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Sample records for neural generators related

  1. Learning-Related Changes in Adolescents' Neural Networks during Hypothesis-Generating and Hypothesis-Understanding Training

    Science.gov (United States)

    Lee, Jun-Ki; Kwon, Yongju

    2012-01-01

    Fourteen science high school students participated in this study, which investigated neural-network plasticity associated with hypothesis-generating and hypothesis-understanding in learning. The students were divided into two groups and participated in either hypothesis-generating or hypothesis-understanding type learning programs, which were…

  2. I think therefore I am: Rest-related prefrontal cortex neural activity is involved in generating the sense of self.

    Science.gov (United States)

    Gruberger, M; Levkovitz, Y; Hendler, T; Harel, E V; Harari, H; Ben Simon, E; Sharon, H; Zangen, A

    2015-05-01

    The sense of self has always been a major focus in the psychophysical debate. It has been argued that this complex ongoing internal sense cannot be explained by any physical measure and therefore substantiates a mind-body differentiation. Recently, however, neuro-imaging studies have associated self-referential spontaneous thought, a core-element of the ongoing sense of self, with synchronous neural activations during rest in the medial prefrontal cortex (PFC), as well as the medial and lateral parietal cortices. By applying deep transcranial magnetic stimulation (TMS) over human PFC before rest, we disrupted activity in this neural circuitry thereby inducing reports of lowered self-awareness and strong feelings of dissociation. This effect was not found with standard or sham TMS, or when stimulation was followed by a task instead of rest. These findings demonstrate for the first time a critical, causal role of intact rest-related PFC activity patterns in enabling integrated, enduring, self-referential mental processing. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. Neural correlates of continuous causal word generation.

    Science.gov (United States)

    Wende, Kim C; Straube, Benjamin; Stratmann, Mirjam; Sommer, Jens; Kircher, Tilo; Nagels, Arne

    2012-09-01

    Causality provides a natural structure for organizing our experience and language. Causal reasoning during speech production is a distinct aspect of verbal communication, whose related brain processes are yet unknown. The aim of the current study was to investigate the neural mechanisms underlying the continuous generation of cause-and-effect coherences during overt word production. During fMRI data acquisition participants performed three verbal fluency tasks on identical cue words: A novel causal verbal fluency task (CVF), requiring the production of multiple reasons to a given cue word (e.g. reasons for heat are fire, sun etc.), a semantic (free association, FA, e.g. associations with heat are sweat, shower etc.) and a phonological control task (phonological verbal fluency, PVF, e.g. rhymes with heat are meat, wheat etc.). We found that, in contrast to PVF, both CVF and FA activated a left lateralized network encompassing inferior frontal, inferior parietal and angular regions, with further bilateral activation in middle and inferior as well as superior temporal gyri and the cerebellum. For CVF contrasted against FA, we found greater bold responses only in the left middle frontal cortex. Large overlaps in the neural activations during free association and causal verbal fluency indicate that the access to causal relationships between verbal concepts is at least partly based on the semantic neural network. The selective activation in the left middle frontal cortex for causal verbal fluency suggests that distinct neural processes related to cause-and-effect-relations are associated with the recruitment of middle frontal brain areas. Copyright © 2012 Elsevier Inc. All rights reserved.

  4. Neural mechanisms of sequence generation in songbirds

    Science.gov (United States)

    Langford, Bruce

    Animal models in research are useful for studying more complex behavior. For example, motor sequence generation of actions requiring good muscle coordination such as writing with a pen, playing an instrument, or speaking, may involve the interaction of many areas in the brain, each a complex system in itself; thus it can be difficult to determine causal relationships between neural behavior and the behavior being studied. Birdsong, however, provides an excellent model behavior for motor sequence learning, memory, and generation. The song consists of learned sequences of notes that are spectrographically stereotyped over multiple renditions of the song, similar to syllables in human speech. The main areas of the songbird brain involve in singing are known, however, the mechanisms by which these systems store and produce song are not well understood. We used a custom built, head-mounted, miniature motorized microdrive to chronically record the neural firing patterns of identified neurons in HVC, a pre-motor cortical nucleus which has been shown to be important in song timing. These were done in Bengalese finch which generate a song made up of stereotyped notes but variable note sequences. We observed song related bursting in neurons projecting to Area X, a homologue to basal ganglia, and tonic firing in HVC interneurons. Interneuron had firing rate patterns that were consistent over multiple renditions of the same note sequence. We also designed and built a light-weight, low-powered wireless programmable neural stimulator using Bluetooth Low Energy Protocol. It was able to generate perturbations in the song when current pulses were administered to RA, which projects to the brainstem nucleus responsible for syringeal muscle control.

  5. Neural network application to diesel generator diagnostics

    International Nuclear Information System (INIS)

    Logan, K.P.

    1990-01-01

    Diagnostic problems typically begin with the observation of some system behavior which is recognized as a deviation from the expected. The fundamental underlying process is one involving pattern matching cf observed symptoms to a set of compiled symptoms belonging to a fault-symptom mapping. Pattern recognition is often relied upon for initial fault detection and diagnosis. Parallel distributed processing (PDP) models employing neural network paradigms are known to be good pattern recognition devices. This paper describes the application of neural network processing techniques to the malfunction diagnosis of subsystems within a typical diesel generator configuration. Neural network models employing backpropagation learning were developed to correctly recognize fault conditions from the input diagnostic symptom patterns pertaining to various engine subsystems. The resulting network models proved to be excellent pattern recognizers for malfunction examples within the training set. The motivation for employing network models in lieu of a rule-based expert system, however, is related to the network's potential for generalizing malfunctions outside of the training set, as in the case of noisy or partial symptom patterns

  6. Generating Seismograms with Deep Neural Networks

    Science.gov (United States)

    Krischer, L.; Fichtner, A.

    2017-12-01

    The recent surge of successful uses of deep neural networks in computer vision, speech recognition, and natural language processing, mainly enabled by the availability of fast GPUs and extremely large data sets, is starting to see many applications across all natural sciences. In seismology these are largely confined to classification and discrimination tasks. In this contribution we explore the use of deep neural networks for another class of problems: so called generative models.Generative modelling is a branch of statistics concerned with generating new observed data samples, usually by drawing from some underlying probability distribution. Samples with specific attributes can be generated by conditioning on input variables. In this work we condition on seismic source (mechanism and location) and receiver (location) parameters to generate multi-component seismograms.The deep neural networks are trained on synthetic data calculated with Instaseis (http://instaseis.net, van Driel et al. (2015)) and waveforms from the global ShakeMovie project (http://global.shakemovie.princeton.edu, Tromp et al. (2010)). The underlying radially symmetric or smoothly three dimensional Earth structures result in comparatively small waveform differences from similar events or at close receivers and the networks learn to interpolate between training data samples.Of particular importance is the chosen misfit functional. Generative adversarial networks (Goodfellow et al. (2014)) implement a system in which two networks compete: the generator network creates samples and the discriminator network distinguishes these from the true training examples. Both are trained in an adversarial fashion until the discriminator can no longer distinguish between generated and real samples. We show how this can be applied to seismograms and in particular how it compares to networks trained with more conventional misfit metrics. Last but not least we attempt to shed some light on the black-box nature of

  7. Neural network based control of Doubly Fed Induction Generator in wind power generation

    Science.gov (United States)

    Barbade, Swati A.; Kasliwal, Prabha

    2012-07-01

    To complement the other types of pollution-free generation wind energy is a viable option. Previously wind turbines were operated at constant speed. The evolution of technology related to wind systems industry leaded to the development of a generation of variable speed wind turbines that present many advantages compared to the fixed speed wind turbines. In this paper the phasor model of DFIG is used. This paper presents a study of a doubly fed induction generator driven by a wind turbine connected to the grid, and controlled by artificial neural network ANN controller. The behaviour of the system is shown with PI control, and then as controlled by ANN. The effectiveness of the artificial neural network controller is compared to that of a PI controller. The SIMULINK/MATLAB simulation for Doubly Fed Induction Generator and corresponding results and waveforms are displayed.

  8. Neural activation in stress-related exhaustion

    DEFF Research Database (Denmark)

    Gavelin, Hanna Malmberg; Neely, Anna Stigsdotter; Andersson, Micael

    2017-01-01

    The primary purpose of this study was to investigate the association between burnout and neural activation during working memory processing in patients with stress-related exhaustion. Additionally, we investigated the neural effects of cognitive training as part of stress rehabilitation. Fifty...... association between burnout level and working memory performance was found, however, our findings indicate that frontostriatal neural responses related to working memory were modulated by burnout severity. We suggest that patients with high levels of burnout need to recruit additional cognitive resources...... to uphold task performance. Following cognitive training, increased neural activation was observed during 3-back in working memory-related regions, including the striatum, however, low sample size limits any firm conclusions....

  9. Application of genetic neural network in steam generator fault diagnosing

    International Nuclear Information System (INIS)

    Lin Xiaogong; Jiang Xingwei; Liu Tao; Shi Xiaocheng

    2005-01-01

    In the paper, a new algorithm which neural network and genetic algorithm are mixed is adopted, aiming at the problems of slow convergence rate and easily falling into part minimums in network studying of traditional BP neural network, and used in the fault diagnosis of steam generator. The result shows that this algorithm can solve the convergence problem in the network trains effectively. (author)

  10. Incorporating Relation Paths in Neural Relation Extraction

    OpenAIRE

    Zeng, Wenyuan; Lin, Yankai; Liu, Zhiyuan; Sun, Maosong

    2016-01-01

    Distantly supervised relation extraction has been widely used to find novel relational facts from plain text. To predict the relation between a pair of two target entities, existing methods solely rely on those direct sentences containing both entities. In fact, there are also many sentences containing only one of the target entities, which provide rich and useful information for relation extraction. To address this issue, we build inference chains between two target entities via intermediate...

  11. Relation Classification via Recurrent Neural Network

    OpenAIRE

    Zhang, Dongxu; Wang, Dong

    2015-01-01

    Deep learning has gained much success in sentence-level relation classification. For example, convolutional neural networks (CNN) have delivered competitive performance without much effort on feature engineering as the conventional pattern-based methods. Thus a lot of works have been produced based on CNN structures. However, a key issue that has not been well addressed by the CNN-based method is the lack of capability to learn temporal features, especially long-distance dependency between no...

  12. Automated Item Generation with Recurrent Neural Networks.

    Science.gov (United States)

    von Davier, Matthias

    2018-03-12

    Utilizing technology for automated item generation is not a new idea. However, test items used in commercial testing programs or in research are still predominantly written by humans, in most cases by content experts or professional item writers. Human experts are a limited resource and testing agencies incur high costs in the process of continuous renewal of item banks to sustain testing programs. Using algorithms instead holds the promise of providing unlimited resources for this crucial part of assessment development. The approach presented here deviates in several ways from previous attempts to solve this problem. In the past, automatic item generation relied either on generating clones of narrowly defined item types such as those found in language free intelligence tests (e.g., Raven's progressive matrices) or on an extensive analysis of task components and derivation of schemata to produce items with pre-specified variability that are hoped to have predictable levels of difficulty. It is somewhat unlikely that researchers utilizing these previous approaches would look at the proposed approach with favor; however, recent applications of machine learning show success in solving tasks that seemed impossible for machines not too long ago. The proposed approach uses deep learning to implement probabilistic language models, not unlike what Google brain and Amazon Alexa use for language processing and generation.

  13. Generating original ideas: The neural underpinning of originality.

    Science.gov (United States)

    Mayseless, Naama; Eran, Ayelet; Shamay-Tsoory, Simone G

    2015-08-01

    One of the key aspects of creativity is the ability to produce original ideas. Originality is defined in terms of the novelty and rarity of an idea and is measured by the infrequency of the idea compared to other ideas. In the current study we focused on divergent thinking (DT) - the ability to produce many alternate ideas - and assessed the neural pathways associated with originality. Considering that generation of original ideas involves both the ability to generate new associations and the ability to overcome automatic common responses, we hypothesized that originality would be associated with activations in regions related to associative thinking, including areas of the default mode network (DMN) such as medial prefrontal areas, as well as with areas involved in cognitive control and inhibition. Thirty participants were scanned while performing a DT task that required the generation of original uses for common objects. The results indicate that the ability to produce original ideas is mediated by activity in several regions that are part of the DMN including the medial prefrontal cortex (mPFC) and the posterior cingulate cortex (PCC). Furthermore, individuals who are more original exhibited enhanced activation in the ventral anterior cingulate cortex (vACC), which was also positively coupled with activity in the left occipital-temporal area. These results are in line with the dual model of creativity, according to which original ideas are a product of the interaction between a system that generates ideas and a control system that evaluates these ideas. Copyright © 2015 Elsevier Inc. All rights reserved.

  14. User-generated content curation with deep convolutional neural networks

    OpenAIRE

    Tous Liesa, Rubén; Wust, Otto; Gómez, Mauro; Poveda, Jonatan; Elena, Marc; Torres Viñals, Jordi; Makni, Mouna; Ayguadé Parra, Eduard

    2016-01-01

    In this paper, we report a work consisting in using deep convolutional neural networks (CNNs) for curating and filtering photos posted by social media users (Instagram and Twitter). The final goal is to facilitate searching and discovering user-generated content (UGC) with potential value for digital marketing tasks. The images are captured in real time and automatically annotated with multiple CNNs. Some of the CNNs perform generic object recognition tasks while others perform what we call v...

  15. Modeling of steam generator in nuclear power plant using neural network ensemble

    International Nuclear Information System (INIS)

    Lee, S. K.; Lee, E. C.; Jang, J. W.

    2003-01-01

    Neural network is now being used in modeling the steam generator is known to be difficult due to the reverse dynamics. However, Neural network is prone to the problem of overfitting. This paper investigates the use of neural network combining methods to model steam generator water level and compares with single neural network. The results show that neural network ensemble is effective tool which can offer improved generalization, lower dependence of the training set and reduced training time

  16. Asymmetric Variate Generation via a Parameterless Dual Neural Learning Algorithm

    Directory of Open Access Journals (Sweden)

    Simone Fiori

    2008-01-01

    Full Text Available In a previous work (S. Fiori, 2006, we proposed a random number generator based on a tunable non-linear neural system, whose learning rule is designed on the basis of a cardinal equation from statistics and whose implementation is based on look-up tables (LUTs. The aim of the present manuscript is to improve the above-mentioned random number generation method by changing the learning principle, while retaining the efficient LUT-based implementation. The new method proposed here proves easier to implement and relaxes some previous limitations.

  17. The neural circuits that generate tics in Tourette's syndrome.

    Science.gov (United States)

    Wang, Zhishun; Maia, Tiago V; Marsh, Rachel; Colibazzi, Tiziano; Gerber, Andrew; Peterson, Bradley S

    2011-12-01

    The purpose of this study was to examine neural activity and connectivity within cortico-striato-thalamo-cortical circuits and to reveal circuit-based neural mechanisms that govern tic generation in Tourette's syndrome. Functional magnetic resonance imaging data were acquired from 13 individuals with Tourette's syndrome and 21 healthy comparison subjects during spontaneous or simulated tics. Independent component analysis with hierarchical partner matching was used to isolate neural activity within functionally distinct regions of cortico-striato-thalamo-cortical circuits. Granger causality was used to investigate causal interactions among these regions. The Tourette's syndrome group exhibited stronger neural activity and interregional causality than healthy comparison subjects throughout all portions of the motor pathway, including the sensorimotor cortex, putamen, pallidum, and substantia nigra. Activity in these areas correlated positively with the severity of tic symptoms. Activity within the Tourette's syndrome group was stronger during spontaneous tics than during voluntary tics in the somatosensory and posterior parietal cortices, putamen, and amygdala/hippocampus complex, suggesting that activity in these regions may represent features of the premonitory urges that generate spontaneous tic behaviors. In contrast, activity was weaker in the Tourette's syndrome group than in the healthy comparison group within portions of cortico-striato-thalamo-cortical circuits that exert top-down control over motor pathways (the caudate and anterior cingulate cortex), and progressively less activity in these regions accompanied more severe tic symptoms, suggesting that faulty activity in these circuits may result in their failure to control tic behaviors or the premonitory urges that generate them. Our findings, taken together, suggest that tics are caused by the combined effects of excessive activity in motor pathways and reduced activation in control portions of cortico

  18. Neural Sequence Generation Using Spatiotemporal Patterns of Inhibition.

    Directory of Open Access Journals (Sweden)

    Jonathan Cannon

    2015-11-01

    Full Text Available Stereotyped sequences of neural activity are thought to underlie reproducible behaviors and cognitive processes ranging from memory recall to arm movement. One of the most prominent theoretical models of neural sequence generation is the synfire chain, in which pulses of synchronized spiking activity propagate robustly along a chain of cells connected by highly redundant feedforward excitation. But recent experimental observations in the avian song production pathway during song generation have shown excitatory activity interacting strongly with the firing patterns of inhibitory neurons, suggesting a process of sequence generation more complex than feedforward excitation. Here we propose a model of sequence generation inspired by these observations in which a pulse travels along a spatially recurrent excitatory chain, passing repeatedly through zones of local feedback inhibition. In this model, synchrony and robust timing are maintained not through redundant excitatory connections, but rather through the interaction between the pulse and the spatiotemporal pattern of inhibition that it creates as it circulates the network. These results suggest that spatially and temporally structured inhibition may play a key role in sequence generation.

  19. Neural Sequence Generation Using Spatiotemporal Patterns of Inhibition.

    Science.gov (United States)

    Cannon, Jonathan; Kopell, Nancy; Gardner, Timothy; Markowitz, Jeffrey

    2015-11-01

    Stereotyped sequences of neural activity are thought to underlie reproducible behaviors and cognitive processes ranging from memory recall to arm movement. One of the most prominent theoretical models of neural sequence generation is the synfire chain, in which pulses of synchronized spiking activity propagate robustly along a chain of cells connected by highly redundant feedforward excitation. But recent experimental observations in the avian song production pathway during song generation have shown excitatory activity interacting strongly with the firing patterns of inhibitory neurons, suggesting a process of sequence generation more complex than feedforward excitation. Here we propose a model of sequence generation inspired by these observations in which a pulse travels along a spatially recurrent excitatory chain, passing repeatedly through zones of local feedback inhibition. In this model, synchrony and robust timing are maintained not through redundant excitatory connections, but rather through the interaction between the pulse and the spatiotemporal pattern of inhibition that it creates as it circulates the network. These results suggest that spatially and temporally structured inhibition may play a key role in sequence generation.

  20. Neural net generated seismic facies map and attribute facies map

    International Nuclear Information System (INIS)

    Addy, S.K.; Neri, P.

    1998-01-01

    The usefulness of 'seismic facies maps' in the analysis of an Upper Wilcox channel system in a 3-D survey shot by CGG in 1995 in Lavaca county in south Texas was discussed. A neural net-generated seismic facies map is a quick hydrocarbon exploration tool that can be applied regionally as well as on a prospect scale. The new technology is used to classify a constant interval parallel to a horizon in a 3-D seismic volume based on the shape of the wiggle traces using a neural network technology. The tool makes it possible to interpret sedimentary features of a petroleum deposit. The same technology can be used in regional mapping by making 'attribute facies maps' in which various forms of amplitude attributes, phase attributes or frequency attributes can be used

  1. Artificial earthquake record generation using cascade neural network

    Directory of Open Access Journals (Sweden)

    Bani-Hani Khaldoon A.

    2017-01-01

    Full Text Available This paper presents the results of using artificial neural networks (ANN in an inverse mapping problem for earthquake accelerograms generation. This study comprises of two parts: 1-D site response analysis; performed for Dubai Emirate at UAE, where eight earthquakes records are selected and spectral matching are performed to match Dubai response spectrum using SeismoMatch software. Site classification of Dubai soil is being considered for two classes C and D based on shear wave velocity of soil profiles. Amplifications factors are estimated to quantify Dubai soil effect. Dubai’s design response spectra are developed for site classes C & D according to International Buildings Code (IBC -2012. In the second part, ANN is employed to solve inverse mapping problem to generate time history earthquake record. Thirty earthquakes records and their design response spectrum with 5% damping are used to train two cascade forward backward neural networks (ANN1, ANN2. ANN1 is trained to map the design response spectrum to time history and ANN2 is trained to map time history records to the design response spectrum. Generalized time history earthquake records are generated using ANN1 for Dubai’s site classes C and D, and ANN2 is used to evaluate the performance of ANN1.

  2. Neural network based daily precipitation generator (NNGEN-P)

    Energy Technology Data Exchange (ETDEWEB)

    Boulanger, Jean-Philippe [LODYC, UMR CNRS/IRD/UPMC, Paris (France); University of Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina); Martinez, Fernando; Segura, Enrique C. [University of Buenos Aires, Departamento de Computacion, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina); Penalba, Olga [University of Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina)

    2007-02-15

    Daily weather generators are used in many applications and risk analyses. The present paper explores the potential of neural network architectures to design daily weather generator models. Focusing this first paper on precipitation, we design a collection of neural networks (multi-layer perceptrons in the present case), which are trained so as to approximate the empirical cumulative distribution (CDF) function for the occurrence of wet and dry spells and for the precipitation amounts. This approach contributes to correct some of the biases of the usual two-step weather generator models. As compared to a rainfall occurrence Markov model, NNGEN-P represents fairly well the mean and standard deviation of the number of wet days per month, and it significantly improves the simulation of the longest dry and wet periods. Then, we compared NNGEN-P to three parametric distribution functions usually applied to fit rainfall cumulative distribution functions (Gamma, Weibull and double-exponential). A data set of 19 Argentine stations was used. Also, data corresponding to stations in the United States, in Europe and in the Tropics were included to confirm the results. One of the advantages of NNGEN-P is that it is non-parametric. Unlike other parametric function, which adapt to certain types of climate regimes, NNGEN-P is fully adaptive to the observed cumulative distribution functions, which, on some occasions, may present complex shapes. On-going works will soon produce an extended version of NNGEN to temperature and radiation. (orig.)

  3. Generation of hourly irradiation synthetic series using the neural network multilayer perceptron

    Energy Technology Data Exchange (ETDEWEB)

    Hontoria, L.; Aguilera, J. [Universidad de Jaen, Linares-Jaen (Spain). Dpto. de Electronica; Zufiria, P. [Ciudad Universitaria, Madrid (Spain). Grupo de Redes Neuronales

    2002-05-01

    In this work, a methodology based on the neural network model called multilayer perceptron (MLP) to solve a typical problem in solar energy is presented. This methodology consists of the generation of synthetic series of hourly solar irradiation. The model presented is based on the capacity of the MLP for finding relations between variables for which interrelation is unknown explicitly. The information available can be included progressively at the series generator at different stages. A comparative study with other solar irradiation synthetic generation methods has been done in order to demonstrate the validity of the one proposed. (author)

  4. Learning Orthographic Structure With Sequential Generative Neural Networks.

    Science.gov (United States)

    Testolin, Alberto; Stoianov, Ivilin; Sperduti, Alessandro; Zorzi, Marco

    2016-04-01

    Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in connectionist modeling. Here, we investigated a sequential version of the restricted Boltzmann machine (RBM), a stochastic recurrent neural network that extracts high-order structure from sensory data through unsupervised generative learning and can encode contextual information in the form of internal, distributed representations. We assessed whether this type of network can extract the orthographic structure of English monosyllables by learning a generative model of the letter sequences forming a word training corpus. We show that the network learned an accurate probabilistic model of English graphotactics, which can be used to make predictions about the letter following a given context as well as to autonomously generate high-quality pseudowords. The model was compared to an extended version of simple recurrent networks, augmented with a stochastic process that allows autonomous generation of sequences, and to non-connectionist probabilistic models (n-grams and hidden Markov models). We conclude that sequential RBMs and stochastic simple recurrent networks are promising candidates for modeling cognition in the temporal domain. Copyright © 2015 Cognitive Science Society, Inc.

  5. Computation of optimal transport and related hedging problems via penalization and neural networks

    OpenAIRE

    Eckstein, Stephan; Kupper, Michael

    2018-01-01

    This paper presents a widely applicable approach to solving (multi-marginal, martingale) optimal transport and related problems via neural networks. The core idea is to penalize the optimization problem in its dual formulation and reduce it to a finite dimensional one which corresponds to optimizing a neural network with smooth objective function. We present numerical examples from optimal transport, martingale optimal transport, portfolio optimization under uncertainty and generative adversa...

  6. Dynamic simulation of a steam generator by neural networks

    International Nuclear Information System (INIS)

    Masini, R.; Padovani, E.; Ricotti, M.E.; Zio, E.

    1999-01-01

    Numerical simulation by computers of the dynamic evolution of complex systems and components is a fundamental phase of any modern engineering design activity. This is of particular importance for risk-based design projects which require that the system behavior be analyzed under several and often extreme conditions. The traditional methods of simulation typically entail long, iterative, processes which lead to large simulation times, often exceeding the transients real time. Artificial neural networks (ANNs) may be exploited in this context, their advantages residing mainly in the speed of computation, in the capability of generalizing from few examples, in the robustness to noisy and partially incomplete data and in the capability of performing empirical input-output mapping without complete knowledge of the underlying physics. In this paper we present a novel approach to dynamic simulation by ANNs based on a superposition scheme in which a set of networks are individually trained, each one to respond to a different input forcing function. The dynamic simulation of a steam generator is considered as an example to show the potentialities of this tool and to point out the difficulties and crucial issues which typically arise when attempting to establish an efficient neural network simulator. The structure of the networks system is such to feedback, at each time step, a portion of the past evolution of the transient and this allows a good reproduction of also non-linear dynamic behaviors. A nice characteristic of the approach is that the modularization of the training reduces substantially its burden and gives this neural simulation tool a nice feature of transportability. (orig.)

  7. ACO-Initialized Wavelet Neural Network for Vibration Fault Diagnosis of Hydroturbine Generating Unit

    Directory of Open Access Journals (Sweden)

    Zhihuai Xiao

    2015-01-01

    Full Text Available Considering the drawbacks of traditional wavelet neural network, such as low convergence speed and high sensitivity to initial parameters, an ant colony optimization- (ACO- initialized wavelet neural network is proposed in this paper for vibration fault diagnosis of a hydroturbine generating unit. In this method, parameters of the wavelet neural network are initialized by the ACO algorithm, and then the wavelet neural network is trained by the gradient descent algorithm. Amplitudes of the frequency components of the hydroturbine generating unit vibration signals are used as feature vectors for wavelet neural network training to realize mapping relationship from vibration features to fault types. A real vibration fault diagnosis case result of a hydroturbine generating unit shows that the proposed method has faster convergence speed and stronger generalization ability than the traditional wavelet neural network and ACO wavelet neural network. Thus it can provide an effective solution for online vibration fault diagnosis of a hydroturbine generating unit.

  8. 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.

  9. Efficient Pruning Method for Ensemble Self-Generating Neural Networks

    Directory of Open Access Journals (Sweden)

    Hirotaka Inoue

    2003-12-01

    Full Text Available Recently, multiple classifier systems (MCS have been used for practical applications to improve classification accuracy. Self-generating neural networks (SGNN are one of the suitable base-classifiers for MCS because of their simple setting and fast learning. However, the computation cost of the MCS increases in proportion to the number of SGNN. In this paper, we propose an efficient pruning method for the structure of the SGNN in the MCS. We compare the pruned MCS with two sampling methods. Experiments have been conducted to compare the pruned MCS with an unpruned MCS, the MCS based on C4.5, and k-nearest neighbor method. The results show that the pruned MCS can improve its classification accuracy as well as reducing the computation cost.

  10. ACO-Initialized Wavelet Neural Network for Vibration Fault Diagnosis of Hydroturbine Generating Unit

    OpenAIRE

    Xiao, Zhihuai; He, Xinying; Fu, Xiangqian; Malik, O. P.

    2015-01-01

    Considering the drawbacks of traditional wavelet neural network, such as low convergence speed and high sensitivity to initial parameters, an ant colony optimization- (ACO-) initialized wavelet neural network is proposed in this paper for vibration fault diagnosis of a hydroturbine generating unit. In this method, parameters of the wavelet neural network are initialized by the ACO algorithm, and then the wavelet neural network is trained by the gradient descent algorithm. Amplitudes of the fr...

  11. Application of Integrated Neural Network Method to Fault Diagnosis of Nuclear Steam Generator

    International Nuclear Information System (INIS)

    Zhou Gang; Yang Li

    2009-01-01

    A new fault diagnosis method based on integrated neural networks for nuclear steam generator (SG) was proposed in view of the shortcoming of the conventional fault monitoring and diagnosis method. In the method, two neural networks (ANNs) were employed for the fault diagnosis of steam generator. A neural network, which was used for predicting the values of steam generator operation parameters, was taken as the dynamics model of steam generator. The principle of fault monitoring method using the neural network model is to detect the deviations between process signals measured from an operating steam generator and corresponding output signals from the neural network model of steam generator. When the deviation exceeds the limit set in advance, the abnormal event is thought to occur. The other neural network as a fault classifier conducts the fault classification of steam generator. So, the fault types of steam generator are given by the fault classifier. The clear information on steam generator faults was obtained by fusing the monitoring and diagnosis results of two neural networks. The simulation results indicate that employing integrated neural networks can improve the capacity of fault monitoring and diagnosis for the steam generator. (authors)

  12. The Neural Border: Induction, Specification and Maturation of the territory that generates Neural Crest cells.

    Science.gov (United States)

    Pla, Patrick; Monsoro-Burq, Anne H

    2018-05-28

    The neural crest is induced at the edge between the neural plate and the nonneural ectoderm, in an area called the neural (plate) border, during gastrulation and neurulation. In recent years, many studies have explored how this domain is patterned, and how the neural crest is induced within this territory, that also participates to the prospective dorsal neural tube, the dorsalmost nonneural ectoderm, as well as placode derivatives in the anterior area. This review highlights the tissue interactions, the cell-cell signaling and the molecular mechanisms involved in this dynamic spatiotemporal patterning, resulting in the induction of the premigratory neural crest. Collectively, these studies allow building a complex neural border and early neural crest gene regulatory network, mostly composed by transcriptional regulations but also, more recently, including novel signaling interactions. Copyright © 2018. Published by Elsevier Inc.

  13. Sequentially firing neurons confer flexible timing in neural pattern generators

    International Nuclear Information System (INIS)

    Urban, Alexander; Ermentrout, Bard

    2011-01-01

    Neuronal networks exhibit a variety of complex spatiotemporal patterns that include sequential activity, synchrony, and wavelike dynamics. Inhibition is the primary means through which such patterns are implemented. This behavior is dependent on both the intrinsic dynamics of the individual neurons as well as the connectivity patterns. Many neural circuits consist of networks of smaller subcircuits (motifs) that are coupled together to form the larger system. In this paper, we consider a particularly simple motif, comprising purely inhibitory interactions, which generates sequential periodic dynamics. We first describe the dynamics of the single motif both for general balanced coupling (all cells receive the same number and strength of inputs) and then for a specific class of balanced networks: circulant systems. We couple these motifs together to form larger networks. We use the theory of weak coupling to derive phase models which, themselves, have a certain structure and symmetry. We show that this structure endows the coupled system with the ability to produce arbitrary timing relationships between symmetrically coupled motifs and that the phase relationships are robust over a wide range of frequencies. The theory is applicable to many other systems in biology and physics.

  14. A hybrid model based on neural networks for biomedical relation extraction.

    Science.gov (United States)

    Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Zhang, Shaowu; Sun, Yuanyuan; Yang, Liang

    2018-05-01

    Biomedical relation extraction can automatically extract high-quality biomedical relations from biomedical texts, which is a vital step for the mining of biomedical knowledge hidden in the literature. Recurrent neural networks (RNNs) and convolutional neural networks (CNNs) are two major neural network models for biomedical relation extraction. Neural network-based methods for biomedical relation extraction typically focus on the sentence sequence and employ RNNs or CNNs to learn the latent features from sentence sequences separately. However, RNNs and CNNs have their own advantages for biomedical relation extraction. Combining RNNs and CNNs may improve biomedical relation extraction. In this paper, we present a hybrid model for the extraction of biomedical relations that combines RNNs and CNNs. First, the shortest dependency path (SDP) is generated based on the dependency graph of the candidate sentence. To make full use of the SDP, we divide the SDP into a dependency word sequence and a relation sequence. Then, RNNs and CNNs are employed to automatically learn the features from the sentence sequence and the dependency sequences, respectively. Finally, the output features of the RNNs and CNNs are combined to detect and extract biomedical relations. We evaluate our hybrid model using five public (protein-protein interaction) PPI corpora and a (drug-drug interaction) DDI corpus. The experimental results suggest that the advantages of RNNs and CNNs in biomedical relation extraction are complementary. Combining RNNs and CNNs can effectively boost biomedical relation extraction performance. Copyright © 2018 Elsevier Inc. All rights reserved.

  15. Imidacloprid Exposure Suppresses Neural Crest Cells Generation during Early Chick Embryo Development.

    Science.gov (United States)

    Wang, Chao-Jie; Wang, Guang; Wang, Xiao-Yu; Liu, Meng; Chuai, Manli; Lee, Kenneth Ka Ho; He, Xiao-Song; Lu, Da-Xiang; Yang, Xuesong

    2016-06-15

    Imidacloprid is a neonicotinoid pesticide that is widely used in the control pests found on crops and fleas on pets. However, it is still unclear whether imidacloprid exposure could affect early embryo development-despite some studies having been conducted on the gametes. In this study, we demonstrated that imidacloprid exposure could lead to abnormal craniofacial osteogenesis in the developing chick embryo. Cranial neural crest cells (NCCs) are the progenitor cells of the chick cranial skull. We found that the imidacloprid exposure retards the development of gastrulating chick embryos. HNK-1, PAX7, and Ap-2α immunohistological stainings indicated that cranial NCCs generation was inhibited after imidacloprid exposure. Double immunofluorescent staining (Ap-2α and PHIS3 or PAX7 and c-Caspase3) revealed that imidacloprid exposure inhibited both NCC proliferation and apoptosis. In addition, it inhibited NCCs production by repressing Msx1 and BMP4 expression in the developing neural tube and by altering expression of EMT-related adhesion molecules (Cad6B, E-Cadherin, and N-cadherin) in the developing neural crests. We also determined that imidacloprid exposure suppressed cranial NCCs migration and their ability to differentiate. In sum, we have provided experimental evidence that imidacloprid exposure during embryogenesis disrupts NCCs development, which in turn causes defective cranial bone development.

  16. The neural coding of creative idea generation across adolescence and early adulthood

    Directory of Open Access Journals (Sweden)

    Sietske eKleibeuker

    2013-12-01

    Full Text Available Creativity is considered key to human prosperity, yet the neurocognitive principles underlying creative performance, and their development, are still poorly understood. To fill this void, we examined the neural correlates of divergent thinking in adults (25-30 yrs and adolescents (15-17 yrs. Participants generated alternative uses (AU or ordinary characteristics (OC for common objects while brain activity was assessed using fMRI. Adults outperformed adolescents on the number of solutions for AU and OC trials. Contrasting neural activity for AU with OC trials revealed increased recruitment of left angular gyrus, left supramarginal gyrus, and bilateral middle temporal gyrus in both adults and adolescents. When only trials with multiple alternative uses were included in the analysis, participants showed additional left inferior frontal gyrus (IFG/middle frontal gyrus (MFG activation for AU compared to OC trials. Correspondingly, individual difference analyses showed a positive correlation between activations for AU relative to OC trials in left IFG/MFG and divergent thinking performance and activations were more pronounced in adults than in adolescents. Taken together, the results of this study demonstrated that creative idea generation involves recruitment of mainly left lateralized parietal and temporal brain regions. Generating multiple creative ideas, a hallmark of divergent thinking, shows additional lateral PFC activation that is not yet optimized in adolescence.

  17. Obesity-related differences in neural correlates of force control.

    Science.gov (United States)

    Mehta, Ranjana K; Shortz, Ashley E

    2014-01-01

    Greater body segment mass due to obesity has shown to impair gross and fine motor functions and reduce balance control. While recent studies suggest that obesity may be linked with altered brain functions involved in fine motor tasks, this association is not well investigated. The purpose of this study was to examine the neural correlates of motor performance in non-obese and obese adults during force control of two upper extremity muscles. Nine non-obese and eight obese young adults performed intermittent handgrip and elbow flexion exertions at 30% of their respective muscle strengths for 4 min. Functional near infrared spectroscopy was employed to measure neural activity in the prefrontal cortex bilaterally, joint steadiness was computed using force fluctuations, and ratings of perceived exertions (RPEs) were obtained to assess perceived effort. Obesity was associated with higher force fluctuations and lower prefrontal cortex activation during handgrip exertions, while RPE scores remained similar across both groups. No obesity-related differences in neural activity, force fluctuation, or RPE scores were observed during elbow flexion exertions. The study is one of the first to examine obesity-related differences on prefrontal cortex activation during force control of the upper extremity musculature. The study findings indicate that the neural correlates of motor activity in the obese may be muscle-specific. Future work is warranted to extend the investigation to monitoring multiple motor-function related cortical regions and examining obesity differences with different task parameters (e.g., longer duration, increased precision demands, larger muscles, etc.).

  18. Neural Alterations in Acquired Age-Related Hearing Loss

    Directory of Open Access Journals (Sweden)

    Raksha Anand Mudar

    2016-06-01

    Full Text Available Hearing loss is one of the most prevalent chronic health conditions in older adults. Growing evidence suggests that hearing loss is associated with reduced cognitive functioning and incident dementia. In this mini-review, we briefly examine literature on anatomical and functional alterations in the brains of adults with acquired age-associated hearing loss, which may underlie the cognitive consequences observed in this population, focusing on studies that have used structural and functional magnetic resonance imaging, diffusion tensor imaging, and event-related electroencephalography. We discuss structural and functional alterations observed in the temporal and frontal cortices and the limbic system. These neural alterations are discussed in the context of common cause, information-degradation, and sensory-deprivation hypotheses, and we suggest possible rehabilitation strategies. Although we are beginning to learn more about changes in neural architecture and functionality related to age-associated hearing loss, much work remains to be done. Understanding the neural alterations will provide objective markers for early identification of neural consequences of age-associated hearing loss and for evaluating benefits of intervention approaches.

  19. Non-Viral Generation of Neural Precursor-like Cells from Adult Human Fibroblasts

    Directory of Open Access Journals (Sweden)

    Maucksch C

    2012-01-01

    Full Text Available Recent studies have reported direct reprogramming of human fibroblasts to mature neurons by the introduction of defined neural genes. This technology has potential use in the areas of neurological disease modeling and drug development. However, use of induced neurons for large-scale drug screening and cell-based replacement strategies is limited due to their inability to expand once reprogrammed. We propose it would be more desirable to induce expandable neural precursor cells directly from human fibroblasts. To date several pluripotent and neural transcription factors have been shown to be capable of converting mouse fibroblasts to neural stem/precursor-like cells when delivered by viral vectors. Here we extend these findings and demonstrate that transient ectopic insertion of the transcription factors SOX2 and PAX6 to adult human fibroblasts through use of non-viral plasmid transfection or protein transduction allows the generation of induced neural precursor (iNP colonies expressing a range of neural stem and pro-neural genes. Upon differentiation, iNP cells give rise to neurons exhibiting typical neuronal morphologies and expressing multiple neuronal markers including tyrosine hydroxylase and GAD65/67. Importantly, iNP-derived neurons demonstrate electrophysiological properties of functionally mature neurons with the capacity to generate action potentials. In addition, iNP cells are capable of differentiating into glial fibrillary acidic protein (GFAP-expressing astrocytes. This study represents a novel virus-free approach for direct reprogramming of human fibroblasts to a neural precursor fate.

  20. Generative Inferences Based on Learned Relations

    Science.gov (United States)

    Chen, Dawn; Lu, Hongjing; Holyoak, Keith J.

    2017-01-01

    A key property of relational representations is their "generativity": From partial descriptions of relations between entities, additional inferences can be drawn about other entities. A major theoretical challenge is to demonstrate how the capacity to make generative inferences could arise as a result of learning relations from…

  1. Neural responses to feedback information produced by self-generated or other-generated decision-making and their impairment in schizophrenia.

    Directory of Open Access Journals (Sweden)

    Atsuhito Toyomaki

    Full Text Available Several studies of self-monitoring dysfunction in schizophrenia have focused on the sense of agency to motor action using behavioral and psychophysiological techniques. So far, no study has ever tried to investigate whether the sense of agency or causal attribution for external events produced by self-generated decision-making is abnormal in schizophrenia. The purpose of this study was to investigate neural responses to feedback information produced by self-generated or other-generated decision-making in a multiplayer gambling task using even-related potentials and electroencephalogram synchronization. We found that the late positive component and theta/alpha synchronization were increased in response to feedback information in the self-decision condition in normal controls, but that these responses were significantly decreased in patients with schizophrenia. These neural activities thus reflect the self-reference effect that affects the cognitive appraisal of external events following decision-making and their impairment in schizophrenia.

  2. Neural responses to feedback information produced by self-generated or other-generated decision-making and their impairment in schizophrenia.

    Science.gov (United States)

    Toyomaki, Atsuhito; Hashimoto, Naoki; Kako, Yuki; Murohashi, Harumitsu; Kusumi, Ichiro

    2017-01-01

    Several studies of self-monitoring dysfunction in schizophrenia have focused on the sense of agency to motor action using behavioral and psychophysiological techniques. So far, no study has ever tried to investigate whether the sense of agency or causal attribution for external events produced by self-generated decision-making is abnormal in schizophrenia. The purpose of this study was to investigate neural responses to feedback information produced by self-generated or other-generated decision-making in a multiplayer gambling task using even-related potentials and electroencephalogram synchronization. We found that the late positive component and theta/alpha synchronization were increased in response to feedback information in the self-decision condition in normal controls, but that these responses were significantly decreased in patients with schizophrenia. These neural activities thus reflect the self-reference effect that affects the cognitive appraisal of external events following decision-making and their impairment in schizophrenia.

  3. ANNarchy: a code generation approach to neural simulations on parallel hardware

    Science.gov (United States)

    Vitay, Julien; Dinkelbach, Helge Ü.; Hamker, Fred H.

    2015-01-01

    Many modern neural simulators focus on the simulation of networks of spiking neurons on parallel hardware. Another important framework in computational neuroscience, rate-coded neural networks, is mostly difficult or impossible to implement using these simulators. We present here the ANNarchy (Artificial Neural Networks architect) neural simulator, which allows to easily define and simulate rate-coded and spiking networks, as well as combinations of both. The interface in Python has been designed to be close to the PyNN interface, while the definition of neuron and synapse models can be specified using an equation-oriented mathematical description similar to the Brian neural simulator. This information is used to generate C++ code that will efficiently perform the simulation on the chosen parallel hardware (multi-core system or graphical processing unit). Several numerical methods are available to transform ordinary differential equations into an efficient C++code. We compare the parallel performance of the simulator to existing solutions. PMID:26283957

  4. Relationship between neural rhythm generation disorders and physical disabilities in Parkinson's disease patients' walking.

    Science.gov (United States)

    Ota, Leo; Uchitomi, Hirotaka; Ogawa, Ken-ichiro; Orimo, Satoshi; Miyake, Yoshihiro

    2014-01-01

    Walking is generated by the interaction between neural rhythmic and physical activities. In fact, Parkinson's disease (PD), which is an example of disease, causes not only neural rhythm generation disorders but also physical disabilities. However, the relationship between neural rhythm generation disorders and physical disabilities has not been determined. The aim of this study was to identify the mechanism of gait rhythm generation. In former research, neural rhythm generation disorders in PD patients' walking were characterized by stride intervals, which are more variable and fluctuate randomly. The variability and fluctuation property were quantified using the coefficient of variation (CV) and scaling exponent α. Conversely, because walking is a dynamic process, postural reflex disorder (PRD) is considered the best way to estimate physical disabilities in walking. Therefore, we classified the severity of PRD using CV and α. Specifically, PD patients and healthy elderly were classified into three groups: no-PRD, mild-PRD, and obvious-PRD. We compared the contributions of CV and α to the accuracy of this classification. In this study, 45 PD patients and 17 healthy elderly people walked 200 m. The severity of PRD was determined using the modified Hoehn-Yahr scale (mH-Y). People with mH-Y scores of 2.5 and 3 had mild-PRD and obvious-PRD, respectively. As a result, CV differentiated no-PRD from PRD, indicating the correlation between CV and PRD. Considering that PRD is independent of neural rhythm generation, this result suggests the existence of feedback process from physical activities to neural rhythmic activities. Moreover, α differentiated obvious-PRD from mild-PRD. Considering α reflects the intensity of interaction between factors, this result suggests the change of the interaction. Therefore, the interaction between neural rhythmic and physical activities is thought to plays an important role for gait rhythm generation. These characteristics have

  5. Classifying medical relations in clinical text via convolutional neural networks.

    Science.gov (United States)

    He, Bin; Guan, Yi; Dai, Rui

    2018-05-16

    Deep learning research on relation classification has achieved solid performance in the general domain. This study proposes a convolutional neural network (CNN) architecture with a multi-pooling operation for medical relation classification on clinical records and explores a loss function with a category-level constraint matrix. Experiments using the 2010 i2b2/VA relation corpus demonstrate these models, which do not depend on any external features, outperform previous single-model methods and our best model is competitive with the existing ensemble-based method. Copyright © 2018. Published by Elsevier B.V.

  6. Dynamic Neural Processing of Linguistic Cues Related to Death

    Science.gov (United States)

    Ma, Yina; Qin, Jungang; Han, Shihui

    2013-01-01

    Behavioral studies suggest that humans evolve the capacity to cope with anxiety induced by the awareness of death’s inevitability. However, the neurocognitive processes that underlie online death-related thoughts remain unclear. Our recent functional MRI study found that the processing of linguistic cues related to death was characterized by decreased neural activity in human insular cortex. The current study further investigated the time course of neural processing of death-related linguistic cues. We recorded event-related potentials (ERP) to death-related, life-related, negative-valence, and neutral-valence words in a modified Stroop task that required color naming of words. We found that the amplitude of an early frontal/central negativity at 84–120 ms (N1) decreased to death-related words but increased to life-related words relative to neutral-valence words. The N1 effect associated with death-related and life-related words was correlated respectively with individuals’ pessimistic and optimistic attitudes toward life. Death-related words also increased the amplitude of a frontal/central positivity at 124–300 ms (P2) and of a frontal/central positivity at 300–500 ms (P3). However, the P2 and P3 modulations were observed for both death-related and negative-valence words but not for life-related words. The ERP results suggest an early inverse coding of linguistic cues related to life and death, which is followed by negative emotional responses to death-related information. PMID:23840787

  7. Disorder generated by interacting neural networks: application to econophysics and cryptography

    International Nuclear Information System (INIS)

    Kinzel, Wolfgang; Kanter, Ido

    2003-01-01

    When neural networks are trained on their own output signals they generate disordered time series. In particular, when two neural networks are trained on their mutual output they can synchronize; they relax to a time-dependent state with identical synaptic weights. Two applications of this phenomenon are discussed for (a) econophysics and (b) cryptography. (a) When agents competing in a closed market (minority game) are using neural networks to make their decisions, the total system relaxes to a state of good performance. (b) Two partners communicating over a public channel can find a common secret key

  8. Application of clustering analysis in the prediction of photovoltaic power generation based on neural network

    Science.gov (United States)

    Cheng, K.; Guo, L. M.; Wang, Y. K.; Zafar, M. T.

    2017-11-01

    In order to select effective samples in the large number of data of PV power generation years and improve the accuracy of PV power generation forecasting model, this paper studies the application of clustering analysis in this field and establishes forecasting model based on neural network. Based on three different types of weather on sunny, cloudy and rainy days, this research screens samples of historical data by the clustering analysis method. After screening, it establishes BP neural network prediction models using screened data as training data. Then, compare the six types of photovoltaic power generation prediction models before and after the data screening. Results show that the prediction model combining with clustering analysis and BP neural networks is an effective method to improve the precision of photovoltaic power generation.

  9. The Effect of Training Data Set Composition on the Performance of a Neural Image Caption Generator

    Science.gov (United States)

    2017-09-01

    REPORT TYPE Technical Report 3. DATES COVERED (From - To) 4. TITLE AND SUBTITLE The Effect of Training Data Set Composition on the Performance of a...ARL-TR-8124 ● SEP 2017 US Army Research Laboratory The Effect of Training Data Set Composition on the Performance of a Neural...Laboratory The Effect of Training Data Set Composition on the Performance of a Neural Image Caption Generator by Abigail Wilson Montgomery Blair

  10. ORGANIC ELECTRODE COATINGS FOR NEXT-GENERATION NEURAL INTERFACES

    Directory of Open Access Journals (Sweden)

    Ulises A Aregueta-Robles

    2014-05-01

    Full Text Available Traditional neuronal interfaces utilize metallic electrodes which in recent years have reached a plateau in terms of the ability to provide safe stimulation at high resolution or rather with high densities of microelectrodes with improved spatial selectivity. To achieve higher resolution it has become clear that reducing the size of electrodes is required to enable higher electrode counts from the implant device. The limitations of interfacing electrodes including low charge injection limits, mechanical mismatch and foreign body response can be addressed through the use of organic electrode coatings which typically provide a softer, more roughened surface to enable both improved charge transfer and lower mechanical mismatch with neural tissue. Coating electrodes with conductive polymers or carbon nanotubes offers a substantial increase in charge transfer area compared to conventional platinum electrodes. These organic conductors provide safe electrical stimulation of tissue while avoiding undesirable chemical reactions and cell damage. However, the mechanical properties of conductive polymers are not ideal, as they are quite brittle. Hydrogel polymers present a versatile coating option for electrodes as they can be chemically modified to provide a soft and conductive scaffold. However, the in vivo chronic inflammatory response of these conductive hydrogels remains unknown. A more recent approach proposes tissue engineering the electrode interface through the use of encapsulated neurons within hydrogel coatings. This approach may provide a method for activating tissue at the cellular scale, however several technological challenges must be addressed to demonstrate feasibility of this innovative idea. The review focuses on the various organic coatings which have been investigated to improve neural interface electrodes.

  11. Generation of artificial accelerograms using neural networks for data of Iran

    International Nuclear Information System (INIS)

    Bargi, Kh.; Loux, C.; Rohani, H.

    2002-01-01

    A new method for generation of artificial earthquake accelerograms from response spectra is proposed by Ghaboussi and Lin in 1997 using neural networks. In this paper the methodology has been extended and enhanced for data of Iran. For this purpose, first 40 records of Iran acceleration is chosen, then an RBF neural network which called generalized regression neural network learn the inverse mapping directly from the response spectrum to the Discrete Cosine Transform of accelerograms. Discrete Cosine Transform has been used as an assisting device to extract the content of frequency domain. Learning of network is reasonable and a generalized regression neural network learns it in a few second. Outputs are presented to demonstrate the performance of this method and show its capabilities

  12. Estimates of hydroelectric generation using neural networks with the artificial bee colony algorithm for Turkey

    International Nuclear Information System (INIS)

    Uzlu, Ergun; Akpınar, Adem; Özturk, Hasan Tahsin; Nacar, Sinan; Kankal, Murat

    2014-01-01

    The primary objective of this study was to apply the ANN (artificial neural network) model with the ABC (artificial bee colony) algorithm to estimate annual hydraulic energy production of Turkey. GEED (gross electricity energy demand), population, AYT (average yearly temperature), and energy consumption were selected as independent variables in the model. The first part of the study compared ANN-ABC model performance with results of classical ANN models trained with the BP (back propagation) algorithm. Mean square and relative error were applied to evaluate model accuracy. The test set errors emphasized positive differences between the ANN-ABC and classical ANN models. After determining optimal configurations, three different scenarios were developed to predict future hydropower generation values for Turkey. Results showed the ANN-ABC method predicted hydroelectric generation better than the classical ANN trained with the BP algorithm. Furthermore, results indicated future hydroelectric generation in Turkey will range from 69.1 to 76.5 TWh in 2021, and the total annual electricity demand represented by hydropower supply rates will range from 14.8% to 18.0%. However, according to Vision 2023 agenda goals, the country plans to produce 30% of its electricity demand from renewable energy sources by 2023, and use 20% less energy than in 2010. This percentage renewable energy provision cannot be accomplished unless changes in energy policy and investments are not addressed and implemented. In order to achieve this goal, the Turkish government must reconsider and raise its own investments in hydropower, wind, solar, and geothermal energy, particularly hydropower. - Highlights: • This study is associated with predicting hydropower generation in Turkey. • Sensitivity analysis was performed to determine predictor variables. • GEED, population, energy consumption and AYT were used as predictor variables. • ANN-ABC predicted the hydropower generation more accurately

  13. Generation and prediction of time series by a neural network

    International Nuclear Information System (INIS)

    Eisenstein, E.; Kanter, I.; Kessler, D.A.; Kinzel, W.

    1995-01-01

    Generation and prediction of time series are analyzed for the case of a bit generator: a perceptron where in each time step the input units are shifted one bit to the right with the state of the leftmost input unit set equal to the output unit in the previous time step. The long-time dynamical behavior of the bit generator consists of cycles whose typical period scales polynomially with the size of the network and whose spatial structure is periodic with a typical finite wavelength. The generalization error on a cycle is zero for a finite training set, and global dynamical behaviors can also be learned in a finite time. Hence, a projection of a rule can be learned in a finite time

  14. A neural model of rule generation in inductive reasoning.

    Science.gov (United States)

    Rasmussen, Daniel; Eliasmith, Chris

    2011-01-01

    Inductive reasoning is a fundamental and complex aspect of human intelligence. In particular, how do subjects, given a set of particular examples, generate general descriptions of the rules governing that set? We present a biologically plausible method for accomplishing this task and implement it in a spiking neuron model. We demonstrate the success of this model by applying it to the problem domain of Raven's Progressive Matrices, a widely used tool in the field of intelligence testing. The model is able to generate the rules necessary to correctly solve Raven's items, as well as recreate many of the experimental effects observed in human subjects. Copyright © 2011 Cognitive Science Society, Inc.

  15. Neural correlates related to action observation in expert archers.

    Science.gov (United States)

    Kim, Yang-Tae; Seo, Jee-Hye; Song, Hui-Jin; Yoo, Done-Sik; Lee, Hui Joong; Lee, Jongmin; Lee, Gunyoung; Kwon, Eunjin; Kim, Jin Goo; Chang, Yongmin

    2011-10-01

    A growing body of evidence suggests that activity of the mirror neuron system is dependent on the observer's motor experience of a given action. It remains unclear, however, whether activity of the mirror neuron system is also associated with the observer's motor experience in sports game. Therefore, the aim of the present study is to investigate differences in activation of the mirror neuron system during action observation between experts and non-archer control subjects. We used video of Western-style archery in which participants were asked to watch the archery movements. Hyperactivation of the premotor and inferior parietal cortex in expert archers relative to non-archer control subjects suggests that the human mirror neuron system could contain and expand representations of the motor repertoire. The fact that dorsomedial prefrontal cortex was more active in expert archers than in non-archer control subjects indicates a spontaneous engagement of theory of mind in experts when watching video of Western-style archery. Compared with the non-archer control subjects, expert archers showed greater activation in the neural system in regions associated with episodic recall from familiar and meaningful information, including the cingulate cortex, retrosplenial cortex, and parahippocampal gyrus. The results demonstrate that expertise effects stimulate brain activity not only in the mirror neuron system but also in the neural networks related to theory of mind and episodic memory. Copyright © 2011 Elsevier B.V. All rights reserved.

