu, T; Fukada, E; Saegusa, M; Hasegawa, T

    1971-07-12

    A new antithrombotic material useful for making artificial organs (artificial blood vessel, artificial heart, etc.) can be prepared by graft-polymerizing an acrylic ester (methyl methacrylate, methyl acrylate, ethyl acrylate, etc.) with a synthetic fiber (teflon, etc.). The graft-polymerization can be carried out by means of gamma radiation with cobalt 60 (dose rate 2.6x10/sup 3/ r/min., total dose 8x10/sup 4/ to 3.5x10/sup 5/ r). A graft ratio of 5 to 80% is attainable. In one example, a tubular sample made of teflon fiber having an inner diameter of 5 to 10 mm was immersed into methyl methacrylate in an ampoule in the absence of air and exposed to cobalt 60 gamma ray at the dose rate of 3.18x10/sup 3/ rad/min. After extraction with acetone, the sample was dried. The total dose was 3.5x10/sup 5/ rad and the graft ratio was ca. 25%. The sample was transplanted to vena cava of dog. No formation of thrombus was observed by autopsy (4 months after the transplantation). In control (teflon tube not graft-polymerized) thrombus was observed by autopsy 7 days after the transplantation.

  1. On the number of preganglionic neurones driving human postganglionic sympathetic neurones: a comparison of modelling and empirical data

    Directory of Open Access Journals (Sweden)

    Vaughan G Macefield

    2011-12-01

    Full Text Available Postganglionic sympathetic axons in awake healthy human subjects, regardless of their identity as muscle vasoconstrictor, cutaneous vasoconstrictor or sudomotor neurones, discharge with a low firing probability (~30%, generate low firing rates (~0.5 Hz and typically fire only once per cardiac interval. The purpose of the present study was to use modelling of spike trains in an attempt to define the number of preganglionic neurones that drive an individual postganglionic neurone. Artificial spike trains were generated in 1-3 preganglionic neurones converging onto a single postganglionic neurone. Each preganglionic input fired with a mean interval distribution of either 1000, 1500, 2000, 2500 or 3000 ms and the standard deviation varied between 0.5, 1.0 and 2.0 x the mean interval; the discharge frequency of each preganglionic neurone exhibited positive skewness and kurtosis. Of the 45 patterns examined, the mean discharge properties of the postganglionic neurone could only be explained by it being driven by, on average, two preganglionic neurones firing with a mean interspike interval of 2500 ms and SD of 5000 ms. The mean firing rate resulting from this pattern was 0.22 Hz, comparable to that of spontaneously active muscle vasoconstrictor neurones in healthy subjects (0.40 Hz. Likewise, the distribution of the number of spikes per cardiac interval was similar between the modelled and actual data: 0 spikes (69.5 vs 66.6 %, 1 spike (25.6 vs 21.2 %, 2 spikes (4.3 vs 6.4 %, 3 spikes (0.5 vs 1.7 % and 4 spikes (0.1 vs 0.7 %. Although some features of the firing patterns could be explained by the postganglionic neurone being driven by a single preganglionic neurone, none of the emulated firing patterns generated by the firing of three preganglionic neurones matched the discharge of the real neurones. These modelling data indicate that, on average, human postganglionic sympathetic neurones are driven by two preganglionic inputs.

  2. NeuronBank: a tool for cataloging neuronal circuitry

    Directory of Open Access Journals (Sweden)

    Paul S Katz

    2010-04-01

    Full Text Available The basic unit of any nervous system is the neuron. Therefore, understanding the operation of nervous systems ultimately requires an inventory of their constituent neurons and synaptic connectivity, which form neural circuits. The presence of uniquely identifiable neurons or classes of neurons in many invertebrates has facilitated the construction of cellular-level connectivity diagrams that can be generalized across individuals within a species. Homologous neurons can also be recognized across species. Here we describe NeuronBank.org, a web-based tool that we are developing for cataloging, searching, and analyzing neuronal circuitry within and across species. Information from a single species is represented in an individual branch of NeuronBank. Users can search within a branch or perform queries across branches to look for similarities in neuronal circuits across species. The branches allow for an extensible ontology so that additional characteristics can be added as knowledge grows. Each entry in NeuronBank generates a unique accession ID, allowing it to be easily cited. There is also an automatic link to a Wiki page allowing an encyclopedic explanation of the entry. All of the 44 previously published neurons plus one previously unpublished neuron from the mollusc, Tritonia diomedea, have been entered into a branch of NeuronBank as have 4 previously published neurons from the mollusc, Melibe leonina. The ability to organize information about neuronal circuits will make this information more accessible, ultimately aiding research on these important models.

  3. Spider Silk as Guiding Biomaterial for Human Model Neurons

    Directory of Open Access Journals (Sweden)

    Frank Roloff

    2014-01-01

    Full Text Available Over the last years, a number of therapeutic strategies have emerged to promote axonal regeneration. An attractive strategy is the implantation of biodegradable and nonimmunogenic artificial scaffolds into injured peripheral nerves. In previous studies, transplantation of decellularized veins filled with spider silk for bridging critical size nerve defects resulted in axonal regeneration and remyelination by invading endogenous Schwann cells. Detailed interaction of elongating neurons and the spider silk as guidance material is unknown. To visualize direct cellular interactions between spider silk and neurons in vitro, we developed an in vitro crossed silk fiber array. Here, we describe in detail for the first time that human (NT2 model neurons attach to silk scaffolds. Extending neurites can bridge gaps between single silk fibers and elongate afterwards on the neighboring fiber. Culturing human neurons on the silk arrays led to an increasing migration and adhesion of neuronal cell bodies to the spider silk fibers. Within three to four weeks, clustered somata and extending neurites formed ganglion-like cell structures. Microscopic imaging of human neurons on the crossed fiber arrays in vitro will allow for a more efficient development of methods to maximize cell adhesion and neurite growth on spider silk prior to transplantation studies.

  4. Sweet taste and nutrient value subdivide rewarding dopaminergic neurons in Drosophila.

    Science.gov (United States)

    Huetteroth, Wolf; Perisse, Emmanuel; Lin, Suewei; Klappenbach, Martín; Burke, Christopher; Waddell, Scott

    2015-03-16

    Dopaminergic neurons provide reward learning signals in mammals and insects [1-4]. Recent work in Drosophila has demonstrated that water-reinforcing dopaminergic neurons are different to those for nutritious sugars [5]. Here, we tested whether the sweet taste and nutrient properties of sugar reinforcement further subdivide the fly reward system. We found that dopaminergic neurons expressing the OAMB octopamine receptor [6] specifically convey the short-term reinforcing effects of sweet taste [4]. These dopaminergic neurons project to the β'2 and γ4 regions of the mushroom body lobes. In contrast, nutrient-dependent long-term memory requires different dopaminergic neurons that project to the γ5b regions, and it can be artificially reinforced by those projecting to the β lobe and adjacent α1 region. Surprisingly, whereas artificial implantation and expression of short-term memory occur in satiated flies, formation and expression of artificial long-term memory require flies to be hungry. These studies suggest that short-term and long-term sugar memories have different physiological constraints. They also demonstrate further functional heterogeneity within the rewarding dopaminergic neuron population. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  5. Neuronal avalanches and learning

    Energy Technology Data Exchange (ETDEWEB)

    Arcangelis, Lucilla de, E-mail: dearcangelis@na.infn.it [Department of Information Engineering and CNISM, Second University of Naples, 81031 Aversa (Italy)

    2011-05-01

    Networks of living neurons represent one of the most fascinating systems of biology. If the physical and chemical mechanisms at the basis of the functioning of a single neuron are quite well understood, the collective behaviour of a system of many neurons is an extremely intriguing subject. Crucial ingredient of this complex behaviour is the plasticity property of the network, namely the capacity to adapt and evolve depending on the level of activity. This plastic ability is believed, nowadays, to be at the basis of learning and memory in real brains. Spontaneous neuronal activity has recently shown features in common to other complex systems. Experimental data have, in fact, shown that electrical information propagates in a cortex slice via an avalanche mode. These avalanches are characterized by a power law distribution for the size and duration, features found in other problems in the context of the physics of complex systems and successful models have been developed to describe their behaviour. In this contribution we discuss a statistical mechanical model for the complex activity in a neuronal network. The model implements the main physiological properties of living neurons and is able to reproduce recent experimental results. Then, we discuss the learning abilities of this neuronal network. Learning occurs via plastic adaptation of synaptic strengths by a non-uniform negative feedback mechanism. The system is able to learn all the tested rules, in particular the exclusive OR (XOR) and a random rule with three inputs. The learning dynamics exhibits universal features as function of the strength of plastic adaptation. Any rule could be learned provided that the plastic adaptation is sufficiently slow.

  6. Neuronal avalanches and learning

    International Nuclear Information System (INIS)

    Arcangelis, Lucilla de

    2011-01-01

    Networks of living neurons represent one of the most fascinating systems of biology. If the physical and chemical mechanisms at the basis of the functioning of a single neuron are quite well understood, the collective behaviour of a system of many neurons is an extremely intriguing subject. Crucial ingredient of this complex behaviour is the plasticity property of the network, namely the capacity to adapt and evolve depending on the level of activity. This plastic ability is believed, nowadays, to be at the basis of learning and memory in real brains. Spontaneous neuronal activity has recently shown features in common to other complex systems. Experimental data have, in fact, shown that electrical information propagates in a cortex slice via an avalanche mode. These avalanches are characterized by a power law distribution for the size and duration, features found in other problems in the context of the physics of complex systems and successful models have been developed to describe their behaviour. In this contribution we discuss a statistical mechanical model for the complex activity in a neuronal network. The model implements the main physiological properties of living neurons and is able to reproduce recent experimental results. Then, we discuss the learning abilities of this neuronal network. Learning occurs via plastic adaptation of synaptic strengths by a non-uniform negative feedback mechanism. The system is able to learn all the tested rules, in particular the exclusive OR (XOR) and a random rule with three inputs. The learning dynamics exhibits universal features as function of the strength of plastic adaptation. Any rule could be learned provided that the plastic adaptation is sufficiently slow.

  7. Deep Learning with Dynamic Spiking Neurons and Fixed Feedback Weights.

    Science.gov (United States)

    Samadi, Arash; Lillicrap, Timothy P; Tweed, Douglas B

    2017-03-01

    Recent work in computer science has shown the power of deep learning driven by the backpropagation algorithm in networks of artificial neurons. But real neurons in the brain are different from most of these artificial ones in at least three crucial ways: they emit spikes rather than graded outputs, their inputs and outputs are related dynamically rather than by piecewise-smooth functions, and they have no known way to coordinate arrays of synapses in separate forward and feedback pathways so that they change simultaneously and identically, as they do in backpropagation. Given these differences, it is unlikely that current deep learning algorithms can operate in the brain, but we that show these problems can be solved by two simple devices: learning rules can approximate dynamic input-output relations with piecewise-smooth functions, and a variation on the feedback alignment algorithm can train deep networks without having to coordinate forward and feedback synapses. Our results also show that deep spiking networks learn much better if each neuron computes an intracellular teaching signal that reflects that cell's nonlinearity. With this mechanism, networks of spiking neurons show useful learning in synapses at least nine layers upstream from the output cells and perform well compared to other spiking networks in the literature on the MNIST digit recognition task.

  8. Artificial intelligence in cardiology

    Directory of Open Access Journals (Sweden)

    Srishti Sharma

    2017-01-01

    Full Text Available Artificial intelligence (AI provides machines with the ability to learn and respond the way humans do and is also referred to as machine learning. The step to building an AI system is to provide the data to learn from so that it can map relations between inputs and outputs and set up parameters such as “weights”/decision boundaries to predict responses for inputs in the future. Then, the model is tested on a second data set. This article outlines the promise this analytic approach has in medicine and cardiology.

  9. Is Intelligence Artificial?

    OpenAIRE

    Greer, Kieran

    2014-01-01

    Our understanding of intelligence is directed primarily at the level of human beings. This paper attempts to give a more unifying definition that can be applied to the natural world in general. The definition would be used more to verify a degree of intelligence, not to quantify it and might help when making judgements on the matter. A version of an accepted test for AI is then put forward as the 'acid test' for Artificial Intelligence itself. It might be what a free-thinking program or robot...

  10. Bayesian artificial intelligence

    CERN Document Server

    Korb, Kevin B

    2010-01-01

    Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology.New to the Second EditionNew chapter on Bayesian network classifiersNew section on object-oriente

  11. Uncertainty in artificial intelligence

    CERN Document Server

    Kanal, LN

    1986-01-01

    How to deal with uncertainty is a subject of much controversy in Artificial Intelligence. This volume brings together a wide range of perspectives on uncertainty, many of the contributors being the principal proponents in the controversy.Some of the notable issues which emerge from these papers revolve around an interval-based calculus of uncertainty, the Dempster-Shafer Theory, and probability as the best numeric model for uncertainty. There remain strong dissenting opinions not only about probability but even about the utility of any numeric method in this context.

  12. Mechanism of artificial heart

    CERN Document Server

    Yamane, Takashi

    2016-01-01

    This book first describes medical devices in relation to regenerative medicine before turning to a more specific topic: artificial heart technologies. Not only the pump mechanisms but also the bearing, motor mechanisms, and materials are described, including expert information. Design methods are described to enhance hemocompatibility: main concerns are reduction of blood cell damage and protein break, as well as prevention of blood clotting. Regulatory science from R&D to clinical trials is also discussed to verify the safety and efficacy of the devices.

  13. How to teach artificial organs.

    Science.gov (United States)

    Zapanta, Conrad M; Borovetz, Harvey S; Lysaght, Michael J; Manning, Keefe B

    2011-01-01

    Artificial organs education is often an overlooked field for many bioengineering and biomedical engineering students. The purpose of this article is to describe three different approaches to teaching artificial organs. This article can serve as a reference for those who wish to offer a similar course at their own institutions or incorporate these ideas into existing courses. Artificial organ classes typically fulfill several ABET (Accreditation Board for Engineering and Technology) criteria, including those specific to bioengineering and biomedical engineering programs.

  14. Artificial Photosynthesis: Beyond Mimicking Nature

    International Nuclear Information System (INIS)

    Dau, Holger; Fujita, Etsuko; Sun, Licheng

    2017-01-01

    In this Editorial, Guest Editors Holger Dau, Etsuko Fujita, and Licheng Sun introduce the Special Issue of ChemSusChem on “Artificial Photosynthesis for Sustainable Fuels”. Here, they discuss the need for non-fossil based fuels, introduce both biological and artificial photosynthesis, and outline various important concepts in artificial photosynthesis, including molecular and solid-state catalysts for water oxidation and hydrogen evolution, catalytic CO 2 reduction, and photoelectrochemical systems.

  15. Artificial Intelligence in Space Platforms.

    Science.gov (United States)

    1984-12-01

    computer algorithms, there still appears to be a need for Artificial Inteligence techniques in the navigation area. The reason is that navigaion, in...RD-RI32 679 ARTIFICIAL INTELLIGENCE IN SPACE PLRTFORNSMU AIR FORCE 1/𔃼 INST OF TECH WRIGHT-PRTTERSON AFB OH SCHOOL OF ENGINEERING M A WRIGHT DEC 94...i4 Preface The purpose of this study was to analyze the feasibility of implementing Artificial Intelligence techniques to increase autonomy for

  16. Artificial Intelligence and Moral intelligence

    OpenAIRE

    Laura Pana

    2008-01-01

    We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined,...

  17. Trimaran Resistance Artificial Neural Network

    Science.gov (United States)

    2011-01-01

    11th International Conference on Fast Sea Transportation FAST 2011, Honolulu, Hawaii, USA, September 2011 Trimaran Resistance Artificial Neural Network Richard...Trimaran Resistance Artificial Neural Network 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e... Artificial Neural Network and is restricted to the center and side-hull configurations tested. The value in the parametric model is that it is able to

  18. Artificial Intelligence and Economic Theories

    OpenAIRE

    Marwala, Tshilidzi; Hurwitz, Evan

    2017-01-01

    The advent of artificial intelligence has changed many disciplines such as engineering, social science and economics. Artificial intelligence is a computational technique which is inspired by natural intelligence such as the swarming of birds, the working of the brain and the pathfinding of the ants. These techniques have impact on economic theories. This book studies the impact of artificial intelligence on economic theories, a subject that has not been extensively studied. The theories that...

  19. Kappe neurons, a novel population of olfactory sensory neurons.

    Science.gov (United States)

    Ahuja, Gaurav; Bozorg Nia, Shahrzad; Zapilko, Veronika; Shiriagin, Vladimir; Kowatschew, Daniel; Oka, Yuichiro; Korsching, Sigrun I

    2014-02-10

    Perception of olfactory stimuli is mediated by distinct populations of olfactory sensory neurons, each with a characteristic set of morphological as well as functional parameters. Beyond two large populations of ciliated and microvillous neurons, a third population, crypt neurons, has been identified in teleost and cartilaginous fishes. We report here a novel, fourth olfactory sensory neuron population in zebrafish, which we named kappe neurons for their characteristic shape. Kappe neurons are identified by their Go-like immunoreactivity, and show a distinct spatial distribution within the olfactory epithelium, similar to, but significantly different from that of crypt neurons. Furthermore, kappe neurons project to a single identified target glomerulus within the olfactory bulb, mdg5 of the mediodorsal cluster, whereas crypt neurons are known to project exclusively to the mdg2 glomerulus. Kappe neurons are negative for established markers of ciliated, microvillous and crypt neurons, but appear to have microvilli. Kappe neurons constitute the fourth type of olfactory sensory neurons reported in teleost fishes and their existence suggests that encoding of olfactory stimuli may require a higher complexity than hitherto assumed already in the peripheral olfactory system.

  20. Artificial Enzymes, "Chemzymes"

    DEFF Research Database (Denmark)

    Bjerre, Jeannette; Rousseau, Cyril Andre Raphaël; Pedersen, Lavinia Georgeta M

    2008-01-01

    Enzymes have fascinated scientists since their discovery and, over some decades, one aim in organic chemistry has been the creation of molecules that mimic the active sites of enzymes and promote catalysis. Nevertheless, even today, there are relatively few examples of enzyme models that successf......Enzymes have fascinated scientists since their discovery and, over some decades, one aim in organic chemistry has been the creation of molecules that mimic the active sites of enzymes and promote catalysis. Nevertheless, even today, there are relatively few examples of enzyme models...... that successfully perform Michaelis-Menten catalysis under enzymatic conditions (i.e., aqueous medium, neutral pH, ambient temperature) and for those that do, very high rate accelerations are seldomly seen. This review will provide a brief summary of the recent developments in artificial enzymes, so called...... "Chemzymes", based on cyclodextrins and other molecules. Only the chemzymes that have shown enzyme-like activity that has been quantified by different methods will be mentioned. This review will summarize the work done in the field of artificial glycosidases, oxidases, epoxidases, and esterases, as well...

  1. The total artificial heart.

    Science.gov (United States)

    Cook, Jason A; Shah, Keyur B; Quader, Mohammed A; Cooke, Richard H; Kasirajan, Vigneshwar; Rao, Kris K; Smallfield, Melissa C; Tchoukina, Inna; Tang, Daniel G

    2015-12-01

    The total artificial heart (TAH) is a form of mechanical circulatory support in which the patient's native ventricles and valves are explanted and replaced by a pneumatically powered artificial heart. Currently, the TAH is approved for use in end-stage biventricular heart failure as a bridge to heart transplantation. However, with an increasing global burden of cardiovascular disease and congestive heart failure, the number of patients with end-stage heart failure awaiting heart transplantation now far exceeds the number of available hearts. As a result, the use of mechanical circulatory support, including the TAH and left ventricular assist device (LVAD), is growing exponentially. The LVAD is already widely used as destination therapy, and destination therapy for the TAH is under investigation. While most patients requiring mechanical circulatory support are effectively treated with LVADs, there is a subset of patients with concurrent right ventricular failure or major structural barriers to LVAD placement in whom TAH may be more appropriate. The history, indications, surgical implantation, post device management, outcomes, complications, and future direction of the TAH are discussed in this review.

  2. THRESHOLD LOGIC IN ARTIFICIAL INTELLIGENCE

    Science.gov (United States)

    COMPUTER LOGIC, ARTIFICIAL INTELLIGENCE , BIONICS, GEOMETRY, INPUT OUTPUT DEVICES, LINEAR PROGRAMMING, MATHEMATICAL LOGIC, MATHEMATICAL PREDICTION, NETWORKS, PATTERN RECOGNITION, PROBABILITY, SWITCHING CIRCUITS, SYNTHESIS

  3. Stochastic neuron models

    CERN Document Server

    Greenwood, Priscilla E

    2016-01-01

    This book describes a large number of open problems in the theory of stochastic neural systems, with the aim of enticing probabilists to work on them. This includes problems arising from stochastic models of individual neurons as well as those arising from stochastic models of the activities of small and large networks of interconnected neurons. The necessary neuroscience background to these problems is outlined within the text, so readers can grasp the context in which they arise. This book will be useful for graduate students and instructors providing material and references for applying probability to stochastic neuron modeling. Methods and results are presented, but the emphasis is on questions where additional stochastic analysis may contribute neuroscience insight. An extensive bibliography is included. Dr. Priscilla E. Greenwood is a Professor Emerita in the Department of Mathematics at the University of British Columbia. Dr. Lawrence M. Ward is a Professor in the Department of Psychology and the Brain...

  4. Improvement of the detection response time of gas sensors using the association of artificial neural networks with pattern recognition technique; Amelioration de la reponse temporelle de capteurs de gaz par reconnaissance de forme a l'aide de reseaux de neurones

    Energy Technology Data Exchange (ETDEWEB)

    Bordieu, Ch.; Rebiere, D. [Bordeaux-1 Univ., Lab. IXL, UMR CNRS 5818, 33 (France); Pistre, J.; Planata, R. [Centre d' Etudes du Bouchet, 91 - Vert-le-Petit (France)

    1999-07-01

    The association of artificial neural networks (multilayer perceptrons) with a real time pattern recognition technique (shifting windows) allowed the development of systems for the detection and the quantification of gases. Shifting window technique is presented and offers an interesting way to improve the detection response time. The partial detector characterization with regard to its parameters was realized. Applications dealing with the detection of gas compounds using surface acoustic sensors permit to show the shifting window technique feasibility. (author)

  5. Generative Artificial Intelligence : Philosophy and Theory of Artificial Intelligence

    NARCIS (Netherlands)

    van der Zant, Tijn; Kouw, Matthijs; Schomaker, Lambertus; Mueller, Vincent C.

    2013-01-01

    The closed systems of contemporary Artificial Intelligence do not seem to lead to intelligent machines in the near future. What is needed are open-ended systems with non-linear properties in order to create interesting properties for the scaffolding of an artificial mind. Using post-structuralistic

  6. Neuronal Migration and Neuronal Migration Disorder in Cerebral Cortex

    OpenAIRE

    SUN, Xue-Zhi; TAKAHASHI, Sentaro; GUI, Chun; ZHANG, Rui; KOGA, Kazuo; NOUYE, Minoru; MURATA, Yoshiharu

    2002-01-01

    Neuronal cell migration is one of the most significant features during cortical development. After final mitosis, neurons migrate from the ventricular zone into the cortical plate, and then establish neuronal lamina and settle onto the outermost layer, forming an "inside-out" gradient of maturation. Neuronal migration is guided by radial glial fibers and also needs proper receptors, ligands, and other unknown extracellular factors, requests local signaling (e.g. some emitted by the Cajal-Retz...

  7. The effect of correlated neuronal firing and neuronal heterogeneity on population coding accuracy in guinea pig inferior colliculus.

    Directory of Open Access Journals (Sweden)

    Oran Zohar

    Full Text Available It has been suggested that the considerable noise in single-cell responses to a stimulus can be overcome by pooling information from a large population. Theoretical studies indicated that correlations in trial-to-trial fluctuations in the responses of different neurons may limit the improvement due to pooling. Subsequent theoretical studies have suggested that inherent neuronal diversity, i.e., the heterogeneity of tuning curves and other response properties of neurons preferentially tuned to the same stimulus, can provide a means to overcome this limit. Here we study the effect of spike-count correlations and the inherent neuronal heterogeneity on the ability to extract information from large neural populations. We use electrophysiological data from the guinea pig Inferior-Colliculus to capture inherent neuronal heterogeneity and single cell statistics, and introduce response correlations artificially. To this end, we generate pseudo-population responses, based on single-cell recording of neurons responding to auditory stimuli with varying binaural correlations. Typically, when pseudo-populations are generated from single cell data, the responses within the population are statistically independent. As a result, the information content of the population will increase indefinitely with its size. In contrast, here we apply a simple algorithm that enables us to generate pseudo-population responses with variable spike-count correlations. This enables us to study the effect of neuronal correlations on the accuracy of conventional rate codes. We show that in a homogenous population, in the presence of even low-level correlations, information content is bounded. In contrast, utilizing a simple linear readout, that takes into account the natural heterogeneity, even of neurons preferentially tuned to the same stimulus, within the neural population, one can overcome the correlated noise and obtain a readout whose accuracy grows linearly with the size of

  8. Artificial organs: recent progress in artificial hearing and vision.

    Science.gov (United States)

    Ifukube, Tohru

    2009-01-01

    Artificial sensory organs are a prosthetic means of sending visual or auditory information to the brain by electrical stimulation of the optic or auditory nerves to assist visually impaired or hearing-impaired people. However, clinical application of artificial sensory organs, except for cochlear implants, is still a trial-and-error process. This is because how and where the information transmitted to the brain is processed is still unknown, and also because changes in brain function (plasticity) remain unknown, even though brain plasticity plays an important role in meaningful interpretation of new sensory stimuli. This article discusses some basic unresolved issues and potential solutions in the development of artificial sensory organs such as cochlear implants, brainstem implants, artificial vision, and artificial retinas.

  9. Artificial Diets for Mosquitoes

    Directory of Open Access Journals (Sweden)

    Kristina K. Gonzales

    2016-12-01

    Full Text Available Mosquito-borne diseases are responsible for more than a million human deaths every year. Modern mosquito control strategies such as sterile insect technique (SIT, release of insects carrying a dominant lethal (RIDL, population replacement strategies (PR, and Wolbachia-based strategies require the rearing of large numbers of mosquitoes in culture for continuous release over an extended period of time. Anautogenous mosquitoes require essential nutrients for egg production, which they obtain through the acquisition and digestion of a protein-rich blood meal. Therefore, mosquito mass production in laboratories and other facilities relies on vertebrate blood from live animal hosts. However, vertebrate blood is expensive to acquire and hard to store for longer times especially under field conditions. This review discusses older and recent studies that were aimed at the development of artificial diets for mosquitoes in order to replace vertebrate blood.

  10. A programmable artificial retina

    International Nuclear Information System (INIS)

    Bernard, T.M.; Zavidovique, B.Y.; Devos, F.J.

    1993-01-01

    An artificial retina is a device that intimately associates an imager with processing facilities on a monolithic circuit. Yet, except for simple environments and applications, analog hardware will not suffice to process and compact the raw image flow from the photosensitive array. To solve this output problem, an on-chip array of bare Boolean processors with halftoning facilities might be used, providing versatility from programmability. By setting the pixel memory size to 3 b, the authors have demonstrated both the technological practicality and the computational efficiency of this programmable Boolean retina concept. Using semi-static shifting structures together with some interaction circuitry, a minimal retina Boolean processor can be built with less than 30 transistors and controlled by as few as 6 global clock signals. The successful design, integration, and test of such a 65x76 Boolean retina on a 50-mm 2 CMOS 2-μm circuit are presented

  11. Artificial intelligence in radiology.

    Science.gov (United States)

    Hosny, Ahmed; Parmar, Chintan; Quackenbush, John; Schwartz, Lawrence H; Aerts, Hugo J W L

    2018-05-17

    Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated remarkable progress in image-recognition tasks. Methods ranging from convolutional neural networks to variational autoencoders have found myriad applications in the medical image analysis field, propelling it forward at a rapid pace. Historically, in radiology practice, trained physicians visually assessed medical images for the detection, characterization and monitoring of diseases. AI methods excel at automatically recognizing complex patterns in imaging data and providing quantitative, rather than qualitative, assessments of radiographic characteristics. In this Opinion article, we establish a general understanding of AI methods, particularly those pertaining to image-based tasks. We explore how these methods could impact multiple facets of radiology, with a general focus on applications in oncology, and demonstrate ways in which these methods are advancing the field. Finally, we discuss the challenges facing clinical implementation and provide our perspective on how the domain could be advanced.

  12. Hydraulically actuated artificial muscles

    Science.gov (United States)

    Meller, M. A.; Tiwari, R.; Wajcs, K. B.; Moses, C.; Reveles, I.; Garcia, E.

    2012-04-01

    Hydraulic Artificial Muscles (HAMs) consisting of a polymer tube constrained by a nylon mesh are presented in this paper. Despite the actuation mechanism being similar to its popular counterpart, which are pneumatically actuated (PAM), HAMs have not been studied in depth. HAMs offer the advantage of compliance, large force to weight ratio, low maintenance, and low cost over traditional hydraulic cylinders. Muscle characterization for isometric and isobaric tests are discussed and compared to PAMs. A model incorporating the effect of mesh angle and friction have also been developed. In addition, differential swelling of the muscle on actuation has also been included in the model. An application of lab fabricated HAMs for a meso-scale robotic system is also presented.

  13. Artificially Engineered Protein Polymers.

    Science.gov (United States)

    Yang, Yun Jung; Holmberg, Angela L; Olsen, Bradley D

    2017-06-07

    Modern polymer science increasingly requires precise control over macromolecular structure and properties for engineering advanced materials and biomedical systems. The application of biological processes to design and synthesize artificial protein polymers offers a means for furthering macromolecular tunability, enabling polymers with dispersities of ∼1.0 and monomer-level sequence control. Taking inspiration from materials evolved in nature, scientists have created modular building blocks with simplified monomer sequences that replicate the function of natural systems. The corresponding protein engineering toolbox has enabled the systematic development of complex functional polymeric materials across areas as diverse as adhesives, responsive polymers, and medical materials. This review discusses the natural proteins that have inspired the development of key building blocks for protein polymer engineering and the function of these elements in material design. The prospects and progress for scalable commercialization of protein polymers are reviewed, discussing both technology needs and opportunities.

  14. Artificial resuspension studies

    International Nuclear Information System (INIS)

    Cooper, B.M.; Marchall, K.B.; Thomas, K.A.; Tracy, B.L.

    1990-01-01

    Artificial resuspension studies on a range of Taranaki and other major trial site soils were performed by use of a mechanical dust-raising apparatus. A cascade impactor was used to analyse airborne dust in terms of mass and 241 Am activities for particle sizes less than 7 μm. Plutonium and americium activities were found to be enhanced in the respirable fraction. Reported enhancement factors (defined as the ratio of activity concentration of the respirable fraction to that of the total soil) ranged from 3.7 to 32.5 for Taranaki soils with an average value of 6 appearing reasonable for general application in outer (plume) areas. Values close to unity were measured at major trial sites , One Tree and Tadje. Results of some experiments where uncontamined dust was raised by activities such as walking and driving over dusty ground are also presented. 7 refs., 9 tabs., 4 figs

  15. Neuronal nets in robotics

    International Nuclear Information System (INIS)

    Jimenez Sanchez, Raul

    1999-01-01

    The paper gives a generic idea of the solutions that the neuronal nets contribute to the robotics. The advantages and the inconveniences are exposed that have regarding the conventional techniques. It also describe the more excellent applications as the pursuit of trajectories, the positioning based on images, the force control or of the mobile robots management, among others

  16. Neuronal variability during handwriting: lognormal distribution.

    Directory of Open Access Journals (Sweden)

    Valery I Rupasov

    Full Text Available We examined time-dependent statistical properties of electromyographic (EMG signals recorded from intrinsic hand muscles during handwriting. Our analysis showed that trial-to-trial neuronal variability of EMG signals is well described by the lognormal distribution clearly distinguished from the Gaussian (normal distribution. This finding indicates that EMG formation cannot be described by a conventional model where the signal is normally distributed because it is composed by summation of many random sources. We found that the variability of temporal parameters of handwriting--handwriting duration and response time--is also well described by a lognormal distribution. Although, the exact mechanism of lognormal statistics remains an open question, the results obtained should significantly impact experimental research, theoretical modeling and bioengineering applications of motor networks. In particular, our results suggest that accounting for lognormal distribution of EMGs can improve biomimetic systems that strive to reproduce EMG signals in artificial actuators.

  17. Sucrose compared with artificial sweeteners

    DEFF Research Database (Denmark)

    Sørensen, Lone Brinkmann; Vasilaras, Tatjana H; Astrup, Arne

    2014-01-01

    There is a lack of appetite studies in free-living subjects supplying the habitual diet with either sucrose or artificially sweetened beverages and foods. Furthermore, the focus of artificial sweeteners has only been on the energy intake (EI) side of the energy-balance equation. The data are from...

  18. Artificial insemination in marsupials.

    Science.gov (United States)

    Rodger, John C; Paris, Damien B B P; Czarny, Natasha A; Harris, Merrilee S; Molinia, Frank C; Taggart, David A; Allen, Camryn D; Johnston, Stephen D

    2009-01-01

    Assisted breeding technology (ART), including artificial insemination (AI), has the potential to advance the conservation and welfare of marsupials. Many of the challenges facing AI and ART for marsupials are shared with other wild species. However, the marsupial mode of reproduction and development also poses unique challenges and opportunities. For the vast majority of marsupials, there is a dearth of knowledge regarding basic reproductive biology to guide an AI strategy. For threatened or endangered species, only the most basic reproductive information is available in most cases, if at all. Artificial insemination has been used to produce viable young in two marsupial species, the koala and tammar wallaby. However, in these species the timing of ovulation can be predicted with considerably more confidence than in any other marsupial. In a limited number of other marsupials, such precise timing of ovulation has only been achieved using hormonal treatment leading to conception but not live young. A unique marsupial ART strategy which has been shown to have promise is cross-fostering; the transfer of pouch young of a threatened species to the pouches of foster mothers of a common related species as a means to increase productivity. For the foreseeable future, except for a few highly iconic or well studied species, there is unlikely to be sufficient reproductive information on which to base AI. However, if more generic approaches can be developed; such as ICSI (to generate embryos) and female synchronization (to provide oocyte donors or embryo recipients), then the prospects for broader application of AI/ART to marsupials are promising.

  19. Beyond AI: Artificial Dreams Conference

    CERN Document Server

    Zackova, Eva; Kelemen, Jozef; Beyond Artificial Intelligence : The Disappearing Human-Machine Divide

    2015-01-01

    This book is an edited collection of chapters based on the papers presented at the conference “Beyond AI: Artificial Dreams” held in Pilsen in November 2012. The aim of the conference was to question deep-rooted ideas of artificial intelligence and cast critical reflection on methods standing at its foundations.  Artificial Dreams epitomize our controversial quest for non-biological intelligence, and therefore the contributors of this book tried to fully exploit such a controversy in their respective chapters, which resulted in an interdisciplinary dialogue between experts from engineering, natural sciences and humanities.   While pursuing the Artificial Dreams, it has become clear that it is still more and more difficult to draw a clear divide between human and machine. And therefore this book tries to portrait such an image of what lies beyond artificial intelligence: we can see the disappearing human-machine divide, a very important phenomenon of nowadays technological society, the phenomenon which i...

  20. Soft computing in artificial intelligence

    CERN Document Server

    Matson, Eric

    2014-01-01

    This book explores the concept of artificial intelligence based on knowledge-based algorithms. Given the current hardware and software technologies and artificial intelligence theories, we can think of how efficient to provide a solution, how best to implement a model and how successful to achieve it. This edition provides readers with the most recent progress and novel solutions in artificial intelligence. This book aims at presenting the research results and solutions of applications in relevance with artificial intelligence technologies. We propose to researchers and practitioners some methods to advance the intelligent systems and apply artificial intelligence to specific or general purpose. This book consists of 13 contributions that feature fuzzy (r, s)-minimal pre- and β-open sets, handling big coocurrence matrices, Xie-Beni-type fuzzy cluster validation, fuzzy c-regression models, combination of genetic algorithm and ant colony optimization, building expert system, fuzzy logic and neural network, ind...

  1. Vasculo-Neuronal Coupling: Retrograde Vascular Communication to Brain Neurons.

    Science.gov (United States)

    Kim, Ki Jung; Ramiro Diaz, Juan; Iddings, Jennifer A; Filosa, Jessica A

    2016-12-14

    Continuous cerebral blood flow is essential for neuronal survival, but whether vascular tone influences resting neuronal function is not known. Using a multidisciplinary approach in both rat and mice brain slices, we determined whether flow/pressure-evoked increases or decreases in parenchymal arteriole vascular tone, which result in arteriole constriction and dilation, respectively, altered resting cortical pyramidal neuron activity. We present evidence for intercellular communication in the brain involving a flow of information from vessel to astrocyte to neuron, a direction opposite to that of classic neurovascular coupling and referred to here as vasculo-neuronal coupling (VNC). Flow/pressure increases within parenchymal arterioles increased vascular tone and simultaneously decreased resting pyramidal neuron firing activity. On the other hand, flow/pressure decreases evoke parenchymal arteriole dilation and increased resting pyramidal neuron firing activity. In GLAST-CreERT2; R26-lsl-GCaMP3 mice, we demonstrate that increased parenchymal arteriole tone significantly increased intracellular calcium in perivascular astrocyte processes, the onset of astrocyte calcium changes preceded the inhibition of cortical pyramidal neuronal firing activity. During increases in parenchymal arteriole tone, the pyramidal neuron response was unaffected by blockers of nitric oxide, GABA A , glutamate, or ecto-ATPase. However, VNC was abrogated by TRPV4 channel, GABA B , as well as an adenosine A 1 receptor blocker. Differently to pyramidal neuron responses, increases in flow/pressure within parenchymal arterioles increased the firing activity of a subtype of interneuron. Together, these data suggest that VNC is a complex constitutive active process that enables neurons to efficiently adjust their resting activity according to brain perfusion levels, thus safeguarding cellular homeostasis by preventing mismatches between energy supply and demand. We present evidence for vessel-to-neuron

  2. Natural and artificial intelligence misconceptions about brains and neural networks

    CERN Document Server

    de Callataÿ, A

    1992-01-01

    How does the mind work? How is data stored in the brain? How does the mental world connect with the physical world? The hybrid system developed in this book shows a radically new view on the brain. Briefly, in this model memory remains permanent by changing the homeostasis rebuilding the neuronal organelles. These transformations are approximately abstracted as all-or-none operations. Thus the computer-like neural systems become plausible biological models. This illustrated book shows how artificial animals with such brains learn invariant methods of behavior control from their repeated action

  3. Medical imaging was boosted by the discovery of artificial radioactivity

    International Nuclear Information System (INIS)

    Demarthon, F.; Dupuy-Maury, F.; Donnars, O.

    2002-01-01

    This article draws the history of medical imaging since the discovery of artificial radioactivity in 1934. The author reviews the PET (positron emission tomography) and MRI (magnetic resonance imaging) technologies and presents the recent progress in neuro-sciences that have been made possible by using these 2 technologies. Brain imaging has allowed to show: - the impact of emotions on logical mental processes and on mental performances, - the management of memory in the brain of talented quick reckoners, - the degeneration of neurons, and - the link between autism and the presence of structural and functional anomalies in the brain. (A.C.)

  4. Emergent properties of interacting populations of spiking neurons.

    Science.gov (United States)

    Cardanobile, Stefano; Rotter, Stefan

    2011-01-01

    Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system. Here, we present and discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks is faithfully reflected by a set of non-linear rate equations, describing all interactions on the population level. These equations are similar in structure to Lotka-Volterra equations, well known by their use in modeling predator-prey relations in population biology, but abundant applications to economic theory have also been described. We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of interacting neuronal populations.

  5. PERSPECTIVE: Electrical activity enhances neuronal survival and regeneration

    Science.gov (United States)

    Corredor, Raul G.; Goldberg, Jeffrey L.

    2009-10-01

    The failure of regeneration in the central nervous system (CNS) remains an enormous scientific and clinical challenge. After injury or in degenerative diseases, neurons in the adult mammalian CNS fail to regrow their axons and reconnect with their normal targets, and furthermore the neurons frequently die and are not normally replaced. While significant progress has been made in understanding the molecular basis for this lack of regenerative ability, a second approach has gained momentum: replacing lost neurons or lost connections with artificial electrical circuits that interface with the nervous system. In the visual system, gene therapy-based 'optogenetics' prostheses represent a competing technology. Now, the two approaches are converging, as recent data suggest that electrical activity itself, via the molecular signaling pathways such activity stimulates, is sufficient to induce neuronal survival and regeneration, particularly in retinal ganglion cells. Here, we review these data, discuss the effects of electrical activity on neurons' molecular signaling pathways and propose specific mechanisms by which exogenous electrical activity may be acting to enhance survival and regeneration.