  16. Learning Orthographic Structure with Sequential Generative Neural Networks

    Science.gov (United States)

    Testolin, Alberto; Stoianov, Ivilin; Sperduti, Alessandro; Zorzi, Marco

    2016-01-01

    Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in…

  17. Neural net based determination of generator-shedding requirements in electric power systems

    Energy Technology Data Exchange (ETDEWEB)

    Djukanovic, M [Electrical Engineering Inst. ' Nikola Tesla' , Belgrade (Yugoslavia); Sobajic, D J; Pao, Y -H [Case Western Reserve Univ., Cleveland, OH (United States). Dept. of Electrical Engineering and Applied Physics Case Western Reserve Univ., Cleveland, OH (United States). Dept. of Computer Engineering and Science AI WARE Inc., Cleveland, OH (United States)

    1992-09-01

    This paper presents an application of artificial neural networks (ANN) in support of a decision-making process by power system operators directed towards the fast stabilisation of multi-machine systems. The proposed approach considers generator shedding as the most effective discrete supplementary control for improving the dynamic performance of faulted power systems and preventing instabilities. The sensitivity of the transient energy function (TEF) with respect to changes in the amount of dropped generation is used during the training phase of ANNs to assess the critical amount of generator shedding required to prevent the loss of synchronism. The learning capabilities of neural nets are used to establish complex mappings between fault information and the amount of generation to be shed, suggesting it as the control signal to the power system operator. (author)

  18. Generation of daily solar irradiation by means of artificial neural net works

    Energy Technology Data Exchange (ETDEWEB)

    Siqueira, Adalberto N.; Tiba, Chigueru; Fraidenraich, Naum [Departamento de Energia Nuclear, da Universidade Federal de Pernambuco, Av. Prof. Luiz Freire, 1000 - CDU, CEP 50.740-540 Recife, Pernambuco (Brazil)

    2010-11-15

    The present study proposes the utilization of Artificial Neural Networks (ANN) as an alternative for generating synthetic series of daily solar irradiation. The sequences were generated from the use of daily temporal series of a group of meteorological variables that were measured simultaneously. The data used were measured between the years of 1998 and 2006 in two temperate climate localities of Brazil, Ilha Solteira (Sao Paulo) and Pelotas (Rio Grande do Sul). The estimates were taken for the months of January, April, July and October, through two models which are distinguished regarding the use or nonuse of measured bright sunshine hours as an input variable. An evaluation of the performance of the 56 months of solar irradiation generated by way of ANN showed that by using the measured bright sunshine hours as an input variable (model 1), the RMSE obtained were less or equal to 23.2% being that of those, although 43 of those months presented RMSE less or equal to 12.3%. In the case of the model that did not use the measured bright sunshine hours but used a daylight length (model 2), RMSE were obtained that varied from 8.5% to 37.5%, although 38 of those months presented RMSE less or equal to 20.0%. A comparison of the monthly series for all of the years, achieved by means of the Kolmogorov-Smirnov test (to a confidence level of 99%), demonstrated that of the 16 series generated by ANN model only two, obtained by model 2 for the months of April and July in Pelotas, presented significant difference in relation to the distributions of the measured series and that all mean deviations obtained were inferior to 0.39 MJ/m{sup 2}. It was also verified that the two ANN models were able to reproduce the principal statistical characteristics of the frequency distributions of the measured series such as: mean, mode, asymmetry and Kurtosis. (author)

  19. Generation of Neural Progenitor Spheres from Human Pluripotent Stem Cells in a Suspension Bioreactor.

    Science.gov (United States)

    Yan, Yuanwei; Song, Liqing; Tsai, Ang-Chen; Ma, Teng; Li, Yan

    2016-01-01

    Conventional two-dimensional (2-D) culture systems cannot provide large numbers of human pluripotent stem cells (hPSCs) and their derivatives that are demanded for commercial and clinical applications in in vitro drug screening, disease modeling, and potentially cell therapy. The technologies that support three-dimensional (3-D) suspension culture, such as a stirred bioreactor, are generally considered as promising approaches to produce the required cells. Recently, suspension bioreactors have also been used to generate mini-brain-like structure from hPSCs for disease modeling, showing the important role of bioreactor in stem cell culture. This chapter describes a detailed culture protocol for neural commitment of hPSCs into neural progenitor cell (NPC) spheres using a spinner bioreactor. The basic steps to prepare hPSCs for bioreactor inoculation are illustrated from cell thawing to cell propagation. The method for generating NPCs from hPSCs in the spinner bioreactor along with the static control is then described. The protocol in this study can be applied to the generation of NPCs from hPSCs for further neural subtype specification, 3-D neural tissue development, or potential preclinical studies or clinical applications in neurological diseases.

  20. Embodied learning of a generative neural model for biological motion perception and inference.

    Science.gov (United States)

    Schrodt, Fabian; Layher, Georg; Neumann, Heiko; Butz, Martin V

    2015-01-01

    Although an action observation network and mirror neurons for understanding the actions and intentions of others have been under deep, interdisciplinary consideration over recent years, it remains largely unknown how the brain manages to map visually perceived biological motion of others onto its own motor system. This paper shows how such a mapping may be established, even if the biologically motion is visually perceived from a new vantage point. We introduce a learning artificial neural network model and evaluate it on full body motion tracking recordings. The model implements an embodied, predictive inference approach. It first learns to correlate and segment multimodal sensory streams of own bodily motion. In doing so, it becomes able to anticipate motion progression, to complete missing modal information, and to self-generate learned motion sequences. When biological motion of another person is observed, this self-knowledge is utilized to recognize similar motion patterns and predict their progress. Due to the relative encodings, the model shows strong robustness in recognition despite observing rather large varieties of body morphology and posture dynamics. By additionally equipping the model with the capability to rotate its visual frame of reference, it is able to deduce the visual perspective onto the observed person, establishing full consistency to the embodied self-motion encodings by means of active inference. In further support of its neuro-cognitive plausibility, we also model typical bistable perceptions when crucial depth information is missing. In sum, the introduced neural model proposes a solution to the problem of how the human brain may establish correspondence between observed bodily motion and its own motor system, thus offering a mechanism that supports the development of mirror neurons.

  1. Embodied Learning of a Generative Neural Model for Biological Motion Perception and Inference

    Directory of Open Access Journals (Sweden)

    Fabian eSchrodt

    2015-07-01

    Full Text Available Although an action observation network and mirror neurons for understanding the actions and intentions of others have been under deep, interdisciplinary consideration over recent years, it remains largely unknown how the brain manages to map visually perceived biological motion of others onto its own motor system. This paper shows how such a mapping may be established, even if the biologically motion is visually perceived from a new vantage point. We introduce a learning artificial neural network model and evaluate it on full body motion tracking recordings. The model implements an embodied, predictive inference approach. It first learns to correlate and segment multimodal sensory streams of own bodily motion. In doing so, it becomes able to anticipate motion progression, to complete missing modal information, and to self-generate learned motion sequences. When biological motion of another person is observed, this self-knowledge is utilized to recognize similar motion patterns and predict their progress. Due to the relative encodings, the model shows strong robustness in recognition despite observing rather large varieties of body morphology and posture dynamics. By additionally equipping the model with the capability to rotate its visual frame of reference, it is able to deduce the visual perspective onto the observed person, establishing full consistency to the embodied self-motion encodings by means of active inference. In further support of its neuro-cognitive plausibility, we also model typical bistable perceptions when crucial depth information is missing. In sum, the introduced neural model proposes a solution to the problem of how the human brain may establish correspondence between observed bodily motion and its own motor system, thus offering a mechanism that supports the development of mirror neurons.

  2. Modulation of Hippocampal Neural Plasticity by Glucose-Related Signaling

    Directory of Open Access Journals (Sweden)

    Marco Mainardi

    2015-01-01

    Full Text Available Hormones and peptides involved in glucose homeostasis are emerging as important modulators of neural plasticity. In this regard, increasing evidence shows that molecules such as insulin, insulin-like growth factor-I, glucagon-like peptide-1, and ghrelin impact on the function of the hippocampus, which is a key area for learning and memory. Indeed, all these factors affect fundamental hippocampal properties including synaptic plasticity (i.e., synapse potentiation and depression, structural plasticity (i.e., dynamics of dendritic spines, and adult neurogenesis, thus leading to modifications in cognitive performance. Here, we review the main mechanisms underlying the effects of glucose metabolism on hippocampal physiology. In particular, we discuss the role of these signals in the modulation of cognitive functions and their potential implications in dysmetabolism-related cognitive decline.

  3. Generation and properties of a new human ventral mesencephalic neural stem cell line

    DEFF Research Database (Denmark)

    Villa, Ana; Liste, Isabel; Courtois, Elise T

    2009-01-01

    . Here we report the generation of a new stable cell line of human neural stem cells derived from ventral mesencephalon (hVM1) based on v-myc immortalization. The cells expressed neural stem cell and radial glia markers like nestin, vimentin and 3CB2 under proliferation conditions. After withdrawal......Neural stem cells (NSCs) are powerful research tools for the design and discovery of new approaches to cell therapy in neurodegenerative diseases like Parkinson's disease. Several epigenetic and genetic strategies have been tested for long-term maintenance and expansion of these cells in vitro...... derivatives may constitute good candidates for the study of development and physiology of human dopaminergic neurons in vitro, and to develop tools for Parkinson's disease cell replacement preclinical research and drug testing....

  4. Social power and approach-related neural activity.

    Science.gov (United States)

    Boksem, Maarten A S; Smolders, Ruud; De Cremer, David

    2012-06-01

    It has been argued that power activates a general tendency to approach whereas powerlessness activates a tendency to inhibit. The assumption is that elevated power involves reward-rich environments, freedom and, as a consequence, triggers an approach-related motivational orientation and attention to rewards. In contrast, reduced power is associated with increased threat, punishment and social constraint and thereby activates inhibition-related motivation. Moreover, approach motivation has been found to be associated with increased relative left-sided frontal brain activity, while withdrawal motivation has been associated with increased right sided activations. We measured EEG activity while subjects engaged in a task priming either high or low social power. Results show that high social power is indeed associated with greater left-frontal brain activity compared to low social power, providing the first neural evidence for the theory that high power is associated with approach-related motivation. We propose a framework accounting for differences in both approach motivation and goal-directed behaviour associated with different levels of power.

  5. Empathy and Stress Related Neural Responses in Maternal Decision Making

    Directory of Open Access Journals (Sweden)

    S. Shaun Ho

    2014-06-01

    Full Text Available Mothers need to make caregiving decisions to meet the needs of children, which may or may not result in positive child feedback. Variations in caregivers’ emotional reactivity to unpleasant child-feedback may be partially explained by their dispositional empathy levels. Furthermore, empathic response to the child’s unpleasant feedback likely helps mothers to regulate their own stress. We investigated the relationship between maternal dispositional empathy, stress reactivity, and neural correlates of child feedback to caregiving decisions. In Part 1 of the study, 33 female participants were recruited to undergo a lab-based mild stressor, the Social Evaluation Test (SET, and then in Part 2 of the study, a subset of the participants, fourteen mothers, performed a Parenting Decision Making Task (PDMT in an fMRI setting. Four dimensions of dispositional empathy based on the Interpersonal Reactivity Index were measured in all participants – Personal Distress, Empathic Concern, Perspective Taking, and Fantasy. Overall, we found that the Personal Distress and Perspective Taking were associated with greater and lesser cortisol reactivity, respectively. The four types of empathy were distinctly associated with the negative (versus positive child feedback activation in the brain. Personal Distress was associated with amygdala and hypothalamus activation, Empathic Concern with the left ventral striatum, ventrolateral prefrontal cortex (VLPFC, and supplemental motor area (SMA activation, and Fantasy with the septal area, right SMA and VLPFC activation. Interestingly, hypothalamus-septal coupling during the negative feedback condition was associated with less PDMT-related cortisol reactivity. The roles of distinct forms of dispositional empathy in neural and stress responses are discussed.

  6. Research of PV Power Generation MPPT based on GABP Neural Network

    Science.gov (United States)

    Su, Yu; Lin, Xianfu

    2018-05-01

    Photovoltaic power generation has become the main research direction of new energy power generation. But high investment and low efficiency of photovoltaic industry arouse concern in some extent. So maximum power point tracking of photovoltaic power generation has been a popular study point. Due to slow response, oscillation at maximum power point and low precision, the algorithm based on genetic algorithm combined with BP neural network are designed detailedly in this paper. And the modeling and simulation are completed by use of MATLAB/SIMULINK. The results show that the algorithm is effective and the maximum power point can be tracked accurately and quickly.

  7. Toward Rigorous Parameterization of Underconstrained Neural Network Models Through Interactive Visualization and Steering of Connectivity Generation

    Directory of Open Access Journals (Sweden)

    Christian Nowke

    2018-06-01

    Full Text Available Simulation models in many scientific fields can have non-unique solutions or unique solutions which can be difficult to find. Moreover, in evolving systems, unique final state solutions can be reached by multiple different trajectories. Neuroscience is no exception. Often, neural network models are subject to parameter fitting to obtain desirable output comparable to experimental data. Parameter fitting without sufficient constraints and a systematic exploration of the possible solution space can lead to conclusions valid only around local minima or around non-minima. To address this issue, we have developed an interactive tool for visualizing and steering parameters in neural network simulation models. In this work, we focus particularly on connectivity generation, since finding suitable connectivity configurations for neural network models constitutes a complex parameter search scenario. The development of the tool has been guided by several use cases—the tool allows researchers to steer the parameters of the connectivity generation during the simulation, thus quickly growing networks composed of multiple populations with a targeted mean activity. The flexibility of the software allows scientists to explore other connectivity and neuron variables apart from the ones presented as use cases. With this tool, we enable an interactive exploration of parameter spaces and a better understanding of neural network models and grapple with the crucial problem of non-unique network solutions and trajectories. In addition, we observe a reduction in turn around times for the assessment of these models, due to interactive visualization while the simulation is computed.

  8. Reconstruction of three-dimensional porous media using generative adversarial neural networks

    Science.gov (United States)

    Mosser, Lukas; Dubrule, Olivier; Blunt, Martin J.

    2017-10-01

    To evaluate the variability of multiphase flow properties of porous media at the pore scale, it is necessary to acquire a number of representative samples of the void-solid structure. While modern x-ray computer tomography has made it possible to extract three-dimensional images of the pore space, assessment of the variability in the inherent material properties is often experimentally not feasible. We present a method to reconstruct the solid-void structure of porous media by applying a generative neural network that allows an implicit description of the probability distribution represented by three-dimensional image data sets. We show, by using an adversarial learning approach for neural networks, that this method of unsupervised learning is able to generate representative samples of porous media that honor their statistics. We successfully compare measures of pore morphology, such as the Euler characteristic, two-point statistics, and directional single-phase permeability of synthetic realizations with the calculated properties of a bead pack, Berea sandstone, and Ketton limestone. Results show that generative adversarial networks can be used to reconstruct high-resolution three-dimensional images of porous media at different scales that are representative of the morphology of the images used to train the neural network. The fully convolutional nature of the trained neural network allows the generation of large samples while maintaining computational efficiency. Compared to classical stochastic methods of image reconstruction, the implicit representation of the learned data distribution can be stored and reused to generate multiple realizations of the pore structure very rapidly.

  9. Efficient and Rapid Derivation of Primitive Neural Stem Cells and Generation of Brain Subtype Neurons From Human Pluripotent Stem Cells

    OpenAIRE

    Yan, Yiping; Shin, Soojung; Jha, Balendu Shekhar; Liu, Qiuyue; Sheng, Jianting; Li, Fuhai; Zhan, Ming; Davis, Janine; Bharti, Kapil; Zeng, Xianmin; Rao, Mahendra; Malik, Nasir; Vemuri, Mohan C.

    2013-01-01

    This study developed a highly efficient serum-free pluripotent stem cell (PSC) neural induction medium that can induce human PSCs into primitive neural stem cells (NSCs) in 7 days, obviating the need for time-consuming, laborious embryoid body generation or rosette picking. This method of primitive NSC derivation sets the stage for the scalable production of clinically relevant neural cells for cell therapy applications in good manufacturing practice conditions.

  10. Training algorithms evaluation for artificial neural network to temporal prediction of photovoltaic generation

    International Nuclear Information System (INIS)

    Arantes Monteiro, Raul Vitor; Caixeta Guimarães, Geraldo; Rocio Castillo, Madeleine; Matheus Moura, Fabrício Augusto; Tamashiro, Márcio Augusto

    2016-01-01

    Current energy policies are encouraging the connection of power generation based on low-polluting technologies, mainly those using renewable sources, to distribution networks. Hence, it becomes increasingly important to understand technical challenges, facing high penetration of PV systems at the grid, especially considering the effects of intermittence of this source on the power quality, reliability and stability of the electric distribution system. This fact can affect the distribution networks on which they are attached causing overvoltage, undervoltage and frequency oscillations. In order to predict these disturbs, artificial neural networks are used. This article aims to analyze 3 training algorithms used in artificial neural networks for temporal prediction of the generated active power thru photovoltaic panels. As a result it was concluded that the algorithm with the best performance among the 3 analyzed was the Levenberg-Marquadrt.

  11. Neural networks for the generation of sea bed models using airborne lidar bathymetry data

    Science.gov (United States)

    Kogut, Tomasz; Niemeyer, Joachim; Bujakiewicz, Aleksandra

    2016-06-01

    Various sectors of the economy such as transport and renewable energy have shown great interest in sea bed models. The required measurements are usually carried out by ship-based echo sounding, but this method is quite expensive. A relatively new alternative is data obtained by airborne lidar bathymetry. This study investigates the accuracy of these data, which was obtained in the context of the project `Investigation on the use of airborne laser bathymetry in hydrographic surveying'. A comparison to multi-beam echo sounding data shows only small differences in the depths values of the data sets. The IHO requirements of the total horizontal and vertical uncertainty for laser data are met. The second goal of this paper is to compare three spatial interpolation methods, namely Inverse Distance Weighting (IDW), Delaunay Triangulation (TIN), and supervised Artificial Neural Networks (ANN), for the generation of sea bed models. The focus of our investigation is on the amount of required sampling points. This is analyzed by manually reducing the data sets. We found that the three techniques have a similar performance almost independently of the amount of sampling data in our test area. However, ANN are more stable when using a very small subset of points.

  12. Neural networks for the generation of sea bed models using airborne lidar bathymetry data

    Directory of Open Access Journals (Sweden)

    Kogut Tomasz

    2016-06-01

    Full Text Available Various sectors of the economy such as transport and renewable energy have shown great interest in sea bed models. The required measurements are usually carried out by ship-based echo sounding, but this method is quite expensive. A relatively new alternative is data obtained by airborne lidar bathymetry. This study investigates the accuracy of these data, which was obtained in the context of the project ‘Investigation on the use of airborne laser bathymetry in hydrographic surveying’. A comparison to multi-beam echo sounding data shows only small differences in the depths values of the data sets. The IHO requirements of the total horizontal and vertical uncertainty for laser data are met. The second goal of this paper is to compare three spatial interpolation methods, namely Inverse Distance Weighting (IDW, Delaunay Triangulation (TIN, and supervised Artificial Neural Networks (ANN, for the generation of sea bed models. The focus of our investigation is on the amount of required sampling points. This is analyzed by manually reducing the data sets. We found that the three techniques have a similar performance almost independently of the amount of sampling data in our test area. However, ANN are more stable when using a very small subset of points.

  13. Routes to the past: Neural substrates of direct and generative autobiographical memory retrieval

    OpenAIRE

    Addis, Donna Rose; Knapp, Katie; Roberts, Reece P.; Schacter, Daniel L.

    2011-01-01

    Models of autobiographical memory propose two routes to retrieval depending on cue specificity. When available cues are specific and personally-relevant, a memory can be directly accessed. However, when available cues are generic, one must engage a generative retrieval process to produce more specific cues to successfully access a relevant memory. The current study sought to characterize the neural bases of these retrieval processes. During functional magnetic resonance imaging (fMRI), partic...

  14. Multivariate synthetic streamflow generation using a hybrid model based on artificial neural networks

    Directory of Open Access Journals (Sweden)

    J. C. Ochoa-Rivera

    2002-01-01

    Full Text Available A model for multivariate streamflow generation is presented, based on a multilayer feedforward neural network. The structure of the model results from two components, the neural network (NN deterministic component and a random component which is assumed to be normally distributed. It is from this second component that the model achieves the ability to incorporate effectively the uncertainty associated with hydrological processes, making it valuable as a practical tool for synthetic generation of streamflow series. The NN topology and the corresponding analytical explicit formulation of the model are described in detail. The model is calibrated with a series of monthly inflows to two reservoir sites located in the Tagus River basin (Spain, while validation is performed through estimation of a set of statistics that is relevant for water resources systems planning and management. Among others, drought and storage statistics are computed and compared for both the synthetic and historical series. The performance of the NN-based model was compared to that of a standard autoregressive AR(2 model. Results show that NN represents a promising modelling alternative for simulation purposes, with interesting potential in the context of water resources systems management and optimisation. Keywords: neural networks, perceptron multilayer, error backpropagation, hydrological scenario generation, multivariate time-series..

  15. Routes to the past: neural substrates of direct and generative autobiographical memory retrieval.

    Science.gov (United States)

    Addis, Donna Rose; Knapp, Katie; Roberts, Reece P; Schacter, Daniel L

    2012-02-01

    Models of autobiographical memory propose two routes to retrieval depending on cue specificity. When available cues are specific and personally-relevant, a memory can be directly accessed. However, when available cues are generic, one must engage a generative retrieval process to produce more specific cues to successfully access a relevant memory. The current study sought to characterize the neural bases of these retrieval processes. During functional magnetic resonance imaging (fMRI), participants were shown personally-relevant cues to elicit direct retrieval, or generic cues (nouns) to elicit generative retrieval. We used spatiotemporal partial least squares to characterize the spatial and temporal characteristics of the networks associated with direct and generative retrieval. Both retrieval tasks engaged regions comprising the autobiographical retrieval network, including hippocampus, and medial prefrontal and parietal cortices. However, some key neural differences emerged. Generative retrieval differentially recruited lateral prefrontal and temporal regions early on during the retrieval process, likely supporting the strategic search operations and initial recovery of generic autobiographical information. However, many regions were activated more strongly during direct versus generative retrieval, even when we time-locked the analysis to the successful recovery of events in both conditions. This result suggests that there may be fundamental differences between memories that are accessed directly and those that are recovered via the iterative search and retrieval process that characterizes generative retrieval. Copyright © 2011 Elsevier Inc. All rights reserved.

  16. Training-Image Based Geostatistical Inversion Using a Spatial Generative Adversarial Neural Network

    Science.gov (United States)

    Laloy, Eric; Hérault, Romain; Jacques, Diederik; Linde, Niklas

    2018-01-01

    Probabilistic inversion within a multiple-point statistics framework is often computationally prohibitive for high-dimensional problems. To partly address this, we introduce and evaluate a new training-image based inversion approach for complex geologic media. Our approach relies on a deep neural network of the generative adversarial network (GAN) type. After training using a training image (TI), our proposed spatial GAN (SGAN) can quickly generate 2-D and 3-D unconditional realizations. A key characteristic of our SGAN is that it defines a (very) low-dimensional parameterization, thereby allowing for efficient probabilistic inversion using state-of-the-art Markov chain Monte Carlo (MCMC) methods. In addition, available direct conditioning data can be incorporated within the inversion. Several 2-D and 3-D categorical TIs are first used to analyze the performance of our SGAN for unconditional geostatistical simulation. Training our deep network can take several hours. After training, realizations containing a few millions of pixels/voxels can be produced in a matter of seconds. This makes it especially useful for simulating many thousands of realizations (e.g., for MCMC inversion) as the relative cost of the training per realization diminishes with the considered number of realizations. Synthetic inversion case studies involving 2-D steady state flow and 3-D transient hydraulic tomography with and without direct conditioning data are used to illustrate the effectiveness of our proposed SGAN-based inversion. For the 2-D case, the inversion rapidly explores the posterior model distribution. For the 3-D case, the inversion recovers model realizations that fit the data close to the target level and visually resemble the true model well.

  17. The Neural Circuits that Generate Tics in Gilles de la Tourette Syndrome

    Science.gov (United States)

    Wang, Zhishun; Maia, Tiago V.; Marsh, Rachel; Colibazzi, Tiziano; Gerber, Andrew; Peterson, Bradley S.

    2014-01-01

    Objective To study neural activity and connectivity within cortico-striato-thalamo-cortical circuits and to reveal circuit-based neural mechanisms that govern tic generation in Tourette syndrome. Method We acquired fMRI data from 13 participants with Tourette syndrome and 21 controls during spontaneous or simulated tics. We used independent component analysis with hierarchical partner matching to isolate neural activity within functionally distinct regions of cortico-striato-thalamo-cortical circuits. We used Granger causality to investigate causal interactions among these regions. Results We found that the Tourette group exhibited stronger neural activity and interregional causality than controls throughout all portions of the motor pathway including sensorimotor cortex, putamen, pallidum, and substania nigra. Activity in these areas correlated positively with the severity of tic symptoms. Activity within the Tourette group was stronger during spontaneous tics than during voluntary tics in somatosensory and posterior parietal cortices, putamen, and amygdala/hippocampus complex, suggesting that activity in these regions may represent features of the premonitory urges that generate spontaneous tic behaviors. In contrast, activity was weaker in the Tourette group than in controls within portions of cortico-striato-thalamo-cortical circuits that exert top-down control over motor pathways (caudate and anterior cingulate cortex), and progressively less activity in these regions accompanied more severe tic symptoms, suggesting that faulty activity in these circuits may fail to control tic behaviors or the premonitory urges that generate them. Conclusions Our findings taken together suggest that tics are caused by the combined effects of excessive activity in motor pathways and reduced activation in control portions of cortico-striato-thalamo-cortical circuits. PMID:21955933

  18. A neural network driving curve generation method for the heavy-haul train

    Directory of Open Access Journals (Sweden)

    Youneng Huang

    2016-05-01

    Full Text Available The heavy-haul train has a series of characteristics, such as the locomotive traction properties, the longer length of train, and the nonlinear train pipe pressure during train braking. When the train is running on a continuous long and steep downgrade railway line, the safety of the train is ensured by cycle braking, which puts high demands on the driving skills of the driver. In this article, a driving curve generation method for the heavy-haul train based on a neural network is proposed. First, in order to describe the nonlinear characteristics of train braking, the neural network model is constructed and trained by practical driving data. In the neural network model, various nonlinear neurons are interconnected to work for information processing and transmission. The target value of train braking pressure reduction and release time is achieved by modeling the braking process. The equation of train motion is computed to obtain the driving curve. Finally, in four typical operation scenarios, comparing the curve data generated by the method with corresponding practical data of the Shuohuang heavy-haul railway line, the results show that the method is effective.

  19. Neural mechanisms regulating different forms of risk-related decision-making: Insights from animal models.

    Science.gov (United States)

    Orsini, Caitlin A; Moorman, David E; Young, Jared W; Setlow, Barry; Floresco, Stan B

    2015-11-01

    Over the past 20 years there has been a growing interest in the neural underpinnings of cost/benefit decision-making. Recent studies with animal models have made considerable advances in our understanding of how different prefrontal, striatal, limbic and monoaminergic circuits interact to promote efficient risk/reward decision-making, and how dysfunction in these circuits underlies aberrant decision-making observed in numerous psychiatric disorders. This review will highlight recent findings from studies exploring these questions using a variety of behavioral assays, as well as molecular, pharmacological, neurophysiological, and translational approaches. We begin with a discussion of how neural systems related to decision subcomponents may interact to generate more complex decisions involving risk and uncertainty. This is followed by an overview of interactions between prefrontal-amygdala-dopamine and habenular circuits in regulating choice between certain and uncertain rewards and how different modes of dopamine transmission may contribute to these processes. These data will be compared with results from other studies investigating the contribution of some of these systems to guiding decision-making related to rewards vs. punishment. Lastly, we provide a brief summary of impairments in risk-related decision-making associated with psychiatric disorders, highlighting recent translational studies in laboratory animals. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Extracting Neural Oscillation Signatures of Laser-Induced Nociception in Pain-Related Regions in Rats

    Directory of Open Access Journals (Sweden)

    Xuezhu Li

    2017-10-01

    Full Text Available Previous studies have shown that multiple brain regions are involved in pain perception and pain-related neural processes by forming a functionally connected pain network. It is still unclear how these pain-related brain areas actively work together to generate the experience of pain. To get a better insight into the pain network, we implanted electrodes in four pain-related areas of rats including the anterior cingulate cortex (ACC, orbitofrontal cortex (OFC, primary somatosensory cortex (S1 and periaqueductal gray (PAG. We analyzed the pattern of local field potential (LFP oscillations under noxious laser stimulations and innoxious laser stimulations. A high-dimensional feature matrix was built based on the LFP characters for both experimental conditions. Generalized linear models (GLMs were trained to classify recorded LFPs under noxious vs. innoxious condition. We found a general power decrease in α and β bands and power increase in γ band in the recorded areas under noxious condition. After noxious laser stimulation, there was a consistent change in LFP power and correlation in all four brain areas among all 13 rats. With GLM classifiers, noxious laser trials were distinguished from innoxious laser trials with high accuracy (86% using high-dimensional LFP features. This work provides a basis for further research to examine which aspects (e.g., sensory, motor or affective processes of noxious stimulation should drive distinct neural activity across the pain network.

  1. Comparative Study of Neural Network Frameworks for the Next Generation of Adaptive Optics Systems.

    Science.gov (United States)

    González-Gutiérrez, Carlos; Santos, Jesús Daniel; Martínez-Zarzuela, Mario; Basden, Alistair G; Osborn, James; Díaz-Pernas, Francisco Javier; De Cos Juez, Francisco Javier

    2017-06-02

    Many of the next generation of adaptive optics systems on large and extremely large telescopes require tomographic techniques in order to correct for atmospheric turbulence over a large field of view. Multi-object adaptive optics is one such technique. In this paper, different implementations of a tomographic reconstructor based on a machine learning architecture named "CARMEN" are presented. Basic concepts of adaptive optics are introduced first, with a short explanation of three different control systems used on real telescopes and the sensors utilised. The operation of the reconstructor, along with the three neural network frameworks used, and the developed CUDA code are detailed. Changes to the size of the reconstructor influence the training and execution time of the neural network. The native CUDA code turns out to be the best choice for all the systems, although some of the other frameworks offer good performance under certain circumstances.

  2. Biological oscillations for learning walking coordination: dynamic recurrent neural network functionally models physiological central pattern generator.

    Science.gov (United States)

    Hoellinger, Thomas; Petieau, Mathieu; Duvinage, Matthieu; Castermans, Thierry; Seetharaman, Karthik; Cebolla, Ana-Maria; Bengoetxea, Ana; Ivanenko, Yuri; Dan, Bernard; Cheron, Guy

    2013-01-01

    The existence of dedicated neuronal modules such as those organized in the cerebral cortex, thalamus, basal ganglia, cerebellum, or spinal cord raises the question of how these functional modules are coordinated for appropriate motor behavior. Study of human locomotion offers an interesting field for addressing this central question. The coordination of the elevation of the 3 leg segments under a planar covariation rule (Borghese et al., 1996) was recently modeled (Barliya et al., 2009) by phase-adjusted simple oscillators shedding new light on the understanding of the central pattern generator (CPG) processing relevant oscillation signals. We describe the use of a dynamic recurrent neural network (DRNN) mimicking the natural oscillatory behavior of human locomotion for reproducing the planar covariation rule in both legs at different walking speeds. Neural network learning was based on sinusoid signals integrating frequency and amplitude features of the first three harmonics of the sagittal elevation angles of the thigh, shank, and foot of each lower limb. We verified the biological plausibility of the neural networks. Best results were obtained with oscillations extracted from the first three harmonics in comparison to oscillations outside the harmonic frequency peaks. Physiological replication steadily increased with the number of neuronal units from 1 to 80, where similarity index reached 0.99. Analysis of synaptic weighting showed that the proportion of inhibitory connections consistently increased with the number of neuronal units in the DRNN. This emerging property in the artificial neural networks resonates with recent advances in neurophysiology of inhibitory neurons that are involved in central nervous system oscillatory activities. The main message of this study is that this type of DRNN may offer a useful model of physiological central pattern generator for gaining insights in basic research and developing clinical applications.

  3. Comparison of 2D and 3D neural induction methods for the generation of neural progenitor cells from human induced pluripotent stem cells.

    Science.gov (United States)

    Chandrasekaran, Abinaya; Avci, Hasan X; Ochalek, Anna; Rösingh, Lone N; Molnár, Kinga; László, Lajos; Bellák, Tamás; Téglási, Annamária; Pesti, Krisztina; Mike, Arpad; Phanthong, Phetcharat; Bíró, Orsolya; Hall, Vanessa; Kitiyanant, Narisorn; Krause, Karl-Heinz; Kobolák, Julianna; Dinnyés, András

    2017-12-01

    Neural progenitor cells (NPCs) from human induced pluripotent stem cells (hiPSCs) are frequently induced using 3D culture methodologies however, it is unknown whether spheroid-based (3D) neural induction is actually superior to monolayer (2D) neural induction. Our aim was to compare the efficiency of 2D induction with 3D induction method in their ability to generate NPCs, and subsequently neurons and astrocytes. Neural differentiation was analysed at the protein level qualitatively by immunocytochemistry and quantitatively by flow cytometry for NPC (SOX1, PAX6, NESTIN), neuronal (MAP2, TUBB3), cortical layer (TBR1, CUX1) and glial markers (SOX9, GFAP, AQP4). Electron microscopy demonstrated that both methods resulted in morphologically similar neural rosettes. However, quantification of NPCs derived from 3D neural induction exhibited an increase in the number of PAX6/NESTIN double positive cells and the derived neurons exhibited longer neurites. In contrast, 2D neural induction resulted in more SOX1 positive cells. While 2D monolayer induction resulted in slightly less mature neurons, at an early stage of differentiation, the patch clamp analysis failed to reveal any significant differences between the electrophysiological properties between the two induction methods. In conclusion, 3D neural induction increases the yield of PAX6 + /NESTIN + cells and gives rise to neurons with longer neurites, which might be an advantage for the production of forebrain cortical neurons, highlighting the potential of 3D neural induction, independent of iPSCs' genetic background. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  4. Effects of turbidity on the neural structures of two closely related ...

    African Journals Online (AJOL)

    The neural structures of the sister species Pseudobarbus afer and P. asper were compared. P. afer, a redfin minnow which inhabits clear, perennial mountain streams, was found to have larger neural structures related to vision than P. asper, which inhabits turbid, intermittent streams of the Gamtoos River system, ...

  5. Development of relative humidity models by using optimized neural network structures

    Energy Technology Data Exchange (ETDEWEB)

    Martinez-romero, A.; Ortega, J. F.; Juan, J. A.; Tarjuelo, J. M.; Moreno, M. A.

    2010-07-01

    Climate has always had a very important role in life on earth, as well as human activity and health. The influence of relative humidity (RH) in controlled environments (e.g. industrial processes in agro-food processing, cold storage of foods such as fruits, vegetables and meat, or controls in greenhouses) is very important. Relative humidity is a main factor in agricultural production and crop yield (due to the influence on crop water demand or the development and distribution of pests and diseases, for example). The main objective of this paper is to estimate RH [maximum (RHmax), average (RHave), and minimum (RHmin)] data in a specific area, being applied to the Region of Castilla-La Mancha (C-LM) in this case, from available data at thermo-pluviometric weather stations. In this paper Artificial neural networks (ANN) are used to generate RH considering maximum and minimum temperatures and extraterrestrial solar radiation data. Model validation and generation is based on data from the years 2000 to 2008 from 44 complete agroclimatic weather stations. Relative errors are estimated as 1) spatial errors of 11.30%, 6.80% and 10.27% and 2) temporal errors of 10.34%, 6.59% and 9.77% for RHmin, RHmax and RHave, respectively. The use of ANNs is interesting in generating climate parameters from available climate data. For determining optimal ANN structure in estimating RH values, model calibration and validation is necessary, considering spatial and temporal variability. (Author) 44 refs.

  6. Engineering applications of fpgas chaotic systems, artificial neural networks, random number generators, and secure communication systems

    CERN Document Server

    Tlelo-Cuautle, Esteban; de la Fraga, Luis Gerardo

    2016-01-01

    This book offers readers a clear guide to implementing engineering applications with FPGAs, from the mathematical description to the hardware synthesis, including discussion of VHDL programming and co-simulation issues. Coverage includes FPGA realizations such as: chaos generators that are described from their mathematical models; artificial neural networks (ANNs) to predict chaotic time series, for which a discussion of different ANN topologies is included, with different learning techniques and activation functions; random number generators (RNGs) that are realized using different chaos generators, and discussions of their maximum Lyapunov exponent values and entropies. Finally, optimized chaotic oscillators are synchronized and realized to implement a secure communication system that processes black and white and grey-scale images. In each application, readers will find VHDL programming guidelines and computer arithmetic issues, along with co-simulation examples with Active-HDL and Simulink. Readers will b...

  7. Generation of Oligodendrogenic Spinal Neural Progenitor Cells From Human Induced Pluripotent Stem Cells.

    Science.gov (United States)

    Khazaei, Mohamad; Ahuja, Christopher S; Fehlings, Michael G

    2017-08-14

    This unit describes protocols for the efficient generation of oligodendrogenic neural progenitor cells (o-NPCs) from human induced pluripotent stem cells (hiPSCs). Specifically, detailed methods are provided for the maintenance and differentiation of hiPSCs, human induced pluripotent stem cell-derived neural progenitor cells (hiPS-NPCs), and human induced pluripotent stem cell-oligodendrogenic neural progenitor cells (hiPSC-o-NPCs) with the final products being suitable for in vitro experimentation or in vivo transplantation. Throughout, cell exposure to growth factors and patterning morphogens has been optimized for both concentration and timing, based on the literature and empirical experience, resulting in a robust and highly efficient protocol. Using this derivation procedure, it is possible to obtain millions of oligodendrogenic-NPCs within 40 days of initial cell plating which is substantially shorter than other protocols for similar cell types. This protocol has also been optimized to use translationally relevant human iPSCs as the parent cell line. The resultant cells have been extensively characterized both in vitro and in vivo and express key markers of an oligodendrogenic lineage. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley and Sons, Inc.

  8. Generation and properties of a new human ventral mesencephalic neural stem cell line

    Energy Technology Data Exchange (ETDEWEB)

    Villa, Ana; Liste, Isabel; Courtois, Elise T.; Seiz, Emma G.; Ramos, Milagros [Center of Molecular Biology ' Severo Ochoa' , Autonomous University of Madrid-C.S.I.C., Campus Cantoblanco 28049-Madrid (Spain); Meyer, Morten [Department of Anatomy and Neurobiology, Institute of Medical Biology, University of Southern Denmark, Winslowparken 21,st, DK-500, Odense C (Denmark); Juliusson, Bengt; Kusk, Philip [NsGene A/S, Ballerup (Denmark); Martinez-Serrano, Alberto, E-mail: amserrano@cbm.uam.es [Center of Molecular Biology ' Severo Ochoa' , Autonomous University of Madrid-C.S.I.C., Campus Cantoblanco 28049-Madrid (Spain)

    2009-07-01

    Neural stem cells (NSCs) are powerful research tools for the design and discovery of new approaches to cell therapy in neurodegenerative diseases like Parkinson's disease. Several epigenetic and genetic strategies have been tested for long-term maintenance and expansion of these cells in vitro. Here we report the generation of a new stable cell line of human neural stem cells derived from ventral mesencephalon (hVM1) based on v-myc immortalization. The cells expressed neural stem cell and radial glia markers like nestin, vimentin and 3CB2 under proliferation conditions. After withdrawal of growth factors, proliferation and expression of v-myc were dramatically reduced and the cells differentiated into astrocytes, oligodendrocytes and neurons. hVM1 cells yield a large number of dopaminergic neurons (about 12% of total cells are TH{sup +}) after differentiation, which also produce dopamine. In addition to proneural genes (NGN2, MASH1), differentiated cells show expression of several genuine mesencephalic dopaminergic markers such as: LMX1A, LMX1B, GIRK2, ADH2, NURR1, PITX3, VMAT2 and DAT, indicating that they retain their regional identity. Our data indicate that this cell line and its clonal derivatives may constitute good candidates for the study of development and physiology of human dopaminergic neurons in vitro, and to develop tools for Parkinson's disease cell replacement preclinical research and drug testing.

  9. Evolutionary mechanisms that generate morphology and neural-circuit diversity of the cerebellum.

    Science.gov (United States)

    Hibi, Masahiko; Matsuda, Koji; Takeuchi, Miki; Shimizu, Takashi; Murakami, Yasunori

    2017-05-01

    The cerebellum is derived from the dorsal part of the anterior-most hindbrain. The vertebrate cerebellum contains glutamatergic granule cells (GCs) and gamma-aminobutyric acid (GABA)ergic Purkinje cells (PCs). These cerebellar neurons are generated from neuronal progenitors or neural stem cells by mechanisms that are conserved among vertebrates. However, vertebrate cerebella are widely diverse with respect to their gross morphology and neural circuits. The cerebellum of cyclostomes, the basal vertebrates, has a negligible structure. Cartilaginous fishes have a cerebellum containing GCs, PCs, and deep cerebellar nuclei (DCNs), which include projection neurons. Ray-finned fish lack DCNs but have projection neurons termed eurydendroid cells (ECs) in the vicinity of the PCs. Among ray-finned fishes, the cerebellum of teleost zebrafish has a simple lobular structure, whereas that of weakly electric mormyrid fish is large and foliated. Amniotes, which include mammals, independently evolved a large, foliated cerebellum, which contains massive numbers of GCs and has functional connections with the dorsal telencephalon (neocortex). Recent studies of cyclostomes and cartilaginous fish suggest that the genetic program for cerebellum development was already encoded in the genome of ancestral vertebrates. In this review, we discuss how alterations of the genetic and cellular programs generated diversity of the cerebellum during evolution. © 2017 Japanese Society of Developmental Biologists.

  10. A Phox2b BAC Transgenic Rat Line Useful for Understanding Respiratory Rhythm Generator Neural Circuitry.

    Directory of Open Access Journals (Sweden)

    Keiko Ikeda

    Full Text Available The key role of the respiratory neural center is respiratory rhythm generation to maintain homeostasis through the control of arterial blood pCO2/pH and pO2 levels. The neuronal network responsible for respiratory rhythm generation in neonatal rat resides in the ventral side of the medulla and is composed of two groups; the parafacial respiratory group (pFRG and the pre-Bötzinger complex group (preBötC. The pFRG partially overlaps in the retrotrapezoid nucleus (RTN, which was originally identified in adult cats and rats. Part of the pre-inspiratory (Pre-I neurons in the RTN/pFRG serves as central chemoreceptor neurons and the CO2 sensitive Pre-I neurons express homeobox gene Phox2b. Phox2b encodes a transcription factor and is essential for the development of the sensory-motor visceral circuits. Mutations in human PHOX2B cause congenital hypoventilation syndrome, which is characterized by blunted ventilatory response to hypercapnia. Here we describe the generation of a novel transgenic (Tg rat harboring fluorescently labeled Pre-I neurons in the RTN/pFRG. In addition, the Tg rat showed fluorescent signals in autonomic enteric neurons and carotid bodies. Because the Tg rat expresses inducible Cre recombinase in PHOX2B-positive cells during development, it is a potentially powerful tool for dissecting the entire picture of the respiratory neural network during development and for identifying the CO2/O2 sensor molecules in the adult central and peripheral nervous systems.

  11. Neural correlates of appetite and hunger-related evaluative judgments.

    Directory of Open Access Journals (Sweden)

    Richard M Piech

    2009-08-01

    Full Text Available How much we desire a meal depends on both the constituent foods and how hungry we are, though not every meal becomes more desirable with increasing hunger. The brain therefore needs to be able to integrate hunger and meal properties to compute the correct incentive value of a meal. The present study investigated the functional role of the amygdala and the orbitofrontal cortex in mediating hunger and dish attractiveness. Furthermore, it explored neural responses to dish descriptions particularly susceptible to value-increase following fasting. We instructed participants to rate how much they wanted food menu items while they were either hungry or sated, and compared the rating differences in these states. Our results point to the representation of food value in the amygdala, and to an integration of attractiveness with hunger level in the orbitofrontal cortex. Dishes particularly desirable during hunger activated the thalamus and the insula. Our results specify the functions of evaluative structures in the context of food attractiveness, and point to a complex neural representation of dish qualities which contribute to state-dependent value.

  12. Neural stem cells induce bone-marrow-derived mesenchymal stem cells to generate neural stem-like cells via juxtacrine and paracrine interactions

    International Nuclear Information System (INIS)

    Alexanian, Arshak R.

    2005-01-01

    Several recent reports suggest that there is far more plasticity that previously believed in the developmental potential of bone-marrow-derived cells (BMCs) that can be induced by extracellular developmental signals of other lineages whose nature is still largely unknown. In this study, we demonstrate that bone-marrow-derived mesenchymal stem cells (MSCs) co-cultured with mouse proliferating or fixed (by paraformaldehyde or methanol) neural stem cells (NSCs) generate neural stem cell-like cells with a higher expression of Sox-2 and nestin when grown in NS-A medium supplemented with N2, NSC conditioned medium (NSCcm) and bFGF. These neurally induced MSCs eventually differentiate into β-III-tubulin and GFAP expressing cells with neuronal and glial morphology when grown an additional week in Neurobasal/B27 without bFGF. We conclude that juxtacrine interaction between NSCs and MSCs combined with soluble factors released from NSCs are important for generation of neural-like cells from bone-marrow-derived adherent MSCs

  13. Functional overlap of top-down emotion regulation and generation: an fMRI study identifying common neural substrates between cognitive reappraisal and cognitively generated emotions.

    Science.gov (United States)

    Otto, Benjamin; Misra, Supriya; Prasad, Aditya; McRae, Kateri

    2014-09-01

    One factor that influences the success of emotion regulation is the manner in which the regulated emotion was generated. Recent research has suggested that reappraisal, a top-down emotion regulation strategy, is more effective in decreasing self-reported negative affect when emotions were generated from the top-down, versus the bottom-up. On the basis of a process overlap framework, we hypothesized that the neural regions active during reappraisal would overlap more with emotions that were generated from the top-down, rather than from the bottom-up. In addition, we hypothesized that increased neural overlap between reappraisal and the history effects of top-down emotion generation would be associated with increased reappraisal success. The results of several analyses suggested that reappraisal and emotions that were generated from the top-down share a core network of prefrontal, temporal, and cingulate regions. This overlap is specific; no such overlap was observed between reappraisal and emotions that were generated in a bottom-up fashion. This network consists of regions previously implicated in linguistic processing, cognitive control, and self-relevant appraisals, which are processes thought to be crucial to both reappraisal and top-down emotion generation. Furthermore, individuals with high reappraisal success demonstrated greater neural overlap between reappraisal and the history of top-down emotion generation than did those with low reappraisal success. The overlap of these key regions, reflecting overlapping processes, provides an initial insight into the mechanism by which generation history may facilitate emotion regulation.

  14. Neural Stem Cell Differentiation Using Microfluidic Device-Generated Growth Factor Gradient.

    Science.gov (United States)

    Kim, Ji Hyeon; Sim, Jiyeon; Kim, Hyun-Jung

    2018-04-11

    Neural stem cells (NSCs) have the ability to self-renew and differentiate into multiple nervous system cell types. During embryonic development, the concentrations of soluble biological molecules have a critical role in controlling cell proliferation, migration, differentiation and apoptosis. In an effort to find optimal culture conditions for the generation of desired cell types in vitro , we used a microfluidic chip-generated growth factor gradient system. In the current study, NSCs in the microfluidic device remained healthy during the entire period of cell culture, and proliferated and differentiated in response to the concentration gradient of growth factors (epithermal growth factor and basic fibroblast growth factor). We also showed that overexpression of ASCL1 in NSCs increased neuronal differentiation depending on the concentration gradient of growth factors generated in the microfluidic gradient chip. The microfluidic system allowed us to study concentration-dependent effects of growth factors within a single device, while a traditional system requires multiple independent cultures using fixed growth factor concentrations. Our study suggests that the microfluidic gradient-generating chip is a powerful tool for determining the optimal culture conditions.

  15. Performance assessment of electric power generations using an adaptive neural network algorithm

    International Nuclear Information System (INIS)

    Azadeh, A.; Ghaderi, S.F.; Anvari, M.; Saberi, M.

    2007-01-01

    Efficiency frontier analysis has been an important approach of evaluating firms' performance in private and public sectors. There have been many efficiency frontier analysis methods reported in the literature. However, the assumptions made for each of these methods are restrictive. Each of these methodologies has its strength as well as major limitations. This study proposes a non-parametric efficiency frontier analysis method based on the adaptive neural network technique for measuring efficiency as a complementary tool for the common techniques of the efficiency studies in the previous studies. The proposed computational method is able to find a stochastic frontier based on a set of input-output observational data and do not require explicit assumptions about the function structure of the stochastic frontier. In this algorithm, for calculating the efficiency scores, a similar approach to econometric methods has been used. Moreover, the effect of the return to scale of decision-making units (DMUs) on its efficiency is included and the unit used for the correction is selected by notice of its scale (under constant return to scale assumption). An example using real data is presented for illustrative purposes. In the application to the power generation sector of Iran, we find that the neural network provide more robust results and identifies more efficient units than the conventional methods since better performance patterns are explored. Moreover, principle component analysis (PCA) is used to verify the findings of the proposed algorithm

  16. Generation of highly purified neural stem cells from human adipose-derived mesenchymal stem cells by Sox1 activation.

    Science.gov (United States)

    Feng, Nianhua; Han, Qin; Li, Jing; Wang, Shihua; Li, Hongling; Yao, Xinglei; Zhao, Robert Chunhua

    2014-03-01

    Neural stem cells (NSCs) are ideal candidates in stem cell-based therapy for neurodegenerative diseases. However, it is unfeasible to get enough quantity of NSCs for clinical application. Generation of NSCs from human adipose-derived mesenchymal stem cells (hAD-MSCs) will provide a solution to this problem. Currently, the differentiation of hAD-MSCs into highly purified NSCs with biological functions is rarely reported. In our study, we established a three-step NSC-inducing protocol, in which hAD-MSCs were induced to generate NSCs with high purity after sequentially cultured in the pre-inducing medium (Step1), the N2B27 medium (Step2), and the N2B27 medium supplement with basic fibroblast growth factor and epidermal growth factor (Step3). These hAD-MSC-derived NSCs (adNSCs) can form neurospheres and highly express Sox1, Pax6, Nestin, and Vimentin; the proportion was 96.1% ± 1.3%, 96.8% ± 1.7%, 96.2% ± 1.3%, and 97.2% ± 2.5%, respectively, as detected by flow cytometry. These adNSCs can further differentiate into astrocytes, oligodendrocytes, and functional neurons, which were able to generate tetrodotoxin-sensitive sodium current. Additionally, we found that the neural differentiation of hAD-MSCs were significantly suppressed by Sox1 interference, and what's more, Step1 was a key step for the following induction, probably because it was associated with the initiation and nuclear translocation of Sox1, an important transcriptional factor for neural development. Finally, we observed that bone morphogenetic protein signal was inhibited, and Wnt/β-catenin signal was activated during inducing process, and both signals were related with Sox1 expression. In conclusion, we successfully established a three-step inducing protocol to derive NSCs from hAD-MSCs with high purity by Sox1 activation. These findings might enable to acquire enough autologous transplantable NSCs for the therapy of neurodegenerative diseases in clinic.

  17. Procedural Content Generation: Concepts and Related Works

    Directory of Open Access Journals (Sweden)

    MARIÑO, J. R. H.

    2016-12-01

    Full Text Available The digital games market is growing every year and game development is becoming increasingly complex. Thus, scalability in content generation may require the work of a team with hundreds of people. Procedural Content Generation (PCG comes as an alternative to decrease costs and accelerate the process of game production by creating content automatically or semi-automatically. This article presents some concepts and reviews works developed in PCG, aiming to provide a starting point for those interested in learning and going deeper in the subject of PCG for digital games.

  18. Prediction of municipal solid waste generation using artificial neural network approach enhanced by structural break analysis.

    Science.gov (United States)

    Adamović, Vladimir M; Antanasijević, Davor Z; Ristić, Mirjana Đ; Perić-Grujić, Aleksandra A; Pocajt, Viktor V

    2017-01-01

    This paper presents the development of a general regression neural network (GRNN) model for the prediction of annual municipal solid waste (MSW) generation at the national level for 44 countries of different size, population and economic development level. Proper modelling of MSW generation is essential for the planning of MSW management system as well as for the simulation of various environmental impact scenarios. The main objective of this work was to examine the potential influence of economy crisis (global or local) on the forecast of MSW generation obtained by the GRNN model. The existence of the so-called structural breaks that occur because of the economic crisis in the studied period (2000-2012) for each country was determined and confirmed using the Chow test and Quandt-Andrews test. Two GRNN models, one which did not take into account the influence of the economic crisis (GRNN) and another one which did (SB-GRNN), were developed. The novelty of the applied method is that it uses broadly available social, economic and demographic indicators and indicators of sustainability, together with GRNN and structural break testing for the prediction of MSW generation at the national level. The obtained results demonstrate that the SB-GRNN model provide more accurate predictions than the model which neglected structural breaks, with a mean absolute percentage error (MAPE) of 4.0 % compared to 6.7 % generated by the GRNN model. The proposed model enhanced with structural breaks can be a viable alternative for a more accurate prediction of MSW generation at the national level, especially for developing countries for which a lack of MSW data is notable.

  19. Applying a Cerebellar Model Articulation Controller Neural Network to a Photovoltaic Power Generation System Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Kuei-Hsiang Chao

    2013-01-01

    Full Text Available This study employed a cerebellar model articulation controller (CMAC neural network to conduct fault diagnoses on photovoltaic power generation systems. We composed a module array using 9 series and 2 parallel connections of SHARP NT-R5E3E 175 W photovoltaic modules. In addition, we used data that were outputted under various fault conditions as the training samples for the CMAC and used this model to conduct the module array fault diagnosis after completing the training. The results of the training process and simulations indicate that the method proposed in this study requires fewer number of training times compared to other methods. In addition to significantly increasing the accuracy rate of the fault diagnosis, this model features a short training duration because the training process only tunes the weights of the exited memory addresses. Therefore, the fault diagnosis is rapid, and the detection tolerance of the diagnosis system is enhanced.

  20. Automatic modulation format recognition for the next generation optical communication networks using artificial neural networks

    Science.gov (United States)

    Guesmi, Latifa; Hraghi, Abir; Menif, Mourad

    2015-03-01

    A new technique for Automatic Modulation Format Recognition (AMFR) in next generation optical communication networks is presented. This technique uses the Artificial Neural Network (ANN) in conjunction with the features of Linear Optical Sampling (LOS) of the detected signal at high bit rates using direct detection or coherent detection. The use of LOS method for this purpose mainly driven by the increase of bit rates which enables the measurement of eye diagrams. The efficiency of this technique is demonstrated under different transmission impairments such as chromatic dispersion (CD) in the range of -500 to 500 ps/nm, differential group delay (DGD) in the range of 0-15 ps and the optical signal tonoise ratio (OSNR) in the range of 10-30 dB. The results of numerical simulation for various modulation formats demonstrate successful recognition from a known bit rates with a higher estimation accuracy, which exceeds 99.8%.

  1. Fracture Mechanics Method for Word Embedding Generation of Neural Probabilistic Linguistic Model.

    Science.gov (United States)

    Bi, Size; Liang, Xiao; Huang, Ting-Lei

    2016-01-01

    Word embedding, a lexical vector representation generated via the neural linguistic model (NLM), is empirically demonstrated to be appropriate for improvement of the performance of traditional language model. However, the supreme dimensionality that is inherent in NLM contributes to the problems of hyperparameters and long-time training in modeling. Here, we propose a force-directed method to improve such problems for simplifying the generation of word embedding. In this framework, each word is assumed as a point in the real world; thus it can approximately simulate the physical movement following certain mechanics. To simulate the variation of meaning in phrases, we use the fracture mechanics to do the formation and breakdown of meaning combined by a 2-gram word group. With the experiments on the natural linguistic tasks of part-of-speech tagging, named entity recognition and semantic role labeling, the result demonstrated that the 2-dimensional word embedding can rival the word embeddings generated by classic NLMs, in terms of accuracy, recall, and text visualization.

  2. Fracture Mechanics Method for Word Embedding Generation of Neural Probabilistic Linguistic Model

    Directory of Open Access Journals (Sweden)

    Size Bi

    2016-01-01

    Full Text Available Word embedding, a lexical vector representation generated via the neural linguistic model (NLM, is empirically demonstrated to be appropriate for improvement of the performance of traditional language model. However, the supreme dimensionality that is inherent in NLM contributes to the problems of hyperparameters and long-time training in modeling. Here, we propose a force-directed method to improve such problems for simplifying the generation of word embedding. In this framework, each word is assumed as a point in the real world; thus it can approximately simulate the physical movement following certain mechanics. To simulate the variation of meaning in phrases, we use the fracture mechanics to do the formation and breakdown of meaning combined by a 2-gram word group. With the experiments on the natural linguistic tasks of part-of-speech tagging, named entity recognition and semantic role labeling, the result demonstrated that the 2-dimensional word embedding can rival the word embeddings generated by classic NLMs, in terms of accuracy, recall, and text visualization.

  3. Generation of novel motor sequences: the neural correlates of musical improvisation.

    Science.gov (United States)

    Berkowitz, Aaron L; Ansari, Daniel

    2008-06-01

    While some motor behavior is instinctive and stereotyped or learned and re-executed, much action is a spontaneous response to a novel set of environmental conditions. The neural correlates of both pre-learned and cued motor sequences have been previously studied, but novel motor behavior has thus far not been examined through brain imaging. In this paper, we report a study of musical improvisation in trained pianists with functional magnetic resonance imaging (fMRI), using improvisation as a case study of novel action generation. We demonstrate that both rhythmic (temporal) and melodic (ordinal) motor sequence creation modulate activity in a network of brain regions comprised of the dorsal premotor cortex, the rostral cingulate zone of the anterior cingulate cortex, and the inferior frontal gyrus. These findings are consistent with a role for the dorsal premotor cortex in movement coordination, the rostral cingulate zone in voluntary selection, and the inferior frontal gyrus in sequence generation. Thus, the invention of novel motor sequences in musical improvisation recruits a network of brain regions coordinated to generate possible sequences, select among them, and execute the decided-upon sequence.