  6. Neuronal survival in the brain: neuron type-specific mechanisms

    DEFF Research Database (Denmark)

    Pfisterer, Ulrich Gottfried; Khodosevich, Konstantin

    2017-01-01

    Neurogenic regions of mammalian brain produce many more neurons that will eventually survive and reach a mature stage. Developmental cell death affects both embryonically produced immature neurons and those immature neurons that are generated in regions of adult neurogenesis. Removal of substantial...... numbers of neurons that are not yet completely integrated into the local circuits helps to ensure that maturation and homeostatic function of neuronal networks in the brain proceed correctly. External signals from brain microenvironment together with intrinsic signaling pathways determine whether...... for survival in a certain brain region. This review focuses on how immature neurons survive during normal and impaired brain development, both in the embryonic/neonatal brain and in brain regions associated with adult neurogenesis, and emphasizes neuron type-specific mechanisms that help to survive for various...

  7. Artificial Leaf Based on Artificial Photosynthesis for Solar Fuel Production

    Science.gov (United States)

    2017-06-30

    collect light energy and separate charge for developing new types of nanobiodevices to construct ”artificial leaf” from solar to fuel. or Concept of...AFRL-AFOSR-JP-TR-2017-0054 Artificial Leaf Based on Artificial Photosynthesis for Solar Fuel Production Mamoru Nango NAGOYA INSTITUTE OF TECHNOLOGY...display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ORGANIZATION. 1. REPORT DATE (DD-MM-YYYY)      30-06-2017 2

  8. natural or artificial diets

    Directory of Open Access Journals (Sweden)

    A. O. Meyer-Willerer

    2005-01-01

    Full Text Available Se probaron alimentos artificiales y naturales con larva de camarón (Litopenaeus vannamei cultivados en diferentes recipientes. Estos fueron ocho frascos cónicos con 15L, ocho acuarios con 50L y como grupo control, seis tanques de fibra de vidrio con 1500L; todos con agua marina fresca y filtrada. La densidad inicial en todos los recipientes fue de 70 nauplios/L. Aquellos en frascos y acuarios recibieron ya sea dieta natural o artificial. El grupo control fue cultivado con dieta natural en los tanques grandes que utilizan los laboratorios para la producción masiva de postlarvas. El principal producto de excreción de larva de camarón es el ión amonio, que es tóxico cuando está presente en concentraciones elevadas. Se determinó diariamente con el método colorimétrico del indofenol. Los resultados muestran diferencias en la concentración del ión amonio y en la sobrevivencia de larvas entre las diferentes dietas y también entre los diferentes recipientes. En aquellos con volúmenes pequeños comparados con los grandes, se presentó mayor concentración de amonio (500 a 750µg/L, en aquellos con dietas naturales, debido a que este ión sirve de fertilizante a las algas adicionadas, necesitando efectuar recambios diarios de agua posteriores al noveno día de cultivo para mantener este ión a una concentración subletal. Se obtuvo una baja cosecha de postlarvas (menor a 15% con el alimento artificial larvario, debido a la presencia de protozoarios, alimentándose con el producto comercial precipitado en el fondo de los frascos o acuarios. Los acuarios con larvas alimentadas con dieta natural también mostraron concentraciones subletales de amonio al noveno día; sin embargo, la sobrevivencia fue cuatro veces mayor que con dietas artificiales. Los tanques control con dietas naturales presentaron tasas de sobrevivencia (70 ± 5% similares a la reportada por otros laboratorios.

  9. Neuronal synchrony: peculiarity and generality.

    Science.gov (United States)

    Nowotny, Thomas; Huerta, Ramon; Rabinovich, Mikhail I

    2008-09-01

    Synchronization in neuronal systems is a new and intriguing application of dynamical systems theory. Why are neuronal systems different as a subject for synchronization? (1) Neurons in themselves are multidimensional nonlinear systems that are able to exhibit a wide variety of different activity patterns. Their "dynamical repertoire" includes regular or chaotic spiking, regular or chaotic bursting, multistability, and complex transient regimes. (2) Usually, neuronal oscillations are the result of the cooperative activity of many synaptically connected neurons (a neuronal circuit). Thus, it is necessary to consider synchronization between different neuronal circuits as well. (3) The synapses that implement the coupling between neurons are also dynamical elements and their intrinsic dynamics influences the process of synchronization or entrainment significantly. In this review we will focus on four new problems: (i) the synchronization in minimal neuronal networks with plastic synapses (synchronization with activity dependent coupling), (ii) synchronization of bursts that are generated by a group of nonsymmetrically coupled inhibitory neurons (heteroclinic synchronization), (iii) the coordination of activities of two coupled neuronal networks (partial synchronization of small composite structures), and (iv) coarse grained synchronization in larger systems (synchronization on a mesoscopic scale). (c) 2008 American Institute of Physics.

  10. From Neurons to Newtons

    DEFF Research Database (Denmark)

    Nielsen, Bjørn Gilbert

    2001-01-01

    proteins generate forces, to the macroscopic levels where overt arm movements are vol- untarily controlled within an unpredictable environment by legions of neurons¯ring in orderly fashion. An extensive computer simulation system has been developed for this thesis, which at present contains a neural...... network scripting language for specifying arbitrary neural architectures, de¯nition ¯les for detailed spinal networks, various biologically realistic models of neurons, and dynamic synapses. Also included are structurally accurate models of intrafusal and extra-fusal muscle ¯bers and a general body...... that an explicit function may be derived which expresses the force that the spindle contractile elements must produce to exactly counter spindle unloading during muscle shortening. This information was used to calculate the corresponding "optimal" °-motoneuronal activity level. For some simple arm movement tasks...

  11. Criticality in Neuronal Networks

    Science.gov (United States)

    Friedman, Nir; Ito, Shinya; Brinkman, Braden A. W.; Shimono, Masanori; Deville, R. E. Lee; Beggs, John M.; Dahmen, Karin A.; Butler, Tom C.

    2012-02-01

    In recent years, experiments detecting the electrical firing patterns in slices of in vitro brain tissue have been analyzed to suggest the presence of scale invariance and possibly criticality in the brain. Much of the work done however has been limited in two ways: 1) the data collected is from local field potentials that do not represent the firing of individual neurons; 2) the analysis has been primarily limited to histograms. In our work we examine data based on the firing of individual neurons (spike data), and greatly extend the analysis by considering shape collapse and exponents. Our results strongly suggest that the brain operates near a tuned critical point of a highly distinctive universality class.

  12. Bioengineering of Artificial Lymphoid Organs.

    Science.gov (United States)

    Nosenko, M A; Drutskaya, M S; Moisenovich, M M; Nedospasov, S A

    2016-01-01

    This review addresses the issue of bioengineering of artificial lymphoid organs.Progress in this field may help to better understand the nature of the structure-function relations that exist in immune organs. Artifical lymphoid organs may also be advantageous in the therapy or correction of immunodefficiencies, autoimmune diseases, and cancer. The structural organization, development, and function of lymphoid tissue are analyzed with a focus on the role of intercellular contacts and on the cytokine signaling pathways regulating these processes. We describe various polymeric materials, as scaffolds, for artificial tissue engineering. Finally, published studies in which artificial lymphoid organs were generated are reviewed and possible future directions in the field are discussed.

  13. Artificial Neural Network Analysis System

    Science.gov (United States)

    2001-02-27

    Contract No. DASG60-00-M-0201 Purchase request no.: Foot in the Door-01 Title Name: Artificial Neural Network Analysis System Company: Atlantic... Artificial Neural Network Analysis System 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Powell, Bruce C 5d. PROJECT NUMBER 5e. TASK NUMBER...34) 27-02-2001 Report Type N/A Dates Covered (from... to) ("DD MON YYYY") 28-10-2000 27-02-2001 Title and Subtitle Artificial Neural Network Analysis

  14. Artificial radioelements; Radioelements artificiels

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1952-07-01

    This catalogs retails the list of the artificial radioelements obtained at the Zoe reactor. A certain number of methods of concentration and separation has been finalized. The targets are submitted to irradiation in a thermal neutron flux in order to get by neutron reaction the wanted radioelements. In the case of the reaction (n,p), the radioactive element separated chemically in order to produce some radioelements 'without trainer'. For the radioelements obtained from the reaction (n, {gamma}) one uses the effect of Szilard and Chalmers to separate the active and inactive atoms in order to increase the specific activity of the radioelement of interest. (M.B.) [French] Ce catalogue detaille la liste des radioelements artificiels obtenus a la Pile ZOE. un certain nombre de methodes de concentration et de separation ont ete mises au point. Les cibles sont soumis a irradiation dans un flux de neutron thermique en vue d'obtenir par reaction neutronique les radioelements desires. Dans le cas de la reaction (n,p), l'element radioactif est separe chimiquement afin de produire des radioelements ''sans entraineur''. Pour les radioelements issus de la reaction (n, {gamma}) on utilise l'Effet de Szilard et Chalmers pour separer les atomes actifs et inactifs afin d'augmenter l'activite specifique du radioelement d'interet. (M.B.)

  15. BioArtificial polymers

    Science.gov (United States)

    Szałata, Kamila; Gumi, Tania

    2017-07-01

    Nowadays, the polymer science has impact in practically all life areas. Countless benefits coming from the usage of materials with high mechanical and chemical resistance, variety of functionalities and potentiality of modification drive to the development of new application fields. Novel approaches of combining these synthetic substances with biomolecules lead to obtain multifunctional hybrid conjugates which merge the bioactivity of natural component with outstanding properties of artificial polymer. Over the decades, an immense progress in bioartificial composites domain allowed to reach a high level of knowledge in terms of natural-like systems engineering, leading to diverse strategies of biomolecule immobilization. Together with different available options, including covalent and noncovalent attachment, come various challenges, related mainly with maintaining the biological activity of fixed molecules. Even though the amount of applications that achieve commercial status is still not substantial, and is expanding continuously in the disciplines like "smart materials," biosensors, delivery systems, nanoreactors and many others. A huge number of remarkable developments reported in the literature present a potential of bioartificial conjugates as a fabrics with highly controllable structure and multiple functionalities, serving as a powerful nanotechnological tool. This novel approach brings closer biologists, chemists and engineers, who sharing their effort and complementing the knowledge can revolutionize the field of bioartificial polymer science.

  16. Artificial intelligence in medicine.

    Science.gov (United States)

    Hamet, Pavel; Tremblay, Johanne

    2017-04-01

    Artificial Intelligence (AI) is a general term that implies the use of a computer to model intelligent behavior with minimal human intervention. AI is generally accepted as having started with the invention of robots. The term derives from the Czech word robota, meaning biosynthetic machines used as forced labor. In this field, Leonardo Da Vinci's lasting heritage is today's burgeoning use of robotic-assisted surgery, named after him, for complex urologic and gynecologic procedures. Da Vinci's sketchbooks of robots helped set the stage for this innovation. AI, described as the science and engineering of making intelligent machines, was officially born in 1956. The term is applicable to a broad range of items in medicine such as robotics, medical diagnosis, medical statistics, and human biology-up to and including today's "omics". AI in medicine, which is the focus of this review, has two main branches: virtual and physical. The virtual branch includes informatics approaches from deep learning information management to control of health management systems, including electronic health records, and active guidance of physicians in their treatment decisions. The physical branch is best represented by robots used to assist the elderly patient or the attending surgeon. Also embodied in this branch are targeted nanorobots, a unique new drug delivery system. The societal and ethical complexities of these applications require further reflection, proof of their medical utility, economic value, and development of interdisciplinary strategies for their wider application. Copyright © 2017. Published by Elsevier Inc.

  17. Artificial UV sources in perspective

    International Nuclear Information System (INIS)

    Coppell, R.

    1993-01-01

    With rare exceptions, the sun is by far the most important source of exposure to ultraviolet radiation. This is the conclusion of a brief examination into use of artificial sources in New Zealand. (author). 1 tab

  18. Parallel artificial liquid membrane extraction

    DEFF Research Database (Denmark)

    Gjelstad, Astrid; Rasmussen, Knut Einar; Parmer, Marthe Petrine

    2013-01-01

    This paper reports development of a new approach towards analytical liquid-liquid-liquid membrane extraction termed parallel artificial liquid membrane extraction. A donor plate and acceptor plate create a sandwich, in which each sample (human plasma) and acceptor solution is separated by an arti......This paper reports development of a new approach towards analytical liquid-liquid-liquid membrane extraction termed parallel artificial liquid membrane extraction. A donor plate and acceptor plate create a sandwich, in which each sample (human plasma) and acceptor solution is separated...... by an artificial liquid membrane. Parallel artificial liquid membrane extraction is a modification of hollow-fiber liquid-phase microextraction, where the hollow fibers are replaced by flat membranes in a 96-well plate format....

  19. Building Explainable Artificial Intelligence Systems

    National Research Council Canada - National Science Library

    Core, Mark G; Lane, H. Chad; van Lent, Michael; Gomboc, Dave; Solomon, Steve; Rosenberg, Milton

    2006-01-01

    As artificial intelligence (AI) systems and behavior models in military simulations become increasingly complex, it has been difficult for users to understand the activities of computer-controlled entities...

  20. Artificial Intelligence in Civil Engineering

    Directory of Open Access Journals (Sweden)

    Pengzhen Lu

    2012-01-01

    Full Text Available Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applications of artificial intelligence in civil engineering, including evolutionary computation, neural networks, fuzzy systems, expert system, reasoning, classification, and learning, as well as others like chaos theory, cuckoo search, firefly algorithm, knowledge-based engineering, and simulated annealing. The main research trends are also pointed out in the end. The paper provides an overview of the advances of artificial intelligence applied in civil engineering.

  1. Artificial intelligence: Deep neural reasoning

    Science.gov (United States)

    Jaeger, Herbert

    2016-10-01

    The human brain can solve highly abstract reasoning problems using a neural network that is entirely physical. The underlying mechanisms are only partially understood, but an artificial network provides valuable insight. See Article p.471

  2. Artificial Intelligence and Expert Systems.

    Science.gov (United States)

    Wilson, Harold O.; Burford, Anna Marie

    1990-01-01

    Delineates artificial intelligence/expert systems (AI/ES) concepts; provides an exposition of some business application areas; relates progress; and creates an awareness of the benefits, limitations, and reservations of AI/ES. (Author)

  3. Artificial Seeds and their Applications

    Indian Academy of Sciences (India)

    currently working on ... heterozygosity of seed, minute seed size, presence of reduced ... Advantages of Artificial or Synthetic Seeds over Somatic Embryos for Propagation .... hour gives optimum bead hardness and rigidity for the produc-.

  4. Metabolic reprogramming during neuronal differentiation.

    Science.gov (United States)

    Agostini, M; Romeo, F; Inoue, S; Niklison-Chirou, M V; Elia, A J; Dinsdale, D; Morone, N; Knight, R A; Mak, T W; Melino, G

    2016-09-01

    Newly generated neurons pass through a series of well-defined developmental stages, which allow them to integrate into existing neuronal circuits. After exit from the cell cycle, postmitotic neurons undergo neuronal migration, axonal elongation, axon pruning, dendrite morphogenesis and synaptic maturation and plasticity. Lack of a global metabolic analysis during early cortical neuronal development led us to explore the role of cellular metabolism and mitochondrial biology during ex vivo differentiation of primary cortical neurons. Unexpectedly, we observed a huge increase in mitochondrial biogenesis. Changes in mitochondrial mass, morphology and function were correlated with the upregulation of the master regulators of mitochondrial biogenesis, TFAM and PGC-1α. Concomitant with mitochondrial biogenesis, we observed an increase in glucose metabolism during neuronal differentiation, which was linked to an increase in glucose uptake and enhanced GLUT3 mRNA expression and platelet isoform of phosphofructokinase 1 (PFKp) protein expression. In addition, glutamate-glutamine metabolism was also increased during the differentiation of cortical neurons. We identified PI3K-Akt-mTOR signalling as a critical regulator role of energy metabolism in neurons. Selective pharmacological inhibition of these metabolic pathways indicate existence of metabolic checkpoint that need to be satisfied in order to allow neuronal differentiation.

  5. Artificial Intelligence in Civil Engineering

    OpenAIRE

    Lu, Pengzhen; Chen, Shengyong; Zheng, Yujun

    2012-01-01

    Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applicati...

  6. Medical applications of artificial intelligence

    CERN Document Server

    Agah, Arvin

    2013-01-01

    Enhanced, more reliable, and better understood than in the past, artificial intelligence (AI) systems can make providing healthcare more accurate, affordable, accessible, consistent, and efficient. However, AI technologies have not been as well integrated into medicine as predicted. In order to succeed, medical and computational scientists must develop hybrid systems that can effectively and efficiently integrate the experience of medical care professionals with capabilities of AI systems. After providing a general overview of artificial intelligence concepts, tools, and techniques, Medical Ap

  7. The handbook of artificial intelligence

    CERN Document Server

    Barr, Avron

    1982-01-01

    The Handbook of Artificial Intelligence, Volume II focuses on the improvements in artificial intelligence (AI) and its increasing applications, including programming languages, intelligent CAI systems, and the employment of AI in medicine, science, and education. The book first elaborates on programming languages for AI research and applications-oriented AI research. Discussions cover scientific applications, teiresias, applications in chemistry, dependencies and assumptions, AI programming-language features, and LISP. The manuscript then examines applications-oriented AI research in medicine

  8. Artificial limb representation in amputees

    OpenAIRE

    van den Heiligenberg, FMZ; Orlov, T; Macdonald, SN; Duff, EP; Henderson Slater, JDE; Beckmann, CF; Johansen-Berg, H; Culham, JC; Makin, TR

    2018-01-01

    The human brain contains multiple hand-selective areas, in both the sensorimotor and visual systems. Could our brain repurpose neural resources, originally developed for supporting hand function, to represent and control artificial limbs? We studied individuals with congenital or acquired hand-loss (hereafter one-handers) using functional MRI. We show that the more one-handers use an artificial limb (prosthesis) in their everyday life, the stronger visual hand-selective areas in the lateral o...

  9. Artificial Intelligence Techniques and Methodology

    OpenAIRE

    Carbonell, Jaime G.; Sleeman, Derek

    1982-01-01

    Two closely related aspects of artificial intelligence that have received comparatively little attention in the recent literature are research methodology, and the analysis of computational techniques that span multiple application areas. We believe both issues to be increasingly significant as Artificial Intelligence matures into a science and spins off major application efforts. It is imperative to analyze the repertoire of AI methods with respect to past experience, utility in new domains,...

  10. What are artificial neural networks?

    DEFF Research Database (Denmark)

    Krogh, Anders

    2008-01-01

    Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene prediction. How do they work and what might they be good for? Udgivelsesdato: 2008-Feb......Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene prediction. How do they work and what might they be good for? Udgivelsesdato: 2008-Feb...

  11. Artificial weathering of granite

    Directory of Open Access Journals (Sweden)

    Silva Hermo, B.

    2008-06-01

    Full Text Available This article summarizes a series of artificial weathering tests run on granite designed to: simulate the action of weathering agents on buildings and identify the underlying mechanisms, determine the salt resistance of different types of rock; evaluate consolidation and water-repellent treatment durability; and confirm hypotheses about the origin of salts such as gypsum that are often found in granite buildings. Salt crystallization tests were also conducted, using sodium chloride, sodium sulphate, calcium sulphate and seawater solutions. One of these tests was conducted in a chamber specifically designed to simulate salt spray weathering and another in an SO2 chamber to ascertain whether granite is subject to sulphation. The test results are analyzed and discussed, along with the shortcomings of each type of trial as a method for simulating the decay observed in monuments. The effect of factors such as wet-dry conditions, type of saline solution and the position of the planes of weakness on the type of decay is also addressed.En este trabajo se hace una síntesis de varios ensayos de alteración artificial realizados con rocas graníticas. Estos ensayos tenían distintos objetivos: reproducir las formas de alteración encontradas en los edificios para llegar a conocer los mecanismos que las generan, determinar la resistencia de las diferentes rocas a la acción de las sales, evaluar la durabilidad de tratamientos de consolidación e hidrofugación y constatar hipótesis acerca del origen de algunas sales, como el yeso, que aparecen frecuentemente en edificios graníticos. En los ensayos de cristalización de sales se utilizaron disoluciones de cloruro de sodio, sulfato de sodio, sulfato de calcio y agua de mar. Uno de estos ensayos se llevó a cabo en una cámara especialmente diseñada para reproducir la alteración por aerosol marino y otro se realizó en una cámara de SO2, con el objeto de comprobar si en rocas graníticas se puede producir

  12. An excitatory paraventricular nucleus to AgRP neuron circuit that drives hunger.

    Science.gov (United States)

    Krashes, Michael J; Shah, Bhavik P; Madara, Joseph C; Olson, David P; Strochlic, David E; Garfield, Alastair S; Vong, Linh; Pei, Hongjuan; Watabe-Uchida, Mitsuko; Uchida, Naoshige; Liberles, Stephen D; Lowell, Bradford B

    2014-03-13

    Hunger is a hard-wired motivational state essential for survival. Agouti-related peptide (AgRP)-expressing neurons in the arcuate nucleus (ARC) at the base of the hypothalamus are crucial to the control of hunger. They are activated by caloric deficiency and, when naturally or artificially stimulated, they potently induce intense hunger and subsequent food intake. Consistent with their obligatory role in regulating appetite, genetic ablation or chemogenetic inhibition of AgRP neurons decreases feeding. Excitatory input to AgRP neurons is important in caloric-deficiency-induced activation, and is notable for its remarkable degree of caloric-state-dependent synaptic plasticity. Despite the important role of excitatory input, its source(s) has been unknown. Here, through the use of Cre-recombinase-enabled, cell-specific neuron mapping techniques in mice, we have discovered strong excitatory drive that, unexpectedly, emanates from the hypothalamic paraventricular nucleus, specifically from subsets of neurons expressing thyrotropin-releasing hormone (TRH) and pituitary adenylate cyclase-activating polypeptide (PACAP, also known as ADCYAP1). Chemogenetic stimulation of these afferent neurons in sated mice markedly activates AgRP neurons and induces intense feeding. Conversely, acute inhibition in mice with caloric-deficiency-induced hunger decreases feeding. Discovery of these afferent neurons capable of triggering hunger advances understanding of how this intense motivational state is regulated.

  13. Artificial Neural Network-Based System for PET Volume Segmentation

    Directory of Open Access Journals (Sweden)

    Mhd Saeed Sharif

    2010-01-01

    Full Text Available Tumour detection, classification, and quantification in positron emission tomography (PET imaging at early stage of disease are important issues for clinical diagnosis, assessment of response to treatment, and radiotherapy planning. Many techniques have been proposed for segmenting medical imaging data; however, some of the approaches have poor performance, large inaccuracy, and require substantial computation time for analysing large medical volumes. Artificial intelligence (AI approaches can provide improved accuracy and save decent amount of time. Artificial neural networks (ANNs, as one of the best AI techniques, have the capability to classify and quantify precisely lesions and model the clinical evaluation for a specific problem. This paper presents a novel application of ANNs in the wavelet domain for PET volume segmentation. ANN performance evaluation using different training algorithms in both spatial and wavelet domains with a different number of neurons in the hidden layer is also presented. The best number of neurons in the hidden layer is determined according to the experimental results, which is also stated Levenberg-Marquardt backpropagation training algorithm as the best training approach for the proposed application. The proposed intelligent system results are compared with those obtained using conventional techniques including thresholding and clustering based approaches. Experimental and Monte Carlo simulated PET phantom data sets and clinical PET volumes of nonsmall cell lung cancer patients were utilised to validate the proposed algorithm which has demonstrated promising results.

  14. Application of artificial neural network for heat transfer in porous cone

    Science.gov (United States)

    Athani, Abdulgaphur; Ahamad, N. Ameer; Badruddin, Irfan Anjum

    2018-05-01

    Heat transfer in porous medium is one of the classical areas of research that has been active for many decades. The heat transfer in porous medium is generally studied by using numerical methods such as finite element method; finite difference method etc. that solves coupled partial differential equations by converting them into simpler forms. The current work utilizes an alternate method known as artificial neural network that mimics the learning characteristics of neurons. The heat transfer in porous medium fixed in a cone is predicted using backpropagation neural network. The artificial neural network is able to predict this behavior quite accurately.

  15. Estimation of monthly wind power outputs of WECS with limited record period using artificial neural networks

    International Nuclear Information System (INIS)

    Tu, Yi-Long; Chang, Tsang-Jung; Chen, Cheng-Lung; Chang, Yu-Jung

    2012-01-01

    Highlights: ► ANN with short record training data is used to estimate power outputs in an existing station. ► The suitable numbers/parameters of input neurons for ANN are presented. ► Current wind speeds and previous power outputs are the most important input neurons. ► Choosing suitable input parameters is more important than choosing multiple parameters. - Abstract: For the brand new wind power industry, online recordings of wind power data are always in a relatively limited period. The aim of the study is to investigate the suitable numbers/parameters of input neurons for artificial neural networks under a short record of measured data. Measured wind speeds, wind directions (yaw angles) and power outputs with 10-min resolution at an existing wind power station, located at Jhongtun, Taiwan, are integrated to form three types of input neuron numbers and sixteen cases of input neurons. The first-10 days of each month in 2006 are used for data training to simulate the following 20-day power generation of the same month. The performance of various input neuron cases is evaluated. The simulated results show that using the first 10-day training data with adequate input neurons can estimate energy outputs well except the weak wind regime (May, June, and July). Among the input neuron parameters used, current wind speeds V(t) and previous power outputs P(t − 1) are the most important. Individually using one of them into input neurons can only provide satisfactory estimation. However, simultaneously using these two parameters into input neurons can give the best estimation. Thus, choosing suitable input parameters is more important than choosing multiple parameters.

  16. Imitation, mirror neurons and autism

    OpenAIRE

    Williams, Justin H.G.; Whiten, Andrew; Suddendorf, Thomas; Perrett, David I.

    2001-01-01

    Various deficits in the cognitive functioning of people with autism have been documented in recent years but these provide only partial explanations for the condition. We focus instead on an imitative disturbance involving difficulties both in copying actions and in inhibiting more stereotyped mimicking, such as echolalia. A candidate for the neural basis of this disturbance may be found in a recently discovered class of neurons in frontal cortex, 'mirror neurons' (MNs). These neurons show ac...

  17. The biophysics of neuronal growth

    International Nuclear Information System (INIS)

    Franze, Kristian; Guck, Jochen

    2010-01-01

    For a long time, neuroscience has focused on biochemical, molecular biological and electrophysiological aspects of neuronal physiology and pathology. However, there is a growing body of evidence indicating the importance of physical stimuli for neuronal growth and development. In this review we briefly summarize the historical background of neurobiophysics and give an overview over the current understanding of neuronal growth from a physics perspective. We show how biophysics has so far contributed to a better understanding of neuronal growth and discuss current inconsistencies. Finally, we speculate how biophysics may contribute to the successful treatment of lesions to the central nervous system, which have been considered incurable until very recently.

  18. Dynamic cardiomyoplasty using artificial muscle.

    Science.gov (United States)

    Suzuki, Yasuyuki; Daitoku, Kazuyuki; Minakawa, Masahito; Fukui, Kozo; Fukuda, Ikuo

    2008-01-01

    Dynamic cardiomyoplasty using latissimus dorsi muscle was previously used to compensate for congestive heart failure. Now, however, this method is not acceptable because the long-term result was not as expected owing to fatigue of the skeletal muscle. BioMetal fiber developed by Toki Corporation is one of the artificial muscles activated by electric current. The behavior of this fiber is similar to that of organic muscle. We made an artificial muscle like the latissimus dorsi using BioMetal fiber and tested whether we could use this new muscle as a cardiac supporting device. Testing one Biometal fiber showed the following performance: practical use maximal generative force was 30 g, exercise variation was 50%, and the standard driving current was 220 mA. We created a 4 x 12-cm tabular artificial muscle using 8 BioMetal fibers as a cardiac support device. We also made a simulation circuit composed of a 6 x 8-cm soft bag with unidirectional valves, reservoir, and connecting tube. The simulation circuit was filled with water and the soft bag was wrapped with the artificial muscle device. After powering the device electrically at 9 V with a current of 220 mA for each fiber, we measured the inside pressure and observed the movement of the artificial device. The artificial muscle contracted in 0.5 s for peak time and squeezed the soft bag. The peak pressure inside the soft bag was measured as 10 mmHg. Although further work will be needed to enhance the speed of deformability and movement simulating contraction, we conclude that artificial muscle may be potentially useful as a cardiac assistance device that can be developed for dynamic cardiomyoplasty.

  19. Peripheral chemoreceptors tune inspiratory drive via tonic expiratory neuron hubs in the medullary ventral respiratory column network.

    Science.gov (United States)

    Segers, L S; Nuding, S C; Ott, M M; Dean, J B; Bolser, D C; O'Connor, R; Morris, K F; Lindsey, B G

    2015-01-01

    Models of brain stem ventral respiratory column (VRC) circuits typically emphasize populations of neurons, each active during a particular phase of the respiratory cycle. We have proposed that "tonic" pericolumnar expiratory (t-E) neurons tune breathing during baroreceptor-evoked reductions and central chemoreceptor-evoked enhancements of inspiratory (I) drive. The aims of this study were to further characterize the coordinated activity of t-E neurons and test the hypothesis that peripheral chemoreceptors also modulate drive via inhibition of t-E neurons and disinhibition of their inspiratory neuron targets. Spike trains of 828 VRC neurons were acquired by multielectrode arrays along with phrenic nerve signals from 22 decerebrate, vagotomized, neuromuscularly blocked, artificially ventilated adult cats. Forty-eight of 191 t-E neurons fired synchronously with another t-E neuron as indicated by cross-correlogram central peaks; 32 of the 39 synchronous pairs were elements of groups with mutual pairwise correlations. Gravitational clustering identified fluctuations in t-E neuron synchrony. A network model supported the prediction that inhibitory populations with spike synchrony reduce target neuron firing probabilities, resulting in offset or central correlogram troughs. In five animals, stimulation of carotid chemoreceptors evoked changes in the firing rates of 179 of 240 neurons. Thirty-two neuron pairs had correlogram troughs consistent with convergent and divergent t-E inhibition of I cells and disinhibitory enhancement of drive. Four of 10 t-E neurons that responded to sequential stimulation of peripheral and central chemoreceptors triggered 25 cross-correlograms with offset features. The results support the hypothesis that multiple afferent systems dynamically tune inspiratory drive in part via coordinated t-E neurons. Copyright © 2015 the American Physiological Society.

  20. Emergent properties of interacting populations of spiking neurons

    Directory of Open Access Journals (Sweden)

    Stefano eCardanobile

    2011-12-01

    Full Text Available Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system.Here, we discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks on the population level is faithfully reflected by a set of non-linear rate equations, describing all interactions on this level. These equations, in turn, are similar in structure to the Lotka-Volterra equations, well known by their use in modeling predator-prey relationships in population biology, but abundant applications to economic theory have also been described.We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of neural populations.

  1. Restoring the encoding properties of a stochastic neuron model by an exogenous noise

    Science.gov (United States)

    Paffi, Alessandra; Camera, Francesca; Apollonio, Francesca; d'Inzeo, Guglielmo; Liberti, Micaela

    2015-01-01

    Here we evaluate the possibility of improving the encoding properties of an impaired neuronal system by superimposing an exogenous noise to an external electric stimulation signal. The approach is based on the use of mathematical neuron models consisting of stochastic HH-like circuit, where the impairment of the endogenous presynaptic inputs is described as a subthreshold injected current and the exogenous stimulation signal is a sinusoidal voltage perturbation across the membrane. Our results indicate that a correlated Gaussian noise, added to the sinusoidal signal can significantly increase the encoding properties of the impaired system, through the Stochastic Resonance (SR) phenomenon. These results suggest that an exogenous noise, suitably tailored, could improve the efficacy of those stimulation techniques used in neuronal systems, where the presynaptic sensory neurons are impaired and have to be artificially bypassed. PMID:25999845

  2. Restoring the encoding properties of a stochastic neuron model by an exogenous noise

    Directory of Open Access Journals (Sweden)

    Alessandra ePaffi

    2015-05-01

    Full Text Available Here we evaluate the possibility of improving the encoding properties of an impaired neuronal system by superimposing an exogenous noise to an external electric stimulation signal. The approach is based on the use of mathematical neuron models consisting of stochastic HH-like circuit, where the impairment of the endogenous presynaptic inputs is described as a subthreshold injected current and the exogenous stimulation signal is a sinusoidal voltage perturbation across the membrane. Our results indicate that a correlated Gaussian noise, added to the sinusoidal signal can significantly increase the encoding properties of the impaired system, through the Stochastic Resonance (SR phenomenon. These results suggest that an exogenous noise, suitably tailored, could improve the efficacy of those stimulation techniques used in neuronal systems, where the presynaptic sensory neurons are impaired and have to be artificially bypassed.

  3. How do auditory cortex neurons represent communication sounds?

    Science.gov (United States)

    Gaucher, Quentin; Huetz, Chloé; Gourévitch, Boris; Laudanski, Jonathan; Occelli, Florian; Edeline, Jean-Marc

    2013-11-01

    A major goal in auditory neuroscience is to characterize how communication sounds are represented at the cortical level. The present review aims at investigating the role of auditory cortex in the processing of speech, bird songs and other vocalizations, which all are spectrally and temporally highly structured sounds. Whereas earlier studies have simply looked for neurons exhibiting higher firing rates to particular conspecific vocalizations over their modified, artificially synthesized versions, more recent studies determined the coding capacity of temporal spike patterns, which are prominent in primary and non-primary areas (and also in non-auditory cortical areas). In several cases, this information seems to be correlated with the behavioral performance of human or animal subjects, suggesting that spike-timing based coding strategies might set the foundations of our perceptive abilities. Also, it is now clear that the responses of auditory cortex neurons are highly nonlinear and that their responses to natural stimuli cannot be predicted from their responses to artificial stimuli such as moving ripples and broadband noises. Since auditory cortex neurons cannot follow rapid fluctuations of the vocalizations envelope, they only respond at specific time points during communication sounds, which can serve as temporal markers for integrating the temporal and spectral processing taking place at subcortical relays. Thus, the temporal sparse code of auditory cortex neurons can be considered as a first step for generating high level representations of communication sounds independent of the acoustic characteristic of these sounds. This article is part of a Special Issue entitled "Communication Sounds and the Brain: New Directions and Perspectives". Copyright © 2013 Elsevier B.V. All rights reserved.

  4. Biological Effects Of Artificial Illumination

    Science.gov (United States)

    Corth, Richard

    1980-10-01

    We are increasingly being warned of the possible effects of so called "polluted" light, that is light that differs in spectral content from that of sunlight. We should be concerned, we are told, because all animals and plants have evolved under this natural daylight and therefore any difference between that illuminant and the artificial illuminants that are on the market today, is suspect. The usual presentation of the differences between the sunlight and the artificial illuminants are as shown in Figure 1. Here we are shown the spectral power distribution of sunlight and Cool White fluorescent light. The spectral power distributions of each have been normalized to some convenient wavelength so that each can be seen and easily compared on the same figure. But this presentation is misleading for one does not experience artificial illuminants at the same intensity as one experiences sunlight. Sunlight intensities are ordinarily found to be in the 8000 to 10,000 footcandle range whereas artificial illuminants are rarely experienced at intensity levels greater than 100 footcandles. Therefore a representative difference between the two types of illumination conditions is more accurately represented as in Figure 2. Thus if evolutionary adaptations require that humans and other animals be exposed to sunlight to ensure wellbeing, it is clear that one must be exposed to sunlight intensities. It is not feasible to expect that artificially illuminated environments will be lit to the same intensity as sunlight

  5. Knitting and weaving artificial muscles.

    Science.gov (United States)

    Maziz, Ali; Concas, Alessandro; Khaldi, Alexandre; Stålhand, Jonas; Persson, Nils-Krister; Jager, Edwin W H

    2017-01-01

    A need exists for artificial muscles that are silent, soft, and compliant, with performance characteristics similar to those of skeletal muscle, enabling natural interaction of assistive devices with humans. By combining one of humankind's oldest technologies, textile processing, with electroactive polymers, we demonstrate here the feasibility of wearable, soft artificial muscles made by weaving and knitting, with tunable force and strain. These textile actuators were produced from cellulose yarns assembled into fabrics and coated with conducting polymers using a metal-free deposition. To increase the output force, we assembled yarns in parallel by weaving. The force scaled linearly with the number of yarns in the woven fabric. To amplify the strain, we knitted a stretchable fabric, exhibiting a 53-fold increase in strain. In addition, the textile construction added mechanical stability to the actuators. Textile processing permits scalable and rational production of wearable artificial muscles, and enables novel ways to design assistive devices.

  6. Artificial sensory organs: latest progress.

    Science.gov (United States)

    Nakamura, Tatsuo; Inada, Yuji; Shigeno, Keiji

    2018-03-01

    This study introduces the latest progress on the study of artificial sensory organs, with a special emphasis on the clinical results of artificial nerves and the concept of in situ tissue engineering. Peripheral nerves have a strong potential for regeneration. An artificial nerve uses this potential to recover a damaged peripheral nerve. The polyglycolic acid collagen tube (PGA-C tube) is a bio-absorbable tube stuffed with collagen of multi-chamber structure that consists of thin collagen films. The clinical application of the PGA-C tube began in 2002 in Japan. The number of PGA-C tubes used is now beyond 300, and satisfactory results have been reported on peripheral nerve repairs. This PGA-C tube is also effective for patients suffering from neuropathic pain.

  7. Artificial heart for humanoid robot

    Science.gov (United States)

    Potnuru, Akshay; Wu, Lianjun; Tadesse, Yonas

    2014-03-01

    A soft robotic device inspired by the pumping action of a biological heart is presented in this study. Developing artificial heart to a humanoid robot enables us to make a better biomedical device for ultimate use in humans. As technology continues to become more advanced, the methods in which we implement high performance and biomimetic artificial organs is getting nearer each day. In this paper, we present the design and development of a soft artificial heart that can be used in a humanoid robot and simulate the functions of a human heart using shape memory alloy technology. The robotic heart is designed to pump a blood-like fluid to parts of the robot such as the face to simulate someone blushing or when someone is angry by the use of elastomeric substrates and certain features for the transport of fluids.

  8. The Neuronal Ceroid-Lipofuscinoses

    Science.gov (United States)

    Bennett, Michael J.; Rakheja, Dinesh

    2013-01-01

    The neuronal ceroid-lipofuscinoses (NCL's, Batten disease) represent a group of severe neurodegenerative diseases, which mostly present in childhood. The phenotypes are similar and include visual loss, seizures, loss of motor and cognitive function, and early death. At autopsy, there is massive neuronal loss with characteristic storage in…

  9. Artificial radioactivity in Lough Foyle

    International Nuclear Information System (INIS)

    Cunningham, J.D.; Ryan, T.P.; Lyons, S.; Smith, V.; McGarry, A.; Mitchell, P.I.; Leon Vintro, L.; Larmour, R.A.; Ledgerwood, F.K.

    1996-04-01

    The purpose of this study was to assess the extent to which the marine environment of Lough Foyle, situated on the north coast of Ireland, has been affected by artificial radioactivity released from Sellafield. Although traces of plutonium, americium and radiocaesium from Sellafield are detectable in Lough Foyle, the concentrations in various marine media are significantly lower than those found along the NE coast of Ireland and in the western Irish Sea. The minute quantities of artificial radioactivity found in Lough Foyle are of negligible radiological significance

  10. In Defense of Artificial Replacement.

    Science.gov (United States)

    Shiller, Derek

    2017-06-01

    If it is within our power to provide a significantly better world for future generations at a comparatively small cost to ourselves, we have a strong moral reason to do so. One way of providing a significantly better world may involve replacing our species with something better. It is plausible that in the not-too-distant future, we will be able to create artificially intelligent creatures with whatever physical and psychological traits we choose. Granted this assumption, it is argued that we should engineer our extinction so that our planet's resources can be devoted to making artificial creatures with better lives. © 2017 John Wiley & Sons Ltd.