  4. Neural Computation of Surface Border Ownership and Relative Surface Depth from Ambiguous Contrast Inputs

    Science.gov (United States)

    Dresp-Langley, Birgitta; Grossberg, Stephen

    2016-01-01

    The segregation of image parts into foreground and background is an important aspect of the neural computation of 3D scene perception. To achieve such segregation, the brain needs information about border ownership; that is, the belongingness of a contour to a specific surface represented in the image. This article presents psychophysical data derived from 3D percepts of figure and ground that were generated by presenting 2D images composed of spatially disjoint shapes that pointed inward or outward relative to the continuous boundaries that they induced along their collinear edges. The shapes in some images had the same contrast (black or white) with respect to the background gray. Other images included opposite contrasts along each induced continuous boundary. Psychophysical results demonstrate conditions under which figure-ground judgment probabilities in response to these ambiguous displays are determined by the orientation of contrasts only, not by their relative contrasts, despite the fact that many border ownership cells in cortical area V2 respond to a preferred relative contrast. Studies are also reviewed in which both polarity-specific and polarity-invariant properties obtain. The FACADE and 3D LAMINART models are used to explain these data. PMID:27516746

  5. Neural Computation of Surface Border Ownership and Relative Surface Depth from Ambiguous Contrast Inputs.

    Science.gov (United States)

    Dresp-Langley, Birgitta; Grossberg, Stephen

    2016-01-01

    The segregation of image parts into foreground and background is an important aspect of the neural computation of 3D scene perception. To achieve such segregation, the brain needs information about border ownership; that is, the belongingness of a contour to a specific surface represented in the image. This article presents psychophysical data derived from 3D percepts of figure and ground that were generated by presenting 2D images composed of spatially disjoint shapes that pointed inward or outward relative to the continuous boundaries that they induced along their collinear edges. The shapes in some images had the same contrast (black or white) with respect to the background gray. Other images included opposite contrasts along each induced continuous boundary. Psychophysical results demonstrate conditions under which figure-ground judgment probabilities in response to these ambiguous displays are determined by the orientation of contrasts only, not by their relative contrasts, despite the fact that many border ownership cells in cortical area V2 respond to a preferred relative contrast. Studies are also reviewed in which both polarity-specific and polarity-invariant properties obtain. The FACADE and 3D LAMINART models are used to explain these data.

  6. Neural computation of surface border ownership and relative surface depth from ambiguous contrast inputs

    Directory of Open Access Journals (Sweden)

    Birgitta Dresp-Langley

    2016-07-01

    Full Text Available The segregation of image parts into foreground and background is an important aspect of the neural computation of 3D scene perception. To achieve such segregation, the brain needs information about border ownership; that is, the belongingness of a contour to a specific surface represented in the image. This article presents psychophysical data derived from 3D percepts of figure and ground that were generated by presenting 2D images composed of spatially disjoint shapes that pointed inward or outward relative to the continuous boundaries that they induced along their collinear edges. The shapes in some images had the same contrast (black or white with respect to the background gray. Other images included opposite contrasts along each induced continuous boundary. Results demonstrate conditions under which figure-ground judgment probabilities in response to these ambiguous displays are determined by the orientation of contrasts only, not by their relative contrasts, despite the fact that many border ownership cells in cortical area V2 respond to a preferred relative contrast. Studies are also reviewed in which both polarity-specific and polarity-invariant properties obtain. The FACADE and 3D LAMINART models are used to explain these data.

  7. Neural mirroring and social interaction: Motor system involvement during action observation relates to early peer cooperation.

    Science.gov (United States)

    Endedijk, H M; Meyer, M; Bekkering, H; Cillessen, A H N; Hunnius, S

    2017-04-01

    Whether we hand over objects to someone, play a team sport, or make music together, social interaction often involves interpersonal action coordination, both during instances of cooperation and entrainment. Neural mirroring is thought to play a crucial role in processing other's actions and is therefore considered important for social interaction. Still, to date, it is unknown whether interindividual differences in neural mirroring play a role in interpersonal coordination during different instances of social interaction. A relation between neural mirroring and interpersonal coordination has particularly relevant implications for early childhood, since successful early interaction with peers is predictive of a more favorable social development. We examined the relation between neural mirroring and children's interpersonal coordination during peer interaction using EEG and longitudinal behavioral data. Results showed that 4-year-old children with higher levels of motor system involvement during action observation (as indicated by lower beta-power) were more successful in early peer cooperation. This is the first evidence for a relation between motor system involvement during action observation and interpersonal coordination during other instances of social interaction. The findings suggest that interindividual differences in neural mirroring are related to interpersonal coordination and thus successful social interaction. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  8. A systematic review of the neural bases of psychotherapy for anxiety and related disorders.

    Science.gov (United States)

    Brooks, Samantha J; Stein, Dan J

    2015-09-01

    Brain imaging studies over two decades have delineated the neural circuitry of anxiety and related disorders, particularly regions involved in fear processing and in obsessive-compulsive symptoms. The neural circuitry of fear processing involves the amygdala, anterior cingulate, and insular cortex, while cortico-striatal-thalamic circuitry plays a key role in obsessive-compulsive disorder. More recently, neuroimaging studies have examined how psychotherapy for anxiety and related disorders impacts on these neural circuits. Here we conduct a systematic review of the findings of such work, which yielded 19 functional magnetic resonance imaging studies examining the neural bases of cognitive-behavioral therapy (CBT) in 509 patients with anxiety and related disorders. We conclude that, although each of these related disorders is mediated by somewhat different neural circuitry, CBT may act in a similar way to increase prefrontal control of subcortical structures. These findings are consistent with an emphasis in cognitive-affective neuroscience on the potential therapeutic value of enhancing emotional regulation in various psychiatric conditions.

  9. Distant supervision for neural relation extraction integrated with word attention and property features.

    Science.gov (United States)

    Qu, Jianfeng; Ouyang, Dantong; Hua, Wen; Ye, Yuxin; Li, Ximing

    2018-04-01

    Distant supervision for neural relation extraction is an efficient approach to extracting massive relations with reference to plain texts. However, the existing neural methods fail to capture the critical words in sentence encoding and meanwhile lack useful sentence information for some positive training instances. To address the above issues, we propose a novel neural relation extraction model. First, we develop a word-level attention mechanism to distinguish the importance of each individual word in a sentence, increasing the attention weights for those critical words. Second, we investigate the semantic information from word embeddings of target entities, which can be developed as a supplementary feature for the extractor. Experimental results show that our model outperforms previous state-of-the-art baselines. Copyright © 2018 Elsevier Ltd. All rights reserved.

  10. Feeling full and being full : how gastric content relates to appetite, food properties and neural activation

    NARCIS (Netherlands)

    Camps, Guido

    2017-01-01

    Aim: This thesis aimed to further determine how gastric content relates to subjective experiences regarding appetite, how this relation is affected by food properties and whether this is visible in neural activation changes.

    Method: This was studied using

  11. Verbal working memory-related neural network communication in schizophrenia.

    Science.gov (United States)

    Kustermann, Thomas; Popov, Tzvetan; Miller, Gregory A; Rockstroh, Brigitte

    2018-04-19

    Impaired working memory (WM) in schizophrenia is associated with reduced hemodynamic and electromagnetic activity and altered network connectivity within and between memory-associated neural networks. The present study sought to determine whether schizophrenia involves disruption of a frontal-parietal network normally supporting WM and/or involvement of another brain network. Nineteen schizophrenia patients (SZ) and 19 healthy comparison subjects (HC) participated in a cued visual-verbal Sternberg task while dense-array EEG was recorded. A pair of item arrays each consisting of 2-4 consonants was presented bilaterally for 200 ms with a prior cue signaling the hemifield of the task-relevant WM set. A central probe letter 2,000 ms later prompted a choice reaction time decision about match/mismatch with the target WM set. Group and WM load effects on time domain and time-frequency domain 11-15 Hz alpha power were assessed for the cue-to-probe time window, and posterior 11-15 Hz alpha power and frontal 4-8 Hz theta power were assessed during the retention period. Directional connectivity was estimated via Granger causality, evaluating group differences in communication. SZ showed slower responding, lower accuracy, smaller overall time-domain alpha power increase, and less load-dependent alpha power increase. Midline frontal theta power increases did not vary by group or load. Network communication in SZ was characterized by temporal-to-posterior information flow, in contrast to bidirectional temporal-posterior communication in HC. Results indicate aberrant WM network activity supporting WM in SZ that might facilitate normal load-dependent and only marginally less accurate task performance, despite generally slower responding. © 2018 Society for Psychophysiological Research.

  12. Schema generation in recurrent neural nets for intercepting a moving target.

    Science.gov (United States)

    Fleischer, Andreas G

    2010-06-01

    The grasping of a moving object requires the development of a motor strategy to anticipate the trajectory of the target and to compute an optimal course of interception. During the performance of perception-action cycles, a preprogrammed prototypical movement trajectory, a motor schema, may highly reduce the control load. Subjects were asked to hit a target that was moving along a circular path by means of a cursor. Randomized initial target positions and velocities were detected in the periphery of the eyes, resulting in a saccade toward the target. Even when the target disappeared, the eyes followed the target's anticipated course. The Gestalt of the trajectories was dependent on target velocity. The prediction capability of the motor schema was investigated by varying the visibility range of cursor and target. Motor schemata were determined to be of limited precision, and therefore visual feedback was continuously required to intercept the moving target. To intercept a target, the motor schema caused the hand to aim ahead and to adapt to the target trajectory. The control of cursor velocity determined the point of interception. From a modeling point of view, a neural network was developed that allowed the implementation of a motor schema interacting with feedback control in an iterative manner. The neural net of the Wilson type consists of an excitation-diffusion layer allowing the generation of a moving bubble. This activation bubble runs down an eye-centered motor schema and causes a planar arm model to move toward the target. A bubble provides local integration and straightening of the trajectory during repetitive moves. The schema adapts to task demands by learning and serves as forward controller. On the basis of these model considerations the principal problem of embedding motor schemata in generalized control strategies is discussed.

  13. Generation of human cortical neurons from a new immortal fetal neural stem cell line

    International Nuclear Information System (INIS)

    Cacci, E.; Villa, A.; Parmar, M.; Cavallaro, M.; Mandahl, N.; Lindvall, O.; Martinez-Serrano, A.; Kokaia, Z.

    2007-01-01

    Isolation and expansion of neural stem cells (NSCs) of human origin are crucial for successful development of cell therapy approaches in neurodegenerative diseases. Different epigenetic and genetic immortalization strategies have been established for long-term maintenance and expansion of these cells in vitro. Here we report the generation of a new, clonal NSC (hc-NSC) line, derived from human fetal cortical tissue, based on v-myc immortalization. Using immunocytochemistry, we show that these cells retain the characteristics of NSCs after more than 50 passages. Under proliferation conditions, when supplemented with epidermal and basic fibroblast growth factors, the hc-NSCs expressed neural stem/progenitor cell markers like nestin, vimentin and Sox2. When growth factors were withdrawn, proliferation and expression of v-myc and telomerase were dramatically reduced, and the hc-NSCs differentiated into glia and neurons (mostly glutamatergic and GABAergic, as well as tyrosine hydroxylase-positive, presumably dopaminergic neurons). RT-PCR analysis showed that the hc-NSCs retained expression of Pax6, Emx2 and Neurogenin2, which are genes associated with regionalization and cell commitment in cortical precursors during brain development. Our data indicate that this hc-NSC line could be useful for exploring the potential of human NSCs to replace dead or damaged cortical cells in animal models of acute and chronic neurodegenerative diseases. Taking advantage of its clonality and homogeneity, this cell line will also be a valuable experimental tool to study the regulatory role of intrinsic and extrinsic factors in human NSC biology

  14. Widespread neural oscillations in the delta band dissociate rule convergence from rule divergence during creative idea generation

    NARCIS (Netherlands)

    Boot, N.; Baas, M.; Mühlfeld, E.; de Dreu, C.K.W.; van Gaal, S.

    Critical to creative cognition and performance is both the generation of multiple alternative solutions in response to open-ended problems (divergent thinking) and a series of cognitive operations that converges on the correct or best possible answer (convergent thinking). Although the neural

  15. Number of generations related to coupling constants by confusion

    International Nuclear Information System (INIS)

    Bennett, D.L.; Nielsen, H.B.

    1987-01-01

    In the context of random dynamics, the mechanism of confusion is used to obtain a relation between the number of generations and standard model coupling constants. Preliminary results predict the existence of four generations. (orig.)

  16. International cost relations in electric power generation

    International Nuclear Information System (INIS)

    Schmitt, D.; Duengen, H.; Wilhelm, M.

    1986-01-01

    In spite of the fact that analyses of the cost of electric power generation as the result of international comparative evaluations are indisputably relevant, problems pending in connection with the costs of representative power plant technologies are of the methodological bind. German authors have hitherto also been failing to clear up and consider all aspects connected with the problems of data acquisition and the adequate interpretation of results. The analysis presented by the paper abstracted therefore aims at the following: 1) Systematization of the different categories of cost relevant in connection with international comparative evaluation. Classification into different categories of decision making and development of standards meeting the requirements of international comparative evaluation. 2) Calculation of relevant average financial costs of Western German, America and French fossil-fuel and nuclear power plants by means of adequate calculation models, that is the assessment of costs with regard to countries and power plant technologies which are relevant to the Federal Republic of Germany. 3) Analysis of the resulting differences and determinantal interpretation. (orig./UA) [de

  17. Self-generation of controller of an underwater robot with neural network

    International Nuclear Information System (INIS)

    Suto, T.; Ura, T.

    1994-01-01

    A self-organizing controller system is constructed based on artificial neural networks and applied to constant altitude swimming of the autonomous underwater robot PTEROA 150. The system consists of a controller and a forward model which calculates the values for evaluation as a result of control. Some methods are introduced for quick and appropriate adjustment of the controller network. Modification of the controller network is executed based on error-back-propagation method utilizing the forward model network. The forward model is divided into three sub-networks which represent dynamics of the vehicle, estimation of relative position to the seabed and calculation of the altitude. The proposed adaptive system is demonstrated in computer simulations where objective of a vehicle is keeping a constant altitude from seabed which is constituted of triangular ridges

  18. Social network size relates to developmental neural sensitivity to biological motion

    Directory of Open Access Journals (Sweden)

    L.A. Kirby

    2018-04-01

    Full Text Available The ability to perceive others’ actions and goals from human motion (i.e., biological motion perception is a critical component of social perception and may be linked to the development of real-world social relationships. Adult research demonstrates two key nodes of the brain’s biological motion perception system—amygdala and posterior superior temporal sulcus (pSTS—are linked to variability in social network properties. The relation between social perception and social network properties, however, has not yet been investigated in middle childhood—a time when individual differences in social experiences and social perception are growing. The aims of this study were to (1 replicate past work showing amygdala and pSTS sensitivity to biological motion in middle childhood; (2 examine age-related changes in the neural sensitivity for biological motion, and (3 determine whether neural sensitivity for biological motion relates to social network characteristics in children. Consistent with past work, we demonstrate a significant relation between social network size and neural sensitivity for biological motion in left pSTS, but do not find age-related change in biological motion perception. This finding offers evidence for the interplay between real-world social experiences and functional brain development and has important implications for understanding disorders of atypical social experience. Keywords: Biological motion, Social networks, Middle childhood, Neural specialization, Brain-behavior relations, pSTS

  19. The use of artificial neural networks and multiple linear regression to predict rate of medical waste generation

    International Nuclear Information System (INIS)

    Jahandideh, Sepideh; Jahandideh, Samad; Asadabadi, Ebrahim Barzegari; Askarian, Mehrdad; Movahedi, Mohammad Mehdi; Hosseini, Somayyeh; Jahandideh, Mina

    2009-01-01

    Prediction of the amount of hospital waste production will be helpful in the storage, transportation and disposal of hospital waste management. Based on this fact, two predictor models including artificial neural networks (ANNs) and multiple linear regression (MLR) were applied to predict the rate of medical waste generation totally and in different types of sharp, infectious and general. In this study, a 5-fold cross-validation procedure on a database containing total of 50 hospitals of Fars province (Iran) were used to verify the performance of the models. Three performance measures including MAR, RMSE and R 2 were used to evaluate performance of models. The MLR as a conventional model obtained poor prediction performance measure values. However, MLR distinguished hospital capacity and bed occupancy as more significant parameters. On the other hand, ANNs as a more powerful model, which has not been introduced in predicting rate of medical waste generation, showed high performance measure values, especially 0.99 value of R 2 confirming the good fit of the data. Such satisfactory results could be attributed to the non-linear nature of ANNs in problem solving which provides the opportunity for relating independent variables to dependent ones non-linearly. In conclusion, the obtained results showed that our ANN-based model approach is very promising and may play a useful role in developing a better cost-effective strategy for waste management in future.

  20. Emotion identification and aging: Behavioral and neural age-related changes.

    Science.gov (United States)

    Gonçalves, Ana R; Fernandes, Carina; Pasion, Rita; Ferreira-Santos, Fernando; Barbosa, Fernando; Marques-Teixeira, João

    2018-05-01

    Aging is known to alter the processing of facial expressions of emotion (FEE), however the impact of this alteration is less clear. Additionally, there is little information about the temporal dynamics of the neural processing of facial affect. We examined behavioral and neural age-related changes in the identification of FEE using event-related potentials. Furthermore, we analyze the relationship between behavioral/neural responses and neuropsychological functioning. To this purpose, 30 younger adults, 29 middle-aged adults and 26 older adults identified FEE. The behavioral results showed a similar performance between groups. The neural results showed no significant differences between groups for the P100 component and an increased N170 amplitude in the older group. Furthermore, a pattern of asymmetric activation was evident in the N170 component. Results also suggest deficits in facial feature decoding abilities, reflected by a reduced N250 amplitude in older adults. Neuropsychological functioning predicts P100 modulation, but does not seem to influence emotion identification ability. The findings suggest the existence of a compensatory function that would explain the age-equivalent performance in emotion identification. The study may help future research addressing behavioral and neural processes involved on processing of FEE in neurodegenerative conditions. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

  1. Age-related difference in the effective neural connectivity associated with probabilistic category learning

    International Nuclear Information System (INIS)

    Yoon, Eun Jin; Cho, Sang Soo; Kim, Hee Jung; Bang, Seong Ae; Park, Hyun Soo; Kim, Yu Kyeong; Kim, Sang Eun

    2007-01-01

    Although it is well known that explicit memory is affected by the deleterious changes in brain with aging, but effect of aging in implicit memory such as probabilistic category learning (PCL) is not clear. To identify the effect of aging on the neural interaction for successful PCL, we investigated the neural substrates of PCL and the age-related changes of the neural network between these brain regions. 23 young (age, 252 y; 11 males) and 14 elderly (673 y; 7 males) healthy subjects underwent FDG PET during a resting state and 150-trial weather prediction (WP) task. Correlations between the WP hit rates and regional glucose metabolism were assessed using SPM2 (P diff (37) = 142.47, P<0.005), Systematic comparisons of each path revealed that frontal crosscallosal and the frontal to parahippocampal connection were most responsible for the model differences (P<0.05). For the successful PCL, the elderly recruits the basal ganglia implicit memory system but MTL recruitment differs from the young. The inadequate MTL correlation pattern in the elderly is may be caused by the changes of the neural pathway related with explicit memory. These neural changes can explain the decreased performance of PCL in elderly subjects

  2. Generating perfect fluid spheres in general relativity

    Science.gov (United States)

    Boonserm, Petarpa; Visser, Matt; Weinfurtner, Silke

    2005-06-01

    Ever since Karl Schwarzschild’s 1916 discovery of the spacetime geometry describing the interior of a particular idealized general relativistic star—a static spherically symmetric blob of fluid with position-independent density—the general relativity community has continued to devote considerable time and energy to understanding the general-relativistic static perfect fluid sphere. Over the last 90 years a tangle of specific perfect fluid spheres has been discovered, with most of these specific examples seemingly independent from each other. To bring some order to this collection, in this article we develop several new transformation theorems that map perfect fluid spheres into perfect fluid spheres. These transformation theorems sometimes lead to unexpected connections between previously known perfect fluid spheres, sometimes lead to new previously unknown perfect fluid spheres, and in general can be used to develop a systematic way of classifying the set of all perfect fluid spheres.

  3. Generating perfect fluid spheres in general relativity

    International Nuclear Information System (INIS)

    Boonserm, Petarpa; Visser, Matt; Weinfurtner, Silke

    2005-01-01

    Ever since Karl Schwarzschild's 1916 discovery of the spacetime geometry describing the interior of a particular idealized general relativistic star--a static spherically symmetric blob of fluid with position-independent density--the general relativity community has continued to devote considerable time and energy to understanding the general-relativistic static perfect fluid sphere. Over the last 90 years a tangle of specific perfect fluid spheres has been discovered, with most of these specific examples seemingly independent from each other. To bring some order to this collection, in this article we develop several new transformation theorems that map perfect fluid spheres into perfect fluid spheres. These transformation theorems sometimes lead to unexpected connections between previously known perfect fluid spheres, sometimes lead to new previously unknown perfect fluid spheres, and in general can be used to develop a systematic way of classifying the set of all perfect fluid spheres

  4. Probabilistic Models and Generative Neural Networks: Towards an Unified Framework for Modeling Normal and Impaired Neurocognitive Functions.

    Science.gov (United States)

    Testolin, Alberto; Zorzi, Marco

    2016-01-01

    Connectionist models can be characterized within the more general framework of probabilistic graphical models, which allow to efficiently describe complex statistical distributions involving a large number of interacting variables. This integration allows building more realistic computational models of cognitive functions, which more faithfully reflect the underlying neural mechanisms at the same time providing a useful bridge to higher-level descriptions in terms of Bayesian computations. Here we discuss a powerful class of graphical models that can be implemented as stochastic, generative neural networks. These models overcome many limitations associated with classic connectionist models, for example by exploiting unsupervised learning in hierarchical architectures (deep networks) and by taking into account top-down, predictive processing supported by feedback loops. We review some recent cognitive models based on generative networks, and we point out promising research directions to investigate neuropsychological disorders within this approach. Though further efforts are required in order to fill the gap between structured Bayesian models and more realistic, biophysical models of neuronal dynamics, we argue that generative neural networks have the potential to bridge these levels of analysis, thereby improving our understanding of the neural bases of cognition and of pathologies caused by brain damage.

  5. Revocation of European patent for neural progenitors highlights patent challenges for inventions relating to human embryonic stem cells.

    Science.gov (United States)

    Rigby, Barbara

    2013-11-01

    Cells derived from human embryonic stem cells have great therapeutic potential. Patents are key to allowing companies that develop methods of generating such cells to recuperate their investment. However, in Europe, inventions relating to the use of human embryos for commercial purposes are excluded from patentability on moral grounds. The scope of this morality exclusion was recently tested before Germany's highest court and before the European Patent Office (EPO), with diverging results. The decision by the EPO's Opposition Division to revoke EP1040185 relating to neural precursors and methods for their generation has received a mixed reception. The decision has very recently been appealed, and the outcome of this Appeal should provide more definitive guidance on the scope of the morality exclusion.

  6. Social power and approach-related neural activity

    OpenAIRE

    Boksem, Maarten; Smolders, Ruud; Cremer, David

    2009-01-01

    textabstractIt has been argued that power activates a general tendency to approach whereas powerlessness activates a tendency to inhibit. The assumption is that elevated power involves reward-rich environments, freedom and, as a consequence, triggers an approach-related motivational orientation and attention to rewards. In contrast, reduced power is associated with increased threat, punishment and social constraint and thereby activates inhibition-related motivation. Moreover, approach motiva...

  7. Neural mechanisms underlying ecstasy-related attentional bias.

    Science.gov (United States)

    Roberts, Gloria M P; Garavan, Hugh

    2013-08-30

    Conditioned responses to cues associated with drug taking play a pivotal role in a number of theories of drug addiction. This study examined whether attentional biases towards drug-related cues exist in recreational drug users who predominantly used ecstasy (3,4-methylenedioxymethamphetamine). Experiment 1 compared 30 ecstasy users, 25 cannabis users, and 30 controls in an attentional distraction task in which neutral, evocative, and ecstasy-related pictures were presented within a coloured border, requiring participants to respond as quickly as possible to the border colour. Experiment 2 employed functional magnetic resonance imaging (fMRI) and the attentional distraction task and tested 20 ecstasy users and 20 controls. Experiment 1 revealed significant response speed interference by the ecstasy-related pictures in the ecstasy users only. Experiment 2 revealed increased prefrontal and occipital activity in ecstasy users in all conditions. Activations in response to the ecstasy stimuli in these regions showed an apparent antagonism whereby ecstasy users, relative to controls, showed increased occipital but decreased right prefrontal activation. These results are interpreted to reflect increased visual processing of, and decreased prefrontal control over, the irrelevant but salient ecstasy-related stimuli. These results suggest that right inferior frontal cortex may play an important role in controlling drug-related attentional biases and may thus play an important role in mediating control over drug usage. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  8. Efficient and rapid derivation of primitive neural stem cells and generation of brain subtype neurons from human pluripotent stem cells.

    Science.gov (United States)

    Yan, Yiping; Shin, Soojung; Jha, Balendu Shekhar; Liu, Qiuyue; Sheng, Jianting; Li, Fuhai; Zhan, Ming; Davis, Janine; Bharti, Kapil; Zeng, Xianmin; Rao, Mahendra; Malik, Nasir; Vemuri, Mohan C

    2013-11-01

    Human pluripotent stem cells (hPSCs), including human embryonic stem cells and human induced pluripotent stem cells, are unique cell sources for disease modeling, drug discovery screens, and cell therapy applications. The first step in producing neural lineages from hPSCs is the generation of neural stem cells (NSCs). Current methods of NSC derivation involve the time-consuming, labor-intensive steps of an embryoid body generation or coculture with stromal cell lines that result in low-efficiency derivation of NSCs. In this study, we report a highly efficient serum-free pluripotent stem cell neural induction medium that can induce hPSCs into primitive NSCs (pNSCs) in 7 days, obviating the need for time-consuming, laborious embryoid body generation or rosette picking. The pNSCs expressed the neural stem cell markers Pax6, Sox1, Sox2, and Nestin; were negative for Oct4; could be expanded for multiple passages; and could be differentiated into neurons, astrocytes, and oligodendrocytes, in addition to the brain region-specific neuronal subtypes GABAergic, dopaminergic, and motor neurons. Global gene expression of the transcripts of pNSCs was comparable to that of rosette-derived and human fetal-derived NSCs. This work demonstrates an efficient method to generate expandable pNSCs, which can be further differentiated into central nervous system neurons and glia with temporal, spatial, and positional cues of brain regional heterogeneity. This method of pNSC derivation sets the stage for the scalable production of clinically relevant neural cells for cell therapy applications in good manufacturing practice conditions.

  9. The Use of Convolutional Neural Network in Relating Precipitation to Circulation

    Science.gov (United States)

    Pan, B.; Hsu, K. L.; AghaKouchak, A.; Sorooshian, S.

    2017-12-01

    Precipitation prediction in dynamical weather and climate models depends on 1) the predictability of pressure or geopotential height for the forecasting period and 2) the successive work of interpreting the pressure field in terms of precipitation events. The later task is represented as parameterization schemes in numerical models, where detailed computing inevitably blurs the hidden cause-and-effect relationship in precipitation generation. The "big data" provided by numerical simulation, reanalysis and observation networks requires better causation analysis for people to digest and realize their use. While classic synoptical analysis methods are very-often insufficient for spatially distributed high dimensional data, a Convolutional Neural Network(CNN) is developed here to directly relate precipitation with circulation. Case study carried over west coast United States during boreal winter showed that CNN can locate and capture key pressure zones of different structures to project precipitation spatial distribution with high accuracy across hourly to monthly scales. This direct connection between atmospheric circulation and precipitation offers a probe for attributing precipitation to the coverage, location, intensity and spatial structure of characteristic pressure zones, which can be used for model diagnosis and improvement.

  10. A Combination of Central Pattern Generator-based and Reflex-based Neural Networks for Dynamic, Adaptive, Robust Bipedal Locomotion

    DEFF Research Database (Denmark)

    Di Canio, Giuliano; Larsen, Jørgen Christian; Wörgötter, Florentin

    2016-01-01

    Robotic systems inspired from humans have always been lightening up the curiosity of engineers and scientists. Of many challenges, human locomotion is a very difficult one where a number of different systems needs to interact in order to generate a correct and balanced pattern. To simulate...... the interaction of these systems, implementations with reflexbased or central pattern generator (CPG)-based controllers have been tested on bipedal robot systems. In this paper we will combine the two controller types, into a controller that works with both reflex and CPG signals. We use a reflex-based neural...... network to generate basic walking patterns of a dynamic bipedal walking robot (DACBOT) and then a CPG-based neural network to ensure robust walking behavior...

  11. Beyond GLMs: a generative mixture modeling approach to neural system identification.

    Directory of Open Access Journals (Sweden)

    Lucas Theis

    Full Text Available Generalized linear models (GLMs represent a popular choice for the probabilistic characterization of neural spike responses. While GLMs are attractive for their computational tractability, they also impose strong assumptions and thus only allow for a limited range of stimulus-response relationships to be discovered. Alternative approaches exist that make only very weak assumptions but scale poorly to high-dimensional stimulus spaces. Here we seek an approach which can gracefully interpolate between the two extremes. We extend two frequently used special cases of the GLM-a linear and a quadratic model-by assuming that the spike-triggered and non-spike-triggered distributions can be adequately represented using Gaussian mixtures. Because we derive the model from a generative perspective, its components are easy to interpret as they correspond to, for example, the spike-triggered distribution and the interspike interval distribution. The model is able to capture complex dependencies on high-dimensional stimuli with far fewer parameters than other approaches such as histogram-based methods. The added flexibility comes at the cost of a non-concave log-likelihood. We show that in practice this does not have to be an issue and the mixture-based model is able to outperform generalized linear and quadratic models.

  12. Multilayer Perceptron Neural Networks Model for Meteosat Second Generation SEVIRI Daytime Cloud Masking

    Directory of Open Access Journals (Sweden)

    Alireza Taravat

    2015-02-01

    Full Text Available A multilayer perceptron neural network cloud mask for Meteosat Second Generation SEVIRI (Spinning Enhanced Visible and Infrared Imager images is introduced and evaluated. The model is trained for cloud detection on MSG SEVIRI daytime data. It consists of a multi-layer perceptron with one hidden sigmoid layer, trained with the error back-propagation algorithm. The model is fed by six bands of MSG data (0.6, 0.8, 1.6, 3.9, 6.2 and 10.8 μm with 10 hidden nodes. The multiple-layer perceptrons lead to a cloud detection accuracy of 88.96%, when trained to map two predefined values that classify cloud and clear sky. The network was further evaluated using sixty MSG images taken at different dates. The network detected not only bright thick clouds but also thin or less bright clouds. The analysis demonstrated the feasibility of using machine learning models of cloud detection in MSG SEVIRI imagery.

  13. Informative sensor selection and learning for prediction of lower limb kinematics using generative stochastic neural networks.

    Science.gov (United States)

    Eunsuk Chong; Taejin Choi; Hyungmin Kim; Seung-Jong Kim; Yoha Hwang; Jong Min Lee

    2017-07-01

    We propose a novel approach of selecting useful input sensors as well as learning a mathematical model for predicting lower limb joint kinematics. We applied a feature selection method based on the mutual information called the variational information maximization, which has been reported as the state-of-the-art work among information based feature selection methods. The main difficulty in applying the method is estimating reliable probability density of input and output data, especially when the data are high dimensional and real-valued. We addressed this problem by applying a generative stochastic neural network called the restricted Boltzmann machine, through which we could perform sampling based probability estimation. The mutual informations between inputs and outputs are evaluated in each backward sensor elimination step, and the least informative sensor is removed with its network connections. The entire network is fine-tuned by maximizing conditional likelihood in each step. Experimental results are shown for 4 healthy subjects walking with various speeds, recording 64 sensor measurements including electromyogram, acceleration, and foot-pressure sensors attached on both lower limbs for predicting hip and knee joint angles. For test set of walking with arbitrary speed, our results show that our suggested method can select informative sensors while maintaining a good prediction accuracy.

  14. U-tube steam generator empirical model development and validation using neural networks

    International Nuclear Information System (INIS)

    Parlos, A.G.; Chong, K.T.; Atiya, A.

    1992-01-01

    Empirical modeling techniques that use model structures motivated from neural networks research have proven effective in identifying complex process dynamics. A recurrent multilayer perception (RMLP) network was developed as a nonlinear state-space model structure along with a static learning algorithm for estimating the parameter associated with it. The methods developed were demonstrated by identifying two submodels of a U-tube steam generator (UTSG), each valid around an operating power level. A significant drawback of this approach is the long off-line training times required for the development of even a simplified model of a UTSG. Subsequently, a dynamic gradient descent-based learning algorithm was developed as an accelerated alternative to train an RMLP network for use in empirical modeling of power plants. The two main advantages of this learning algorithm are its ability to consider past error gradient information for future use and the two forward passes associated with its implementation. The enhanced learning capabilities provided by the dynamic gradient descent-based learning algorithm were demonstrated via the case study of a simple steam boiler power plant. In this paper, the dynamic gradient descent-based learning algorithm is used for the development and validation of a complete UTSG empirical model

  15. Developmental Pathway Genes and Neural Plasticity Underlying Emotional Learning and Stress-Related Disorders

    Science.gov (United States)

    Maheau, Marissa E.; Ressler, Kerry J.

    2017-01-01

    The manipulation of neural plasticity as a means of intervening in the onset and progression of stress-related disorders retains its appeal for many researchers, despite our limited success in translating such interventions from the laboratory to the clinic. Given the challenges of identifying individual genetic variants that confer increased risk…

  16. Social power and approach-related neural activity

    NARCIS (Netherlands)

    M.A.S. Boksem (Maarten); R. Smolders (Ruud); D. de Cremer (David)

    2009-01-01

    textabstractIt has been argued that power activates a general tendency to approach whereas powerlessness activates a tendency to inhibit. The assumption is that elevated power involves reward-rich environments, freedom and, as a consequence, triggers an approach-related motivational orientation and

  17. Environmental influences on neural systems of relational complexity

    Directory of Open Access Journals (Sweden)

    Layne eKalbfleisch

    2013-09-01

    Full Text Available Constructivist learning theory contends that we construct knowledge by experience and that environmental context influences learning. To explore this principle, we examined the cognitive process relational complexity (RC, defined as the number of visual dimensions considered during problem solving on a matrix reasoning task and a well-documented measure of mature reasoning capacity. We sought to determine how the visual environment influences RC by examining the influence of color and visual contrast on RC in a neuroimaging task. To specify the contributions of sensory demand and relational integration to reasoning, our participants performed a non-verbal matrix task comprised of color, no-color line, or black-white visual contrast conditions parametrically varied by complexity (relations 0, 1, 2. The use of matrix reasoning is ecologically valid for its psychometric relevance and for its potential to link the processing of psychophysically specific visual properties with various levels of relational complexity during reasoning. The role of these elements is important because matrix tests assess intellectual aptitude based on these seemingly context-less exercises. This experiment is a first step toward examining the psychophysical underpinnings of performance on these types of problems. The importance of this is increased in light of recent evidence that intelligence can be linked to visual discrimination. We submit three main findings. First, color and black-white visual contrast add demand at a basic sensory level, but contributions from color and from black-white visual contrast are dissociable in cortex such that color engages a reasoning heuristic and black-white visual contrast engages a sensory heuristic. Second, color supports contextual sense-making by boosting salience resulting in faster problem solving. Lastly, when visual complexity reaches 2-relations, color and visual contrast relinquish salience to other dimensions of problem

  18. Convolutional neural networks for event-related potential detection: impact of the architecture.

    Science.gov (United States)

    Cecotti, H

    2017-07-01

    The detection of brain responses at the single-trial level in the electroencephalogram (EEG) such as event-related potentials (ERPs) is a difficult problem that requires different processing steps to extract relevant discriminant features. While most of the signal and classification techniques for the detection of brain responses are based on linear algebra, different pattern recognition techniques such as convolutional neural network (CNN), as a type of deep learning technique, have shown some interests as they are able to process the signal after limited pre-processing. In this study, we propose to investigate the performance of CNNs in relation of their architecture and in relation to how they are evaluated: a single system for each subject, or a system for all the subjects. More particularly, we want to address the change of performance that can be observed between specifying a neural network to a subject, or by considering a neural network for a group of subjects, taking advantage of a larger number of trials from different subjects. The results support the conclusion that a convolutional neural network trained on different subjects can lead to an AUC above 0.9 by using an appropriate architecture using spatial filtering and shift invariant layers.

  19. MR-based synthetic CT generation using a deep convolutional neural network method.

    Science.gov (United States)

    Han, Xiao

    2017-04-01

    Interests have been rapidly growing in the field of radiotherapy to replace CT with magnetic resonance imaging (MRI), due to superior soft tissue contrast offered by MRI and the desire to reduce unnecessary radiation dose. MR-only radiotherapy also simplifies clinical workflow and avoids uncertainties in aligning MR with CT. Methods, however, are needed to derive CT-equivalent representations, often known as synthetic CT (sCT), from patient MR images for dose calculation and DRR-based patient positioning. Synthetic CT estimation is also important for PET attenuation correction in hybrid PET-MR systems. We propose in this work a novel deep convolutional neural network (DCNN) method for sCT generation and evaluate its performance on a set of brain tumor patient images. The proposed method builds upon recent developments of deep learning and convolutional neural networks in the computer vision literature. The proposed DCNN model has 27 convolutional layers interleaved with pooling and unpooling layers and 35 million free parameters, which can be trained to learn a direct end-to-end mapping from MR images to their corresponding CTs. Training such a large model on our limited data is made possible through the principle of transfer learning and by initializing model weights from a pretrained model. Eighteen brain tumor patients with both CT and T1-weighted MR images are used as experimental data and a sixfold cross-validation study is performed. Each sCT generated is compared against the real CT image of the same patient on a voxel-by-voxel basis. Comparison is also made with respect to an atlas-based approach that involves deformable atlas registration and patch-based atlas fusion. The proposed DCNN method produced a mean absolute error (MAE) below 85 HU for 13 of the 18 test subjects. The overall average MAE was 84.8 ± 17.3 HU for all subjects, which was found to be significantly better than the average MAE of 94.5 ± 17.8 HU for the atlas-based method. The DCNN

  20. Cognitive flexibility modulates maturation and music-training-related changes in neural sound discrimination.

    Science.gov (United States)

    Saarikivi, Katri; Putkinen, Vesa; Tervaniemi, Mari; Huotilainen, Minna

    2016-07-01

    Previous research has demonstrated that musicians show superior neural sound discrimination when compared to non-musicians, and that these changes emerge with accumulation of training. Our aim was to investigate whether individual differences in executive functions predict training-related changes in neural sound discrimination. We measured event-related potentials induced by sound changes coupled with tests for executive functions in musically trained and non-trained children aged 9-11 years and 13-15 years. High performance in a set-shifting task, indexing cognitive flexibility, was linked to enhanced maturation of neural sound discrimination in both musically trained and non-trained children. Specifically, well-performing musically trained children already showed large mismatch negativity (MMN) responses at a young age as well as at an older age, indicating accurate sound discrimination. In contrast, the musically trained low-performing children still showed an increase in MMN amplitude with age, suggesting that they were behind their high-performing peers in the development of sound discrimination. In the non-trained group, in turn, only the high-performing children showed evidence of an age-related increase in MMN amplitude, and the low-performing children showed a small MMN with no age-related change. These latter results suggest an advantage in MMN development also for high-performing non-trained individuals. For the P3a amplitude, there was an age-related increase only in the children who performed well in the set-shifting task, irrespective of music training, indicating enhanced attention-related processes in these children. Thus, the current study provides the first evidence that, in children, cognitive flexibility may influence age-related and training-related plasticity of neural sound discrimination. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  1. Physiological modules for generating discrete and rhythmic movements: action identification by a dynamic recurrent neural network.

    Science.gov (United States)

    Bengoetxea, Ana; Leurs, Françoise; Hoellinger, Thomas; Cebolla, Ana M; Dan, Bernard; McIntyre, Joseph; Cheron, Guy

    2014-01-01

    In this study we employed a dynamic recurrent neural network (DRNN) in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight movements in each of two workspaces (frontal plane and sagittal plane). We then trained a DRNN to predict the movement of the wrist from information in the EMG signals from seven different muscles. We trained different instances of the same network on a single movement direction, on all four movement directions in a single movement plane, or on all eight possible movement patterns and looked at the ability of the DRNN to generalize and predict movements for trials that were not included in the training set. Within a single movement plane, a DRNN trained on one movement direction was not able to predict movements of the hand for trials in the other three directions, but a DRNN trained simultaneously on all four movement directions could generalize across movement directions within the same plane. Similarly, the DRNN was able to reproduce the kinematics of the hand for both movement planes, but only if it was trained on examples performed in each one. As we will discuss, these results indicate that there are important dynamical constraints on the mapping of EMG to hand movement that depend on both the time sequence of the movement and on the anatomical constraints of the musculoskeletal system. In a second step, we injected EMG signals constructed from different synergies derived by the PCA in order to identify the mechanical significance of each of these components. From these results, one can surmise that discrete-rhythmic movements may be constructed from three different fundamental modules, one regulating the co-activation of all muscles over the time span of the movement and two others elliciting patterns of reciprocal activation operating in orthogonal directions.

  2. Neural Plasticity and Proliferation in the Generation of Antidepressant Effects: Hippocampal Implication

    Directory of Open Access Journals (Sweden)

    Fuencisla Pilar-Cuéllar

    2013-01-01

    Full Text Available It is widely accepted that changes underlying depression and antidepressant-like effects involve not only alterations in the levels of neurotransmitters as monoamines and their receptors in the brain, but also structural and functional changes far beyond. During the last two decades, emerging theories are providing new explanations about the neurobiology of depression and the mechanism of action of antidepressant strategies based on cellular changes at the CNS level. The neurotrophic/plasticity hypothesis of depression, proposed more than a decade ago, is now supported by multiple basic and clinical studies focused on the role of intracellular-signalling cascades that govern neural proliferation and plasticity. Herein, we review the state-of-the-art of the changes in these signalling pathways which appear to underlie both depressive disorders and antidepressant actions. We will especially focus on the hippocampal cellularity and plasticity modulation by serotonin, trophic factors as brain-derived neurotrophic factor (BDNF, and vascular endothelial growth factor (VEGF through intracellular signalling pathways—cAMP, Wnt/β-catenin, and mTOR. Connecting the classic monoaminergic hypothesis with proliferation/neuroplasticity-related evidence is an appealing and comprehensive attempt for improving our knowledge about the neurobiological events leading to depression and associated to antidepressant therapies.

  3. An Exploratory Application of Neural Networks to the Sortie Generation Forecasting Problem

    Science.gov (United States)

    1991-09-01

    research of Dr. David A. Diener, Major, USAF. As the initial research increment to be improved upon by future researchers, this study (1) provides a... David A. Diener, Major, USAF, who virtually transformed my dream of exploring neural network techniques into concrete reality. His talents in...New York: John Wiley & Sons, 1978. Barron R. L., Gilstrap, L. 0., and Shrier , S. "Polynomial al and Neural Networks: Analogies and Engineering

  4. On the relationships between generative encodings, regularity, and learning abilities when evolving plastic artificial neural networks.

    Directory of Open Access Journals (Sweden)

    Paul Tonelli

    Full Text Available A major goal of bio-inspired artificial intelligence is to design artificial neural networks with abilities that resemble those of animal nervous systems. It is commonly believed that two keys for evolving nature-like artificial neural networks are (1 the developmental process that links genes to nervous systems, which enables the evolution of large, regular neural networks, and (2 synaptic plasticity, which allows neural networks to change during their lifetime. So far, these two topics have been mainly studied separately. The present paper shows that they are actually deeply connected. Using a simple operant conditioning task and a classic evolutionary algorithm, we compare three ways to encode plastic neural networks: a direct encoding, a developmental encoding inspired by computational neuroscience models, and a developmental encoding inspired by morphogen gradients (similar to HyperNEAT. Our results suggest that using a developmental encoding could improve the learning abilities of evolved, plastic neural networks. Complementary experiments reveal that this result is likely the consequence of the bias of developmental encodings towards regular structures: (1 in our experimental setup, encodings that tend to produce more regular networks yield networks with better general learning abilities; (2 whatever the encoding is, networks that are the more regular are statistically those that have the best learning abilities.

  5. Differentiation of neurons from neural precursors generated in floating spheres from embryonic stem cells

    Directory of Open Access Journals (Sweden)

    Forrester Jeff

    2009-09-01

    Full Text Available Abstract Background Neural differentiation of embryonic stem (ES cells is usually achieved by induction of ectoderm in embryoid bodies followed by the enrichment of neuronal progenitors using a variety of factors. Obtaining reproducible percentages of neural cells is difficult and the methods are time consuming. Results Neural progenitors were produced from murine ES cells by a combination of nonadherent conditions and serum starvation. Conversion to neural progenitors was accompanied by downregulation of Oct4 and NANOG and increased expression of nestin. ES cells containing a GFP gene under the control of the Sox1 regulatory regions became fluorescent upon differentiation to neural progenitors, and ES cells with a tau-GFP fusion protein became fluorescent upon further differentiation to neurons. Neurons produced from these cells upregulated mature neuronal markers, or differentiated to glial and oligodendrocyte fates. The neurons gave rise to action potentials that could be recorded after application of fixed currents. Conclusion Neural progenitors were produced from murine ES cells by a novel method that induced neuroectoderm cells by a combination of nonadherent conditions and serum starvation, in contrast to the embryoid body method in which neuroectoderm cells must be selected after formation of all three germ layers.

  6. Calculation of the energy provided by a PV generator. Comparative study: Conventional methods vs. artificial neural networks

    International Nuclear Information System (INIS)

    Almonacid, F.; Rus, C.; Perez-Higueras, P.; Hontoria, L.

    2011-01-01

    The use of photovoltaics for electricity generation purposes has recorded one of the largest increases in the field of renewable energies. The energy production of a grid-connected PV system depends on various factors. In a wide sense, it is considered that the annual energy provided by a generator is directly proportional to the annual radiation incident on the plane of the generator and to the installed nominal power. However, a range of factors is influencing the expected outcome by reducing the generation of energy. The aim of this study is to compare the results of four different methods for estimating the annual energy produced by a PV generator: three of them are classical methods and the fourth one is based on an artificial neural network developed by the R and D Group for Solar and Automatic Energy at the University of Jaen. The results obtained shown that the method based on an artificial neural network provides better results than the alternative classical methods in study, mainly due to the fact that this method takes also into account some second order effects, such as low irradiance, angular and spectral effects. -- Research highlights: → It is considered that the annual energy provided by a PV generator is directly proportional to the annual radiation incident on the plane of the generator and to the installed nominal power. → A range of factors are influencing the expected outcome by reducing the generation of energy (mismatch losses, dirt and dust, Ohmic losses,.). → The aim of this study is to compare the results of four different methods for estimating the annual energy produced by a PV generator: three of them are classical methods and the fourth one is based on an artificial neural network. → The results obtained shown that the method based on an artificial neural network provides better results than the alternative classical methods in study. While classical methods have only taken into account temperature losses, the method based in

  7. Age-related difference in the effective neural connectivity associated with probabilistic category learning

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Eun Jin; Cho, Sang Soo; Kim, Hee Jung; Bang, Seong Ae; Park, Hyun Soo; Kim, Yu Kyeong; Kim, Sang Eun [Seoul National Univ. College of Medicine, Seoul (Korea, Republic of)

    2007-07-01

    Although it is well known that explicit memory is affected by the deleterious changes in brain with aging, but effect of aging in implicit memory such as probabilistic category learning (PCL) is not clear. To identify the effect of aging on the neural interaction for successful PCL, we investigated the neural substrates of PCL and the age-related changes of the neural network between these brain regions. 23 young (age, 252 y; 11 males) and 14 elderly (673 y; 7 males) healthy subjects underwent FDG PET during a resting state and 150-trial weather prediction (WP) task. Correlations between the WP hit rates and regional glucose metabolism were assessed using SPM2 (P<0.05 uncorrected). For path analysis, seven brain regions (bilateral middle frontal gyri and putamen, left fusiform gyrus, anterior cingulate and right parahippocampal gyri) were selected based on the results of the correlation analysis. Model construction and path analysis processing were done by AMOS 5.0. The elderly had significantly lower total hit rates than the young (P<0.005). In the correlation analysis, both groups showed similar metabolic correlation in frontal and striatal area. But correlation in the medial temporal lobe (MTL) was found differently by group. In path analysis, the functional networks for the constructed model was accepted (X(2) =0.80, P=0.67) and it proved to be significantly different between groups (X{sub diff}(37) = 142.47, P<0.005), Systematic comparisons of each path revealed that frontal crosscallosal and the frontal to parahippocampal connection were most responsible for the model differences (P<0.05). For the successful PCL, the elderly recruits the basal ganglia implicit memory system but MTL recruitment differs from the young. The inadequate MTL correlation pattern in the elderly is may be caused by the changes of the neural pathway related with explicit memory. These neural changes can explain the decreased performance of PCL in elderly subjects.

  8. Generating Relational Competitive Advantage from Strategic Technological Partnership

    DEFF Research Database (Denmark)

    Hu, Yimei; Zhang, Si; Li, Jizhen

    2012-01-01

    Collaborating with external partners on strategic technological partnerships (STPs) have been popular phenomena for long, which leads new development in existing theories on competitive advantage. Under the relational view, the competitive advantage is jointly generated by alliance firms. Though...... the relational view of competitive advantage has been proposed for more than a decade, few in-depth empirical researches are down within this field, especially case study on R&D strategic alliance from this perspective. Based on these considerations, we investigate an STP between a Danish transnational...... corporation and a Chinese private firm aiming to understand how to generate relational competitive from an STP? Based on the explorative case study, we find that there are three key processes related to relational competitive advantage: partner selection, relational rents generation and relational rents...

  9. Adolescent girls' neural response to reward mediates the relation between childhood financial disadvantage and depression.

    Science.gov (United States)

    Romens, Sarah E; Casement, Melynda D; McAloon, Rose; Keenan, Kate; Hipwell, Alison E; Guyer, Amanda E; Forbes, Erika E

    2015-11-01

    Children who experience socioeconomic disadvantage are at heightened risk for developing depression; however, little is known about neurobiological mechanisms underlying this association. Low socioeconomic status (SES) during childhood may confer risk for depression through its stress-related effects on the neural circuitry associated with processing monetary rewards. In a prospective study, we examined the relationships among the number of years of household receipt of public assistance from age 5-16 years, neural activation during monetary reward anticipation and receipt at age 16, and depression symptoms at age 16 in 123 girls. Number of years of household receipt of public assistance was positively associated with heightened response in the medial prefrontal cortex during reward anticipation, and this heightened neural response mediated the relationship between socioeconomic disadvantage and current depression symptoms, controlling for past depression. Chronic exposure to socioeconomic disadvantage in childhood may alter neural circuitry involved in reward anticipation in adolescence, which in turn may confer risk for depression. © 2015 Association for Child and Adolescent Mental Health.

  10. Neural Basis of Intrinsic Motivation: Evidence from Event-Related Potentials.

    Science.gov (United States)

    Jin, Jia; Yu, Liping; Ma, Qingguo

    2015-01-01

    Human intrinsic motivation is of great importance in human behavior. However, although researchers have focused on this topic for decades, its neural basis was still unclear. The current study employed event-related potentials to investigate the neural disparity between an interesting stop-watch (SW) task and a boring watch-stop task (WS) to understand the neural mechanisms of intrinsic motivation. Our data showed that, in the cue priming stage, the cue of the SW task elicited smaller N2 amplitude than that of the WS task. Furthermore, in the outcome feedback stage, the outcome of the SW task induced smaller FRN amplitude and larger P300 amplitude than that of the WS task. These results suggested that human intrinsic motivation did exist and that it can be detected at the neural level. Furthermore, intrinsic motivation could be quantitatively indexed by the amplitude of ERP components, such as N2, FRN, and P300, in the cue priming stage or feedback stage. Quantitative measurements would also be convenient for intrinsic motivation to be added as a candidate social factor in the construction of a machine learning model.

  11. Photovoltaic generator. Estimate of the energy produced by neural networks; Generador fotovoltaico. Estimacion de la energia producida mediante redes neuronales

    Energy Technology Data Exchange (ETDEWEB)

    Almonacid, F.; Rus, C.; Perez-Higueras, P.; Hontoria, L.

    2010-07-01

    Despite the great technological advances in photovoltaic and in particular in network-connected systems, efforts are still required in research, technological development and innovation (i + d + i) must be aimed primarily at addressing the different system parts. one aspect that can help achieve this goal is majorette estimation methods of energy produced by photovoltaic generators. There are a number of cases resulting in a decrease of the expected energy. In this paper we will compare a standard method widely used in the estimation of the power of the photovoltaic generator with another novel method, developed at the University of Jaen, based on artificial neural networks (ANN). (Author) 9 refs.

  12. Distinct Neural Substrates for Maintaining Locations and Spatial Relations in Working Memory

    Directory of Open Access Journals (Sweden)

    Kara J Blacker

    2016-11-01

    Full Text Available Previous work has demonstrated a distinction between maintenance of two types of spatial information in working memory (WM: spatial locations and spatial relations. While a body of work has investigated the neural mechanisms of sensory-based information like spatial locations, little is known about how spatial relations are maintained in WM. In two experiments, we used fMRI to investigate the involvement of early visual cortex in the maintenance of spatial relations in WM. In both experiments, we found less quadrant-specific BOLD activity in visual cortex when a single spatial relation, compared to a single spatial location, was held in WM. Also across both experiments, we found a consistent set of brain regions that were differentially activated during maintenance of locations versus relations. Maintaining a location, compared to a relation, was associated with greater activity in typical spatial WM regions like posterior parietal cortex and prefrontal regions. Whereas maintaining a relation, compared to a location, was associated with greater activity in the parahippocampal gyrus and precuneus/retrosplenial cortex. Further, in Experiment 2 we manipulated WM load and included trials where participants had to maintain three spatial locations or relations. Under this high load condition, the regions sensitive to locations versus relations were somewhat different than under low load. We also identified regions that were sensitive to load specifically for location or relation maintenance, as well as overlapping regions sensitive to load more generally. These results suggest that the neural substrates underlying WM maintenance of spatial locations and relations are distinct from one another and that the neural representations of these distinct types of spatial information change with load.

  13. Calibration of Relative Humidity Sensors using a Dew Point Generator

    OpenAIRE

    Brooks, Milo

    2010-01-01

    A relative humidity sensor can be calibrated using a dew point generator to continuously supply an air stream of known constant humidity and a temperature chamber to control the dew point and ambient temperature.

  14. Large-scale generation of human iPSC-derived neural stem cells/early neural progenitor cells and their neuronal differentiation.

    Science.gov (United States)

    D'Aiuto, Leonardo; Zhi, Yun; Kumar Das, Dhanjit; Wilcox, Madeleine R; Johnson, Jon W; McClain, Lora; MacDonald, Matthew L; Di Maio, Roberto; Schurdak, Mark E; Piazza, Paolo; Viggiano, Luigi; Sweet, Robert; Kinchington, Paul R; Bhattacharjee, Ayantika G; Yolken, Robert; Nimgaonka, Vishwajit L; Nimgaonkar, Vishwajit L

    2014-01-01

    Induced pluripotent stem cell (iPSC)-based technologies offer an unprecedented opportunity to perform high-throughput screening of novel drugs for neurological and neurodegenerative diseases. Such screenings require a robust and scalable method for generating large numbers of mature, differentiated neuronal cells. Currently available methods based on differentiation of embryoid bodies (EBs) or directed differentiation of adherent culture systems are either expensive or are not scalable. We developed a protocol for large-scale generation of neuronal stem cells (NSCs)/early neural progenitor cells (eNPCs) and their differentiation into neurons. Our scalable protocol allows robust and cost-effective generation of NSCs/eNPCs from iPSCs. Following culture in neurobasal medium supplemented with B27 and BDNF, NSCs/eNPCs differentiate predominantly into vesicular glutamate transporter 1 (VGLUT1) positive neurons. Targeted mass spectrometry analysis demonstrates that iPSC-derived neurons express ligand-gated channels and other synaptic proteins and whole-cell patch-clamp experiments indicate that these channels are functional. The robust and cost-effective differentiation protocol described here for large-scale generation of NSCs/eNPCs and their differentiation into neurons paves the way for automated high-throughput screening of drugs for neurological and neurodegenerative diseases.

  15. Doctor, Teacher, and Stethoscope: Neural Representation of Different Types of Semantic Relations.

    Science.gov (United States)

    Xu, Yangwen; Wang, Xiaosha; Wang, Xiaoying; Men, Weiwei; Gao, Jia-Hong; Bi, Yanchao

    2018-03-28

    Concepts can be related in many ways. They can belong to the same taxonomic category (e.g., "doctor" and "teacher," both in the category of people) or be associated with the same event context (e.g., "doctor" and "stethoscope," both associated with medical scenarios). How are these two major types of semantic relations coded in the brain? We constructed stimuli from three taxonomic categories (people, manmade objects, and locations) and three thematic categories (school, medicine, and sports) and investigated the neural representations of these two dimensions using representational similarity analyses in human participants (10 men and nine women). In specific regions of interest, the left anterior temporal lobe (ATL) and the left temporoparietal junction (TPJ), we found that, whereas both areas had significant effects of taxonomic information, the taxonomic relations had stronger effects in the ATL than in the TPJ ("doctor" and "teacher" closer in ATL neural activity), with the reverse being true for thematic relations ("doctor" and "stethoscope" closer in TPJ neural activity). A whole-brain searchlight analysis revealed that widely distributed regions, mainly in the left hemisphere, represented the taxonomic dimension. Interestingly, the significant effects of the thematic relations were only observed after the taxonomic differences were controlled for in the left TPJ, the right superior lateral occipital cortex, and other frontal, temporal, and parietal regions. In summary, taxonomic grouping is a primary organizational dimension across distributed brain regions, with thematic grouping further embedded within such taxonomic structures. SIGNIFICANCE STATEMENT How are concepts organized in the brain? It is well established that concepts belonging to the same taxonomic categories (e.g., "doctor" and "teacher") share neural representations in specific brain regions. How concepts are associated in other manners (e.g., "doctor" and "stethoscope," which are thematically

  16. Generation of Regionally Specific Neural Progenitor Cells (NPCs) and Neurons from Human Pluripotent Stem Cells (hPSCs).

    Science.gov (United States)

    Cutts, Josh; Brookhouser, Nicholas; Brafman, David A

    2016-01-01

    Neural progenitor cells (NPCs) derived from human pluripotent stem cells (hPSCs) are a multipotent cell population capable of long-term expansion and differentiation into a variety of neuronal subtypes. As such, NPCs have tremendous potential for disease modeling, drug screening, and regenerative medicine. Current methods for the generation of NPCs results in cell populations homogenous for pan-neural markers such as SOX1 and SOX2 but heterogeneous with respect to regional identity. In order to use NPCs and their neuronal derivatives to investigate mechanisms of neurological disorders and develop more physiologically relevant disease models, methods for generation of regionally specific NPCs and neurons are needed. Here, we describe a protocol in which exogenous manipulation of WNT signaling, through either activation or inhibition, during neural differentiation of hPSCs, promotes the formation of regionally homogenous NPCs and neuronal cultures. In addition, we provide methods to monitor and characterize the efficiency of hPSC differentiation to these regionally specific cell identities.

  17. Generation of Regionally Specified Neural Progenitors and Functional Neurons from Human Embryonic Stem Cells under Defined Conditions

    Directory of Open Access Journals (Sweden)

    Agnete Kirkeby

    2012-06-01

    Full Text Available To model human neural-cell-fate specification and to provide cells for regenerative therapies, we have developed a method to generate human neural progenitors and neurons from human embryonic stem cells, which recapitulates human fetal brain development. Through the addition of a small molecule that activates canonical WNT signaling, we induced rapid and efficient dose-dependent specification of regionally defined neural progenitors ranging from telencephalic forebrain to posterior hindbrain fates. Ten days after initiation of differentiation, the progenitors could be transplanted to the adult rat striatum, where they formed neuron-rich and tumor-free grafts with maintained regional specification. Cells patterned toward a ventral midbrain (VM identity generated a high proportion of authentic dopaminergic neurons after transplantation. The dopamine neurons showed morphology, projection pattern, and protein expression identical to that of human fetal VM cells grafted in parallel. VM-patterned but not forebrain-patterned neurons released dopamine and reversed motor deficits in an animal model of Parkinson's disease.

  18. Stator current harmonics evolution by neural network method based on CFE/SS algorithm for ACEC generator of Rey Power Plant

    International Nuclear Information System (INIS)

    Soleymani, S.; Ranjbar, A.M.; Mirabedini, H.

    2001-01-01

    One method for on-line fault diagnosis in synchronous generator is stator current harmonics analysis. Then artificial neural network is considered in this paper in order to evaluate stator current harmonics in different loads. Training set of artificial neural network is made ready by generator modeling, finite element method and state space model. Many points from generator capability curve are used in order to complete this set. Artificial neural network which is used in this paper is a percept ron network with a single hidden layer, Eight hidden neurons and back propagation algorithm. Results are indicated that the trained artificial neural network can identify stator current harmonics for arbitrary load from the capability curve. The error is less than 10% in comparison with values obtained directly from the CFE-SS algorithm. The rating parameters of modeled generator are 43950 (kV A), 11(KV), 3000 (rpm), 50 (H Z), (P F=0.8)

  19. Neural Connectivity and Immunocytochemical Studies of Anatomical Sites Related to Nauseogenic and Emetic Reflexes

    Science.gov (United States)

    Fox, Robert A. (Principal Investigator)

    1992-01-01

    The studies conducted in this research project examined several aspects of neuroanatomical structures and neurochemical processes related to motion sickness in animal models. A principle objective of these studies was to investigate neurochemical changes in the central nervous system that are related to motion sickness with the objective of defining neural mechanisms important to this malady. For purposes of exposition, the studies and research finding have been classified into five categories. These are: immunoreactivity in the brainstem, vasopressin effects, lesion studies of area postrema, role of the vagus nerve, and central nervous system structure related to adaptation to microgravity.

  20. Multi-Layer Artificial Neural Networks Based MPPT-Pitch Angle Control of a Tidal Stream Generator

    Directory of Open Access Journals (Sweden)

    Khaoula Ghefiri

    2018-04-01

    Full Text Available Artificial intelligence technologies are widely investigated as a promising technique for tackling complex and ill-defined problems. In this context, artificial neural networks methodology has been considered as an effective tool to handle renewable energy systems. Thereby, the use of Tidal Stream Generator (TSG systems aim to provide clean and reliable electrical power. However, the power captured from tidal currents is highly disturbed due to the swell effect and the periodicity of the tidal current phenomenon. In order to improve the quality of the generated power, this paper focuses on the power smoothing control. For this purpose, a novel Artificial Neural Network (ANN is investigated and implemented to provide the proper rotational speed reference and the blade pitch angle. The ANN supervisor adequately switches the system in variable speed and power limitation modes. In order to recover the maximum power from the tides, a rotational speed control is applied to the rotor side converter following the Maximum Power Point Tracking (MPPT generated from the ANN block. In case of strong tidal currents, a pitch angle control is set based on the ANN approach to keep the system operating within safe limits. Two study cases were performed to test the performance of the output power. Simulation results demonstrate that the implemented control strategies achieve a smoothed generated power in the case of swell disturbances.

  1. Generation of Induced Pluripotent Stem Cells and Neural Stem/Progenitor Cells from Newborns with Spina Bifida Aperta.

    Science.gov (United States)

    Bamba, Yohei; Nonaka, Masahiro; Sasaki, Natsu; Shofuda, Tomoko; Kanematsu, Daisuke; Suemizu, Hiroshi; Higuchi, Yuichiro; Pooh, Ritsuko K; Kanemura, Yonehiro; Okano, Hideyuki; Yamasaki, Mami

    2017-12-01

    We established induced pluripotent stem cells (iPSCs) and neural stem/progenitor cells (NSPCs) from three newborns with spina bifida aperta (SBa) using clinically practical methods. We aimed to develop stem cell lines derived from newborns with SBa for future therapeutic use. SBa is a common congenital spinal cord abnormality that causes defects in neurological and urological functions. Stem cell transplantation therapies are predicted to provide beneficial effects for patients with SBa. However, the availability of appropriate cell sources is inadequate for clinical use because of their limited accessibility and expandability, as well as ethical issues. Fibroblast cultures were established from small fragments of skin obtained from newborns with SBa during SBa repair surgery. The cultured cells were transfected with episomal plasmid vectors encoding reprogramming factors necessary for generating iPSCs. These cells were then differentiated into NSPCs by chemical compound treatment, and NSPCs were expanded using neurosphere technology. We successfully generated iPSC lines from the neonatal dermal fibroblasts of three newborns with SBa. We confirmed that these lines exhibited the characteristics of human pluripotent stem cells. We successfully generated NSPCs from all SBa newborn-derived iPSCs with a combination of neural induction and neurosphere technology. We successfully generated iPSCs and iPSC-NSPCs from surgical samples obtained from newborns with SBa with the goal of future clinical use in patients with SBa.

  2. Effect of Explicit Evaluation on Neural Connectivity Related to Listening to Unfamiliar Music

    Science.gov (United States)

    Liu, Chao; Brattico, Elvira; Abu-jamous, Basel; Pereira, Carlos S.; Jacobsen, Thomas; Nandi, Asoke K.

    2017-01-01

    People can experience different emotions when listening to music. A growing number of studies have investigated the brain structures and neural connectivities associated with perceived emotions. However, very little is known about the effect of an explicit act of judgment on the neural processing of emotionally-valenced music. In this study, we adopted the novel consensus clustering paradigm, called binarisation of consensus partition matrices (Bi-CoPaM), to study whether and how the conscious aesthetic evaluation of the music would modulate brain connectivity networks related to emotion and reward processing. Participants listened to music under three conditions – one involving a non-evaluative judgment, one involving an explicit evaluative aesthetic judgment, and one involving no judgment at all (passive listening only). During non-evaluative attentive listening we obtained auditory-limbic connectivity whereas when participants were asked to decide explicitly whether they liked or disliked the music excerpt, only two clusters of intercommunicating brain regions were found: one including areas related to auditory processing and action observation, and the other comprising higher-order structures involved with visual processing. Results indicate that explicit evaluative judgment has an impact on the neural auditory-limbic connectivity during affective processing of music. PMID:29311874

  3. DNA methylation-based forensic age prediction using artificial neural networks and next generation sequencing.

    Science.gov (United States)

    Vidaki, Athina; Ballard, David; Aliferi, Anastasia; Miller, Thomas H; Barron, Leon P; Syndercombe Court, Denise

    2017-05-01

    The ability to estimate the age of the donor from recovered biological material at a crime scene can be of substantial value in forensic investigations. Aging can be complex and is associated with various molecular modifications in cells that accumulate over a person's lifetime including epigenetic patterns. The aim of this study was to use age-specific DNA methylation patterns to generate an accurate model for the prediction of chronological age using data from whole blood. In total, 45 age-associated CpG sites were selected based on their reported age coefficients in a previous extensive study and investigated using publicly available methylation data obtained from 1156 whole blood samples (aged 2-90 years) analysed with Illumina's genome-wide methylation platforms (27K/450K). Applying stepwise regression for variable selection, 23 of these CpG sites were identified that could significantly contribute to age prediction modelling and multiple regression analysis carried out with these markers provided an accurate prediction of age (R 2 =0.92, mean absolute error (MAE)=4.6 years). However, applying machine learning, and more specifically a generalised regression neural network model, the age prediction significantly improved (R 2 =0.96) with a MAE=3.3 years for the training set and 4.4 years for a blind test set of 231 cases. The machine learning approach used 16 CpG sites, located in 16 different genomic regions, with the top 3 predictors of age belonged to the genes NHLRC1, SCGN and CSNK1D. The proposed model was further tested using independent cohorts of 53 monozygotic twins (MAE=7.1 years) and a cohort of 1011 disease state individuals (MAE=7.2 years). Furthermore, we highlighted the age markers' potential applicability in samples other than blood by predicting age with similar accuracy in 265 saliva samples (R 2 =0.96) with a MAE=3.2 years (training set) and 4.0 years (blind test). In an attempt to create a sensitive and accurate age prediction test, a next

  4. Plasmid-based generation of induced neural stem cells from adult human fibroblasts

    Directory of Open Access Journals (Sweden)

    Philipp Capetian

    2016-10-01

    Full Text Available Direct reprogramming from somatic to neural cell types has become an alternative to induced pluripotent stem cells. Most protocols employ viral expression systems, posing the risk of random genomic integration. Recent developments led to plasmid-based protocols, lowering this risk. However, these protocols either relied on continuous presence of a variety of small molecules or were only able to reprogram murine cells. We therefore established a reprogramming protocol based on vectors containing the Epstein-Barr virus (EBV-derived oriP/EBNA1 as well as the defined expression factors Oct3/4, Sox2, Klf4, L-myc, Lin28, and a small hairpin directed against p53. We employed a defined neural medium in combination with the neurotrophins bFGF, EGF and FGF4 for cultivation without the addition of small molecules. After reprogramming, cells demonstrated a temporary increase in the expression of endogenous Oct3/4. We obtained induced neural stem cells (iNSC 30 days after transfection. In contrast to previous results, plasmid vectors as well as a residual expression of reprogramming factors remained detectable in all cell lines. Cells showed a robust differentiation into neuronal (72% and glial cells (9% astrocytes, 6% oligodendrocytes. Despite the temporary increase of pluripotency-associated Oct3/4 expression during reprogramming, we did not detect pluripotent stem cells or non-neural cells in culture (except occasional residual fibroblasts. Neurons showed electrical activity and functional glutamatergic synapses. Our results demonstrate that reprogramming adult human fibroblasts to iNSC by plasmid vectors and basic neural medium without small molecules is possible and feasible. However, a full set of pluripotency-associated transcription factors may indeed result in the acquisition of a transient (at least partial pluripotent intermediate during reprogramming. In contrast to previous reports, the EBV-based plasmid system remained present and active inside

  5. The wandering mood: psychological and neural determinants of rest-related negative affect

    Directory of Open Access Journals (Sweden)

    Michal eGruberger

    2013-12-01

    Full Text Available Rest related negative affect (RRNA has gained scientific interest in the past decade. However, it is mostly studied within the context of mind-wandering (MW, and the relevance of other psychological and neural aspects of the resting state to its' occurrence has never been studied. Several indications associate RRNA with internally directed attention, yet the nature of this relation remains largely unknown. Moreover, the role of neural networks associated with rest related phenomenology - the default mode (DMN, executive (EXE and salience (SAL networks, has not been studied in this context. To this end, we explored two 5- (baseline and 15-minute resting-state simultaneous fMRI-EEG scans of 29 participants. As vigilance has been shown to affect attention, and thus its availability for inward allocation, EEG-based vigilance levels were computed for each participant. Questionnaires for affective assessment were administered before and after scans, and retrospective reports of MW were additionally collected. Results revealed increased negative affect following rest, but only among participants who retained high vigilance levels. Among low-vigilance participants, changes in negative affect were negligible, despite reports of MW occurrence in both groups. In addition, in the high-vigilance group only, a significant increase in functional connectivity (FC levels was found between the DMN-related ventral anterior cingulate cortex (ACC,associated with emotional processing, and the EXE-related dorsal ACC, associated with monitoring of self and other's behavior. These heightened FC levels further correlated with reported negative affect among this group. Taken together, these results demonstrate that, rather than an unavoidable outcome of the resting state, RRNA depends on internal allocation of attention at rest. Results are discussed in terms of two rest-related possible scenarios which defer in mental and neural processing, and subsequently, in the

  6. The wandering mood: psychological and neural determinants of rest-related negative affect.

    Science.gov (United States)

    Gruberger, Michal; Maron-Katz, Adi; Sharon, Haggai; Hendler, Talma; Ben-Simon, Eti

    2013-01-01

    Rest related negative affect (RRNA) has gained scientific interest in the past decade. However, it is mostly studied within the context of mind-wandering (MW), and the relevance of other psychological and neural aspects of the resting state to its' occurrence has never been studied. Several indications associate RRNA with internally directed attention, yet the nature of this relation remains largely unknown. Moreover, the role of neural networks associated with rest related phenomenology - the default mode (DMN), executive (EXE), and salience (SAL) networks, has not been studied in this context. To this end, we explored two 5 (baseline) and 15-minute resting-state simultaneous fMRI-EEG scans of 29 participants. As vigilance has been shown to affect attention, and thus its availability for inward allocation, EEG-based vigilance levels were computed for each participant. Questionnaires for affective assessment were administered before and after scans, and retrospective reports of MW were additionally collected. Results revealed increased negative affect following rest, but only among participants who retained high vigilance levels. Among low-vigilance participants, changes in negative affect were negligible, despite reports of MW occurrence in both groups. In addition, in the high-vigilance group only, a significant increase in functional connectivity (FC) levels was found between the DMN-related ventral anterior cingulate cortex (ACC), associated with emotional processing, and the EXE-related dorsal ACC, associated with monitoring of self and other's behavior. These heightened FC levels further correlated with reported negative affect among this group. Taken together, these results demonstrate that, rather than an unavoidable outcome of the resting state, RRNA depends on internal allocation of attention at rest. Results are discussed in terms of two rest-related possible scenarios which defer in mental and neural processing, and subsequently, in the occurrence of

  7. On the estimation of stellar parameters with uncertainty prediction from Generative Artificial Neural Networks: application to Gaia RVS simulated spectra

    Science.gov (United States)

    Dafonte, C.; Fustes, D.; Manteiga, M.; Garabato, D.; Álvarez, M. A.; Ulla, A.; Allende Prieto, C.

    2016-10-01

    Aims: We present an innovative artificial neural network (ANN) architecture, called Generative ANN (GANN), that computes the forward model, that is it learns the function that relates the unknown outputs (stellar atmospheric parameters, in this case) to the given inputs (spectra). Such a model can be integrated in a Bayesian framework to estimate the posterior distribution of the outputs. Methods: The architecture of the GANN follows the same scheme as a normal ANN, but with the inputs and outputs inverted. We train the network with the set of atmospheric parameters (Teff, log g, [Fe/H] and [α/ Fe]), obtaining the stellar spectra for such inputs. The residuals between the spectra in the grid and the estimated spectra are minimized using a validation dataset to keep solutions as general as possible. Results: The performance of both conventional ANNs and GANNs to estimate the stellar parameters as a function of the star brightness is presented and compared for different Galactic populations. GANNs provide significantly improved parameterizations for early and intermediate spectral types with rich and intermediate metallicities. The behaviour of both algorithms is very similar for our sample of late-type stars, obtaining residuals in the derivation of [Fe/H] and [α/ Fe] below 0.1 dex for stars with Gaia magnitude Grvs satellite. Conclusions: Uncertainty estimation of computed astrophysical parameters is crucial for the validation of the parameterization itself and for the subsequent exploitation by the astronomical community. GANNs produce not only the parameters for a given spectrum, but a goodness-of-fit between the observed spectrum and the predicted one for a given set of parameters. Moreover, they allow us to obtain the full posterior distribution over the astrophysical parameters space once a noise model is assumed. This can be used for novelty detection and quality assessment.

  8. Promotion of public awareness relating nuclear power in young generation

    International Nuclear Information System (INIS)

    Kobayashi, Yoko

    2011-01-01

    Although nuclear power presents problems of waste, safety and non-proliferation, many people understand that it is an essential energy for addressing the global climate and reducing CO2. However, a vague negative-image to the radiation and nuclear power is deep-rooted among the public. Young generation is not an exception. It is very important to transfer many information from the experienced generation in the industry to young generations. In this paper, the research that applied the information intelligence to nuclear power, which involves of the nuclear fuel cycle, and the communication related activities for the social acceptance and improvement. (author)

  9. Age-Related Reversals in Neural Recruitment across Memory Retrieval Phases.

    Science.gov (United States)

    Ford, Jaclyn H; Kensinger, Elizabeth A

    2017-05-17

    Over the last several decades, neuroimaging research has identified age-related neural changes that occur during cognitive tasks. These changes are used to help researchers identify functional changes that contribute to age-related impairments in cognitive performance. One commonly reported example of such a change is an age-related decrease in the recruitment of posterior sensory regions coupled with an increased recruitment of prefrontal regions across multiple cognitive tasks. This shift is often described as a compensatory recruitment of prefrontal regions due to age-related sensory-processing deficits in posterior regions. However, age is not only associated with spatial shifts in recruitment, but also with temporal shifts, in which younger and older adults recruit the same neural region at different points in a task trial. The current study examines the possible contribution of temporal modifications in the often-reported posterior-anterior shift. Participants, ages 19-85, took part in a memory retrieval task with a protracted retrieval trial consisting of an initial memory search phase and a subsequent detail elaboration phase. Age-related neural patterns during search replicated prior reports of age-related decreases in posterior recruitment and increases in prefrontal recruitment. However, during the later elaboration phase, the same posterior regions were associated with age-related increases in activation. Further, ROI and functional connectivity results suggest that these posterior regions function similarly during search and elaboration. These results suggest that the often-reported posterior-anterior shift may not reflect the inability of older adults to engage in sensory processing, but rather a change in when they recruit this processing. SIGNIFICANCE STATEMENT The current study provides evidence that the often-reported posterior-anterior shift in aging may not reflect a global sensory-processing deficit, as has often been reported, but rather a

  10. Comparison of 2D and 3D neural induction methods for the generation of neural progenitor cells from human induced pluripotent stem cells

    DEFF Research Database (Denmark)

    Chandrasekaran, Abinaya; Avci, Hasan; Ochalek, Anna

    2017-01-01

    Neural progenitor cells (NPCs) from human induced pluripotent stem cells (hiPSCs) are frequently induced using 3D culture methodologies however, it is unknown whether spheroid-based (3D) neural induction is actually superior to monolayer (2D) neural induction. Our aim was to compare the efficiency......), cortical layer (TBR1, CUX1) and glial markers (SOX9, GFAP, AQP4). Electron microscopy demonstrated that both methods resulted in morphologically similar neural rosettes. However, quantification of NPCs derived from 3D neural induction exhibited an increase in the number of PAX6/NESTIN double positive cells...... the electrophysiological properties between the two induction methods. In conclusion, 3D neural induction increases the yield of PAX6+/NESTIN+ cells and gives rise to neurons with longer neurites, which might be an advantage for the production of forebrain cortical neurons, highlighting the potential of 3D neural...

  11. In a distinguishing spacetime the horismos relation generates the causal relation

    International Nuclear Information System (INIS)

    Minguzzi, E

    2009-01-01

    It is proved that in a distinguishing spacetime the horismos relation E + = J + /I + generates the causal relation J + . In other words two causally related events are joined by a chain of horismotically related events, or again, the causal relation is the smallest transitive relation containing the horismos relation. The result is sharp in the sense that the distinction cannot be weakened to future or past distinction. Finally, it is proved that a spacetime in which the horismos relation generates the causal relation is necessarily non-total imprisoning.

  12. Specific neural basis of Chinese idioms processing: an event-related functional MRI study

    International Nuclear Information System (INIS)

    Chen Shaoqi; Zhang Yanzhen; Xiao Zhuangwei; Zhang Xuexin

    2007-01-01

    Objective: To address the neural basis of Chinese idioms processing with different kinds of stimuli using an event-related fMRI design. Methods: Sixteen native Chinese speakers were asked to perform a semantic decision task during fMRI scanning. Three kinds of stimuli were used: Real idioms (Real-idiom condition); Literally plausible phrases (Pseudo-idiom condition, the last character of a real idiom was replaced by a character with similar meaning); Literally implausible strings (Non-idiom condition, the last character of a real idiom was replaced by a character with unrelated meaning). Reaction time and correct rate were recorded at the same time. Results: The error rate was 2.6%, 5.2% and 0.9% (F=3.51, P 0.05) for real idioms, pseudo-idioms and wrong idioms, respectively. Similar neural network was activated in all of the three conditions. However, the right hippocampus was only activated in the real idiom condition, and significant activations were found in anterior portion of left inferior frontal gyms (BA47) in real-and pseudo-idiom conditions, but not in non-idiom condition. Conclusion: The right hippocampus plays a specific role in the particular wording of the Chinese idioms. And the left anterior inferior frontal gyms (BA47) may be engaged in the semantic processing of Chinese idioms. The results support the notion that there were specific neural bases for Chinese idioms processing. (authors)

  13. Transient Global Amnesia following Neural and Cardiac Angiography May Be Related to Ischemia

    Directory of Open Access Journals (Sweden)

    Hongzhou Duan

    2016-01-01

    Full Text Available Introduction. Transient global amnesia (TGA following angiography is rare, and the pathogenesis has not been illustrated clearly till now. The aim of this research is to explore the pathogenesis of TGA following angiography by analyzing our data and reviewing the literature. Methods. We retrospectively studied 20836 cases with angiography in our hospital between 2007 and 2015 and found 9 cases with TGA following angiography. The data of these 9 cases were analyzed. Results. We found all 9 cases with TGA following neural angiography (5 in 4360 or cardiac angiography (4 in 8817 and no case with TGA following peripheral angiography (0 in 7659. Statistical difference was found when comparing the neural and cardiac angiography group with peripheral group (p=0.022. Two cases with TGA were confirmed with small acute infarctions in hippocampus after angiography. This might be related to the microemboli which were rushed into vertebral artery following blood flow during neural angiography or cardiac angiography. There was no statistical difference when comparing the different approaches for angiography (p=0.82 and different contrast agents (p=0.619. Conclusion. Based on the positive findings of imaging study and our analysis, we speculate that ischemia in the medial temporal lobe with the involvement of the hippocampus might be an important reason of TGA following angiography.

  14. Relation of obesity to neural activation in response to food commercials.

    Science.gov (United States)

    Gearhardt, Ashley N; Yokum, Sonja; Stice, Eric; Harris, Jennifer L; Brownell, Kelly D

    2014-07-01

    Adolescents view thousands of food commercials annually, but the neural response to food advertising and its association with obesity is largely unknown. This study is the first to examine how neural response to food commercials differs from other stimuli (e.g. non-food commercials and television show) and to explore how this response may differ by weight status. The blood oxygen level-dependent functional magnetic resonance imaging activation was measured in 30 adolescents ranging from lean to obese in response to food and non-food commercials imbedded in a television show. Adolescents exhibited greater activation in regions implicated in visual processing (e.g. occipital gyrus), attention (e.g. parietal lobes), cognition (e.g. temporal gyrus and posterior cerebellar lobe), movement (e.g. anterior cerebellar cortex), somatosensory response (e.g. postcentral gyrus) and reward [e.g. orbitofrontal cortex and anterior cingulate cortex (ACC)] during food commercials. Obese participants exhibited less activation during food relative to non-food commercials in neural regions implicated in visual processing (e.g. cuneus), attention (e.g. posterior cerebellar lobe), reward (e.g. ventromedial prefrontal cortex and ACC) and salience detection (e.g. precuneus). Obese participants did exhibit greater activation in a region implicated in semantic control (e.g. medial temporal gyrus). These findings may inform current policy debates regarding the impact of food advertising to minors. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  15. Power to punish norm violations affects the neural processes of fairness-related decision making

    Directory of Open Access Journals (Sweden)

    Xuemei eCheng

    2015-12-01

    Full Text Available Punishing norm violations is considered an important motive during rejection of unfair offers in the Ultimatum Game (UG. The present study investigates the impact of the power to punish norm violations on people’s responses to unfairness and associated neural correlates. In the UG condition participants had the power to punish norm violations, while an alternate condition, the Impunity Game (IG, was presented where participants had no power to punish norm violations since rejection only reduced the responder’s income to zero. Results showed that unfair offers were rejected more often in UG compared to IG. At the neural level, anterior insula and dorsal anterior cingulate cortex were more active when participants received and rejected unfair offers in both UG and IG. Moreover, greater dorsolateral prefrontal cortex activity was observed when participants rejected than accepted unfair offers in UG but not in IG. Ventromedial prefrontal cortex activation was higher in UG than IG when unfair offers were accepted as well as when rejecting unfair offers in IG as opposed to UG. Taken together, our results demonstrate that the power to punish norm violations affects not only people’s behavioral responses to unfairness but also the neural correlates of the fairness-related social decision-making process.

  16. Neural response to catecholamine depletion in remitted bulimia nervosa: Relation to depression and relapse.

    Science.gov (United States)

    Mueller, Stefanie Verena; Mihov, Yoan; Federspiel, Andrea; Wiest, Roland; Hasler, Gregor

    2017-07-01

    Bulimia nervosa has been associated with a dysregulated catecholamine system. Nevertheless, the influence of this dysregulation on bulimic symptoms, on neural activity, and on the course of the illness is not clear yet. An instructive paradigm for directly investigating the relationship between catecholaminergic functioning and bulimia nervosa has involved the behavioral and neural responses to experimental catecholamine depletion. The purpose of this study was to examine the neural substrate of catecholaminergic dysfunction in bulimia nervosa and its relationship to relapse. In a randomized, double-blind and crossover study design, catecholamine depletion was achieved by using the oral administration of alpha-methyl-paratyrosine (AMPT) over 24 h in 18 remitted bulimic (rBN) and 22 healthy (HC) female participants. Cerebral blood flow (CBF) was measured using a pseudo continuous arterial spin labeling (pCASL) sequence. In a follow-up telephone interview, bulimic relapse was assessed. Following AMPT, rBN participants revealed an increased vigor reduction and CBF decreases in the pallidum and posterior midcingulate cortex (pMCC) relative to HC participants showing no CBF changes in these regions. These results indicated that the pallidum and the pMCC are the functional neural correlates of the dysregulated catecholamine system in bulimia nervosa. Bulimic relapse was associated with increased depressive symptoms and CBF reduction in the hippocampus/parahippocampal gyrus following catecholamine depletion. AMPT-induced increased CBF in this region predicted staying in remission. These findings demonstrated the importance of depressive symptoms and the stress system in the course of bulimia nervosa. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  17. Neural networks

    International Nuclear Information System (INIS)

    Denby, Bruce; Lindsey, Clark; Lyons, Louis

    1992-01-01

    The 1980s saw a tremendous renewal of interest in 'neural' information processing systems, or 'artificial neural networks', among computer scientists and computational biologists studying cognition. Since then, the growth of interest in neural networks in high energy physics, fueled by the need for new information processing technologies for the next generation of high energy proton colliders, can only be described as explosive

  18. A Computational Model of Torque Generation: Neural, Contractile, Metabolic and Musculoskeletal Components

    Science.gov (United States)

    Callahan, Damien M.; Umberger, Brian R.; Kent-Braun, Jane A.

    2013-01-01

    The pathway of voluntary joint torque production includes motor neuron recruitment and rate-coding, sarcolemmal depolarization and calcium release by the sarcoplasmic reticulum, force generation by motor proteins within skeletal muscle, and force transmission by tendon across the joint. The direct source of energetic support for this process is ATP hydrolysis. It is possible to examine portions of this physiologic pathway using various in vivo and in vitro techniques, but an integrated view of the multiple processes that ultimately impact joint torque remains elusive. To address this gap, we present a comprehensive computational model of the combined neuromuscular and musculoskeletal systems that includes novel components related to intracellular bioenergetics function. Components representing excitatory drive, muscle activation, force generation, metabolic perturbations, and torque production during voluntary human ankle dorsiflexion were constructed, using a combination of experimentally-derived data and literature values. Simulation results were validated by comparison with torque and metabolic data obtained in vivo. The model successfully predicted peak and submaximal voluntary and electrically-elicited torque output, and accurately simulated the metabolic perturbations associated with voluntary contractions. This novel, comprehensive model could be used to better understand impact of global effectors such as age and disease on various components of the neuromuscular system, and ultimately, voluntary torque output. PMID:23405245

  19. Entropy generation in a condenser and related correlations

    Directory of Open Access Journals (Sweden)

    Askowski Rafał

    2015-06-01

    Full Text Available The paper presents an analysis of relations describing entropy generation in a condenser of a steam unit. Connections between entropy generation, condenser ratio, and heat exchanger effectiveness, as well as relations implied by them are shown. Theoretical considerations allowed to determine limits of individual parameters which describe the condenser operation. Various relations for average temperature of the cold fluid were compared. All the proposed relations were verified against data obtained using a simulator and actual measurement data from a 200 MW unit condenser. Based on data from a simulator it was examined how the sum of entropy rates, steam condenser effectiveness, terminal temperature difference and condenser ratio vary with the change in the inlet cooling water temperature, mass flow rate of steam and the cooling water mass flow rate.

  20. Neural circuitry of abdominal pain-related fear learning and reinstatement in irritable bowel syndrome.

    Science.gov (United States)

    Icenhour, A; Langhorst, J; Benson, S; Schlamann, M; Hampel, S; Engler, H; Forsting, M; Elsenbruch, S

    2015-01-01

    Altered pain anticipation likely contributes to disturbed central pain processing in chronic pain conditions like irritable bowel syndrome (IBS), but the learning processes shaping the expectation of pain remain poorly understood. We assessed the neural circuitry mediating the formation, extinction, and reactivation of abdominal pain-related memories in IBS patients compared to healthy controls (HC) in a differential fear conditioning paradigm. During fear acquisition, predictive visual cues (CS(+)) were paired with rectal distensions (US), while control cues (CS(-)) were presented unpaired. During extinction, only CSs were presented. Subsequently, memory reactivation was assessed with a reinstatement procedure involving unexpected USs. Using functional magnetic resonance imaging, group differences in neural activation to CS(+) vs CS(-) were analyzed, along with skin conductance responses (SCR), CS valence, CS-US contingency, state anxiety, salivary cortisol, and alpha-amylase activity. The contribution of anxiety symptoms was addressed in covariance analyses. Fear acquisition was altered in IBS, as indicated by more accurate contingency awareness, greater CS-related valence change, and enhanced CS(+)-induced differential activation of prefrontal cortex and amygdala. IBS patients further revealed enhanced differential cingulate activation during extinction and greater differential hippocampal activation during reinstatement. Anxiety affected neural responses during memory formation and reinstatement. Abdominal pain-related fear learning and memory processes are altered in IBS, mediated by amygdala, cingulate cortex, prefrontal areas, and hippocampus. Enhanced reinstatement may contribute to hypervigilance and central pain amplification, especially in anxious patients. Preventing a 'relapse' of learned fear utilizing extinction-based interventions may be a promising treatment goal in IBS. © 2014 John Wiley & Sons Ltd.

  1. A formula relating infinitesimal Backlund transformations to hierarchy generating operators

    International Nuclear Information System (INIS)

    Hou, B.Y.; Tu, G.Z.

    1982-12-01

    Let u'=Bsub(eta)u and l be, respectively, the elementary Backlund transformation and hierarchy generating operators for the AKNS equations. It is shown that (dB/d eta)(Bsub(eta)) - 1 =σ 3 /(l-eta). A similar formula relating to the general NxN matrix spectral problem is also derived. (author)

  2. Lie-theoretic generating relations of two variable Laguerre polynomials

    International Nuclear Information System (INIS)

    Khan, Subuhi; Yasmin, Ghazala

    2002-07-01

    Generating relations involving two variable Lagneire polynonuals L n (x, y) are derived. The process involves the construction of a three dimensional Lie algebra isomorphic to special linear algebra sl(2) with the help of Weisner's method by giving suitable interpretations to the index n of the polynomials L n (x, y). (author)

  3. Excess lead in the neural retina in age-related macular degeneration.

    Science.gov (United States)

    Erie, Jay C; Good, Jonathan A; Butz, John A

    2009-12-01

    To measure lead and cadmium in retinal tissues of human donor eyes with and without age-related macular degeneration (AMD). Laboratory investigation. Lead and cadmium concentrations in retinal tissues (neural retina and retinal pigment epithelium [RPE]-choroid complex) in 25 subjects with AMD (50 donor eyes) and 36 normal subjects (72 donor eyes) were determined by using inductively coupled plasma-mass spectrometry. Severity of AMD was graded by using color fundus photographs and the Minnesota Grading System. Differences in metal concentrations were compared by using Wilcoxon rank-sum tests. The neural retinas of subjects with AMD had increased lead concentrations (median, 12.0 ng/g; 25% to 75% interquartile range, 8 to 18 ng/g; n = 25) compared with normal subjects (median, 8.0 ng/g; 25% to 75% interquartile range, 0 to 11 ng/g; P = .04; n = 36). There was no difference in lead concentration in the RPE-choroid complex between subjects with AMD (median, 198 ng/g; 25% to 75% interquartile range, 87 to 381 ng/g) and normal subjects (median, 172 ng/g; 25% to 75% interquartile range, 100 to 288 ng/g; P = .25). Cadmium concentration in the neural retina (median, 0.9 microg/g; 25% to 75% interquartile range, 0.7 to 1.8 microg/g) and RPE-choroid complex (median, 2.2 microg/g; 25% to 75% interquartile range, 1.8 to 3.7 microg/g) in subjects with AMD was not different from concentrations in the neural retina (median, 0.9 microg/g; 25% to 75% interquartile range, 0.7 to 1.4 microg/g; P = .32) and RPE-choroid complex (median, 1.5 microg/g; 25% to 75% interquartile range, 0.9 to 2.5 microg/g; P = .12) of normal subjects. AMD is associated with excess lead in the neural retina, and this relationship suggests that metal homeostasis in AMD eyes is different from normal.

  4. The structure of relation algebras generated by relativizations

    CERN Document Server

    Givant, Steven R

    1994-01-01

    The foundation for an algebraic theory of binary relations was laid by De Morgan, Peirce, and Schröder during the second half of the nineteenth century. Modern development of the subject as a theory of abstract algebras, called "relation algebras", was undertaken by Tarski and his students. This book aims to analyze the structure of relation algebras that are generated by relativized subalgebras. As examples of their potential for applications, the main results are used to establish representation theorems for classes of relation algebras and to prove existence and uniqueness theorems for simple closures (i.e., for minimal simple algebras containing a given family of relation algebras as relativized subalgebras). This book is well written and accessible to those who are not specialists in this area. In particular, it contains two introductory chapters on the arithmetic and the algebraic theory of relation algebras. This book is suitable for use in graduate courses on algebras of binary relations or algebraic...

  5. Neural network-based voltage regulator for an isolated asynchronous generator supplying three-phase four-wire loads

    Energy Technology Data Exchange (ETDEWEB)

    Singh, Bhim; Kasal, Gaurav Kumar [Department of Electrical Engineering, Indian Institute of Technology, Delhi, Hauz-Khas, New Delhi 110016 (India)

    2008-06-15

    This paper deals with a neural network-based solid state voltage controller for an isolated asynchronous generator (IAG) driven by constant speed prime mover like diesel engine, bio-gas or gasoline engine and supplying three-phase four-wire loads. The proposed control scheme uses an indirect current control and a fast adaptive linear element (adaline) based neural network reference current extractor, which extracts the real positive sequence current component without any phase shift. The neutral current of the source is also compensated by using three single-phase bridge configuration of IGBT (insulated gate bipolar junction transistor) based voltage source converter (VSC) along-with single-phase transformer having self-supported dc bus. The proposed controller provides the functions as a voltage regulator, a harmonic eliminator, a neutral current compensator, and a load balancer. The proposed isolated electrical system with its controller is modeled and simulated in MATLAB along with Simulink and PSB (Power System Block set) toolboxes. The simulated results are presented to demonstrate the capability of an isolated asynchronous generating system driven by a constant speed prime mover for feeding three-phase four-wire loads. (author)

  6. Handedness is related to neural mechanisms underlying hemispheric lateralization of face processing

    Science.gov (United States)

    Frässle, Stefan; Krach, Sören; Paulus, Frieder Michel; Jansen, Andreas

    2016-06-01

    While the right-hemispheric lateralization of the face perception network is well established, recent evidence suggests that handedness affects the cerebral lateralization of face processing at the hierarchical level of the fusiform face area (FFA). However, the neural mechanisms underlying differential hemispheric lateralization of face perception in right- and left-handers are largely unknown. Using dynamic causal modeling (DCM) for fMRI, we aimed to unravel the putative processes that mediate handedness-related differences by investigating the effective connectivity in the bilateral core face perception network. Our results reveal an enhanced recruitment of the left FFA in left-handers compared to right-handers, as evidenced by more pronounced face-specific modulatory influences on both intra- and interhemispheric connections. As structural and physiological correlates of handedness-related differences in face processing, right- and left-handers varied with regard to their gray matter volume in the left fusiform gyrus and their pupil responses to face stimuli. Overall, these results describe how handedness is related to the lateralization of the core face perception network, and point to different neural mechanisms underlying face processing in right- and left-handers. In a wider context, this demonstrates the entanglement of structurally and functionally remote brain networks, suggesting a broader underlying process regulating brain lateralization.

  7. Learning to Generate Sequences with Combination of Hebbian and Non-hebbian Plasticity in Recurrent Spiking Neural Networks.

    Science.gov (United States)

    Panda, Priyadarshini; Roy, Kaushik

    2017-01-01

    Synaptic Plasticity, the foundation for learning and memory formation in the human brain, manifests in various forms. Here, we combine the standard spike timing correlation based Hebbian plasticity with a non-Hebbian synaptic decay mechanism for training a recurrent spiking neural model to generate sequences. We show that inclusion of the adaptive decay of synaptic weights with standard STDP helps learn stable contextual dependencies between temporal sequences, while reducing the strong attractor states that emerge in recurrent models due to feedback loops. Furthermore, we show that the combined learning scheme suppresses the chaotic activity in the recurrent model substantially, thereby enhancing its' ability to generate sequences consistently even in the presence of perturbations.

  8. Neural activations are related to body-shape, anxiety, and outcomes in adolescent anorexia nervosa.

    Science.gov (United States)

    Xu, Jie; Harper, Jessica A; Van Enkevort, Erin A; Latimer, Kelsey; Kelley, Urszula; McAdams, Carrie J

    2017-04-01

    Anorexia nervosa (AN) is an illness that frequently begins during adolescence and involves weight loss. Two groups of adolescent girls (AN-A, weight-recovered following AN) and (HC-A, healthy comparison) completed a functional magnetic resonance imaging task involving social evaluations, allowing comparison of neural activations during self-evaluations, friend-evaluations, and perspective-taking self-evaluations. Although the two groups were not different in their whole-brain activations, anxiety and body shape concerns were correlated with neural activity in a priori regions of interest. A cluster in medial prefrontal cortex and the dorsal anterior cingulate correlated with the body shape questionnaire; subjects with more body shape concerns used this area less during self than friend evaluations. A cluster in medial prefrontal cortex and the cingulate also correlated with anxiety such that more anxiety was associated with engagement when disagreeing rather than agreeing with social terms during self-evaluations. This data suggests that differences in the utilization of frontal brain regions during social evaluations may contribute to both anxiety and body shape concerns in adolescents with AN. Clinical follow-up was obtained, allowing exploration of whether brain function early in course of disease relates to illness trajectory. The adolescents successful in recovery used the posterior cingulate and precuneus more for friend than self evaluations than the adolescents that remained ill, suggesting that neural differences related to social evaluations may provide clinical predictive value. Utilization of both MPFC and the precuneus during social and self evaluations may be a key biological component for achieving sustained weight-recovery in adolescents with AN. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Reduced reward-related neural response to mimicry in individuals with autism.

    Science.gov (United States)

    Hsu, Chun-Ting; Neufeld, Janina; Chakrabarti, Bhismadev

    2018-03-01

    Mimicry is a facilitator of social bonds in humans, from infancy. This facilitation is made possible through changing the reward value of social stimuli; for example, we like and affiliate more with people who mimic us. Autism spectrum disorders (ASD) are marked by difficulties in forming social bonds. In this study, we investigate whether the reward-related neural response to being mimicked is altered in individuals with ASD, using a simple conditioning paradigm. Multiple studies in humans and nonhuman primates have established a crucial role for the ventral striatal (VS) region in responding to rewards. In this study, adults with ASD and matched controls first underwent a conditioning task outside the scanner, where they were mimicked by one face and 'anti-mimicked' by another. In the second part, participants passively viewed the conditioned faces in a 3T MRI scanner using a multi-echo sequence. The differential neural response towards mimicking vs. anti-mimicking faces in the VS was tested for group differences as well as an association with self-reported autistic traits. Multiple regression analysis revealed lower left VS response to mimicry (mimicking > anti-mimicking faces) in the ASD group compared to controls. The VS response to mimicry was negatively correlated with autistic traits across the whole sample. Our results suggest that for individuals with ASD and high autistic traits, being mimicked is associated with lower reward-related neural response. This result points to a potential mechanism underlying the difficulties reported by many of individuals with ASD in building social rapport. © 2017 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  10. Performance assessment of electric power generations using an adaptive neural network algorithm and fuzzy DEA

    Energy Technology Data Exchange (ETDEWEB)

    Javaheri, Zahra

    2010-09-15

    Modeling, evaluating and analyzing performance of Iranian thermal power plants is the main goal of this study which is based on multi variant methods analysis. These methods include fuzzy DEA and adaptive neural network algorithm. At first, we determine indicators, then data is collected, next we obtained values of ranking and efficiency by Fuzzy DEA, Case study is thermal power plants In view of the fact that investment to establish on power plant is very high, and maintenance of power plant causes an expensive expenditure, moreover using fossil fuel effected environment hence optimum produce of current power plants is important.

  11. A model of microsaccade-related neural responses induced by short-term depression in thalamocortical synapses

    Directory of Open Access Journals (Sweden)

    Wujie eYuan

    2013-04-01

    Full Text Available Microsaccades during fixation have been suggested to counteract visual fading. Recent experi- ments have also observed microsaccade-related neural responses from cellular record, scalp elec- troencephalogram (EEG and functional magnetic resonance imaging (fMRI. The underlying mechanism, however, is not yet understood and highly debated. It has been proposed that the neural activity of primary visual cortex (V1 is a crucial component for counteracting visual adaptation. In this paper, we use computational modeling to investigate how short-term depres- sion (STD in thalamocortical synapses might affect the neural responses of V1 in the presence of microsaccades. Our model not only gives a possible synaptic explanation for microsaccades in counteracting visual fading, but also reproduces several features in experimental findings. These modeling results suggest that STD in thalamocortical synapses plays an important role in microsaccade-related neural responses and the model may be useful for further investigation of behavioral properties and functional roles of microsaccades.

  12. A model of microsaccade-related neural responses induced by short-term depression in thalamocortical synapses

    Science.gov (United States)

    Yuan, Wu-Jie; Dimigen, Olaf; Sommer, Werner; Zhou, Changsong

    2013-01-01

    Microsaccades during fixation have been suggested to counteract visual fading. Recent experiments have also observed microsaccade-related neural responses from cellular record, scalp electroencephalogram (EEG), and functional magnetic resonance imaging (fMRI). The underlying mechanism, however, is not yet understood and highly debated. It has been proposed that the neural activity of primary visual cortex (V1) is a crucial component for counteracting visual adaptation. In this paper, we use computational modeling to investigate how short-term depression (STD) in thalamocortical synapses might affect the neural responses of V1 in the presence of microsaccades. Our model not only gives a possible synaptic explanation for microsaccades in counteracting visual fading, but also reproduces several features in experimental findings. These modeling results suggest that STD in thalamocortical synapses plays an important role in microsaccade-related neural responses and the model may be useful for further investigation of behavioral properties and functional roles of microsaccades. PMID:23630494

  13. The missing link: Mothers’ neural response to infant cry related to infant attachment behaviors

    Science.gov (United States)

    Laurent, Heidemarie K.; Ablow, Jennifer C.

    2012-01-01

    This study addresses a gap in the attachment literature by investigating maternal neural response to cry related to infant attachment classifications and behaviors. Twenty-two primiparous mothers and their 18-month old infants completed the Strange Situation Procedure (SS) to elicit attachment behaviors. During a separate functional MRI session, mothers were exposed to their own infant’s cry sound, as well as an unfamiliar infant’s cry and control sound. Maternal neural response to own infant cry related to both overall attachment security and specific infant behaviors. Mothers of less secure infants maintained greater activation to their cry in left parahippocampal and amygdala regions and the right posterior insula. consistent with a negative schematic response bias. Mothers of infants exhibiting more avoidant or contact maintaining behaviors during the SS showed diminished response across left prefrontal, parietal, and cerebellar areas involved in attentional processing and cognitive control. Mothers of infants exhibiting more disorganized behavior showed reduced response in bilateral temporal and subcallosal areas relevant to social cognition and emotion regulation. No differences by attachment classification were found. Implications for attachment transmission models are discussed. PMID:22982277

  14. The missing link: mothers' neural response to infant cry related to infant attachment behaviors.

    Science.gov (United States)

    Laurent, Heidemarie K; Ablow, Jennifer C

    2012-12-01

    This study addresses a gap in the attachment literature by investigating maternal neural response to cry related to infant attachment classifications and behaviors. Twenty-two primiparous mothers and their 18-month old infants completed the Strange Situation (SS) procedure to elicit attachment behaviors. During a separate functional MRI session, mothers were exposed to their own infant's cry sound, as well as an unfamiliar infant's cry and control sound. Maternal neural response to own infant cry related to both overall attachment security and specific infant behaviors. Mothers of less secure infants maintained greater activation to their cry in left parahippocampal and amygdala regions and the right posterior insula consistent with a negative schematic response bias. Mothers of infants exhibiting more avoidant or contact maintaining behaviors during the SS showed diminished response across left prefrontal, parietal, and cerebellar areas involved in attentional processing and cognitive control. Mothers of infants exhibiting more disorganized behavior showed reduced response in bilateral temporal and subcallosal areas relevant to social cognition and emotion regulation. No differences by attachment classification were found. Implications for attachment transmission models are discussed. Copyright © 2012 Elsevier Inc. All rights reserved.

  15. Cognitive control in adolescence: neural underpinnings and relation to self-report behaviors.

    Directory of Open Access Journals (Sweden)

    Jessica R Andrews-Hanna

    Full Text Available Adolescence is commonly characterized by impulsivity, poor decision-making, and lack of foresight. However, the developmental neural underpinnings of these characteristics are not well established.To test the hypothesis that these adolescent behaviors are linked to under-developed proactive control mechanisms, the present study employed a hybrid block/event-related functional Magnetic Resonance Imaging (fMRI Stroop paradigm combined with self-report questionnaires in a large sample of adolescents and adults, ranging in age from 14 to 25. Compared to adults, adolescents under-activated a set of brain regions implicated in proactive top-down control across task blocks comprised of difficult and easy trials. Moreover, the magnitude of lateral prefrontal activity in adolescents predicted self-report measures of impulse control, foresight, and resistance to peer pressure. Consistent with reactive compensatory mechanisms to reduced proactive control, older adolescents exhibited elevated transient activity in regions implicated in response-related interference resolution.Collectively, these results suggest that maturation of cognitive control may be partly mediated by earlier development of neural systems supporting reactive control and delayed development of systems supporting proactive control. Importantly, the development of these mechanisms is associated with cognitive control in real-life behaviors.

  16. Dissociating neural variability related to stimulus quality and response times in perceptual decision-making.

    Science.gov (United States)

    Bode, Stefan; Bennett, Daniel; Sewell, David K; Paton, Bryan; Egan, Gary F; Smith, Philip L; Murawski, Carsten

    2018-03-01

    According to sequential sampling models, perceptual decision-making is based on accumulation of noisy evidence towards a decision threshold. The speed with which a decision is reached is determined by both the quality of incoming sensory information and random trial-by-trial variability in the encoded stimulus representations. To investigate those decision dynamics at the neural level, participants made perceptual decisions while functional magnetic resonance imaging (fMRI) was conducted. On each trial, participants judged whether an image presented under conditions of high, medium, or low visual noise showed a piano or a chair. Higher stimulus quality (lower visual noise) was associated with increased activation in bilateral medial occipito-temporal cortex and ventral striatum. Lower stimulus quality was related to stronger activation in posterior parietal cortex (PPC) and dorsolateral prefrontal cortex (DLPFC). When stimulus quality was fixed, faster response times were associated with a positive parametric modulation of activation in medial prefrontal and orbitofrontal cortex, while slower response times were again related to more activation in PPC, DLPFC and insula. Our results suggest that distinct neural networks were sensitive to the quality of stimulus information, and to trial-to-trial variability in the encoded stimulus representations, but that reaching a decision was a consequence of their joint activity. Copyright © 2018 Elsevier Ltd. All rights reserved.

  17. A face a mother could love: depression-related maternal neural responses to infant emotion faces.

    Science.gov (United States)

    Laurent, Heidemarie K; Ablow, Jennifer C

    2013-01-01

    Depressed mothers show negatively biased responses to their infants' emotional bids, perhaps due to faulty processing of infant cues. This study is the first to examine depression-related differences in mothers' neural response to their own infant's emotion faces, considering both effects of perinatal depression history and current depressive symptoms. Primiparous mothers (n = 22), half of whom had a history of major depressive episodes (with one episode occurring during pregnancy and/or postpartum), were exposed to images of their own and unfamiliar infants' joy and distress faces during functional neuroimaging. Group differences (depression vs. no-depression) and continuous effects of current depressive symptoms were tested in relation to neural response to own infant emotion faces. Compared to mothers with no psychiatric diagnoses, those with depression showed blunted responses to their own infant's distress faces in the dorsal anterior cingulate cortex. Mothers with higher levels of current symptomatology showed reduced responses to their own infant's joy faces in the orbitofrontal cortex and insula. Current symptomatology also predicted lower responses to own infant joy-distress in left-sided prefrontal and insula/striatal regions. These deficits in self-regulatory and motivational response circuits may help explain parenting difficulties in depressed mothers.

  18. Striatal Activity and Reward Relativity: Neural Signals Encoding Dynamic Outcome Valuation.

    Science.gov (United States)

    Webber, Emily S; Mankin, David E; Cromwell, Howard C

    2016-01-01

    The striatum is a key brain region involved in reward processing. Striatal activity has been linked to encoding reward magnitude and integrating diverse reward outcome information. Recent work has supported the involvement of striatum in the valuation of outcomes. The present work extends this idea by examining striatal activity during dynamic shifts in value that include different levels and directions of magnitude disparity. A novel task was used to produce diverse relative reward effects on a chain of instrumental action. Rats ( Rattus norvegicus ) were trained to respond to cues associated with specific outcomes varying by food pellet magnitude. Animals were exposed to single-outcome sessions followed by mixed-outcome sessions, and neural activity was compared among identical outcome trials from the different behavioral contexts. Results recording striatal activity show that neural responses to different task elements reflect incentive contrast as well as other relative effects that involve generalization between outcomes or possible influences of outcome variety. The activity that was most prevalent was linked to food consumption and post-food consumption periods. Relative encoding was sensitive to magnitude disparity. A within-session analysis showed strong contrast effects that were dependent upon the outcome received in the immediately preceding trial. Significantly higher numbers of responses were found in ventral striatum linked to relative outcome effects. Our results support the idea that relative value can incorporate diverse relationships, including comparisons from specific individual outcomes to general behavioral contexts. The striatum contains these diverse relative processes, possibly enabling both a higher information yield concerning value shifts and a greater behavioral flexibility.

  19. Neural Correlates of Drug-Related Attentional Bias in Heroin Dependence

    Directory of Open Access Journals (Sweden)

    Qinglin Zhao

    2018-01-01

    Full Text Available The attention of drug-dependent persons tends to be captured by stimuli associated with drug consumption. This involuntary cognitive process is considered as attentional bias (AB. AB has been hypothesized to have causal effects on drug abuse and drug relapse, but its underlying neural mechanisms are still unclear. This study investigated the neural basis of AB in abstinent heroin addicts (AHAs, combining event-related potential (ERP analysis and source localization techniques. Electroencephalography data were collected in 21 abstinent heroin addicts and 24 age- and gender-matched healthy controls (HCs during a dot-probe task. In the task, a pair of drug-related image and neutral image was presented randomly in left and right side of the cross fixation, followed by a dot probe replacing one of the images. Behaviorally, AHAs had shorter reaction times (RTs for the congruent condition compared to the incongruent condition, whereas this was not the case in the HCs. This finding demonstrated the presence of AB towards drug cues in AHAs. Furthermore, the image-evoked ERPs in AHAs had significant shorter P1 latency compared to HCs, as well as larger N1, N2, and P2 amplitude, suggesting that drug-related stimuli might capture attention early and overall require more attentional resources in AHAs. The target-related P3 had significantly shorter latency and lower amplitude in the congruent than incongruent condition in AHAs compared to HCs. Moreover, source localization of ERP components revealed increased activity for AHAs as compared to HCs in the dorsal posterior cingulate cortex (dPCC, superior parietal lobule and inferior frontal gyrus (IFG for image-elicited responses, and decreased activity in the occipital and the medial parietal lobes for target-elicited responses. Overall, the results of our study confirmed that AHAs may exhibit AB in drug-related contexts, and suggested that the bias might be related to an abnormal neural activity, both in

  20. Artificial Neural Networks as an Architectural Design Tool-Generating New Detail Forms Based On the Roman Corinthian Order Capital

    Science.gov (United States)

    Radziszewski, Kacper

    2017-10-01

    The following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital. During the experiment, as an input training data set, five local geometry parameters combined has given the best results: Theta, Pi, Rho in spherical coordinate system based on the capital volume centroid, followed by Z value of the Cartesian coordinate system and a distance from vertical planes created based on the capital symmetry. Additionally during the experiment, artificial neural network hidden layers optimal count and structure was found, giving results of the error below 0.2% for the mentioned before input parameters. Once successfully trained artificial network, was able to mimic the details composition on any other geometry type given. Despite of calculating the transformed geometry locally and separately for each of the thousands of surface points, system could create visually attractive and diverse, complex patterns. Designed tool, based on the supervised learning method of machine learning, gives possibility of generating new architectural forms- free of the designer’s imagination bounds. Implementing the infinitely broad computational methods of machine learning, or Artificial Intelligence in general, not only could accelerate and simplify the design process, but give an opportunity to explore never seen before, unpredictable forms or everyday architectural practice solutions.

  1. Neural network radiative transfer solvers for the generation of high resolution solar irradiance spectra parameterized by cloud and aerosol parameters

    International Nuclear Information System (INIS)

    Taylor, M.; Kosmopoulos, P.G.; Kazadzis, S.; Keramitsoglou, I.; Kiranoudis, C.T.

    2016-01-01

    This paper reports on the development of a neural network (NN) model for instantaneous and accurate estimation of solar radiation spectra and budgets geared toward satellite cloud data using a ≈2.4 M record, high-spectral resolution look up table (LUT) generated with the radiative transfer model libRadtran. Two NN solvers, one for clear sky conditions dominated by aerosol and one for cloudy skies, were trained on a normally-distributed and multiparametric subset of the LUT that spans a very broad class of atmospheric and meteorological conditions as inputs with corresponding high resolution solar irradiance target spectra as outputs. The NN solvers were tested by feeding them with a large (10 K record) “off-grid” random subset of the LUT spanning the training data space, and then comparing simulated outputs with target values provided by the LUT. The NN solvers demonstrated a capability to interpolate accurately over the entire multiparametric space. Once trained, the NN solvers allow for high-speed estimation of solar radiation spectra with high spectral resolution (1 nm) and for a quantification of the effect of aerosol and cloud optical parameters on the solar radiation budget without the need for a massive database. The cloudy sky NN solver was applied to high spatial resolution (54 K pixel) cloud data extracted from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the geostationary Meteosat Second Generation 3 (MSG3) satellite and demonstrated that coherent maps of spectrally-integrated global horizontal irradiance at this resolution can be produced on the order of 1 min. - Highlights: • Neural network radiative transfer solvers for generation of solar irradiance spectra. • Sensitivity analysis of irradiance spectra with respect to aerosol and cloud parameters. • Regional maps of total global horizontal irradiance for cloudy sky conditions. • Regional solar radiation maps produced directly from MSG3/SEVIRI satellite inputs.