  11. Artificial intelligence techniques in Prolog

    CERN Document Server

    Shoham, Yoav

    1993-01-01

    Artificial Intelligence Techniques in Prolog introduces the reader to the use of well-established algorithmic techniques in the field of artificial intelligence (AI), with Prolog as the implementation language. The techniques considered cover general areas such as search, rule-based systems, and truth maintenance, as well as constraint satisfaction and uncertainty management. Specific application domains such as temporal reasoning, machine learning, and natural language are also discussed.Comprised of 10 chapters, this book begins with an overview of Prolog, paying particular attention to Prol

  12. Contributions of intrinsic motor neuron properties to the production of rhythmic motor output in the mammalian spinal cord

    DEFF Research Database (Denmark)

    Kiehn, O; Kjaerulff, O; Tresch, M C

    2000-01-01

    Motor neurons are endowed with intrinsic and conditional membrane properties that may shape the final motor output. In the first half of this paper we present data on the contribution of I(h), a hyperpolarization-activated inward cation current, to phase-transition in motor neurons during rhythmic...... firing. Motor neurons were recorded intracellularly during locomotion induced with a mixture of N-methyl-D-aspartate (NMDA) and serotonin, after pharmacological blockade of I(h). I(h) was then replaced by using dynamic clamp, a computer program that allows artificial conductances to be inserted into real...... neurons. I(h) was simulated with biophysical parameters determined in voltage clamp experiments. The data showed that electronic replacement of the native I(h) caused a depolarization of the average membrane potential, a phase-advance of the locomotor drive potential, and increased motor neuron spiking...

  13. Neuronal discrimination capacity

    International Nuclear Information System (INIS)

    Deng Yingchun; Williams, Peter; Feng Jianfeng; Liu Feng

    2003-01-01

    We explore neuronal mechanisms of discriminating between masked signals. It is found that when the correlation between input signals is zero, the output signals are separable if and only if input signals are separable. With positively (negatively) correlated signals, the output signals are separable (mixed) even when input signals are mixed (separable). Exact values of discrimination capacity are obtained for two most interesting cases: the exactly balanced inhibitory and excitatory input case and the uncorrelated input case. Interestingly, the discrimination capacity obtained in these cases is independent of model parameters, input distribution and is universal. Our results also suggest a functional role of inhibitory inputs and correlated inputs or, more generally, the large variability of efferent spike trains observed in in vivo experiments: the larger the variability of efferent spike trains, the easier it is to discriminate between masked input signals

  14. Neuronal discrimination capacity

    Energy Technology Data Exchange (ETDEWEB)

    Deng Yingchun [Department of Mathematics, Hunan Normal University 410081, Changsha (China); COGS, University of Sussex at Brighton, BN1 9QH (United Kingdom); Williams, Peter; Feng Jianfeng [COGS, University of Sussex at Brighton, BN1 9QH (United Kingdom); Liu Feng [COGS, University of Sussex at Brighton, BN1 9QH (United Kingdom); Physics Department, Nanjing University (China)

    2003-12-19

    We explore neuronal mechanisms of discriminating between masked signals. It is found that when the correlation between input signals is zero, the output signals are separable if and only if input signals are separable. With positively (negatively) correlated signals, the output signals are separable (mixed) even when input signals are mixed (separable). Exact values of discrimination capacity are obtained for two most interesting cases: the exactly balanced inhibitory and excitatory input case and the uncorrelated input case. Interestingly, the discrimination capacity obtained in these cases is independent of model parameters, input distribution and is universal. Our results also suggest a functional role of inhibitory inputs and correlated inputs or, more generally, the large variability of efferent spike trains observed in in vivo experiments: the larger the variability of efferent spike trains, the easier it is to discriminate between masked input signals.

  15. Orexin neurons receive glycinergic innervations.

    Directory of Open Access Journals (Sweden)

    Mari Hondo

    Full Text Available Glycine, a nonessential amino-acid that acts as an inhibitory neurotransmitter in the central nervous system, is currently used as a dietary supplement to improve the quality of sleep, but its mechanism of action is poorly understood. We confirmed the effects of glycine on sleep/wakefulness behavior in mice when administered peripherally. Glycine administration increased non-rapid eye movement (NREM sleep time and decreased the amount and mean episode duration of wakefulness when administered in the dark period. Since peripheral administration of glycine induced fragmentation of sleep/wakefulness states, which is a characteristic of orexin deficiency, we examined the effects of glycine on orexin neurons. The number of Fos-positive orexin neurons markedly decreased after intraperitoneal administration of glycine to mice. To examine whether glycine acts directly on orexin neurons, we examined the effects of glycine on orexin neurons by patch-clamp electrophysiology. Glycine directly induced hyperpolarization and cessation of firing of orexin neurons. These responses were inhibited by a specific glycine receptor antagonist, strychnine. Triple-labeling immunofluorescent analysis showed close apposition of glycine transporter 2 (GlyT2-immunoreactive glycinergic fibers onto orexin-immunoreactive neurons. Immunoelectron microscopic analysis revealed that GlyT2-immunoreactive terminals made symmetrical synaptic contacts with somata and dendrites of orexin neurons. Double-labeling immunoelectron microscopy demonstrated that glycine receptor alpha subunits were localized in the postsynaptic membrane of symmetrical inhibitory synapses on orexin neurons. Considering the importance of glycinergic regulation during REM sleep, our observations suggest that glycine injection might affect the activity of orexin neurons, and that glycinergic inhibition of orexin neurons might play a role in physiological sleep regulation.

  16. Neurons are MHC class I-dependent targets for CD8 T cells upon neurotropic viral infection.

    Directory of Open Access Journals (Sweden)

    Grégoire Chevalier

    2011-11-01

    Full Text Available Following infection of the central nervous system (CNS, the immune system is faced with the challenge of eliminating the pathogen without causing significant damage to neurons, which have limited capacities of renewal. In particular, it was thought that neurons were protected from direct attack by cytotoxic T lymphocytes (CTL because they do not express major histocompatibility class I (MHC I molecules, at least at steady state. To date, most of our current knowledge on the specifics of neuron-CTL interaction is based on studies artificially inducing MHC I expression on neurons, loading them with exogenous peptide and applying CTL clones or lines often differentiated in culture. Thus, much remains to be uncovered regarding the modalities of the interaction between infected neurons and antiviral CD8 T cells in the course of a natural disease. Here, we used the model of neuroinflammation caused by neurotropic Borna disease virus (BDV, in which virus-specific CTL have been demonstrated as the main immune effectors triggering disease. We tested the pathogenic properties of brain-isolated CD8 T cells against pure neuronal cultures infected with BDV. We observed that BDV infection of cortical neurons triggered a significant up regulation of MHC I molecules, rendering them susceptible to recognition by antiviral CTL, freshly isolated from the brains of acutely infected rats. Using real-time imaging, we analyzed the spatio-temporal relationships between neurons and CTL. Brain-isolated CTL exhibited a reduced mobility and established stable contacts with BDV-infected neurons, in an antigen- and MHC-dependent manner. This interaction induced rapid morphological changes of the neurons, without immediate killing or impairment of electrical activity. Early signs of neuronal apoptosis were detected only hours after this initial contact. Thus, our results show that infected neurons can be recognized efficiently by brain-isolated antiviral CD8 T cells and

  17. Responses of mirror neurons in area F5 to hand and tool grasping observation

    Science.gov (United States)

    Rochat, Magali J.; Caruana, Fausto; Jezzini, Ahmad; Escola, Ludovic; Intskirveli, Irakli; Grammont, Franck; Gallese, Vittorio; Rizzolatti, Giacomo

    2010-01-01

    Mirror neurons are a distinct class of neurons that discharge both during the execution of a motor act and during observation of the same or similar motor act performed by another individual. However, the extent to which mirror neurons coding a motor act with a specific goal (e.g., grasping) might also respond to the observation of a motor act having the same goal, but achieved with artificial effectors, is not yet established. In the present study, we addressed this issue by recording mirror neurons from the ventral premotor cortex (area F5) of two monkeys trained to grasp objects with pliers. Neuron activity was recorded during the observation and execution of grasping performed with the hand, with pliers and during observation of an experimenter spearing food with a stick. The results showed that virtually all neurons responding to the observation of hand grasping also responded to the observation of grasping with pliers and, many of them to the observation of spearing with a stick. However, the intensity and pattern of the response differed among conditions. Hand grasping observation determined the earliest and the strongest discharge, while pliers grasping and spearing observation triggered weaker responses at longer latencies. We conclude that F5 grasping mirror neurons respond to the observation of a family of stimuli leading to the same goal. However, the response pattern depends upon the similarity between the observed motor act and the one executed by the hand, the natural motor template. PMID:20577726

  18. Short term wind speed forecasting in La Venta, Oaxaca, Mexico, using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Cadenas, Erasmo [Facultad de Ingenieria Mecanica, Universidad Michoacana de San Nicolas de Hidalgo, Santiago Tapia No. 403, Centro, 5000, Mor., Mich. (Mexico); Rivera, Wilfrido [Centro de Ivestigacion en Energia, Universidad Nacional Autonoma de Mexico, Apartado Postal 34, Temixco 62580, Morelos (Mexico)

    2009-01-15

    In this paper the short term wind speed forecasting in the region of La Venta, Oaxaca, Mexico, applying the technique of artificial neural network (ANN) to the hourly time series representative of the site is presented. The data were collected by the Comision Federal de Electricidad (CFE) during 7 years through a network of measurement stations located in the place of interest. Diverse configurations of ANN were generated and compared through error measures, guaranteeing the performance and accuracy of the chosen models. First a model with three layers and seven neurons was chosen, according to the recommendations of diverse authors, nevertheless, the results were not sufficiently satisfactory so other three models were developed, consisting of three layers and six neurons, two layers and four neurons and two layers and three neurons. The simplest model of two layers, with two input neurons and one output neuron, was the best for the short term wind speed forecasting, with mean squared error and mean absolute error values of 0.0016 and 0.0399, respectively. The developed model for short term wind speed forecasting showed a very good accuracy to be used by the Electric Utility Control Centre in Oaxaca for the energy supply. (author)

  19. Artificial neural networks for spatial distribution of fuel assemblies in reload of PWR reactors

    International Nuclear Information System (INIS)

    Oliveira, Edyene; Castro, Victor F.; Velásquez, Carlos E.; Pereira, Claubia

    2017-01-01

    An artificial neural network methodology is being developed in order to find an optimum spatial distribution of the fuel assemblies in a nuclear reactor core during reload. The main bounding parameter of the modelling was the neutron multiplication factor, k ef f . The characteristics of the network are defined by the nuclear parameters: cycle, burnup, enrichment, fuel type, and average power peak of each element. These parameters were obtained by the ORNL nuclear code package SCALE6.0. As for the artificial neural network, the ANN Feedforward Multi L ayer P erceptron with various layers and neurons were constructed. Three algorithms were used and tested: LM (Levenberg-Marquardt), SCG (Scaled Conjugate Gradient) and BayR (Bayesian Regularization). Artificial neural network have implemented using MATLAB 2015a version. As preliminary results, the spatial distribution of the fuel assemblies in the core using a neural network was slightly better than the standard core. (author)

  20. Multidirectional Artificial Muscles from Nylon.

    Science.gov (United States)

    Mirvakili, Seyed M; Hunter, Ian W

    2017-01-01

    Multidirectional artificial muscles are made from highly oriented nylon filaments. Thanks to the low thermal conductivity of nylon and its anisotropic thermal expansion, bending occurs when a nylon beam is differentially heated. This heat can be generated via a Joule heating mechanism or high power laser pulses. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Artificial Intelligence: A Selected Bibliography.

    Science.gov (United States)

    Smith, Linda C., Comp.

    1984-01-01

    This 19-item annotated bibliography introducing the literature of artificial intelligence (AI) is arranged by type of material--handbook, books (general interest, textbooks, collected readings), journals and newsletters, and conferences and workshops. The availability of technical reports from AI laboratories at universities and private companies…

  2. Artificial epitaxy of indium antimonide

    International Nuclear Information System (INIS)

    Ershov, V.I.; Givargizov, E.I.

    1987-01-01

    The results of the experiments on recrystallization of thin InSb films deposited on oxidized silicon by flash evaporation with ionized beams are given. Artificial microreliefs (topographic and thermal ones) were used for controlling the growth process. An orientation mechanism of the growing film by the microrelief is discussed. The experiments on preparation of regular single-crystal islands are described

  3. Hybrid Applications Of Artificial Intelligence

    Science.gov (United States)

    Borchardt, Gary C.

    1988-01-01

    STAR, Simple Tool for Automated Reasoning, is interactive, interpreted programming language for development and operation of artificial-intelligence application systems. Couples symbolic processing with compiled-language functions and data structures. Written in C language and currently available in UNIX version (NPO-16832), and VMS version (NPO-16965).

  4. Artificial Intelligence: Applications in Education.

    Science.gov (United States)

    Thorkildsen, Ron J.; And Others

    1986-01-01

    Artificial intelligence techniques are used in computer programs to search out rapidly and retrieve information from very large databases. Programing advances have also led to the development of systems that provide expert consultation (expert systems). These systems, as applied to education, are the primary emphasis of this article. (LMO)

  5. Artificial Intelligence and Science Education.

    Science.gov (United States)

    Good, Ron

    1987-01-01

    Defines artificial intelligence (AI) in relation to intelligent computer-assisted instruction (ICAI) and science education. Provides a brief background of AI work, examples of expert systems, examples of ICAI work, and addresses problems facing AI workers that have implications for science education. Proposes a revised model of the Karplus/Renner…

  6. Research and applications: Artificial intelligence

    Science.gov (United States)

    Chaitin, L. J.; Duda, R. O.; Johanson, P. A.; Raphael, B.; Rosen, C. A.; Yates, R. A.

    1970-01-01

    The program is reported for developing techniques in artificial intelligence and their application to the control of mobile automatons for carrying out tasks autonomously. Visual scene analysis, short-term problem solving, and long-term problem solving are discussed along with the PDP-15 simulator, LISP-FORTRAN-MACRO interface, resolution strategies, and cost effectiveness.

  7. Artificial Promoters for Metabolic Optimization

    DEFF Research Database (Denmark)

    Jensen, Peter Ruhdal; Hammer, Karin

    1998-01-01

    In this article, we review some of the expression systems that are available for Metabolic Control Analysis and Metabolic Engineering, and examine their advantages and disadvantages in different contexts. In a recent approach, artificial promoters for modulating gene expression in micro-organisms...

  8. What Is Artificial Intelligence Anyway?

    Science.gov (United States)

    Kurzweil, Raymond

    1985-01-01

    Examines the past, present, and future status of Artificial Intelligence (AI). Acknowledges the limitations of AI but proposes possible areas of application and further development. Urges a concentration on the unique strengths of machine intelligence rather than a copying of human intelligence. (ML)

  9. Artificial Intelligence: The Expert Way.

    Science.gov (United States)

    Bitter, Gary G.

    1989-01-01

    Discussion of artificial intelligence (AI) and expert systems focuses on their use in education. Characteristics of good expert systems are explained; computer software programs that contain applications of AI are described, highlighting one used to help educators identify learning-disabled students; and the future of AI is discussed. (LRW)

  10. Electrophotometric observations of artificial satellites

    International Nuclear Information System (INIS)

    Vovchyk, Yeva; Blagodyr, Yaroslav; Kraynyuk, Gennadiy; Bilinsky, Andriy; Lohvynenko, Alexander; Klym, Bogdan; Pochapsky, Yevhen

    2004-01-01

    Problems associated with polarimetric observations of low Earth orbit artificial satellites as important solar system objects are discussed. The instrumentation (the optical and mechanical parts, the control and drive electronics, and the application software) for performing such observations is also described

  11. Artificial life, the new paradigm

    International Nuclear Information System (INIS)

    Martinez Paez, Jose Jesus

    1998-01-01

    A chronological synthesis of the most important facts is presented in the theoretical development and computational simulation that they have taken to the formation of a new paradigm that is known as artificial life; their characteristics and their main investigation lines are analyzed. Finally, a description of its work is made in the National University of Colombia

  12. Artificial intelligence approaches in statistics

    International Nuclear Information System (INIS)

    Phelps, R.I.; Musgrove, P.B.

    1986-01-01

    The role of pattern recognition and knowledge representation methods from Artificial Intelligence within statistics is considered. Two areas of potential use are identified and one, data exploration, is used to illustrate the possibilities. A method is presented to identify and separate overlapping groups within cluster analysis, using an AI approach. The potential of such ''intelligent'' approaches is stressed

  13. Artificial Intelligence Assists Ultrasonic Inspection

    Science.gov (United States)

    Schaefer, Lloyd A.; Willenberg, James D.

    1992-01-01

    Subtle indications of flaws extracted from ultrasonic waveforms. Ultrasonic-inspection system uses artificial intelligence to help in identification of hidden flaws in electron-beam-welded castings. System involves application of flaw-classification logic to analysis of ultrasonic waveforms.

  14. Artificial Neural Network applied to lightning flashes

    Science.gov (United States)

    Gin, R. B.; Guedes, D.; Bianchi, R.

    2013-05-01

    The development of video cameras enabled cientists to study lightning discharges comportment with more precision. The main goal of this project is to create a system able to detect images of lightning discharges stored in videos and classify them using an Artificial Neural Network (ANN)using C Language and OpenCV libraries. The developed system, can be split in two different modules: detection module and classification module. The detection module uses OpenCV`s computer vision libraries and image processing techniques to detect if there are significant differences between frames in a sequence, indicating that something, still not classified, occurred. Whenever there is a significant difference between two consecutive frames, two main algorithms are used to analyze the frame image: brightness and shape algorithms. These algorithms detect both shape and brightness of the event, removing irrelevant events like birds, as well as detecting the relevant events exact position, allowing the system to track it over time. The classification module uses a neural network to classify the relevant events as horizontal or vertical lightning, save the event`s images and calculates his number of discharges. The Neural Network was implemented using the backpropagation algorithm, and was trained with 42 training images , containing 57 lightning events (one image can have more than one lightning). TheANN was tested with one to five hidden layers, with up to 50 neurons each. The best configuration achieved a success rate of 95%, with one layer containing 20 neurons (33 test images with 42 events were used in this phase). This configuration was implemented in the developed system to analyze 20 video files, containing 63 lightning discharges previously manually detected. Results showed that all the lightning discharges were detected, many irrelevant events were unconsidered, and the event's number of discharges was correctly computed. The neural network used in this project achieved a

  15. Pathogenesis of motor neuron disease

    Institute of Scientific and Technical Information of China (English)

    Xuefei Wang

    2006-01-01

    OBJECTIVE: To summarize and analyze the factors and theories related to the attack of motor neuron disease, and comprehensively investigate the pathogenesis of motor neuron disease.DATA SOURCES: A search of Pubmed database was undertaken to identify articles about motor neuron disease published in English from January 1994 to June 2006 by using the keywords of "neurodegenerative diseases". Other literatures were collected by retrieving specific journals and articles.STUDY SELECTION: The data were checked primarily, articles related to the pathogenesis of motor neuron disease were involved, and those obviously irrelated to the articles were excluded.DATA EXTRACTION: Totally 54 articles were collected, 30 of them were involved, and the other 24 were excluded.DATA SYNTHESIS: The pathogenesis of motor neuron disease has multiple factors, and the present related theories included free radical oxidation, excitotoxicity, genetic and immune factors, lack of neurotrophic factor,injury of neurofilament, etc. The studies mainly come from transgenic animal models, cell culture in vitro and patients with familial motor neuron disease, but there are still many restrictions and disadvantages.CONCLUSION: It is necessary to try to find whether there is internal association among different mechanisms,comprehensively investigate the pathogenesis of motor neuron diseases, in order to provide reliable evidence for the clinical treatment.

  16. ARTIFICIAL INTELLIGENCE APPLICATIONS IN THE FINANCIAL SECTOR

    OpenAIRE

    Adrian Cozgarea; Gabriel Cozgarea; Andrei Stanciu

    2008-01-01

    The present paper exposes some of artificial intelligence specific technologies regarding financial sector. Through non-deterministic solutions and simple algorithms, artificial intelligence could become a base alternative for solving financial problems which require complex mathematic calculations or complex optimization.

  17. Inteligência artificial aplicada à Zootecnia Artificial intelligence in Animal Science

    Directory of Open Access Journals (Sweden)

    Ernane José Xavier Costa

    2009-07-01

    Full Text Available Os sistemas biológicos são surpreendentemente flexíveis pra processar informação proveniente do mundo real. Alguns organismos biológicos possuem uma unidade central de processamento denominada de cérebro. O cérebro humano consiste de 10(11 neurônios e realiza processamento inteligente de forma exata e subjetiva. A Inteligência Artificial (IA tenta trazer para o mundo da computação digital a heurística dos sistemas biológicos de várias maneiras, mas, ainda resta muito para que isso seja concretizado. No entanto, algumas técnicas como Redes neurais artificiais e lógica fuzzy tem mostrado efetivas para resolver problemas complexos usando a heurística dos sistemas biológicos. Recentemente o numero de aplicação dos métodos da IA em sistemas zootécnicos tem aumentado significativamente. O objetivo deste artigo é explicar os princípios básicos da resolução de problemas usando heurística e demonstrar como a IA pode ser aplicada para construir um sistema especialista para resolver problemas na área de zootecnia.Biological systems are surprising flexible in processing information in the real world. Some biological organisms have a central unit processing named brain. The human's brain, consisting of 10(11 neurons, realizes intelligent information processing based on exact and commonsense reasoning. Artificial intelligence (AI has been trying to implement biological intelligence in computers in various ways, but is still far from real one. Therefore, there are approaches like Symbolic AI, Artificial Neural Network and Fuzzy system that partially successful in implementing heuristic from biological intelligence. Many recent applications of these approaches show an increased interest in animal science research. The main goal of this article is to explain the principles of heuristic problem-solving approach and to demonstrate how they can be applied to building knowledge-based systems for animal science problem solving.

  18. Simulating synchronization in neuronal networks

    Science.gov (United States)

    Fink, Christian G.

    2016-06-01

    We discuss several techniques used in simulating neuronal networks by exploring how a network's connectivity structure affects its propensity for synchronous spiking. Network connectivity is generated using the Watts-Strogatz small-world algorithm, and two key measures of network structure are described. These measures quantify structural characteristics that influence collective neuronal spiking, which is simulated using the leaky integrate-and-fire model. Simulations show that adding a small number of random connections to an otherwise lattice-like connectivity structure leads to a dramatic increase in neuronal synchronization.

  19. Glial tumors with neuronal differentiation.

    Science.gov (United States)

    Park, Chul-Kee; Phi, Ji Hoon; Park, Sung-Hye

    2015-01-01

    Immunohistochemical studies for neuronal differentiation in glial tumors revealed subsets of tumors having both characteristics of glial and neuronal lineages. Glial tumors with neuronal differentiation can be observed with diverse phenotypes and histologic grades. The rosette-forming glioneuronal tumor of the fourth ventricle and papillary glioneuronal tumor have been newly classified as distinct disease entities. There are other candidates for classification, such as the glioneuronal tumor without pseudopapillary architecture, glioneuronal tumor with neuropil-like islands, and the malignant glioneuronal tumor. The clinical significance of these previously unclassified tumors should be confirmed. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. Mechanosensing in hypothalamic osmosensory neurons.

    Science.gov (United States)

    Prager-Khoutorsky, Masha

    2017-11-01

    Osmosensory neurons are specialized cells activated by increases in blood osmolality to trigger thirst, secretion of the antidiuretic hormone vasopressin, and elevated sympathetic tone during dehydration. In addition to multiple extrinsic factors modulating their activity, osmosensory neurons are intrinsically osmosensitive, as they are activated by increased osmolality in the absence of neighboring cells or synaptic contacts. This intrinsic osmosensitivity is a mechanical process associated with osmolality-induced changes in cell volume. This review summarises recent findings revealing molecular mechanisms underlying the mechanical activation of osmosensory neurons and highlighting important roles of microtubules, actin, and mechanosensitive ion channels in this process. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. From Neurons to Brain: Adaptive Self-Wiring of Neurons

    OpenAIRE

    Segev, Ronen; Ben-Jacob, Eshel

    1998-01-01

    During embryonic morpho-genesis, a collection of individual neurons turns into a functioning network with unique capabilities. Only recently has this most staggering example of emergent process in the natural world, began to be studied. Here we propose a navigational strategy for neurites growth cones, based on sophisticated chemical signaling. We further propose that the embryonic environment (the neurons and the glia cells) acts as an excitable media in which concentric and spiral chemical ...

  2. Artificial humidification for the mechanically ventilated patient.

    Science.gov (United States)

    Selvaraj, N

    Caring for patients who are mechanically ventilated poses many challenges for critical care nurses. It is important to humidify the patient's airways artificially to prevent complications such as ventilator-associated pneumonia. There is no gold standard to determine which type of humidification is best for patients who are artificially ventilated. This article provides an overview of commonly used artificial humidification for mechanically ventilated patients and discusses nurses' responsibilities in caring for patients receiving artificial humidification.

  3. Imaging of intracranial neuronal and mixed neuronal-glial tumours

    International Nuclear Information System (INIS)

    Cui Shimin; Qin Jinxi; Zhang Leili; Liu Meili; Jin Song; Yan Shixin; Liu Li; Dai Weiying; Li Tao; Gao Man

    2001-01-01

    Objective: To investigate the characteristic clinical, imaging , and pathologic findings of intracranial neuronal and mixed neuronal-glial tumours. Methods: The imaging findings of surgery and pathobiology proved intracranial neuronal and mixed neuronal-glial tumours in 14 cases (7 male and 7 female, ranging in age from 6-56 years; mean age 33.8 years) were retrospectively analyzed. Results: Eight gangliogliomas were located in the frontal lobe (4 cases), temporal lobe (1 case), front- temporal lobe (2 cases), and pons (1 case). They appeared as iso-or low density on CT, iso-or low signal intensity on T 1 WI, and high signal intensity on T 2 WI on MR imaging. Two central neurocytomas were located in the supratentorial ventricles. Four desmoplastic gangliogliomas were seen as cystic masses, appearing as low signal intensity on T 1 WI and high signal intensity on T 2 WI. Conclusion: Intracranial neuronal and mixed neuronal-glial tumours had imaging characteristics. Combined with clinical history, it was possible to make a tendency preoperative diagnosis using CT or MR

  4. Perceptron-like computation based on biologically-inspired neurons with heterosynaptic mechanisms

    Science.gov (United States)

    Kaluza, Pablo; Urdapilleta, Eugenio

    2014-10-01

    Perceptrons are one of the fundamental paradigms in artificial neural networks and a key processing scheme in supervised classification tasks. However, the algorithm they provide is given in terms of unrealistically simple processing units and connections and therefore, its implementation in real neural networks is hard to be fulfilled. In this work, we present a neural circuit able to perform perceptron's computation based on realistic models of neurons and synapses. The model uses Wang-Buzsáki neurons with coupling provided by axodendritic and axoaxonic synapses (heterosynapsis). The main characteristics of the feedforward perceptron operation are conserved, which allows to combine both approaches: whereas the classical artificial system can be used to learn a particular problem, its solution can be directly implemented in this neural circuit. As a result, we propose a biologically-inspired system able to work appropriately in a wide range of frequencies and system parameters, while keeping robust to noise and error.

  5. [Preparation of nano-nacre artificial bone].

    Science.gov (United States)

    Chen, Jian-ting; Tang, Yong-zhi; Zhang, Jian-gang; Wang, Jian-jun; Xiao, Ying

    2008-12-01

    To assess the improvements in the properties of nano-nacre artificial bone prepared on the basis of nacre/polylactide acid composite artificial bone and its potential for clinical use. The compound of nano-scale nacre powder and poly-D, L-lactide acid (PDLLA) was used to prepare the cylindrical hollow artificial bone, whose properties including raw material powder scale, pore size, porosity and biomechanical characteristics were compared with another artificial bone made of micron-scale nacre powder and PDLLA. Scanning electron microscope showed that the average particle size of the nano-nacre powder was 50.4-/+12.4 nm, and the average pore size of the artificial bone prepared using nano-nacre powder was 215.7-/+77.5 microm, as compared with the particle size of the micron-scale nacre powder of 5.0-/+3.0 microm and the pore size of the resultant artificial bone of 205.1-/+72.0 microm. The porosities of nano-nacre artificial bone and the micron-nacre artificial bone were (65.4-/+2.9)% and (53.4-/+2.2)%, respectively, and the two artificial bones had comparable compressive strength and Young's modulus, but the flexural strength of the nano-nacre artificial bone was lower than that of the micro-nacre artificial bone. The nano-nacre artificial bone allows better biodegradability and possesses appropriate pore size, porosity and biomechanical properties for use as a promising material in bone tissue engineering.

  6. Artificial Intelligence and Its Importance in Education.

    Science.gov (United States)

    Tilmann, Martha J.

    Artificial intelligence, or the study of ideas that enable computers to be intelligent, is discussed in terms of what it is, what it has done, what it can do, and how it may affect the teaching of tomorrow. An extensive overview of artificial intelligence examines its goals and applications and types of artificial intelligence including (1) expert…

  7. Impact of Artificial Intelligence on Economic Theory

    OpenAIRE

    Tshilidzi Marwala

    2015-01-01

    Artificial intelligence has impacted many aspects of human life. This paper studies the impact of artificial intelligence on economic theory. In particular we study the impact of artificial intelligence on the theory of bounded rationality, efficient market hypothesis and prospect theory.

  8. Tinbergen on mirror neurons

    Science.gov (United States)

    Heyes, Cecilia

    2014-01-01

    Fifty years ago, Niko Tinbergen defined the scope of behavioural biology with his four problems: causation, ontogeny, survival value and evolution. About 20 years ago, there was another highly significant development in behavioural biology—the discovery of mirror neurons (MNs). Here, I use Tinbergen's original four problems (rather than the list that appears in textbooks) to highlight the differences between two prominent accounts of MNs, the genetic and associative accounts; to suggest that the latter provides the defeasible ‘best explanation’ for current data on the causation and ontogeny of MNs; and to argue that functional analysis, of the kind that Tinbergen identified somewhat misleadingly with studies of ‘survival value’, should be a high priority for future research. In this kind of functional analysis, system-level theories would assign MNs a small, but potentially important, role in the achievement of action understanding—or another social cognitive function—by a production line of interacting component processes. These theories would be tested by experimental intervention in human and non-human animal samples with carefully documented and controlled developmental histories. PMID:24778376

  9. Neurons on the couch.

    Science.gov (United States)

    Marić, Nadja P; Jašović-Gašić, Miroslava

    2010-12-01

    A hundred years after psychoanalysis was introduced, neuroscience has taken a giant step forward. It seems nowadays that effects of psychotherapy could be monitored and measured by state-of-the art brain imaging techniques. Today, the psychotherapy is considered as a strategic and purposeful environmental influence intended to enhance learning. Since gene expression is regulated by environmental influences throughout life and these processes create brain architecture and influence the strength of synaptic connections, psychotherapy (as a kind of learning) should be explored in the context of aforementioned paradigm. In other words, when placing a client on the couch, therapist actually placed client's neuronal network; while listening and talking, expressing and analyzing, experiencing transference and counter transference, therapist tends to stabilize synaptic connections and influence dendritic growth by regulating gene-transcriptional activity. Therefore, we strongly believe that, in the near future, an increasing knowledge on cellular and molecular interactions and mechanisms of action of different psycho- and pharmaco-therapeutic procedures will enable us to tailor a sophisticated therapeutic approach toward a person, by combining major therapeutic strategies in psychiatry on the basis of rational goals and evidence-based therapeutic expectations.

  10. Tinbergen on mirror neurons.

    Science.gov (United States)

    Heyes, Cecilia

    2014-01-01

    Fifty years ago, Niko Tinbergen defined the scope of behavioural biology with his four problems: causation, ontogeny, survival value and evolution. About 20 years ago, there was another highly significant development in behavioural biology-the discovery of mirror neurons (MNs). Here, I use Tinbergen's original four problems (rather than the list that appears in textbooks) to highlight the differences between two prominent accounts of MNs, the genetic and associative accounts; to suggest that the latter provides the defeasible 'best explanation' for current data on the causation and ontogeny of MNs; and to argue that functional analysis, of the kind that Tinbergen identified somewhat misleadingly with studies of 'survival value', should be a high priority for future research. In this kind of functional analysis, system-level theories would assign MNs a small, but potentially important, role in the achievement of action understanding-or another social cognitive function-by a production line of interacting component processes. These theories would be tested by experimental intervention in human and non-human animal samples with carefully documented and controlled developmental histories.

  11. Artificial Intelligence and Moral intelligence

    Directory of Open Access Journals (Sweden)

    Laura Pana

    2008-07-01

    Full Text Available We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined, even unpredictable conduct, 2- entities endowed with diverse or even multiple intelligence forms, like moral intelligence, 3- open and, even, free-conduct performing systems (with specific, flexible and heuristic mechanisms and procedures of decision, 4 – systems which are open to education, not just to instruction, 5- entities with “lifegraphy”, not just “stategraphy”, 6- equipped not just with automatisms but with beliefs (cognitive and affective complexes, 7- capable even of reflection (“moral life” is a form of spiritual, not just of conscious activity, 8 – elements/members of some real (corporal or virtual community, 9 – cultural beings: free conduct gives cultural value to the action of a ”natural” or artificial being. Implementation of such characteristics does not necessarily suppose efforts to design, construct and educate machines like human beings. The human moral code is irremediably imperfect: it is a morality of preference, of accountability (not of responsibility and a morality of non-liberty, which cannot be remedied by the invention of ethical systems, by the circulation of ideal values and by ethical (even computing education. But such an imperfect morality needs perfect instruments for its implementation: applications of special logic fields; efficient psychological (theoretical and technical attainments to endow the machine not just with intelligence, but with conscience and even spirit; comprehensive technical

  12. Understanding Neuronal Mechanisms of Epilepsy ...

    Indian Academy of Sciences (India)

    Admin

    α subunit of Rat Brain type IIA Voltage Gated Sodium Channel and geneticin selection ..... scaling the mother wavelet. Scale = 1/ .... through dynamic clamp. Dynamic Clamp ... It has been shown that like in vivo neurons, cortical networks in.

  13. Imitation, mirror neurons and autism.

    Science.gov (United States)

    Williams, J H; Whiten, A; Suddendorf, T; Perrett, D I

    2001-06-01

    Various deficits in the cognitive functioning of people with autism have been documented in recent years but these provide only partial explanations for the condition. We focus instead on an imitative disturbance involving difficulties both in copying actions and in inhibiting more stereotyped mimicking, such as echolalia. A candidate for the neural basis of this disturbance may be found in a recently discovered class of neurons in frontal cortex, 'mirror neurons' (MNs). These neurons show activity in relation both to specific actions performed by self and matching actions performed by others, providing a potential bridge between minds. MN systems exist in primates without imitative and 'theory of mind' abilities and we suggest that in order for them to have become utilized to perform social cognitive functions, sophisticated cortical neuronal systems have evolved in which MNs function as key elements. Early developmental failures of MN systems are likely to result in a consequent cascade of developmental impairments characterised by the clinical syndrome of autism.

  14. Information processing by neuronal populations

    National Research Council Canada - National Science Library

    Hölscher, Christian; Munk, Matthias

    2009-01-01

    ... simultaneously recorded spike trains 120 Mark Laubach, Nandakumar S. Narayanan, and Eyal Y. Kimchi Part III Neuronal population information coding and plasticity in specific brain areas 149 7 F...

  15. Chimera states in bursting neurons

    OpenAIRE

    Bera, Bidesh K.; Ghosh, Dibakar; Lakshmanan, M.

    2015-01-01

    We study the existence of chimera states in pulse-coupled networks of bursting Hindmarsh-Rose neurons with nonlocal, global and local (nearest neighbor) couplings. Through a linear stability analysis, we discuss the behavior of stability function in the incoherent (i.e. disorder), coherent, chimera and multi-chimera states. Surprisingly, we find that chimera and multi-chimera states occur even using local nearest neighbor interaction in a network of identical bursting neurons alone. This is i...

  16. Progress in artificial vision through suprachoroidal retinal implants

    Science.gov (United States)

    Bareket, Lilach; Barriga-Rivera, Alejandro; Zapf, Marc Patrick; Lovell, Nigel H.; Suaning, Gregg J.

    2017-08-01

    Retinal implants have proven their ability to restore visual sensation to people with degenerative retinopathy, characterized by photoreceptor cell death and the retina’s inability to sense light. Retinal bionics operate by electrically stimulating the surviving neurons in the retina, thus triggering the transfer of visual sensory information to the brain. Suprachoroidal implants were first investigated in Australia in the 1950s. In this approach, the neuromodulation hardware is positioned between the sclera and the choroid, thus providing significant surgical and safety benefits for patients, with the potential to maintain residual vision combined with the artificial input from the device. Here we review the latest advances and state of the art devices for suprachoroidal prostheses, highlight future technologies and discuss challenges and perspectives towards improved rehabilitation of vision.

  17. An artificial neural network model for periodic trajectory generation

    Science.gov (United States)

    Shankar, S.; Gander, R. E.; Wood, H. C.

    A neural network model based on biological systems was developed for potential robotic application. The model consists of three interconnected layers of artificial neurons or units: an input layer subdivided into state and plan units, an output layer, and a hidden layer between the two outer layers which serves to implement nonlinear mappings between the input and output activation vectors. Weighted connections are created between the three layers, and learning is effected by modifying these weights. Feedback connections between the output and the input state serve to make the network operate as a finite state machine. The activation vector of the plan units of the input layer emulates the supraspinal commands in biological central pattern generators in that different plan activation vectors correspond to different sequences or trajectories being recalled, even with different frequencies. Three trajectories were chosen for implementation, and learning was accomplished in 10,000 trials. The fault tolerant behavior, adaptiveness, and phase maintenance of the implemented network are discussed.

  18. Torsional carbon nanotube artificial muscles.

    Science.gov (United States)

    Foroughi, Javad; Spinks, Geoffrey M; Wallace, Gordon G; Oh, Jiyoung; Kozlov, Mikhail E; Fang, Shaoli; Mirfakhrai, Tissaphern; Madden, John D W; Shin, Min Kyoon; Kim, Seon Jeong; Baughman, Ray H

    2011-10-28

    Rotary motors of conventional design can be rather complex and are therefore difficult to miniaturize; previous carbon nanotube artificial muscles provide contraction and bending, but not rotation. We show that an electrolyte-filled twist-spun carbon nanotube yarn, much thinner than a human hair, functions as a torsional artificial muscle in a simple three-electrode electrochemical system, providing a reversible 15,000° rotation and 590 revolutions per minute. A hydrostatic actuation mechanism, as seen in muscular hydrostats in nature, explains the simultaneous occurrence of lengthwise contraction and torsional rotation during the yarn volume increase caused by electrochemical double-layer charge injection. The use of a torsional yarn muscle as a mixer for a fluidic chip is demonstrated.

  19. Tadpole-like artificial micromotor

    Science.gov (United States)

    Liu, Limei; Liu, Mei; Su, Yajun; Dong, Yonggang; Zhou, Wei; Zhang, Lina; Zhang, Hui; Dong, Bin; Chi, Lifeng

    2015-01-01

    We describe a polymer-based artificial tadpole-like micromotor, which is fabricated through the electrospinning technique. By incorporating functional materials onto its surface or within its body, the resulting tadpole-like micromotor can not only move autonomously in an aqueous solution with a flexible tail, but also exhibit thermo- and magnetic responsive properties.We describe a polymer-based artificial tadpole-like micromotor, which is fabricated through the electrospinning technique. By incorporating functional materials onto its surface or within its body, the resulting tadpole-like micromotor can not only move autonomously in an aqueous solution with a flexible tail, but also exhibit thermo- and magnetic responsive properties. Electronic supplementary information (ESI) available: Experimental section, Fig. S1-S3 and Video S1-S4. See DOI: 10.1039/c4nr06621a

  20. Computer automation and artificial intelligence

    International Nuclear Information System (INIS)

    Hasnain, S.B.

    1992-01-01

    Rapid advances in computing, resulting from micro chip revolution has increased its application manifold particularly for computer automation. Yet the level of automation available, has limited its application to more complex and dynamic systems which require an intelligent computer control. In this paper a review of Artificial intelligence techniques used to augment automation is presented. The current sequential processing approach usually adopted in artificial intelligence has succeeded in emulating the symbolic processing part of intelligence, but the processing power required to get more elusive aspects of intelligence leads towards parallel processing. An overview of parallel processing with emphasis on transputer is also provided. A Fuzzy knowledge based controller for amination drug delivery in muscle relaxant anesthesia on transputer is described. 4 figs. (author)

  1. Anesthesiology, automation, and artificial intelligence.

    Science.gov (United States)

    Alexander, John C; Joshi, Girish P

    2018-01-01

    There have been many attempts to incorporate automation into the practice of anesthesiology, though none have been successful. Fundamentally, these failures are due to the underlying complexity of anesthesia practice and the inability of rule-based feedback loops to fully master it. Recent innovations in artificial intelligence, especially machine learning, may usher in a new era of automation across many industries, including anesthesiology. It would be wise to consider the implications of such potential changes before they have been fully realized.

  2. Scheduling with artificial neural networks

    OpenAIRE

    Gürgün, Burçkaan

    1993-01-01

    Ankara : Department of Industrial Engineering and The Institute of Engineering and Sciences of Bilkent Univ., 1993. Thesis (Master's) -- Bilkent University, 1993. Includes bibliographical references leaves 59-65. Artificial Neural Networks (ANNs) attempt to emulate the massively parallel and distributed processing of the human brain. They are being examined for a variety of problems that have been very difficult to solve. The objective of this thesis is to review the curren...

  3. Important Themas in Artificial Intelligence

    OpenAIRE

    Šudoma, Petr

    2013-01-01

    The paper studies description logics as a method of field of artificial intelligence, describes history of knowledge representation as series of events leading to founding of description logics. Furthermore the paper compares description logics with their predecessor, the frame systems. Syntax, semantics and description logics naming convention is also presented and algorithms solving common knowledge representation tasks with usage of description logics are described. Paper compares computat...

  4. Bioengineering of artificial lymphoid organs

    OpenAIRE

    NOSENKO M.A.; DRUTSKAYA M.S.; MOISENOVICH M.M.; NEDOSPASOV S.A.

    2016-01-01

    This review addresses the issue of bioengineering of artificial lymphoid organs.Progress in this field may help to better understand the nature of the structure-function relations that exist in immune organs. Artifical lymphoid organs may also be advantageous in the therapy or correction of immunodefficiencies, autoimmune diseases, and cancer. The structural organization, development, and function of lymphoid tissue are analyzed with a focus on the role of intercellular contacts and on the cy...

  5. Automated Scheduling Via Artificial Intelligence

    Science.gov (United States)

    Biefeld, Eric W.; Cooper, Lynne P.

    1991-01-01

    Artificial-intelligence software that automates scheduling developed in Operations Mission Planner (OMP) research project. Software used in both generation of new schedules and modification of existing schedules in view of changes in tasks and/or available resources. Approach based on iterative refinement. Although project focused upon scheduling of operations of scientific instruments and other equipment aboard spacecraft, also applicable to such terrestrial problems as scheduling production in factory.

  6. Artificial intelligence and computer vision

    CERN Document Server

    Li, Yujie

    2017-01-01

    This edited book presents essential findings in the research fields of artificial intelligence and computer vision, with a primary focus on new research ideas and results for mathematical problems involved in computer vision systems. The book provides an international forum for researchers to summarize the most recent developments and ideas in the field, with a special emphasis on the technical and observational results obtained in the past few years.

  7. Artificial wetlands - yes or no?

    Czech Academy of Sciences Publication Activity Database

    Horák, Václav; Lusk, Stanislav; Halačka, Karel; Lusková, Věra

    2004-01-01

    Roč. 4, č. 2 (2004), s. 119-127 ISSN 1642-3593. [International Symposium on the Ecology of Fluvial Fishes /9./. Lodz, 23.06.2003-26.06.2003] R&D Projects: GA AV ČR IBS6093007; GA AV ČR KSK6005114 Institutional research plan: CEZ:AV0Z6093917 Keywords : floodplain * artificial wetlands * fish communities Subject RIV: EH - Ecology, Behaviour

  8. Viewpoint: Artificial Intelligence and Labour

    OpenAIRE

    Samothrakis, Spyridon

    2018-01-01

    The welfare of modern societies has been intrinsically linked to wage labour. With some exceptions, the modern human has to sell her labour-power to be able reproduce biologically and socially. Thus, a lingering fear of technological unemployment features predominately as a theme among Artificial Intelligence researchers. In this short paper we show that, if past trends are anything to go by, this fear is irrational. On the contrary, we argue that the main problem humanity will be facing is t...

  9. Artificial Intelligence, Employment, and Income

    OpenAIRE

    Nilsson, Nils J.

    1984-01-01

    Artificial intelligence (AI) will have profound societal effects. It promises potential benefits (and may also pose risks) in education, defense, business, law and science. In this article we explore how AI is likely to affect employment and the distribution of income. We argue that AI will indeed reduce drastically the need of human toil. We also note that some people fear the automation of work by machines and the resulting of unemployment. Yet, since the majority of us probably would rathe...

  10. Towards photovoltaic powered artificial retina

    Directory of Open Access Journals (Sweden)

    Santiago Silvestre

    2011-11-01

    Full Text Available The aim of this article is to provide an overview of current and future concepts in the field of retinal prostheses, and is focused on the power supply based on solar energy conversion; we introduce the possibility of using PV minimodules as power supply for a new concept of retinal prostheses: Photovoltaic Powered Artificial Retina (PVAR. Main characteristics of these PV modules are presented showing its potential for this application.

  11. Behavior acquisition in artificial agents

    OpenAIRE

    Thurau, Christian

    2006-01-01

    Computational skill acquisition in robots and simulated agents has been a topic of increasing popularity throughout the last years. Despite impressive progress, autonomous behavior at a level of animals and humans are not yet replicated by machines. Especially when a complex environment demands versatile, goal-oriented behavior, current artificial systems show shortcomings. Consider for instance modern 3D computer games. Despite their key role for more emersive game experience, surprisingly l...

  12. New twist on artificial muscles.

    Science.gov (United States)

    Haines, Carter S; Li, Na; Spinks, Geoffrey M; Aliev, Ali E; Di, Jiangtao; Baughman, Ray H

    2016-10-18

    Lightweight artificial muscle fibers that can match the large tensile stroke of natural muscles have been elusive. In particular, low stroke, limited cycle life, and inefficient energy conversion have combined with high cost and hysteretic performance to restrict practical use. In recent years, a new class of artificial muscles, based on highly twisted fibers, has emerged that can deliver more than 2,000 J/kg of specific work during muscle contraction, compared with just 40 J/kg for natural muscle. Thermally actuated muscles made from ordinary polymer fibers can deliver long-life, hysteresis-free tensile strokes of more than 30% and torsional actuation capable of spinning a paddle at speeds of more than 100,000 rpm. In this perspective, we explore the mechanisms and potential applications of present twisted fiber muscles and the future opportunities and challenges for developing twisted muscles having improved cycle rates, efficiencies, and functionality. We also demonstrate artificial muscle sewing threads and textiles and coiled structures that exhibit nearly unlimited actuation strokes. In addition to robotics and prosthetics, future applications include smart textiles that change breathability in response to temperature and moisture and window shutters that automatically open and close to conserve energy.

  13. Artificial life: The coming evolution

    Energy Technology Data Exchange (ETDEWEB)

    Farmer, J.D. (Los Alamos National Lab., NM (USA) Santa Fe Inst., NM (USA)); Belin, A.d' A. (Shute, Mihaly, and Weinberger, Santa Fe, NM (USA))

    1990-01-01

    Within fifty to a hundred years a new class of organisms is likely to emerge. These organisms will be artificial in the sense that they will originally be designed by humans. However, they will reproduce, and will evolve into something other than their initial form; they will be alive'' under any reasonable definition of the word. These organisms will evolve in a fundamentally different manner than contemporary biological organisms, since their reproduction will be under at least partial conscious control, giving it a Lamarckian component. The pace of evolutionary change consequently will be extremely rapid. The advent of artificial life will be the most significant historical event since the emergence of human beings. The impact on humanity and the biosphere could be enormous, larger than the industrial revolution, nuclear weapons, or environmental pollution. We must take steps now to shape the emergence of artificial organisms; they have potential to be either the ugliest terrestrial disaster, or the most beautiful creation of humanity. 22 refs., 3 figs.

  14. Philosophical foundations of artificial consciousness.

    Science.gov (United States)

    Chrisley, Ron

    2008-10-01

    Consciousness is often thought to be that aspect of mind that is least amenable to being understood or replicated by artificial intelligence (AI). The first-personal, subjective, what-it-is-like-to-be-something nature of consciousness is thought to be untouchable by the computations, algorithms, processing and functions of AI method. Since AI is the most promising avenue toward artificial consciousness (AC), the conclusion many draw is that AC is even more doomed than AI supposedly is. The objective of this paper is to evaluate the soundness of this inference. The results are achieved by means of conceptual analysis and argumentation. It is shown that pessimism concerning the theoretical possibility of artificial consciousness is unfounded, based as it is on misunderstandings of AI, and a lack of awareness of the possible roles AI might play in accounting for or reproducing consciousness. This is done by making some foundational distinctions relevant to AC, and using them to show that some common reasons given for AC scepticism do not touch some of the (usually neglected) possibilities for AC, such as prosthetic, discriminative, practically necessary, and lagom (necessary-but-not-sufficient) AC. Along the way three strands of the author's work in AC--interactive empiricism, synthetic phenomenology, and ontologically conservative heterophenomenology--are used to illustrate and motivate the distinctions and the defences of AC they make possible.

  15. PIXE Analysis of Artificial Turf

    Science.gov (United States)

    Conlan, Skye; Chalise, Sajju; Porat, Zachary; Labrake, Scott; Vineyard, Michael

    2017-09-01

    In recent years, there has been debate regarding the use of the crumb rubber infill in artificial turf on high school and college campuses due to the potential presence of heavy metals and carcinogenic chemicals. We performed Proton-Induced X-Ray Emission (PIXE) analysis of artificial turf infill and blade samples collected from high school and college campuses around the Capital District of NYS to search for potentially toxic substances. Crumb rubber pellets were made by mixing 1g of rubber infill and 1g of epoxy. The pellets and the turf blades were bombarded with 2.2 MeV proton beams from a 1.1-MV tandem Pelletron accelerator in the Union College Ion-Beam Analysis Laboratory and x-ray energy spectra were collected with an Amptek silicon drift detector. We analyzed the spectra using GUPIX software to determine the elemental concentrations of the samples. The turf infill showed significant levels of Ti, Fe, Co, Ni, Cu, Zn, Br, and Pb. The highest concentration of Br in the crumb rubber was 1500 +/-100 ppm while the highest detectable amount of Pb concentration was 110 +/-20 ppm. The artificial turf blades showed significant levels of Ti, Fe, and Zn with only the yellow blade showing concentrations of V and Bi.

  16. Communication among neurons.

    Science.gov (United States)

    Marner, Lisbeth

    2012-04-01

    The communication among neurons is the prerequisite for the working brain. To understand the cellular, neurochemical, and structural basis of this communication, and the impacts of aging and disease on brain function, quantitative measures are necessary. This thesis evaluates several quantitative neurobiological methods with respect to possible bias and methodological issues. Stereological methods are suited for the unbiased estimation of number, length, and volumes of components of the nervous system. Stereological estimates of the total length of myelinated nerve fibers were made in white matter of post mortem brains, and the impact of aging and diseases as Schizophrenia and Alzheimer's disease were evaluated. Although stereological methods are in principle unbiased, shrinkage artifacts are difficult to account for. Positron emission tomography (PET) recordings, in conjunction with kinetic modeling, permit the quantitation of radioligand binding in brain. The novel serotonin 5-HT4 antagonist [11C]SB207145 was used as an example of the validation process for quantitative PET receptor imaging. Methods based on reference tissue as well as methods based on an arterial plasma input function were evaluated with respect to precision and accuracy. It was shown that [11C]SB207145 binding had high sensitivity to occupancy by unlabeled ligand, necessitating high specific activity in the radiosynthesis to avoid bias. The established serotonin 5-HT2A ligand [18F]altanersin was evaluated in a two-year follow-up study in elderly subjects. Application of partial volume correction of the PET data diminished the reliability of the measures, but allowed for the correct distinction between changes due to brain atrophy and receptor availability. Furthermore, a PET study of patients with Alzheimer's disease with the serotonin transporter ligand [11C]DASB showed relatively preserved serotonergic projections, despite a marked decrease in 5-HT2A receptor binding. Possible confounders are

  17. Artificial neural nets application in the cotton yarn industry

    Directory of Open Access Journals (Sweden)

    Gilberto Clóvis Antoneli

    2016-06-01

    Full Text Available The competitiveness in the yarn production sector has led companies to search for solutions to attain quality yarn at a low cost. Today, the difference between them, and thus the sector, is in the raw material, meaning processed cotton and its characteristics. There are many types of cotton with different characteristics due to its production region, harvest, storage and transportation. Yarn industries work with cotton mixtures, which makes it difficult to determine the quality of the yarn produced from the characteristics of the processed fibers. This study uses data from a conventional spinning, from a raw material made of 100% cotton, and presents a solution with artificial neural nets that determine the thread quality information, using the fibers’ characteristics values and settings of some process adjustments. In this solution a neural net of the type MultiLayer Perceptron with 11 entry neurons (8 characteristics of the fiber and 3 process adjustments, 7 output neurons (yarn quality and two types of training, Back propagation and Conjugate gradient descent. The selection and organization of the production data of the yarn industry of the cocamar® indústria de fios company are described, to apply the artificial neural nets developed. In the application of neural nets to determine yarn quality, one concludes that, although the ideal precision of absolute values is lacking, the presented solution represents an excellent tool to define yarn quality variations when modifying the raw material composition. The developed system enables a simulation to define the raw material percentage mixture to be processed in the plant using the information from the stocked cotton packs, thus obtaining a mixture that maintains the stability of the entire productive process.

  18. Fecundación Artificial

    Directory of Open Access Journals (Sweden)

    Ochoa. Fidel

    1939-10-01

    Full Text Available Por Fecundación artificial se entiende, la fecundación de una hembra sin el servicio directo del macho, es decir la introducción al aparato genital femenino, del esperma que se ha recogido por medios artificiales. Esta fecundación, practicada en debidas condiciones, tiene el mismo efecto de la fecundación natural, con las ventajas que veremos más adelante. La fecundación artificial permite explotar un reproductor a su máximum de capacidad, ya que se considera, para no hacer cálculos alegres, que un servicio de un caballo puede servir, diluido, por lo menos para cuatro yeguas, según los autores americanos, y para 10 a 15, según otros autores. El toro y el carnero pueden dar esperma suficiente en un servicio para fecundar de 10 a 12 hembras, según,los americanos, y según otros autores, hasta para 40. Los investigadores rusos han podido fecundar hasta 60 vacas con un solo servicio y han logrado con reproductores valiosos, fecundar 10.263 vacas por toro, a pesar de que éstos sólo han servido, durante un periodo de monta de sólo dos meses. Estos mismos han logrado fecundar artificialmente 2.733 ovejas con un solo carnero, y 1.403 con otro Los investigadores americanos han contado 22 servicios a un carnero vigoroso en un periodo de ocho horas, y durante este tiempo produjo esperma suficiente para haber fecundado 200 ovejas artificialmente. La fecundación artificial sirve para evitar la trasmisión de enfermedades que se contagian por el coito, tales como la durina, enfermedad ésta producida por un tripanosoma que por fortuna no existe entre nosotros. A las estaciones de monta llevan con frecuencia hembras afectadas de enfermedades como la vaginitis granulosa de la vaca, que se contagia al toro y de éste a otras hembras. Como el control sanitario de toda hembra llevada al servicio de un reproductor de estas estaciones de monta no siempre puede efectuarse por dificultades de distinta índole, mediante la fecundación artificial

  19. Electrically controllable artificial PAN muscles

    Science.gov (United States)

    Salehpoor, Karim; Shahinpoor, Mohsen; Mojarrad, Mehran

    1996-02-01

    Artificial muscles made with polyacrylonitrile (PAN) fibers are traditionally activated in electrolytic solution by changing the pH of the solution by the addition of acids and/or bases. This usually consumes a considerable amount of weak acids or bases. Furthermore, the synthetic muscle (PAN) itself has to be impregnated with an acid or a base and must have an appropriate enclosure or provision for waste collection after actuation. This work introduces a method by which the PAN muscle may be elongated or contracted in an electric field. We believe this is the first time that this has been achieved with PAN fibers as artificial muscles. In this new development the PAN muscle is first put in close contact with one of the two platinum wires (electrodes) immersed in an aqueous solution of sodium chloride. Applying an electric voltage between the two wires changes the local acidity of the solution in the regions close to the platinum wires. This is because of the ionization of sodium chloride molecules and the accumulation of Na+ and Cl- ions at the negative and positive electrode sites, respectively. This ion accumulation, in turn, is accompanied by a sharp increase and decrease of the local acidity in regions close to either of the platinum wires, respectively. An artificial muscle, in close contact with the platinum wire, because of the change in the local acidity will contract or expand depending on the polarity of the electric field. This scheme allows the experimenter to use a fixed flexible container of an electrolytic solution whose local pH can be modulated by an imposed electric field while the produced ions are basically trapped to stay in the neighborhood of a given electrode. This method of artificial muscle activation has several advantages. First, the need to use a large quantity of acidic or alkaline solutions is eliminated. Second, the use of a compact PAN muscular system is facilitated for applications in active musculoskeletal structures. Third, the

  20. An FPGA Platform for Real-Time Simulation of Spiking Neuronal Networks.

    Science.gov (United States)

    Pani, Danilo; Meloni, Paolo; Tuveri, Giuseppe; Palumbo, Francesca; Massobrio, Paolo; Raffo, Luigi

    2017-01-01

    In the last years, the idea to dynamically interface biological neurons with artificial ones has become more and more urgent. The reason is essentially due to the design of innovative neuroprostheses where biological cell assemblies of the brain can be substituted by artificial ones. For closed-loop experiments with biological neuronal networks interfaced with in silico modeled networks, several technological challenges need to be faced, from the low-level interfacing between the living tissue and the computational model to the implementation of the latter in a suitable form for real-time processing. Field programmable gate arrays (FPGAs) can improve flexibility when simple neuronal models are required, obtaining good accuracy, real-time performance, and the possibility to create a hybrid system without any custom hardware, just programming the hardware to achieve the required functionality. In this paper, this possibility is explored presenting a modular and efficient FPGA design of an in silico spiking neural network exploiting the Izhikevich model. The proposed system, prototypically implemented on a Xilinx Virtex 6 device, is able to simulate a fully connected network counting up to 1,440 neurons, in real-time, at a sampling rate of 10 kHz, which is reasonable for small to medium scale extra-cellular closed-loop experiments.

  1. Learning of time series through neuron-to-neuron instruction

    Energy Technology Data Exchange (ETDEWEB)

    Miyazaki, Y [Department of Physics, Kyoto University, Kyoto 606-8502, (Japan); Kinzel, W [Institut fuer Theoretische Physik, Universitaet Wurzburg, 97074 Wurzburg (Germany); Shinomoto, S [Department of Physics, Kyoto University, Kyoto (Japan)

    2003-02-07

    A model neuron with delayline feedback connections can learn a time series generated by another model neuron. It has been known that some student neurons that have completed such learning under the instruction of a teacher's quasi-periodic sequence mimic the teacher's time series over a long interval, even after instruction has ceased. We found that in addition to such faithful students, there are unfaithful students whose time series eventually diverge exponentially from that of the teacher. In order to understand the circumstances that allow for such a variety of students, the orbit dimension was estimated numerically. The quasi-periodic orbits in question were found to be confined in spaces with dimensions significantly smaller than that of the full phase space.

  2. Learning of time series through neuron-to-neuron instruction

    International Nuclear Information System (INIS)

    Miyazaki, Y; Kinzel, W; Shinomoto, S

    2003-01-01

    A model neuron with delayline feedback connections can learn a time series generated by another model neuron. It has been known that some student neurons that have completed such learning under the instruction of a teacher's quasi-periodic sequence mimic the teacher's time series over a long interval, even after instruction has ceased. We found that in addition to such faithful students, there are unfaithful students whose time series eventually diverge exponentially from that of the teacher. In order to understand the circumstances that allow for such a variety of students, the orbit dimension was estimated numerically. The quasi-periodic orbits in question were found to be confined in spaces with dimensions significantly smaller than that of the full phase space

  3. Internet advertising of artificial tanning in Australia.

    Science.gov (United States)

    Team, Victoria; Markovic, Milica

    2006-08-01

    Artificial tanning, defined as deliberate exposure to ultraviolet rays produced by artificial tanning devices, is a new and emerging public health issue in Australia and globally. Epidemiological research suggests that artificial tanning may contribute to the incidence of melanoma, nonmelanoma skin cancer as well as other health problems. Given that Australia has a high incidence of skin cancer, we have undertaken a study to explore how artificial tanning has been promoted to its users. The aim was to analyze the completeness and accuracy of information about artificial tanning. A content analysis of web sites of tanning salons and distributors of tanning equipment in Australia was conducted. A total of 22 web sites were analyzed. None of the solarium operators or distributors of equipment provided full information about the risks of artificial tanning. Fifty-nine percent of web advertisements had no information and 41% provided only partial information regarding the risks of artificial tanning. Pictures with the image of bronze-tanned bodies, predominantly women, were used by all web advertisers. In light of the success of sun-safety campaigns in Australia, the findings of future epidemiological research on the prevalence of artificial tanning and sociological and anthropological research on why people utilize artificial tanning should be a basis for developing effective targeted health promotion on the elimination of artificial tanning in the country.

  4. The mirror-neuron system.

    Science.gov (United States)

    Rizzolatti, Giacomo; Craighero, Laila

    2004-01-01

    A category of stimuli of great importance for primates, humans in particular, is that formed by actions done by other individuals. If we want to survive, we must understand the actions of others. Furthermore, without action understanding, social organization is impossible. In the case of humans, there is another faculty that depends on the observation of others' actions: imitation learning. Unlike most species, we are able to learn by imitation, and this faculty is at the basis of human culture. In this review we present data on a neurophysiological mechanism--the mirror-neuron mechanism--that appears to play a fundamental role in both action understanding and imitation. We describe first the functional properties of mirror neurons in monkeys. We review next the characteristics of the mirror-neuron system in humans. We stress, in particular, those properties specific to the human mirror-neuron system that might explain the human capacity to learn by imitation. We conclude by discussing the relationship between the mirror-neuron system and language.

  5. Neuronal factors determining high intelligence.

    Science.gov (United States)

    Dicke, Ursula; Roth, Gerhard

    2016-01-05

    Many attempts have been made to correlate degrees of both animal and human intelligence with brain properties. With respect to mammals, a much-discussed trait concerns absolute and relative brain size, either uncorrected or corrected for body size. However, the correlation of both with degrees of intelligence yields large inconsistencies, because although they are regarded as the most intelligent mammals, monkeys and apes, including humans, have neither the absolutely nor the relatively largest brains. The best fit between brain traits and degrees of intelligence among mammals is reached by a combination of the number of cortical neurons, neuron packing density, interneuronal distance and axonal conduction velocity--factors that determine general information processing capacity (IPC), as reflected by general intelligence. The highest IPC is found in humans, followed by the great apes, Old World and New World monkeys. The IPC of cetaceans and elephants is much lower because of a thin cortex, low neuron packing density and low axonal conduction velocity. By contrast, corvid and psittacid birds have very small and densely packed pallial neurons and relatively many neurons, which, despite very small brain volumes, might explain their high intelligence. The evolution of a syntactical and grammatical language in humans most probably has served as an additional intelligence amplifier, which may have happened in songbirds and psittacids in a convergent manner. © 2015 The Author(s).

  6. Energy Model of Neuron Activation.

    Science.gov (United States)

    Romanyshyn, Yuriy; Smerdov, Andriy; Petrytska, Svitlana

    2017-02-01

    On the basis of the neurophysiological strength-duration (amplitude-duration) curve of neuron activation (which relates the threshold amplitude of a rectangular current pulse of neuron activation to the pulse duration), as well as with the use of activation energy constraint (the threshold curve corresponds to the energy threshold of neuron activation by a rectangular current pulse), an energy model of neuron activation by a single current pulse has been constructed. The constructed model of activation, which determines its spectral properties, is a bandpass filter. Under the condition of minimum-phase feature of the neuron activation model, on the basis of Hilbert transform, the possibilities of phase-frequency response calculation from its amplitude-frequency response have been considered. Approximation to the amplitude-frequency response by the response of the Butterworth filter of the first order, as well as obtaining the pulse response corresponding to this approximation, give us the possibility of analyzing the efficiency of activating current pulses of various shapes, including analysis in accordance with the energy constraint.

  7. Effects of aspartame metabolites on astrocytes and neurons.

    Science.gov (United States)

    Rycerz, Karol; Jaworska-Adamu, Jadwiga Elżbieta

    2013-01-01

    Aspartame, a widespread sweetener used in many food products, is considered as a highly hazardous compound. Aspartame was discovered in 1965 and raises a lot of controversy up to date. Astrocytes are glial cells, the presence and functions of which are closely connected with the central nervous system (CNS). The aim of this article is to demonstrate the direct and indirect role of astrocytes participating in the harmful effects of aspartame metabolites on neurons. The artificial sweetener is broken down into phenylalanine (50%), aspartic acid (40%) and methanol (10%) during metabolism in the body. The excess of phenylalanine blocks the transport of important amino acids to the brain contributing to reduced levels of dopamine and serotonin. Astrocytes directly affect the transport of this amino acid and also indirectly by modulation of carriers in the endothelium. Aspartic acid at high concentrations is a toxin that causes hyperexcitability of neurons and is also a precursor of other excitatory amino acid - glutamates. Their excess in quantity and lack of astrocytic uptake induces excitotoxicity and leads to the degeneration of astrocytes and neurons. The methanol metabolites cause CNS depression, vision disorders and other symptoms leading ultimately to metabolic acidosis and coma. Astrocytes do not play a significant role in methanol poisoning due to a permanent consumption of large amounts of aspartame. Despite intense speculations about the carcinogenicity of aspartame, the latest studies show that its metabolite - diketopiperazine - is cancirogenic in the CNS. It contributes to the formation of tumors in the CNS such as gliomas, medulloblastomas and meningiomas. Glial cells are the main source of tumors, which can be caused inter alia by the sweetener in the brain. On the one hand the action of astrocytes during aspartame poisoning may be advantageous for neuro-protection while on the other it may intensify the destruction of neurons. The role of the glia in

  8. Artificial organic networks artificial intelligence based on carbon networks

    CERN Document Server

    Ponce-Espinosa, Hiram; Molina, Arturo

    2014-01-01

    This monograph describes the synthesis and use of biologically-inspired artificial hydrocarbon networks (AHNs) for approximation models associated with machine learning and a novel computational algorithm with which to exploit them. The reader is first introduced to various kinds of algorithms designed to deal with approximation problems and then, via some conventional ideas of organic chemistry, to the creation and characterization of artificial organic networks and AHNs in particular. The advantages of using organic networks are discussed with the rules to be followed to adapt the network to its objectives. Graph theory is used as the basis of the necessary formalism. Simulated and experimental examples of the use of fuzzy logic and genetic algorithms with organic neural networks are presented and a number of modeling problems suitable for treatment by AHNs are described: ·        approximation; ·        inference; ·        clustering; ·        control; ·        class...

  9. FPGA controlled artificial vascular system

    Directory of Open Access Journals (Sweden)

    Laqua D.

    2015-09-01

    Full Text Available Monitoring the oxygen saturation of an unborn child is an invasive procedure, so far. Transabdominal fetal pulse oximetry is a promising method under research, used to estimate the oxygen saturation of a fetus noninvasively. Due to the nature of the method, the fetal information needs to be extracted from a mixed signal. To properly evaluate signal processing algorithms, a phantom modeling fetal and maternal blood circuits and tissue layers is necessary. This paper presents an improved hardware concept for an artificial vascular system, utilizing an FPGA based CompactRIO System from National Instruments. The experimental model to simulate the maternal and fetal blood pressure curve consists of two identical hydraulic circuits. Each of these circuits consists of a pre-pressure system and an artificial vascular system. Pulse curves are generated by proportional valves, separating these two systems. The dilation of the fetal and maternal artificial vessels in tissue substitutes is measured by transmissive and reflective photoplethysmography. The measurement results from the pressure sensors and the transmissive optical sensors are visualized to show the functionality of the pulse generating systems. The trigger frequency for the maternal valve was set to 1 per second, the fetal valve was actuated at 0.7 per second for validation. The reflective curve, capturing pulsations of the fetal and maternal circuit, was obtained with a high power LED (905 nm as light source. The results show that the system generates pulse curves, similar to its physiological equivalent. Further, the acquired reflective optical signal is modulated by the alternating diameter of the tubes of both circuits, allowing for tests of signal processing algorithms.

  10. Coal ash artificial reef demonstration

    International Nuclear Information System (INIS)

    Livingston, R.J.; Brendel, G.F.; Bruzek, D.A.

    1991-01-01

    This experimental project evaluated the use of coal ash to construct artificial reefs. An artificial reef consisting of approximately 33 tons of cement-stabilized coal ash blocks was constructed in approximately 20 feet of water in the Gulf of Mexico approximately 9.3 miles west of Cedar Key, Florida. The project objectives were: (1) demonstrate that a durable coal ash/cement block can be manufactured by commercial block-making machines for use in artificial reefs, and (2) evaluate the possibility that a physically stable and environmentally acceptable coal ash/cement block reef can be constructed as a means of expanding recreational and commercial fisheries. The reef was constructed in February 1988 and biological surveys were made at monthly intervals from May 1988 to April 1989. The project provided information regarding: Development of an optimum design mix, block production and reef construction, chemical composition of block leachate, biological colonization of the reef, potential concentration of metals in the food web associated with the reef, acute bioassays (96-hour LC 50 ). The Cedar Key reef was found to be a habitat that was associated with a relatively rich assemblage of plants and animals. The reef did not appear to be a major source of heavy metals to species at various levels of biological organization. GAI Consultants, Inc (GAI) of Monroeville, Pennsylvania was the prime consultant for the project. The biological monitoring surveys and evaluations were performed by Environmental Planning and Analysis, Inc. of Tallahassee, Florida. The chemical analyses of biological organisms and bioassay elutriates were performed by Savannah Laboratories of Tallahassee, Florida. Florida Power Corporation of St. Petersburg, Florida sponsored the project and supplied ash from their Crystal River Energy Complex

  11. Artificial intelligence and knowledge management

    OpenAIRE

    Hoesch, Hugo Cesar; Barcellos, Vânia

    2006-01-01

    This article intends to make an analysis about the Artificial Intelligence (AI) and the Knowledge Management (KM). Faced with the dualism mind and body how we be able to see it AI? It doesn’t intent to create identical copy of human being, but try to find the better form to represent all the knowledge contained in our minds. The society of the information lives a great paradox, at the same time that we have access to an innumerable amount of information, the capacity and the forms of its proc...

  12. Cybersecurity in Artificial Pancreas Experiments.

    Science.gov (United States)

    O'Keeffe, Derek T; Maraka, Spyridoula; Basu, Ananda; Keith-Hynes, Patrick; Kudva, Yogish C

    2015-09-01

    Medical devices have transformed modern health care, and ongoing experimental medical technology trials (such as the artificial pancreas) have the potential to significantly improve the treatment of several chronic conditions, including diabetes mellitus. However, we suggest that, to date, the essential concept of cybersecurity has not been adequately addressed in this field. This article discusses several key issues of cybersecurity in medical devices and proposes some solutions. In addition, it outlines the current requirements and efforts of regulatory agencies to increase awareness of this topic and to improve cybersecurity.

  13. Artificial intelligence in Animal Science

    OpenAIRE

    COSTA, Ernane José Xavier

    2009-01-01

    Os sistemas biológicos são surpreendentemente flexíveis pra processar informação proveniente do mundo real. Alguns organismos biológicos possuem uma unidade central de processamento denominada de cérebro. O cérebro humano consiste de 10(11) neurônios e realiza processamento inteligente de forma exata e subjetiva. A Inteligência Artificial (IA) tenta trazer para o mundo da computação digital a heurística dos sistemas biológicos de várias maneiras, mas, ainda resta muito para que isso seja conc...

  14. Vida artificial, el nuevo paradigma

    Directory of Open Access Journals (Sweden)

    José Jesús Martínez Páez

    1998-05-01

    Full Text Available Se presenta una síntesis cronológica de los hechos más importantes en el desarrollo teórico y de simulación computacional, que han llevado a la formación de un nuevo paradigma que se conoce como vida artificial; se analizan sus características y sus príncipales líneas de investigación. Finalmente, se hace una descripción de su trabajo en la Universidad Nacional.

  15. Improving designer productivity. [artificial intelligence

    Science.gov (United States)

    Hill, Gary C.

    1992-01-01

    Designer and design team productivity improves with skill, experience, and the tools available. The design process involves numerous trials and errors, analyses, refinements, and addition of details. Computerized tools have greatly speeded the analysis, and now new theories and methods, emerging under the label Artificial Intelligence (AI), are being used to automate skill and experience. These tools improve designer productivity by capturing experience, emulating recognized skillful designers, and making the essence of complex programs easier to grasp. This paper outlines the aircraft design process in today's technology and business climate, presenting some of the challenges ahead and some of the promising AI methods for meeting these challenges.

  16. Advanced Artificial Intelligence Technology Testbed

    Science.gov (United States)

    Anken, Craig S.

    1993-01-01

    The Advanced Artificial Intelligence Technology Testbed (AAITT) is a laboratory testbed for the design, analysis, integration, evaluation, and exercising of large-scale, complex, software systems, composed of both knowledge-based and conventional components. The AAITT assists its users in the following ways: configuring various problem-solving application suites; observing and measuring the behavior of these applications and the interactions between their constituent modules; gathering and analyzing statistics about the occurrence of key events; and flexibly and quickly altering the interaction of modules within the applications for further study.

  17. Artificial intelligence a beginner's guide

    CERN Document Server

    Whitby, Blay

    2012-01-01

    Tomorrow begins right here as we embark on an enthralling and jargon-free journey into the world of computers and the inner recesses of the human mind. Readers encounter everything from the nanotechnology used to make insect-like robots, to computers that perform surgery, in addition to discovering the biggest controversies to dog the field of AI. Blay Whitby is a Lecturer on Cognitive Science and Artificial Intelligence at the University of Sussex UK. He is the author of two books and numerous papers.

  18. Epistasis analysis using artificial intelligence.

    Science.gov (United States)

    Moore, Jason H; Hill, Doug P

    2015-01-01

    Here we introduce artificial intelligence (AI) methodology for detecting and characterizing epistasis in genetic association studies. The ultimate goal of our AI strategy is to analyze genome-wide genetics data as a human would using sources of expert knowledge as a guide. The methodology presented here is based on computational evolution, which is a type of genetic programming. The ability to generate interesting solutions while at the same time learning how to solve the problem at hand distinguishes computational evolution from other genetic programming approaches. We provide a general overview of this approach and then present a few examples of its application to real data.

  19. ARTIFICIAL INTELLIGENCE: APPLICATIONS AND FUTURE

    OpenAIRE

    Ellur Anand; S. G. Varun Kumar

    2017-01-01

    Artificial Intelligence (AI) or Augmented Intelligence happens to be the most talked about technology that would have a major impact on the way the current day world functions. The next step in evolution of digital world is AI. The safety of the world with more and more use of AI also becomes necessity. Safety rules and regulations of the digital world need to be drafted and redrafted as AI evolves and becomes a new normal in every one’s life just as mobile phone has become in the current sce...

  20. Artificial Intelligence in Autonomous Telescopes

    Science.gov (United States)

    Mahoney, William; Thanjavur, Karun

    2011-03-01

    Artificial Intelligence (AI) is key to the natural evolution of today's automated telescopes to fully autonomous systems. Based on its rapid development over the past five decades, AI offers numerous, well-tested techniques for knowledge based decision making essential for real-time telescope monitoring and control, with minimal - and eventually no - human intervention. We present three applications of AI developed at CFHT for monitoring instantaneous sky conditions, assessing quality of imaging data, and a prototype for scheduling observations in real-time. Closely complementing the current remote operations at CFHT, we foresee further development of these methods and full integration in the near future.

  1. Artificial intelligence methods for diagnostic

    International Nuclear Information System (INIS)

    Dourgnon-Hanoune, A.; Porcheron, M.; Ricard, B.

    1996-01-01

    To assist in diagnosis of its nuclear power plants, the Research and Development Division of Electricite de France has been developing skills in Artificial Intelligence for about a decade. Different diagnostic expert systems have been designed. Among them, SILEX for control rods cabinet troubleshooting, DIVA for turbine generator diagnosis, DIAPO for reactor coolant pump diagnosis. This know how in expert knowledge modeling and acquisition is direct result of experience gained during developments and of a more general reflection on knowledge based system development. We have been able to reuse this results for other developments such as a guide for auxiliary rotating machines diagnosis. (authors)

  2. Apartes desde la inteligencia artificial

    OpenAIRE

    Luis Carlos Torres Soler

    1998-01-01

    El estudio y desarrollo de la inteligencia artificial no debe centrarse sólo en la creación de software o hardware que permita realizar procesos algorítmicos o heurísticos en el computador, de tal forma que produzcan soluciones óptimas y eficientes al resolver un problema complejo, ya sea de manejo de información o de toma de decisiones, o crear máquinas que tengan buena apariencia del ser humano; se debe, sobre todo, analizar la parte neurológica y sicológica que presenta el individuo al sol...

  3. Neuroscience-Inspired Artificial Intelligence.

    Science.gov (United States)

    Hassabis, Demis; Kumaran, Dharshan; Summerfield, Christopher; Botvinick, Matthew

    2017-07-19

    The fields of neuroscience and artificial intelligence (AI) have a long and intertwined history. In more recent times, however, communication and collaboration between the two fields has become less commonplace. In this article, we argue that better understanding biological brains could play a vital role in building intelligent machines. We survey historical interactions between the AI and neuroscience fields and emphasize current advances in AI that have been inspired by the study of neural computation in humans and other animals. We conclude by highlighting shared themes that may be key for advancing future research in both fields. Copyright © 2017. Published by Elsevier Inc.

  4. Turning skin into dopamine neurons

    Institute of Scientific and Technical Information of China (English)

    Malin Parmar; Johan Jakobsson

    2011-01-01

    The possibility to generate neurons from fibroblasts became a reality with the development of iPS technology a few years ago.By reprogramming somatic cells using transcription factor (TF) overexpression,it is possible to generate pluripotent stem cells that then can be differentiated into any somatic cell type including various subtypes of neurons.This raises the possibility of using donor-matched or even patientspecific cells for cell therapy of neurological disorders such as Parkinson's disease (PD),Huntington's disease and stroke.Supporting this idea,dopamine neurons,which are the cells dying in PD,derived from human iPS cells have been demonstrated to survive transplantation and reverse motor symptoms in animal models of PD [1].

  5. An Investigation on the Role of Spike Latency in an Artificial Olfactory System

    Directory of Open Access Journals (Sweden)

    Corrado eDi Natale

    2011-12-01

    Full Text Available Experimental studies have shown that the reactions to external stimuli may appear only few hundreds of milliseconds after the physical interaction of the stimulus with the proper receptor. This behavior suggests that neurons transmit the largest meaningful part of their signal in the first spikes, and than that the spike latency is a good descriptor of the information content in biological neural networks. In this paper this property has been investigated in an artificial sensorial system where a single layer of spiking neurons is trained with the data generated by an artificial olfactory platform based on a large array of chemical sensors. The capability to discriminate between distinct chemicals and mixtures of them was studied with spiking neural networks endowed with and without lateral inhibitions and considering as output feature of the network both the spikes latency and the average firing rate. Results show that the average firing rate of the output spikes sequences shows the best separation among the experienced vapors, however the latency code is able in a shorter time to correctly discriminate all the tested volatile compounds. This behavior is qualitatively similar to those recently found in natural olfaction, and noteworthy it provides practical suggestions to tail the measurement conditions of artificial olfactory systems defining for each specific case a proper measurement time.

  6. Suitability assessment of artificial neural network to approximate surface subsidence due to rock mass drainage

    Directory of Open Access Journals (Sweden)

    Ryszard Hejmanowski

    2015-01-01

    Full Text Available Based on the previous studies conducted by the authors, a new approach was proposed, namely the tools of artificial intelligence. One of neural networks is a multilayer perceptron network (MLP, which has already found applications in many fields of science. Sequentially, a series of calculations was made for different MLP neural network configuration and the best of them was selected. Mean square error (MSE and the correlation coefficient R were adopted as the selection criterion for the optimal network. The obtained results were characterized with a considerable dispersion. With an increase in the amount of hidden neurons, the MSE of the network increased while the correlation coefficient R decreased. Similar conclusions were drawn for the network with a small number of hidden neurons. The analysis allowed to select a network composed of 24 neurons as the best one for the issue under question. The obtained final answers of artificial neural network were presented in a histogram as differences between the calculated and expected value.

  7. Neuronal involvement in cisplatin neuropathy

    DEFF Research Database (Denmark)

    Krarup-Hansen, A; Helweg-Larsen, Susanne Elisabeth; Schmalbruch, H

    2007-01-01

    of large dorsal root ganglion cells. Motor conduction studies, autonomic function and warm and cold temperature sensation remained unchanged at all doses of cisplatin treatment. The results of these studies are consistent with degeneration of large sensory neurons whereas there was no evidence of distal......Although it is well known that cisplatin causes a sensory neuropathy, the primary site of involvement is not established. The clinical symptoms localized in a stocking-glove distribution may be explained by a length dependent neuronopathy or by a distal axonopathy. To study whether the whole neuron...