  2. Artificial neural Network-Based modeling and monitoring of photovoltaic generator

    Directory of Open Access Journals (Sweden)

    H. MEKKI

    2015-03-01

    Full Text Available In this paper, an artificial neural network based-model (ANNBM is introduced for partial shading detection losses in photovoltaic (PV panel. A Multilayer Perceptron (MLP is used to estimate the electrical outputs (current and voltage of the photovoltaic module using the external meteorological data: solar irradiation G (W/m2 and the module temperature T (°C. Firstly, a database of the BP150SX photovoltaic module operating without any defect has been used to train the considered MLP. Subsequently, in the first case of this study, the developed model is used to estimate the output current and voltage of the PV module considering the partial shading effect. Results confirm the good ability of the ANNBM to detect the partial shading effect in the photovoltaic module with logical accuracy. The proposed strategy could also be used for the online monitoring and supervision of PV modules.

  3. Convolutional neural network using generated data for SAR ATR with limited samples

    Science.gov (United States)

    Cong, Longjian; Gao, Lei; Zhang, Hui; Sun, Peng

    2018-03-01

    Being able to adapt all weather at all times, it has been a hot research topic that using Synthetic Aperture Radar(SAR) for remote sensing. Despite all the well-known advantages of SAR, it is hard to extract features because of its unique imaging methodology, and this challenge attracts the research interest of traditional Automatic Target Recognition(ATR) methods. With the development of deep learning technologies, convolutional neural networks(CNNs) give us another way out to detect and recognize targets, when a huge number of samples are available, but this premise is often not hold, when it comes to monitoring a specific type of ships. In this paper, we propose a method to enhance the performance of Faster R-CNN with limited samples to detect and recognize ships in SAR images.

  4. Segment convolutional neural networks (Seg-CNNs) for classifying relations in clinical notes.

    Science.gov (United States)

    Luo, Yuan; Cheng, Yu; Uzuner, Özlem; Szolovits, Peter; Starren, Justin

    2018-01-01

    We propose Segment Convolutional Neural Networks (Seg-CNNs) for classifying relations from clinical notes. Seg-CNNs use only word-embedding features without manual feature engineering. Unlike typical CNN models, relations between 2 concepts are identified by simultaneously learning separate representations for text segments in a sentence: preceding, concept1, middle, concept2, and succeeding. We evaluate Seg-CNN on the i2b2/VA relation classification challenge dataset. We show that Seg-CNN achieves a state-of-the-art micro-average F-measure of 0.742 for overall evaluation, 0.686 for classifying medical problem-treatment relations, 0.820 for medical problem-test relations, and 0.702 for medical problem-medical problem relations. We demonstrate the benefits of learning segment-level representations. We show that medical domain word embeddings help improve relation classification. Seg-CNNs can be trained quickly for the i2b2/VA dataset on a graphics processing unit (GPU) platform. These results support the use of CNNs computed over segments of text for classifying medical relations, as they show state-of-the-art performance while requiring no manual feature engineering. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  5. Neural correlates of age-related decline and compensation in visual attention capacity

    DEFF Research Database (Denmark)

    Wiegand, Iris; Töllner, Thomas; Dyrholm, Mads

    2014-01-01

    -individual differences in K. Moreover, both parameters were selectively related to two further ERP waves in older age: The anterior N1 was reduced for older participants with lower processing speed, indicating that age-related loss of attentional resources slows encoding. An enhanced right-central positivity (RCP......We identified neural correlates of declined and preserved basic visual attention functions in aging individuals based on Bundesen’s ‘Theory of Visual Attention’ (TVA). In an inter-individual difference approach, we contrasted electrophysiology of higher- and lower-performing younger and older......) was found only for older participants with high storage capacity, suggesting compensatory recruitment for retaining vSTM performance. Together, our results demonstrate that attentional capacity in older age depends on both preservation and successful reorganization of the underlying brain circuits...

  6. Relative Permittivity of Carbon Dioxide + Ethanol Mixtures prediction by means of Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Gonzalo Astray

    2014-07-01

    Full Text Available CO2 + ethanol mixtures have a huge scientific interest and enormous relevance for many industrial processes. Obtaining of their chemical and physical properties is a fundamental task. Relative permittivity (r of these mixtures is a key property because allows a better knowledge of the structure and the interactions in other media. In this work predictive values of relative permittivity (r of carbon dioxide + ethanol mixtures were obtained implementing artificial neural networks (ANNs. They are used successfully in very different fields; therefore it is a very useful tool. In this case the obtained results enhance the ones from the usual multiple linear regression analysis. In both cases mass fraction, pressure and temperature experimental data from a direct capacitance method were used.

  7. Performance monitoring in the medial frontal cortex and related neural networks: From monitoring self actions to understanding others' actions.

    Science.gov (United States)

    Ninomiya, Taihei; Noritake, Atsushi; Ullsperger, Markus; Isoda, Masaki

    2018-04-27

    Action is a key channel for interacting with the outer world. As such, the ability to monitor actions and their consequences - regardless as to whether they are self-generated or other-generated - is of crucial importance for adaptive behavior. The medial frontal cortex (MFC) has long been studied as a critical node for performance monitoring in nonsocial contexts. Accumulating evidence suggests that the MFC is involved in a wide range of functions necessary for one's own performance monitoring, including error detection, and monitoring and resolving response conflicts. Recent studies, however, have also pointed to the importance of the MFC in performance monitoring under social conditions, ranging from monitoring and understanding others' actions to reading others' mental states, such as their beliefs and intentions (i.e., mentalizing). Here we review the functional roles of the MFC and related neural networks in performance monitoring in both nonsocial and social contexts, with an emphasis on the emerging field of a social systems neuroscience approach using macaque monkeys as a model system. Future work should determine the way in which the MFC exerts its monitoring function via interactions with other brain regions, such as the superior temporal sulcus in the mentalizing system and the ventral premotor cortex in the mirror system. Copyright © 2018. Published by Elsevier B.V.

  8. Disentangling the Attention Network Test: Behavioral, Event Related Potentials and neural source analyses.

    Directory of Open Access Journals (Sweden)

    Alejandro eGalvao-Carmona

    2014-10-01

    Full Text Available Background. The study of the attentional system remains a challenge for current neuroscience. The Attention Network Test (ANT was designed to study simultaneously three different attentional networks (alerting, orienting and executive based in subtraction of different experimental conditions. However, some studies recommend caution with these calculations due to the interactions between the attentional networks. In particular, it is highly relevant that several interpretations about attentional impairment have arisen from these calculations in diverse pathologies. Event Related Potentials (ERPs and neural source analysis can be applied to disentangle the relationships between these attentional networks not specifically shown by behavioural measures. Results. This study shows that there is a basic level of alerting (tonic alerting in the no cue condition, represented by a slow negative trend in the ERP trace prior to the onset of the target stimuli. A progressive increase in the CNV amplitude related to the amount of information provided by the cue conditions is also shown. Neural source analysis reveals specific modulations of the CNV related to a task-related expectancy presented in the no cue condition; a late modulation triggered by the central cue condition and probably representing a generic motor preparation; and an early and late modulation for spatial cue condition suggesting specific motor and sensory preactivation. Finally, the first component in the information processing of the target stimuli modulated by the interaction between orienting network and the executive system can be represented by N1. Conclusions. The ANT is useful as a paradigm to study specific attentional mechanisms and their interactions. However, calculation of network effects is based in subtractions with non-comparable experimental conditions, as evidenced by the present data, which can induce misinterpretations in the study of the attentional capacity in human

  9. From sensation to percept: the neural signature of auditory event-related potentials.

    Science.gov (United States)

    Joos, Kathleen; Gilles, Annick; Van de Heyning, Paul; De Ridder, Dirk; Vanneste, Sven

    2014-05-01

    An external auditory stimulus induces an auditory sensation which may lead to a conscious auditory perception. Although the sensory aspect is well known, it is still a question how an auditory stimulus results in an individual's conscious percept. To unravel the uncertainties concerning the neural correlates of a conscious auditory percept, event-related potentials may serve as a useful tool. In the current review we mainly wanted to shed light on the perceptual aspects of auditory processing and therefore we mainly focused on the auditory late-latency responses. Moreover, there is increasing evidence that perception is an active process in which the brain searches for the information it expects to be present, suggesting that auditory perception requires the presence of both bottom-up, i.e. sensory and top-down, i.e. prediction-driven processing. Therefore, the auditory evoked potentials will be interpreted in the context of the Bayesian brain model, in which the brain predicts which information it expects and when this will happen. The internal representation of the auditory environment will be verified by sensation samples of the environment (P50, N100). When this incoming information violates the expectation, it will induce the emission of a prediction error signal (Mismatch Negativity), activating higher-order neural networks and inducing the update of prior internal representations of the environment (P300). Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. Neural activity related to cognitive and emotional empathy in post-traumatic stress disorder.

    Science.gov (United States)

    Mazza, Monica; Tempesta, Daniela; Pino, Maria Chiara; Nigri, Anna; Catalucci, Alessia; Guadagni, Veronica; Gallucci, Massimo; Iaria, Giuseppe; Ferrara, Michele

    2015-04-01

    The aim of this study is to evaluate the empathic ability and its functional brain correlates in post-traumatic stress disorder subjects (PTSD). Seven PTSD subjects and ten healthy controls, all present in the L'Aquila area during the earthquake of the April 2009, underwent fMRI during which they performed a modified version of the Multifaceted Empathy Test. PTSD patients showed impairments in implicit and explicit emotional empathy, but not in cognitive empathy. Brain responses during cognitive empathy showed an increased activation in patients compared to controls in the right medial frontal gyrus and the left inferior frontal gyrus. During implicit emotional empathy responses patients with PTSD, compared to controls, exhibited greater neural activity in the left pallidum and right insula; instead the control group showed an increased activation in right inferior frontal gyrus. Finally, in the explicit emotional empathy responses the PTSD group showed a reduced neural activity in the left insula and the left inferior frontal gyrus. The behavioral deficit limited to the emotional empathy dimension, accompanied by different patterns of activation in empathy related brain structures, represent a first piece of evidence of a dissociation between emotional and cognitive empathy in PTSD patients. The present findings support the idea that empathy is a multidimensional process, with different facets depending on distinct anatomical substrates. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. Trait self-esteem and neural activities related to self-evaluation and social feedback

    Science.gov (United States)

    Yang, Juan; Xu, Xiaofan; Chen, Yu; Shi, Zhenhao; Han, Shihui

    2016-01-01

    Self-esteem has been associated with neural responses to self-reflection and attitude toward social feedback but in different brain regions. The distinct associations might arise from different tasks or task-related attitudes in the previous studies. The current study aimed to clarify these by investigating the association between self-esteem and neural responses to evaluation of one’s own personality traits and of others’ opinion about one’s own personality traits. We scanned 25 college students using functional MRI during evaluation of oneself or evaluation of social feedback. Trait self-esteem was measured using the Rosenberg self-esteem scale after scanning. Whole-brain regression analyses revealed that trait self-esteem was associated with the bilateral orbitofrontal activity during evaluation of one’s own positive traits but with activities in the medial prefrontal cortex, posterior cingulate, and occipital cortices during evaluation of positive social feedback. Our findings suggest that trait self-esteem modulates the degree of both affective processes in the orbitofrontal cortex during self-reflection and cognitive processes in the medial prefrontal cortex during evaluation of social feedback. PMID:26842975

  12. Trait self-esteem and neural activities related to self-evaluation and social feedback.

    Science.gov (United States)

    Yang, Juan; Xu, Xiaofan; Chen, Yu; Shi, Zhenhao; Han, Shihui

    2016-02-04

    Self-esteem has been associated with neural responses to self-reflection and attitude toward social feedback but in different brain regions. The distinct associations might arise from different tasks or task-related attitudes in the previous studies. The current study aimed to clarify these by investigating the association between self-esteem and neural responses to evaluation of one's own personality traits and of others' opinion about one's own personality traits. We scanned 25 college students using functional MRI during evaluation of oneself or evaluation of social feedback. Trait self-esteem was measured using the Rosenberg self-esteem scale after scanning. Whole-brain regression analyses revealed that trait self-esteem was associated with the bilateral orbitofrontal activity during evaluation of one's own positive traits but with activities in the medial prefrontal cortex, posterior cingulate, and occipital cortices during evaluation of positive social feedback. Our findings suggest that trait self-esteem modulates the degree of both affective processes in the orbitofrontal cortex during self-reflection and cognitive processes in the medial prefrontal cortex during evaluation of social feedback.

  13. Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin, E-mail: xmli@cqu.edu.cn [Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education, Chongqing University, Chongqing 400044 (China); College of Automation, Chongqing University, Chongqing 400044 (China)

    2015-11-15

    In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.

  14. Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule

    International Nuclear Information System (INIS)

    Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin

    2015-01-01

    In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing

  15. Work-Related Attitudes of Czech Generation Z: International Comparison

    Directory of Open Access Journals (Sweden)

    Jaroslava Kubátová,

    2016-12-01

    Full Text Available The goal of this article is to present work-related attitudes of a sample of Czech Generation Z and their comparison to the results of an international research study. Currently, there are three important trends influencing the labor market: (1 the origin and development of a ubiquitous working environment, (2 the thriving of coworking centers, and (3 Generation Z's entering the labor market. Instead of traditional jobs, the bearers of human capital tend to choose independent work in an online environment, and often work in coworking centers. Using self-determination theory, we substantiate why they thrive better this way. Based on the results of an international research project focused on work attitudes among Generation Z and the results of a replication study we carried out in the Czech Republic, we attest that members of Generation Z may prefer independent virtual work in coworking centers, too. The total amount of available human capital, the lack of which is pointed out by companies, may grow thanks to new ways of working. Companies, which can use human capital of independent workers, gain a competitive advantage.

  16. Neural correlates of emotional distractibility in bipolar disorder patients, unaffected relatives, and individuals with hypomanic personality.

    Science.gov (United States)

    Kanske, Philipp; Heissler, Janine; Schönfelder, Sandra; Forneck, Johanna; Wessa, Michèle

    2013-12-01

    Neuropsychological deficits and emotion dysregulation are present in symptomatic and euthymic patients with bipolar disorder. However, there is little evidence on how cognitive functioning is influenced by emotion, what the neural correlates of emotional distraction effects are, and whether such deficits are a consequence or a precursor of the disorder. The authors used functional MRI (fMRI) to investigate these questions. fMRI was used first to localize the neural network specific to a certain cognitive task (mental arithmetic) and then to test the effect of emotional distractors on this network. Euthymic patients with bipolar I disorder (N=22), two populations at high risk for developing the disorder (unaffected first-degree relatives of individuals with bipolar disorder [N=17]), and healthy participants with hypomanic personality traits [N=22]) were tested, along with three age-, gender-, and education-matched healthy comparison groups (N=22, N=17, N=24, respectively). There were no differences in performance or activation in the task network for mental arithmetic. However, while all participants exhibited slower responses when emotional distractors were present, this response slowing was greatly enlarged in bipolar patients. Similarly, task-related activation was generally increased under emotional distraction; however, bipolar patients exhibited a further increase in right parietal activation that correlated positively with the response slowing effect. The results suggest that emotional dysregulation leads to exacerbated neuropsychological deficits in bipolar patients, as evidenced by behavioral slowing and task-related hyperactivation. The lack of such a deficit in high-risk populations suggests that it occurs only after disease onset, rather than representing a vulnerability marker.

  17. Neural Network based Control of SG based Standalone Generating System with Energy Storage for Power Quality Enhancement

    Science.gov (United States)

    Nayar, Priya; Singh, Bhim; Mishra, Sukumar

    2017-08-01

    An artificial intelligence based control algorithm is used in solving power quality problems of a diesel engine driven synchronous generator with automatic voltage regulator and governor based standalone system. A voltage source converter integrated with a battery energy storage system is employed to mitigate the power quality problems. An adaptive neural network based signed regressor control algorithm is used for the estimation of the fundamental component of load currents for control of a standalone system with load leveling as an integral feature. The developed model of the system performs accurately under varying load conditions and provides good dynamic response to the step changes in loads. The real time performance is achieved using MATLAB along with simulink/simpower system toolboxes and results adhere to an IEEE-519 standard for power quality enhancement.

  18. Activational and effort-related aspects of motivation: neural mechanisms and implications for psychopathology

    Science.gov (United States)

    Yohn, Samantha E.; López-Cruz, Laura; San Miguel, Noemí; Correa, Mercè

    2016-01-01

    Abstract Motivation has been defined as the process that allows organisms to regulate their internal and external environment, and control the probability, proximity and availability of stimuli. As such, motivation is a complex process that is critical for survival, which involves multiple behavioural functions mediated by a number of interacting neural circuits. Classical theories of motivation suggest that there are both directional and activational aspects of motivation, and activational aspects (i.e. speed and vigour of both the instigation and persistence of behaviour) are critical for enabling organisms to overcome work-related obstacles or constraints that separate them from significant stimuli. The present review discusses the role of brain dopamine and related circuits in behavioural activation, exertion of effort in instrumental behaviour, and effort-related decision-making, based upon both animal and human studies. Impairments in behavioural activation and effort-related aspects of motivation are associated with psychiatric symptoms such as anergia, fatigue, lassitude and psychomotor retardation, which cross multiple pathologies, including depression, schizophrenia, and Parkinson’s disease. Therefore, this review also attempts to provide an interdisciplinary approach that integrates findings from basic behavioural neuroscience, behavioural economics, clinical neuropsychology, psychiatry, and neurology, to provide a coherent framework for future research and theory in this critical field. Although dopamine systems are a critical part of the brain circuitry regulating behavioural activation, exertion of effort, and effort-related decision-making, mesolimbic dopamine is only one part of a distributed circuitry that includes multiple neurotransmitters and brain areas. Overall, there is a striking similarity between the brain areas involved in behavioural activation and effort-related processes in rodents and in humans. Animal models of effort-related

  19. Activational and effort-related aspects of motivation: neural mechanisms and implications for psychopathology.

    Science.gov (United States)

    Salamone, John D; Yohn, Samantha E; López-Cruz, Laura; San Miguel, Noemí; Correa, Mercè

    2016-05-01

    Motivation has been defined as the process that allows organisms to regulate their internal and external environment, and control the probability, proximity and availability of stimuli. As such, motivation is a complex process that is critical for survival, which involves multiple behavioural functions mediated by a number of interacting neural circuits. Classical theories of motivation suggest that there are both directional and activational aspects of motivation, and activational aspects (i.e. speed and vigour of both the instigation and persistence of behaviour) are critical for enabling organisms to overcome work-related obstacles or constraints that separate them from significant stimuli. The present review discusses the role of brain dopamine and related circuits in behavioural activation, exertion of effort in instrumental behaviour, and effort-related decision-making, based upon both animal and human studies. Impairments in behavioural activation and effort-related aspects of motivation are associated with psychiatric symptoms such as anergia, fatigue, lassitude and psychomotor retardation, which cross multiple pathologies, including depression, schizophrenia, and Parkinson's disease. Therefore, this review also attempts to provide an interdisciplinary approach that integrates findings from basic behavioural neuroscience, behavioural economics, clinical neuropsychology, psychiatry, and neurology, to provide a coherent framework for future research and theory in this critical field. Although dopamine systems are a critical part of the brain circuitry regulating behavioural activation, exertion of effort, and effort-related decision-making, mesolimbic dopamine is only one part of a distributed circuitry that includes multiple neurotransmitters and brain areas. Overall, there is a striking similarity between the brain areas involved in behavioural activation and effort-related processes in rodents and in humans. Animal models of effort-related decision

  20. Wind Turbine Driving a PM Synchronous Generator Using Novel Recurrent Chebyshev Neural Network Control with the Ideal Learning Rate

    Directory of Open Access Journals (Sweden)

    Chih-Hong Lin

    2016-06-01

    Full Text Available A permanent magnet (PM synchronous generator system driven by wind turbine (WT, connected with smart grid via AC-DC converter and DC-AC converter, are controlled by the novel recurrent Chebyshev neural network (NN and amended particle swarm optimization (PSO to regulate output power and output voltage in two power converters in this study. Because a PM synchronous generator system driven by WT is an unknown non-linear and time-varying dynamic system, the on-line training novel recurrent Chebyshev NN control system is developed to regulate DC voltage of the AC-DC converter and AC voltage of the DC-AC converter connected with smart grid. Furthermore, the variable learning rate of the novel recurrent Chebyshev NN is regulated according to discrete-type Lyapunov function for improving the control performance and enhancing convergent speed. Finally, some experimental results are shown to verify the effectiveness of the proposed control method for a WT driving a PM synchronous generator system in smart grid.

  1. Age-related changes in expression of the neural cell adhesion molecule in skeletal muscle

    DEFF Research Database (Denmark)

    Andersson, A M; Olsen, M; Zhernosekov, D

    1993-01-01

    Neural cell adhesion molecule (NCAM) is expressed by muscle and involved in muscle-neuron and muscle-muscle cell interactions. The expression in muscle is regulated during myogenesis and by the state of innervation. In aged muscle, both neurogenic and myogenic degenerative processes occur. We here...... report quantitative and qualitative changes in NCAM protein and mRNA forms during aging in normal rat skeletal muscle. Determination of the amount of NCAM by e.l.i.s.a. showed that the level decreased from perinatal to adult age, followed by a considerable increase in 24-month-old rat muscle. Thus NCAM...... concentration in aged muscle was sixfold higher than in young adult muscle. In contrast with previous reports, NCAM polypeptides of 200, 145, 125 and 120 kDa were observed by immunoblotting throughout postnatal development and aging, the relative proportions of the individual NCAM polypeptides remaining...

  2. Neural network approach in multichannel auditory event-related potential analysis.

    Science.gov (United States)

    Wu, F Y; Slater, J D; Ramsay, R E

    1994-04-01

    Even though there are presently no clearly defined criteria for the assessment of P300 event-related potential (ERP) abnormality, it is strongly indicated through statistical analysis that such criteria exist for classifying control subjects and patients with diseases resulting in neuropsychological impairment such as multiple sclerosis (MS). We have demonstrated the feasibility of artificial neural network (ANN) methods in classifying ERP waveforms measured at a single channel (Cz) from control subjects and MS patients. In this paper, we report the results of multichannel ERP analysis and a modified network analysis methodology to enhance automation of the classification rule extraction process. The proposed methodology significantly reduces the work of statistical analysis. It also helps to standardize the criteria of P300 ERP assessment and facilitate the computer-aided analysis on neuropsychological functions.

  3. Impact of load-related neural processes on feature binding in visuospatial working memory.

    Directory of Open Access Journals (Sweden)

    Nicole A Kochan

    Full Text Available BACKGROUND: The capacity of visual working memory (WM is substantially limited and only a fraction of what we see is maintained as a temporary trace. The process of binding visual features has been proposed as an adaptive means of minimising information demands on WM. However the neural mechanisms underlying this process, and its modulation by task and load effects, are not well understood. OBJECTIVE: To investigate the neural correlates of feature binding and its modulation by WM load during the sequential phases of encoding, maintenance and retrieval. METHODS AND FINDINGS: 18 young healthy participants performed a visuospatial WM task with independent factors of load and feature conjunction (object identity and position in an event-related functional MRI study. During stimulus encoding, load-invariant conjunction-related activity was observed in left prefrontal cortex and left hippocampus. During maintenance, greater activity for task demands of feature conjunction versus single features, and for increased load was observed in left-sided regions of the superior occipital cortex, precuneus and superior frontal cortex. Where these effects were expressed in overlapping cortical regions, their combined effect was additive. During retrieval, however, an interaction of load and feature conjunction was observed. This modulation of feature conjunction activity under increased load was expressed through greater deactivation in medial structures identified as part of the default mode network. CONCLUSIONS AND SIGNIFICANCE: The relationship between memory load and feature binding qualitatively differed through each phase of the WM task. Of particular interest was the interaction of these factors observed within regions of the default mode network during retrieval which we interpret as suggesting that at low loads, binding processes may be 'automatic' but at higher loads it becomes a resource-intensive process leading to disengagement of activity in this

  4. Religious Fundamentalism Modulates Neural Responses to Error-Related Words: The Role of Motivation Toward Closure

    Directory of Open Access Journals (Sweden)

    Małgorzata Kossowska

    2018-03-01

    Full Text Available Examining the relationship between brain activity and religious fundamentalism, this study explores whether fundamentalist religious beliefs increase responses to error-related words among participants intolerant to uncertainty (i.e., high in the need for closure in comparison to those who have a high degree of toleration for uncertainty (i.e., those who are low in the need for closure. We examine a negative-going event-related brain potentials occurring 400 ms after stimulus onset (the N400 due to its well-understood association with the reactions to emotional conflict. Religious fundamentalism and tolerance of uncertainty were measured on self-report measures, and electroencephalographic neural reactivity was recorded as participants were performing an emotional Stroop task. In this task, participants read neutral words and words related to uncertainty, errors, and pondering, while being asked to name the color of the ink with which the word is written. The results confirm that among people who are intolerant of uncertainty (i.e., those high in the need for closure, religious fundamentalism is associated with an increased N400 on error-related words compared with people who tolerate uncertainty well (i.e., those low in the need for closure.

  5. Religious Fundamentalism Modulates Neural Responses to Error-Related Words: The Role of Motivation Toward Closure.

    Science.gov (United States)

    Kossowska, Małgorzata; Szwed, Paulina; Wyczesany, Miroslaw; Czarnek, Gabriela; Wronka, Eligiusz

    2018-01-01

    Examining the relationship between brain activity and religious fundamentalism, this study explores whether fundamentalist religious beliefs increase responses to error-related words among participants intolerant to uncertainty (i.e., high in the need for closure) in comparison to those who have a high degree of toleration for uncertainty (i.e., those who are low in the need for closure). We examine a negative-going event-related brain potentials occurring 400 ms after stimulus onset (the N400) due to its well-understood association with the reactions to emotional conflict. Religious fundamentalism and tolerance of uncertainty were measured on self-report measures, and electroencephalographic neural reactivity was recorded as participants were performing an emotional Stroop task. In this task, participants read neutral words and words related to uncertainty, errors, and pondering, while being asked to name the color of the ink with which the word is written. The results confirm that among people who are intolerant of uncertainty (i.e., those high in the need for closure), religious fundamentalism is associated with an increased N400 on error-related words compared with people who tolerate uncertainty well (i.e., those low in the need for closure).

  6. Religious Fundamentalism Modulates Neural Responses to Error-Related Words: The Role of Motivation Toward Closure

    Science.gov (United States)

    Kossowska, Małgorzata; Szwed, Paulina; Wyczesany, Miroslaw; Czarnek, Gabriela; Wronka, Eligiusz

    2018-01-01

    Examining the relationship between brain activity and religious fundamentalism, this study explores whether fundamentalist religious beliefs increase responses to error-related words among participants intolerant to uncertainty (i.e., high in the need for closure) in comparison to those who have a high degree of toleration for uncertainty (i.e., those who are low in the need for closure). We examine a negative-going event-related brain potentials occurring 400 ms after stimulus onset (the N400) due to its well-understood association with the reactions to emotional conflict. Religious fundamentalism and tolerance of uncertainty were measured on self-report measures, and electroencephalographic neural reactivity was recorded as participants were performing an emotional Stroop task. In this task, participants read neutral words and words related to uncertainty, errors, and pondering, while being asked to name the color of the ink with which the word is written. The results confirm that among people who are intolerant of uncertainty (i.e., those high in the need for closure), religious fundamentalism is associated with an increased N400 on error-related words compared with people who tolerate uncertainty well (i.e., those low in the need for closure). PMID:29636709

  7. Grey relational and neural network approach for multi-objective optimization in small scale resistance spot welding of titanium alloy

    Energy Technology Data Exchange (ETDEWEB)

    Wan, Xiaodong; Wang, Yuanxun; Zhao, Dawei [Huazhong University of Science and Technology, Wuhan (China)

    2016-06-15

    The prediction and optimization of weld quality characteristics in small scale resistance spot welding of TC2 titanium alloy were investigated. Grey relational analysis, neural network and genetic algorithm were applied separately. Quality characteristics were selected as nugget diameter, failure load, failure displacement and failure energy. Welding parameters to be optimized were set as electrode force, welding current and welding time. Grey relational analysis was conducted for a rough estimation of the optimum welding parameters. Results showed that welding current played a key role in weld quality improvement. Different back propagation neural network architectures were then arranged to predict multiple quality characteristics. Interaction effects of welding parameters were analyzed with the proposed neural network. Failure load was found more sensitive to the change of welding parameters than nugget diameter. Optimum welding parameters were determined by genetic algorithm. The predicted responses showed good agreement with confirmation experiments.

  8. Prediction of power system frequency response after generator outages using neural nets

    Energy Technology Data Exchange (ETDEWEB)

    Djukanovic, M B; Popovic, D P [Electrotechnicki Inst. ' Nikola Tesla' , Belgrade (Yugoslavia); Sobajic, D J; Pao, Y -H [Case Western Reserve Univ., Cleveland, OH (United States)

    1993-09-01

    A new methodology is presented for estimating the frequency behaviour of power systems necessary for an indication of under-frequency load shedding in steady-state security assessment. It is well known that large structural disturbances such as generator tripping or load outages can initiate cascading outages, system separation into islands, and even the complete breakup. The approach provides a fairly accurate method of estimating the system average frequency response without making simplifications or neglecting non-linearities and small time constants in the equations of generating units, voltage regulators and turbines. The efficiency of the new procedure is demonstrated using the New England power system model for a series of characteristic perturbations. The validity of the proposed approach is verified by comparison with the simulation of short-term dynamics including effects of control and automatic devices. (author)

  9. Eddy Current Signature Classification of Steam Generator Tube Defects Using A Learning Vector Quantization Neural Network

    International Nuclear Information System (INIS)

    Garcia, Gabe V.

    2005-01-01

    A major cause of failure in nuclear steam generators is degradation of their tubes. Although seven primary defect categories exist, one of the principal causes of tube failure is intergranular attack/stress corrosion cracking (IGA/SCC). This type of defect usually begins on the secondary side surface of the tubes and propagates both inwards and laterally. In many cases this defect is found at or near the tube support plates

  10. Biophysical studies related to energy generation: Progress report

    International Nuclear Information System (INIS)

    Green, A.E.S.

    1988-01-01

    This report covers work subsequent to our previous report of December 24, 1986. At that time we were groping to find relationships between vibrational and rotational electron impact cross sections in the vapor and liquid phases of water. Having reached an impass within the radiological literature, we drew upon the atmospheric, oceanographic and flame radiation literatures. Here a much broader body of excitation energy and intensity data related to the vibrational and rotational excitation of water in the vapor phases and liquid phases enabled us to identify certain ''big bands'' of H 2 O. These bands account for the major infrared absorption features observed in atmospheric transmission studies as well as important spectral radiation features observed in hydrocarbon combustion. Related liquid phase-gas phase involvement also entered our work on co-combustion of biomass and waste, and natural gas in studies directed toward contributing to the solution of national energy-environmental and economic problems. Attachments to this report include our published works, submitted works, and in complete studies related to radiological, atmospheric, and combustion studies which encompass biophysical studies related to energy generation and which have a common thread involving water in liquid and vapor form. These works are tied together in this brief report, along with some comments on trends in science and technology which they might illustrate

  11. Neural computational modeling reveals a major role of corticospinal gating of central oscillations in the generation of essential tremor

    Directory of Open Access Journals (Sweden)

    Hong-en Qu

    2017-01-01

    Full Text Available Essential tremor, also referred to as familial tremor, is an autosomal dominant genetic disease and the most common movement disorder. It typically involves a postural and motor tremor of the hands, head or other part of the body. Essential tremor is driven by a central oscillation signal in the brain. However, the corticospinal mechanisms involved in the generation of essential tremor are unclear. Therefore, in this study, we used a neural computational model that includes both monosynaptic and multisynaptic corticospinal pathways interacting with a propriospinal neuronal network. A virtual arm model is driven by the central oscillation signal to simulate tremor activity behavior. Cortical descending commands are classified as alpha or gamma through monosynaptic or multisynaptic corticospinal pathways, which converge respectively on alpha or gamma motoneurons in the spinal cord. Several scenarios are evaluated based on the central oscillation signal passing down to the spinal motoneurons via each descending pathway. The simulated behaviors are compared with clinical essential tremor characteristics to identify the corticospinal pathways responsible for transmitting the central oscillation signal. A propriospinal neuron with strong cortical inhibition performs a gating function in the generation of essential tremor. Our results indicate that the propriospinal neuronal network is essential for relaying the central oscillation signal and the production of essential tremor.

  12. Neural computational modeling reveals a major role of corticospinal gating of central oscillations in the generation of essential tremor.

    Science.gov (United States)

    Qu, Hong-En; Niu, Chuanxin M; Li, Si; Hao, Man-Zhao; Hu, Zi-Xiang; Xie, Qing; Lan, Ning

    2017-12-01

    Essential tremor, also referred to as familial tremor, is an autosomal dominant genetic disease and the most common movement disorder. It typically involves a postural and motor tremor of the hands, head or other part of the body. Essential tremor is driven by a central oscillation signal in the brain. However, the corticospinal mechanisms involved in the generation of essential tremor are unclear. Therefore, in this study, we used a neural computational model that includes both monosynaptic and multisynaptic corticospinal pathways interacting with a propriospinal neuronal network. A virtual arm model is driven by the central oscillation signal to simulate tremor activity behavior. Cortical descending commands are classified as alpha or gamma through monosynaptic or multisynaptic corticospinal pathways, which converge respectively on alpha or gamma motoneurons in the spinal cord. Several scenarios are evaluated based on the central oscillation signal passing down to the spinal motoneurons via each descending pathway. The simulated behaviors are compared with clinical essential tremor characteristics to identify the corticospinal pathways responsible for transmitting the central oscillation signal. A propriospinal neuron with strong cortical inhibition performs a gating function in the generation of essential tremor. Our results indicate that the propriospinal neuronal network is essential for relaying the central oscillation signal and the production of essential tremor.

  13. Memory's aging echo: age-related decline in neural reactivation of perceptual details during recollection.

    Science.gov (United States)

    McDonough, Ian M; Cervantes, Sasha N; Gray, Stephen J; Gallo, David A

    2014-09-01

    Episodic memory decline is a hallmark of normal cognitive aging. Here, we report the first event-related fMRI study to directly investigate age differences in the neural reactivation of qualitatively rich perceptual details during recollection. Younger and older adults studied pictures of complex scenes at different presentation durations along with descriptive verbal labels, and these labels subsequently were used during fMRI scanning to cue picture recollections of varying perceptual detail. As expected from prior behavioral work, the two age groups subjectively rated their recollections as containing similar amounts of perceptual detail, despite objectively measured recollection impairment in older adults. In both age groups, comparisons of retrieval trials that varied in recollected detail revealed robust activity in brain regions previously linked to recollection, including hippocampus and both medial and lateral regions of the prefrontal and posterior parietal cortex. Critically, this analysis also revealed recollection-related activity in visual processing regions that were active in an independent picture-perception task, and these regions showed age-related reductions in activity during recollection that cannot be attributed to age differences in response criteria. These fMRI findings provide new evidence that aging reduces the absolute quantity of perceptual details that are reactivated from memory, and they help to explain why aging reduces the reliability of subjective memory judgments. Copyright © 2014 Elsevier Inc. All rights reserved.

  14. Time spent with friends in adolescence relates to less neural sensitivity to later peer rejection.

    Science.gov (United States)

    Masten, Carrie L; Telzer, Eva H; Fuligni, Andrew J; Lieberman, Matthew D; Eisenberger, Naomi I

    2012-01-01

    Involvement with friends carries many advantages for adolescents, including protection from the detrimental effects of being rejected by peers. However, little is known about the mechanisms through which friendships may serve their protective role at this age, or the potential benefit of these friendships as adolescents transition to adulthood. As such, this investigation tested whether friend involvement during adolescence related to less neural sensitivity to social threats during young adulthood. Twenty-one adolescents reported the amount of time they spent with friends outside of school using a daily diary. Two years later they underwent an fMRI scan, during which they were ostensibly excluded from an online ball-tossing game by two same-age peers. Findings from region of interest and whole brain analyses revealed that spending more time with friends during adolescence related to less activity in the dorsal anterior cingulate cortex and anterior insula--regions previously linked with negative affect and pain processing--during an experience of peer rejection 2 years later. These findings are consistent with the notion that positive relationships during adolescence may relate to individuals being less sensitive to negative social experiences later on.

  15. Novel Behavioral and Neural Evidences for Age-Related changes in Force complexity.

    Science.gov (United States)

    Chen, Yi-Ching; Lin, Linda L; Hwang, Ing-Shiou

    2018-02-17

    This study investigated age-related changes in behavioral and neural complexity for a polyrhythmic movement, which appeared to be an exception to the loss of complexity hypothesis. Young (n = 15; age = 24.2 years) and older (15; 68.1 years) adults performed low-level force-tracking with isometric index abduction to couple a compound sinusoidal target. Multi-scale entropy (MSE) of tracking force and inter-spike interval (ISI) of motor unit (MU) in the first dorsal interosseus muscle were assessed. The MSE area of tracking force at shorter time scales of older adults was greater (more complex) than that of young adults, whereas an opposite trend (less complex for the elders) was noted at longer time scales. The MSE area of force fluctuations (the stochastic component of the tracking force) were generally smaller (less complex) for older adults. Along with greater mean and coefficient of ISI, the MSE area of the cumulative discharge rate of elders tended to be lower (less complex) than that of young adults. In conclusion, age-related complexity changes in polyrhythmic force-tracking depended on the time scale. The adaptive behavioral consequences could be multi-factorial origins of the age-related impairment in rate coding, increased discharge noises, and lower discharge complexity of pooled MUs.

  16. The effect of visual parameters on neural activation during nonsymbolic number comparison and its relation to math competency.

    Science.gov (United States)

    Wilkey, Eric D; Barone, Jordan C; Mazzocco, Michèle M M; Vogel, Stephan E; Price, Gavin R

    2017-10-01

    Nonsymbolic numerical comparison task performance (whereby a participant judges which of two groups of objects is numerically larger) is thought to index the efficiency of neural systems supporting numerical magnitude perception, and performance on such tasks has been related to individual differences in math competency. However, a growing body of research suggests task performance is heavily influenced by visual parameters of the stimuli (e.g. surface area and dot size of object sets) such that the correlation with math is driven by performance on trials in which number is incongruent with visual cues. Almost nothing is currently known about whether the neural correlates of nonsymbolic magnitude comparison are also affected by visual congruency. To investigate this issue, we used functional magnetic resonance imaging (fMRI) to analyze neural activity during a nonsymbolic comparison task as a function of visual congruency in a sample of typically developing high school students (n = 36). Further, we investigated the relation to math competency as measured by the preliminary scholastic aptitude test (PSAT) in 10th grade. Our results indicate that neural activity was modulated by the ratio of the dot sets being compared in brain regions previously shown to exhibit an effect of ratio (i.e. left anterior cingulate, left precentral gyrus, left intraparietal sulcus, and right superior parietal lobe) when calculated from the average of congruent and incongruent trials, as it is in most studies, and that the effect of ratio within those regions did not differ as a function of congruency condition. However, there were significant differences in other regions in overall task-related activation, as opposed to the neural ratio effect, when congruent and incongruent conditions were contrasted at the whole-brain level. Math competency negatively correlated with ratio-dependent neural response in the left insula across congruency conditions and showed distinct correlations when

  17. Dental anomalies in different cleft groups related to neural crest developmental fields contributes to the understanding of cleft aetiology

    DEFF Research Database (Denmark)

    Riis, Louise Claudius; Kjær, Inger; Mølsted, Kirsten

    2014-01-01

    OBJECTIVE: To analyze dental deviations in three cleft groups and relate findings to embryological neural crest fields (frontonasal, maxillary, and palatal). The overall purpose was to evaluate how fields are involved in different cleft types. DESIGN: Retrospective audit of clinical photographs...

  18. Wood Modification at High Temperature and Pressurized Steam: a Relational Model of Mechanical Properties Based on a Neural Network

    Directory of Open Access Journals (Sweden)

    Hong Yang

    2015-07-01

    Full Text Available Thermally modified wood has high dimensional stability and biological durability.But if the process parameters of thermal modification are not appropriate, then there will be a decline in the physical properties of wood.A neural network algorithm was employed in this study to establish the relationship between the process parameters of high-temperature and high-pressure thermal modification and the mechanical properties of the wood. Three important parameters: temperature, relative humidity, and treatment time, were considered as the inputs to the neural network. Back propagation (BP neural network and radial basis function (RBF neural network models for prediction were built and compared. The comparison showed that the RBF neural network model had advantages in network structure, convergence speed, and generalization capacity. On this basis, the inverse model, reflecting the relationship between the process parameters and the mechanical properties of wood, was established. Given the desired mechanical properties of the wood, the thermal modification process parameters could be inversely optimized and predicted. The results indicated that the model has good learning ability and generalization capacity. This is of great importance for the theoretical and applicational studies of the thermal modification of wood.

  19. Effects of selective serotonin reuptake inhibition on neural activity related to risky decisions and monetary rewards in healthy males

    DEFF Research Database (Denmark)

    Macoveanu, Julian; Fisher, Patrick M; Haahr, Mette E

    2014-01-01

    the involvement of the normally functioning 5HT-system in decision-making under risk and processing of monetary rewards. The data suggest that prolonged SSRI treatment might reduce emotional engagement by reducing the impact of risk during decision-making or the impact of reward during outcome evaluation....... to placebo, the SSRI intervention did not alter individual risk-choice preferences, but modified neural activity during decision-making and reward processing: During the choice phase, SSRI reduced the neural response to increasing risk in lateral orbitofrontal cortex, a key structure for value-based decision-making...... functional MRI (fMRI) to investigate how a three-week fluoxetine intervention influences neural activity related to risk taking and reward processing. Employing a double-blinded parallel-group design, 29 healthy young males were randomly assigned to receive 3 weeks of a daily dose of 40 mg fluoxetine...

  20. Neural correlates to food-related behavior in normal-weight and overweight/obese participants.

    Directory of Open Access Journals (Sweden)

    Alan Ho

    Full Text Available Two thirds of US adults are either obese or overweight and this rate is rising. Although the etiology of obesity is not yet fully understood, neuroimaging studies have demonstrated that the central nervous system has a principal role in regulating eating behavior. In this study, functional magnetic resonance imaging and survey data were evaluated for correlations between food-related problem behaviors and the neural regions underlying responses to visual food cues before and after eating in normal-weight individuals and overweight/obese individuals. In normal-weight individuals, activity in the left amygdala in response to high-calorie food vs. nonfood object cues was positively correlated with impaired satiety scores during fasting, suggesting that those with impaired satiety scores may have an abnormal anticipatory reward response. In overweight/obese individuals, activity in the dorsolateral prefrontal cortex (DLPFC in response to low-calorie food cues was negatively correlated with impaired satiety during fasting, suggesting that individuals scoring lower in satiety impairment were more likely to activate the DLPFC inhibitory system. After eating, activity in both the putamen and the amygdala was positively correlated with impaired satiety scores among obese/overweight participants. While these individuals may volitionally suggest they are full, their functional response to food cues suggests food continues to be salient. These findings suggest brain regions involved in the evaluation of visual food cues may be mediated by satiety-related problems, dependent on calorie content, state of satiation, and body mass index.

  1. Developmental pathway genes and neural plasticity underlying emotional learning and stress-related disorders.

    Science.gov (United States)

    Maheu, Marissa E; Ressler, Kerry J

    2017-09-01

    The manipulation of neural plasticity as a means of intervening in the onset and progression of stress-related disorders retains its appeal for many researchers, despite our limited success in translating such interventions from the laboratory to the clinic. Given the challenges of identifying individual genetic variants that confer increased risk for illnesses like depression and post-traumatic stress disorder, some have turned their attention instead to focusing on so-called "master regulators" of plasticity that may provide a means of controlling these potentially impaired processes in psychiatric illnesses. The mammalian homolog of Tailless (TLX), Wnt, and the homeoprotein Otx2 have all been proposed to constitute master regulators of different forms of plasticity which have, in turn, each been implicated in learning and stress-related disorders. In the present review, we provide an overview of the changing distribution of these genes and their roles both during development and in the adult brain. We further discuss how their distinct expression profiles provide clues as to their function, and may inform their suitability as candidate drug targets in the treatment of psychiatric disorders. © 2017 Maheu and Ressler; Published by Cold Spring Harbor Laboratory Press.

  2. Disentangling the neural mechanisms involved in Hinduism- and Buddhism-related meditations.

    Science.gov (United States)

    Tomasino, Barbara; Chiesa, Alberto; Fabbro, Franco

    2014-10-01

    The most diffuse forms of meditation derive from Hinduism and Buddhism spiritual traditions. Different cognitive processes are set in place to reach these meditation states. According to an historical-philological hypothesis (Wynne, 2009) the two forms of meditation could be disentangled. While mindfulness is the focus of Buddhist meditation reached by focusing sustained attention on the body, on breathing and on the content of the thoughts, reaching an ineffable state of nothigness accompanied by a loss of sense of self and duality (Samadhi) is the main focus of Hinduism-inspired meditation. It is possible that these different practices activate separate brain networks. We tested this hypothesis by conducting an activation likelihood estimation (ALE) meta-analysis of functional magnetic resonance imaging (fMRI) studies. The network related to Buddhism-inspired meditation (16 experiments, 263 subjects, and 96 activation foci) included activations in some frontal lobe structures associated with executive attention, possibly confirming the fundamental role of mindfulness shared by many Buddhist meditations. By contrast, the network related to Hinduism-inspired meditation (8 experiments, 54 activation foci and 66 subjects) triggered a left lateralized network of areas including the postcentral gyrus, the superior parietal lobe, the hippocampus and the right middle cingulate cortex. The dissociation between anterior and posterior networks support the notion that different meditation styles and traditions are characterized by different patterns of neural activation. Copyright © 2014. Published by Elsevier Inc.

  3. Fine-Tuning Neural Patient Question Retrieval Model with Generative Adversarial Networks.

    Science.gov (United States)

    Tang, Guoyu; Ni, Yuan; Wang, Keqiang; Yong, Qin

    2018-01-01

    The online patient question and answering (Q&A) system attracts an increasing amount of users in China. Patient will post their questions and wait for doctors' response. To avoid the lag time involved with the waiting and to reduce the workload on the doctors, a better method is to automatically retrieve the semantically equivalent question from the archive. We present a Generative Adversarial Networks (GAN) based approach to automatically retrieve patient question. We apply supervised deep learning based approaches to determine the similarity between patient questions. Then a GAN framework is used to fine-tune the pre-trained deep learning models. The experiment results show that fine-tuning by GAN can improve the performance.

  4. Voltage regulation in MV networks with dispersed generations by a neural-based multiobjective methodology

    Energy Technology Data Exchange (ETDEWEB)

    Galdi, Vincenzo [Dipartimento di Ingegneria dell' Informazione e Ingegneria Elettrica, Universita degli studi di Salerno, Via Ponte Don Melillo 1, 84084 Fisciano (Italy); Vaccaro, Alfredo; Villacci, Domenico [Dipartimento di Ingegneria, Universita degli Studi del Sannio, Piazza Roma 21, 82100 Benevento (Italy)

    2008-05-15

    This paper puts forward the role of learning techniques in addressing the problem of an efficient and optimal centralized voltage control in distribution networks equipped with dispersed generation systems (DGSs). The proposed methodology employs a radial basis function network (RBFN) to identify the multidimensional nonlinear mapping between a vector of observable variables describing the network operating point and the optimal set points of the voltage regulating devices. The RBFN is trained by numerical data generated by solving the voltage regulation problem for a set of network operating points by a rigorous multiobjective solution methodology. The RBFN performance is continuously monitored by a supervisor process that notifies when there is the need of a more accurate solution of the voltage regulation problem if nonoptimal network operating conditions (ex post monitoring) or excessive distances between the actual network state and the neuron's centres (ex ante monitoring) are detected. A more rigorous problem solution, if required, can be obtained by solving the voltage regulation problem by a conventional multiobjective optimization technique. This new solution, in conjunction with the corresponding input vector, is then adopted as a new train data sample to adapt the RBFN. This online training process allows RBFN to (i) adaptively learn the more representative domain space regions of the input/output mapping without needing a prior knowledge of a complete and representative training set, and (ii) manage effectively any time varying phenomena affecting this mapping. The results obtained by simulating the regulation policy in the case of a medium-voltage network are very promising. (author)

  5. Neural activity underlying tinnitus generation : Results from PET and fMRI

    NARCIS (Netherlands)

    Lanting, C. P.; de Kleine, E.; van Dijk, P.

    Tinnitus is the percept of sound that is not related to an acoustic source outside the body. For many forms of tinnitus, mechanisms in the central nervous system are believed to play an important role in the pathology. Specifically, three mechanisms have been proposed to underlie tinnitus: (1)

  6. Relative location prediction in CT scan images using convolutional neural networks.

    Science.gov (United States)

    Guo, Jiajia; Du, Hongwei; Zhu, Jianyue; Yan, Ting; Qiu, Bensheng

    2018-07-01

    Relative location prediction in computed tomography (CT) scan images is a challenging problem. Many traditional machine learning methods have been applied in attempts to alleviate this problem. However, the accuracy and speed of these methods cannot meet the requirement of medical scenario. In this paper, we propose a regression model based on one-dimensional convolutional neural networks (CNN) to determine the relative location of a CT scan image both quickly and precisely. In contrast to other common CNN models that use a two-dimensional image as an input, the input of this CNN model is a feature vector extracted by a shape context algorithm with spatial correlation. Normalization via z-score is first applied as a pre-processing step. Then, in order to prevent overfitting and improve model's performance, 20% of the elements of the feature vectors are randomly set to zero. This CNN model consists primarily of three one-dimensional convolutional layers, three dropout layers and two fully-connected layers with appropriate loss functions. A public dataset is employed to validate the performance of the proposed model using a 5-fold cross validation. Experimental results demonstrate an excellent performance of the proposed model when compared with contemporary techniques, achieving a median absolute error of 1.04 cm and mean absolute error of 1.69 cm. The time taken for each relative location prediction is approximately 2 ms. Results indicate that the proposed CNN method can contribute to a quick and accurate relative location prediction in CT scan images, which can improve efficiency of the medical picture archiving and communication system in the future. Copyright © 2018 Elsevier B.V. All rights reserved.

  7. Meditation reduces pain-related neural activity in the anterior cingulate cortex, insula, secondary somatosensory cortex, and thalamus

    Science.gov (United States)

    Nakata, Hiroki; Sakamoto, Kiwako; Kakigi, Ryusuke

    2014-01-01

    Recent studies have shown that meditation inhibits or relieves pain perception. To clarify the underlying mechanisms for this phenomenon, neuroimaging methods, such as functional magnetic resonance imaging, and neurophysiological methods, such as magnetoencephalography and electroencephalography, have been used. However, it has been difficult to interpret the results, because there is some paradoxical evidence. For example, some studies reported increased neural responses to pain stimulation during meditation in the anterior cingulate cortex (ACC) and insula, whereas others showed a decrease in these regions. There have been inconsistent findings to date. Moreover, in general, since the activities of the ACC and insula are correlated with pain perception, the increase in neural activities during meditation would be related to the enhancement of pain perception rather than its reduction. These contradictions might directly contribute to the ‘mystery of meditation.’ In this review, we presented previous findings for brain regions during meditation and the anatomical changes that occurred in the brain with long-term meditation training. We then discussed the findings of previous studies that examined pain-related neural activity during meditation. We also described the brain mechanisms responsible for pain relief during meditation, and possible reasons for paradoxical evidence among previous studies. By thoroughly overviewing previous findings, we hypothesized that meditation reduces pain-related neural activity in the ACC, insula, secondary somatosensory cortex, and thalamus. We suggest that the characteristics of the modulation of this activity may depend on the kind of meditation and/or number of years of experience of meditation, which were associated with paradoxical findings among previous studies that investigated pain-related neural activities during meditation. PMID:25566158

  8. Age-related neural correlates of cognitive task performance under increased postural load

    NARCIS (Netherlands)

    Van Impe, A; Bruijn, S M; Coxon, J P; Wenderoth, N; Sunaert, S; Duysens, J; Swinnen, S P

    2013-01-01

    Behavioral studies suggest that postural control requires increased cognitive control and visuospatial processing with aging. Consequently, performance can decline when concurrently performing a postural and a demanding cognitive task. We aimed to identify the neural substrate underlying this

  9. Solving differential equations with unknown constitutive relations as recurrent neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Hagge, Tobias J.; Stinis, Panagiotis; Yeung, Enoch H.; Tartakovsky, Alexandre M.

    2017-12-08

    We solve a system of ordinary differential equations with an unknown functional form of a sink (reaction rate) term. We assume that the measurements (time series) of state variables are partially available, and use a recurrent neural network to “learn” the reaction rate from this data. This is achieved by including discretized ordinary differential equations as part of a recurrent neural network training problem. We extend TensorFlow’s recurrent neural network architecture to create a simple but scalable and effective solver for the unknown functions, and apply it to a fedbatch bioreactor simulation problem. Use of techniques from recent deep learning literature enables training of functions with behavior manifesting over thousands of time steps. Our networks are structurally similar to recurrent neural networks, but differ in purpose, and require modified training strategies.

  10. Hierarchical neural network model of the visual system determining figure/ground relation

    Science.gov (United States)

    Kikuchi, Masayuki

    2017-07-01

    One of the most important functions of the visual perception in the brain is figure/ground interpretation from input images. Figural region in 2D image corresponding to object in 3D space are distinguished from background region extended behind the object. Previously the author proposed a neural network model of figure/ground separation constructed on the standpoint that local geometric features such as curvatures and outer angles at corners are extracted and propagated along input contour in a single layer network (Kikuchi & Akashi, 2001). However, such a processing principle has the defect that signal propagation requires manyiterations despite the fact that actual visual system determines figure/ground relation within the short period (Zhou et al., 2000). In order to attain speed-up for determining figure/ground, this study incorporates hierarchical architecture into the previous model. This study confirmed the effect of the hierarchization as for the computation time by simulation. As the number of layers increased, the required computation time reduced. However, such speed-up effect was saturatedas the layers increased to some extent. This study attempted to explain this saturation effect by the notion of average distance between vertices in the area of complex network, and succeeded to mimic the saturation effect by computer simulation.

  11. Soil infiltration based on bp neural network and grey relational analysis

    Directory of Open Access Journals (Sweden)

    Wang Juan

    2013-02-01

    Full Text Available Soil infiltration is a key link of the natural water cycle process. Studies on soil permeability are conducive for water resources assessment and estimation, runoff regulation and management, soil erosion modeling, nonpoint and point source pollution of farmland, among other aspects. The unequal influence of rainfall duration, rainfall intensity, antecedent soil moisture, vegetation cover, vegetation type, and slope gradient on soil cumulative infiltration was studied under simulated rainfall and different underlying surfaces. We established a six factor-model of soil cumulative infiltration by the improved back propagation (BP-based artificial neural network algorithm with a momentum term and self-adjusting learning rate. Compared to the multiple nonlinear regression method, the stability and accuracy of the improved BP algorithm was better. Based on the improved BP model, the sensitive index of these six factors on soil cumulative infiltration was investigated. Secondly, the grey relational analysis method was used to individually study grey correlations among these six factors and soil cumulative infiltration. The results of the two methods were very similar. Rainfall duration was the most influential factor, followed by vegetation cover, vegetation type, rainfall intensity and antecedent soil moisture. The effect of slope gradient on soil cumulative infiltration was not significant.

  12. Music training relates to the development of neural mechanisms of selective auditory attention.

    Science.gov (United States)

    Strait, Dana L; Slater, Jessica; O'Connell, Samantha; Kraus, Nina

    2015-04-01

    Selective attention decreases trial-to-trial variability in cortical auditory-evoked activity. This effect increases over the course of maturation, potentially reflecting the gradual development of selective attention and inhibitory control. Work in adults indicates that music training may alter the development of this neural response characteristic, especially over brain regions associated with executive control: in adult musicians, attention decreases variability in auditory-evoked responses recorded over prefrontal cortex to a greater extent than in nonmusicians. We aimed to determine whether this musician-associated effect emerges during childhood, when selective attention and inhibitory control are under development. We compared cortical auditory-evoked variability to attended and ignored speech streams in musicians and nonmusicians across three age groups: preschoolers, school-aged children and young adults. Results reveal that childhood music training is associated with reduced auditory-evoked response variability recorded over prefrontal cortex during selective auditory attention in school-aged child and adult musicians. Preschoolers, on the other hand, demonstrate no impact of selective attention on cortical response variability and no musician distinctions. This finding is consistent with the gradual emergence of attention during this period and may suggest no pre-existing differences in this attention-related cortical metric between children who undergo music training and those who do not. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  13. Discrepancy of neural response between exogenous and endogenous task switching: an event-related potentials study.

    Science.gov (United States)

    Miyajima, Maki; Toyomaki, Atsuhito; Hashimoto, Naoki; Kusumi, Ichiro; Murohashi, Harumitsu; Koyama, Tsukasa

    2012-08-01

    Task switching is a well-known cognitive paradigm to explore task-set reconfiguration processes such as rule shifting. In particular, endogenous task switching is thought to differ qualitatively from stimulus-triggered exogenous task switching. However, no previous study has examined the neural substrate of endogenous task switching. The purpose of the present study is to explore the differences between event-related potential responses to exogenous and endogenous rule switching at cue stimulus. We modified two patterns of cued switching tasks: exogenous (bottom-up) rule switching and endogenous (top-down) rule switching. In each task cue stimulus was configured to induce switching or maintaining rule. In exogenous switching tasks, late positive deflection was larger in the switch rule condition than in the maintain rule condition. However, in endogenous switching tasks late positive deflection was unexpectedly larger in the maintain-rule condition than in the switch-rule condition. These results indicate that exogenous rule switching is explicit stimulus-driven processes, whereas endogenous rule switching is implicitly parallel processes independent of external stimulus.

  14. Adolescent neural response to reward is related to participant sex and task motivation.

    Science.gov (United States)

    Alarcón, Gabriela; Cservenka, Anita; Nagel, Bonnie J

    2017-02-01

    Risky decision making is prominent during adolescence, perhaps contributed to by heightened sensation seeking and ongoing maturation of reward and dopamine systems in the brain, which are, in part, modulated by sex hormones. In this study, we examined sex differences in the neural substrates of reward sensitivity during a risky decision-making task and hypothesized that compared with girls, boys would show heightened brain activation in reward-relevant regions, particularly the nucleus accumbens, during reward receipt. Further, we hypothesized that testosterone and estradiol levels would mediate this sex difference. Moreover, we predicted boys would make more risky choices on the task. While boys showed increased nucleus accumbens blood oxygen level-dependent (BOLD) response relative to girls, sex hormones did not mediate this effect. As predicted, boys made a higher percentage of risky decisions during the task. Interestingly, boys also self-reported more motivation to perform well and earn money on the task, while girls self-reported higher state anxiety prior to the scan session. Motivation to earn money partially mediated the effect of sex on nucleus accumbens activity during reward. Previous research shows that increased motivation and salience of reinforcers is linked with more robust striatal BOLD response, therefore psychosocial factors, in addition to sex, may play an important role in reward sensitivity. Elucidating neurobiological mechanisms that support adolescent sex differences in risky decision making has important implications for understanding individual differences that lead to advantageous and adverse behaviors that affect health outcomes. Copyright © 2016 Elsevier Inc. All rights reserved.

  15. Distribution of language-related Cntnap2 protein in neural circuits critical for vocal learning.

    Science.gov (United States)

    Condro, Michael C; White, Stephanie A

    2014-01-01

    Variants of the contactin associated protein-like 2 (Cntnap2) gene are risk factors for language-related disorders including autism spectrum disorder, specific language impairment, and stuttering. Songbirds are useful models for study of human speech disorders due to their shared capacity for vocal learning, which relies on similar cortico-basal ganglia circuitry and genetic factors. Here we investigate Cntnap2 protein expression in the brain of the zebra finch, a songbird species in which males, but not females, learn their courtship songs. We hypothesize that Cntnap2 has overlapping functions in vocal learning species, and expect to find protein expression in song-related areas of the zebra finch brain. We further expect that the distribution of this membrane-bound protein may not completely mirror its mRNA distribution due to the distinct subcellular localization of the two molecular species. We find that Cntnap2 protein is enriched in several song control regions relative to surrounding tissues, particularly within the adult male, but not female, robust nucleus of the arcopallium (RA), a cortical song control region analogous to human layer 5 primary motor cortex. The onset of this sexually dimorphic expression coincides with the onset of sensorimotor learning in developing males. Enrichment in male RA appears due to expression in projection neurons within the nucleus, as well as to additional expression in nerve terminals of cortical projections to RA from the lateral magnocellular nucleus of the nidopallium. Cntnap2 protein expression in zebra finch brain supports the hypothesis that this molecule affects neural connectivity critical for vocal learning across taxonomic classes. Copyright © 2013 Wiley Periodicals, Inc.

  16. Parametric models to relate spike train and LFP dynamics with neural information processing.

    Science.gov (United States)

    Banerjee, Arpan; Dean, Heather L; Pesaran, Bijan

    2012-01-01

    Spike trains and local field potentials (LFPs) resulting from extracellular current flows provide a substrate for neural information processing. Understanding the neural code from simultaneous spike-field recordings and subsequent decoding of information processing events will have widespread applications. One way to demonstrate an understanding of the neural code, with particular advantages for the development of applications, is to formulate a parametric statistical model of neural activity and its covariates. Here, we propose a set of parametric spike-field models (unified models) that can be used with existing decoding algorithms to reveal the timing of task or stimulus specific processing. Our proposed unified modeling framework captures the effects of two important features of information processing: time-varying stimulus-driven inputs and ongoing background activity that occurs even in the absence of environmental inputs. We have applied this framework for decoding neural latencies in simulated and experimentally recorded spike-field sessions obtained from the lateral intraparietal area (LIP) of awake, behaving monkeys performing cued look-and-reach movements to spatial targets. Using both simulated and experimental data, we find that estimates of trial-by-trial parameters are not significantly affected by the presence of ongoing background activity. However, including background activity in the unified model improves goodness of fit for predicting individual spiking events. Uncovering the relationship between the model parameters and the timing of movements offers new ways to test hypotheses about the relationship between neural activity and behavior. We obtained significant spike-field onset time correlations from single trials using a previously published data set where significantly strong correlation was only obtained through trial averaging. We also found that unified models extracted a stronger relationship between neural response latency and trial

  17. Intelligent Prediction of Soccer Technical Skill on Youth Soccer Player's Relative Performance Using Multivariate Analysis and Artificial Neural Network Techniques

    OpenAIRE

    Abdullah, M. R; Maliki, A. B. H. M; Musa, R. M; Kosni, N. A; Juahir, H

    2016-01-01

    This study aims to predict the potential pattern of soccer technical skill on Malaysia youth soccer players relative performance using multivariate analysis and artificial neural network techniques. 184 male youth soccer players were recruited in Malaysia soccer academy (average age = 15.2±2.0) underwent to, physical fitness test, anthropometric, maturity, motivation and the level of skill related soccer. Unsupervised pattern recognition of principal component analysis (PCA) was used to ident...

  18. Rationale and Methodology of Reprogramming for Generation of Induced Pluripotent Stem Cells and Induced Neural Progenitor Cells

    Directory of Open Access Journals (Sweden)

    Zuojun Tian

    2016-04-01

    Full Text Available Great progress has been made regarding the capabilities to modify somatic cell fate ever since the technology for generation of induced pluripotent stem cells (iPSCs was discovered in 2006. Later, induced neural progenitor cells (iNPCs were generated from mouse and human cells, bypassing some of the concerns and risks of using iPSCs in neuroscience applications. To overcome the limitation of viral vector induced reprogramming, bioactive small molecules (SM have been explored to enhance the efficiency of reprogramming or even replace transcription factors (TFs, making the reprogrammed cells more amenable to clinical application. The chemical induced reprogramming process is a simple process from a technical perspective, but the choice of SM at each step is vital during the procedure. The mechanisms underlying cell transdifferentiation are still poorly understood, although, several experimental data and insights have indicated the rationale of cell reprogramming. The process begins with the forced expression of specific TFs or activation/inhibition of cell signaling pathways by bioactive chemicals in defined culture condition, which initiates the further reactivation of endogenous gene program and an optimal stoichiometric expression of the endogenous pluri- or multi-potency genes, and finally leads to the birth of reprogrammed cells such as iPSCs and iNPCs. In this review, we first outline the rationale and discuss the methodology of iPSCs and iNPCs in a stepwise manner; and then we also discuss the chemical-based reprogramming of iPSCs and iNPCs.

  19. Automatic processing of semantic relations in fMRI: neural activation during semantic priming of taxonomic and thematic categories.

    Science.gov (United States)

    Sachs, Olga; Weis, Susanne; Zellagui, Nadia; Huber, Walter; Zvyagintsev, Mikhail; Mathiak, Klaus; Kircher, Tilo

    2008-07-07

    Most current models of knowledge organization are based on hierarchical or taxonomic categories (animals, tools). Another important organizational pattern is thematic categorization, i.e. categories held together by external relations, a unifying scene or event (car and garage). The goal of this study was to compare the neural correlates of these categories under automatic processing conditions that minimize strategic influences. We used fMRI to examine neural correlates of semantic priming for category members with a short stimulus onset asynchrony (SOA) of 200 ms as subjects performed a lexical decision task. Four experimental conditions were compared: thematically related words (car-garage); taxonomically related (car-bus); unrelated (car-spoon); non-word trials (car-derf). We found faster reaction times for related than for unrelated prime-target pairs for both thematic and taxonomic categories. However, the size of the thematic priming effect was greater than that of the taxonomic. The imaging data showed signal changes for the taxonomic priming effects in the right precuneus, postcentral gyrus, middle frontal and superior frontal gyri and thematic priming effects in the right middle frontal gyrus and anterior cingulate. The contrast of neural priming effects showed larger signal changes in the right precuneus associated with the taxonomic but not with thematic priming response. We suggest that the greater involvement of precuneus in the processing of taxonomic relations indicates their reduced salience in the knowledge structure compared to more prominent thematic relations.

  20. Digital generation, net generation, millennials, Y generation: reflecting about the relation between the youths and digital technologies

    OpenAIRE

    Martins, Cristina; Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS) Rede La Salle

    2015-01-01

    This study aimed is critically reflect on the relationship of the youths with the TD, by discussing the generational approach. This approach in different researches linked the youths, through terms like Digital Generation, Net Generation, Millennials and Y Generation, creating stereotypes and excluding social, cultural, economic and political perspectives. The results of this qualitative research, based on reflections through literature, sees reality of Brazilian youths that do not have acces...

  1. The neural basis of analogical reasoning: an event-related potential study.

    Science.gov (United States)

    Qiu, Jiang; Li, Hong; Chen, Antao; Zhang, Qinglin

    2008-10-01

    The spatiotemporal analysis of brain activation during the execution of easy analogy (EA) and difficult analogy (DA) tasks was investigated using high-density event-related brain potentials (ERPs). Results showed that reasoning tasks (schema induction) elicited a more negative ERP deflection (N500-1000) than did the baseline task (BS) between 500 and 1000 ms. Dipole source analysis of difference waves (EA-BS and DA-BS) indicated that the negative components were both localized near the left thalamus, possibly associated with the retrieval of alphabetical information. Furthermore, DA elicited a more positive ERP component (P600-1000) than did EA in the same time window. Two generators of P600-1000 were located in the medial prefrontal cortex (BA10) and the left frontal cortex (BA6) which was possibly involved in integrating information in schema abstraction. In the stage of analogy mapping, a greater negativity (N400-600) in the reasoning tasks as compared to BS was found over fronto-central scalp regions. A generator of this effect was located in the left fusiform gyrus and was possibly related to associative memory and activation of schema. Then, a greater negativity in the reasoning tasks, in comparison to BS task, developed between 900-1200 ms (LNC1) and 2000-2500 ms (LNC2). Dipole source analysis (EA-BS) localized the generator of LNC1 in the left prefrontal cortex (BA 10) which was possibly related to mapping the schema to the target problem, and the generator of LNC2 in the left prefrontal cortex (BA 9) which was possibly related to deciding whether a conclusion correctly follows from the schema.

  2. Visual working memory load-related changes in neural activity and functional connectivity.

    Directory of Open Access Journals (Sweden)

    Ling Li

    Full Text Available BACKGROUND: Visual working memory (VWM helps us store visual information to prepare for subsequent behavior. The neuronal mechanisms for sustaining coherent visual information and the mechanisms for limited VWM capacity have remained uncharacterized. Although numerous studies have utilized behavioral accuracy, neural activity, and connectivity to explore the mechanism of VWM retention, little is known about the load-related changes in functional connectivity for hemi-field VWM retention. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we recorded electroencephalography (EEG from 14 normal young adults while they performed a bilateral visual field memory task. Subjects had more rapid and accurate responses to the left visual field (LVF memory condition. The difference in mean amplitude between the ipsilateral and contralateral event-related potential (ERP at parietal-occipital electrodes in retention interval period was obtained with six different memory loads. Functional connectivity between 128 scalp regions was measured by EEG phase synchronization in the theta- (4-8 Hz, alpha- (8-12 Hz, beta- (12-32 Hz, and gamma- (32-40 Hz frequency bands. The resulting matrices were converted to graphs, and mean degree, clustering coefficient and shortest path length was computed as a function of memory load. The results showed that brain networks of theta-, alpha-, beta-, and gamma- frequency bands were load-dependent and visual-field dependent. The networks of theta- and alpha- bands phase synchrony were most predominant in retention period for right visual field (RVF WM than for LVF WM. Furthermore, only for RVF memory condition, brain network density of theta-band during the retention interval were linked to the delay of behavior reaction time, and the topological property of alpha-band network was negative correlation with behavior accuracy. CONCLUSIONS/SIGNIFICANCE: We suggest that the differences in theta- and alpha- bands between LVF and RVF

  3. The modulating effect of personality traits on neural error monitoring: evidence from event-related FMRI.

    Science.gov (United States)

    Sosic-Vasic, Zrinka; Ulrich, Martin; Ruchsow, Martin; Vasic, Nenad; Grön, Georg

    2012-01-01

    The present study investigated the association between traits of the Five Factor Model of Personality (Neuroticism, Extraversion, Openness for Experiences, Agreeableness, and Conscientiousness) and neural correlates of error monitoring obtained from a combined Eriksen-Flanker-Go/NoGo task during event-related functional magnetic resonance imaging in 27 healthy subjects. Individual expressions of personality traits were measured using the NEO-PI-R questionnaire. Conscientiousness correlated positively with error signaling in the left inferior frontal gyrus and adjacent anterior insula (IFG/aI). A second strong positive correlation was observed in the anterior cingulate gyrus (ACC). Neuroticism was negatively correlated with error signaling in the inferior frontal cortex possibly reflecting the negative inter-correlation between both scales observed on the behavioral level. Under present statistical thresholds no significant results were obtained for remaining scales. Aligning the personality trait of Conscientiousness with task accomplishment striving behavior the correlation in the left IFG/aI possibly reflects an inter-individually different involvement whenever task-set related memory representations are violated by the occurrence of errors. The strong correlations in the ACC may indicate that more conscientious subjects were stronger affected by these violations of a given task-set expressed by individually different, negatively valenced signals conveyed by the ACC upon occurrence of an error. Present results illustrate that for predicting individual responses to errors underlying personality traits should be taken into account and also lend external validity to the personality trait approach suggesting that personality constructs do reflect more than mere descriptive taxonomies.

  4. The modulating effect of personality traits on neural error monitoring: evidence from event-related FMRI.

    Directory of Open Access Journals (Sweden)

    Zrinka Sosic-Vasic

    Full Text Available The present study investigated the association between traits of the Five Factor Model of Personality (Neuroticism, Extraversion, Openness for Experiences, Agreeableness, and Conscientiousness and neural correlates of error monitoring obtained from a combined Eriksen-Flanker-Go/NoGo task during event-related functional magnetic resonance imaging in 27 healthy subjects. Individual expressions of personality traits were measured using the NEO-PI-R questionnaire. Conscientiousness correlated positively with error signaling in the left inferior frontal gyrus and adjacent anterior insula (IFG/aI. A second strong positive correlation was observed in the anterior cingulate gyrus (ACC. Neuroticism was negatively correlated with error signaling in the inferior frontal cortex possibly reflecting the negative inter-correlation between both scales observed on the behavioral level. Under present statistical thresholds no significant results were obtained for remaining scales. Aligning the personality trait of Conscientiousness with task accomplishment striving behavior the correlation in the left IFG/aI possibly reflects an inter-individually different involvement whenever task-set related memory representations are violated by the occurrence of errors. The strong correlations in the ACC may indicate that more conscientious subjects were stronger affected by these violations of a given task-set expressed by individually different, negatively valenced signals conveyed by the ACC upon occurrence of an error. Present results illustrate that for predicting individual responses to errors underlying personality traits should be taken into account and also lend external validity to the personality trait approach suggesting that personality constructs do reflect more than mere descriptive taxonomies.

  5. Visual Working Memory Load-Related Changes in Neural Activity and Functional Connectivity

    Science.gov (United States)

    Li, Ling; Zhang, Jin-Xiang; Jiang, Tao

    2011-01-01

    Background Visual working memory (VWM) helps us store visual information to prepare for subsequent behavior. The neuronal mechanisms for sustaining coherent visual information and the mechanisms for limited VWM capacity have remained uncharacterized. Although numerous studies have utilized behavioral accuracy, neural activity, and connectivity to explore the mechanism of VWM retention, little is known about the load-related changes in functional connectivity for hemi-field VWM retention. Methodology/Principal Findings In this study, we recorded electroencephalography (EEG) from 14 normal young adults while they performed a bilateral visual field memory task. Subjects had more rapid and accurate responses to the left visual field (LVF) memory condition. The difference in mean amplitude between the ipsilateral and contralateral event-related potential (ERP) at parietal-occipital electrodes in retention interval period was obtained with six different memory loads. Functional connectivity between 128 scalp regions was measured by EEG phase synchronization in the theta- (4–8 Hz), alpha- (8–12 Hz), beta- (12–32 Hz), and gamma- (32–40 Hz) frequency bands. The resulting matrices were converted to graphs, and mean degree, clustering coefficient and shortest path length was computed as a function of memory load. The results showed that brain networks of theta-, alpha-, beta-, and gamma- frequency bands were load-dependent and visual-field dependent. The networks of theta- and alpha- bands phase synchrony were most predominant in retention period for right visual field (RVF) WM than for LVF WM. Furthermore, only for RVF memory condition, brain network density of theta-band during the retention interval were linked to the delay of behavior reaction time, and the topological property of alpha-band network was negative correlation with behavior accuracy. Conclusions/Significance We suggest that the differences in theta- and alpha- bands between LVF and RVF conditions in

  6. Histamine H3 receptor density is negatively correlated with neural activity related to working memory in humans.

    Science.gov (United States)

    Ito, Takehito; Kimura, Yasuyuki; Seki, Chie; Ichise, Masanori; Yokokawa, Keita; Kawamura, Kazunori; Takahashi, Hidehiko; Higuchi, Makoto; Zhang, Ming-Rong; Suhara, Tetsuya; Yamada, Makiko

    2018-06-14

    The histamine H 3 receptor is regarded as a drug target for cognitive impairments in psychiatric disorders. H 3 receptors are expressed in neocortical areas, including the prefrontal cortex, the key region of cognitive functions such as working memory. However, the role of prefrontal H 3 receptors in working memory has not yet been clarified. Therefore, using functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) techniques, we aimed to investigate the association between the neural activity of working memory and the density of H 3 receptors in the prefrontal cortex. Ten healthy volunteers underwent both fMRI and PET scans. The N-back task was used to assess the neural activities related to working memory. H 3 receptor density was measured with the selective PET radioligand [ 11 C] TASP457. The neural activity of the right dorsolateral prefrontal cortex during the performance of the N-back task was negatively correlated with the density of H 3 receptors in this region. Higher neural activity of working memory was associated with lower H 3 receptor density in the right dorsolateral prefrontal cortex. This finding elucidates the role of H 3 receptors in working memory and indicates the potential of H 3 receptors as a therapeutic target for the cognitive impairments associated with neuropsychiatric disorders.

  7. Artificial Neural Network Model for Alkali-Surfactant-Polymer Flooding in Viscous Oil Reservoirs: Generation and Application

    Directory of Open Access Journals (Sweden)

    Si Le Van

    2016-12-01

    Full Text Available Chemical flooding has been widely utilized to recover a large portion of the oil remaining in light and viscous oil reservoirs after the primary and secondary production processes. As core-flood tests and reservoir simulations take time to accurately estimate the recovery performances as well as analyzing the feasibility of an injection project, it is necessary to find a powerful tool to quickly predict the results with a level of acceptable accuracy. An approach involving the use of an artificial neural network to generate a representative model for estimating the alkali-surfactant-polymer flooding performance and evaluating the economic feasibility of viscous oil reservoirs from simulation is proposed in this study. A typical chemical flooding project was referenced for this numerical study. A number of simulations have been made for training on the basis of a base case from the design of 13 parameters. After training, the network scheme generated from a ratio data set of 50%-20%-30% corresponding to the number of samples used for training-validation-testing was selected for estimation with the total coefficient of determination of 0.986 and a root mean square error of 1.63%. In terms of model application, the chemical concentration and injection strategy were optimized to maximize the net present value (NPV of the project at a specific oil price from the just created ANN model. To evaluate the feasibility of the project comprehensively in terms of market variations, a range of oil prices from 30 $/bbl to 60 $/bbl referenced from a real market situation was considered in conjunction with its probability following a statistical distribution on the NPV computation. Feasibility analysis of the optimal chemical injection scheme revealed a variation of profit from 0.42 $MM to 1.0 $MM, corresponding to the changes in oil price. In particular, at the highest possible oil prices, the project can earn approximately 0.61 $MM to 0.87 $MM for a quarter

  8. Decision Support System for Age-Related Macular Degeneration Using Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Mostafa Langarizadeh

    2017-09-01

    Full Text Available Introduction: Age-related macular degeneration (AMD is one of the major causes of visual loss among the elderly. It causes degeneration of cells in the macula. Early diagnosis can be helpful in preventing blindness. Drusen are the initial symptoms of AMD. Since drusen have a wide variety, locating them in screening images is difficult and time-consuming. An automated digital fundus photography-based screening system help overcome such drawbacks. The main objective of this study was to suggest a novel method to classify AMD and normal retinal fundus images. Materials and Methods: The suggested system was developed using convolutional neural networks. Several methods were adopted for increasing data such as horizontal reflection, random crop, as well as transfer and combination of such methods. The suggested system was evaluated using images obtained from STARE database and a local dataset. Results: The local dataset contained 3195 images (2070 images of AMD suspects and 1125 images of healthy retina and the STARE dataset comprised of 201 images (105 images of AMD suspects and 96 images of healthy retina. According to the results, the accuracies of the local and standard datasets were 0.95 and 0.81, respectively. Conclusion: Diagnosis and screening of AMD is a time-consuming task for specialists. To overcome this limitation, we attempted to design an intelligent decision support system for the diagnosis of AMD fundus using retina images. The proposed system is an important step toward providing a reliable tool for supervising patients. Early diagnosis of AMD can lead to timely access to treatment.

  9. The Neural Cell Adhesion Molecule NCAM2/OCAM/RNCAM, a Close Relative to NCAM

    DEFF Research Database (Denmark)

    Kulahin, Nikolaj; Walmod, Peter

    2008-01-01

    molecule (NCAM) is a well characterized, ubiquitously expressed CAM that is highly expressed in the nervous system. In addition to mediating cell adhesion, NCAM participates in a multitude of cellular events, including survival, migration, and differentiation of cells, outgrowth of neurites, and formation......Cell adhesion molecules (CAMs) constitute a large class of plasma membrane-anchored proteins that mediate attachment between neighboring cells and between cells and the surrounding extracellular matrix (ECM). However, CAMs are more than simple mediators of cell adhesion. The neural cell adhesion...... and plasticity of synapses. NCAM shares an overall sequence identity of approximately 44% with the neural cell adhesion molecule 2 (NCAM2), a protein also known as olfactory cell adhesion molecule (OCAM) and Rb-8 neural cell adhesion molecule (RNCAM), and the region-for-region sequence homology between the two...

  10. Chaotic diagonal recurrent neural network

    International Nuclear Information System (INIS)

    Wang Xing-Yuan; Zhang Yi

    2012-01-01

    We propose a novel neural network based on a diagonal recurrent neural network and chaos, and its structure and learning algorithm are designed. The multilayer feedforward neural network, diagonal recurrent neural network, and chaotic diagonal recurrent neural network are used to approach the cubic symmetry map. The simulation results show that the approximation capability of the chaotic diagonal recurrent neural network is better than the other two neural networks. (interdisciplinary physics and related areas of science and technology)

  11. Identifying Tmem59 related gene regulatory network of mouse neural stem cell from a compendium of expression profiles

    Directory of Open Access Journals (Sweden)

    Guo Xiuyun

    2011-09-01

    Full Text Available Abstract Background Neural stem cells offer potential treatment for neurodegenerative disorders, such like Alzheimer's disease (AD. While much progress has been made in understanding neural stem cell function, a precise description of the molecular mechanisms regulating neural stem cells is not yet established. This lack of knowledge is a major barrier holding back the discovery of therapeutic uses of neural stem cells. In this paper, the regulatory mechanism of mouse neural stem cell (NSC differentiation by tmem59 is explored on the genome-level. Results We identified regulators of tmem59 during the differentiation of mouse NSCs from a compendium of expression profiles. Based on the microarray experiment, we developed the parallelized SWNI algorithm to reconstruct gene regulatory networks of mouse neural stem cells. From the inferred tmem59 related gene network including 36 genes, pou6f1 was identified to regulate tmem59 significantly and might play an important role in the differentiation of NSCs in mouse brain. There are four pathways shown in the gene network, indicating that tmem59 locates in the downstream of the signalling pathway. The real-time RT-PCR results shown that the over-expression of pou6f1 could significantly up-regulate tmem59 expression in C17.2 NSC line. 16 out of 36 predicted genes in our constructed network have been reported to be AD-related, including Ace, aqp1, arrdc3, cd14, cd59a, cds1, cldn1, cox8b, defb11, folr1, gdi2, mmp3, mgp, myrip, Ripk4, rnd3, and sncg. The localization of tmem59 related genes and functional-related gene groups based on the Gene Ontology (GO annotation was also identified. Conclusions Our findings suggest that the expression of tmem59 is an important factor contributing to AD. The parallelized SWNI algorithm increased the efficiency of network reconstruction significantly. This study enables us to highlight novel genes that may be involved in NSC differentiation and provides a shortcut to

  12. Towards modeling of combined cooling, heating and power system with artificial neural network for exergy destruction and exergy efficiency prognostication of tri-generation components

    International Nuclear Information System (INIS)

    Taghavifar, Hadi; Anvari, Simin; Saray, Rahim Khoshbakhti; Khalilarya, Shahram; Jafarmadar, Samad; Taghavifar, Hamid

    2015-01-01

    The current study is an attempt to address the investigation of the CCHP (combined cooling, heating and power) system when 10 input variables were chosen to analyze 10 most important objective output parameters. Moreover, ANN (artificial neural network) was successfully applied on the tri-generation system on account of its capability to predict responses with great confidence. The results of sensitivity analysis were considered as foundation for selecting the most suitable and potent input parameters of the supposed cycle. Furthermore, the best ANN topology was attained based on the least amount of MSE and number of iterations. Consequently, the trainlm (Levenberg–Marquardt) training approach with 10-9-10 configuration has been exploited for ANN modeling in order to give the best output correspondence. The maximum MRE = 1.75% (mean relative error) and minimum R 2  = 0.984 represents the reliability and outperformance of the developed ANN over common conventional thermodynamic analysis carried out by EES (engineering equation solver) software. - Highlights: • Exergy analysis is undertaken for CCHP components based on operative factors. • ANN tool is applied to obtained database from thermodynamic analyses session. • The best ANN topology is detected at 10-9-10 with trainlm learning algorithm. • The input and output layer parameters were selected based on sensitivity analysis.

  13. Estimation of Entropy Generation for Ag-MgO/Water Hybrid Nanofluid Flow through Rectangular Minichannel by Using Artificial Neural Network

    OpenAIRE

    Uysal, Cuneyt; Korkmaz, Mehmet Erdi

    2018-01-01

    The convective heat transfer andentropy generation characteristics of Ag-MgO/water hybrid nanofluid flowthrough rectangular minichannel were numerically investigated. The Reynoldsnumber was in the range of 200 to 2000 and different nanoparticle volume fractionswere varied between = 0.005 and 0.02. In addition, ArtificialNeural Network was used to create a model for estimating of entropy generationof Ag-MgO/water hybrid nanofluid flow. As a result, it was found th...

  14. A methodology based on dynamic artificial neural network for short-term forecasting of the power output of a PV generator

    International Nuclear Information System (INIS)

    Almonacid, F.; Pérez-Higueras, P.J.; Fernández, Eduardo F.; Hontoria, L.

    2014-01-01

    Highlights: • The output of the majority of renewables energies depends on the variability of the weather conditions. • The short-term forecast is going to be essential for effectively integrating solar energy sources. • A new method based on artificial neural network to predict the power output of a PV generator one hour ahead is proposed. • This new method is based on dynamic artificial neural network to predict global solar irradiance and the air temperature. • The methodology developed can be used to estimate the power output of a PV generator with a satisfactory margin of error. - Abstract: One of the problems of some renewables energies is that the output of these kinds of systems is non-dispatchable depending on variability of weather conditions that cannot be predicted and controlled. From this point of view, the short-term forecast is going to be essential for effectively integrating solar energy sources, being a very useful tool for the reliability and stability of the grid ensuring that an adequate supply is present. In this paper a new methodology for forecasting the output of a PV generator one hour ahead based on dynamic artificial neural network is presented. The results of this study show that the proposed methodology could be used to forecast the power output of PV systems one hour ahead with an acceptable degree of accuracy

  15. Sowing Seeds for Future Generations: Development of Generative Concern and Its Relation to Environmental Narrative Identity

    Science.gov (United States)

    Jia, Fanli; Soucie, Kendall; Alisat, Susan; Pratt, Michael

    2016-01-01

    In this longitudinal study, we examined the relationship between the trajectory of generative concern measured at ages 23, 26 and 32 and environmental narrative identity at age 32. Canadian participants completed a questionnaire on generative concern at ages 23, 26 and 32 and were then interviewed about their personal experiences with the…

  16. Neural substrates of semantic relationships: common and distinct left-frontal activities for generation of synonyms vs. antonyms.

    Science.gov (United States)

    Jeon, Hyeon-Ae; Lee, Kyoung-Min; Kim, Young-Bo; Cho, Zang-Hee

    2009-11-01

    Synonymous and antonymous relationships among words may reflect the organization and/or processing in the mental lexicon and its implementation in the brain. In this study, functional magnetic resonance imaging (fMRI) is employed to compare brain activities during generation of synonyms (SYN) and antonyms (ANT) prompted by the same words. Both SYN and ANT, when compared with reading nonwords (NW), activated a region in the left middle frontal gyrus (BA 46). Neighboring this region, there was a dissociation observed in that the ANT activation extended more anteriorly and laterally to the SYN activation. The activations in the left middle frontal gyrus may be related to mental processes that are shared in the SYN and ANT generations, such as engaging semantically related parts of mental lexicon for the word search, whereas the distinct activations unique for either SYN or ANT generation may reflect the additional component of antonym retrieval, namely, reversing the polarity of semantic relationship in one crucial dimension. These findings suggest that specific components in the semantic processing, such as the polarity reversal for antonym generation and the similarity assessment for synonyms, are separately and systematically laid out in the left-frontal cortex.

  17. Identification and integration of sensory modalities: Neural basis and relation to consciousness

    NARCIS (Netherlands)

    Pennartz, C.M.A.

    2009-01-01

    A key question in studying consciousness is how neural operations in the brain can identify streams of sensory input as belonging to distinct modalities, which contributes to the representation of qualitatively different experiences. The basis for identification of modalities is proposed to be

  18. Identifying beneficial task relations for multi-task learning in deep neural networks

    DEFF Research Database (Denmark)

    Bingel, Joachim; Søgaard, Anders

    2017-01-01

    Multi-task learning (MTL) in deep neural networks for NLP has recently received increasing interest due to some compelling benefits, including its potential to efficiently regularize models and to reduce the need for labeled data. While it has brought significant improvements in a number of NLP...

  19. Neural reward processing is modulated by approach- and avoidance-related personality traits

    NARCIS (Netherlands)

    Simon, J.J.; Walther, S.; Fiebach, C.J.; Friederich, H.C.; Stippich, C.; Weisbrod, M.; Kaiser, S.

    2009-01-01

    The neural processing of reward can be differentiated into two sub-components with different functions, "wanting" (i.e., the expectation of a reward which includes appetitive and motivational components) and "liking" (i.e., the hedonic impact experienced during the receipt of a reward), involving

  20. Neural Networks Relating Alloy Composition, Microstructure, and Tensile Properties of α/ β-Processed TIMETAL 6-4

    Science.gov (United States)

    Collins, Peter C.; Koduri, Santhosh; Welk, Brian; Tiley, Jaimie; Fraser, Hamish L.

    2013-03-01

    Bayesian neural networks have been developed, which relate composition, microstructure, and tensile properties of the alloy TIMETAL 6-4 (nominal composition: Ti-6Al-4V (wt pct) after thermomechanical processing (TMP) in the two-phase ( α + β)-phase field. The developed networks are able to make interpolative predictions of properties within the ranges of composition and microstructural features that are in the population of the database used for training and testing of the networks. In addition, the neural networks have been used to conduct virtual experiments which permit the functional dependencies of properties on composition and microstructural features to be determined. In this way, it is shown that in the microstructural condition resulting from TMP in the two-phase ( α + β) phase field, the most significant contribution to strength is from solid solution strengthening, with microstructural features apparently influencing the balance of a number of properties.

  1. A study of the relative importance of the peroxiredoxin-, catalase-, and glutathione-dependent systems in neural peroxide metabolism.

    Science.gov (United States)

    Mitozo, Péricles Arruda; de Souza, Luiz Felipe; Loch-Neckel, Gecioni; Flesch, Samira; Maris, Angelica Francesca; Figueiredo, Cláudia Pinto; Dos Santos, Adair Roberto Soares; Farina, Marcelo; Dafre, Alcir Luiz

    2011-07-01

    Cells are endowed with several overlapping peroxide-degrading systems whose relative importance is a matter of debate. In this study, three different sources of neural cells (rat hippocampal slices, rat C6 glioma cells, and mouse N2a neuroblastoma cells) were used as models to understand the relative contributions of individual peroxide-degrading systems. After a pretreatment (30 min) with specific inhibitors, each system was challenged with either H₂O₂ or cumene hydroperoxide (CuOOH), both at 100 μM. Hippocampal slices, C6 cells, and N2a cells showed a decrease in the H₂O₂ decomposition rate (23-28%) by a pretreatment with the catalase inhibitor aminotriazole. The inhibition of glutathione reductase (GR) by BCNU (1,3-bis(2-chloroethyl)-1-nitrosourea) significantly decreased H₂O₂ and CuOOH decomposition rates (31-77%). Inhibition of catalase was not as effective as BCNU at decreasing cell viability (MTT assay) and cell permeability or at increasing DNA damage (comet test). Impairing the thioredoxin (Trx)-dependent peroxiredoxin (Prx) recycling by thioredoxin reductase (TrxR) inhibition with auranofin neither potentiated peroxide toxicity nor decreased the peroxide-decomposition rate. The results indicate that neural peroxidatic systems depending on Trx/TrxR for recycling are not as important as those depending on GSH/GR. Dimer formation, which leads to Prx2 inactivation, was observed in hippocampal slices and N2a cells treated with H₂O₂, but not in C6 cells. However, Prx-SO₃ formation, another form of Prx inactivation, was observed in all neural cell types tested, indicating that redox-mediated signaling pathways can be modulated in neural cells. These differences in Prx2 dimerization suggest specific redox regulation mechanisms in glia-derived (C6) compared to neuron-derived (N2a) cells and hippocampal slices. Copyright © 2011 Elsevier Inc. All rights reserved.

  2. Optimal design of permanent magnet flux switching generator for wind applications via artificial neural network and multi-objective particle swarm optimization hybrid approach

    International Nuclear Information System (INIS)

    Meo, Santolo; Zohoori, Alireza; Vahedi, Abolfazl

    2016-01-01

    Highlights: • A new optimal design of flux switching permanent magnet generator is developed. • A prototype is employed to validate numerical data used for optimization. • A novel hybrid multi-objective particle swarm optimization approach is proposed. • Optimization targets are weight, cost, voltage and its total harmonic distortion. • The hybrid approach preference is proved compared with other optimization methods. - Abstract: In this paper a new hybrid approach obtained combining a multi-objective particle swarm optimization and artificial neural network is proposed for the design optimization of a direct-drive permanent magnet flux switching generators for low power wind applications. The targets of the proposed multi-objective optimization are to reduce the costs and weight of the machine while maximizing the amplitude of the induced voltage as well as minimizing its total harmonic distortion. The permanent magnet width, the stator and rotor tooth width, the rotor teeth number and stator pole number of the machine define the search space for the optimization problem. Four supervised artificial neural networks are designed for modeling the complex relationships among the weight, the cost, the amplitude and the total harmonic distortion of the output voltage respect to the quantities of the search space. Finite element analysis is adopted to generate training dataset for the artificial neural networks. Finite element analysis based model is verified by experimental results with a 1.5 kW permanent magnet flux switching generator prototype suitable for renewable energy applications, having 6/19 stator poles/rotor teeth. Finally the effectiveness of the proposed hybrid procedure is compared with the results given by conventional multi-objective optimization algorithms. The obtained results show the soundness of the proposed multi objective optimization technique and its feasibility to be adopted as suitable methodology for optimal design of permanent

  3. The Relation between Finger Gnosis and Mathematical Ability: Why Redeployment of Neural Circuits Best Explains the Finding

    Directory of Open Access Journals (Sweden)

    Marcie ePenner-Wilger

    2013-12-01

    Full Text Available This paper elaborates a novel hypothesis regarding the observed predictive relation between finger gnosis and mathematical ability. In brief, we suggest that these two cognitive phenomena have overlapping neural substrates, as the result of the re-use (redeployment of part of the finger gnosis circuit for the purpose of representing numbers. We offer some background on the relation and current explanations for it; an outline of our alternate hypothesis; some evidence supporting redeployment over current views; and a plan for further research.

  4. Fgf8-related secondary organizers exert different polarizing planar instructions along the mouse anterior neural tube.

    Science.gov (United States)

    Crespo-Enriquez, Ivan; Partanen, Juha; Martinez, Salvador; Echevarria, Diego

    2012-01-01

    Early brain patterning depends on proper arrangement of positional information. This information is given by gradients of secreted signaling molecules (morphogens) detected by individual cells within the responding tissue, leading to specific fate decisions. Here we report that the morphogen FGF8 exerts initially a differential signal activity along the E9.5 mouse neural tube. We demonstrate that this polarizing activity codes by RAS-regulated ERK1/2 signaling and depends on the topographical location of the secondary organizers: the isthmic organizer (IsO) and the anterior neural ridge (anr) but not on zona limitans intrathalamica (zli). Our results suggest that Sprouty2, a negative modulator of RAS/ERK pathway, is important for regulating Fgf8 morphogenetic signal activity by controlling Fgf8-induced signaling pathways and positional information during early brain development.

  5. Application of neural networks for finding the relation between stress and operational parameters of NPP Temelin

    International Nuclear Information System (INIS)

    Ruzek, L.

    2003-01-01

    Quick and sufficiently precise determination of stresses and strains measured by I and C, TMDS a CHEMIS is very important for on-line assessment of continuous damage of material under operating conditions. The application of some of the artificial intelligence methods, viz. neural network, is convenient in this context. A practical example of the application of this method is presented and the advantages in comparison with the finite element method (FEM) are discussed. The approach to the selection of characteristic loading used for the preparation of training data is also shown. The paper presents the results of actual calculation and analyses the merits of the attained coincidence for the determination of the tensor of stresses by FEM and neural networks

  6. The Rack-Gear Tool Generation Modelling. Non-Analytical Method Developed in CATIA, Using the Relative Generating Trajectories Method

    Science.gov (United States)

    Teodor, V. G.; Baroiu, N.; Susac, F.; Oancea, N.

    2016-11-01

    The modelling of a curl of surfaces associated with a pair of rolling centrodes, when it is known the profile of the rack-gear's teeth profile, by direct measuring, as a coordinate matrix, has as goal the determining of the generating quality for an imposed kinematics of the relative motion of tool regarding the blank. In this way, it is possible to determine the generating geometrical error, as a base of the total error. The generation modelling allows highlighting the potential errors of the generating tool, in order to correct its profile, previously to use the tool in machining process. A method developed in CATIA is proposed, based on a new method, namely the method of “relative generating trajectories”. They are presented the analytical foundation, as so as some application for knows models of rack-gear type tools used on Maag teething machines.

  7. Assessing neural activity related to decision-making through flexible odds ratio curves and their derivatives.

    Science.gov (United States)

    Roca-Pardiñas, Javier; Cadarso-Suárez, Carmen; Pardo-Vazquez, Jose L; Leboran, Victor; Molenberghs, Geert; Faes, Christel; Acuña, Carlos

    2011-06-30

    It is well established that neural activity is stochastically modulated over time. Therefore, direct comparisons across experimental conditions and determination of change points or maximum firing rates are not straightforward. This study sought to compare temporal firing probability curves that may vary across groups defined by different experimental conditions. Odds-ratio (OR) curves were used as a measure of comparison, and the main goal was to provide a global test to detect significant differences of such curves through the study of their derivatives. An algorithm is proposed that enables ORs based on generalized additive models, including factor-by-curve-type interactions to be flexibly estimated. Bootstrap methods were used to draw inferences from the derivatives curves, and binning techniques were applied to speed up computation in the estimation and testing processes. A simulation study was conducted to assess the validity of these bootstrap-based tests. This methodology was applied to study premotor ventral cortex neural activity associated with decision-making. The proposed statistical procedures proved very useful in revealing the neural activity correlates of decision-making in a visual discrimination task. Copyright © 2011 John Wiley & Sons, Ltd.

  8. Neural network approaches to tracer identification as related to PIV research

    International Nuclear Information System (INIS)

    Seeley, C.H. Jr.

    1992-12-01

    Neural networks have become very powerful tools in many fields of interest. This thesis examines the application of neural networks to another rapidly growing field flow visualization. Flow visualization research is used to experimentally determine how fluids behave and to verify computational results obtained analytically. A form of flow visualization, particle image velocimetry (PIV). determines the flow movement by tracking neutrally buoyant particles suspended in the fluid. PIV research has begun to improve rapidly with the advent of digital imagers, which can quickly digitize an image into arrays of grey levels. These grey level arrays are analyzed to determine the location of the tracer particles. Once the particles positions have been determined across multiple image frames, it is possible to track their movements, and hence, the flow of the fluid. This thesis explores the potential of several different neural networks to identify the positions of the tracer particles. Among these networks are Backpropagation, Kohonen (counter-propagation), and Cellular. Each of these algorithms were employed in their basic form, and training and testing were performed on a synthetic grey level array. Modifications were then made to them in attempts to improve the results

  9. Neural network approaches to tracer identification as related to PIV research

    Energy Technology Data Exchange (ETDEWEB)

    Seeley, C.H. Jr.

    1992-12-01

    Neural networks have become very powerful tools in many fields of interest. This thesis examines the application of neural networks to another rapidly growing field flow visualization. Flow visualization research is used to experimentally determine how fluids behave and to verify computational results obtained analytically. A form of flow visualization, particle image velocimetry (PIV). determines the flow movement by tracking neutrally buoyant particles suspended in the fluid. PIV research has begun to improve rapidly with the advent of digital imagers, which can quickly digitize an image into arrays of grey levels. These grey level arrays are analyzed to determine the location of the tracer particles. Once the particles positions have been determined across multiple image frames, it is possible to track their movements, and hence, the flow of the fluid. This thesis explores the potential of several different neural networks to identify the positions of the tracer particles. Among these networks are Backpropagation, Kohonen (counter-propagation), and Cellular. Each of these algorithms were employed in their basic form, and training and testing were performed on a synthetic grey level array. Modifications were then made to them in attempts to improve the results.

  10. Emotional expectations influence neural sensitivity to fearful faces in humans:An event-related potential study

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The present study tested whether neural sensitivity to salient emotional facial expressions was influenced by emotional expectations induced by a cue that validly predicted the expression of a subsequently presented target face. Event-related potentials (ERPs) elicited by fearful and neutral faces were recorded while participants performed a gender discrimination task under cued (‘expected’) and uncued (‘unexpected’) conditions. The behavioral results revealed that accuracy was lower for fearful compared with neutral faces in the unexpected condition, while accuracy was similar for fearful and neutral faces in the expected condition. ERP data revealed increased amplitudes in the P2 component and 200–250 ms interval for unexpected fearful versus neutral faces. By contrast, ERP responses were similar for fearful and neutral faces in the expected condition. These findings indicate that human neural sensitivity to fearful faces is modulated by emotional expectations. Although the neural system is sensitive to unpredictable emotionally salient stimuli, sensitivity to salient stimuli is reduced when these stimuli are predictable.

  11. Nicotinergic Modulation of Attention-Related Neural Activity Differentiates Polymorphisms of DRD2 and CHRNA4 Receptor Genes.

    Directory of Open Access Journals (Sweden)

    Thomas P K Breckel

    Full Text Available Cognitive and neuronal effects of nicotine show high interindividual variability. Recent findings indicate that genetic variations that affect the cholinergic and dopaminergic neurotransmitter system impact performance in cognitive tasks and effects of nicotine. The current pharmacogenetic functional magnetic resonance imaging (fMRI study aimed to investigate epistasis effects of CHRNA4/DRD2 variations on behavioural and neural correlates of visuospatial attention after nicotine challenge using a data driven partial least squares discriminant analysis (PLS-DA approach. Fifty young healthy non-smokers were genotyped for CHRNA4 (rs1044396 and DRD2 (rs6277. They received either 7 mg transdermal nicotine or a matched placebo in a double blind within subject design prior to performing a cued target detection task with valid and invalid trials. On behavioural level, the strongest benefits of nicotine in invalid trials were observed in participants carrying both, the DRD2 T- and CHRNA4 C+ variant. Neurally, we were able to demonstrate that different DRD2/CHRNA4 groups can be decoded from the pattern of brain activity in invalid trials under nicotine. Neural substrates of interindividual variability were found in a network of attention-related brain regions comprising the pulvinar, the striatum, the middle and superior frontal gyri, the insula, the left precuneus, and the right middle temporal gyrus. Our findings suggest that polymorphisms in the CHRNA4 and DRD2 genes are a relevant source of individual variability in pharmacological studies with nicotine.

  12. Overvoltages related to distributed generation-power system interconnection transformer

    Energy Technology Data Exchange (ETDEWEB)

    Zamanillo, G.R.; Gomez, J.C.; Florena, E.F. [Rio Cuarto National University (IPSEP/UNRC), Cordoba (Argentina). Electric Power Systems Protection Institute], Email: jcgomez@ing.unrc.edu.ar

    2009-07-01

    The energy crisis that experiences the world drives to carry to an extreme, the use of all energy sources which are available. The sources need to be connected to the electric network in their next point, requiring of electric-electronic interfaces. The traditional electric power systems are changing their characteristics, in what concerns to structure, operation and on overvoltage generation. This change is not taking place in coordinated form among the involved sectors. The interconnection of a Distributed Generator (DG) directly with the power system is objectionable and risky. It is required of an interconnection transformer which performs several functions. Rigid specifications do not exist in this respect, for the variety of systems in use in the world, nevertheless there are utilities recommendations. Overvoltages caused by the DG, which arise due to the change of structure of the electric system, are explained. The transformer connection selection, presents positive and negative aspects that impact the utility and the user in a different or many times in an antagonistic way. The phenomenon of balanced and unbalanced ferroresonance overvoltage is studied. This phenomenon can takes place when using DG, either with synchronous or asynchronous generator, and for any type of connection of the transformer. The necessary conditions so that the phenomenon appears are presented. Eight interconnection transformer connection ways were studied. It is concluded that the solutions to reach by means of the employment of the DG, offer technical-economic advantages so much to the utility as to the user. It is also concluded in this work that the more advisable interconnection type is function of the system connection type. (author)

  13. The perception of risks related to electricity generation

    Energy Technology Data Exchange (ETDEWEB)

    Midden, C J; Daamen, D D; Verplanken, B

    1987-01-01

    Some of the key findings are discussed of psychological research on the perception of risks and attitudes with respect to the use of uranium and coal for electricity generation. It appears that attitudes are mostly not based on ideology but rather determined by a trade-off of expected risks and advantages. Lay estimates of probabilities are compared with expert judgements. In the last section attitudes of people living near existing or planned power plants are analyzed. Serious doubts are raised about the possibilities to give residents economic compensation for exposure to risks. 1 fig., 29 refs.

  14. Optimizing the wind power generation in low wind speed areas using an advanced hybrid RBF neural network coupled with the HGA-GSA optimization method

    Energy Technology Data Exchange (ETDEWEB)

    Assareh, Ehsanolah; Poultangari, Iman [Dezful Branch, Islamic Azad University, Dezful (Iran, Islamic Republic of); Tandis, Emad [Mechanical Engineering Department, University of Jundi Shapor, Dezful (Iran, Islamic Republic of); Nedael, Mojtaba [Dept. of Energy Engineering, Graduate School of the Environment and Energy, Science and Research Branch, Islamic Azad University, Tehran (Iran, Islamic Republic of)

    2016-10-15

    Enhancing the energy production from wind power in low-wind areas has always been a fundamental subject of research in the field of wind energy industry. In the first phase of this research, an initial investigation was performed to evaluate the potential of wind in south west of Iran. The initial results indicate that the wind potential in the studied location is not sufficient enough and therefore the investigated region is identified as a low wind speed area. In the second part of this study, an advanced optimization model was presented to regulate the torque in the wind generators. For this primary purpose, the torque of wind turbine is adjusted using a Proportional and integral (PI) control system so that at lower speeds of the wind, the power generated by generator is enhanced significantly. The proposed model uses the RBF neural network to adjust the net obtained gains of the PI controller for the purpose of acquiring the utmost electricity which is produced through the generator. Furthermore, in order to edify and instruct the neural network, the optimal data set is obtained by a Hybrid genetic algorithm along with a gravitational search algorithm (HGA-GSA). The proposed method is evaluated by using a 5MW wind turbine manufactured by National Renewable Energy Laboratory (NREL). Final results of this study are indicative of the satisfactory and successful performance of the proposed investigated model.

  15. Neural correlates of consciousness: a definition of the dorsal and ventral streams and their relation to phenomenology.

    Science.gov (United States)

    Vakalopoulos, Costa

    2005-01-01

    The paper presents a hypothesis for a neural correlate of consciousness. A proposal is made that both the dorsal and ventral streams must be concurrently active to generate conscious awareness and that V1 (striate cortex) provides a serial link between them. An argument is presented against a true extrastriate communication between the dorsal and ventral streams. Secondly, a detailed theory is developed for the structure of the visual hierarchy. Premotor theory states that each organism-object interaction can be described by the two quantitative measures of torque and change in joint position served by the basal ganglia and cerebellum, respectively. This leads to a component theory of motor efference copy providing a fundamental tool for categorizing dorsal and ventral stream networks. The rationale for this is that the dorsal stream specifies spatial coordinates of the external world, which can be coded by the reafference of changes in joint position. The ventral stream is concerned with object recognition and is coded for by forces exerted on the world during a developmental exploratory phase of the organism. The proposed pathways for a component motor efference copy from both the cerebellum and basal ganglia converge on the thalamus and modulate thalamocortical projections via the thalamic reticular nucleus. The origin of the corticopontine projections, which are a massive pathway for cortical information to reach the cerebellum, coincides with the area typically considered as part of the dorsal stream, whereas the entire cortex projects to the striatum. This adds empirical support for a new conceptualization of the visual streams. The model also presents a solution to the binding problem of a neural correlate of consciousness, that is, how a distributed neural network synchronizes its activity during a cognitive event. It represents a reinterpretation of the current status of the visual hierarchy.

  16. The role of trauma-related distractors on neural systems for working memory and emotion processing in posttraumatic stress disorder.

    Science.gov (United States)

    Morey, Rajendra A; Dolcos, Florin; Petty, Christopher M; Cooper, Debra A; Hayes, Jasmeet Pannu; LaBar, Kevin S; McCarthy, Gregory

    2009-05-01

    The relevance of emotional stimuli to threat and survival confers a privileged role in their processing. In PTSD, the ability of trauma-related information to divert attention is especially pronounced. Information unrelated to the trauma may also be highly distracting when it shares perceptual features with trauma material. Our goal was to study how trauma-related environmental cues modulate working memory networks in PTSD. We examined neural activity in participants performing a visual working memory task while distracted by task-irrelevant trauma and non-trauma material. Recent post-9/11 veterans were divided into a PTSD group (n=22) and a trauma-exposed control group (n=20) based on the Davidson trauma scale. Using fMRI, we measured hemodynamic change in response to emotional (trauma-related) and neutral distraction presented during the active maintenance period of a delayed-response working memory task. The goal was to examine differences in functional networks associated with working memory (dorsolateral prefrontal cortex and lateral parietal cortex) and emotion processing (amygdala, ventrolateral prefrontal cortex, and fusiform gyrus). The PTSD group showed markedly different neural activity compared to the trauma-exposed control group in response to task-irrelevant visual distractors. Enhanced activity in ventral emotion processing regions was associated with trauma distractors in the PTSD group, whereas activity in brain regions associated with working memory and attention regions was disrupted by distractor stimuli independent of trauma content. Neural evidence for the impact of distraction on working memory is consistent with PTSD symptoms of hypervigilance and general distractibility during goal-directed cognitive processing.

  17. Organization of the sleep-related neural systems in the brain of the minke whale (Balaenoptera acutorostrata).

    Science.gov (United States)

    Dell, Leigh-Anne; Karlsson, Karl Ae; Patzke, Nina; Spocter, Muhammad A; Siegel, Jerome M; Manger, Paul R

    2016-07-01

    The current study analyzed the nuclear organization of the neural systems related to the control and regulation of sleep and wake in the basal forebrain, diencephalon, midbrain, and pons of the minke whale, a mysticete cetacean. While odontocete cetaceans sleep in an unusual manner, with unihemispheric slow wave sleep (USWS) and suppressed REM sleep, it is unclear whether the mysticete whales show a similar sleep pattern. Previously, we detailed a range of features in the odontocete brain that appear to be related to odontocete-type sleep, and here present our analysis of these features in the minke whale brain. All neural elements involved in sleep regulation and control found in bihemispheric sleeping mammals and the harbor porpoise were present in the minke whale, with no specific nuclei being absent, and no novel nuclei being present. This qualitative similarity relates to the cholinergic, noradrenergic, serotonergic and orexinergic systems, and the GABAergic elements of these nuclei. Quantitative analysis revealed that the numbers of pontine cholinergic (274,242) and noradrenergic (203,686) neurons, and hypothalamic orexinergic neurons (277,604), are markedly higher than other large-brained bihemispheric sleeping mammals. Small telencephalic commissures (anterior, corpus callosum, and hippocampal), an enlarged posterior commissure, supernumerary pontine cholinergic and noradrenergic cells, and an enlarged peripheral division of the dorsal raphe nuclear complex of the minke whale, all indicate that the suite of neural characteristics thought to be involved in the control of USWS and the suppression of REM in the odontocete cetaceans are present in the minke whale. J. Comp. Neurol. 524:2018-2035, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  18. Neural tube defects – disorders of neurulation and related embryonic processes

    Science.gov (United States)

    Copp, Andrew J.; Greene, Nicholas D. E.

    2014-01-01

    Neural tube defects (NTDs) are severe congenital malformations affecting 1 in every 1000 pregnancies. ‘Open’ NTDs result from failure of primary neurulation as seen in anencephaly, myelomeningocele (open spina bifida) and craniorachischisis. Degeneration of the persistently open neural tube in utero leads to loss of neurological function below the lesion level. ‘Closed’ NTDs are skin-covered disorders of spinal cord structure, ranging from asymptomatic spina bifida occulta to severe spinal cord tethering, and usually traceable to disruption of secondary neurulation. ‘Herniation’ NTDs are those in which meninges, with or without brain or spinal cord tissue, become exteriorised through a pathological opening in the skull or vertebral column (e.g. encephalocele and meningocele). NTDs have multifactorial etiology, with genes and environmental factors interacting to determine individual risk of malformation. While over 200 mutant genes cause open NTDs in mice, much less is known about the genetic causation of human NTDs. Recent evidence has implicated genes of the planar cell polarity signalling pathway in a proportion of cases. The embryonic development of NTDs is complex, with diverse cellular and molecular mechanisms operating at different levels of the body axis. Molecular regulatory events include the BMP and Sonic hedgehog pathways which have been implicated in control of neural plate bending. Primary prevention of NTDs has been implemented clinically following the demonstration that folic acid, when taken as a peri-conceptional supplement, can prevent many cases. Not all NTDs respond to folic acid, however, and adjunct therapies are required for prevention of this folic acid-resistant category. PMID:24009034

  19. Lateralised sleep spindles relate to false memory generation.

    Science.gov (United States)

    Shaw, John J; Monaghan, Padraic

    2017-12-01

    Sleep is known to enhance false memories: After presenting participants with lists of semantically related words, sleeping before recalling these words results in a greater acceptance of unseen "lure" words related in theme to previously seen words. Furthermore, the right hemisphere (RH) seems to be more prone to false memories than the left hemisphere (LH). In the current study, we investigated the sleep architecture associated with these false memory and lateralisation effects in a nap study. Participants viewed lists of related words, then stayed awake or slept for approximately 90min, and were then tested for recognition of previously seen-old, unseen-new, or unseen-lure words presented either to the LH or RH. Sleep increased acceptance of unseen-lure words as previously seen compared to the wake group, particularly for RH presentations of word lists. RH lateralised stage 2 sleep spindle density relative to the LH correlated with this increase in false memories, suggesting that RH sleep spindles enhanced false memories in the RH. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Neural Networks

    International Nuclear Information System (INIS)

    Smith, Patrick I.