  8. Calcium signals in olfactory neurons.

    Science.gov (United States)

    Tareilus, E; Noé, J; Breer, H

    1995-11-09

    Laser scanning confocal microscopy in combination with the fluorescent calcium indicators Fluo-3 and Fura-Red was employed to estimate the intracellular concentration of free calcium ions in individual olfactory receptor neurons and to monitor temporal and spatial changes in the Ca(2+)-level upon stimulation. The chemosensory cells responded to odorants with a significant increase in the calcium concentration, preferentially in the dendritic knob. Applying various stimulation paradigma, it was found that in a population of isolated cells, subsets of receptor neurons display distinct patterns of responsiveness.

  9. Acetaminophen inhibits neuronal inflammation and protects neurons from oxidative stress

    Directory of Open Access Journals (Sweden)

    Grammas Paula

    2009-03-01

    Full Text Available Abstract Background Recent studies have demonstrated a link between the inflammatory response, increased cytokine formation, and neurodegeneration in the brain. The beneficial effects of anti-inflammatory drugs in neurodegenerative diseases, such as Alzheimer's disease (AD, have been documented. Increasing evidence suggests that acetaminophen has unappreciated anti-oxidant and anti-inflammatory properties. The objectives of this study are to determine the effects of acetaminophen on cultured brain neuronal survival and inflammatory factor expression when exposed to oxidative stress. Methods Cerebral cortical cultured neurons are pretreated with acetaminophen and then exposed to the superoxide-generating compound menadione (5 μM. Cell survival is assessed by MTT assay and inflammatory protein (tumor necrosis factor alpha, interleukin-1, macrophage inflammatory protein alpha, and RANTES release quantitated by ELISA. Expression of pro- and anti-apoptotic proteins is assessed by western blots. Results Acetaminophen has pro-survival effects on neurons in culture. Menadione, a superoxide releasing oxidant stressor, causes a significant (p Conclusion These data show that acetaminophen has anti-oxidant and anti-inflammatory effects on neurons and suggest a heretofore unappreciated therapeutic potential for this drug in neurodegenerative diseases such as AD that are characterized by oxidant and inflammatory stress.

  10. Neuronal coherence and its functional role in communication between neurons

    NARCIS (Netherlands)

    Zeitler-Geurds, M.

    2010-01-01

    Neuronal oscillations are observed in many brain areas in various frequency bands. Each of the frequency bands is associated with a particular functional role. Gamma oscillations (30-80 Hz) are thought to be related to cognitive tasks like memory and attention and possibly also involved in the

  11. Control Neuronal Combinado para Generar Espectros de Oleajes

    Directory of Open Access Journals (Sweden)

    Luis P. Sánchez Fernández

    2013-10-01

    Full Text Available Resumen: Se presenta un método novedoso para controlar la obtención de espectros de energía de oleajes, de gran utilidad en los laboratorios de investigación y desarrollo de Hidráulica Marítima. El elemento final de control o manipulador es un motor eléctrico lineal conectado a un servo-control el cual es supervisado mediante una computadora. El algoritmo de control automático se realiza con un esquema neuronal combinado, compuesto por una red neuronal artificial “feed-forward” y un controlador proporcional integral. El sistema computacional implementado incluye características de autoaprendizaje, materializado en el re-entrenamiento en línea de la red neuronal lo cual hace posible adaptarse a cambios en los parámetros del “proceso controlado” y a perturbaciones, altamente influyentes en el espectro de energía que impacta una obra hidráulica objeto de estudio. Abstract: A novel method is presented to control the generation of wave energy spectrum, useful in research and development laboratories of Maritime Hydraulic. The final control element is a linear electric motor connected to a servo-control which is monitored by a computer. The automatic control algorithm is performed with a combined neural scheme. It consists of an artificial neural network “feed-forward” and a proportional integral controller. The computer system includes self-learning based on an online training of the neural network. It makes possible to adapt to changes in the parameters of the “controlled process” and disturbances that impact the studied hydraulic work. Palabras clave: Control, neuronal, oleaje, espectros, hidráulica, Keywords: Control, neural, wave, spectrums, hydraulic

  12. Readings in artificial intelligence and software engineering

    CERN Document Server

    Rich, Charles

    1986-01-01

    Readings in Artificial Intelligence and Software Engineering covers the main techniques and application of artificial intelligence and software engineering. The ultimate goal of artificial intelligence applied to software engineering is automatic programming. Automatic programming would allow a user to simply say what is wanted and have a program produced completely automatically. This book is organized into 11 parts encompassing 34 chapters that specifically tackle the topics of deductive synthesis, program transformations, program verification, and programming tutors. The opening parts p

  13. Artificial Immune Networks: Models and Applications

    Directory of Open Access Journals (Sweden)

    Xian Shen

    2008-06-01

    Full Text Available Artificial Immune Systems (AIS, which is inspired by the nature immune system, has been applied for solving complex computational problems in classification, pattern rec- ognition, and optimization. In this paper, the theory of the natural immune system is first briefly introduced. Next, we compare some well-known AIS and their applications. Several representative artificial immune networks models are also dis- cussed. Moreover, we demonstrate the applications of artificial immune networks in various engineering fields.

  14. Digital Genesis: Computers, Evolution and Artificial Life

    OpenAIRE

    Taylor, Tim; Dorin, Alan; Korb, Kevin

    2015-01-01

    The application of evolution in the digital realm, with the goal of creating artificial intelligence and artificial life, has a history as long as that of the digital computer itself. We illustrate the intertwined history of these ideas, starting with the early theoretical work of John von Neumann and the pioneering experimental work of Nils Aall Barricelli. We argue that evolutionary thinking and artificial life will continue to play an integral role in the future development of the digital ...

  15. Artificial Intelligence (AI) Studies in Water Resources

    OpenAIRE

    Ay, Murat; Özyıldırım, Serhat

    2018-01-01

    Artificial intelligence has been extensively used in many areas such as computer science,robotics, engineering, medicine, translation, economics, business, and psychology. Variousstudies in the literature show that the artificial intelligence in modeling approaches give closeresults to the real data for solution of linear, non-linear, and other systems. In this study, wereviewed the current state-of-the-art and progress on the modelling of artificial intelligence forwater variables: rainfall-...

  16. Ethical Considerations in Artificial Intelligence Courses

    OpenAIRE

    Burton, Emanuelle; Goldsmith, Judy; Koenig, Sven; Kuipers, Benjamin; Mattei, Nicholas; Walsh, Toby

    2017-01-01

    The recent surge in interest in ethics in artificial intelligence may leave many educators wondering how to address moral, ethical, and philosophical issues in their AI courses. As instructors we want to develop curriculum that not only prepares students to be artificial intelligence practitioners, but also to understand the moral, ethical, and philosophical impacts that artificial intelligence will have on society. In this article we provide practical case studies and links to resources for ...

  17. Artificial humidification for the mechanically ventilated patient

    OpenAIRE

    Selvaraj, Nelson

    2010-01-01

    Caring for patients who are mechanically ventilated poses many\\ud challenges for critical care nurses. It is important to humidify the\\ud patient’s airways artificially to prevent complications such as\\ud ventilator-associated pneumonia. There is no gold standard to\\ud determine which type of humidification is best for patients who\\ud are artificially ventilated. This article provides an overview of\\ud commonly used artificial humidification for mechanically ventilated\\ud patients and discuss...

  18. Artificial muscle: facts and fiction.

    Science.gov (United States)

    Schaub, Marcus C

    2011-12-19

    Mechanical devices are sought to support insufficient or paralysed striated muscles including the failing heart. Nickel-titanium alloys (nitinol) present the following two properties: (i) super-elasticity, and (ii) the potential to assume different crystal structures depending on temperature and/or stress. Starting from the martensite state nitinol is able to resume the austenite form (state of low potential energy and high entropy) even against an external resistance. This one-way shape change is deployed in self-expanding vascular stents. Heating induces the force generating transformation from martensite to the austenite state while cooling induces relaxation back to the martensite state. This two-way shape change oscillating between the two states may be used in cyclically contracting support devices of silicon-coated nitinol wires. Such a contractile device sutured to the right atrium has been tested in vitro in a bench model and in vivo in sheep. The contraction properties of natural muscles, specifically of the myocardium, and the tight correlation with ATP production by oxidative phosphorylation in the mitochondria is briefly outlined. Force development by the nitinol device cannot be smoothly regulated as in natural muscle. Its mechanical impact is forced onto the natural muscle regardless of the actual condition with regard to metabolism and Ca2+-homeostasis. The development of artificial muscle on the basis of nitinol wires is still in its infancy. The nitinol artificial muscle will have to prove its viability in the various clinical settings.

  19. Development of artificial soft rock

    International Nuclear Information System (INIS)

    Kishi, Kiyoshi

    1995-01-01

    When foundation base rocks are deeper than the level of installing structures or there exist weathered rocks and crushed rocks in a part of base rocks, often sound artificial base rocks are made by substituting the part with concrete. But in the construction of Kashiwazaki Kariwa Nuclear Power Station of Tokyo Electric Power Co., Inc., the foundation base rocks consist of mudstone, and the stiffness of concrete is large as compared with the surrounding base rocks. As the quality of the substituting material, the nearly same stiffness as that of the surrounding soft rocks and long term stability are suitable, and the excellent workability and economical efficiency are required, therefore, artificial soft rocks were developed. As the substituting material, the soil mortar that can obtain the physical property values in stable form, which are similar to those of Nishiyama mudstone, was selected. The mechanism of its hardening and the long term stability, and the manufacturing plant are reported. As for its application to the base rocks of Kashiwazaki Kariwa Nuclear Power Station, the verification test at the site and the application to the base rocks for No. 7 plant reactor building and other places are described. (K.I.)

  20. Economic reasoning and artificial intelligence.

    Science.gov (United States)

    Parkes, David C; Wellman, Michael P

    2015-07-17

    The field of artificial intelligence (AI) strives to build rational agents capable of perceiving the world around them and taking actions to advance specified goals. Put another way, AI researchers aim to construct a synthetic homo economicus, the mythical perfectly rational agent of neoclassical economics. We review progress toward creating this new species of machine, machina economicus, and discuss some challenges in designing AIs that can reason effectively in economic contexts. Supposing that AI succeeds in this quest, or at least comes close enough that it is useful to think about AIs in rationalistic terms, we ask how to design the rules of interaction in multi-agent systems that come to represent an economy of AIs. Theories of normative design from economics may prove more relevant for artificial agents than human agents, with AIs that better respect idealized assumptions of rationality than people, interacting through novel rules and incentive systems quite distinct from those tailored for people. Copyright © 2015, American Association for the Advancement of Science.

  1. Evolution Engines and Artificial Intelligence

    Science.gov (United States)

    Hemker, Andreas; Becks, Karl-Heinz

    In the last years artificial intelligence has achieved great successes, mainly in the field of expert systems and neural networks. Nevertheless the road to truly intelligent systems is still obscured. Artificial intelligence systems with a broad range of cognitive abilities are not within sight. The limited competence of such systems (brittleness) is identified as a consequence of the top-down design process. The evolution principle of nature on the other hand shows an alternative and elegant way to build intelligent systems. We propose to take an evolution engine as the driving force for the bottom-up development of knowledge bases and for the optimization of the problem-solving process. A novel data analysis system for the high energy physics experiment DELPHI at CERN shows the practical relevance of this idea. The system is able to reconstruct the physical processes after the collision of particles by making use of the underlying standard model of elementary particle physics. The evolution engine acts as a global controller of a population of inference engines working on the reconstruction task. By implementing the system on the Connection Machine (Model CM-2) we use the full advantage of the inherent parallelization potential of the evolutionary approach.

  2. Progress and Challenge of Artificial Intelligence

    Institute of Scientific and Technical Information of China (English)

    Zhong-Zhi Shi; Nan-Ning Zheng

    2006-01-01

    Artificial Intelligence (AI) is generally considered to be a subfield of computer science, that is concerned to attempt simulation, extension and expansion of human intelligence. Artificial intelligence has enjoyed tremendous success over the last fifty years. In this paper we only focus on visual perception, granular computing, agent computing, semantic grid. Human-level intelligence is the long-term goal of artificial intelligence. We should do joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. A new cross discipline intelligence science is undergoing a rapid development. Future challenges are given in final section.

  3. The Japanese artificial organs scene: current status.

    Science.gov (United States)

    Mitamura, Yoshinori; Murabayashi, Shun

    2005-08-01

    Artificial organs and regenerative medicine are the subjects of very active research and development (R&D) in Japan and various artificial organs are widely used in patients. Results of the R&D are presented at the annual conference of the Japanese Society for Artificial Organs (JSAO). Progress in the fields of artificial organs and regenerative medicine are reviewed annually in the Japanese Journal of Artificial Organs. The official English-language journal of JSAO, Journal of Artificial Organs, also publishes many original articles by Japanese researchers. Although the annual conference and the publications of JSAO provide the world with update information on artificial organs and regenerative medicine in Japan, the information is not always understood appropriately in the rest of the world, mainly due to language problems. This article therefore introduces the current status of artificial organs and regenerative medicine in Japan. Artificial hearts and metabolic support systems are reviewed here and other interesting areas such as regenerative medicine can be found elsewhere.

  4. Polymeric membrane materials for artificial organs.

    Science.gov (United States)

    Kawakami, Hiroyoshi

    2008-01-01

    Many polymeric materials have already been used in the field of artificial organs. However, the materials used in artificial organs are not necessarily created with the best material selectivity and materials design; therefore, the development of synthesized polymeric membrane materials for artificial organs based on well-defined designs is required. The approaches to the development of biocompatible polymeric materials fall into three categories: (1) control of physicochemical characteristics on material surfaces, (2) modification of material surfaces using biomolecules, and (3) construction of biomimetic membrane surfaces. This review will describe current issues regarding polymeric membrane materials for use in artificial organs.

  5. Artificial senses for characterization of food quality

    Institute of Scientific and Technical Information of China (English)

    HUANG Yan-bo; LAN Yu-bin; R.E. Lacey

    2004-01-01

    Food quality is of primary concern in the food industry and to the consumer. Systems that mimic human senses have been developed and applied to the characterization of food quality. The five primary senses are: vision, hearing, smell, taste and touch.In the characterization of food quality, people assess the samples sensorially and differentiate "good" from "bad" on a continuum.However, the human sensory system is subjective, with mental and physical inconsistencies, and needs time to work. Artificial senses such as machine vision, the electronic ear, electronic nose, electronic tongue, artificial mouth and even artificial the head have been developed that mimic the human senses. These artificial senses are coordinated individually or collectively by a pattern recognition technique, typically artificial neural networks, which have been developed based on studies of the mechanism of the human brain. Such a structure has been used to formulate methods for rapid characterization of food quality. This research presents and discusses individual artificial sensing systems. With the concept of multi-sensor data fusion these sensor systems can work collectively in some way. Two such fused systems, artificial mouth and artificial head, are described and discussed. It indicates that each of the individual systems has their own artificially sensing ability to differentiate food samples. It further indicates that with a more complete mimic of human intelligence the fused systems are more powerful than the individual systems in differentiation of food samples.

  6. Artificial reefs: “Attraction versus Production”

    Directory of Open Access Journals (Sweden)

    Eduardo Barros Fagundes Netto

    2011-04-01

    Full Text Available The production of fish is the most common reason for the construction and installation of an artificial reef. More recently, environmental concerns and conservation of biological resources have been instrumental to the formulation of new goals of the research. One of the issues to be resolved is the biological function of “attraction vs. production” as a result of the use of artificial reefs. The uncertainty as to the answer to the question whether the artificial reefs will or not benefit the development of fish stocks could be solved if the artificial reefs would be managed as marine protected areas.

  7. A Pathway to Artificial Metalloenzymes

    KAUST Repository

    Fischer, Johannes

    2015-12-01

    The advancement of catalytic systems and the application thereof has proven to be the key to overcome traditional limitations of industrial-scale synthetic processes. Converging organometallic and biocatalytic principles lead to the development of Artificial Metalloenzymes (ArMs) that comprise a synthetic metal catalyst embedded in a protein scaffold, thereby combining the reactivity of the former with the versatility of the latter. This synergistic approach introduces rationally designed building blocks for the catalytic site and the host protein to assemble enzyme-like structures that follow regio-, chemo-, enantio- and substrate-selective principles. Yet, the identification of suitable protein scaffolds has thus far been challenging. Herein we report a rationally optimized fluorescent protein host, mTFP*, that was engineered to have no intrinsic metal binding capability and, owing to its robust nature, can act as scaffold for the design of novel ArMs. We demonstrate the potential of site-specific modifications within the protein host, use protein X-Ray analysis to validate the respective scaffolds and show how artificial mutant binding sites can be introduced. Transition metal Förster Resonance Energy transfer (tmFRET) methodologies help to evaluate micromolar dissociation constants and reveal structural rearrangements upon coordination of the metal centers. In conjunction with molecular insights from X-Ray crystallographic structure determination, dynamics of the binding pocket can be inferred. The versatile subset of different binding motifs paired with transition metal catalysts create artificial metalloenzymes that provide reactivities which otherwise do not exist in nature. As a proof of concept, Diels-Alder cycloadditions highlight the potential of the present mTFP* based catalysts by stereoselectively converting azachalcone and cyclopentadiene substrates. Screens indicate an enantiomeric excess of up to 60% and provide insights into the electronic and

  8. Altered olfactory processing of stress-related body odors and artificial odors in patients with panic disorder.

    Science.gov (United States)

    Wintermann, Gloria-Beatrice; Donix, Markus; Joraschky, Peter; Gerber, Johannes; Petrowski, Katja

    2013-01-01

    Patients with Panic Disorder (PD) direct their attention towards potential threat, followed by panic attacks, and increased sweat production. Onés own anxiety sweat odor influences the attentional focus, and discrimination of threat or non-threat. Since olfactory projection areas overlap with neuronal areas of a panic-specific fear network, the present study investigated the neuronal processing of odors in general and of stress-related sweat odors in particular in patients with PD. A sample of 13 patients with PD with/ without agoraphobia and 13 age- and gender-matched healthy controls underwent an fMRI investigation during olfactory stimulation with their stress-related sweat odors (TSST, ergometry) as well as artificial odors (peach, artificial sweat) as non-fearful non-body odors. The two groups did not differ with respect to their olfactory identification ability. Independent of the kind of odor, the patients with PD showed activations in fronto-cortical areas in contrast to the healthy controls who showed activations in olfaction-related areas such as the amygdalae and the hippocampus. For artificial odors, the patients with PD showed a decreased neuronal activation of the thalamus, the posterior cingulate cortex and the anterior cingulate cortex. Under the presentation of sweat odor caused by ergometric exercise, the patients with PD showed an increased activation in the superior temporal gyrus, the supramarginal gyrus, and the cingulate cortex which was positively correlated with the severity of the psychopathology. For the sweat odor from the anxiety condition, the patients with PD showed an increased activation in the gyrus frontalis inferior, which was positively correlated with the severity of the psychopathology. The results suggest altered neuronal processing of olfactory stimuli in PD. Both artificial odors and stress-related body odors activate specific parts of a fear-network which is associated with an increased severity of the psychopathology.

  9. Altered olfactory processing of stress-related body odors and artificial odors in patients with panic disorder.

    Directory of Open Access Journals (Sweden)

    Gloria-Beatrice Wintermann

    Full Text Available Patients with Panic Disorder (PD direct their attention towards potential threat, followed by panic attacks, and increased sweat production. Onés own anxiety sweat odor influences the attentional focus, and discrimination of threat or non-threat. Since olfactory projection areas overlap with neuronal areas of a panic-specific fear network, the present study investigated the neuronal processing of odors in general and of stress-related sweat odors in particular in patients with PD.A sample of 13 patients with PD with/ without agoraphobia and 13 age- and gender-matched healthy controls underwent an fMRI investigation during olfactory stimulation with their stress-related sweat odors (TSST, ergometry as well as artificial odors (peach, artificial sweat as non-fearful non-body odors.The two groups did not differ with respect to their olfactory identification ability. Independent of the kind of odor, the patients with PD showed activations in fronto-cortical areas in contrast to the healthy controls who showed activations in olfaction-related areas such as the amygdalae and the hippocampus. For artificial odors, the patients with PD showed a decreased neuronal activation of the thalamus, the posterior cingulate cortex and the anterior cingulate cortex. Under the presentation of sweat odor caused by ergometric exercise, the patients with PD showed an increased activation in the superior temporal gyrus, the supramarginal gyrus, and the cingulate cortex which was positively correlated with the severity of the psychopathology. For the sweat odor from the anxiety condition, the patients with PD showed an increased activation in the gyrus frontalis inferior, which was positively correlated with the severity of the psychopathology.The results suggest altered neuronal processing of olfactory stimuli in PD. Both artificial odors and stress-related body odors activate specific parts of a fear-network which is associated with an increased severity of the

  10. Unbalanced Neuronal Circuits in Addiction

    OpenAIRE

    Volkow, Nora D.; Wang, Gen-Jack; Tomasi, Dardo; Baler, Ruben D.

    2013-01-01

    Through sequential waves of drug-induced neurochemical stimulation, addiction co-opts the brain's neuronal circuits that mediate reward, motivation, , to behavioral inflexibility and a severe disruption of self-control and compulsive drug intake. Brain imaging technologies have allowed neuroscientists to map out the neural landscape of addiction in the human brain and to understand how drugs modify it.

  11. Computing with Spiking Neuron Networks

    NARCIS (Netherlands)

    H. Paugam-Moisy; S.M. Bohte (Sander); G. Rozenberg; T.H.W. Baeck (Thomas); J.N. Kok (Joost)

    2012-01-01

    htmlabstractAbstract Spiking Neuron Networks (SNNs) are often referred to as the 3rd gener- ation of neural networks. Highly inspired from natural computing in the brain and recent advances in neurosciences, they derive their strength and interest from an ac- curate modeling of synaptic interactions

  12. What do mirror neurons mirror?

    NARCIS (Netherlands)

    Uithol, S.; Rooij, I.J.E.I. van; Bekkering, H.; Haselager, W.F.G.

    2011-01-01

    Single cell recordings in monkeys provide strong evidence for an important role of the motor system in action understanding. This evidence is backed up by data from studies of the (human) mirror neuron system using neuroimaging or TMS techniques, and behavioral experiments. Although the data

  13. Optimal compensation for neuron loss

    Science.gov (United States)

    Barrett, David GT; Denève, Sophie; Machens, Christian K

    2016-01-01

    The brain has an impressive ability to withstand neural damage. Diseases that kill neurons can go unnoticed for years, and incomplete brain lesions or silencing of neurons often fail to produce any behavioral effect. How does the brain compensate for such damage, and what are the limits of this compensation? We propose that neural circuits instantly compensate for neuron loss, thereby preserving their function as much as possible. We show that this compensation can explain changes in tuning curves induced by neuron silencing across a variety of systems, including the primary visual cortex. We find that compensatory mechanisms can be implemented through the dynamics of networks with a tight balance of excitation and inhibition, without requiring synaptic plasticity. The limits of this compensatory mechanism are reached when excitation and inhibition become unbalanced, thereby demarcating a recovery boundary, where signal representation fails and where diseases may become symptomatic. DOI: http://dx.doi.org/10.7554/eLife.12454.001 PMID:27935480

  14. Hypothalamic neurones governing glucose homeostasis.

    Science.gov (United States)

    Coppari, R

    2015-06-01

    The notion that the brain directly controls the level of glucose in the blood (glycaemia) independent of its known action on food intake and body weight has been known ever since 1849. That year, the French physiologist Dr Claude Bernard reported that physical puncture of the floor of the fourth cerebral ventricle rapidly leads to an increased level of sugar in the blood (and urine) in rabbits. Despite this important discovery, it took approximately 150 years before significant efforts aimed at understanding the underlying mechanism of brain-mediated control of glucose metabolism were made. Technological developments allowing for genetically-mediated manipulation of selected molecular pathways in a neurone-type-specific fashion unravelled the importance of specific molecules in specific neuronal populations. These neuronal pathways govern glucose metabolism in the presence and even in the absence of insulin. Also, a peculiarity of these pathways is that certain biochemically-defined neurones govern glucose metabolism in a tissue-specific fashion. © 2015 British Society for Neuroendocrinology.

  15. Differences in predators of artificial and real songbirds nests: Evidence of bias in artificial nest studies

    Science.gov (United States)

    Frank R. Thompson; Dirk E. Burhans

    2004-01-01

    In the past two decades, many researchers have used artificial nest to measure relative rates of nest predation. Recent comparisons show that real and artificial nests may not be depredated at the same rate, but no one has examined the mechanisms underlying these patterns. We determined differences in predator-specific predation rates of real and artificial nests. we...

  16. Injection of fully-defined signal mixtures: a novel high-throughput tool to study neuronal encoding and computations.

    Directory of Open Access Journals (Sweden)

    Vladimir Ilin

    Full Text Available Understanding of how neurons transform fluctuations of membrane potential, reflecting input activity, into spike responses, which communicate the ultimate results of single-neuron computation, is one of the central challenges for cellular and computational neuroscience. To study this transformation under controlled conditions, previous work has used a signal immersed in noise paradigm where neurons are injected with a current consisting of fluctuating noise that mimics on-going synaptic activity and a systematic signal whose transmission is studied. One limitation of this established paradigm is that it is designed to examine the encoding of only one signal under a specific, repeated condition. As a result, characterizing how encoding depends on neuronal properties, signal parameters, and the interaction of multiple inputs is cumbersome. Here we introduce a novel fully-defined signal mixture paradigm, which allows us to overcome these problems. In this paradigm, current for injection is synthetized as a sum of artificial postsynaptic currents (PSCs resulting from the activity of a large population of model presynaptic neurons. PSCs from any presynaptic neuron(s can be now considered as "signal", while the sum of all other inputs is considered as "noise". This allows us to study the encoding of a large number of different signals in a single experiment, thus dramatically increasing the throughput of data acquisition. Using this novel paradigm, we characterize the detection of excitatory and inhibitory PSCs from neuronal spike responses over a wide range of amplitudes and firing-rates. We show, that for moderately-sized neuronal populations the detectability of individual inputs is higher for excitatory than for inhibitory inputs during the 2-5 ms following PSC onset, but becomes comparable after 7-8 ms. This transient imbalance of sensitivity in favor of excitation may enhance propagation of balanced signals through neuronal networks. Finally, we

  17. The application and development of artificial intelligence in smart clothing

    Science.gov (United States)

    Wei, Xiong

    2018-03-01

    This paper mainly introduces the application of artificial intelligence in intelligent clothing. Starting from the development trend of artificial intelligence, analysis the prospects for development in smart clothing with artificial intelligence. Summarize the design key of artificial intelligence in smart clothing. Analysis the feasibility of artificial intelligence in smart clothing.

  18. BlastNeuron for Automated Comparison, Retrieval and Clustering of 3D Neuron Morphologies.

    Science.gov (United States)

    Wan, Yinan; Long, Fuhui; Qu, Lei; Xiao, Hang; Hawrylycz, Michael; Myers, Eugene W; Peng, Hanchuan

    2015-10-01

    Characterizing the identity and types of neurons in the brain, as well as their associated function, requires a means of quantifying and comparing 3D neuron morphology. Presently, neuron comparison methods are based on statistics from neuronal morphology such as size and number of branches, which are not fully suitable for detecting local similarities and differences in the detailed structure. We developed BlastNeuron to compare neurons in terms of their global appearance, detailed arborization patterns, and topological similarity. BlastNeuron first compares and clusters 3D neuron reconstructions based on global morphology features and moment invariants, independent of their orientations, sizes, level of reconstruction and other variations. Subsequently, BlastNeuron performs local alignment between any pair of retrieved neurons via a tree-topology driven dynamic programming method. A 3D correspondence map can thus be generated at the resolution of single reconstruction nodes. We applied BlastNeuron to three datasets: (1) 10,000+ neuron reconstructions from a public morphology database, (2) 681 newly and manually reconstructed neurons, and (3) neurons reconstructions produced using several independent reconstruction methods. Our approach was able to accurately and efficiently retrieve morphologically and functionally similar neuron structures from large morphology database, identify the local common structures, and find clusters of neurons that share similarities in both morphology and molecular profiles.

  19. Oscillating from Neurosecretion to Multitasking Dopamine Neurons

    Directory of Open Access Journals (Sweden)

    David R. Grattan

    2016-04-01

    Full Text Available In this issue of Cell Reports, Stagkourakis et al. (2016 report that oscillating hypothalamic TIDA neurons, previously thought to be simple neurosecretory neurons controlling pituitary prolactin secretion, control dopamine output via autoregulatory mechanisms and thus could potentially regulate other physiologically important hypothalamic neuronal circuits.

  20. Reduction in spontaneous firing of mouse excitatory layer 4 cortical neurons following visual classical conditioning

    Science.gov (United States)

    Bekisz, Marek; Shendye, Ninad; Raciborska, Ida; Wróbel, Andrzej; Waleszczyk, Wioletta J.

    2017-08-01

    The process of learning induces plastic changes in neuronal network of the brain. Our earlier studies on mice showed that classical conditioning in which monocular visual stimulation was paired with an electric shock to the tail enhanced GABA immunoreactivity within layer 4 of the monocular part of the primary visual cortex (V1), contralaterally to the stimulated eye. In the present experiment we investigated whether the same classical conditioning paradigm induces changes of neuronal excitability in this cortical area. Two experimental groups were used: mice that underwent 7-day visual classical conditioning and controls. Patch-clamp whole-cell recordings were performed from ex vivo slices of mouse V1. The slices were perfused with the modified artificial cerebrospinal fluid, the composition of which better mimics the brain interstitial fluid in situ and induces spontaneous activity. The neuronal excitability was characterized by measuring the frequency of spontaneous action potentials. We found that layer 4 star pyramidal cells located in the monocular representation of the "trained" eye in V1 had lower frequency of spontaneous activity in comparison with neurons from the same cortical region of control animals. Weaker spontaneous firing indicates decreased general excitability of star pyramidal neurons within layer 4 of the monocular representation of the "trained" eye in V1. Such effect could result from enhanced inhibitory processes accompanying learning in this cortical area.

  1. β1 integrin signaling promotes neuronal migration along vascular scaffolds in the post-stroke brain

    Directory of Open Access Journals (Sweden)

    Teppei Fujioka

    2017-02-01

    Full Text Available Cerebral ischemic stroke is a main cause of chronic disability. However, there is currently no effective treatment to promote recovery from stroke-induced neurological symptoms. Recent studies suggest that after stroke, immature neurons, referred to as neuroblasts, generated in a neurogenic niche, the ventricular-subventricular zone, migrate toward the injured area, where they differentiate into mature neurons. Interventions that increase the number of neuroblasts distributed at and around the lesion facilitate neuronal repair in rodent models for ischemic stroke, suggesting that promoting neuroblast migration in the post-stroke brain could improve efficient neuronal regeneration. To move toward the lesion, neuroblasts form chain-like aggregates and migrate along blood vessels, which are thought to increase their migration efficiency. However, the molecular mechanisms regulating these migration processes are largely unknown. Here we studied the role of β1-class integrins, transmembrane receptors for extracellular matrix proteins, in these migrating neuroblasts. We found that the neuroblast chain formation and blood vessel-guided migration critically depend on β1 integrin signaling. β1 integrin facilitated the adhesion of neuroblasts to laminin and the efficient translocation of their soma during migration. Moreover, artificial laminin-containing scaffolds promoted neuroblast chain formation and migration toward the injured area. These data suggest that laminin signaling via β1 integrin supports vasculature-guided neuronal migration to efficiently supply neuroblasts to injured areas. This study also highlights the importance of vascular scaffolds for cell migration in development and regeneration.

  2. Proposal for an All-Spin Artificial Neural Network: Emulating Neural and Synaptic Functionalities Through Domain Wall Motion in Ferromagnets.

    Science.gov (United States)

    Sengupta, Abhronil; Shim, Yong; Roy, Kaushik

    2016-12-01

    Non-Boolean computing based on emerging post-CMOS technologies can potentially pave the way for low-power neural computing platforms. However, existing work on such emerging neuromorphic architectures have either focused on solely mimicking the neuron, or the synapse functionality. While memristive devices have been proposed to emulate biological synapses, spintronic devices have proved to be efficient at performing the thresholding operation of the neuron at ultra-low currents. In this work, we propose an All-Spin Artificial Neural Network where a single spintronic device acts as the basic building block of the system. The device offers a direct mapping to synapse and neuron functionalities in the brain while inter-layer network communication is accomplished via CMOS transistors. To the best of our knowledge, this is the first demonstration of a neural architecture where a single nanoelectronic device is able to mimic both neurons and synapses. The ultra-low voltage operation of low resistance magneto-metallic neurons enables the low-voltage operation of the array of spintronic synapses, thereby leading to ultra-low power neural architectures. Device-level simulations, calibrated to experimental results, was used to drive the circuit and system level simulations of the neural network for a standard pattern recognition problem. Simulation studies indicate energy savings by  ∼  100× in comparison to a corresponding digital/analog CMOS neuron implementation.

  3. Artificial neural networks in NDT

    International Nuclear Information System (INIS)

    Abdul Aziz Mohamed

    2001-01-01

    Artificial neural networks, simply known as neural networks, have attracted considerable interest in recent years largely because of a growing recognition of the potential of these computational paradigms as powerful alternative models to conventional pattern recognition or function approximation techniques. The neural networks approach is having a profound effect on almost all fields, and has been utilised in fields Where experimental inter-disciplinary work is being carried out. Being a multidisciplinary subject with a broad knowledge base, Nondestructive Testing (NDT) or Nondestructive Evaluation (NDE) is no exception. This paper explains typical applications of neural networks in NDT/NDE. Three promising types of neural networks are highlighted, namely, back-propagation, binary Hopfield and Kohonen's self-organising maps. (Author)

  4. An artificial neuro-anatomist

    International Nuclear Information System (INIS)

    Mangin, J.F.

    2006-01-01

    The fact that the human brain visual system is based on stereo-vision is a real handicap when analysing dense 3D representations of the human brain. The success of the methods of analysis based on the 3D proportional system has shown the advantage of using computer based system to interpret such complex images. The underlying strategy, however, is restricted to low level vision, which can not address any issue. Our approach advocates for the development of complete computer vision systems dedicated to the brain, which may be of great help for the future of neuroimaging. In our opinion, indeed, brain imaging is sufficiently focused to be a promising niche for the development of artificial intelligence. (N.C.)

  5. Apartes desde la inteligencia artificial

    Directory of Open Access Journals (Sweden)

    Luis Carlos Torres Soler

    1998-05-01

    Full Text Available El estudio y desarrollo de la inteligencia artificial no debe centrarse sólo en la creación de software o hardware que permita realizar procesos algorítmicos o heurísticos en el computador, de tal forma que produzcan soluciones óptimas y eficientes al resolver un problema complejo, ya sea de manejo de información o de toma de decisiones, o crear máquinas que tengan buena apariencia del ser humano; se debe, sobre todo, analizar la parte neurológica y sicológica que presenta el individuo al solucionar problemas. Además, es importante conocer la capacidad intelectual de la persona, de ahí la variedad de carreras profesionales que existen; no puede quedar por fuera de los sistemas inteligentes la concepción del amor o admiración.

  6. Research and applications: Artificial intelligence

    Science.gov (United States)

    Raphael, B.; Fikes, R. E.; Chaitin, L. J.; Hart, P. E.; Duda, R. O.; Nilsson, N. J.

    1971-01-01

    A program of research in the field of artificial intelligence is presented. The research areas discussed include automatic theorem proving, representations of real-world environments, problem-solving methods, the design of a programming system for problem-solving research, techniques for general scene analysis based upon television data, and the problems of assembling an integrated robot system. Major accomplishments include the development of a new problem-solving system that uses both formal logical inference and informal heuristic methods, the development of a method of automatic learning by generalization, and the design of the overall structure of a new complete robot system. Eight appendices to the report contain extensive technical details of the work described.

  7. Artificial intelligence and process management

    International Nuclear Information System (INIS)

    Epton, J.B.A.

    1989-01-01

    Techniques derived from work in artificial intelligence over the past few decades are beginning to change the approach in applying computers to process management. To explore this new approach and gain real practical experience of its potential a programme of experimental applications was initiated by Sira in collaboration with the process industry. This programme encompassed a family of experimental applications ranging from process monitoring, through supervisory control and troubleshooting to planning and scheduling. The experience gained has led to a number of conclusions regarding the present level of maturity of the technology, the potential for further developments and the measures required to secure the levels of system integrity necessary in on-line applications to critical processes. (author)

  8. [Artificial Intelligence in Drug Discovery].

    Science.gov (United States)

    Fujiwara, Takeshi; Kamada, Mayumi; Okuno, Yasushi

    2018-04-01

    According to the increase of data generated from analytical instruments, application of artificial intelligence(AI)technology in medical field is indispensable. In particular, practical application of AI technology is strongly required in "genomic medicine" and "genomic drug discovery" that conduct medical practice and novel drug development based on individual genomic information. In our laboratory, we have been developing a database to integrate genome data and clinical information obtained by clinical genome analysis and a computational support system for clinical interpretation of variants using AI. In addition, with the aim of creating new therapeutic targets in genomic drug discovery, we have been also working on the development of a binding affinity prediction system for mutated proteins and drugs by molecular dynamics simulation using supercomputer "Kei". We also have tackled for problems in a drug virtual screening. Our developed AI technology has successfully generated virtual compound library, and deep learning method has enabled us to predict interaction between compound and target protein.

  9. Innovative applications of artificial intelligence

    Science.gov (United States)

    Schorr, Herbert; Rappaport, Alain

    Papers concerning applications of artificial intelligence are presented, covering applications in aerospace technology, banking and finance, biotechnology, emergency services, law, media planning, music, the military, operations management, personnel management, retail packaging, and manufacturing assembly and design. Specific topics include Space Shuttle telemetry monitoring, an intelligent training system for Space Shuttle flight controllers, an expert system for the diagnostics of manufacturing equipment, a logistics management system, a cooling systems design assistant, and a knowledge-based integrated circuit design critic. Additional topics include a hydraulic circuit design assistant, the use of a connector assembly specification expert system to harness detailed assembly process knowledge, a mixed initiative approach to airlift planning, naval battle management decision aids, an inventory simulation tool, a peptide synthesis expert system, and a system for planning the discharging and loading of container ships.

  10. Coherence resonance in globally coupled neuronal networks with different neuron numbers

    International Nuclear Information System (INIS)

    Ning Wei-Lian; Zhang Zheng-Zhen; Zeng Shang-You; Luo Xiao-Shu; Hu Jin-Lin; Zeng Shao-Wen; Qiu Yi; Wu Hui-Si

    2012-01-01

    Because a brain consists of tremendous neuronal networks with different neuron numbers ranging from tens to tens of thousands, we study the coherence resonance due to ion channel noises in globally coupled neuronal networks with different neuron numbers. We confirm that for all neuronal networks with different neuron numbers there exist the array enhanced coherence resonance and the optimal synaptic conductance to cause the maximal spiking coherence. Furthermoremore, the enhancement effects of coupling on spiking coherence and on optimal synaptic conductance are almost the same, regardless of the neuron numbers in the neuronal networks. Therefore for all the neuronal networks with different neuron numbers in the brain, relative weak synaptic conductance (0.1 mS/cm 2 ) is sufficient to induce the maximal spiking coherence and the best sub-threshold signal encoding. (interdisciplinary physics and related areas of science and technology)

  11. A microsensor array for quantification of lubricant contaminants using a back propagation artificial neural network

    International Nuclear Information System (INIS)

    Zhu, Xiaoliang; Du, Li; Zhe, Jiang; Liu, Bendong

    2016-01-01

    We present a method based on an electrochemical sensor array and a back propagation artificial neural network for detection and quantification of four properties of lubrication oil, namely water (0, 500 ppm, 1000 ppm), total acid number (TAN) (13.1, 13.7, 14.4, 15.6 mg KOH g −1 ), soot (0, 1%, 2%, 3%) and sulfur content (1.3%, 1.37%, 1.44%, 1.51%). The sensor array, consisting of four micromachined electrochemical sensors, detects the four properties with overlapping sensitivities. A total set of 36 oil samples containing mixtures of water, soot, and sulfuric acid with different concentrations were prepared for testing. The sensor array’s responses were then divided to three sets: training sets (80% data), validation sets (10%) and testing sets (10%). Several back propagation artificial neural network architectures were trained with the training and validation sets; one architecture with four input neurons, 50 and 5 neurons in the first and second hidden layer, and four neurons in the output layer was selected. The selected neural network was then tested using the four sets of testing data (10%). Test results demonstrated that the developed artificial neural network is able to quantitatively determine the four lubrication properties (water, TAN, soot, and sulfur content) with a maximum prediction error of 18.8%, 6.0%, 6.7%, and 5.4%, respectively, indicting a good match between the target and predicted values. With the developed network, the sensor array could be potentially used for online lubricant oil condition monitoring. (paper)

  12. Artificial neural network modeling and optimization of ultrahigh pressure extraction of green tea polyphenols.

    Science.gov (United States)

    Xi, Jun; Xue, Yujing; Xu, Yinxiang; Shen, Yuhong

    2013-11-01

    In this study, the ultrahigh pressure extraction of green tea polyphenols was modeled and optimized by a three-layer artificial neural network. A feed-forward neural network trained with an error back-propagation algorithm was used to evaluate the effects of pressure, liquid/solid ratio and ethanol concentration on the total phenolic content of green tea extracts. The neural network coupled with genetic algorithms was also used to optimize the conditions needed to obtain the highest yield of tea polyphenols. The obtained optimal architecture of artificial neural network model involved a feed-forward neural network with three input neurons, one hidden layer with eight neurons and one output layer including single neuron. The trained network gave the minimum value in the MSE of 0.03 and the maximum value in the R(2) of 0.9571, which implied a good agreement between the predicted value and the actual value, and confirmed a good generalization of the network. Based on the combination of neural network and genetic algorithms, the optimum extraction conditions for the highest yield of green tea polyphenols were determined as follows: 498.8 MPa for pressure, 20.8 mL/g for liquid/solid ratio and 53.6% for ethanol concentration. The total phenolic content of the actual measurement under the optimum predicated extraction conditions was 582.4 ± 0.63 mg/g DW, which was well matched with the predicted value (597.2mg/g DW). This suggests that the artificial neural network model described in this work is an efficient quantitative tool to predict the extraction efficiency of green tea polyphenols. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

  13. The Nexus Between Artificial Intellgence and Economics

    NARCIS (Netherlands)

    van de Gevel, A.J.W.; Noussair, C.N.