    2003-01-01

    Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neural networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing

  1. The specificity of neural responses to music and their relation to voice processing: an fMRI-adaptation study.

    Science.gov (United States)

    Armony, Jorge L; Aubé, William; Angulo-Perkins, Arafat; Peretz, Isabelle; Concha, Luis

    2015-04-23

    Several studies have identified, using functional magnetic resonance imaging (fMRI), a region within the superior temporal gyrus that preferentially responds to musical stimuli. However, in most cases, significant responses to other complex stimuli, particularly human voice, were also observed. Thus, it remains unknown if the same neurons respond to both stimulus types, albeit with different strengths, or whether the responses observed with fMRI are generated by distinct, overlapping neural populations. To address this question, we conducted an fMRI experiment in which short music excerpts and human vocalizations were presented in a pseudo-random order. Critically, we performed an adaptation-based analysis in which responses to the stimuli were analyzed taking into account the category of the preceding stimulus. Our results confirm the presence of a region in the anterior STG that responds more strongly to music than voice. Moreover, we found a music-specific adaptation effect in this area, consistent with the existence of music-preferred neurons. Lack of differences between musicians and non-musicians argues against an expertise effect. These findings provide further support for neural separability between music and speech within the temporal lobe. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  2. Altered Neural Activity during Irony Comprehension in Unaffected First-Degree Relatives of Schizophrenia Patients—An fMRI Study

    Directory of Open Access Journals (Sweden)

    Róbert Herold

    2018-01-01

    Full Text Available Irony is a type of figurative language in which the literal meaning of the expression is the opposite of what the speaker intends to communicate. Even though schizophrenic patients are known as typically impaired in irony comprehension and in the underlying neural functions, to date no one has explored the neural correlates of figurative language comprehension in first-degree relatives of schizophrenic patients. In the present study, we examined the neural correlates of irony understanding in schizophrenic patients and in unaffected first-degree relatives of patients compared to healthy adults with functional MRI. Our aim was to investigate if possible alterations of the neural circuits supporting irony comprehension in first-degree relatives of patients with schizophrenia would fulfill the familiality criterion of an endophenotype. We examined 12 schizophrenic patients, 12 first-degree relatives of schizophrenia patients and 12 healthy controls with functional MRI while they were performing irony and control tasks. Different phases of irony processing were examined, such as context processing and ironic statement comprehension. Patients had significantly more difficulty understanding irony than controls or relatives. Patients also showed markedly different neural activation pattern compared to controls in both stages of irony processing. Although no significant differences were found in the performance of the irony tasks between the control group and the relative group, during the fMRI analysis, the relatives showed stronger brain activity in the left dorsolateral prefrontal cortex during the context processing phase of irony tasks than the control group. However, the controls demonstrated higher activations in the left dorsomedial prefrontal cortex and in the right inferior frontal gyrus during the ironic statement phase of the irony tasks than the relative group. Our results show that despite good task performance, first-degree relatives of

  3. Internal mechanisms underlying anticipatory language processing: Evidence from event-related-potentials and neural oscillations.

    Science.gov (United States)

    Li, Xiaoqing; Zhang, Yuping; Xia, Jinyan; Swaab, Tamara Y

    2017-07-28

    Although numerous studies have demonstrated that the language processing system can predict upcoming content during comprehension, there is still no clear picture of the anticipatory stage of predictive processing. This electroencephalograph study examined the cognitive and neural oscillatory mechanisms underlying anticipatory processing during language comprehension, and the consequences of this prediction for bottom-up processing of predicted/unpredicted content. Participants read Mandarin Chinese sentences that were either strongly or weakly constraining and that contained critical nouns that were congruent or incongruent with the sentence contexts. We examined the effects of semantic predictability on anticipatory processing prior to the onset of the critical nouns and on integration of the critical nouns. The results revealed that, at the integration stage, the strong-constraint condition (compared to the weak-constraint condition) elicited a reduced N400 and reduced theta activity (4-7Hz) for the congruent nouns, but induced beta (13-18Hz) and theta (4-7Hz) power decreases for the incongruent nouns, indicating benefits of confirmed predictions and potential costs of disconfirmed predictions. More importantly, at the anticipatory stage, the strongly constraining context elicited an enhanced sustained anterior negativity and beta power decrease (19-25Hz), which indicates that strong prediction places a higher processing load on the anticipatory stage of processing. The differences (in the ease of processing and the underlying neural oscillatory activities) between anticipatory and integration stages of lexical processing were discussed with regard to predictive processing models. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Mass generation and related issues from exotic higher dimensions

    Energy Technology Data Exchange (ETDEWEB)

    Colatto, Luiz Paulo [Centro Federal de Educacao Tecnologica Celso Suckow da Fonseca (CEFET), Petropolis, RJ (Brazil); Andrade, Marco Antonio de [Universidade do Estado do Rio de Janeiro (UERJ), Resende, RJ (Brazil); Assis, Leonardo Paulo Guimaraes de; Helayel-Neto, Jose Abdalla [Centro Brasileiro de Pesquisas Fisicas(LAFEX/CBPF), Rio de Janeiro, RJ (Brazil). Coordenacao de Fisica Experimental de Altas Energias; Matheus-Valle, Jose Luiz [Universidade Federal de Juiz de Fora (UFJF), MG (Brazil); Rojas, Moises [Universidade Federal de Lavras, MG (Brazil)

    2011-07-01

    Full text: he main purpose of this work is to show that massless Dirac equation formulated for non-interacting Majorana-Weyl spinors in higher dimensions, particularly in D = 1 + 9 and D = 5 + 5, may yield to an interpretation of massive Majorana and Dirac spinors in D = 1 + 3 dimensions. The particular case of a dimensional reduction from D = 4 + 4 to D = 1 + 3 has already been fairly-well discussed in the literature. By adopting suitable representations of the Dirac matrices in higher dimensions, we pursue the investigation of which higher dimensional space-times and which metric signatures concerning massless Dirac equations in highermay induce massive spinors in D = 1+3 dimensions. The mixing of the chiral fermions in higher dimensions may induce a mechanism such that four massive Majorana fermions may show up and, at an appropriate limit an almost zero and a huge mass show up with corresponding left-handed and right-handed eigenstates. This mechanism could reassess a peculiar connection with the See-Saw scheme associated to neutrino with Majorana-type masses. The masses of the particle are fixed by the dimensional reduction scheme, which the decoupled dimensions contribute coordinates and depend on the mass invariants in lower dimensions. This proposal should allow us to understand the generation of hierarchies for the fermionic masses in D = 1 + 3, or in lower dimensions in general, starting from the constraints between the energy and the momentum in (n; n) dimensions. For the initial D = 5 + 5 Majorana-Weyl spinors framework using the Weyl representation to the Dirac matrices we observe an intriguing decomposition of space-time that result in two equivalent D = 1 + 4 massive spinors which mass term, in D = 1 + 3 included, is originated from the remained component and that could induce a Brane-World mechanism. (author)

  5. A Model for Hourly Solar Radiation Data Generation from Daily Solar Radiation Data Using a Generalized Regression Artificial Neural Network

    OpenAIRE

    Khatib, Tamer; Elmenreich, Wilfried

    2015-01-01

    This paper presents a model for predicting hourly solar radiation data using daily solar radiation averages. The proposed model is a generalized regression artificial neural network. This model has three inputs, namely, mean daily solar radiation, hour angle, and sunset hour angle. The output layer has one node which is mean hourly solar radiation. The training and development of the proposed model are done using MATLAB and 43800 records of hourly global solar radiation. The results show that...

  6. Neural responses to threat and reward interact to predict stress-related problem drinking: A novel protective role of the amygdala

    Science.gov (United States)

    2012-01-01

    Background Research into neural mechanisms of drug abuse risk has focused on the role of dysfunction in neural circuits for reward. In contrast, few studies have examined the role of dysfunction in neural circuits of threat in mediating drug abuse risk. Although typically regarded as a risk factor for mood and anxiety disorders, threat-related amygdala reactivity may serve as a protective factor against substance use disorders, particularly in individuals with exaggerated responsiveness to reward. Findings We used well-established neuroimaging paradigms to probe threat-related amygdala and reward-related ventral striatum reactivity in a sample of 200 young adult students from the ongoing Duke Neurogenetics Study. Recent life stress and problem drinking were assessed using self-report. We found a significant three-way interaction between threat-related amygdala reactivity, reward-related ventral striatum reactivity, and recent stress, wherein individuals with higher reward-related ventral striatum reactivity exhibit higher levels of problem drinking in the context of stress, but only if they also have lower threat-related amygdala reactivity. This three-way interaction predicted both contemporaneous problem drinking and problem drinking reported three-months later in a subset of participants. Conclusions These findings suggest complex interactions between stress and neural responsiveness to both threat and reward mediate problem drinking. Furthermore, they highlight a novel protective role for threat-related amygdala reactivity against drug use in individuals with high neural reactivity to reward. PMID:23151390

  7. Suppressing images of desire: Neural correlates of chocolate-related thoughts in high and low trait chocolate cravers.

    Science.gov (United States)

    Miedl, Stephan F; Blechert, Jens; Meule, Adrian; Richard, Anna; Wilhelm, Frank H

    2018-03-05

    Chocolate is the most often craved food in Western societies and many individuals try to resist its temptation due to weight concerns. Suppressing chocolate-related thoughts might, however, lead to paradoxical enhancements of these thoughts and this effect might be more pronounced in individuals with frequent chocolate cravings. In the current study, neural and cognitive correlates of chocolate thought suppression were investigated as a function of trait chocolate craving. Specifically, 20 high and 20 low trait chocolate cravers followed suppression vs. free thinking instructions after being exposed to chocolate and neutral images. Enhanced cue reactivity was evident in high trait chocolate cravers in that they reported more chocolate-related thoughts selectively after chocolate images compared to their low trait craving counterparts. This cue reactivity was mirrored neurally by higher activation in the ventral and dorsal striatum, demonstrating enhanced reward system activity. Unexpectedly, high trait chocolate cravers successfully reduced their elevated chocolate thoughts in the suppression condition. This lends support for the use of thought suppression as a means of regulating unwanted thoughts, cravings and imagery. Whether this thought manipulation is able to curb the elevated cue reactivity and the underlying reward sensitivity in chocolate cravers in applied settings remains to be shown. Copyright © 2018 Elsevier Ltd. All rights reserved.

  8. Considerations in relation to some research on the possible neural underpinnings linked to visual artworks observation

    Directory of Open Access Journals (Sweden)

    Gabriella Bartoli

    2017-05-01

    Full Text Available On the basis of the observations conducted by Freedberg & Gallese (2007 on neural processes implication in organizing the empathetic/aesthetic response, some recent research carried out by neuroscientists and art historians are analyzed, as they demonstrated cortical sensorimotor activation during the observation of abstract artworks (2012, 2013. The role of the “embodied simulation” of artist’s gesture in the empathic perception of artworks is hereby confirmed. These results are commented in light of psychological studies about aesthetic experience, with special regard to those based on a phenomenological methodology. The intention is to further explore possible interactions between neurosciences and phenomenological psychology, in accordance with their respective theoretical and methodological differences.

  9. Fatigue sensation induced by the sounds associated with mental fatigue and its related neural activities: revealed by magnetoencephalography.

    Science.gov (United States)

    Ishii, Akira; Tanaka, Masaaki; Iwamae, Masayoshi; Kim, Chongsoo; Yamano, Emi; Watanabe, Yasuyoshi

    2013-06-13

    It has been proposed that an inappropriately conditioned fatigue sensation could be one cause of chronic fatigue. Although classical conditioning of the fatigue sensation has been reported in rats, there have been no reports in humans. Our aim was to examine whether classical conditioning of the mental fatigue sensation can take place in humans and to clarify the neural mechanisms of fatigue sensation using magnetoencephalography (MEG). Ten and 9 healthy volunteers participated in a conditioning and a control experiment, respectively. In the conditioning experiment, we used metronome sounds as conditioned stimuli and two-back task trials as unconditioned stimuli to cause fatigue sensation. Participants underwent MEG measurement while listening to the metronome sounds for 6 min. Thereafter, fatigue-inducing mental task trials (two-back task trials), which are demanding working-memory task trials, were performed for 60 min; metronome sounds were started 30 min after the start of the task trials (conditioning session). The next day, neural activities while listening to the metronome for 6 min were measured. Levels of fatigue sensation were also assessed using a visual analogue scale. In the control experiment, participants listened to the metronome on the first and second days, but they did not perform conditioning session. MEG was not recorded in the control experiment. The level of fatigue sensation caused by listening to the metronome on the second day was significantly higher relative to that on the first day only when participants performed the conditioning session on the first day. Equivalent current dipoles (ECDs) in the insular cortex, with mean latencies of approximately 190 ms, were observed in six of eight participants after the conditioning session, although ECDs were not identified in any participant before the conditioning session. We demonstrated that the metronome sounds can cause mental fatigue sensation as a result of repeated pairings of the sounds

  10. An analysis of nonlinear dynamics underlying neural activity related to auditory induction in the rat auditory cortex.

    Science.gov (United States)

    Noto, M; Nishikawa, J; Tateno, T

    2016-03-24

    A sound interrupted by silence is perceived as discontinuous. However, when high-intensity noise is inserted during the silence, the missing sound may be perceptually restored and be heard as uninterrupted. This illusory phenomenon is called auditory induction. Recent electrophysiological studies have revealed that auditory induction is associated with the primary auditory cortex (A1). Although experimental evidence has been accumulating, the neural mechanisms underlying auditory induction in A1 neurons are poorly understood. To elucidate this, we used both experimental and computational approaches. First, using an optical imaging method, we characterized population responses across auditory cortical fields to sound and identified five subfields in rats. Next, we examined neural population activity related to auditory induction with high temporal and spatial resolution in the rat auditory cortex (AC), including the A1 and several other AC subfields. Our imaging results showed that tone-burst stimuli interrupted by a silent gap elicited early phasic responses to the first tone and similar or smaller responses to the second tone following the gap. In contrast, tone stimuli interrupted by broadband noise (BN), considered to cause auditory induction, considerably suppressed or eliminated responses to the tone following the noise. Additionally, tone-burst stimuli that were interrupted by notched noise centered at the tone frequency, which is considered to decrease the strength of auditory induction, partially restored the second responses from the suppression caused by BN. To phenomenologically mimic the neural population activity in the A1 and thus investigate the mechanisms underlying auditory induction, we constructed a computational model from the periphery through the AC, including a nonlinear dynamical system. The computational model successively reproduced some of the above-mentioned experimental results. Therefore, our results suggest that a nonlinear, self

  11. Design and related R and D works of 'Monju' steam generators

    Energy Technology Data Exchange (ETDEWEB)

    Nakai, Y; Imanaka, N; Hoshi, Y; Tanaka, K; Hori, M; Yoshikawa, Y

    1975-07-01

    The steam generator is considered to be one of the key components in LMFBR plant. Helical coil type steam generator is selected as a reference for the first Japanese demonstration plant 'MONJU'. The paper gives the structural and functional features of 'MONJU' steam generator together with a brief description of secondary cooling system. The related R and D works are also illustrated. (author)

  12. Obesity and Age-Related Changes in Markers of Oxidative Stress and Inflammation Across Four Generations

    NARCIS (Netherlands)

    Hulsegge, Gerben; Herber-Gast, Gerrie-Cor M; Spijkerman, Annemieke M W; Picavet, H. Susan J; van der Schouw, Yvonne T; Bakker, Stephan J L; Gansevoort, Ron T; Dollé, Martijn E T; Smit, Henriette A; Monique Verschuren, W M

    OBJECTIVE: The prevalence of obesity increases with age and is higher in each younger generation (unfavorable generation shift). This may influence patterns of oxidative stress and inflammation. Age-related changes and generation shifts in markers of oxidative stress and inflammation were

  13. Obesity and Age-Related Changes in Markers of Oxidative Stress and Inflammation Across Four Generations

    NARCIS (Netherlands)

    Hulsegge, Gerben; Herber-Gast, Gerrie-Cor M; Spijkerman, Annemieke M W; Susan, H; Picavet, J; van der Schouw, Yvonne T; Bakker, Stephan J L; Gansevoort, Ron T; Dollé, Martijn E T; Smit, Henriette A; Monique Verschuren, W M

    ObjectiveThe prevalence of obesity increases with age and is higher in each younger generation (unfavorable generation shift). This may influence patterns of oxidative stress and inflammation. Age-related changes and generation shifts in markers of oxidative stress and inflammation were

  14. Neural correlates of instrumental responding in the context of alcohol-related cues index disorder severity and relapse risk.

    Science.gov (United States)

    Schad, Daniel J; Garbusow, Maria; Friedel, Eva; Sommer, Christian; Sebold, Miriam; Hägele, Claudia; Bernhardt, Nadine; Nebe, Stephan; Kuitunen-Paul, Sören; Liu, Shuyan; Eichmann, Uta; Beck, Anne; Wittchen, Hans-Ulrich; Walter, Henrik; Sterzer, Philipp; Zimmermann, Ulrich S; Smolka, Michael N; Schlagenhauf, Florian; Huys, Quentin J M; Heinz, Andreas; Rapp, Michael A

    2018-01-08

    The influence of Pavlovian conditioned stimuli on ongoing behavior may contribute to explaining how alcohol cues stimulate drug seeking and intake. Using a Pavlovian-instrumental transfer task, we investigated the effects of alcohol-related cues on approach behavior (i.e., instrumental response behavior) and its neural correlates, and related both to the relapse after detoxification in alcohol-dependent patients. Thirty-one recently detoxified alcohol-dependent patients and 24 healthy controls underwent instrumental training, where approach or non-approach towards initially neutral stimuli was reinforced by monetary incentives. Approach behavior was tested during extinction with either alcohol-related or neutral stimuli (as Pavlovian cues) presented in the background during functional magnetic resonance imaging (fMRI). Patients were subsequently followed up for 6 months. We observed that alcohol-related background stimuli inhibited the approach behavior in detoxified alcohol-dependent patients (t = - 3.86, p < .001), but not in healthy controls (t = - 0.92, p = .36). This behavioral inhibition was associated with neural activation in the nucleus accumbens (NAcc) (t (30)  = 2.06, p < .05). Interestingly, both the effects were only present in subsequent abstainers, but not relapsers and in those with mild but not severe dependence. Our data show that alcohol-related cues can acquire inhibitory behavioral features typical of aversive stimuli despite being accompanied by a stronger NAcc activation, suggesting salience attribution. The fact that these findings are restricted to abstinence and milder illness suggests that they may be potential resilience factors. LeAD study, http://www.lead-studie.de , NCT01679145.

  15. Persistent neural activity in auditory cortex is related to auditory working memory in humans and nonhuman primates.

    Science.gov (United States)

    Huang, Ying; Matysiak, Artur; Heil, Peter; König, Reinhard; Brosch, Michael

    2016-07-20

    Working memory is the cognitive capacity of short-term storage of information for goal-directed behaviors. Where and how this capacity is implemented in the brain are unresolved questions. We show that auditory cortex stores information by persistent changes of neural activity. We separated activity related to working memory from activity related to other mental processes by having humans and monkeys perform different tasks with varying working memory demands on the same sound sequences. Working memory was reflected in the spiking activity of individual neurons in auditory cortex and in the activity of neuronal populations, that is, in local field potentials and magnetic fields. Our results provide direct support for the idea that temporary storage of information recruits the same brain areas that also process the information. Because similar activity was observed in the two species, the cellular bases of some auditory working memory processes in humans can be studied in monkeys.

  16. Modeling of energy consumption and related GHG (greenhouse gas) intensity and emissions in Europe using general regression neural networks

    International Nuclear Information System (INIS)

    Antanasijević, Davor; Pocajt, Viktor; Ristić, Mirjana; Perić-Grujić, Aleksandra

    2015-01-01

    This paper presents a new approach for the estimation of energy-related GHG (greenhouse gas) emissions at the national level that combines the simplicity of the concept of GHG intensity and the generalization capabilities of ANNs (artificial neural networks). The main objectives of this work includes the determination of the accuracy of a GRNN (general regression neural network) model applied for the prediction of EC (energy consumption) and GHG intensity of energy consumption, utilizing general country statistics as inputs, as well as analysis of the accuracy of energy-related GHG emissions obtained by multiplying the two aforementioned outputs. The models were developed using historical data from the period 2004–2012, for a set of 26 European countries (EU Members). The obtained results demonstrate that the GRNN GHG intensity model provides a more accurate prediction, with the MAPE (mean absolute percentage error) of 4.5%, than tested MLR (multiple linear regression) and second-order and third-order non-linear MPR (multiple polynomial regression) models. Also, the GRNN EC model has high accuracy (MAPE = 3.6%), and therefore both GRNN models and the proposed approach can be considered as suitable for the calculation of GHG emissions. The energy-related predicted GHG emissions were very similar to the actual GHG emissions of EU Members (MAPE = 6.4%). - Highlights: • ANN modeling of GHG intensity of energy consumption is presented. • ANN modeling of energy consumption at the national level is presented. • GHG intensity concept was used for the estimation of energy-related GHG emissions. • The ANN models provide better results in comparison with conventional models. • Forecast of GHG emissions for 26 countries was made successfully with MAPE of 6.4%

  17. The neural basis of love as a subliminal prime: an event-related functional magnetic resonance imaging study.

    Science.gov (United States)

    Ortigue, S; Bianchi-Demicheli, F; Hamilton, A F de C; Grafton, S T

    2007-07-01

    Throughout the ages, love has been defined as a motivated and goal-directed mechanism with explicit and implicit mechanisms. Recent evidence demonstrated that the explicit representation of love recruits subcorticocortical pathways mediating reward, emotion, and motivation systems. However, the neural basis of the implicit (unconscious) representation of love remains unknown. To assess this question, we combined event-related functional magnetic resonance imaging (fMRI) with a behavioral subliminal priming paradigm embedded in a lexical decision task. In this task, the name of either a beloved partner, a neutral friend, or a passionate hobby was subliminally presented before a target stimulus (word, nonword, or blank), and participants were required to decide if the target was a word or not. Behavioral results showed that subliminal presentation of either a beloved's name (love prime) or a passion descriptor (passion prime) enhanced reaction times in a similar fashion. Subliminal presentation of a friend's name (friend prime) did not show any beneficial effects. Functional results showed that subliminal priming with a beloved's name (as opposed to either a friend's name or a passion descriptor) specifically recruited brain areas involved in abstract representations of others and the self, in addition to motivation circuits shared with other sources of passion. More precisely, love primes recruited the fusiform and angular gyri. Our findings suggest that love, as a subliminal prime, involves a specific neural network that surpasses a dopaminergic-motivation system.

  18. Neural correlates of psychological resilience and their relation to life satisfaction in a sample of healthy young adults.

    Science.gov (United States)

    Kong, Feng; Wang, Xu; Hu, Siyuan; Liu, Jia

    2015-12-01

    Psychological resilience refers to the ability to thrive in the face of risk and adversity, which is crucial for individuals' mental and physical health. However, its precise neural correlates are still largely unknown. Here we used resting-state functional magnetic resonance imaging (rs-fMRI) to identify the brain regions underlying this construct by correlating individuals' psychological resilience scores with the regional homogeneity (ReHo) and then examined how these resilience-related regions predicted life satisfaction in a sample of healthy young adults. We found that the ReHo in the bilateral insula, right dorsal anterior cingulate cortex (dACC) and right rostral ACC (rACC) negatively predicted individual differences in psychological resilience, revealing the critical role of the salience network (SN) in psychological resilience. Crucially, the ReHo in the dACC within the SN mediated the effects of psychological resilience on life satisfaction. In summary, these findings suggest that spontaneous activity of the human brain reflect the efficiency of psychological resilience and highlight the dACC within the SN as a neural substrate linking psychological resilience and life satisfaction. Copyright © 2015 Elsevier Inc. All rights reserved.

  19. Mode of effective connectivity within a putative neural network differentiates moral cognitions related to care and justice ethics.

    Science.gov (United States)

    Cáceda, Ricardo; James, G Andrew; Ely, Timothy D; Snarey, John; Kilts, Clinton D

    2011-02-25

    Moral sensitivity refers to the interpretive awareness of moral conflict and can be justice or care oriented. Justice ethics is associated primarily with human rights and the application of moral rules, whereas care ethics is related to human needs and a situational approach involving social emotions. Among the core brain regions involved in moral issue processing are: medial prefrontal cortex, anterior (ACC) and posterior (PCC) cingulate cortex, posterior superior temporal sulcus (pSTS), insula and amygdala. This study sought to inform the long standing debate of whether care and justice moral ethics represent one or two different forms of cognition. Model-free and model-based connectivity analysis were used to identify functional neural networks underlying care and justice ethics for a moral sensitivity task. In addition to modest differences in patterns of associated neural activity, distinct modes of functional and effective connectivity were observed for moral sensitivity for care and justice issues that were modulated by individual variation in moral ability. These results support a neurobiological differentiation between care and justice ethics and suggest that human moral behavior reflects the outcome of integrating opposing rule-based, self-other perspectives, and emotional responses.

  20. Mode of Effective Connectivity within a Putative Neural Network Differentiates Moral Cognitions Related to Care and Justice Ethics

    Science.gov (United States)

    Cáceda, Ricardo; James, G. Andrew; Ely, Timothy D.; Snarey, John; Kilts, Clinton D.

    2011-01-01

    Background Moral sensitivity refers to the interpretive awareness of moral conflict and can be justice or care oriented. Justice ethics is associated primarily with human rights and the application of moral rules, whereas care ethics is related to human needs and a situational approach involving social emotions. Among the core brain regions involved in moral issue processing are: medial prefrontal cortex, anterior (ACC) and posterior (PCC) cingulate cortex, posterior superior temporal sulcus (pSTS), insula and amygdala. This study sought to inform the long standing debate of whether care and justice moral ethics represent one or two different forms of cognition. Methodology/Principal Findings Model-free and model-based connectivity analysis were used to identify functional neural networks underlying care and justice ethics for a moral sensitivity task. In addition to modest differences in patterns of associated neural activity, distinct modes of functional and effective connectivity were observed for moral sensitivity for care and justice issues that were modulated by individual variation in moral ability. Conclusions/Significance These results support a neurobiological differentiation between care and justice ethics and suggest that human moral behavior reflects the outcome of integrating opposing rule-based, self-other perspectives, and emotional responses. PMID:21364916

  1. Effects of the BDNF Val66Met polymorphism and met allele load on declarative memory related neural networks.

    Science.gov (United States)

    Dodds, Chris M; Henson, Richard N; Suckling, John; Miskowiak, Kamilla W; Ooi, Cinly; Tait, Roger; Soltesz, Fruzsina; Lawrence, Phil; Bentley, Graham; Maltby, Kay; Skeggs, Andrew; Miller, Sam R; McHugh, Simon; Bullmore, Edward T; Nathan, Pradeep J

    2013-01-01

    It has been suggested that the BDNF Val66Met polymorphism modulates episodic memory performance via effects on hippocampal neural circuitry. However, fMRI studies have yielded inconsistent results in this respect. Moreover, very few studies have examined the effect of met allele load on activation of memory circuitry. In the present study, we carried out a comprehensive analysis of the effects of the BDNF polymorphism on brain responses during episodic memory encoding and retrieval, including an investigation of the effect of met allele load on memory related activation in the medial temporal lobe. In contrast to previous studies, we found no evidence for an effect of BDNF genotype or met load during episodic memory encoding. Met allele carriers showed increased activation during successful retrieval in right hippocampus but this was contrast-specific and unaffected by met allele load. These results suggest that the BDNF Val66Met polymorphism does not, as previously claimed, exert an observable effect on neural systems underlying encoding of new information into episodic memory but may exert a subtle effect on the efficiency with which such information can be retrieved.

  2. Effects of the BDNF Val66Met polymorphism and met allele load on declarative memory related neural networks.

    Directory of Open Access Journals (Sweden)

    Chris M Dodds

    Full Text Available It has been suggested that the BDNF Val66Met polymorphism modulates episodic memory performance via effects on hippocampal neural circuitry. However, fMRI studies have yielded inconsistent results in this respect. Moreover, very few studies have examined the effect of met allele load on activation of memory circuitry. In the present study, we carried out a comprehensive analysis of the effects of the BDNF polymorphism on brain responses during episodic memory encoding and retrieval, including an investigation of the effect of met allele load on memory related activation in the medial temporal lobe. In contrast to previous studies, we found no evidence for an effect of BDNF genotype or met load during episodic memory encoding. Met allele carriers showed increased activation during successful retrieval in right hippocampus but this was contrast-specific and unaffected by met allele load. These results suggest that the BDNF Val66Met polymorphism does not, as previously claimed, exert an observable effect on neural systems underlying encoding of new information into episodic memory but may exert a subtle effect on the efficiency with which such information can be retrieved.

  3. Mode of effective connectivity within a putative neural network differentiates moral cognitions related to care and justice ethics.

    Directory of Open Access Journals (Sweden)

    Ricardo Cáceda

    Full Text Available BACKGROUND: Moral sensitivity refers to the interpretive awareness of moral conflict and can be justice or care oriented. Justice ethics is associated primarily with human rights and the application of moral rules, whereas care ethics is related to human needs and a situational approach involving social emotions. Among the core brain regions involved in moral issue processing are: medial prefrontal cortex, anterior (ACC and posterior (PCC cingulate cortex, posterior superior temporal sulcus (pSTS, insula and amygdala. This study sought to inform the long standing debate of whether care and justice moral ethics represent one or two different forms of cognition. METHODOLOGY/PRINCIPAL FINDINGS: Model-free and model-based connectivity analysis were used to identify functional neural networks underlying care and justice ethics for a moral sensitivity task. In addition to modest differences in patterns of associated neural activity, distinct modes of functional and effective connectivity were observed for moral sensitivity for care and justice issues that were modulated by individual variation in moral ability. CONCLUSIONS/SIGNIFICANCE: These results support a neurobiological differentiation between care and justice ethics and suggest that human moral behavior reflects the outcome of integrating opposing rule-based, self-other perspectives, and emotional responses.

  4. Interfering with the neural activity of mirror-related frontal areas impairs mentalistic inferences.

    Science.gov (United States)

    Herbet, Guillaume; Lafargue, Gilles; Moritz-Gasser, Sylvie; Bonnetblanc, François; Duffau, Hugues

    2015-07-01

    According to recently proposed interactive dual-process theories, mentalizing abilities emerge from the coherent interaction between two physically distinct neural systems: (1) the mirror network, coding for the low-level embodied representations involved in pre-reflective sociocognitive processes and (2) the mentalizing network per se, which codes for higher level representations subtending the reflective attribution of psychological states. However, although the latest studies have shown that the core areas forming these two neurocognitive systems do indeed maintain effective connectivity during mentalizing, it is unclear whether an intact mirror system (and, more specifically, its anterior node, namely the posterior inferior frontal cortex) is a prerequisite for accurate mentalistic inferences. Intraoperative brain mapping via direct electrical stimulation offers a unique opportunity to address this issue. Electrical stimulation of the brain creates a "virtual" lesion, which provides functional information on well-defined parts of the cerebral cortex. In the present study, five patients were mapped in real time while they performed a mentalizing task. We found six responsive sites: four in the lateral part of the right pars opercularis and two in the dorsal part of the right pars triangularis. On the subcortical level, two additional sites were located within the white matter connectivity of the pars opercularis. Taken as a whole, our results suggest that the right inferior frontal cortex and its underlying axonal connectivity have a key role in mentalizing. Specifically, our findings support the hypothesis whereby transient, functional disruption of the mirror network influences higher order mentalistic inferences.

  5. Let7a involves in neural stem cell differentiation relating with TLX level.

    Science.gov (United States)

    Song, Juhyun; Cho, Kyoung Joo; Oh, Yumi; Lee, Jong Eun

    2015-07-10

    Neural stem cells (NSCs) have the potential for differentiation into neurons known as a groundbreaking therapeutic solution for central nervous system (CNS) diseases. To resolve the therapeutic efficiency of NSCs, recent researchers have focused on the study on microRNA's role in CNS. Some micro RNAs have been reported significant functions in NSC self-renewal and differentiation through the post-transcriptional regulation of neurogenesis genes. MicroRNA-Let7a (Let7a) has known as the regulator of diverse cellular mechanisms including cell differentiation and proliferation. In present study, we investigated whether Let7a regulates NSC differentiation by targeting the nuclear receptor TLX, which is an essential regulator of NSC self-renewal, proliferation and differentiation. We performed the following experiments: western blot analysis, TaqMan assay, RT-PCR, and immunocytochemistry to confirm the alteration of NSCs. Our data showed that let7a play important roles in controlling NSC fate determination. Thus, manipulating Let-7A and TLX could be a novel strategy to enhance the efficiency of NSC's neuronal differentiation for CNS disorders. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  6. Let7a involves in neural stem cell differentiation relating with TLX level

    Energy Technology Data Exchange (ETDEWEB)

    Song, Juhyun [Department of Anatomy, Yonsei University College of Medicine, Seoul (Korea, Republic of); Cho, Kyoung Joo; Oh, Yumi [Department of Anatomy, Yonsei University College of Medicine, Seoul (Korea, Republic of); BK21 Plus Project for Medical Sciences, and Brain Research Institute, Yonsei University College of Medicine, Seoul (Korea, Republic of); Lee, Jong Eun, E-mail: jelee@yuhs.ac [Department of Anatomy, Yonsei University College of Medicine, Seoul (Korea, Republic of); BK21 Plus Project for Medical Sciences, and Brain Research Institute, Yonsei University College of Medicine, Seoul (Korea, Republic of)

    2015-07-10

    Neural stem cells (NSCs) have the potential for differentiation into neurons known as a groundbreaking therapeutic solution for central nervous system (CNS) diseases. To resolve the therapeutic efficiency of NSCs, recent researchers have focused on the study on microRNA's role in CNS. Some micro RNAs have been reported significant functions in NSC self-renewal and differentiation through the post-transcriptional regulation of neurogenesis genes. MicroRNA-Let7a (Let7a) has known as the regulator of diverse cellular mechanisms including cell differentiation and proliferation. In present study, we investigated whether Let7a regulates NSC differentiation by targeting the nuclear receptor TLX, which is an essential regulator of NSC self-renewal, proliferation and differentiation. We performed the following experiments: western blot analysis, TaqMan assay, RT-PCR, and immunocytochemistry to confirm the alteration of NSCs. Our data showed that let7a play important roles in controlling NSC fate determination. Thus, manipulating Let-7A and TLX could be a novel strategy to enhance the efficiency of NSC's neuronal differentiation for CNS disorders. - Highlights: • Let7a influences on NSC differentiation and proliferation. • Let7a involves in mainly NSC differentiation rather than proliferation. • Let7a positively regulates the TLX expression.

  7. Concepts and Relations in Neurally Inspired In Situ Concept-Based Computing.

    Science.gov (United States)

    van der Velde, Frank

    2016-01-01

    In situ concept-based computing is based on the notion that conceptual representations in the human brain are "in situ." In this way, they are grounded in perception and action. Examples are neuronal assemblies, whose connection structures develop over time and are distributed over different brain areas. In situ concepts representations cannot be copied or duplicated because that will disrupt their connection structure, and thus the meaning of these concepts. Higher-level cognitive processes, as found in language and reasoning, can be performed with in situ concepts by embedding them in specialized neurally inspired "blackboards." The interactions between the in situ concepts and the blackboards form the basis for in situ concept computing architectures. In these architectures, memory (concepts) and processing are interwoven, in contrast with the separation between memory and processing found in Von Neumann architectures. Because the further development of Von Neumann computing (more, faster, yet power limited) is questionable, in situ concept computing might be an alternative for concept-based computing. In situ concept computing will be illustrated with a recently developed BABI reasoning task. Neurorobotics can play an important role in the development of in situ concept computing because of the development of in situ concept representations derived in scenarios as needed for reasoning tasks. Neurorobotics would also benefit from power limited and in situ concept computing.

  8. Elucidating the neural correlates of related false memories using a systematic measure of perceptual relatedness.

    Science.gov (United States)

    Turney, Indira C; Dennis, Nancy A

    2017-02-01

    Previous memory research has exploited the perceptual similarities between lures and targets in order to evoke false memories. Nevertheless, while some studies have attempted to use lures that are objectively more similar than others, no study has systematically controlled for perceptual overlap between target and lure items and its role in accounting for false alarm rates or the neural processes underlying such perceptual false memories. The current study looked to fill this gap in the literature by using a face-morphing program to systematically control for the amount of perceptual overlap between lures and targets. Our results converge with previous studies in finding a pattern of differences between true and false memories. Most importantly, expanding upon this work, parametric analyses showed false memory activity increases with respect to the similarity between lures and targets within bilateral middle temporal gyri and right medial prefrontal cortex (mPFC). Moreover, this pattern of activation was unique to false memories and could not be accounted for by relatedness alone. Connectivity analyses further find that activity in the mPFC and left middle temporal gyrus co-vary, suggestive of gist-based monitoring within the context of false memories. Interestingly, neither the MTL nor the fusiform face area exhibited modulation as a function of target-lure relatedness. Overall, these results provide insight into the processes underlying false memories and further enhance our understanding of the role perceptual similarity plays in supporting false memories. Copyright © 2016 Elsevier Inc. All rights reserved.

  9. Repetition-related reductions in neural activity reveal component processes of mental simulation.

    Science.gov (United States)

    Szpunar, Karl K; St Jacques, Peggy L; Robbins, Clifford A; Wig, Gagan S; Schacter, Daniel L

    2014-05-01

    In everyday life, people adaptively prepare for the future by simulating dynamic events about impending interactions with people, objects and locations. Previous research has consistently demonstrated that a distributed network of frontal-parietal-temporal brain regions supports this ubiquitous mental activity. Nonetheless, little is known about the manner in which specific regions of this network contribute to component features of future simulation. In two experiments, we used a functional magnetic resonance (fMR)-repetition suppression paradigm to demonstrate that distinct frontal-parietal-temporal regions are sensitive to processing the scenarios or what participants imagined was happening in an event (e.g., medial prefrontal, posterior cingulate, temporal-parietal and middle temporal cortices are sensitive to the scenarios associated with future social events), people (medial prefrontal cortex), objects (inferior frontal and premotor cortices) and locations (posterior cingulate/retrosplenial, parahippocampal and posterior parietal cortices) that typically constitute simulations of personal future events. This pattern of results demonstrates that the neural substrates of these component features of event simulations can be reliably identified in the context of a task that requires participants to simulate complex, everyday future experiences.

  10. The relation of ongoing brain activity, evoked neural responses, and cognition

    Directory of Open Access Journals (Sweden)

    Sepideh Sadaghiani

    2010-06-01

    Full Text Available Ongoing brain activity has been observed since the earliest neurophysiological recordings and is found over a wide range of temporal and spatial scales. It is characterized by remarkably large spontaneous modulations. Here, we review evidence for the functional role of these ongoing activity fluctuations and argue that they constitute an essential property of the neural architecture underlying cognition. The role of spontaneous activity fluctuations is probably best understood when considering both their spatiotemporal structure and their functional impact on cognition. We first briefly argue against a ‘segregationist’ view on ongoing activity, both in time and space, countering this view with an emphasis on integration within a hierarchical spatiotemporal organization of intrinsic activity. We then highlight the flexibility and context-sensitivity of intrinsic functional connectivity that suggest its involvement in functionally relevant information processing. This role in information processing is pursued by reviewing how ongoing brain activity interacts with afferent and efferent information exchange of the brain with its environment. We focus on the relationship between the variability of ongoing and evoked brain activity, and review recent reports that tie ongoing brain activity fluctuations to variability in human perception and behavior. Finally, these observations are discussed within the framework of the free-energy principle which – applied to human brain function - provides a theoretical account for a non-random, coordinated interaction of ongoing and evoked activity in perception and behaviour.

  11. Neural noise and movement-related codes in the macaque supplementary motor area.

    Science.gov (United States)

    Averbeck, Bruno B; Lee, Daeyeol

    2003-08-20

    We analyzed the variability of spike counts and the coding capacity of simultaneously recorded pairs of neurons in the macaque supplementary motor area (SMA). We analyzed the mean-variance functions for single neurons, as well as signal and noise correlations between pairs of neurons. All three statistics showed a strong dependence on the bin width chosen for analysis. Changes in the correlation structure of single neuron spike trains over different bin sizes affected the mean-variance function, and signal and noise correlations between pairs of neurons were much smaller at small bin widths, increasing monotonically with the width of the bin. Analyses in the frequency domain showed that the noise between pairs of neurons, on average, was most strongly correlated at low frequencies, which explained the increase in noise correlation with increasing bin width. The coding performance was analyzed to determine whether the temporal precision of spike arrival times and the interactions within and between neurons could improve the prediction of the upcoming movement. We found that in approximately 62% of neuron pairs, the arrival times of spikes at a resolution between 66 and 40 msec carried more information than spike counts in a 200 msec bin. In addition, in 19% of neuron pairs, inclusion of within (11%)- or between-neuron (8%) correlations in spike trains improved decoding accuracy. These results suggest that in some SMA neurons elements of the spatiotemporal pattern of activity may be relevant for neural coding.

  12. Let7a involves in neural stem cell differentiation relating with TLX level

    International Nuclear Information System (INIS)

    Song, Juhyun; Cho, Kyoung Joo; Oh, Yumi; Lee, Jong Eun

    2015-01-01

    Neural stem cells (NSCs) have the potential for differentiation into neurons known as a groundbreaking therapeutic solution for central nervous system (CNS) diseases. To resolve the therapeutic efficiency of NSCs, recent researchers have focused on the study on microRNA's role in CNS. Some micro RNAs have been reported significant functions in NSC self-renewal and differentiation through the post-transcriptional regulation of neurogenesis genes. MicroRNA-Let7a (Let7a) has known as the regulator of diverse cellular mechanisms including cell differentiation and proliferation. In present study, we investigated whether Let7a regulates NSC differentiation by targeting the nuclear receptor TLX, which is an essential regulator of NSC self-renewal, proliferation and differentiation. We performed the following experiments: western blot analysis, TaqMan assay, RT-PCR, and immunocytochemistry to confirm the alteration of NSCs. Our data showed that let7a play important roles in controlling NSC fate determination. Thus, manipulating Let-7A and TLX could be a novel strategy to enhance the efficiency of NSC's neuronal differentiation for CNS disorders. - Highlights: • Let7a influences on NSC differentiation and proliferation. • Let7a involves in mainly NSC differentiation rather than proliferation. • Let7a positively regulates the TLX expression

  13. Neural network based tomographic approach to detect earthquake-related ionospheric anomalies

    Directory of Open Access Journals (Sweden)

    S. Hirooka

    2011-08-01

    Full Text Available A tomographic approach is used to investigate the fine structure of electron density in the ionosphere. In the present paper, the Residual Minimization Training Neural Network (RMTNN method is selected as the ionospheric tomography with which to investigate the detailed structure that may be associated with earthquakes. The 2007 Southern Sumatra earthquake (M = 8.5 was selected because significant decreases in the Total Electron Content (TEC have been confirmed by GPS and global ionosphere map (GIM analyses. The results of the RMTNN approach are consistent with those of TEC approaches. With respect to the analyzed earthquake, we observed significant decreases at heights of 250–400 km, especially at 330 km. However, the height that yields the maximum electron density does not change. In the obtained structures, the regions of decrease are located on the southwest and southeast sides of the Integrated Electron Content (IEC (altitudes in the range of 400–550 km and on the southern side of the IEC (altitudes in the range of 250–400 km. The global tendency is that the decreased region expands to the east with increasing altitude and concentrates in the Southern hemisphere over the epicenter. These results indicate that the RMTNN method is applicable to the estimation of ionospheric electron density.

  14. Disrupting neural activity related to awake-state sharp wave-ripple complexes prevents hippocampal learning.

    Science.gov (United States)

    Nokia, Miriam S; Mikkonen, Jarno E; Penttonen, Markku; Wikgren, Jan

    2012-01-01

    Oscillations in hippocampal local-field potentials (LFPs) reflect the crucial involvement of the hippocampus in memory trace formation: theta (4-8 Hz) oscillations and ripples (~200 Hz) occurring during sharp waves are thought to mediate encoding and consolidation, respectively. During sharp wave-ripple complexes (SPW-Rs), hippocampal cell firing closely follows the pattern that took place during the initial experience, most likely reflecting replay of that event. Disrupting hippocampal ripples using electrical stimulation either during training in awake animals or during sleep after training retards spatial learning. Here, adult rabbits were trained in trace eyeblink conditioning, a hippocampus-dependent associative learning task. A bright light was presented to the animals during the inter-trial interval (ITI), when awake, either during SPW-Rs or irrespective of their neural state. Learning was particularly poor when the light was presented following SPW-Rs. While the light did not disrupt the ripple itself, it elicited a theta-band oscillation, a state that does not usually coincide with SPW-Rs. Thus, it seems that consolidation depends on neuronal activity within and beyond the hippocampus taking place immediately after, but by no means limited to, hippocampal SPW-Rs.

  15. Non-Relative Value Unit-Generating Activities Represent One-Fifth of Academic Neuroradiologist Productivity.

    Science.gov (United States)

    Wintermark, M; Zeineh, M; Zaharchuk, G; Srivastava, A; Fischbein, N

    2016-07-01

    A neuroradiologist's activity includes many tasks beyond interpreting relative value unit-generating imaging studies. Our aim was to test a simple method to record and quantify the non-relative value unit-generating clinical activity represented by consults and clinical conferences, including tumor boards. Four full-time neuroradiologists, working an average of 50% clinical and 50% academic activity, systematically recorded all the non-relative value unit-generating consults and conferences in which they were involved during 3 months by using a simple, Web-based, computer-based application accessible from smartphones, tablets, or computers. The number and type of imaging studies they interpreted during the same period and the associated relative value units were extracted from our billing system. During 3 months, the 4 neuroradiologists working an average of 50% clinical activity interpreted 4241 relative value unit-generating imaging studies, representing 8152 work relative value units. During the same period, they recorded 792 non-relative value unit-generating study reviews as part of consults and conferences (not including reading room consults), representing 19% of the interpreted relative value unit-generating imaging studies. We propose a simple Web-based smartphone app to record and quantify non-relative value unit-generating activities including consults, clinical conferences, and tumor boards. The quantification of non-relative value unit-generating activities is paramount in this time of a paradigm shift from volume to value. It also represents an important tool for determining staffing levels, which cannot be performed on the basis of relative value unit only, considering the importance of time spent by radiologists on non-relative value unit-generating activities. It may also influence payment models from medical centers to radiology departments or practices. © 2016 by American Journal of Neuroradiology.

  16. Are Student Evaluations of Teaching Effectiveness Valid for Measuring Student Learning Outcomes in Business Related Classes? A Neural Network and Bayesian Analyses

    Science.gov (United States)

    Galbraith, Craig S.; Merrill, Gregory B.; Kline, Doug M.

    2012-01-01

    In this study we investigate the underlying relational structure between student evaluations of teaching effectiveness (SETEs) and achievement of student learning outcomes in 116 business related courses. Utilizing traditional statistical techniques, a neural network analysis and a Bayesian data reduction and classification algorithm, we find…

  17. Age-related changes in neural oscillations supporting context memory retrieval.

    Science.gov (United States)

    Strunk, Jonathan; James, Taylor; Arndt, Jason; Duarte, Audrey

    2017-06-01

    Recent evidence suggests that directing attention toward single item-context associations during encoding improves young and older adults' context memory performance and reduces demands on executive functions during retrieval. In everyday situations, there are many event features competing for our attention, and our ability to successfully recover those details may depend on our ability to ignore others. Failures of selective attention may contribute to older adults' context memory impairments. In the current electroencephalogram (EEG) study, we assessed the effects of age on processes supporting successful context memory retrieval of selectively attended features as indexed by neural oscillations. During encoding, young and older adults were directed to attend to a picture of an object and its relationship to one of two concurrently presented contextual details: a color or scene. At retrieval, we tested their memory for the object, its attended and unattended context features, and their confidence for both the attended and unattended features. Both groups showed greater memory for attended than unattended contextual features. However, older adults showed evidence of hyper-binding between attended and unattended context features while the young adults did not. EEG results in the theta band suggest that young and older adults recollect similar amounts of information but brain-behavior correlations suggest that this information was supportive of contextual memory performance, particularly for young adults. By contrast, sustained beta desynchronization, indicative of sensory reactivation and episodic reconstruction, was correlated with contextual memory performance for older adults only. We conclude that older adults' inhibition deficits during encoding reduced the selectivity of their contextual memories, which led to reliance on executive functions like episodic reconstruction to support successful memory retrieval. Copyright © 2017 Elsevier Ltd. All rights

  18. Effects of selective serotonin reuptake inhibition on neural activity related to risky decisions and monetary rewards in healthy males

    DEFF Research Database (Denmark)

    Macoveanu, Julian; Fisher, Patrick M; Haahr, Mette E

    2014-01-01

    the involvement of the normally functioning 5HT-system in decision-making under risk and processing of monetary rewards. The data suggest that prolonged SSRI treatment might reduce emotional engagement by reducing the impact of risk during decision-making or the impact of reward during outcome evaluation.......Selective serotonin reuptake inhibitors (SSRIs) such as fluoxetine are commonly prescribed antidepressant drugs targeting the dysfunctional serotonin (5-HT) system, yet little is known about the functional effects of prolonged serotonin reuptake inhibition in healthy individuals. Here we used...... functional MRI (fMRI) to investigate how a three-week fluoxetine intervention influences neural activity related to risk taking and reward processing. Employing a double-blinded parallel-group design, 29 healthy young males were randomly assigned to receive 3 weeks of a daily dose of 40 mg fluoxetine...

  19. Neural activity in relation to clinically derived personality syndromes in depression using a psychodynamic fMRI paradigm

    Directory of Open Access Journals (Sweden)

    Svenja eTaubner

    2013-12-01

    Full Text Available Objective: The heterogeneity between patients with depression cannot be captured adequately with existing descriptive systems of diagnosis and neurobiological models of depression. Furthermore, considering the highly individual nature of depression, the application of general stimuli in past research efforts may not capture the essence of the disorder. This study aims to identify subtypes of depression by using empirically-derived personality-syndromes, and to explore neural correlates of the derived personality syndromes.Method: In the present exploratory study an individually tailored and psychodynamically based fMRI paradigm using dysfunctional relationship patterns was presented to 20 chronically depressed patients. Results from the Shedler-Westen-Assessment-Procedure (SWAP-200 were analyzed by Q-factor analysis to identify clinically relevant subgroups of depression and related brain activation.Results: The principle component analysis of SWAP-200 items from all 20 patients lead to a 2-factor solution: Depressive Personality and Emotional-Hostile-Externalizing Personality. Both factors were used in a whole-brain correlational analysis but only the second factor yielded significant positive correlations in four regions: A large cluster in the right orbitofrontal cortex (OFC, the left ventral striatum, a small cluster in the left temporal pole and another small cluster in the right middle frontal gyrus. Discussion: The degree to which patients with depression score high on the factor Emotional-Hostile-Externalizing Personality correlated with relatively higher activity in three key areas involved in emotion processing, evaluation of reward/punishment, negative cognitions, depressive pathology and social knowledge (OFC, ventral striatum, temporal pole. Results may contribute to an alternative description of neural correlates of depression showing differential brain activation dependent on the extent of specific personality syndromes in

  20. Organization of the sleep-related neural systems in the brain of the harbour porpoise (Phocoena phocoena).

    Science.gov (United States)

    Dell, Leigh-Anne; Patzke, Nina; Spocter, Muhammad A; Siegel, Jerome M; Manger, Paul R

    2016-07-01

    The present study provides the first systematic immunohistochemical neuroanatomical investigation of the systems involved in the control and regulation of sleep in an odontocete cetacean, the harbor porpoise (Phocoena phocoena). The odontocete cetaceans show an unusual form of mammalian sleep, with unihemispheric slow waves, suppressed REM sleep, and continuous bodily movement. All the neural elements involved in sleep regulation and control found in bihemispheric sleeping mammals were present in the harbor porpoise, with no specific nuclei being absent, and no novel nuclei being present. This qualitative similarity of nuclear organization relates to the cholinergic, noradrenergic, serotonergic, and orexinergic systems and is extended to the γ-aminobutyric acid (GABA)ergic elements involved with these nuclei. Quantitative analysis of the cholinergic and noradrenergic nuclei of the pontine region revealed that in comparison with other mammals, the numbers of pontine cholinergic (126,776) and noradrenergic (122,878) neurons are markedly higher than in other large-brained bihemispheric sleeping mammals. The diminutive telencephalic commissures (anterior commissure, corpus callosum, and hippocampal commissure) along with an enlarged posterior commissure and supernumerary pontine cholinergic and noradrenergic neurons indicate that the control of unihemispheric slow-wave sleep is likely to be a function of interpontine competition, facilitated through the posterior commissure, in response to unilateral telencephalic input related to the drive for sleep. In addition, an expanded peripheral division of the dorsal raphe nuclear complex appears likely to play a role in the suppression of REM sleep in odontocete cetaceans. Thus, the current study provides several clues to the understanding of the neural control of the unusual sleep phenomenology present in odontocete cetaceans. J. Comp. Neurol. 524:1999-2017, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals

  1. A simple, xeno-free method for oligodendrocyte generation from human neural stem cells derived from umbilical cord: engagement of gelatinases in cell commitment and differentiation.

    Science.gov (United States)

    Sypecka, Joanna; Ziemka-Nalecz, Małgorzata; Dragun-Szymczak, Patrycja; Zalewska, Teresa

    2017-05-01

    Oligodendrocyte progenitors (OPCs) are ranked among the most likely candidates for cell-based strategies aimed at treating neurodegenerative diseases accompanied by dys/demyelination of the central nervous system (CNS). In this regard, different sources of stem cells are being tested to elaborate xeno-free protocols for efficient generation of OPCs for clinical applications. In the present study, neural stem cells of human umbilical cord blood (HUCB-NSCs) have been used to derive OPCs and subsequently to differentiate them into mature, GalC-expressing oligodendrocytes. Applied components of the extracellular matrix (ECM) and the analogues of physiological substances known to increase glial commitment of neural stem cells have been shown to significantly increase the yield of the resulting OPC fraction. The efficiency of ECM components in promoting oligodendrocyte commitment and differentiation prompted us to investigate the potential role of gelatinases in those processes. Subsequently, endogenous and ECM metalloproteinases (MMPs) activity has been compared with that detected in primary cultures of rat oligodendrocytes in vitro, as well as in rat brains in vivo. The data indicate that gelatinases are engaged in gliogenesis both in vitro and in vivo, although differently, which presumably results from distinct extracellular conditions. In conclusion, the study presents an efficient xeno-free method of deriving oligodendrocyte from HUCB-NSCs and analyses the engagement of MMP-2/MMP-9 in the processes of cell commitment and maturation. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

  2. Interpretations of Frequency Domain Analyses of Neural Entrainment: Periodicity, Fundamental Frequency, and Harmonics.

    Science.gov (United States)

    Zhou, Hong; Melloni, Lucia; Poeppel, David; Ding, Nai

    2016-01-01

    Brain activity can follow the rhythms of dynamic sensory stimuli, such as speech and music, a phenomenon called neural entrainment. It has been hypothesized that low-frequency neural entrainment in the neural delta and theta bands provides a potential mechanism to represent and integrate temporal information. Low-frequency neural entrainment is often studied using periodically changing stimuli and is analyzed in the frequency domain using the Fourier analysis. The Fourier analysis decomposes a periodic signal into harmonically related sinusoids. However, it is not intuitive how these harmonically related components are related to the response waveform. Here, we explain the interpretation of response harmonics, with a special focus on very low-frequency neural entrainment near 1 Hz. It is illustrated why neural responses repeating at f Hz do not necessarily generate any neural response at f Hz in the Fourier spectrum. A strong neural response at f Hz indicates that the time scales of the neural response waveform within each cycle match the time scales of the stimulus rhythm. Therefore, neural entrainment at very low frequency implies not only that the neural response repeats at f Hz but also that each period of the neural response is a slow wave matching the time scale of a f Hz sinusoid.

  3. Neural correlates of relational memory: successful encoding and retrieval of semantic and perceptual associations

    NARCIS (Netherlands)

    Prince, S.E.; Daselaar, S.M.; Cabeza, R.

    2005-01-01

    Using event-related functional magnetic resonance imaging, we identified brain regions involved in successful relational memory (RM) during encoding and retrieval for semantic and perceptual associations or in general, independent of phase and content. Participants were scanned while encoding and

  4. Neural correlates of derived relational responding on tests of stimulus equivalence

    Directory of Open Access Journals (Sweden)

    Cataldo Michael F

    2008-02-01

    Full Text Available Abstract Background An essential component of cognition and language involves the formation of new conditional relations between stimuli based upon prior experiences. Results of investigations on transitive inference (TI highlight a prominent role for the medial temporal lobe in maintaining associative relations among sequentially arranged stimuli (A > B > C > D > E. In this investigation, medial temporal lobe activity was assessed while subjects completed "Stimulus Equivalence" (SE tests that required deriving conditional relations among stimuli within a class (A ≡ B ≡ C. Methods Stimuli consisted of six consonant-vowel-consonant triads divided into two classes (A1, B1, C1; A2, B2, C2. A simultaneous matching-to-sample task and differential reinforcement were employed during pretraining to establish the conditional relations A1:B1 and B1:C1 in class 1 and A2:B2 and B2:C2 in class 2. During functional neuroimaging, recombined stimulus pairs were presented and subjects judged (yes/no whether stimuli were related. SE tests involved presenting three different types of within-class pairs: Symmetrical (B1 A1; C1 B1; B2 A2; C2 B2, and Transitive (A1 C1; A2 C2 and Equivalence (C1 A1; C2 A2 relations separated by a nodal stimulus. Cross-class 'Foils' consisting of unrelated stimuli (e.g., A1 C2 were also presented. Results Relative to cross-class Foils, Transitive and Equivalence relations requiring inferential judgments elicited bilateral activation in the anterior hippocampus while Symmetrical relations elicited activation in the parahippocampus. Relative to each derived relation, Foils generally elicited bilateral activation in the parahippocampus, as well as in frontal and parietal lobe regions. Conclusion Activation observed in the hippocampus to nodal-dependent derived conditional relations (Transitive and Equivalence relations highlights its involvement in maintaining relational structure and flexible memory expression among stimuli within a

  5. Disruption in neural phase synchrony is related to identification of inattentional deafness in real-world setting.

    Science.gov (United States)

    Callan, Daniel E; Gateau, Thibault; Durantin, Gautier; Gonthier, Nicolas; Dehais, Frédéric

    2018-06-01

    Individuals often have reduced ability to hear alarms in real world situations (e.g., anesthesia monitoring, flying airplanes) when attention is focused on another task, sometimes with devastating consequences. This phenomenon is called inattentional deafness and usually occurs under critical high workload conditions. It is difficult to simulate the critical nature of these tasks in the laboratory. In this study, dry electroencephalography is used to investigate inattentional deafness in real flight while piloting an airplane. The pilots participating in the experiment responded to audio alarms while experiencing critical high workload situations. It was found that missed relative to detected alarms were marked by reduced stimulus evoked phase synchrony in theta and alpha frequencies (6-14 Hz) from 120 to 230 ms poststimulus onset. Correlation of alarm detection performance with intertrial coherence measures of neural phase synchrony showed different frequency and time ranges for detected and missed alarms. These results are consistent with selective attentional processes actively disrupting oscillatory coherence in sensory networks not involved with the primary task (piloting in this case) under critical high load conditions. This hypothesis is corroborated by analyses of flight parameters showing greater maneuvering associated with difficult phases of flight occurring during missed alarms. Our results suggest modulation of neural oscillation is a general mechanism of attention utilizing enhancement of phase synchrony to sharpen alarm perception during successful divided attention, and disruption of phase synchrony in brain networks when attentional demands of the primary task are great, such as in the case of inattentional deafness. © 2018 Wiley Periodicals, Inc.