    2013-01-01

    The manuscript reviews some key ideas about artificial intelligence, and relates them to economics. These include its relation to robotics, and the concepts of synthetic emotions, consciousness, and life. The economic implications of the advent of artificial intelligence, such as its effect on

  14. Artificial Intelligence--Applications in Education.

    Science.gov (United States)

    Poirot, James L.; Norris, Cathleen A.

    1987-01-01

    This first in a projected series of five articles discusses artificial intelligence and its impact on education. Highlights include the history of artificial intelligence and the impact of microcomputers; learning processes; human factors and interfaces; computer assisted instruction and intelligent tutoring systems; logic programing; and expert…

  15. On the Design of Artificial Stock Markets

    NARCIS (Netherlands)

    K. Boer-Sorban (Katalin); A. de Bruin (Arie); U. Kaymak (Uzay)

    2005-01-01

    textabstractArtificial stock markets are designed with the aim to study and understand market dynamics by representing (part of) real stock markets. Since there is a large variety of real stock markets with several partially observable elements and hidden processes, artificial markets differ

  16. Artificial intelligence in astronomy - a forecast.

    Science.gov (United States)

    Adorf, H. M.

    Since several years artificial intelligence techniques are being actively used in astronomy, particularly within the Hubble Space Telescope project. This contribution reviews achievements, analyses some problems of using artificial intelligence in an astronomical environment, and projects current AI programming trends into the future.

  17. The Artificial Intelligence Applications to Learning Programme.

    Science.gov (United States)

    Williams, Noel

    1992-01-01

    Explains the Artificial Intelligence Applications to Learning Programme, which was developed in the United Kingdom to explore and accelerate the use of artificial intelligence (AI) technologies in learning in both the educational and industrial sectors. Highlights include program evaluation, marketing, ownership of information, consortia, and cost…

  18. Artificial Neural Networks and Instructional Technology.

    Science.gov (United States)

    Carlson, Patricia A.

    1991-01-01

    Artificial neural networks (ANN), part of artificial intelligence, are discussed. Such networks are fed sample cases (training sets), learn how to recognize patterns in the sample data, and use this experience in handling new cases. Two cognitive roles for ANNs (intelligent filters and spreading, associative memories) are examined. Prototypes…

  19. Contribution of artificial intelligence to operation

    International Nuclear Information System (INIS)

    Malvache, P.; Mourlevat, J.L.

    1993-01-01

    Artificial Intelligence techniques are already used in nuclear plants for assistance to operation: synthesis from numerous information sources may be then derived, based on expert knowledge. Artificial intelligence may be used also for quality and reliability assessment of software-based control-command systems. Various expert systems developed by CEA, EDF and Framatome are presented

  20. Airway Complications of Total Artificial Heart.

    Science.gov (United States)

    Pathak, Vikas; Donovan, Colin; Malhotra, Rajiv

    2017-02-01

    The total artificial heart is the mechanical device which is used as a bridge to the heart transplant in patients with biventricular failure. Due to the mechanical nature of the device, patients receiving total artificial heart (TAH) require to be on anticoagulation therapy. Hemorrhage and coagulopathy are few of the known complications of TAH.

  1. The artificial pancreas : From logic to life

    NARCIS (Netherlands)

    Kropff, J.

    2017-01-01

    In this thesis we investigated the efficacy of real-life use of an artificial pancreas starting with use of these systems in a hotel setting and finally 24/7 long-term use at home. We investigated the accuracy of continuous glucose monitoring (CGM) systems that act as input for the artificial

  2. Web Intelligence and Artificial Intelligence in Education

    Science.gov (United States)

    Devedzic, Vladan

    2004-01-01

    This paper surveys important aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED) research. WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web-related products, systems, services, and…

  3. Artificial intelligence and the future.

    Science.gov (United States)

    Clocksin, William F

    2003-08-15

    We consider some of the ideas influencing current artificial-intelligence research and outline an alternative conceptual framework that gives priority to social relationships as a key component and constructor of intelligent behaviour. The framework starts from Weizenbaum's observation that intelligence manifests itself only relative to specific social and cultural contexts. This is in contrast to a prevailing view, which sees intelligence as an abstract capability of the individual mind based on a mechanism for rational thought. The new approach is not based on the conventional idea that the mind is a rational processor of symbolic information, nor does it require the idea that thought is a kind of abstract problem solving with a semantics that is independent of its embodiment. Instead, priority is given to affective and social responses that serve to engage the whole agent in the life of the communities in which it participates. Intelligence is seen not as the deployment of capabilities for problem solving, but as constructed by the continual, ever-changing and unfinished engagement with the social group within the environment. The construction of the identity of the intelligent agent involves the appropriation or 'taking up' of positions within the conversations and narratives in which it participates. Thus, the new approach argues that the intelligent agent is shaped by the meaning ascribed to experience, by its situation in the social matrix, and by practices of self and of relationship into which intelligent life is recruited. This has implications for the technology of the future, as, for example, classic artificial intelligence models such as goal-directed problem solving are seen as special cases of narrative practices instead of as ontological foundations.

  4. Artificial limb representation in amputees.

    Science.gov (United States)

    van den Heiligenberg, Fiona M Z; Orlov, Tanya; Macdonald, Scott N; Duff, Eugene P; Henderson Slater, David; Beckmann, Christian F; Johansen-Berg, Heidi; Culham, Jody C; Makin, Tamar R

    2018-05-01

    The human brain contains multiple hand-selective areas, in both the sensorimotor and visual systems. Could our brain repurpose neural resources, originally developed for supporting hand function, to represent and control artificial limbs? We studied individuals with congenital or acquired hand-loss (hereafter one-handers) using functional MRI. We show that the more one-handers use an artificial limb (prosthesis) in their everyday life, the stronger visual hand-selective areas in the lateral occipitotemporal cortex respond to prosthesis images. This was found even when one-handers were presented with images of active prostheses that share the functionality of the hand but not necessarily its visual features (e.g. a 'hook' prosthesis). Further, we show that daily prosthesis usage determines large-scale inter-network communication across hand-selective areas. This was demonstrated by increased resting state functional connectivity between visual and sensorimotor hand-selective areas, proportional to the intensiveness of everyday prosthesis usage. Further analysis revealed a 3-fold coupling between prosthesis activity, visuomotor connectivity and usage, suggesting a possible role for the motor system in shaping use-dependent representation in visual hand-selective areas, and/or vice versa. Moreover, able-bodied control participants who routinely observe prosthesis usage (albeit less intensively than the prosthesis users) showed significantly weaker associations between degree of prosthesis observation and visual cortex activity or connectivity. Together, our findings suggest that altered daily motor behaviour facilitates prosthesis-related visual processing and shapes communication across hand-selective areas. This neurophysiological substrate for prosthesis embodiment may inspire rehabilitation approaches to improve usage of existing substitutionary devices and aid implementation of future assistive and augmentative technologies.

  5. Biofluid lubrication for artificial joints

    Science.gov (United States)

    Pendleton, Alice Mae

    This research investigated biofluid lubrication related to artificial joints using tribological and rheological approaches. Biofluids studied here represent two categories of fluids, base fluids and nanostructured biofluids. Base fluids were studied through comparison of synthetic fluids (simulated body fluid and hyaluronic acid) as well as natural biofluids (from dogs, horses, and humans) in terms of viscosity and fluid shear stress. The nano-structured biofluids were formed using molecules having well-defined shapes. Understanding nano-structured biofluids leads to new ways of design and synthesis of biofluids that are beneficial for artificial joint performance. Experimental approaches were utilized in the present research. This includes basic analysis of biofluids' property, such as viscosity, fluid shear stress, and shear rate using rheological experiments. Tribological investigation and surface characterization were conducted in order to understand effects of molecular and nanostructures on fluid lubrication. Workpiece surface structure and wear mechanisms were investigated using a scanning electron microscope and a transmission electron microscope. The surface topography was examined using a profilometer. The results demonstrated that with the adding of solid additives, such as crown ether or fullerene acted as rough as the other solids in the 3-body wear systems. In addition, the fullerene supplied low friction and low wear, which designates the lubrication purpose of this particular particle system. This dissertation is constructed of six chapters. The first chapter is an introduction to body fluids, as mentioned earlier. After Chapter II, it examines the motivation and approach of the present research, Chapter III discusses the experimental approaches, including materials, experimental setup, and conditions. In Chapter IV, lubrication properties of various fluids are discussed. The tribological properties and performance nanostructured biofluids are

  6. ESTIMACIÓN DE LA CARGA DE TRANSFORMADORES DE POTENCIA UTILIZANDO UNA RED NEURONAL ARTIFICIAL

    OpenAIRE

    Agudelo, Laura; Velilla, Esteban; López, Jesús M

    2014-01-01

    En este artículo se presenta una metodología para estimar la curva de carga de transformadores de potencia utilizando redes neuronales artificiales. Para implementar la metodología propuesta se utilizaron datos reales de dos transformadores ubicados en diferentes zonas geográficas y con diferentes condiciones de operación. La técnica de estimación de carga fue implementada con datos históricos de la empresa Interconexión Eléctrica S.A (ISA). Para realizar la predicción de las curvas de carga ...

  7. Responses of single neurons and neuronal ensembles in frog first- and second-order olfactory neurons

    Czech Academy of Sciences Publication Activity Database

    Rospars, J. P.; Šanda, Pavel; Lánský, Petr; Duchamp-Viret, P.

    2013-01-01

    Roč. 1536, NOV 6 (2013), s. 144-158 ISSN 0006-8993 R&D Projects: GA ČR(CZ) GBP304/12/G069; GA ČR(CZ) GAP103/11/0282 Institutional support: RVO:67985823 Keywords : olfaction * spiking activity * neuronal model Subject RIV: JD - Computer Applications, Robotics Impact factor: 2.828, year: 2013

  8. Application of artificial neural networks to identify equilibration in computer simulations

    Science.gov (United States)

    Leibowitz, Mitchell H.; Miller, Evan D.; Henry, Michael M.; Jankowski, Eric

    2017-11-01

    Determining which microstates generated by a thermodynamic simulation are representative of the ensemble for which sampling is desired is a ubiquitous, underspecified problem. Artificial neural networks are one type of machine learning algorithm that can provide a reproducible way to apply pattern recognition heuristics to underspecified problems. Here we use the open-source TensorFlow machine learning library and apply it to the problem of identifying which hypothetical observation sequences from a computer simulation are “equilibrated” and which are not. We generate training populations and test populations of observation sequences with embedded linear and exponential correlations. We train a two-neuron artificial network to distinguish the correlated and uncorrelated sequences. We find that this simple network is good enough for > 98% accuracy in identifying exponentially-decaying energy trajectories from molecular simulations.

  9. Artificial Synaptic Devices Based on Natural Chicken Albumen Coupled Electric-Double-Layer Transistors.

    Science.gov (United States)

    Wu, Guodong; Feng, Ping; Wan, Xiang; Zhu, Liqiang; Shi, Yi; Wan, Qing

    2016-03-24

    Recent progress in using biomaterials to fabricate functional electronics has got growing attention for the new generation of environmentally friendly and biocompatible electronic devices. As a kind of biological material with rich source, proteins are essential natural component of all organisms. At the same time, artificial synaptic devices are of great significance for neuromorphic systems because they can emulate the signal process and memory behaviors of biological synapses. In this report, natural chicken albumen with high proton conductivity was used as the coupling electrolyte film for organic/inorganic hybrid synaptic devices fabrication. Some important synaptic functions including paired-pulse facilitation, dynamic filtering, short-term to long-term memory transition and spatial summation and shunting inhibition were successfully mimicked. Our results are very interesting for biological friendly artificial neuron networks and neuromorphic systems.

  10. Modeling the thermotaxis behavior of C.elegans based on the artificial neural network.

    Science.gov (United States)

    Li, Mingxu; Deng, Xin; Wang, Jin; Chen, Qiaosong; Tang, Yun

    2016-07-03

    ASBTRACT This research aims at modeling the thermotaxis behavior of C.elegans which is a kind of nematode with full clarified neuronal connections. Firstly, this work establishes the motion model which can perform the undulatory locomotion with turning behavior. Secondly, the thermotaxis behavior is modeled by nonlinear functions and the nonlinear functions are learned by artificial neural network. Once the artificial neural networks have been well trained, they can perform the desired thermotaxis behavior. Last, several testing simulations are carried out to verify the effectiveness of the model for thermotaxis behavior. This work also analyzes the different performances of the model under different environments. The testing results reveal the essence of the thermotaxis of C.elegans to some extent, and theoretically support the research on the navigation of the crawling robots.

  11. Artificial Synaptic Devices Based on Natural Chicken Albumen Coupled Electric-Double-Layer Transistors

    Science.gov (United States)

    Wu, Guodong; Feng, Ping; Wan, Xiang; Zhu, Liqiang; Shi, Yi; Wan, Qing

    2016-03-01

    Recent progress in using biomaterials to fabricate functional electronics has got growing attention for the new generation of environmentally friendly and biocompatible electronic devices. As a kind of biological material with rich source, proteins are essential natural component of all organisms. At the same time, artificial synaptic devices are of great significance for neuromorphic systems because they can emulate the signal process and memory behaviors of biological synapses. In this report, natural chicken albumen with high proton conductivity was used as the coupling electrolyte film for organic/inorganic hybrid synaptic devices fabrication. Some important synaptic functions including paired-pulse facilitation, dynamic filtering, short-term to long-term memory transition and spatial summation and shunting inhibition were successfully mimicked. Our results are very interesting for biological friendly artificial neuron networks and neuromorphic systems.

  12. Three-Dimensional Human iPSC-Derived Artificial Skeletal Muscles Model Muscular Dystrophies and Enable Multilineage Tissue Engineering

    Directory of Open Access Journals (Sweden)

    Sara Martina Maffioletti

    2018-04-01

    Full Text Available Summary: Generating human skeletal muscle models is instrumental for investigating muscle pathology and therapy. Here, we report the generation of three-dimensional (3D artificial skeletal muscle tissue from human pluripotent stem cells, including induced pluripotent stem cells (iPSCs from patients with Duchenne, limb-girdle, and congenital muscular dystrophies. 3D skeletal myogenic differentiation of pluripotent cells was induced within hydrogels under tension to provide myofiber alignment. Artificial muscles recapitulated characteristics of human skeletal muscle tissue and could be implanted into immunodeficient mice. Pathological cellular hallmarks of incurable forms of severe muscular dystrophy could be modeled with high fidelity using this 3D platform. Finally, we show generation of fully human iPSC-derived, complex, multilineage muscle models containing key isogenic cellular constituents of skeletal muscle, including vascular endothelial cells, pericytes, and motor neurons. These results lay the foundation for a human skeletal muscle organoid-like platform for disease modeling, regenerative medicine, and therapy development. : Maffioletti et al. generate human 3D artificial skeletal muscles from healthy donors and patient-specific pluripotent stem cells. These human artificial muscles accurately model severe genetic muscle diseases. They can be engineered to include other cell types present in skeletal muscle, such as vascular cells and motor neurons. Keywords: skeletal muscle, pluripotent stem cells, iPS cells, myogenic differentiation, tissue engineering, disease modeling, muscular dystrophy, organoids

  13. Development of Artificial Neural Network Model of Crude Oil Distillation Column

    Directory of Open Access Journals (Sweden)

    Ali Hussein Khalaf

    2016-02-01

    Full Text Available Artificial neural network in MATLAB simulator is used to model Baiji crude oil distillation unit based on data generated from aspen-HYSYS simulator. Thirteen inputs, six outputs and over 1487 data set are used to model the actual unit. Nonlinear autoregressive network with exogenous inputs (NARXand back propagation algorithm are used for training. Seventy percent of data are used for training the network while the remaining  thirty percent are used for testing  and validating the network to determine its prediction accuracy. One hidden layer and 34 hidden neurons are used for the proposed network with MSE of 0.25 is obtained. The number of neuron are selected based on less MSE for the network. The model founded to predict the optimal operating conditions for different objective functions within the training limit since ANN models are poor extrapolators. They are usually only reliable within the range of data that they had been trained for.

  14. Development of Artificial Neural Network Model of Crude Oil Distillation Column

    Directory of Open Access Journals (Sweden)

    Duraid F. Ahmed

    2016-02-01

    Full Text Available Artificial neural network in MATLAB simulator is used to model Baiji crude oil distillation unit based on data generated from aspen-HYSYS simulator. Thirteen inputs, six outputs and over 1487 data set are used to model the actual unit. Nonlinear autoregressive network with exogenous inputs (NARX and back propagation algorithm are used for training. Seventy percent of data are used for training the network while the remaining thirty percent are used for testing and validating the network to determine its prediction accuracy. One hidden layer and 34 hidden neurons are used for the proposed network with MSE of 0.25 is obtained. The number of neuron are selected based on less MSE for the network. The model founded to predict the optimal operating conditions for different objective functions within the training limit since ANN models are poor extrapolators. They are usually only reliable within the range of data that they had been trained for.

  15. Artificial Lipid Membranes: Past, Present, and Future.

    Science.gov (United States)

    Siontorou, Christina G; Nikoleli, Georgia-Paraskevi; Nikolelis, Dimitrios P; Karapetis, Stefanos K

    2017-07-26

    The multifaceted role of biological membranes prompted early the development of artificial lipid-based models with a primary view of reconstituting the natural functions in vitro so as to study and exploit chemoreception for sensor engineering. Over the years, a fair amount of knowledge on the artificial lipid membranes, as both, suspended or supported lipid films and liposomes, has been disseminated and has helped to diversify and expand initial scopes. Artificial lipid membranes can be constructed by several methods, stabilized by various means, functionalized in a variety of ways, experimented upon intensively, and broadly utilized in sensor development, drug testing, drug discovery or as molecular tools and research probes for elucidating the mechanics and the mechanisms of biological membranes. This paper reviews the state-of-the-art, discusses the diversity of applications, and presents future perspectives. The newly-introduced field of artificial cells further broadens the applicability of artificial membranes in studying the evolution of life.

  16. Reinforcement Learning Based Artificial Immune Classifier

    Directory of Open Access Journals (Sweden)

    Mehmet Karakose

    2013-01-01

    Full Text Available One of the widely used methods for classification that is a decision-making process is artificial immune systems. Artificial immune systems based on natural immunity system can be successfully applied for classification, optimization, recognition, and learning in real-world problems. In this study, a reinforcement learning based artificial immune classifier is proposed as a new approach. This approach uses reinforcement learning to find better antibody with immune operators. The proposed new approach has many contributions according to other methods in the literature such as effectiveness, less memory cell, high accuracy, speed, and data adaptability. The performance of the proposed approach is demonstrated by simulation and experimental results using real data in Matlab and FPGA. Some benchmark data and remote image data are used for experimental results. The comparative results with supervised/unsupervised based artificial immune system, negative selection classifier, and resource limited artificial immune classifier are given to demonstrate the effectiveness of the proposed new method.

  17. Transport modeling: An artificial immune system approach

    Directory of Open Access Journals (Sweden)

    Teodorović Dušan

    2006-01-01

    Full Text Available This paper describes an artificial immune system approach (AIS to modeling time-dependent (dynamic, real time transportation phenomenon characterized by uncertainty. The basic idea behind this research is to develop the Artificial Immune System, which generates a set of antibodies (decisions, control actions that altogether can successfully cover a wide range of potential situations. The proposed artificial immune system develops antibodies (the best control strategies for different antigens (different traffic "scenarios". This task is performed using some of the optimization or heuristics techniques. Then a set of antibodies is combined to create Artificial Immune System. The developed Artificial Immune transportation systems are able to generalize, adapt, and learn based on new knowledge and new information. Applications of the systems are considered for airline yield management, the stochastic vehicle routing, and real-time traffic control at the isolated intersection. The preliminary research results are very promising.

  18. A DISTRIBUTED SMART HOME ARTIFICIAL INTELLIGENCE SYSTEM

    DEFF Research Database (Denmark)

    Lynggaard, Per

    2013-01-01

    A majority of the research performed today explore artificial intelligence in smart homes by using a centralized approach where a smart home server performs the necessary calculations. This approach has some disadvantages that can be overcome by shifting focus to a distributed approach where...... the artificial intelligence system is implemented as distributed as agents running parts of the artificial intelligence system. This paper presents a distributed smart home architecture that distributes artificial intelligence in smart homes and discusses the pros and cons of such a concept. The presented...... distributed model is a layered model. Each layer offers a different complexity level of the embedded distributed artificial intelligence. At the lowest layer smart objects exists, they are small cheap embedded microcontroller based smart devices that are powered by batteries. The next layer contains a more...

  19. Prediction of electricity and lpg consumption in a hotel using artificial neural networks

    International Nuclear Information System (INIS)

    Montero, L Reiners; Perez T, Carlos; Gongora L, Ever; Marrero, R Secundino

    2009-01-01

    This work was developed in order to improve the current tools for energy planning. This makes possible to predict electricity and LPG consumption in a tourist facility with accuracy higher than 90% by using Artificial Neuronal Networks (ANN) as fitting and predictive models. Local climatology and occupational patterns were used as entering variables for the models. Parametric modeling was performed as starting conditions and then improved with ANN. Matlab tools were used for calculations. The average deviation when predicting electricity consumption was 0.6% with a standard deviation of 4%. For LPG consumption the average deviation was less than 1% with a standard deviation of 1.3%.

  20. Differential effects of cocaine on histone posttranslational modifications in identified populations of striatal neurons.

    Science.gov (United States)

    Jordi, Emmanuelle; Heiman, Myriam; Marion-Poll, Lucile; Guermonprez, Pierre; Cheng, Shuk Kei; Nairn, Angus C; Greengard, Paul; Girault, Jean-Antoine

    2013-06-04

    Drugs of abuse, such as cocaine, induce changes in gene expression and epigenetic marks including alterations in histone posttranslational modifications in striatal neurons. These changes are thought to participate in physiological memory mechanisms and to be critical for long-term behavioral alterations. However, the striatum is composed of multiple cell types, including two distinct populations of medium-sized spiny neurons, and little is known concerning the cell-type specificity of epigenetic modifications. To address this question we used bacterial artificial chromosome transgenic mice, which express EGFP fused to the N-terminus of the large subunit ribosomal protein L10a driven by the D1 or D2 dopamine receptor (D1R, D2R) promoter, respectively. Fluorescence in nucleoli was used to sort nuclei from D1R- or D2R-expressing neurons and to quantify by flow cytometry the cocaine-induced changes in histone acetylation and methylation specifically in these two types of nuclei. The two populations of medium-sized spiny neurons displayed different patterns of histone modifications 15 min or 24 h after a single injection of cocaine or 24 h after seven daily injections. In particular, acetylation of histone 3 on Lys 14 and of histone 4 on Lys 5 and 12, and methylation of histone 3 on Lys 9 exhibited distinct and persistent changes in the two cell types. Our data provide insights into the differential epigenetic responses to cocaine in D1R- and D2R-positive neurons and their potential regulation, which may participate in the persistent effects of cocaine in these neurons. The method described should have general utility for studying nuclear modifications in different types of neuronal or nonneuronal cell types.

  1. Evaluation of extra virgin olive oil stability by artificial neural network.

    Science.gov (United States)

    Silva, Simone Faria; Anjos, Carlos Alberto Rodrigues; Cavalcanti, Rodrigo Nunes; Celeghini, Renata Maria dos Santos

    2015-07-15

    The stability of extra virgin olive oil in polyethylene terephthalate bottles and tinplate cans stored for 6 months under dark and light conditions was evaluated. The following analyses were carried out: free fatty acids, peroxide value, specific extinction at 232 and 270 nm, chlorophyll, L(∗)C(∗)h color, total phenolic compounds, tocopherols and squalene. The physicochemical changes were evaluated by artificial neural network (ANN) modeling with respect to light exposure conditions and packaging material. The optimized ANN structure consists of 11 input neurons, 18 hidden neurons and 5 output neurons using hyperbolic tangent and softmax activation functions in hidden and output layers, respectively. The five output neurons correspond to five possible classifications according to packaging material (PET amber, PET transparent and tinplate can) and light exposure (dark and light storage). The predicted physicochemical changes agreed very well with the experimental data showing high classification accuracy for test (>90%) and training set (>85). Sensitivity analysis showed that free fatty acid content, peroxide value, L(∗)Cab(∗)hab(∗) color parameters, tocopherol and chlorophyll contents were the physicochemical attributes with the most discriminative power. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Lateral Information Processing by Spiking Neurons: A Theoretical Model of the Neural Correlate of Consciousness

    Directory of Open Access Journals (Sweden)

    Marc Ebner

    2011-01-01

    Full Text Available Cognitive brain functions, for example, sensory perception, motor control and learning, are understood as computation by axonal-dendritic chemical synapses in networks of integrate-and-fire neurons. Cognitive brain functions may occur either consciously or nonconsciously (on “autopilot”. Conscious cognition is marked by gamma synchrony EEG, mediated largely by dendritic-dendritic gap junctions, sideways connections in input/integration layers. Gap-junction-connected neurons define a sub-network within a larger neural network. A theoretical model (the “conscious pilot” suggests that as gap junctions open and close, a gamma-synchronized subnetwork, or zone moves through the brain as an executive agent, converting nonconscious “auto-pilot” cognition to consciousness, and enhancing computation by coherent processing and collective integration. In this study we implemented sideways “gap junctions” in a single-layer artificial neural network to perform figure/ground separation. The set of neurons connected through gap junctions form a reconfigurable resistive grid or sub-network zone. In the model, outgoing spikes are temporally integrated and spatially averaged using the fixed resistive grid set up by neurons of similar function which are connected through gap-junctions. This spatial average, essentially a feedback signal from the neuron's output, determines whether particular gap junctions between neurons will open or close. Neurons connected through open gap junctions synchronize their output spikes. We have tested our gap-junction-defined sub-network in a one-layer neural network on artificial retinal inputs using real-world images. Our system is able to perform figure/ground separation where the laterally connected sub-network of neurons represents a perceived object. Even though we only show results for visual stimuli, our approach should generalize to other modalities. The system demonstrates a moving sub-network zone of

  3. Neurons with two sites of synaptic integration learn invariant representations.

    Science.gov (United States)

    Körding, K P; König, P

    2001-12-01

    Neurons in mammalian cerebral cortex combine specific responses with respect to some stimulus features with invariant responses to other stimulus features. For example, in primary visual cortex, complex cells code for orientation of a contour but ignore its position to a certain degree. In higher areas, such as the inferotemporal cortex, translation-invariant, rotation-invariant, and even view point-invariant responses can be observed. Such properties are of obvious interest to artificial systems performing tasks like pattern recognition. It remains to be resolved how such response properties develop in biological systems. Here we present an unsupervised learning rule that addresses this problem. It is based on a neuron model with two sites of synaptic integration, allowing qualitatively different effects of input to basal and apical dendritic trees, respectively. Without supervision, the system learns to extract invariance properties using temporal or spatial continuity of stimuli. Furthermore, top-down information can be smoothly integrated in the same framework. Thus, this model lends a physiological implementation to approaches of unsupervised learning of invariant-response properties.

  4. 7 CFR 51.2542 - U.S. Artificially Opened.

    Science.gov (United States)

    2010-01-01

    ... STANDARDS) United States Standards for Grades of Pistachio Nuts in the Shell § 51.2542 U.S. Artificially Opened. “U.S. Artificially Opened” consists of artificially opened pistachio nuts in the shell which meet...

  5. How to make spinal motor neurons.

    Science.gov (United States)

    Davis-Dusenbery, Brandi N; Williams, Luis A; Klim, Joseph R; Eggan, Kevin

    2014-02-01

    All muscle movements, including breathing, walking, and fine motor skills rely on the function of the spinal motor neuron to transmit signals from the brain to individual muscle groups. Loss of spinal motor neuron function underlies several neurological disorders for which treatment has been hampered by the inability to obtain sufficient quantities of primary motor neurons to perform mechanistic studies or drug screens. Progress towards overcoming this challenge has been achieved through the synthesis of developmental biology paradigms and advances in stem cell and reprogramming technology, which allow the production of motor neurons in vitro. In this Primer, we discuss how the logic of spinal motor neuron development has been applied to allow generation of motor neurons either from pluripotent stem cells by directed differentiation and transcriptional programming, or from somatic cells by direct lineage conversion. Finally, we discuss methods to evaluate the molecular and functional properties of motor neurons generated through each of these techniques.

  6. Firing dynamics of an autaptic neuron

    International Nuclear Information System (INIS)

    Wang Heng-Tong; Chen Yong

    2015-01-01

    Autapses are synapses that connect a neuron to itself in the nervous system. Previously, both experimental and theoretical studies have demonstrated that autaptic connections in the nervous system have a significant physiological function. Autapses in nature provide self-delayed feedback, thus introducing an additional timescale to neuronal activities and causing many dynamic behaviors in neurons. Recently, theoretical studies have revealed that an autapse provides a control option for adjusting the response of a neuron: e.g., an autaptic connection can cause the electrical activities of the Hindmarsh–Rose neuron to switch between quiescent, periodic, and chaotic firing patterns; an autapse can enhance or suppress the mode-locking status of a neuron injected with sinusoidal current; and the firing frequency and interspike interval distributions of the response spike train can also be modified by the autapse. In this paper, we review recent studies that showed how an autapse affects the response of a single neuron. (topical review)

  7. Neurons from the adult human dentate nucleus: neural networks in the neuron classification.

    Science.gov (United States)

    Grbatinić, Ivan; Marić, Dušica L; Milošević, Nebojša T

    2015-04-07

    Topological (central vs. border neuron type) and morphological classification of adult human dentate nucleus neurons according to their quantified histomorphological properties using neural networks on real and virtual neuron samples. In the real sample 53.1% and 14.1% of central and border neurons, respectively, are classified correctly with total of 32.8% of misclassified neurons. The most important result present 62.2% of misclassified neurons in border neurons group which is even greater than number of correctly classified neurons (37.8%) in that group, showing obvious failure of network to classify neurons correctly based on computational parameters used in our study. On the virtual sample 97.3% of misclassified neurons in border neurons group which is much greater than number of correctly classified neurons (2.7%) in that group, again confirms obvious failure of network to classify neurons correctly. Statistical analysis shows that there is no statistically significant difference in between central and border neurons for each measured parameter (p>0.05). Total of 96.74% neurons are morphologically classified correctly by neural networks and each one belongs to one of the four histomorphological types: (a) neurons with small soma and short dendrites, (b) neurons with small soma and long dendrites, (c) neuron with large soma and short dendrites, (d) neurons with large soma and long dendrites. Statistical analysis supports these results (pneurons can be classified in four neuron types according to their quantitative histomorphological properties. These neuron types consist of two neuron sets, small and large ones with respect to their perykarions with subtypes differing in dendrite length i.e. neurons with short vs. long dendrites. Besides confirmation of neuron classification on small and large ones, already shown in literature, we found two new subtypes i.e. neurons with small soma and long dendrites and with large soma and short dendrites. These neurons are

  8. Mirror neurons and motor intentionality.

    Science.gov (United States)

    Rizzolatti, Giacomo; Sinigaglia, Corrado

    2007-01-01

    Our social life rests to a large extent on our ability to understand the intentions of others. What are the bases of this ability? A very influential view is that we understand the intentions of others because we are able to represent them as having mental states. Without this meta-representational (mind-reading) ability their behavior would be meaningless to us. Over the past few years this view has been challenged by neurophysiological findings and, in particular, by the discovery of mirror neurons. The functional properties of these neurons indicate that intentional understanding is based primarily on a mechanism that directly matches the sensory representation of the observed actions with one's own motor representation of those same actions. These findings reveal how deeply motor and intentional components of action are intertwined, suggesting that both can be fully comprehended only starting from a motor approach to intentionality.

  9. Oscillatory integration windows in neurons

    Science.gov (United States)

    Gupta, Nitin; Singh, Swikriti Saran; Stopfer, Mark

    2016-01-01

    Oscillatory synchrony among neurons occurs in many species and brain areas, and has been proposed to help neural circuits process information. One hypothesis states that oscillatory input creates cyclic integration windows: specific times in each oscillatory cycle when postsynaptic neurons become especially responsive to inputs. With paired local field potential (LFP) and intracellular recordings and controlled stimulus manipulations we directly test this idea in the locust olfactory system. We find that inputs arriving in Kenyon cells (KCs) sum most effectively in a preferred window of the oscillation cycle. With a computational model, we show that the non-uniform structure of noise in the membrane potential helps mediate this process. Further experiments performed in vivo demonstrate that integration windows can form in the absence of inhibition and at a broad range of oscillation frequencies. Our results reveal how a fundamental coincidence-detection mechanism in a neural circuit functions to decode temporally organized spiking. PMID:27976720

  10. Advanced Applications of Neural Networks and Artificial Intelligence: A Review

    OpenAIRE

    Koushal Kumar; Gour Sundar Mitra Thakur

    2012-01-01

    Artificial Neural Network is a branch of Artificial intelligence and has been accepted as a new computing technology in computer science fields. This paper reviews the field of Artificial intelligence and focusing on recent applications which uses Artificial Neural Networks (ANN’s) and Artificial Intelligence (AI). It also considers the integration of neural networks with other computing methods Such as fuzzy logic to enhance the interpretation ability of data. Artificial Neural Networks is c...

  11. Unbalanced neuronal circuits in addiction.

    Science.gov (United States)

    Volkow, Nora D; Wang, Gen-Jack; Tomasi, Dardo; Baler, Ruben D

    2013-08-01

    Through sequential waves of drug-induced neurochemical stimulation, addiction co-opts the brain's neuronal circuits that mediate reward, motivation to behavioral inflexibility and a severe disruption of self-control and compulsive drug intake. Brain imaging technologies have allowed neuroscientists to map out the neural landscape of addiction in the human brain and to understand how drugs modify it. Published by Elsevier Ltd.

  12. Neurochemical phenotypes of cardiorespiratory neurons.

    Science.gov (United States)

    Pilowsky, Paul M

    2008-12-10

    Interactions between the cardiovascular and respiratory systems have been known for many years but the functional significance of the interactions is still widely debated. Here I discuss the possible role of metabotropic receptors in regulating cardiorespiratory neurons in the brainstem and spinal cord. It is clear that, although much has been discovered, cardiorespiratory regulation is certainly one area that still has a long way to go before its secrets are fully divulged and their function in controlling circulatory and respiratory function is revealed.

  13. Mirror Neurons from Associative Learning

    OpenAIRE

    Catmur, Caroline; Press, Clare; Heyes, Cecilia

    2016-01-01

    Mirror neurons fire both when executing actions and observing others perform similar actions. Their sensorimotor matching properties have generally been considered a genetic adaptation for social cognition; however, in the present chapter we argue that the evidence in favor of this account is not compelling. Instead we present evidence supporting an alternative account: that mirror neurons’ matching properties arise from associative learning during individual development. Notably, this proces...

  14. Trafficking of neuronal calcium channels

    Czech Academy of Sciences Publication Activity Database

    Weiss, Norbert; Zamponi, G. W.

    2017-01-01

    Roč. 1, č. 1 (2017), č. článku NS20160003. ISSN 2059-6553 R&D Projects: GA ČR GA15-13556S; GA MŠk 7AMB15FR015 Institutional support: RVO:61388963 Keywords : calcium channel * neuron * trafficing Subject RIV: ED - Physiology OBOR OECD: Physiology (including cytology) http://www.neuronalsignaling.org/content/1/1/NS20160003

  15. Selective serotonergic excitation of callosal projection neurons

    Directory of Open Access Journals (Sweden)

    Daniel eAvesar

    2012-03-01

    Full Text Available Serotonin (5-HT acting as a neurotransmitter in the cerebral cortex is critical for cognitive function, yet how 5-HT regulates information processing in cortical circuits is not well understood. We tested the serotonergic responsiveness of layer 5 pyramidal neurons (L5PNs of the mouse medial prefrontal cortex (mPFC, and found 3 distinct response types: long-lasting 5-HT1A (1A receptor-dependent inhibitory responses (84% of L5PNs, 5-HT2A (2A receptor-dependent excitatory responses (9%, and biphasic responses in which 2A-dependent excitation followed brief inhibition (5%. Relative to 5-HT-inhibited neurons, those excited by 5-HT had physiological properties characteristic of callosal/commissural (COM neurons that project to the contralateral cortex. We tested whether serotonergic responses in cortical pyramidal neurons are correlated with their axonal projection pattern using retrograde fluorescent labeling of COM and corticopontine-projecting (CPn neurons. 5-HT generated excitatory or biphasic responses in all 5-HT-responsive layer 5 COM neurons. Conversely, CPn neurons were universally inhibited by 5-HT. Serotonergic excitation of COM neurons was blocked by the 2A antagonist MDL 11939, while serotonergic inhibition of CPn neurons was blocked by the 1A antagonist WAY 100635, confirming a role for these two receptor subtypes in regulating pyramidal neuron activity. Selective serotonergic excitation of COM neurons was not layer-specific, as COM neurons in layer 2/3 were also selectively excited by 5-HT relative to their non-labeled pyramidal neuron neighbors. Because neocortical 2A receptors are implicated in the etiology and pathophysiology of schizophrenia, we propose that COM neurons may represent a novel cellular target for intervention in psychiatric disease.

  16. Engineering a Light-Attenuating Artificial Iris.

    Science.gov (United States)

    Shareef, Farah J; Sun, Shan; Kotecha, Mrignayani; Kassem, Iris; Azar, Dimitri; Cho, Michael

    2016-04-01

    Discomfort from light exposure leads to photophobia, glare, and poor vision in patients with congenital or trauma-induced iris damage. Commercial artificial iris lenses are static in nature to provide aesthetics without restoring the natural iris's dynamic response to light. A new photo-responsive artificial iris was therefore developed using a photochromic material with self-adaptive light transmission properties and encased in a transparent biocompatible polymer matrix. The implantable artificial iris was designed and engineered using Photopia, a class of photo-responsive materials (termed naphthopyrans) embedded in polyethylene. Photopia was reshaped into annular disks that were spin-coated with polydimethylsiloxane (PDMS) to form our artificial iris lens of controlled thickness. Activated by UV and blue light in approximately 5 seconds with complete reversal in less than 1 minute, the artificial iris demonstrates graded attenuation of up to 40% of visible and 60% of UV light. There optical characteristics are suitable to reversibly regulate the incident light intensity. In vitro cell culture experiments showed up to 60% cell death within 10 days of exposure to Photopia, but no significant cell death observed when cultured with the artificial iris with protective encapsulation. Nuclear magnetic resonance spectroscopy confirmed these results as there was no apparent leakage of potentially toxic photochromic material from the ophthalmic device. Our artificial iris lens mimics the functionality of the natural iris by attenuating light intensity entering the eye with its rapid reversible change in opacity and thus potentially providing an improved treatment option for patients with iris damage.

  17. Results on a Binding Neuron Model and Their Implications for Modified Hourglass Model for Neuronal Network

    Directory of Open Access Journals (Sweden)

    Viswanathan Arunachalam

    2013-01-01

    Full Text Available The classical models of single neuron like Hodgkin-Huxley point neuron or leaky integrate and fire neuron assume the influence of postsynaptic potentials to last till the neuron fires. Vidybida (2008 in a refreshing departure has proposed models for binding neurons in which the trace of an input is remembered only for a finite fixed period of time after which it is forgotten. The binding neurons conform to the behaviour of real neurons and are applicable in constructing fast recurrent networks for computer modeling. This paper develops explicitly several useful results for a binding neuron like the firing time distribution and other statistical characteristics. We also discuss the applicability of the developed results in constructing a modified hourglass network model in which there are interconnected neurons with excitatory as well as inhibitory inputs. Limited simulation results of the hourglass network are presented.

  18. Single-cell axotomy of cultured hippocampal neurons integrated in neuronal circuits.

    Science.gov (United States)

    Gomis-Rüth, Susana; Stiess, Michael; Wierenga, Corette J; Meyn, Liane; Bradke, Frank

    2014-05-01

    An understanding of the molecular mechanisms of axon regeneration after injury is key for the development of potential therapies. Single-cell axotomy of dissociated neurons enables the study of the intrinsic regenerative capacities of injured axons. This protocol describes how to perform single-cell axotomy on dissociated hippocampal neurons containing synapses. Furthermore, to axotomize hippocampal neurons integrated in neuronal circuits, we describe how to set up coculture with a few fluorescently labeled neurons. This approach allows axotomy of single cells in a complex neuronal network and the observation of morphological and molecular changes during axon regeneration. Thus, single-cell axotomy of mature neurons is a valuable tool for gaining insights into cell intrinsic axon regeneration and the plasticity of neuronal polarity of mature neurons. Dissociation of the hippocampus and plating of hippocampal neurons takes ∼2 h. Neurons are then left to grow for 2 weeks, during which time they integrate into neuronal circuits. Subsequent axotomy takes 10 min per neuron and further imaging takes 10 min per neuron.

  19. Glutamate neurons are intermixed with midbrain dopamine neurons in nonhuman primates and humans

    Science.gov (United States)

    Root, David H.; Wang, Hui-Ling; Liu, Bing; Barker, David J.; Mód, László; Szocsics, Péter; Silva, Afonso C.; Maglóczky, Zsófia; Morales, Marisela

    2016-01-01

    The rodent ventral tegmental area (VTA) and substantia nigra pars compacta (SNC) contain dopamine neurons intermixed with glutamate neurons (expressing vesicular glutamate transporter 2; VGluT2), which play roles in reward and aversion. However, identifying the neuronal compositions of the VTA and SNC in higher mammals has remained challenging. Here, we revealed VGluT2 neurons within the VTA and SNC of nonhuman primates and humans by simultaneous detection of VGluT2 mRNA and tyrosine hydroxylase (TH; for identification of dopamine neurons). We found that several VTA subdivisions share similar cellular compositions in nonhuman primates and humans; their rostral linear nuclei have a high prevalence of VGluT2 neurons lacking TH; their paranigral and parabrachial pigmented nuclei have mostly TH neurons, and their parabrachial pigmented nuclei have dual VGluT2-TH neurons. Within nonhuman primates and humans SNC, the vast majority of neurons are TH neurons but VGluT2 neurons were detected in the pars lateralis subdivision. The demonstration that midbrain dopamine neurons are intermixed with glutamate or glutamate-dopamine neurons from rodents to humans offers new opportunities for translational studies towards analyzing the roles that each of these neurons play in human behavior and in midbrain-associated illnesses such as addiction, depression, schizophrenia, and Parkinson’s disease. PMID:27477243

  20. Artificial organs 2010: a year in review.

    Science.gov (United States)

    Malchesky, Paul S

    2011-03-01

    In this Editor's Review, articles published in 2010 are organized by category and briefly summarized. As the official journal of The International Federation for Artificial Organs, The International Faculty for Artificial Organs, and the International Society for Rotary Blood Pumps, Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level."Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ Replacement, Recovery, and Regeneration from all over the world. We take this time also to express our gratitude to our authors for offering their work to this journal. We offer our very special thanks to our reviewers who give so generously of time and expertise to review, critique, and especially provide such meaningful suggestions to the author's work whether eventually accepted or rejected and especially to those whose native tongue is not English. Without these excellent and dedicated reviewers the quality expected from such a journal could not be possible. We also express our special thanks to our Publisher, Wiley-Blackwell, for their expert attention and support in the production and marketing of Artificial Organs. In this Editor's Review, that historically has been widely received by our readership, we aim to provide a brief reflection of the currently available worldwide knowledge that is intended to advance and better human life while providing insight for continued application of technologies and methods of organ Replacement, Recovery, and Regeneration. We look forward to recording further advances in the coming years. © 2011, Copyright the Author. Artificial Organs © 2011, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

  1. Artificial organs 2011: a year in review.

    Science.gov (United States)

    Malchesky, Paul S

    2012-03-01

    In this Editor's Review, articles published in 2011 are organized by category and briefly summarized. As the official journal of The International Federation for Artificial Organs, The International Faculty for Artificial Organs, and the International Society for Rotary Blood Pumps, Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level."Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ replacement, recovery, and regeneration from all over the world. We take this time also to express our gratitude to our authors for offering their work to this journal. We offer our very special thanks to our reviewers who give so generously of time and expertise to review, critique, and especially provide meaningful suggestions to the author's work whether eventually accepted or rejected. Without these excellent and dedicated reviewers, the quality expected from such a journal would not be possible. We also express our special thanks to our Publisher, Wiley-Blackwell, for their expert attention and support in the production and marketing of Artificial Organs. In this Editor's Review, that historically has been widely well-received by our readership, we aim to provide a brief reflection of the currently available worldwide knowledge that is intended to advance and better human life while providing insight for continued application of technologies and methods of organ replacement, recovery, and regeneration. We look forward to recording further advances in the coming years. © 2012, Copyright the Author. Artificial Organs © 2012, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

  2. Artificial Organs 2012: a year in review.

    Science.gov (United States)

    Malchesky, Paul S

    2013-03-01

    In this editor's review, articles published in 2012 are organized by category and briefly summarized. We aim to provide a brief reflection of the currently available worldwide knowledge that is intended to advance and better human life while providing insight for continued application of technologies and methods of organ replacement, recovery, and regeneration. As the official journal of the International Federation for Artificial Organs, the International Faculty for Artificial Organs, and the International Society for Rotary Blood Pumps, Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level." Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ replacement, recovery, and regeneration from all over the world. We take this time also to express our gratitude to our authors for offering their work to this journal. We offer our very special thanks to our reviewers who give so generously of time and expertise to review, critique, and especially provide such meaningful suggestions to the author's work whether eventually accepted or rejected, and especially to those whose native tongue is not English. Without these excellent and dedicated reviewers, the quality expected from such a journal could not be possible. We also express our special thanks to our publisher, Wiley Periodicals, for their expert attention and support in the production and marketing of Artificial Organs. We look forward to recording further advances in the coming years. © 2013, Copyright the Author. Artificial Organs © 2013, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

  3. Development of A-type allatostatin immunoreactivity in antennal lobe neurons of the sphinx moth Manduca sexta.

    Science.gov (United States)

    Utz, Sandra; Schachtner, Joachim

    2005-04-01

    The antennal lobe (AL) of the sphinx moth Manduca sexta is a well-established model system for studying mechanisms of neuronal development. To understand whether neuropeptides are suited to playing a role during AL development, we have studied the cellular localization and temporal expression pattern of neuropeptides of the A-type allatostatin family. Based on morphology and developmental appearance, we distinguished four types of AST-A-immunoreactive cell types. The majority of the cells were local interneurons of the AL (type Ia) which acquired AST-A immunostaining in a complex pattern consisting of three rising (RI-RIII) and two declining phases (DI, DII). Type Ib neurons consisted of two local neurons with large cell bodies not appearing before 7/8 days after pupal ecdysis (P7/P8). Types II and III neurons accounted for single centrifugal neurons, with type II neurons present in the larva and disappearing in the early pupa. The type III neuron did not appear before P7/P8. RI and RII coincided with the rises of the ecdysteroid hemolymph titer. Artificially shifting the pupal 20-hydroxyecdysone (20E) peak to an earlier developmental time point resulted in the precocious appearance of AST-A immunostaining in types Ia, Ib, and III neurons. This result supports the hypothesis that the pupal rise in 20E plays a role in AST-A expression during AL development. Because of their early appearance in newly forming glomeruli, AST-A-immunoreactive fibers could be involved in glomerulus formation. Diffuse AST-A labeling during early AL development is discussed as a possible signal providing information for ingrowing olfactory receptor neurons.

  4. The role of glycogen, glucose and lactate in neuronal activity during hypoxia in the hooded seal (Cystophora cristata) brain.

    Science.gov (United States)

    Czech-Damal, N U; Geiseler, S J; Hoff, M L M; Schliep, R; Ramirez, J-M; Folkow, L P; Burmester, T

    2014-09-05

    The brains of diving mammals are repeatedly exposed to hypoxic conditions during diving. Brain neurons of the hooded seal (Cystophora cristata) have been shown to be more hypoxia tolerant than those of mice, but the underlying mechanisms are not clear. Here we investigated the roles of different metabolic substrates for maintenance of neuronal activity and integrity, by comparing the in vitro spontaneous neuronal activity of brain slices from layer V of the visual cortex of hooded seals with those in mice (Mus musculus). Studies were conducted by manipulating the composition of the artificial cerebrospinal fluid (aCSF), containing either 10 mM glucose, or 20 mM lactate, or no external carbohydrate supply (aglycemia). Normoxic, hypoxic and ischemic conditions were applied. The lack of glucose or the application of lactate in the aCSF containing no glucose had little effect on the neuronal activity of seal neurons in either normoxia or hypoxia, while neurons from mice survived in hypoxia only few minutes regardless of the composition of the aCSF. We propose that seal neurons have higher intrinsic energy stores. Indeed, we found about three times higher glycogen stores in the seal brain (∼4.1 ng per μg total protein in the seal cerebrum) than in the mouse brain. Notably, in aCSF containing no glucose, seal neurons can tolerate 20 mM lactate while in mouse neuronal activity vanished after few minutes even in normoxia. This can be considered as an adaptation to long dives, during which lactate accumulates in the blood. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

  5. Bringing Artificial Gravity into the Classroom

    Science.gov (United States)

    Thompson, Grant; Aning, Isaac

    2018-01-01

    We recently conducted an experimental test of artificial gravity by placing various species of plants in centrifuges and analyzed the plants’ germination and growth. This research project incorporated several topics covered in undergraduate astronomy, biology, and physics courses. Given the interest of introductory astronomy students in artificial gravity and their pre-existing images of applications such as rotating spacecraft from pop culture, the results of the experiment may provide a gateway to discuss artificial gravity beyond teaching the traditional examples of Newton’s laws. We will discuss the experiment in detail and provide suggestions for how the experiment could be incorporated into your classroom.

  6. Artificial intelligence in power system optimization

    CERN Document Server

    Ongsakul, Weerakorn

    2013-01-01

    With the considerable increase of AI applications, AI is being increasingly used to solve optimization problems in engineering. In the past two decades, the applications of artificial intelligence in power systems have attracted much research. This book covers the current level of applications of artificial intelligence to the optimization problems in power systems. This book serves as a textbook for graduate students in electric power system management and is also be useful for those who are interested in using artificial intelligence in power system optimization.

  7. Abstraction in artificial intelligence and complex systems

    CERN Document Server

    Saitta, Lorenza

    2013-01-01

    Abstraction is a fundamental mechanism underlying both human and artificial perception, representation of knowledge, reasoning and learning. This mechanism plays a crucial role in many disciplines, notably Computer Programming, Natural and Artificial Vision, Complex Systems, Artificial Intelligence and Machine Learning, Art, and Cognitive Sciences. This book first provides the reader with an overview of the notions of abstraction proposed in various disciplines by comparing both commonalities and differences.  After discussing the characterizing properties of abstraction, a formal model, the K

  8. Computed Flow Through An Artificial Heart Valve

    Science.gov (United States)

    Rogers, Stewart E.; Kwak, Dochan; Kiris, Cetin; Chang, I-Dee

    1994-01-01

    Report discusses computations of blood flow through prosthetic tilting disk valve. Computational procedure developed in simulation used to design better artificial hearts and valves by reducing or eliminating following adverse flow characteristics: large pressure losses, which prevent hearts from working efficiently; separated and secondary flows, which causes clotting; and high turbulent shear stresses, which damages red blood cells. Report reiterates and expands upon part of NASA technical memorandum "Computed Flow Through an Artificial Heart and Valve" (ARC-12983). Also based partly on research described in "Numerical Simulation of Flow Through an Artificial Heart" (ARC-12478).

  9. Artificial Intelligence and Information Management

    Science.gov (United States)

    Fukumura, Teruo

    After reviewing the recent popularization of the information transmission and processing technologies, which are supported by the progress of electronics, the authors describe that by the introduction of the opto-electronics into the information technology, the possibility of applying the artificial intelligence (AI) technique to the mechanization of the information management has emerged. It is pointed out that althuogh AI deals with problems in the mental world, its basic methodology relies upon the verification by evidence, so the experiment on computers become indispensable for the study of AI. The authors also describe that as computers operate by the program, the basic intelligence which is concerned in AI is that expressed by languages. This results in the fact that the main tool of AI is the logical proof and it involves an intrinsic limitation. To answer a question “Why do you employ AI in your problem solving”, one must have ill-structured problems and intend to conduct deep studies on the thinking and the inference, and the memory and the knowledge-representation. Finally the authors discuss the application of AI technique to the information management. The possibility of the expert-system, processing of the query, and the necessity of document knowledge-base are stated.

  10. Learning in Artificial Neural Systems

    Science.gov (United States)

    Matheus, Christopher J.; Hohensee, William E.

    1987-01-01

    This paper presents an overview and analysis of learning in Artificial Neural Systems (ANS's). It begins with a general introduction to neural networks and connectionist approaches to information processing. The basis for learning in ANS's is then described, and compared with classical Machine learning. While similar in some ways, ANS learning deviates from tradition in its dependence on the modification of individual weights to bring about changes in a knowledge representation distributed across connections in a network. This unique form of learning is analyzed from two aspects: the selection of an appropriate network architecture for representing the problem, and the choice of a suitable learning rule capable of reproducing the desired function within the given network. The various network architectures are classified, and then identified with explicit restrictions on the types of functions they are capable of representing. The learning rules, i.e., algorithms that specify how the network weights are modified, are similarly taxonomized, and where possible, the limitations inherent to specific classes of rules are outlined.

  11. Escalated convergent artificial bee colony

    Science.gov (United States)

    Jadon, Shimpi Singh; Bansal, Jagdish Chand; Tiwari, Ritu

    2016-03-01

    Artificial bee colony (ABC) optimisation algorithm is a recent, fast and easy-to-implement population-based meta heuristic for optimisation. ABC has been proved a rival algorithm with some popular swarm intelligence-based algorithms such as particle swarm optimisation, firefly algorithm and ant colony optimisation. The solution search equation of ABC is influenced by a random quantity which helps its search process in exploration at the cost of exploitation. In order to find a fast convergent behaviour of ABC while exploitation capability is maintained, in this paper basic ABC is modified in two ways. First, to improve exploitation capability, two local search strategies, namely classical unidimensional local search and levy flight random walk-based local search are incorporated with ABC. Furthermore, a new solution search strategy, namely stochastic diffusion scout search is proposed and incorporated into the scout bee phase to provide more chance to abandon solution to improve itself. Efficiency of the proposed algorithm is tested on 20 benchmark test functions of different complexities and characteristics. Results are very promising and they prove it to be a competitive algorithm in the field of swarm intelligence-based algorithms.

  12. Improving Tools in Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2010-01-01

    Full Text Available The historical origin of the Artificial Intelligence (AI is usually established in the Dartmouth Conference, of 1956. But we can find many more arcane origins [1]. Also, we can consider, in more recent times, very great thinkers, as Janos Neumann (then, John von Neumann, arrived in USA, Norbert Wiener, Alan Mathison Turing, or Lofti Zadeh, for instance [12, 14]. Frequently AI requires Logic. But its Classical version shows too many insufficiencies. So, it was necessary to introduce more sophisticated tools, as Fuzzy Logic, Modal Logic, Non-Monotonic Logic and so on [1, 2]. Among the things that AI needs to represent are categories, objects, properties, relations between objects, situations, states, time, events, causes and effects, knowledge about knowledge, and so on. The problems in AI can be classified in two general types [3, 5], search problems and representation problems. On this last "peak", there exist different ways to reach their summit. So, we have [4] Logics, Rules, Frames, Associative Nets, Scripts, and so on, many times connected among them. We attempt, in this paper, a panoramic vision of the scope of application of such representation methods in AI. The two more disputable questions of both modern philosophy of mind and AI will be perhaps the Turing Test and the Chinese Room Argument. To elucidate these very difficult questions, see our final note.

  13. Artificial Intelligence in planetary spectroscopy

    Science.gov (United States)

    Waldmann, Ingo

    2017-10-01

    The field of exoplanetary spectroscopy is as fast moving as it is new. Analysing currently available observations of exoplanetary atmospheres often invoke large and correlated parameter spaces that can be difficult to map or constrain. This is true for both: the data analysis of observations as well as the theoretical modelling of their atmospheres.Issues of low signal-to-noise data and large, non-linear parameter spaces are nothing new and commonly found in many fields of engineering and the physical sciences. Recent years have seen vast improvements in statistical data analysis and machine learning that have revolutionised fields as diverse as telecommunication, pattern recognition, medical physics and cosmology.In many aspects, data mining and non-linearity challenges encountered in other data intensive fields are directly transferable to the field of extrasolar planets. In this conference, I will discuss how deep neural networks can be designed to facilitate solving said issues both in exoplanet atmospheres as well as for atmospheres in our own solar system. I will present a deep belief network, RobERt (Robotic Exoplanet Recognition), able to learn to recognise exoplanetary spectra and provide artificial intelligences to state-of-the-art atmospheric retrieval algorithms. Furthermore, I will present a new deep convolutional network that is able to map planetary surface compositions using hyper-spectral imaging and demonstrate its uses on Cassini-VIMS data of Saturn.

  14. Artificial insemination in pigs today.

    Science.gov (United States)

    Knox, R V

    2016-01-01

    Use of artificial insemination (AI) for breeding pigs has been instrumental for facilitating global improvements in fertility, genetics, labor, and herd health. The establishment of AI centers for management of boars and production of semen has allowed for selection of boars for fertility and sperm production using in vitro and in vivo measures. Today, boars can be managed for production of 20 to 40 traditional AI doses containing 2.5 to 3.0 billion motile sperm in 75 to 100 mL of extender or 40 to 60 doses with 1.5 to 2.0 billion sperm in similar or reduced volumes for use in cervical or intrauterine AI. Regardless of the sperm dose, in liquid form, extenders are designed to sustain sperm fertility for 3 to 7 days. On farm, AI is the predominant form for commercial sow breeding and relies on manual detection of estrus with sows receiving two cervical or two intrauterine inseminations of the traditional or low sperm doses on each day detected in standing estrus. New approaches for increasing rates of genetic improvement through use of AI are aimed at methods to continue to lower the number of sperm in an AI dose and reducing the number of inseminations through use of a single, fixed-time AI after ovulation induction. Both approaches allow greater selection pressure for economically important swine traits in the sires and help extend the genetic advantages through AI on to more production farms. Copyright © 2016 Elsevier Inc. All rights reserved.

  15. Neuronal Differentiation Modulated by Polymeric Membrane Properties.

    Science.gov (United States)

    Morelli, Sabrina; Piscioneri, Antonella; Drioli, Enrico; De Bartolo, Loredana

    2017-01-01

    In this study, different collagen-blend membranes were successfully constructed by blending collagen with chitosan (CHT) or poly(lactic-co-glycolic acid) (PLGA) to enhance their properties and thus create new biofunctional materials with great potential use for neuronal tissue engineering and regeneration. Collagen blending strongly affected membrane properties in the following ways: (i) it improved the surface hydrophilicity of both pure CHT and PLGA membranes, (ii) it reduced the stiffness of CHT membranes, but (iii) it did not modify the good mechanical properties of PLGA membranes. Then, we investigated the effect of the different collagen concentrations on the neuronal behavior of the membranes developed. Morphological observations, immunocytochemistry, and morphometric measures demonstrated that the membranes developed, especially CHT/Col30, PLGA, and PLGA/Col1, provided suitable microenvironments for neuronal growth owing to their enhanced properties. The most consistent neuronal differentiation was obtained in neurons cultured on PLGA-based membranes, where a well-developed neuronal network was achieved due to their improved mechanical properties. Our findings suggest that tensile strength and elongation at break are key material parameters that have potential influence on both axonal elongation and neuronal structure and organization, which are of fundamental importance for the maintenance of efficient neuronal growth. Hence, our study has provided new insights regarding the effects of membrane mechanical properties on neuronal behavior, and thus it may help to design and improve novel instructive biomaterials for neuronal tissue engineering. © 2017 S. Karger AG, Basel.

  16. Synaptic Circuit Organization of Motor Corticothalamic Neurons

    Science.gov (United States)

    Yamawaki, Naoki

    2015-01-01

    Corticothalamic (CT) neurons in layer 6 constitute a large but enigmatic class of cortical projection neurons. How they are integrated into intracortical and thalamo-cortico-thalamic circuits is incompletely understood, especially outside of sensory cortex. Here, we investigated CT circuits in mouse forelimb motor cortex (M1) using multiple circuit-analysis methods. Stimulating and recording from CT, intratelencephalic (IT), and pyramidal tract (PT) projection neurons, we found strong CT↔ CT and CT↔ IT connections; however, CT→IT connections were limited to IT neurons in layer 6, not 5B. There was strikingly little CT↔ PT excitatory connectivity. Disynaptic inhibition systematically accompanied excitation in these pathways, scaling with the amplitude of excitation according to both presynaptic (class-specific) and postsynaptic (cell-by-cell) factors. In particular, CT neurons evoked proportionally more inhibition relative to excitation (I/E ratio) than IT neurons. Furthermore, the amplitude of inhibition was tuned to match the amount of excitation at the level of individual neurons; in the extreme, neurons receiving no excitation received no inhibition either. Extending these studies to dissect the connectivity between cortex and thalamus, we found that M1-CT neurons and thalamocortical neurons in the ventrolateral (VL) nucleus were remarkably unconnected in either direction. Instead, VL axons in the cortex excited both IT and PT neurons, and CT axons in the thalamus excited other thalamic neurons, including those in the posterior nucleus, which additionally received PT excitation. These findings, which contrast in several ways with previous observations in sensory areas, illuminate the basic circuit organization of CT neurons within M1 and between M1 and thalamus. PMID:25653383

  17. Power-law inter-spike interval distributions infer a conditional maximization of entropy in cortical neurons.

    Directory of Open Access Journals (Sweden)

    Yasuhiro Tsubo

    Full Text Available The brain is considered to use a relatively small amount of energy for its efficient information processing. Under a severe restriction on the energy consumption, the maximization of mutual information (MMI, which is adequate for designing artificial processing machines, may not suit for the brain. The MMI attempts to send information as accurate as possible and this usually requires a sufficient energy supply for establishing clearly discretized communication bands. Here, we derive an alternative hypothesis for neural code from the neuronal activities recorded juxtacellularly in the sensorimotor cortex of behaving rats. Our hypothesis states that in vivo cortical neurons maximize the entropy of neuronal firing under two constraints, one limiting the energy consumption (as assumed previously and one restricting the uncertainty in output spike sequences at given firing rate. Thus, the conditional maximization of firing-rate entropy (CMFE solves a tradeoff between the energy cost and noise in neuronal response. In short, the CMFE sends a rich variety of information through broader communication bands (i.e., widely distributed firing rates at the cost of accuracy. We demonstrate that the CMFE is reflected in the long-tailed, typically power law, distributions of inter-spike intervals obtained for the majority of recorded neurons. In other words, the power-law tails are more consistent with the CMFE rather than the MMI. Thus, we propose the mathematical principle by which cortical neurons may represent information about synaptic input into their output spike trains.

  18. Attenuation of hypoxic current by intracellular applications of ATP regenerating agents in hippocampal CA1 neurons of rat brain slices.

    Science.gov (United States)

    Chung, I; Zhang, Y; Eubanks, J H; Zhang, L

    1998-10-01

    Hypoxia-induced outward currents (hyperpolarization) were examined in hippocampal CA1 neurons of rat brain slices, using the whole-cell recording technique. Hypoxic episodes were induced by perfusing slices with an artificial cerebrospinal fluid aerated with 5% CO2/95% N2 rather than 5% CO2/95% O2, for about 3 min. The hypoxic current was consistently and reproducibly induced in CA1 neurons dialysed with an ATP-free patch pipette solution. This current manifested as an outward shift in the holding current in association with increased conductance, and it reversed at -78 +/- 2.5 mV, with a linear I-V relation in the range of -100 to -40 mV. To provide extra energy resources to individual neurons recorded, agents were added to the patch pipette solution, including MgATP alone, MgATP + phosphocreatine + creatine kinase, or MgATP + creatine. In CA1 neurons dialysed with patch solutions including these agents, hypoxia produced small outward currents in comparison with those observed in CA1 neurons dialysed with the ATP-free solution. Among the above agents examined, whole-cell dialysis with MgATP + creatine was the most effective at decreasing the hypoxic outward currents. We suggest that the hypoxic hyperpolarization is closely related to energy metabolism in individual CA1 neurons, and that the energy supply provided by phosphocreatine metabolism may play a critical role during transient metabolic stress.

  19. Biologically inspired toys using artificial muscles

    Science.gov (United States)

    Bar-Cohen, Y.

    2001-01-01

    Recent developments in electroactive polymers, so-called artificial muscles, could one day be used to make bionics possible. Meanwhile, as this technology evolves novel mechanisms are expected to emerge that are biologically inspired.

  20. Artificial Muscles: Mechanisms, Applications, and Challenges.

    Science.gov (United States)

    Mirvakili, Seyed M; Hunter, Ian W

    2018-02-01

    The area of artificial muscle is a highly interdisciplinary field of research that has evolved rapidly in the last 30 years. Recent advances in nanomaterial fabrication and characterization, specifically carbon nanotubes and nanowires, have had major contributions in the development of artificial muscles. However, what can artificial muscles really do for humans? This question is considered here by first examining nature's solutions to this design problem and then discussing the structure, actuation mechanism, applications, and limitations of recently developed artificial muscles, including highly oriented semicrystalline polymer fibers; nanocomposite actuators; twisted nanofiber yarns; thermally activated shape-memory alloys; ionic-polymer/metal composites; dielectric-elastomer actuators; conducting polymers; stimuli-responsive gels; piezoelectric, electrostrictive, magnetostrictive, and photostrictive actuators; photoexcited actuators; electrostatic actuators; and pneumatic actuators. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Natural and artificial atoms for quantum computation

    Energy Technology Data Exchange (ETDEWEB)

    Buluta, Iulia; Ashhab, Sahel; Nori, Franco, E-mail: fnori@riken.jp [Advanced Science Institute, RIKEN, Wako-shi, Saitama, 351-0198 (Japan)

    2011-10-15

    Remarkable progress towards realizing quantum computation has been achieved using natural and artificial atoms as qubits. This paper presents a brief overview of the current status of different types of qubits. On the one hand, natural atoms (such as neutral atoms and ions) have long coherence times, and could be stored in large arrays, providing ideal 'quantum memories'. On the other hand, artificial atoms (such as superconducting circuits or semiconductor quantum dots) have the advantage of custom-designed features and could be used as 'quantum processing units'. Natural and artificial atoms can be coupled with each other and can also be interfaced with photons for long-distance communications. Hybrid devices made of natural/artificial atoms and photons may provide the next-generation design for quantum computers.

  2. Design of artificial human joints & organs

    CERN Document Server

    Pal, Subrata

    2013-01-01

    This book covers the design science and methodology of artificial joints and organs.  It presents the mechanical characterization of the hard and soft tissues as well as the viscoelastic properties of the tissue.

  3. Artificial Intelligence and Public Healthcare Service Innovation

    DEFF Research Database (Denmark)

    Sun, Tara Qian; Medaglia, Rony

    Public healthcare ecosystems are complex networks of diverse actors that are subject to pressures to innovate, also a result of technological advancements. Artificial Intelligence (AI), in particular, has the potential to transform the way hospitals, doctors, patients, government agencies...

  4. Hindbrain Catecholamine Neurons Activate Orexin Neurons During Systemic Glucoprivation in Male Rats.

    Science.gov (United States)

    Li, Ai-Jun; Wang, Qing; Elsarelli, Megan M; Brown, R Lane; Ritter, Sue

    2015-08-01

    Hindbrain catecholamine neurons are required for elicitation of feeding responses to glucose deficit, but the forebrain circuitry required for these responses is incompletely understood. Here we examined interactions of catecholamine and orexin neurons in eliciting glucoprivic feeding. Orexin neurons, located in the perifornical lateral hypothalamus (PeFLH), are heavily innervated by hindbrain catecholamine neurons, stimulate food intake, and increase arousal and behavioral activation. Orexin neurons may therefore contribute importantly to appetitive responses, such as food seeking, during glucoprivation. Retrograde tracing results showed that nearly all innervation of the PeFLH from the hindbrain originated from catecholamine neurons and some raphe nuclei. Results also suggested that many catecholamine neurons project collaterally to the PeFLH and paraventricular hypothalamic nucleus. Systemic administration of the antiglycolytic agent, 2-deoxy-D-glucose, increased food intake and c-Fos expression in orexin neurons. Both responses were eliminated by a lesion of catecholamine neurons innervating orexin neurons using the retrogradely transported immunotoxin, anti-dopamine-β-hydroxylase saporin, which is specifically internalized by dopamine-β-hydroxylase-expressing catecholamine neurons. Using designer receptors exclusively activated by designer drugs in transgenic rats expressing Cre recombinase under the control of tyrosine hydroxylase promoter, catecholamine neurons in cell groups A1 and C1 of the ventrolateral medulla were activated selectively by peripheral injection of clozapine-N-oxide. Clozapine-N-oxide injection increased food intake and c-Fos expression in PeFLH orexin neurons as well as in paraventricular hypothalamic nucleus neurons. In summary, catecholamine neurons are required for the activation of orexin neurons during glucoprivation. Activation of orexin neurons may contribute to appetitive responses required for glucoprivic feeding.

  5. Artificial Life - Why Should Musicians Bother?

    DEFF Research Database (Denmark)

    Berry, Rodney; Dahlstedt, Palle

    2003-01-01

    for artistic expression. Artists serve to prepare society for the invisible changes going on within it by producing artworks in response to the mechanisms of change. This paper discusses the authors' approaches to using concepts from artificial life in their musical works, which are basically of two kinds...... - artificial worlds producing music as an output, and interactive compositional tools using evolutionary algorithms to generate music and sound. It also provides a brief cultural context for these works....

  6. Artificial reef evaluation capabilities of Florida counties

    OpenAIRE

    Halusky, Joseph G.; Antonini, Gustavo A.; Seaman, William

    1993-01-01

    Florida's coastal county artificial reef sampling and data management programs are surveyed in this report. The survey describes the county level capability for artificial reef documentation and performance assessment based on their needs, interests, organizational structure and "in-situ" data collection and data management techniques. The. primary purpose of this study is to describe what staffing, training, techniques, organizational procedures and equipment are used by the c...

  7. Artificial hammerhead ribozymes: engineering and applications

    International Nuclear Information System (INIS)

    Vorobjeva, M A; Davydova, A S; Venyaminova, Aliya G

    2011-01-01

    The properties of hammerhead ribozymes are described. Various hammerhead ribozyme constructs for target RNA cleavage were considered. Approaches to enhancement of the stability of artificial ribozymes in biological media and to regulation of the catalytic activity of hammerhead ribozymes using effector molecules are described. The effect of ribozymes on extended structured natural RNAs is discussed. Applications of artificial hammerhead ribozymes as inhibitors of gene expression at matrix RNA level were considered.

  8. Artificial intelligence approaches to astronomical observation scheduling

    Science.gov (United States)

    Johnston, Mark D.; Miller, Glenn

    1988-01-01

    Automated scheduling will play an increasing role in future ground- and space-based observatory operations. Due to the complexity of the problem, artificial intelligence technology currently offers the greatest potential for the development of scheduling tools with sufficient power and flexibility to handle realistic scheduling situations. Summarized here are the main features of the observatory scheduling problem, how artificial intelligence (AI) techniques can be applied, and recent progress in AI scheduling for Hubble Space Telescope.

  9. Exploring Artificial Intelligence Utilizing BioArt

    OpenAIRE

    Simou , Panagiota; Tiligadis , Konstantinos; Alexiou , Athanasios

    2013-01-01

    Part 15: First Workshop on Ethics and Philosophy in Artificial Intelligence (EPAI 2013); International audience; While artificial intelligence combined with Bioinformatics and Nanotechnology offers a variety of improvements and a technological and healthcare revolution, Bioartists attempt to replace the traditional artistic medium with biological materials, bio-imaging techniques, bioreactors and several times to treat their own body as an alive canvas. BioArt seems to play the role of a new ...

  10. Artificial Organs 2015: A Year in Review.

    Science.gov (United States)

    Malchesky, Paul S

    2016-03-01

    In this Editor's Review, articles published in 2015 are organized by category and briefly summarized. We aim to provide a brief reflection of the currently available worldwide knowledge that is intended to advance and better human life while providing insight for continued application of technologies and methods of organ Replacement, Recovery, and Regeneration. As the official journal of The International Federation for Artificial Organs, The International Faculty for Artificial Organs, the International Society for Rotary Blood Pumps, the International Society for Pediatric Mechanical Cardiopulmonary Support, and the Vienna International Workshop on Functional Electrical Stimulation, Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level." Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ Replacement, Recovery, and Regeneration from all over the world. We take this time also to express our gratitude to our authors for providing their work to this journal. We offer our very special thanks to our reviewers who give so generously of their time and expertise to review, critique, and especially provide meaningful suggestions to the author's work whether eventually accepted or rejected. Without these excellent and dedicated reviewers, the quality expected from such a journal could not be possible. We also express our special thanks to our Publisher, John Wiley & Sons for their expert attention and support in the production and marketing of Artificial Organs. We look forward to reporting further advances in the coming years. Copyright © 2016 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

  11. Artificial Organs 2013: a year in review.

    Science.gov (United States)

    Malchesky, Paul S

    2014-03-01

    In this Editor's Review, articles published in 2013 are organized by category and briefly summarized. We aim to provide a brief reflection of the currently available worldwide knowledge that is intended to advance and better human life while providing insight for continued application of technologies and methods of organ Replacement, Recovery, and Regeneration. As the official journal of The International Federation for Artificial Organs, The International Faculty for Artificial Organs, the International Society for Rotary Blood Pumps, the International Society for Pediatric Mechanical Cardiopulmonary Support, and the Vienna International Workshop on Functional Electrical Stimulation, Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level". Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ Replacement, Recovery, and Regeneration from all over the world. We take this time also to express our gratitude to our authors for offering their work to this journal. We offer our very special thanks to our reviewers who give so generously of time and expertise to review, critique, and especially provide so meaningful suggestions to the author's work whether eventually accepted or rejected and especially to those whose native tongue is not English. Without these excellent and dedicated reviewers the quality expected from such a journal could not be possible. We also express our special thanks to our Publisher, Wiley Periodicals, for their expert attention and support in the production and marketing of Artificial Organs. We look forward to recording further advances in the coming years. © 2014 Wiley Periodicals, Inc. and International Center for Artificial Organs and Transplantation.

  12. Artificial Organs 2017: A Year in Review.

    Science.gov (United States)

    Malchesky, Paul S

    2018-03-01

    In this Editor's Review, articles published in 2017 are organized by category and summarized. We provide a brief reflection of the research and progress in artificial organs intended to advance and better human life while providing insight for continued application of these technologies and methods. Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level." Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ Replacement, Recovery, and Regeneration from all over the world. Peer-reviewed Special Issues this year included contributions from the 12th International Conference on Pediatric Mechanical Circulatory Support Systems and Pediatric Cardiopulmonary Perfusion edited by Dr. Akif Undar, Artificial Oxygen Carriers edited by Drs. Akira Kawaguchi and Jan Simoni, the 24th Congress of the International Society for Mechanical Circulatory Support edited by Dr. Toru Masuzawa, Challenges in the Field of Biomedical Devices: A Multidisciplinary Perspective edited by Dr. Vincenzo Piemonte and colleagues and Functional Electrical Stimulation edited by Dr. Winfried Mayr and colleagues. We take this time also to express our gratitude to our authors for offering their work to this journal. We offer our very special thanks to our reviewers who give so generously of time and expertise to review, critique, and especially provide meaningful suggestions to the author's work whether eventually accepted or rejected. Without these excellent and dedicated reviewers the quality expected from such a journal could not be possible. We also express our special thanks to our Publisher, John Wiley & Sons for their expert attention and support in the production and marketing of Artificial Organs. We look forward to reporting further advances in the coming years. © 2018 International Center for

  13. Artificial intelligence in medicine: the challenges ahead.

    OpenAIRE

    Coiera, E W

    1996-01-01

    The modern study of artificial intelligence in medicine (AIM) is 25 years old. Throughout this period, the field has attracted many of the best computer scientists, and their work represents a remarkable achievement. However, AIM has not been successful-if success is judged as making an impact on the practice of medicine. Much recent work in AIM has been focused inward, addressing problems that are at the crossroads of the parent disciplines of medicine and artificial intelligence. Now, AIM m...

  14. Brain Intelligence: Go Beyond Artificial Intelligence

    OpenAIRE

    Lu, Huimin; Li, Yujie; Chen, Min; Kim, Hyoungseop; Serikawa, Seiichi

    2017-01-01

    Artificial intelligence (AI) is an important technology that supports daily social life and economic activities. It contributes greatly to the sustainable growth of Japan's economy and solves various social problems. In recent years, AI has attracted attention as a key for growth in developed countries such as Europe and the United States and developing countries such as China and India. The attention has been focused mainly on developing new artificial intelligence information communication ...

  15. ARTIFICIAL INTELLIGENCE- BENEFITS, CHALLENGES AND ETHICAL ISSUES

    OpenAIRE

    Elena Juganaru Andreou

    2017-01-01

    Nowadays, all big companies and most of small businesses are focused on increasing profitability and improving competitiveness. With this goal in mind, many of them turned to replace many tasks performed by humans with Artificial Intelligence. Artificial Intelligence (AI) is receiving an increasing attention lately and the debate is fiercely growing with a question not being answered yet: will it change the world for the better or for worse?

  16. The 2002 Starting Artificial Intelligence Researchers Symposium

    OpenAIRE

    Vidal, Thierry

    2003-01-01

    During the 2002 European Conference on Artificial Intelligence (ECAI-02) was introduced the Starting Artificial Intelligence Researchers Symposium STAIRS), the first-ever international symposium specifically aimed at Ph.D. students in AI. The outcome was a thorough, high-quality, and successful event, with all the features one usually finds in the best international conferences: large international committees, comprehensive coverage, published proceedings, renowned speakers and panelists, sub...

  17. Ethical Issues of Artificial Biomedical Applications

    OpenAIRE

    Alexiou , Athanasios; Psixa , Maria; Vlamos , Panagiotis

    2011-01-01

    Part 12: Medical Applications of ANN and Ethics of AI; International audience; While the plethora of artificial biomedical applications is enriched and combined with the possibilities of artificial intelligence, bioinformatics and nanotechnology, the variability in the ideological use of such concepts is associated with bioethical issues and several legal aspects. The convergence of bioethics and computer ethics, attempts to illustrate and approach problems, occurring by the fusion of human a...

  18. Artificial Intelligence and Spacecraft Power Systems

    Science.gov (United States)

    Dugel-Whitehead, Norma R.

    1997-01-01

    This talk will present the work which has been done at NASA Marshall Space Flight Center involving the use of Artificial Intelligence to control the power system in a spacecraft. The presentation will include a brief history of power system automation, and some basic definitions of the types of artificial intelligence which have been investigated at MSFC for power system automation. A video tape of one of our autonomous power systems using co-operating expert systems, and advanced hardware will be presented.

  19. How to Improve Artificial Intelligence through Web

    OpenAIRE

    Adrian Lupasc

    2005-01-01

    Intelligent agents, intelligent software applications and artificial intelligent applications from artificial intelligence service providers may make their way onto the Web in greater number as adaptive software, dynamic programming languages and Learning Algorithms are introduced into Web Services. The evolution of Web architecture may allow intelligent applications to run directly on the Web by introducing XML, RDF and logic layer. The Intelligent Wireless Web’s significant potential for ra...

  20. A chimeric path to neuronal synchronization

    Science.gov (United States)

    Essaki Arumugam, Easwara Moorthy; Spano, Mark L.

    2015-01-01

    Synchronization of neuronal activity is associated with neurological disorders such as epilepsy. This process of neuronal synchronization is not fully understood. To further our understanding, we have experimentally studied the progression of this synchronization from normal neuronal firing to full synchronization. We implemented nine FitzHugh-Nagumo neurons (a simplified Hodgkin-Huxley model) via discrete electronics. For different coupling parameters (synaptic strengths), the neurons in the ring were either unsynchronized or completely synchronized when locally coupled in a ring. When a single long-range connection (nonlocal coupling) was introduced, an intermediate state known as a chimera appeared. The results indicate that (1) epilepsy is likely not only a dynamical disease but also a topological disease, strongly tied to the connectivity of the underlying network of neurons, and (2) the synchronization process in epilepsy may not be an "all or none" phenomenon, but can pass through an intermediate stage (chimera).

  1. A chimeric path to neuronal synchronization

    Energy Technology Data Exchange (ETDEWEB)

    Essaki Arumugam, Easwara Moorthy; Spano, Mark L. [School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85287-9709 (United States)

    2015-01-15

    Synchronization of neuronal activity is associated with neurological disorders such as epilepsy. This process of neuronal synchronization is not fully understood. To further our understanding, we have experimentally studied the progression of this synchronization from normal neuronal firing to full synchronization. We implemented nine FitzHugh-Nagumo neurons (a simplified Hodgkin-Huxley model) via discrete electronics. For different coupling parameters (synaptic strengths), the neurons in the ring were either unsynchronized or completely synchronized when locally coupled in a ring. When a single long-range connection (nonlocal coupling) was introduced, an intermediate state known as a chimera appeared. The results indicate that (1) epilepsy is likely not only a dynamical disease but also a topological disease, strongly tied to the connectivity of the underlying network of neurons, and (2) the synchronization process in epilepsy may not be an “all or none” phenomenon, but can pass through an intermediate stage (chimera)

  2. Mini Review: Biomaterials for Enhancing Neuronal Repair

    Science.gov (United States)

    Cangellaris, Olivia V.; Gillette, Martha U.

    2018-04-01

    As they differentiate from neuroblasts, nascent neurons become highly polarized and elongate. Neurons extend and elaborate fine and fragile cellular extensions that form circuits enabling long-distance communication and signal integration within the body. While other organ systems are developing, projections of differentiating neurons find paths to distant targets. Subsequent post-developmental neuronal damage is catastrophic because the cues for reinnervation are no longer active. Advances in biomaterials are enabling fabrication of micro-environments that encourage neuronal regrowth and restoration of function by recreating these developmental cues. This mini-review considers new materials that employ topographical, chemical, electrical, and/or mechanical cues for use in neuronal repair. Manipulating and integrating these elements in different combinations will generate new technologies to enhance neural repair.

  3. Npas4: Linking Neuronal Activity to Memory.

    Science.gov (United States)

    Sun, Xiaochen; Lin, Yingxi

    2016-04-01

    Immediate-early genes (IEGs) are rapidly activated after sensory and behavioral experience and are believed to be crucial for converting experience into long-term memory. Neuronal PAS domain protein 4 (Npas4), a recently discovered IEG, has several characteristics that make it likely to be a particularly important molecular link between neuronal activity and memory: it is among the most rapidly induced IEGs, is expressed only in neurons, and is selectively induced by neuronal activity. By orchestrating distinct activity-dependent gene programs in different neuronal populations, Npas4 affects synaptic connections in excitatory and inhibitory neurons, neural circuit plasticity, and memory formation. It may also be involved in circuit homeostasis through negative feedback and psychiatric disorders. We summarize these findings and discuss their implications. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. A chimeric path to neuronal synchronization

    International Nuclear Information System (INIS)

    Essaki Arumugam, Easwara Moorthy; Spano, Mark L.

    2015-01-01

    Synchronization of neuronal activity is associated with neurological disorders such as epilepsy. This process of neuronal synchronization is not fully understood. To further our understanding, we have experimentally studied the progression of this synchronization from normal neuronal firing to full synchronization. We implemented nine FitzHugh-Nagumo neurons (a simplified Hodgkin-Huxley model) via discrete electronics. For different coupling parameters (synaptic strengths), the neurons in the ring were either unsynchronized or completely synchronized when locally coupled in a ring. When a single long-range connection (nonlocal coupling) was introduced, an intermediate state known as a chimera appeared. The results indicate that (1) epilepsy is likely not only a dynamical disease but also a topological disease, strongly tied to the connectivity of the underlying network of neurons, and (2) the synchronization process in epilepsy may not be an “all or none” phenomenon, but can pass through an intermediate stage (chimera)

  5. Artificial muscles with adjustable stiffness

    International Nuclear Information System (INIS)

    Mutlu, Rahim; Alici, Gursel

    2010-01-01

    This paper reports on a stiffness enhancement methodology based on using a suitably designed contact surface with which cantilevered-type conducting polymer bending actuators are in contact during operation. The contact surface constrains the bending behaviour of the actuators. Depending on the topology of the contact surface, the resistance of the polymer actuators to deformation, i.e. stiffness, is varied. As opposed to their predecessors, these polymer actuators operate in air. Finite element analysis and modelling are used to quantify the effect of the contact surface on the effective stiffness of a trilayer cantilevered beam, which represents a one-end-free, the-other-end-fixed polypyrrole (PPy) conducting polymer actuator under a uniformly distributed load. After demonstrating the feasibility of the adjustable stiffness concept, experiments were conducted to determine the stiffness of bending-type conducting polymer actuators in contact with a range (20–40 mm in radius) of circular contact surfaces. The numerical and experimental results presented demonstrate that the stiffness of the actuators can be varied using a suitably profiled contact surface. The larger the radius of the contact surface is, the higher is the stiffness of the polymer actuators. The outcomes of this study suggest that, although the stiffness of the artificial muscles considered in this study is constant for a given geometric size, and electrical and chemical operation conditions, it can be changed in a nonlinear fashion to suit the stiffness requirement of a considered application. The stiffness enhancement methodology can be extended to other ionic-type conducting polymer actuators

  6. Neuronal Networks on Nanocellulose Scaffolds.

    Science.gov (United States)

    Jonsson, Malin; Brackmann, Christian; Puchades, Maja; Brattås, Karoline; Ewing, Andrew; Gatenholm, Paul; Enejder, Annika

    2015-11-01

    Proliferation, integration, and neurite extension of PC12 cells, a widely used culture model for cholinergic neurons, were studied in nanocellulose scaffolds biosynthesized by Gluconacetobacter xylinus to allow a three-dimensional (3D) extension of neurites better mimicking neuronal networks in tissue. The interaction with control scaffolds was compared with cationized nanocellulose (trimethyl ammonium betahydroxy propyl [TMAHP] cellulose) to investigate the impact of surface charges on the cell interaction mechanisms. Furthermore, coatings with extracellular matrix proteins (collagen, fibronectin, and laminin) were investigated to determine the importance of integrin-mediated cell attachment. Cell proliferation was evaluated by a cellular proliferation assay, while cell integration and neurite propagation were studied by simultaneous label-free Coherent anti-Stokes Raman Scattering and second harmonic generation microscopy, providing 3D images of PC12 cells and arrangement of nanocellulose fibrils, respectively. Cell attachment and proliferation were enhanced by TMAHP modification, but not by protein coating. Protein coating instead promoted active interaction between the cells and the scaffold, hence lateral cell migration and integration. Irrespective of surface modification, deepest cell integration measured was one to two cell layers, whereas neurites have a capacity to integrate deeper than the cell bodies in the scaffold due to their fine dimensions and amoeba-like migration pattern. Neurites with lengths of >50 μm were observed, successfully connecting individual cells and cell clusters. In conclusion, TMAHP-modified nanocellulose scaffolds promote initial cellular scaffold adhesion, which combined with additional cell-scaffold treatments enables further formation of 3D neuronal networks.

  7. Artificial Psychology: The Psychology of AI

    Directory of Open Access Journals (Sweden)

    James A. Crowder

    2013-12-01

    Full Text Available Having artificially intelligent machines that think, learn, reason, experience, and can function autonomously, without supervision, is one of the most intriguing goals in all of Computer Science. As the types of problems we would like machines to solve get more complex, it is becoming a necessary goal as well. One of the many problems associated with this goal is that what learning and reasoning are have so many possible meanings that the solution can easily get lost in the sea of opinions and options. The goal of this paper is to establish some foundational principles, theory, and concepts that we feel are the backbone of real, autonomous Artificial Intelligence. With this fully autonomous, learning, reasoning, artificially intelligent system (an artificial brain, comes the need to possess constructs in its hardware and software that mimic processes and subsystems that exist within the human brain, including intuitive and emotional memory concepts. Presented here is a discussion of the psychological constructs of artificial intelligence and how they might play out in an artificial mind.

  8. C. elegans model of neuronal aging

    OpenAIRE

    Peng, Chiu-Ying; Chen, Chun-Hao; Hsu, Jiun-Min; Pan, Chun-Liang

    2011-01-01

    Aging of the nervous system underlies the behavioral and cognitive decline associated with senescence. Understanding the molecular and cellular basis of neuronal aging will therefore contribute to the development of effective treatments for aging and age-associated neurodegenerative disorders. Despite this pressing need, there are surprisingly few animal models that aim at recapitulating neuronal aging in a physiological context. We recently developed a C. elegans model of neuronal aging, and...

  9. Spike timing precision of neuronal circuits.

    Science.gov (United States)

    Kilinc, Deniz; Demir, Alper

    2018-04-17

    Spike timing is believed to be a key factor in sensory information encoding and computations performed by the neurons and neuronal circuits. However, the considerable noise and variability, arising from the inherently stochastic mechanisms that exist in the neurons and the synapses, degrade spike timing precision. Computational modeling can help decipher the mechanisms utilized by the neuronal circuits in order to regulate timing precision. In this paper, we utilize semi-analytical techniques, which were adapted from previously developed methods for electronic circuits, for the stochastic characterization of neuronal circuits. These techniques, which are orders of magnitude faster than traditional Monte Carlo type simulations, can be used to directly compute the spike timing jitter variance, power spectral densities, correlation functions, and other stochastic characterizations of neuronal circuit operation. We consider three distinct neuronal circuit motifs: Feedback inhibition, synaptic integration, and synaptic coupling. First, we show that both the spike timing precision and the energy efficiency of a spiking neuron are improved with feedback inhibition. We unveil the underlying mechanism through which this is achieved. Then, we demonstrate that a neuron can improve on the timing precision of its synaptic inputs, coming from multiple sources, via synaptic integration: The phase of the output spikes of the integrator neuron has the same variance as that of the sample average of the phases of its inputs. Finally, we reveal that weak synaptic coupling among neurons, in a fully connected network, enables them to behave like a single neuron with a larger membrane area, resulting in an improvement in the timing precision through cooperation.

  10. Do enteric neurons make hypocretin? ☆

    OpenAIRE

    Baumann, Christian R.; Clark, Erika L.; Pedersen, Nigel P.; Hecht, Jonathan L.; Scammell, Thomas E.

    2007-01-01

    Hypocretins (orexins) are wake-promoting neuropeptides produced by hypothalamic neurons. These hypocretin-producing cells are lost in people with narcolepsy, possibly due to an autoimmune attack. Prior studies described hypocretin neurons in the enteric nervous system, and these cells could be an additional target of an autoimmune process. We sought to determine whether enteric hypocretin neurons are lost in narcoleptic subjects. Even though we tried several methods (including whole mounts, s...

  11. High-Degree Neurons Feed Cortical Computations.

    Directory of Open Access Journals (Sweden)

    Nicholas M Timme

    2016-05-01

    Full Text Available Recent work has shown that functional connectivity among cortical neurons is highly varied, with a small percentage of neurons having many more connections than others. Also, recent theoretical developments now make it possible to quantify how neurons modify information from the connections they receive. Therefore, it is now possible to investigate how information modification, or computation, depends on the number of connections a neuron receives (in-degree or sends out (out-degree. To do this, we recorded the simultaneous spiking activity of hundreds of neurons in cortico-hippocampal slice cultures using a high-density 512-electrode array. This preparation and recording method combination produced large numbers of neurons recorded at temporal and spatial resolutions that are not currently available in any in vivo recording system. We utilized transfer entropy (a well-established method for detecting linear and nonlinear interactions in time series and the partial information decomposition (a powerful, recently developed tool for dissecting multivariate information processing into distinct parts to quantify computation between neurons where information flows converged. We found that computations did not occur equally in all neurons throughout the networks. Surprisingly, neurons that computed large amounts of information tended to receive connections from high out-degree neurons. However, the in-degree of a neuron was not related to the amount of information it computed. To gain insight into these findings, we developed a simple feedforward network model. We found that a degree-modified Hebbian wiring rule best reproduced the pattern of computation and degree correlation results seen in the real data. Interestingly, this rule also maximized signal propagation in the presence of network-wide correlations, suggesting a mechanism by which cortex could deal with common random background input. These are the first results to show that the extent to

  12. Design of memristive interface between electronic neurons

    Science.gov (United States)

    Gerasimova, S. A.; Mikhaylov, A. N.; Belov, A. I.; Korolev, D. S.; Guseinov, D. V.; Lebedeva, A. V.; Gorshkov, O. N.; Kazantsev, V. B.

    2018-05-01

    Nonlinear dynamics of two electronic oscillators coupled via a memristive device has been investigated. Such model mimics the interaction between synaptically coupled brain neurons with the memristive device imitating neuron axon. The synaptic connection is provided by the adaptive behavior of memristive device that changes its resistance under the action of spike-like activity. Mathematical model of such a memristive interface has been developed to describe and predict the experimentally observed regularities of forced synchronization of neuron-like oscillators.

  13. Mirror neurons: From origin to function

    OpenAIRE

    Cook, R; Bird, G; Catmur, C; Press, C; Heyes, C

    2014-01-01

    This article argues that mirror neurons originate in sensorimotor associative learning and therefore a new approach is needed to investigate their functions. Mirror neurons were discovered about 20 years ago in the monkey brain, and there is now evidence that they are also present in the human brain. The intriguing feature of many mirror neurons is that they fire not only when the animal is performing an action, such as grasping an object using a power grip, but also when the animal passively...

  14. Geometrical Determinants of Neuronal Actin Waves

    OpenAIRE

    Tomba, Caterina; Bra?ni, C?line; Bugnicourt, Ghislain; Cohen, Floriane; Friedrich, Benjamin M.; Gov, Nir S.; Villard, Catherine

    2017-01-01

    Hippocampal neurons produce in their early stages of growth propagative, actin-rich dynamical structures called actin waves. The directional motion of actin waves from the soma to the tip of neuronal extensions has been associated with net forward growth, and ultimately with the specification of neurites into axon and dendrites. Here, geometrical cues are used to control actin wave dynamics by constraining neurons on adhesive stripes of various widths. A key observable, the average time betwe...

  15. The Relevance of AgRP Neuron-Derived GABA Inputs to POMC Neurons Differs for Spontaneous and Evoked Release

    OpenAIRE

    Rau, Andrew R.; Hentges, Shane T.

    2017-01-01

    Hypothalamic agouti-related peptide (AgRP) neurons potently stimulate food intake, whereas proopiomelanocortin (POMC) neurons inhibit feeding. Whether AgRP neurons exert their orexigenic actions, at least in part, by inhibiting anorexigenic POMC neurons remains unclear. Here, the connectivity between GABA-releasing AgRP neurons and POMC neurons was examined in brain slices from male and female mice. GABA-mediated spontaneous IPSCs (sIPSCs) in POMC neurons were unaffected by disturbing GABA re...

  16. Changes in Lymantria dispar protocerebral neurosecretory neurons after exposure to cadmium

    Directory of Open Access Journals (Sweden)

    Ilijin Larisa

    2011-01-01

    Full Text Available Gypsy moth 4th instar caterpillars were fed for 3 days with an artificial diet supplemented with increasing cadmium (Cd concentrations (0, 10, 30, 100 and 250 μg⁄g of dry food weight. Changes in the morphometric characteristics of A1’ dorso-medial and L2 dorso-lateral neurosecretory neurons (nsn were analyzed. In the A1’ nsn, Cd supplements led to an enhanced nuclear size, except in the group treated with 250 μg Cd⁄g in the form of dry food. The size of L2 type nsn was increased in the groups provided with 30 and 100 μg Cd⁄g, while no differences in the size of nuclei was detected in L2 neurons among the experimental groups.

  17. Clustering predicts memory performance in networks of spiking and non-spiking neurons

    Directory of Open Access Journals (Sweden)

    Weiliang eChen

    2011-03-01

    Full Text Available The problem we address in this paper is that of finding effective and parsimonious patterns of connectivity in sparse associative memories. This problem must be addressed in real neuronal systems, so that results in artificial systems could throw light on real systems. We show that there are efficient patterns of connectivity and that these patterns are effective in models with either spiking or non-spiking neurons. This suggests that there may be some underlying general principles governing good connectivity in such networks. We also show that the clustering of the network, measured by Clustering Coefficient, has a strong linear correlation to the performance of associative memory. This result is important since a purely static measure of network connectivity appears to determine an important dynamic property of the network.

  18. Performance limitations of relay neurons.

    Directory of Open Access Journals (Sweden)

    Rahul Agarwal

    Full Text Available Relay cells are prevalent throughout sensory systems and receive two types of inputs: driving and modulating. The driving input contains receptive field properties that must be transmitted while the modulating input alters the specifics of transmission. For example, the visual thalamus contains relay neurons that receive driving inputs from the retina that encode a visual image, and modulating inputs from reticular activating system and layer 6 of visual cortex that control what aspects of the image will be relayed back to visual cortex for perception. What gets relayed depends on several factors such as attentional demands and a subject's goals. In this paper, we analyze a biophysical based model of a relay cell and use systems theoretic tools to construct analytic bounds on how well the cell transmits a driving input as a function of the neuron's electrophysiological properties, the modulating input, and the driving signal parameters. We assume that the modulating input belongs to a class of sinusoidal signals and that the driving input is an irregular train of pulses with inter-pulse intervals obeying an exponential distribution. Our analysis applies to any [Formula: see text] order model as long as the neuron does not spike without a driving input pulse and exhibits a refractory period. Our bounds on relay reliability contain performance obtained through simulation of a second and third order model, and suggest, for instance, that if the frequency of the modulating input increases or the DC offset decreases, then relay increases. Our analysis also shows, for the first time, how the biophysical properties of the neuron (e.g. ion channel dynamics define the oscillatory patterns needed in the modulating input for appropriately timed relay of sensory information. In our discussion, we describe how our bounds predict experimentally observed neural activity in the basal ganglia in (i health, (ii in Parkinson's disease (PD, and (iii in PD during

  19. Neurosemantics, neurons and system theory.

    Science.gov (United States)

    Breidbach, Olaf

    2007-08-01

    Following the concept of internal representations, signal processing in a neuronal system has to be evaluated exclusively based on internal system characteristics. Thus, this approach omits the external observer as a control function for sensory integration. Instead, the configuration of the system and its computational performance are the effects of endogenous factors. Such self-referential operation is due to a strictly local computation in a network and, thereby, computations follow a set of rules that constitute the emergent behaviour of the system. These rules can be shown to correspond to a "logic" that is intrinsic to the system, an idea which provides the basis for neurosemantics.

  20. Neuronal involvement in cisplatin neuropathy

    DEFF Research Database (Denmark)

    Krarup-Hansen, A; Helweg-Larsen, Susanne Elisabeth; Schmalbruch, H

    2007-01-01

    Although it is well known that cisplatin causes a sensory neuropathy, the primary site of involvement is not established. The clinical symptoms localized in a stocking-glove distribution may be explained by a length dependent neuronopathy or by a distal axonopathy. To study whether the whole neuron...... of the foot evoked by a tactile probe showed similar changes to those observed in SNAPs evoked by electrical stimulation. At these doses, somatosensory evoked potentials (SEPs) from the tibial nerve had increased latencies of peripheral, spinal and central responses suggesting loss of central processes...

  1. Implementing Signature Neural Networks with Spiking Neurons.

    Science.gov (United States)

    Carrillo-Medina, José Luis; Latorre, Roberto

    2016-01-01

    Spiking Neural Networks constitute the most promising approach to develop realistic Artificial Neural Networks (ANNs). Unlike traditional firing rate-based paradigms, information coding in spiking models is based on the precise timing of individual spikes. It has been demonstrated that spiking ANNs can be successfully and efficiently applied to multiple realistic problems solvable with traditional strategies (e.g., data classification or pattern recognition). In recent years, major breakthroughs in neuroscience research have discovered new relevant computational principles in different living neural systems. Could ANNs benefit from some of these recent findings providing novel elements of inspiration? This is an intriguing question for the research community and the development of spiking ANNs including novel bio-inspired information coding and processing strategies is gaining attention. From this perspective, in this work, we adapt the core concepts of the recently proposed Signature Neural Network paradigm-i.e., neural signatures to identify each unit in the network, local information contextualization during the processing, and multicoding strategies for information propagation regarding the origin and the content of the data-to be employed in a spiking neural network. To the best of our knowledge, none of these mechanisms have been used yet in the context of ANNs of spiking neurons. This paper provides a proof-of-concept for their applicability in such networks. Computer simulations show that a simple network model like the discussed here exhibits complex self-organizing properties. The combination of multiple simultaneous encoding schemes allows the network to generate coexisting spatio-temporal patterns of activity encoding information in different spatio-temporal spaces. As a function of the network and/or intra-unit parameters shaping the corresponding encoding modality, different forms of competition among the evoked patterns can emerge even in the absence

  2. Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications.

    Science.gov (United States)

    Pastur-Romay, Lucas Antón; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana Belén

    2016-08-11

    Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL) and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs). All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS), Quantitative Structure-Activity Relationship (QSAR) research, protein structure prediction and genomics (and other omics) data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron-Astrocyte Networks (DANAN) could overcome the difficulties in architecture design, learning process and scalability of the current ML methods.

  3. Multielectrode recordings from auditory neurons in the brain of a small grasshopper.

    Science.gov (United States)

    Bhavsar, Mit Balvantray; Heinrich, Ralf; Stumpner, Andreas

    2015-12-30

    Grasshoppers have been used as a model system to study the neuronal basis of insect acoustic behavior. Auditory neurons have been described from intracellular recordings. The growing interest to study population activity of neurons has been satisfied so far with artificially combining data from different individuals. We for the first time used multielectrode recordings from a small grasshopper brain. We used three 12μm tungsten wires (combined in a multielectrode) to record from local brain neurons and from a population of auditory neurons entering the brain from the thorax. Spikes of the recorded units were separated by sorting algorithms and spike collision analysis. The tungsten wires enabled stable recordings with high signal to noise ratio. Due to the tight temporal coupling of auditory activity to the stimulus spike collisions were frequent and collision analysis retrieved 10-15% of additional spikes. Marking the electrode position was possible using a fluorescent dye or electrocoagulation with high current. Physiological identification of units described from intracellular recordings was hard to achieve. 12μm tungsten wires gave a better signal to noise ratio than 15μm copper wires previously used in recordings from bees' brains. Recording the population activity of auditory neurons in one individual prevents interindividual and trial-to-trial variability which otherwise reduce the validity of the analysis. Double intracellular recordings have quite low success rate and therefore are rarely achieved and their stability is much lower than that of multielectrode recordings which allows sampling of data for 30min or more. Copyright © 2015 Elsevier B.V. All rights reserved.

  4. A New Population of Parvocellular Oxytocin Neurons Controlling Magnocellular Neuron Activity and Inflammatory Pain Processing.

    Science.gov (United States)

    Eliava, Marina; Melchior, Meggane; Knobloch-Bollmann, H Sophie; Wahis, Jérôme; da Silva Gouveia, Miriam; Tang, Yan; Ciobanu, Alexandru Cristian; Triana Del Rio, Rodrigo; Roth, Lena C; Althammer, Ferdinand; Chavant, Virginie; Goumon, Yannick; Gruber, Tim; Petit-Demoulière, Nathalie; Busnelli, Marta; Chini, Bice; Tan, Linette L; Mitre, Mariela; Froemke, Robert C; Chao, Moses V; Giese, Günter; Sprengel, Rolf; Kuner, Rohini; Poisbeau, Pierrick; Seeburg, Peter H; Stoop, Ron; Charlet, Alexandre; Grinevich, Valery

    2016-03-16

    Oxytocin (OT) is a neuropeptide elaborated by the hypothalamic paraventricular (PVN) and supraoptic (SON) nuclei. Magnocellular OT neurons of these nuclei innervate numerous forebrain regions and release OT into the blood from the posterior pituitary. The PVN also harbors parvocellular OT cells that project to the brainstem and spinal cord, but their function has not been directly assessed. Here, we identified a subset of approximately 30 parvocellular OT neurons, with collateral projections onto magnocellular OT neurons and neurons of deep layers of the spinal cord. Evoked OT release from these OT neurons suppresses nociception and promotes analgesia in an animal model of inflammatory pain. Our findings identify a new population of OT neurons that modulates nociception in a two tier process: (1) directly by release of OT from axons onto sensory spinal cord neurons and inhibiting their activity and (2) indirectly by stimulating OT release from SON neurons into the periphery. Copyright © 2016 Elsevier Inc. All rights reserved.

  5. Mechanisms of Neuronal Apoptosis In Vivo

    National Research Council Canada - National Science Library

    Martin, Lee J

    2004-01-01

    .... Neuronal cell death in the form of apoptosis or necrosis occurs after exposure to neurotoxins, chemical warfare agents, radiation, viruses, and after seizures, trauma, limb amputation, and hypoxic...

  6. Autosomal dominant adult neuronal ceroid lipofuscinosis

    NARCIS (Netherlands)

    Nijssen, Peter C.G.

    2011-01-01

    this thesis investigates a family with autosomal dominant neuronal ceroid lipofuscinosis, with chapters on clinical neurology, neuropathology, neurogenetics, neurophysiology, auditory and visual aspects.

  7. Neurochemistry of olivocochlear neurons in the hamster.

    Science.gov (United States)

    Reuss, Stefan; Disque-Kaiser, Ursula; Antoniou-Lipfert, Patricia; Gholi, Maryam Najaf; Riemann, Elke; Riemann, Randolf

    2009-04-01

    The present study was conducted to characterize the superior olivary complex (SOC) of the lower brain stem in the pigmented Djungarian hamster Phodopus sungorus. Using Nissl-stained serial cryostat sections from fresh-frozen brains, we determined the borders of the SOC nuclei. We also identified olivocochlear (OC) neurons by retrograde neuronal tracing upon injection of Fluoro-Gold into the scala tympani. To evaluate the SOC as a putative source of neuronal nitric oxide synthase (nNOS), arginine-vasopressin (AVP), oxytocin (OT), vasoactive intestinal polypeptide (VIP), or pituitary adenylate cyclase-activating polypeptide (PACAP) that were all found in the cochlea, we conducted immunohistochemistry on sections exhibiting retrogradely labeled neurons. We did not observe AVP-, OT-, or VIP-immunoreactivity, neither in OC neurons nor in the SOC at all, revealing that cochlear AVP, OT, and VIP are of nonolivary origin. However, we found nNOS, the enzyme responsible for nitric oxide synthesis in neurons, and PACAP in neuronal perikarya of the SOC. Retrogradely labeled neurons of the lateral olivocochlear (LOC) system in the lateral superior olive did not contain PACAP and were only infrequently nNOS-immunoreactive. In contrast, some shell neurons and some of the medial OC (MOC) system exhibited immunofluorescence for either substance. Our data obtained from the dwarf hamster Phodopus sungorus confirm previous observations that a part of the LOC system is nitrergic. They further demonstrate that the medial olivocochlear system is partly nitrergic and use PACAP as neurotransmitter or modulator.

  8. Mirror neurons and language in schizophrenia

    OpenAIRE

    Bendová, Marie

    2016-01-01

    Mirror neurons are a specific kind of visuomotor neurons that are involved in action execution and also in action perception. The mirror mechanism is linked to a variety of complex psychological functions such as social-cognitive functions and language. People with schizophrenia have often difficulties both in mirror neuron system and in language skills. In the first part of our research we studied the connectivity of mirror neuron areas (such as IFG, STG, PMC, SMC and so on) by fMRI in resti...

  9. Beyond Critical Exponents in Neuronal Avalanches

    Science.gov (United States)

    Friedman, Nir; Butler, Tom; Deville, Robert; Beggs, John; Dahmen, Karin

    2011-03-01

    Neurons form a complex network in the brain, where they interact with one another by firing electrical signals. Neurons firing can trigger other neurons to fire, potentially causing avalanches of activity in the network. In many cases these avalanches have been found to be scale independent, similar to critical phenomena in diverse systems such as magnets and earthquakes. We discuss models for neuronal activity that allow for the extraction of testable, statistical predictions. We compare these models to experimental results, and go beyond critical exponents.

  10. Glutamate mediated astrocytic filtering of neuronal activity.

    Directory of Open Access Journals (Sweden)

    Gilad Wallach

    2014-12-01

    Full Text Available Neuron-astrocyte communication is an important regulatory mechanism in various brain functions but its complexity and role are yet to be fully understood. In particular, the temporal pattern of astrocyte response to neuronal firing has not been fully characterized. Here, we used neuron-astrocyte cultures on multi-electrode arrays coupled to Ca2+ imaging and explored the range of neuronal stimulation frequencies while keeping constant the amount of stimulation. Our results reveal that astrocytes specifically respond to the frequency of neuronal stimulation by intracellular Ca2+ transients, with a clear onset of astrocytic activation at neuron firing rates around 3-5 Hz. The cell-to-cell heterogeneity of the astrocyte Ca2+ response was however large and increasing with stimulation frequency. Astrocytic activation by neurons was abolished with antagonists of type I metabotropic glutamate receptor, validating the glutamate-dependence of this neuron-to-astrocyte pathway. Using a realistic biophysical model of glutamate-based intracellular calcium signaling in astrocytes, we suggest that the stepwise response is due to the supralinear dynamics of intracellular IP3 and that the heterogeneity of the responses may be due to the heterogeneity of the astrocyte-to-astrocyte couplings via gap junction channels. Therefore our results present astrocyte intracellular Ca2+ activity as a nonlinear integrator of glutamate-dependent neuronal activity.

  11. Glutamate Mediated Astrocytic Filtering of Neuronal Activity

    Science.gov (United States)

    Herzog, Nitzan; De Pittà, Maurizio; Jacob, Eshel Ben; Berry, Hugues; Hanein, Yael

    2014-01-01

    Neuron-astrocyte communication is an important regulatory mechanism in various brain functions but its complexity and role are yet to be fully understood. In particular, the temporal pattern of astrocyte response to neuronal firing has not been fully characterized. Here, we used neuron-astrocyte cultures on multi-electrode arrays coupled to Ca2+ imaging and explored the range of neuronal stimulation frequencies while keeping constant the amount of stimulation. Our results reveal that astrocytes specifically respond to the frequency of neuronal stimulation by intracellular Ca2+ transients, with a clear onset of astrocytic activation at neuron firing rates around 3-5 Hz. The cell-to-cell heterogeneity of the astrocyte Ca2+ response was however large and increasing with stimulation frequency. Astrocytic activation by neurons was abolished with antagonists of type I metabotropic glutamate receptor, validating the glutamate-dependence of this neuron-to-astrocyte pathway. Using a realistic biophysical model of glutamate-based intracellular calcium signaling in astrocytes, we suggest that the stepwise response is due to the supralinear dynamics of intracellular IP3 and that the heterogeneity of the responses may be due to the heterogeneity of the astrocyte-to-astrocyte couplings via gap junction channels. Therefore our results present astrocyte intracellular Ca2+ activity as a nonlinear integrator of glutamate-dependent neuronal activity. PMID:25521344

  12. Adaptive Neuron Model: An architecture for the rapid learning of nonlinear topological transformations

    Science.gov (United States)

    Tawel, Raoul (Inventor)

    1994-01-01

    A method for the rapid learning of nonlinear mappings and topological transformations using a dynamically reconfigurable artificial neural network is presented. This fully-recurrent Adaptive Neuron Model (ANM) network was applied to the highly degenerate inverse kinematics problem in robotics, and its performance evaluation is bench-marked. Once trained, the resulting neuromorphic architecture was implemented in custom analog neural network hardware and the parameters capturing the functional transformation downloaded onto the system. This neuroprocessor, capable of 10(exp 9) ops/sec, was interfaced directly to a three degree of freedom Heathkit robotic manipulator. Calculation of the hardware feed-forward pass for this mapping was benchmarked at approximately 10 microsec.

  13. Life-long stability of neurons: a century of research on neurogenesis, neuronal death and neuron quantification in adult CNS.

    Science.gov (United States)

    Turlejski, Kris; Djavadian, Ruzanna

    2002-01-01

    In this chapter we provide an extensive review of 100 years of research on the stability of neurons in the mammalian brain, with special emphasis on humans. Although Cajal formulated the Neuronal Doctrine, he was wrong in his beliefs that adult neurogenesis did not occur and adult neurons are dying throughout life. These two beliefs became accepted "common knowledge" and have shaped much of neuroscience research and provided much of the basis for clinical treatment of age-related brain diseases. In this review, we consider adult neurogenesis from a historical and evolutionary perspective. It is concluded, that while adult neurogenesis is a factor in the dynamics of the dentate gyrus and olfactory bulb, it is probably not a major factor during the life-span in most brain areas. Likewise, the acceptance of neuronal death as an explanation for normal age-related senility is challenged with evidence collected over the last fifty years. Much of the problem in changing this common belief of dying neurons was the inadequacies of neuronal counting methods. In this review we discuss in detail implications of recent improvements in neuronal quantification. We conclude: First, age-related neuronal atrophy is the major factor in functional deterioration of existing neurons and could be slowed down, or even reversed by various pharmacological interventions. Second, in most cases neuronal degeneration during aging is a pathology that in principle may be avoided. Third, loss of myelin and of the white matter is more frequent and important than the limited neuronal death in normal aging.

  14. Spin-neurons: A possible path to energy-efficient neuromorphic computers

    Energy Technology Data Exchange (ETDEWEB)

    Sharad, Mrigank; Fan, Deliang; Roy, Kaushik [School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907 (United States)

    2013-12-21

    Recent years have witnessed growing interest in the field of brain-inspired computing based on neural-network architectures. In order to translate the related algorithmic models into powerful, yet energy-efficient cognitive-computing hardware, computing-devices beyond CMOS may need to be explored. The suitability of such devices to this field of computing would strongly depend upon how closely their physical characteristics match with the essential computing primitives employed in such models. In this work, we discuss the rationale of applying emerging spin-torque devices for bio-inspired computing. Recent spin-torque experiments have shown the path to low-current, low-voltage, and high-speed magnetization switching in nano-scale magnetic devices. Such magneto-metallic, current-mode spin-torque switches can mimic the analog summing and “thresholding” operation of an artificial neuron with high energy-efficiency. Comparison with CMOS-based analog circuit-model of a neuron shows that “spin-neurons” (spin based circuit model of neurons) can achieve more than two orders of magnitude lower energy and beyond three orders of magnitude reduction in energy-delay product. The application of spin-neurons can therefore be an attractive option for neuromorphic computers of future.

  15. A hierarchical model for structure learning based on the physiological characteristics of neurons

    Institute of Scientific and Technical Information of China (English)

    WEI Hui

    2007-01-01

    Almost all applications of Artificial Neural Networks (ANNs) depend mainly on their memory ability.The characteristics of typical ANN models are fixed connections,with evolved weights,globalized representations,and globalized optimizations,all based on a mathematical approach.This makes those models to be deficient in robustness,efficiency of learning,capacity,anti-jamming between training sets,and correlativity of samples,etc.In this paper,we attempt to address these problems by adopting the characteristics of biological neurons in morphology and signal processing.A hierarchical neural network was designed and realized to implement structure learning and representations based on connected structures.The basic characteristics of this model are localized and random connections,field limitations of neuron fan-in and fan-out,dynamic behavior of neurons,and samples represented through different sub-circuits of neurons specialized into different response patterns.At the end of this paper,some important aspects of error correction,capacity,learning efficiency,and soundness of structural representation are analyzed theoretically.This paper has demonstrated the feasibility and advantages of structure learning and representation.This model can serve as a fundamental element of cognitive systems such as perception and associative memory.Key-words structure learning,representation,associative memory,computational neuroscience

  16. Out of time: a possible link between mirror neurons, autism and electromagnetic radiation.

    Science.gov (United States)

    Thornton, Ian M

    2006-01-01

    Recent evidence suggests a link between autism and the human mirror neuron system. In this paper, I argue that temporal disruption from the environment may play an important role in the observed mirror neuron dysfunction, leading in turn to the pattern of deficits associated with autism. I suggest that the developing nervous system of an infant may be particularly prone to temporal noise that can interfere with the initial calibration of brain networks such as the mirror neuron system. The most likely source of temporal noise in the environment is artificially generated electromagnetic radiation. To date, there has been little evidence that electromagnetic radiation poses a direct biological hazard. It is clear, however, that time-varying electromagnetic waves have the potential to temporally modulate the nervous system, particularly when populations of neurons are required to act together. This modulation may be completely harmless for the fully developed nervous system of an adult. For an infant, this same temporal disruption might act to severely delay or disrupt vital calibration processes.

  17. Endorphinic neurons are contacting the tuberoinfundibular dopaminergic neurons in the rat brain

    International Nuclear Information System (INIS)

    Morel, G.; Pelletier, G.

    1986-01-01

    The anatomical relationships between endorphinic neurons and dopaminergic neurons were evaluated in the rat hypothalamus using a combination of immunocytochemistry and autoradiography. In the arcuate nucleus, endorphinic endings were seen making contacts with dopaminergic cell bodies and dendrites. No synapsis could be observed at the sites of contacts. These results strongly suggest that the endorphinic neurons are directly acting on dopaminergic neurons to modify the release of dopamine into the pituitary portal system

  18. Discrimination of communication vocalizations by single neurons and groups of neurons in the auditory midbrain.

    Science.gov (United States)

    Schneider, David M; Woolley, Sarah M N

    2010-06-01

    Many social animals including songbirds use communication vocalizations for individual recognition. The perception of vocalizations depends on the encoding of complex sounds by neurons in the ascending auditory system, each of which is tuned to a particular subset of acoustic features. Here, we examined how well the responses of single auditory neurons could be used to discriminate among bird songs and we compared discriminability to spectrotemporal tuning. We then used biologically realistic models of pooled neural responses to test whether the responses of groups of neurons discriminated among songs better than the responses of single neurons and whether discrimination by groups of neurons was related to spectrotemporal tuning and trial-to-trial response variability. The responses of single auditory midbrain neurons could be used to discriminate among vocalizations with a wide range of abilities, ranging from chance to 100%. The ability to discriminate among songs using single neuron responses was not correlated with spectrotemporal tuning. Pooling the responses of pairs of neurons generally led to better discrimination than the average of the two inputs and the most discriminating input. Pooling the responses of three to five single neurons continued to improve neural discrimination. The increase in discriminability was largest for groups of neurons with similar spectrotemporal tuning. Further, we found that groups of neurons with correlated spike trains achieved the largest gains in discriminability. We simulated neurons with varying levels of temporal precision and measured the discriminability of responses from single simulated neurons and groups of simulated neurons. Simulated neurons with biologically observed levels of temporal precision benefited more from pooling correlated inputs than did neurons with highly precise or imprecise spike trains. These findings suggest that pooling correlated neural responses with the levels of precision observed in the

  19. BigNeuron: Large-scale 3D Neuron Reconstruction from Optical Microscopy Images

    OpenAIRE

    Peng, Hanchuan; Hawrylycz, Michael; Roskams, Jane; Hill, Sean; Spruston, Nelson; Meijering, Erik; Ascoli, Giorgio A.

    2015-01-01

    textabstractUnderstanding the structure of single neurons is critical for understanding how they function within neural circuits. BigNeuron is a new community effort that combines modern bioimaging informatics, recent leaps in labeling and microscopy, and the widely recognized need for openness and standardization to provide a community resource for automated reconstruction of dendritic and axonal morphology of single neurons. Understanding the structure of single neurons is critical for unde...

  20. Leptin Action on GABAergic Neurons Prevents Obesity and Reduces Inhibitory Tone to POMC Neurons

    OpenAIRE

    Vong, Linh; Ye, Chianping; Yang, Zongfang; Choi, Brian; Chua, Streamson; Lowell, Bradford B.

    2011-01-01

    Leptin acts in the brain to prevent obesity. The underlying neurocircuitry responsible for this is poorly understood, in part due to incomplete knowledge regarding first order, leptin-responsive neurons. To address this, we and others have been removing leptin receptors from candidate first order neurons. While functionally relevant neurons have been identified, the observed effects have been small suggesting that most first order neurons remain unidentified. Here we take an alternative appro...