  6. Commercial grade item (CGI) dedication of generators for nuclear safety related applications

    International Nuclear Information System (INIS)

    Das, R.K.; Hajos, L.G.

    1993-01-01

    The number of nuclear safety related equipment suppliers and the availability of spare and replacement parts designed specifically for nuclear safety related application are shrinking rapidly. These have made it necessary for utilities to apply commercial grade spare and replacement parts in nuclear safety related applications after implementing proper acceptance and dedication process to verify that such items conform with the requirements of their use in nuclear safety related application. The general guidelines for the commercial grade item (CGI) acceptance and dedication are provided in US Nuclear Regulatory Commission (NRC) Generic Letters and Electric Power Research Institute (EPRI) Report NP-5652, Guideline for the Utilization of Commercial Grade Items in Nuclear Safety Related Applications. This paper presents an application of these generic guidelines for procurement, acceptance, and dedication of a commercial grade generator for use as a standby generator at Salem Generating Station Units 1 and 2. The paper identifies the critical characteristics of the generator which once verified, will provide reasonable assurance that the generator will perform its intended safety function. The paper also delineates the method of verification of the critical characteristics through tests and provide acceptance criteria for the test results. The methodology presented in this paper may be used as specific guidelines for reliable and cost effective procurement and dedication of commercial grade generators for use as standby generators at nuclear power plants

  7. Cultural shaping of neural responses: Feedback-related potentials vary with self-construal and face priming.

    Science.gov (United States)

    Hitokoto, Hidefumi; Glazer, James; Kitayama, Shinobu

    2016-01-01

    Previous work shows that when an image of a face is presented immediately prior to each trial of a speeded cognitive task (face-priming), the error-related negativity (ERN) is upregulated for Asians, but it is downregulated for Caucasians. These findings are consistent with the hypothesis that images of "generalized other" vary cross-culturally such that they evoke anxiety for Asians, whereas they serve as safety cues for Caucasians. Here, we tested whether the cross-cultural variation in the face-priming effect would be observed in a gambling paradigm. Caucasian Americans, Asian Americans, and Asian sojourners were exposed to a brief flash of a schematic face during a gamble. For Asian Americans, face-priming resulted in significant increases of both negative-going deflection of ERP upon negative feedback (feedback-related negativity [FRN]) and positive-going deflection of ERP upon positive feedback (feedback-related positivity [FRP]). For Caucasian Americans, face-priming showed a significant reversal, decreasing both FRN and FRP. The cultural difference in the face-priming effect in FRN and FRP was partially mediated by interdependent self-construal. Curiously, Asian sojourners showed a pattern similar to the one for Caucasian Americans. Our findings suggest that culture shapes neural pathways in both systematic and highly dynamic fashion. © 2015 Society for Psychophysiological Research.

  8. Losing Control in Social Situations: How the Presence of Others Affects Neural Processes Related to Sense of Agency.

    Science.gov (United States)

    Beyer, Frederike; Sidarus, Nura; Fleming, Stephen; Haggard, Patrick

    2018-01-01

    Social contexts substantially influence individual behavior, but little is known about how they affect cognitive processes related to voluntary action. Previously, it has been shown that social context reduces participants' sense of agency over the outcomes of their actions and outcome monitoring. In this fMRI study on human volunteers, we investigated the neural mechanisms by which social context alters sense of agency. Participants made costly actions to stop inflating a balloon before it burst. On "social" trials, another player could act in their stead, but we analyzed only trials in which the other player remained passive. We hypothesized that mentalizing processes during social trials would affect decision-making fluency and lead to a decreased sense of agency. In line with this hypothesis, we found increased activity in the bilateral temporo-parietal junction (TPJ), precuneus, and middle frontal gyrus during social trials compared with nonsocial trials. Activity in the precuneus was, in turn, negatively related to sense of agency at a single-trial level. We further found a double dissociation between TPJ and angular gyrus (AG): activity in the left AG was not sensitive to social context but was negatively related to sense of agency. In contrast, activity in the TPJ was modulated by social context but was not sensitive to sense of agency.

  9. Losing Control in Social Situations: How the Presence of Others Affects Neural Processes Related to Sense of Agency

    Science.gov (United States)

    Fleming, Stephen

    2018-01-01

    Social contexts substantially influence individual behavior, but little is known about how they affect cognitive processes related to voluntary action. Previously, it has been shown that social context reduces participants’ sense of agency over the outcomes of their actions and outcome monitoring. In this fMRI study on human volunteers, we investigated the neural mechanisms by which social context alters sense of agency. Participants made costly actions to stop inflating a balloon before it burst. On “social” trials, another player could act in their stead, but we analyzed only trials in which the other player remained passive. We hypothesized that mentalizing processes during social trials would affect decision-making fluency and lead to a decreased sense of agency. In line with this hypothesis, we found increased activity in the bilateral temporo-parietal junction (TPJ), precuneus, and middle frontal gyrus during social trials compared with nonsocial trials. Activity in the precuneus was, in turn, negatively related to sense of agency at a single-trial level. We further found a double dissociation between TPJ and angular gyrus (AG): activity in the left AG was not sensitive to social context but was negatively related to sense of agency. In contrast, activity in the TPJ was modulated by social context but was not sensitive to sense of agency. PMID:29527568

  10. Programming of stress-related behavior and epigenetic neural gene regulation in mice offspring through maternal exposure to predator odor

    Science.gov (United States)

    St-Cyr, Sophie; McGowan, Patrick O.

    2015-01-01

    Perinatal stress mediated through the mother can lead to long-term alterations in stress-related phenotypes in offspring. The capacity for adaptation to adversity in early life depends in part on the life history of the animal. This study was designed to examine the behavioral and neural response in adult offspring to prenatal exposure to predator odor: an ethologically-relevant psychological stressor. Pregnant mice were exposed daily to predator odors or distilled water control over the second half of the pregnancy. Predator odor exposure lead to a transient decrease in maternal care in the mothers. As adults, the offspring of predator odor-exposed mothers showed increased anti-predator behavior, a predator-odor induced decrease in activity and, in female offspring, an increased corticosterone (CORT) response to predator odor exposure. We found a highly specific response among stress-related genes within limbic brain regions. Transcript abundance of Corticotropin-releasing hormone receptor 1 (CRHR1) was elevated in the amygdala in adult female offspring of predator odor-exposed mothers. In the hippocampus of adult female offspring, decreased Brain-derived neurotrophic factor (BDNF) transcript abundance was correlated with a site-specific decrease in DNA methylation in Bdnf exon IV, indicating the potential contribution of this epigenetic mechanism to maternal programming by maternal predator odor exposure. These data indicate that maternal predator odor exposure alone is sufficient to induce an altered stress-related phenotype in adulthood, with implications for anti-predator behavior in offspring. PMID:26082698

  11. Gender and neural substrates subserving implicit processing of death-related linguistic cues.

    Science.gov (United States)

    Qin, Jungang; Shi, Zhenhao; Ma, Yina; Han, Shihui

    2018-02-01

    Our recent functional magnetic resonance imaging study revealed decreased activities in the anterior cingulate cortex (ACC) and bilateral insula for women during the implicit processing of death-related linguistic cues. Current work tested whether aforementioned activities are common for women and men and explored potential gender differences. We scanned twenty males while they performed a color-naming task on death-related, negative-valence, and neutral-valence words. Whole-brain analysis showed increased left frontal activity and decreased activities in the ACC and bilateral insula to death-related versus negative-valence words for both men and women. However, relative to women, men showed greater increased activity in the left middle frontal cortex and decreased activity in the right cerebellum to death-related versus negative-valence words. The results suggest, while implicit processing of death-related words is characterized with weakened sense of oneself for both women and men, men may recruit stronger cognitive regulation of emotion than women.

  12. Age-Related Cognitive Impairments in Mice with a Conditional Ablation of the Neural Cell Adhesion Molecule

    Science.gov (United States)

    Bisaz, Reto; Boadas-Vaello, Pere; Genoux, David; Sandi, Carmen

    2013-01-01

    Most of the mechanisms involved in neural plasticity support cognition, and aging has a considerable effect on some of these processes. The neural cell adhesion molecule (NCAM) of the immunoglobulin superfamily plays a pivotal role in structural and functional plasticity and is required to modulate cognitive and emotional behaviors. However,…

  13. International retrospective cohort study of neural tube defects in relation to folic acid recommendations : are the recommendations working?

    NARCIS (Netherlands)

    Botto, LD; Lisi, A; Robert-Gnansia, E; Erickson, JD; Vollset, SE; Mastroiacovo, P; Botting, B; Cocchi, G; de Vigan, C; de Walle, H; Feijoo, M; Irgens, LM; McDonnell, B; Merlob, P; Ritvanen, A; Scarano, G; Siffel, C; Metneki, J; Stoll, C; Smithells, R; Goujard, J

    2005-01-01

    Objective To evaluate the effectiveness of policies and recommendations on folic acid aimed at reducing the occurrence of neural tube defects. Design Retrospective cohort study of births monitored by birth defect registries. Setting 13 birth defects registries monitoring rates of neural tube defects

  14. able utilizando redes neuronales artificiales; UTILIZATION OF ARTIFICIAL NEURAL NETWORK IN THE SIMULATION AND CONTROL OF WIND TURBINE GENERATORS WITH VARIABLE SPEED AND VARIABLE PITCH.

    Directory of Open Access Journals (Sweden)

    Osley López González

    2011-02-01

    , considered as a whole, must be able of respond with anadequate precision and speed in response to the randomness and variability of the wind.The relationship between the wind speed, the blade pitch and the generator speed in order to produce themaximum power and also be able to limit the output power for large wind speeds is a very complicated oneand it is very difficult to find its mathematical function.In this paper, the authors, utilizing the MATLABSIMULINK toolboxes, propose representing this functional relation by means of an Artificial Neural Network(ANN. The parameters and characteristics of an existing wind turbine generator are utilized and it isdemonstrated that it is possible to use an ANN in the simulation and control of a variable speed, variablepitch wind turbine that capture the maximum power from the wind.

  15. Recurrence Relations and Generating Functions of the Sequence of Sums of Corresponding Factorials and Triangular Numbers

    Directory of Open Access Journals (Sweden)

    Romer C. Castillo

    2015-11-01

    Full Text Available This study established some recurrence relations and exponential generating functions of the sequence of factoriangular numbers. A factoriangular number is defined as a sum of corresponding factorial and triangular number. The proofs utilize algebraic manipulations with some known results from calculus, particularly on power series and Maclaurin’s series. The recurrence relations were found by manipulating the formula defining a factoringular number while the ascertained exponential generating functions were in the closed form.

  16. Generating relations of multi-variable Tricomi functions of two indices using Lie algebra representation

    Directory of Open Access Journals (Sweden)

    Nader Ali Makboul Hassan

    2014-01-01

    Full Text Available This paper is an attempt to stress the usefulness of the multi-variable special functions. In this paper, we derive certain generating relations involving 2-indices 5-variables 5-parameters Tricomi functions (2I5V5PTF by using a Lie-algebraic method. Further, we derive certain new and known generating relations involving other forms of Tricomi and Bessel functions as applications.

  17. Human Prolactin Point Mutations and Their Projected Effect on Vasoinhibin Generation and Vasoinhibin-Related Diseases

    Directory of Open Access Journals (Sweden)

    Jakob Triebel

    2017-11-01

    Full Text Available BackgroundA dysregulation of the generation of vasoinhibin hormones by proteolytic cleavage of prolactin (PRL has been brought into context with diabetic retinopathy, retinopathy of prematurity, preeclampsia, pregnancy-induced hypertension, and peripartum cardiomyopathy. Factors governing vasoinhibin generation are incompletely characterized, and the composition of vasoinhibin isoforms in human tissues or compartments, such as the circulation, is unknown. The aim of this study was to determine the possible contribution of PRL point mutations to the generation of vasoinhibins as well as to project their role in vasoinhibin-related diseases.MethodsProlactin sequences, point mutations, and substrate specificity information about the PRL cleaving enzymes cathepsin D, matrix metalloproteinases 8 and 13, and bone-morphogenetic protein 1 were retrieved from public databases. The consequences of point mutations in regard to their possible effect on vasoinhibin levels were projected on the basis of a score indicating the suitability of a particular sequence for enzymatic cleavage that result in vasoinhibin generation. The relative abundance and type of vasoinhibin isoforms were estimated by comparing the relative cleavage efficiency of vasoinhibin-generating enzymes.ResultsSix point mutations leading to amino acid substitutions in vasoinhibin-generating cleavage sites were found and projected to either facilitate or inhibit vasoinhibin generation. Four mutations affecting vasoinhibin generation in cancer tissues were found. The most likely composition of the relative abundance of vasoinhibin isoforms is projected to be 15 > 17.2 > 16.8 > 17.7 > 18 kDa vasoinhibin.ConclusionProlactin point mutations are likely to influence vasoinhibin levels by affecting the proteolysis efficiency of vasoinhibin-generating enzymes and should be monitored in patients with vasoinhibin-related diseases. Attempts to characterize vasoinhibin-related diseases

  18. A Neural Mechanism for Surprise-related Interruptions of Visuospatial Working Memory.

    Science.gov (United States)

    Wessel, Jan R

    2018-01-01

    Surprising perceptual events recruit a fronto-basal ganglia mechanism for inhibition, which suppresses motor activity following surprise. A recent study found that this inhibitory mechanism also disrupts the maintenance of verbal working memory (WM) after surprising tones. However, it is unclear whether this same mechanism also relates to surprise-related interruptions of non-verbal WM. We tested this hypothesis using a change-detection task, in which surprising tones impaired visuospatial WM. Participants also performed a stop-signal task (SST). We used independent component analysis and single-trial scalp-electroencephalogram to test whether the same inhibitory mechanism that reflects motor inhibition in the SST relates to surprise-related visuospatial WM decrements, as was the case for verbal WM. As expected, surprising tones elicited activity of the inhibitory mechanism, and this activity correlated strongly with the trial-by-trial level of surprise. However, unlike for verbal WM, the activity of this mechanism was unrelated to visuospatial WM accuracy. Instead, inhibition-independent activity that immediately succeeded the inhibitory mechanism was increased when visuospatial WM was disrupted. This shows that surprise-related interruptions of visuospatial WM are not effected by the same inhibitory mechanism that interrupts verbal WM, and instead provides evidence for a 2-stage model of distraction. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  19. The neural cell adhesion molecule L1 is distinct from the N-CAM related group of surface antigens BSP-2 and D2

    DEFF Research Database (Denmark)

    Faissner, A; Kruse, J; Goridis, C

    1984-01-01

    The neural cell adhesion molecule L1 and the group of N-CAM related molecules, BSP-2 and D2 antigen, are immunochemically distinct molecular species. The two groups of surface molecules are also functionally distinct entities, since inhibition of Ca2+-independent adhesion among early post-natal m...

  20. Individual Differences in Neural Regions Functionally Related to Real and Imagined Stuttering

    Science.gov (United States)

    Wymbs, Nicholas F.; Ingham, Roger J.; Ingham, Janis C.; Paolini, Katherine E.; Grafton, Scott T.

    2013-01-01

    Recent brain imaging investigations of developmental stuttering show considerable disagreement regarding which regions are related to stuttering. These divergent findings have been mainly derived from group studies. To investigate functional neurophysiology with improved precision, an individual-participant approach (N = 4) using event-related…

  1. Neural activation patterns during retrieval of schema-related memories: differences and commonalities between children and adults.

    Science.gov (United States)

    Brod, Garvin; Lindenberger, Ulman; Shing, Yee Lee

    2017-11-01

    Schemas represent stable properties of individuals' experiences, and allow them to classify new events as being congruent or incongruent with existing knowledge. Research with adults indicates that the prefrontal cortex (PFC) is involved in memory retrieval of schema-related information. However, developmental differences between children and adults in the neural correlates of schema-related memories are not well understood. One reason for this is the inherent confound between schema-relevant experience and maturation, as both are related to time. To overcome this limitation, we used a novel paradigm that experimentally induces, and then probes for, task-relevant knowledge during encoding of new information. Thirty-one children aged 8-12 years and 26 young adults participated in the experiment. While successfully retrieving schema-congruent events, children showed less medial PFC activity than adults. In addition, medial PFC activity during successful retrieval correlated positively with children's age. While successfully retrieving schema-incongruent events, children showed stronger hippocampus (HC) activation as well as weaker connectivity between the striatum and the dorsolateral PFC than adults. These findings were corroborated by an exploratory full-factorial analysis investigating age differences in the retrieval of schema-congruent versus schema-incongruent events, comparing the two conditions directly. Consistent with the findings of the separate analyses, two clusters, one in the medial PFC, one in the HC, were identified that exhibited a memory × congruency × age group interaction. In line with the two-component model of episodic memory development, the present findings point to an age-related shift from a more HC-bound processing to an increasing recruitment of prefrontal brain regions in the retrieval of schema-related events. © 2016 John Wiley & Sons Ltd.

  2. Differential alterations of phospholipid metabolism in cultured cells of neural origin by phorbol esters, fatty acids, diacylglycerols and related compounds

    International Nuclear Information System (INIS)

    Cook, H.W.; Spence, M.W.

    1986-01-01

    The uptake and metabolism of [ 3 H]methylcholine, [1,2- 14 C]-ethanolamine, [1- 14 C]fatty acids and [ 32 P] were studied in glioma (C6), neuroblastoma (N1E-115) and neuroblastoma-glioma hybrid (NG108-15) cells in culture in the presence of tetradecanoylphorbolacetate (TPA) and related analogues, fatty acids and diacylglycerol (DAG) to assess mechanisms of stimulation of phospholipid synthesis. Choline incorporation into phosphatidylcholine (PC) was stimulated 1.5-3 fold by phorbol esters and 3-10 fold by 18:1(n-9) in C6 cultures; these agents were without effect on N1E-115 and had intermediate effects on NG108-15 cells. Stimulation of [ 32 P] incorporation was predominantly into PC, ethanolamine incorporation into phosphatidylethanolamine (PE) was less stimulated ( 3 H]choline and its incorporation via intracellular phosphocholine into PC whereas exogenous 18:1(n-9) stimulated only utilization of intracellular P-choline in C6 cells. Choline incorporation into PC and relative stimulation by TPA or 18:1 was influenced by medium glucose and choline. Thus, metabolism of phospholipids and their precursors in neural cells can be markedly influenced by phorbol esters and fatty acids but this stimulation is dependent on cell type, growth medium, phospholipid class and nature of the stimulator

  3. Age-Related Differences in Neural Recruitment During the Use of Cognitive Reappraisal and Selective Attention as Emotion Regulation Strategies

    Directory of Open Access Journals (Sweden)

    Eric S Allard

    2014-04-01

    Full Text Available The present study examined age differences in the timing and neural recruitment within lateral and medial PFC while younger and older adults hedonically regulated their responses to unpleasant film clips. When analyses focused on activity during the emotional peak of the film clip (the most emotionally salient portion of the film, several age differences emerged. When comparing regulation to passive viewing (combined effects of selective attention and reappraisal younger adults showed greater regulation related activity in lateral PFC (DLPFC, VLPFC, OFC and medial PFC (ACC while older adults showed greater activation within a region DLPFC. When assessing distinct effects of the regulation conditions, an ANOVA revealed a significant Age X Regulation Condition interaction within bilateral DLPFC and ACC; older adults but not young adults showed greater recruitment within these regions for reappraisal than selective attention. When examining activity at the onset of the film clip and at its emotional peak, the timing of reappraisal-related activity within VLPFC differed between age groups: Younger adults showed greater activity at film onset while older adults showed heightened activity during the peak. Our results suggest that older adults rely more heavily on PFC recruitment when engaging cognitively demanding reappraisal strategies while PFC-mediated regulation might not be as task-specific for younger adults. Older adults’ greater reliance on cognitive control processing during emotion regulation may also be reflected in the time needed to implement these strategies.

  4. The neural architecture of age-related dual-task interferences

    Directory of Open Access Journals (Sweden)

    Witold Xaver Chmielewski

    2014-07-01

    Full Text Available In daily life elderly adults exhibit deficits when dual-tasking is involved. So far these deficits have been verified on a behavioral level in dual-tasking. Yet, the neuronal architecture of these deficits in aging still remains to be explored especially when late-middle aged individuals around 60 years of age are concerned. Neuroimaging studies in young participants concerning dual-tasking were, among others, related to activity in middle frontal (MFG and superior frontal gyrus (SFG and the anterior insula (AI. According to the frontal lobe hypothesis of aging, alterations in these frontal regions (i.e., SFG and MFG might be responsible for cognitive deficits. We measured brain activity using fMRI, while examining age-dependent variations in dual-tasking by utilizing the PRP (psychological refractory period test. Behavioral data showed an increasing PRP effect in late-middle aged adults. The results suggest the age-related deteriorated performance in dual-tasking, especially in conditions of risen complexity. These effects are related to changes in networks involving the anterior insula, the SFG and the MFG. The results suggest that different cognitive subprocesses are affected that mediate the observed dual-tasking problems in late-middle aged individuals.

  5. The neural architecture of age-related dual-task interferences.

    Science.gov (United States)

    Chmielewski, Witold X; Yildiz, Ali; Beste, Christian

    2014-01-01

    In daily life elderly adults exhibit deficits when dual-tasking is involved. So far these deficits have been verified on a behavioral level in dual-tasking. Yet, the neuronal architecture of these deficits in aging still remains to be explored especially when late-middle aged individuals around 60 years of age are concerned. Neuroimaging studies in young participants concerning dual-tasking were, among others, related to activity in middle frontal (MFG) and superior frontal gyrus (SFG) and the anterior insula (AI). According to the frontal lobe hypothesis of aging, alterations in these frontal regions (i.e., SFG and MFG) might be responsible for cognitive deficits. We measured brain activity using fMRI, while examining age-dependent variations in dual-tasking by utilizing the PRP (psychological refractory period) test. Behavioral data showed an increasing PRP effect in late-middle aged adults. The results suggest the age-related deteriorated performance in dual-tasking, especially in conditions of risen complexity. These effects are related to changes in networks involving the AI, the SFG and the MFG. The results suggest that different cognitive subprocesses are affected that mediate the observed dual-tasking problems in late-middle aged individuals.

  6. Effects of loss aversion on neural responses to loss outcomes: An event-related potential study.

    Science.gov (United States)

    Kokmotou, Katerina; Cook, Stephanie; Xie, Yuxin; Wright, Hazel; Soto, Vicente; Fallon, Nicholas; Giesbrecht, Timo; Pantelous, Athanasios; Stancak, Andrej

    2017-05-01

    Loss aversion is the tendency to prefer avoiding losses over acquiring gains of the same amount. To shed light on the spatio-temporal processes underlying loss aversion, we analysed the associations between individual loss aversion and electrophysiological responses to loss and gain outcomes in a monetary gamble task. Electroencephalographic feedback-related negativity (FRN) was computed in 29 healthy participants as the difference in electrical potentials between losses and gains. Loss aversion was evaluated using non-linear parametric fitting of choices in a separate gamble task. Loss aversion correlated positively with FRN amplitude (233-263ms) at electrodes covering the lower face. Feedback related potentials were modelled by five equivalent source dipoles. From these dipoles, stronger activity in a source located in the orbitofrontal cortex was associated with loss aversion. The results suggest that loss aversion implemented during risky decision making is related to a valuation process in the orbitofrontal cortex, which manifests during learning choice outcomes. Copyright © 2017. Published by Elsevier B.V.

  7. Motor-related brain activity during action observation: a neural substrate for electrocorticographic brain-computer interfaces after spinal cord injury

    Directory of Open Access Journals (Sweden)

    Jennifer L Collinger

    2014-02-01

    Full Text Available After spinal cord injury (SCI, motor commands from the brain are unable to reach peripheral nerves and muscles below the level of the lesion. Action observation, in which a person observes someone else performing an action, has been used to augment traditional rehabilitation paradigms. Similarly, action observation can be used to derive the relationship between brain activity and movement kinematics for a motor-based brain-computer interface (BCI even when the user cannot generate overt movements. BCIs use brain signals to control external devices to replace functions that have been lost due to SCI or other motor impairment. Previous studies have reported congruent motor cortical activity during observed and overt movements using magnetoencephalography (MEG and functional magnetic resonance imaging (fMRI. Recent single-unit studies using intracortical microelectrodes also demonstrated that a large number of motor cortical neurons had similar firing rate patterns between overt and observed movements. Given the increasing interest in electrocorticography (ECoG-based BCIs, our goal was to identify whether action observation-related cortical activity could be recorded using ECoG during grasping tasks. Specifically, we aimed to identify congruent neural activity during observed and executed movements in both the sensorimotor rhythm (10-40 Hz and the high-gamma band (65-115 Hz which contains significant movement-related information. We observed significant motor-related high-gamma band activity during action observation in both able-bodied individuals and one participant with a complete C4 SCI. Furthermore, in able-bodied participants, both the low and high frequency bands demonstrated congruent activity between action execution and observation. Our results suggest that action observation could be an effective and critical procedure for deriving the mapping from ECoG signals to intended movement for an ECoG-based BCI system for individuals with

  8. Neural correlates of economic value and valuation context: an event-related potential study.

    Science.gov (United States)

    Tyson-Carr, John; Kokmotou, Katerina; Soto, Vicente; Cook, Stephanie; Fallon, Nicholas; Giesbrecht, Timo; Stancak, Andrej

    2018-05-01

    The value of environmental cues and internal states is continuously evaluated by the human brain, and it is this subjective value that largely guides decision making. The present study aimed to investigate the initial value attribution process, specifically the spatiotemporal activation patterns associated with values and valuation context, using electroencephalographic event-related potentials (ERPs). Participants completed a stimulus rating task in which everyday household items marketed up to a price of £4 were evaluated with respect to their desirability or material properties. The subjective values of items were evaluated as willingness to pay (WTP) in a Becker-DeGroot-Marschak auction. On the basis of the individual's subjective WTP values, the stimuli were divided into high- and low-value items. Source dipole modeling was applied to estimate the cortical sources underlying ERP components modulated by subjective values (high vs. low WTP) and the evaluation condition (value-relevant vs. value-irrelevant judgments). Low-WTP items and value-relevant judgments both led to a more pronounced N2 visual evoked potential at right frontal scalp electrodes. Source activity in right anterior insula and left orbitofrontal cortex was larger for low vs. high WTP at ∼200 ms. At a similar latency, source activity in right anterior insula and right parahippocampal gyrus was larger for value-relevant vs. value-irrelevant judgments. A stronger response for low- than high-value items in anterior insula and orbitofrontal cortex appears to reflect aversion to low-valued item acquisition, which in an auction experiment would be perceived as a relative loss. This initial low-value bias occurs automatically irrespective of the valuation context. NEW & NOTEWORTHY We demonstrate the spatiotemporal characteristics of the brain valuation process using event-related potentials and willingness to pay as a measure of subjective value. The N2 component resolves values of objects with a

  9. Study on reciprocal relation of pore water pressure with genetic algorithm and neural network model (Contract research)

    International Nuclear Information System (INIS)

    Seno, Shoji; Nakajima, Makoto; Toida, Masaru; Kunimaru, Takanori; Watanabe, Kunio; Sohail Ahmed Rai

    2009-12-01

    Horonobe Underground Research Center has carried out the Horonobe Underground Research Laboratory Project which is a comprehensive research project to investigate the deep geological environment within sedimentary rock. In this project, long-term observation of the pore water pressure has been conducted with monitoring systems introduced in 9 of 11 boreholes drilled in phase I (surface-based investigation). Since August 2003 the monitoring systems have been settled successively in the boreholes, and a certain amount of the pore water pressure data has been already accumulated. Using 6 borehole data (HDB-1,3,6,7,8,9) among this, this report summarized the result of a study on reciprocal relation of pore water pressure to investigate the hydrogeological environment of this site. At first, to exclude the influences of working of nature such as tide and atmospheric pressure from the source data, an analysis with Bayesian model was progressed. As the result of the estimation of these influences calculated by BAYTAP-G (Bayesian Tidal Analysis Program Grouping Model), it was found that the influence of the atmospheric pressure was comparatively large and that of tide was comparatively small. Secondly, an analysis on the reciprocal relation of the pore water pressure was carried out to investigate the relation between the different depth points of the same borehole and the relation between different boreholes. As the result of the calculations with genetic algorithm (GA) and neural network models (BPANN, GAANN), it was found that estimation by GA models was better than other models in the case where analyzing data included radical changes. And the result also showed that in regions lower than GL.-400m of HDB-3,6,7,8, the pore water pressures change in the same manner. These results indicate the effectiveness of this analysis method. (author)

  10. Scaling relations for soliton compression and dispersive-wave generation in tapered optical fibers

    DEFF Research Database (Denmark)

    Lægsgaard, Jesper

    2018-01-01

    In this paper, scaling relations for soliton compression in tapered optical fibers are derived and discussed. The relations allow simple and semi-accurate estimates of the compression point and output noise level, which is useful, for example, for tunable dispersive-wave generation with an agile ...

  11. 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.

  12. Verifying the performance of artificial neural network and multiple linear regression in predicting the mean seasonal municipal solid waste generation rate: A case study of Fars province, Iran.

    Science.gov (United States)

    Azadi, Sama; Karimi-Jashni, Ayoub

    2016-02-01

    Predicting the mass of solid waste generation plays an important role in integrated solid waste management plans. In this study, the performance of two predictive models, Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) was verified to predict mean Seasonal Municipal Solid Waste Generation (SMSWG) rate. The accuracy of the proposed models is illustrated through a case study of 20 cities located in Fars Province, Iran. Four performance measures, MAE, MAPE, RMSE and R were used to evaluate the performance of these models. The MLR, as a conventional model, showed poor prediction performance. On the other hand, the results indicated that the ANN model, as a non-linear model, has a higher predictive accuracy when it comes to prediction of the mean SMSWG rate. As a result, in order to develop a more cost-effective strategy for waste management in the future, the ANN model could be used to predict the mean SMSWG rate. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. A pilot study for distinguishing chromophobe renal cell carcinoma and oncocytoma using second harmonic generation imaging and convolutional neural network analysis of collagen fibrillar structure

    Science.gov (United States)

    Judd, Nicolas; Smith, Jason; Jain, Manu; Mukherjee, Sushmita; Icaza, Michael; Gallagher, Ryan; Szeligowski, Richard; Wu, Binlin

    2018-02-01

    A clear distinction between oncocytoma and chromophobe renal cell carcinoma (chRCC) is critically important for clinical management of patients. But it may often be difficult to distinguish the two entities based on hematoxylin and eosin (H and E) stained sections alone. In this study, second harmonic generation (SHG) signals which are very specific to collagen were used to image collagen fibril structure. We conduct a pilot study to develop a new diagnostic method based on the analysis of collagen associated with kidney tumors using convolutional neural networks (CNNs). CNNs comprise a type of machine learning process well-suited for drawing information out of images. This study examines a CNN model's ability to differentiate between oncocytoma (benign), and chRCC (malignant) kidney tumor images acquired with second harmonic generation (SHG), which is very specific for collagen matrix. To the best of our knowledge, this is the first study that attempts to distinguish the two entities based on their collagen structure. The model developed from this study demonstrated an overall classification accuracy of 68.7% with a specificity of 66.3% and sensitivity of 74.6%. While these results reflect an ability to classify the kidney tumors better than chance, further studies will be carried out to (a) better realize the tumor classification potential of this method with a larger sample size and (b) combining SHG with two-photon excited intrinsic fluorescence signal to achieve better classification.

  14. Dificultades en los métodos de estudio de exposiciones ambientales y defectos del tubo neural Methodological challenges to assess environmental exposures related to neural tube defects

    Directory of Open Access Journals (Sweden)

    Víctor Hugo Borja-Aburto

    1999-11-01

    Full Text Available Objetivo. Discutir las actitudes en la evaluación de las exposiciones ambientales como factores de riesgo para defectos de riesgo del tubo neural, al tiempo que se presentan los principales factores estudiados hasta la fecha. Resultados. Las exposiciones ambientales se citan muy a menudo como causa de malformaciones congénitas; sin embargo, ha sido difícil establecer esta asociación en los estudios de poblaciones humanas, debido a problemas en su diseño y conducción. Lo anterior es particularmente marcado en el caso del estudio de los defectos del cierre del tubo neural (DTN, que es una de las principales malformaciones y que incluye anencefalia, espina bífida y encefalocele, y su asociación con exposiciones ambientales. Las dificultades en los métodos surgen de: a la medida de frecuencia para realizar comparaciones espacio-temporales; b la clasificación y heterogeneidad de las malformaciones; c la consideración de los factores relacionados con la madre, el padre y el producto, de manera conjunta, y d la evaluación de las exposiciones ambientales. Conclusiones. Hipotéticamente las exposiciones ambientales tanto del padre como de la madre pueden producir daño genético antes y/o después de la concepción por la acción directa sobre el embrión o sobre el complejo fetoplacentario, de tal manera que en la evaluación de exposiciones ambientales: a deben tomarse en cuenta las exposiciones maternas y paternas; b debe considerarse el periodo crítico de exposición, esto es, tres meses anteriores a la concepción para el padre y un mes alrededor de la concepción para la madre; c en la medida de lo posible, la evaluación de la exposición deberá ser cuantitativa, evitando clasificar a los grupos únicamente como expuestos y no expuestos, y d es recomendable emplear marcadores biológicos de exposición siempre que sea posible, así como utilizar marcadores biológicos que permitan clasificar a la población en grupos con distinta

  15. Neural correlates of cued recall in young and older adults: an event-related potential study.

    Science.gov (United States)

    Angel, Lucie; Fay, Séverine; Bouazzaoui, Badiâa; Granjon, Lionel; Isingrini, Michel

    2009-01-07

    This experiment investigated age differences in electrophysiological correlates of retrieval success in a word-stem cued recall task. Young adults (M+/-SD: 21.4 years+/-1.9) performed this memory task more accurately than older participants (M+/-SD: 65.1 years+/-3.3). Robust event-related brain potential (ERP) old/new effects were identified in both age groups. The main age differences were observed in latency and lateralization of ERP effects. Young adults exhibited a parietal effect that became focused over left parietal electrodes, whereas no asymmetry was observed in older adults. Moreover, ERP effects were more delayed in the older group. Overall, these findings provide some evidence of the reduction of processing speed during aging and suggest that young and older adults may recruit distinct cerebral patterns during episodic cued recall.

  16. Neural activity in the reward-related brain regions predicts implicit self-esteem: A novel validity test of psychological measures using neuroimaging.

    Science.gov (United States)

    Izuma, Keise; Kennedy, Kate; Fitzjohn, Alexander; Sedikides, Constantine; Shibata, Kazuhisa

    2018-03-01

    Self-esteem, arguably the most important attitudes an individual possesses, has been a premier research topic in psychology for more than a century. Following a surge of interest in implicit attitude measures in the 90s, researchers have tried to assess self-esteem implicitly to circumvent the influence of biases inherent in explicit measures. However, the validity of implicit self-esteem measures remains elusive. Critical tests are often inconclusive, as the validity of such measures is examined in the backdrop of imperfect behavioral measures. To overcome this serious limitation, we tested the neural validity of the most widely used implicit self-esteem measure, the implicit association test (IAT). Given the conceptualization of self-esteem as attitude toward the self, and neuroscience findings that the reward-related brain regions represent an individual's attitude or preference for an object when viewing its image, individual differences in implicit self-esteem should be associated with neural signals in the reward-related regions during passive-viewing of self-face (the most obvious representation of the self). Using multi-voxel pattern analysis (MVPA) on functional MRI (fMRI) data, we demonstrate that the neural signals in the reward-related regions were robustly associated with implicit (but not explicit) self-esteem, thus providing unique evidence for the neural validity of the self-esteem IAT. In addition, both implicit and explicit self-esteem were related, although differently, to neural signals in regions involved in self-processing. Our finding highlights the utility of neuroscience methods in addressing fundamental psychological questions and providing unique insights into important psychological constructs. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  17. Baseline Levels of Rapid Eye Movement Sleep May Protect Against Excessive Activity in Fear-Related Neural Circuitry.

    Science.gov (United States)

    Lerner, Itamar; Lupkin, Shira M; Sinha, Neha; Tsai, Alan; Gluck, Mark A

    2017-11-15

    Sleep, and particularly rapid eye movement sleep (REM), has been implicated in the modulation of neural activity following fear conditioning and extinction in both human and animal studies. It has long been presumed that such effects play a role in the formation and persistence of posttraumatic stress disorder, of which sleep impairments are a core feature. However, to date, few studies have thoroughly examined the potential effects of sleep prior to conditioning on subsequent acquisition of fear learning in humans. Furthermore, these studies have been restricted to analyzing the effects of a single night of sleep-thus assuming a state-like relationship between the two. In the current study, we used long-term mobile sleep monitoring and functional neuroimaging (fMRI) to explore whether trait-like variations in sleep patterns, measured in advance in both male and female participants, predict subsequent patterns of neural activity during fear learning. Our results indicate that higher baseline levels of REM sleep predict reduced fear-related activity in, and connectivity between, the hippocampus, amygdala and ventromedial PFC during conditioning. Additionally, skin conductance responses (SCRs) were weakly correlated to the activity in the amygdala. Conversely, there was no direct correlation between REM sleep and SCRs, indicating that REM may only modulate fear acquisition indirectly. In a follow-up experiment, we show that these results are replicable, though to a lesser extent, when measuring sleep over a single night just before conditioning. As such, baseline sleep parameters may be able to serve as biomarkers for resilience, or lack thereof, to trauma. SIGNIFICANCE STATEMENT Numerous studies over the past two decades have established a clear role of sleep in fear-learning processes. However, previous work has focused on the effects of sleep following fear acquisition, thus neglecting the potential effects of baseline sleep levels on the acquisition itself. The

  18. Social contexts modulate neural responses in the processing of others' pain: An event-related potential study.

    Science.gov (United States)

    Cui, Fang; Zhu, Xiangru; Luo, Yuejia

    2017-08-01

    Two hypotheses have been proposed regarding the response that is triggered by observing others' pain: the "empathizing hypothesis" and the "threat value of pain hypothesis." The former suggests that observing others' pain triggers an empathic response. The latter suggests that it activates the threat-detection system. In the present study, participants were instructed to observe pictures that showed an anonymous hand or foot in a painful or non-painful situation in a threatening or friendly social context. Event-related potentials were recorded when the participants passively observed these pictures in different contexts. We observed an interaction between context and picture in the early automatic N1 component, in which the painful pictures elicited a larger amplitude than the non-painful pictures only in the threatening context and not in the friendly context. We also observed an interaction between context and picture in the late P3 component, in which the painful pictures elicited a larger amplitude than the non-painful pictures only in the friendly context and not in the threatening context. These results indicate that specific social contexts can modulate the neural responses to observing others' pain. The "empathic hypothesis" and "threat value of pain hypothesis" are not mutually exclusive and do not contradict each other but rather work in different temporal stages.

  19. The COMT Val/Met polymorphism is associated with reading related skills and consistent patterns of functional neural activation

    Science.gov (United States)

    Landi, Nicole; Frost, Stephen J.; Mencl, W. Einar; Preston, Jonathan L.; Jacobsen, Leslie K.; Lee, Maria; Yrigollen, Carolyn; Pugh, Kenneth R.; Grigorenko, Elena L.

    2013-01-01

    In both children and adults there is large variability in reading skill, with approximately 5–10% of individuals characterized as having reading disability; these individuals struggle to learn to read despite adequate intelligence and opportunity. Although it is well established that a substantial portion of this variability is attributed to the genetic differences between individuals, specifics of the connections between reading and the genome are not understood. This article presents data that suggest that variation in the COMT gene, which has previously been associated with variation in higher-order cognition, is associated with reading and reading-related skills, both at the level of brain and behavior. In particular, we found that the COMT Val/Met polymorphism at rs4680, which results in the substitution of the ancestral Valine (Val) by Methionine (Met), was associated with better performance on a number of critical reading measures and with patterns of functional neural activation that have been linked to better readers. We argue that this polymorphism, known for its broad effects on cognition, may modulate (likely through frontal lobe function) reading skill. PMID:23278923

  20. The COMT Val/Met polymorphism is associated with reading-related skills and consistent patterns of functional neural activation.

    Science.gov (United States)

    Landi, Nicole; Frost, Stephen J; Mencl, W Einar; Preston, Jonathan L; Jacobsen, Leslie K; Lee, Maria; Yrigollen, Carolyn; Pugh, Kenneth R; Grigorenko, Elena L

    2013-01-01

    In both children and adults there is large variability in reading skill, with approximately 5-10% of individuals characterized as having reading disability; these individuals struggle to learn to read despite adequate intelligence and opportunity. Although it is well established that a substantial portion of this variability is attributed to the genetic differences between individuals, specifics of the connections between reading and the genome are not understood. This article presents data that suggest that variation in the COMT gene, which has previously been associated with variation in higher-order cognition, is associated with reading and reading-related skills, at the level of both brain and behavior. In particular, we found that the COMT Val/Met polymorphism at rs4680, which results in the substitution of the ancestral Valine (Val) by Methionine (Met), was associated with better performance on a number of critical reading measures and with patterns of functional neural activation that have been linked to better readers. We argue that this polymorphism, known for its broad effects on cognition, may modulate (likely through frontal lobe function) reading skill. © 2012 Blackwell Publishing Ltd.

  1. Neural correlates of self-appraisals in the near and distant future: an event-related potential study.

    Directory of Open Access Journals (Sweden)

    Yangmei Luo

    Full Text Available To investigate perceptual and neural correlates of future self-appraisals as a function of temporal distance, event-related potentials (ERPs were recorded while participants (11 women, eight men made judgments about the applicability of trait adjectives to their near future selves (i.e., one month from now and their distant future selves (i.e., three years from now. Behavioral results indicated people used fewer positive adjectives, more negative adjectives, recalled more specific events coming to mind and felt more psychologically connected to the near future self than the distant future self. Electrophysiological results demonstrated that negative trait adjectives elicited more positive ERP deflections than did positive trait adjectives in the interval between 550 and 800 ms (late positive component within the near future self condition. However, within the same interval, there were no significant differences between negative and positive traits adjectives in the distant future self condition. The results suggest that negative emotional processing in future self-appraisals is modulated by temporal distance, consistent with predictions of construal level theory.

  2. Helping or punishing strangers: neural correlates of altruistic decisions as third-party and of its relation to empathic concern.

    Science.gov (United States)

    Hu, Yang; Strang, Sabrina; Weber, Bernd

    2015-01-01

    Social norms are a cornerstone of human society. When social norms are violated (e.g., fairness) people can either help the victim or punish the violator in order to restore justice. Recent research has shown that empathic concern influences this decision to help or punish. Using functional magnetic resonance imaging (fMRI) we investigated the neural underpinnings of third-party help and punishment and the involvement of empathic concern. Participants saw a person violating a social norm, i.e., proposing unfair offers in a dictator game, at the expense of another person. The participants could then decide to either punish the violator or help the victim. Our results revealed that both third-party helping as well as third-party punishing activated the bilateral striatum, a region strongly related with reward processing, indicating that both altruistic decisions share a common neuronal basis. In addition, also different networks were involved in the two processes compared with control conditions; bilateral striatum and the right lateral prefrontal cortex (lPFC) during helping and bilateral striatum as well as left lPFC and ventral medial prefrontal cortex (vmPFC) during punishment. Further we found that individual differences in empathic concern influenced whether people prefer to help or to punish. People with high empathic concern helped more frequently, were faster in their decision and showed higher activation in frontoparietal regions during helping compared with punishing. Our findings provide insights into the neuronal basis of human altruistic behavior and social norm enforcement mechanism.

  3. Neural Temporal Dynamics of Social Exclusion Elicited by Averted Gaze: An Event-Related Potentials Study

    Directory of Open Access Journals (Sweden)

    Yue Leng

    2018-02-01

    Full Text Available Eye gaze plays a fundamental role in social communication. The averted eye gaze during social interaction, as the most common form of silent treatment, conveys a signal of social exclusion. In the present study, we examined the time course of brain response to social exclusion by using a modified version of Eye-gaze paradigm. The event-related potentials (ERPs data and the subjective rating data showed that the frontocentral P200 was positively correlated with negative mood of excluded events, whereas, the centroparietal late positive potential (LPP was positively correlated with the perceived ostracism intensity. Both the P200 and LPP were more positive-going for excluded events than for included events. These findings suggest that brain responses sensitive to social exclusion can be divided into the early affective processing stage, linking to the early pre-cognitive warning system; and the late higher-order processes stage, demanding attentional resources for elaborate stimuli evaluation and categorization generally not under specific situation.

  4. Safety-Evaluation Report related to the D2/D3 steam-generator design modification

    International Nuclear Information System (INIS)

    1983-03-01

    This Safety Evaluation Report (SER) related to the D2/D3 steam generator design modification has been prepared by the Office of Nuclear Reactor Regulation of the US Nuclear Regulatory Commission. The purpose of this SER is to issue the staff's evaluation of the acceptability of the design modification for both installation and full-power operation in the D2/D3 steam generators based on the Design Review Panel Report of January 1983

  5. Age-related vulnerability in the neural systems supporting semantic processing

    Directory of Open Access Journals (Sweden)

    Jonathan E Peelle

    2013-09-01

    Full Text Available Our ability to form abstract representations of objects in semantic memory is crucial to language and thought. The utility of this information relies both on the representations of sensory-motor feature knowledge stored in long-term memory and the executive processes required to retrieve, manipulate, and evaluate this semantic knowledge in a task-relevant manner. These complementary components of semantic memory can be differentially impacted by aging. We investigated semantic processing in normal aging using functional magnetic resonance imaging (fMRI. Young and older adults were asked to judge whether two printed object names match on a particular feature (for example, whether a tomato and strawberry have the same color. The task thus required both retrieval of relevant visual feature knowledge of object concepts and evaluating this information. Objects were drawn from either natural kinds or manufactured objects, and were queried on either color or shape in a factorial design. Behaviorally, all subjects performed well, but older adults could be divided into those whose performance matched that of young adults (better performers and those whose performance was worse (poorer performers. All subjects activated several cortical regions while performing this task, including bilateral inferior and lateral temporal cortex and left frontal and prefrontal cortex. Better performing older adults showed increased overall activity in bilateral premotor cortex and left lateral occipital cortex compared to young adults, and increased activity in these brain regions relative to poorer performing older adults who also showed gray matter atrophy in premotor cortex. These findings highlight the contribution of domain-general executive processing brain regions to semantic memory, and illustrate differences in how these regions are recruited in healthy older adults.

  6. Sensory modality specificity of neural activity related to memory in visual cortex.

    Science.gov (United States)

    Gibson, J R; Maunsell, J H

    1997-09-01

    Previous studies have shown that when monkeys perform a delayed match-to-sample (DMS) task, some neurons in inferotemporal visual cortex are activated selectively during the delay period when the animal must remember particular visual stimuli. This selective delay activity may be involved in short-term memory. It does not depend on visual stimulation: both auditory and tactile stimuli can trigger selective delay activity in inferotemporal cortex when animals expect to respond to visual stimuli in a DMS task. We have examined the overall modality specificity of delay period activity using a variety of auditory/visual cross-modal and unimodal DMS tasks. The cross-modal DMS tasks involved making specific long-term memory associations between visual and auditory stimuli, whereas the unimodal DMS tasks were standard identity matching tasks. Delay activity existed in auditory/visual cross-modal DMS tasks whether the animal anticipated responding to visual or auditory stimuli. No evidence of selective delay period activation was seen in a purely auditory DMS task. Delay-selective cells were relatively common in one animal where they constituted up to 53% neurons tested with a given task. This was only the case for up to 9% of cells in a second animal. In the first animal, a specific long-term memory representation for learned cross-modal associations was observed in delay activity, indicating that this type of representation need not be purely visual. Furthermore, in this same animal, delay activity in one cross-modal task, an auditory-to-visual task, predicted correct and incorrect responses. These results suggest that neurons in inferotemporal cortex contribute to abstract memory representations that can be activated by input from other sensory modalities, but these representations are specific to visual behaviors.

  7. Rapid generation of sub-type, region-specific neurons and neural networks from human pluripotent stem cell-derived neurospheres

    Directory of Open Access Journals (Sweden)

    Aynun N. Begum

    2015-11-01

    Full Text Available Stem cell-based neuronal differentiation has provided a unique opportunity for disease modeling and regenerative medicine. Neurospheres are the most commonly used neuroprogenitors for neuronal differentiation, but they often clump in culture, which has always represented a challenge for neurodifferentiation. In this study, we report a novel method and defined culture conditions for generating sub-type or region-specific neurons from human embryonic and induced pluripotent stem cells derived neurosphere without any genetic manipulation. Round and bright-edged neurospheres were generated in a supplemented knockout serum replacement medium (SKSRM with 10% CO2, which doubled the expression of the NESTIN, PAX6 and FOXG1 genes compared with those cultured with 5% CO2. Furthermore, an additional step (AdSTEP was introduced to fragment the neurospheres and facilitate the formation of a neuroepithelial-type monolayer that we termed the “neurosphederm”. The large neural tube-type rosette (NTTR structure formed from the neurosphederm, and the NTTR expressed higher levels of the PAX6, SOX2 and NESTIN genes compared with the neuroectoderm-derived neuroprogenitors. Different layers of cortical, pyramidal, GABAergic, glutamatergic, cholinergic neurons appeared within 27 days using the neurosphederm, which is a shorter period than in traditional neurodifferentiation-protocols (42–60 days. With additional supplements and timeline dopaminergic and Purkinje neurons were also generated in culture too. Furthermore, our in vivo results indicated that the fragmented neurospheres facilitated significantly better neurogenesis in severe combined immunodeficiency (SCID mouse brains compared with the non-fragmented neurospheres. Therefore, this neurosphere-based neurodifferentiation protocol is a valuable tool for studies of neurodifferentiation, neuronal transplantation and high throughput screening assays.

  8. Dopamine-signalled reward predictions generated by competitive excitation and inhibition in a spiking neural network model

    Directory of Open Access Journals (Sweden)

    Paul eChorley

    2011-05-01

    Full Text Available Dopaminergic neurons in the mammalian substantia nigra displaycharacteristic phasic responses to stimuli which reliably predict thereceipt of primary rewards. These responses have been suggested toencode reward prediction-errors similar to those used in reinforcementlearning. Here, we propose a model of dopaminergic activity in whichprediction error signals are generated by the joint action ofshort-latency excitation and long-latency inhibition, in a networkundergoing dopaminergic neuromodulation of both spike-timing dependentsynaptic plasticity and neuronal excitability. In contrast toprevious models, sensitivity to recent events is maintained by theselective modification of specific striatal synapses, efferent tocortical neurons exhibiting stimulus-specific, temporally extendedactivity patterns. Our model shows, in the presence of significantbackground activity, (i a shift in dopaminergic response from rewardto reward predicting stimuli, (ii preservation of a response tounexpected rewards, and (iii a precisely-timed below-baseline dip inactivity observed when expected rewards are omitted.

  9. Relational and item-specific influences on generate-recognize processes in recall.

    Science.gov (United States)

    Guynn, Melissa J; McDaniel, Mark A; Strosser, Garrett L; Ramirez, Juan M; Castleberry, Erica H; Arnett, Kristen H

    2014-02-01

    The generate-recognize model and the relational-item-specific distinction are two approaches to explaining recall. In this study, we consider the two approaches in concert. Following Jacoby and Hollingshead (Journal of Memory and Language 29:433-454, 1990), we implemented a production task and a recognition task following production (1) to evaluate whether generation and recognition components were evident in cued recall and (2) to gauge the effects of relational and item-specific processing on these components. An encoding task designed to augment item-specific processing (anagram-transposition) produced a benefit on the recognition component (Experiments 1-3) but no significant benefit on the generation component (Experiments 1-3), in the context of a significant benefit to cued recall. By contrast, an encoding task designed to augment relational processing (category-sorting) did produce a benefit on the generation component (Experiment 3). These results converge on the idea that in recall, item-specific processing impacts a recognition component, whereas relational processing impacts a generation component.

  10. Altered Neural Activity during Semantic Object Memory Retrieval in Amnestic Mild Cognitive Impairment as Measured by Event-Related Potentials.

    Science.gov (United States)

    Chiang, Hsueh-Sheng; Mudar, Raksha A; Pudhiyidath, Athula; Spence, Jeffrey S; Womack, Kyle B; Cullum, C Munro; Tanner, Jeremy A; Eroh, Justin; Kraut, Michael A; Hart, John

    2015-01-01

    Deficits in semantic memory in individuals with amnestic mild cognitive impairment (aMCI) have been previously reported, but the underlying neurobiological mechanisms remain to be clarified. We examined event-related potentials (ERPs) associated with semantic memory retrieval in 16 individuals with aMCI as compared to 17 normal controls using the Semantic Object Retrieval Task (EEG SORT). In this task, subjects judged whether pairs of words (object features) elicited retrieval of an object (retrieval trials) or not (non-retrieval trials). Behavioral findings revealed that aMCI subjects had lower accuracy scores and marginally longer reaction time compared to controls. We used a multivariate analytical technique (STAT-PCA) to investigate similarities and differences in ERPs between aMCI and control groups. STAT-PCA revealed a left fronto-temporal component starting at around 750 ms post-stimulus in both groups. However, unlike controls, aMCI subjects showed an increase in the frontal-parietal scalp potential that distinguished retrieval from non-retrieval trials between 950 and 1050 ms post-stimulus negatively correlated with the performance on the logical memory subtest of the Wechsler Memory Scale-III. Thus, individuals with aMCI were not only impaired in their behavioral performance on SORT relative to controls, but also displayed alteration in the corresponding ERPs. The altered neural activity in aMCI compared to controls suggests a more sustained and effortful search during object memory retrieval, which may be a potential marker indicating disease processes at the pre-dementia stage.

  11. Experience on environmental qualification of safety-related components for Darlington Nuclear Generating Station

    International Nuclear Information System (INIS)

    Yu, A.S.; Kukreti, B.M.

    1987-01-01

    The proliferation of Nuclear Power Plant safety concerns has lead to increasing attention over the Environmental Qualification (EQ) of Nuclear Power Plant Safety-Related Components to provide the assurance that the safety related equipment will meet their intended functions during normal operation and postulated accident conditions. The environmental qualification of these components is also a Licensing requirement for Darlington Nuclear Generating Station. This paper provides an overview of EQ and the experience of a pilot project, in the qualification of the Main Moderator System safety-related functions for the Darlington Nuclear Generating Station currently under construction. It addresses the various phases of qualification from the identification of the EQ Safety-Related Components List, definition of location specific service conditions (normal, adbnormal and accident), safety-related functions, Environmental Qualification Assessments and finally, an EQ system summary report for the Main Moderator System. The results of the pilot project are discussed and the methodology reviewed. The paper concludes that the EQ Program developed for Darlington Nuclear Generating Station, as applied to the qualification of the Main Moderator System, contained all the elements necessary in the qualification of safety-related equipment. The approach taken in the qualification of the Moderator safety-related equipment proves to provide a sound framework for the qualification of other safety-related components in the station

  12. INTEGRATED APPROACH TO GENERATION OF PRECEDENCE RELATIONS AND PRECEDENCE GRAPHS FOR ASSEMBLY SEQUENCE PLANNING

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    An integrated approach to generation of precedence relations and precedence graphs for assembly sequence planning is presented, which contains more assembly flexibility. The approach involves two stages. Based on the assembly model, the components in the assembly can be divided into partially constrained components and completely constrained components in the first stage, and then geometric precedence relation for every component is generated automatically. According to the result of the first stage, the second stage determines and constructs all precedence graphs. The algorithms of these two stages proposed are verified by two assembly examples.

  13. Specifying the Concept of Future Generations for Addressing Issues Related to High-Level Radioactive Waste.

    Science.gov (United States)

    Kermisch, Celine

    2016-12-01

    The nuclear community frequently refers to the concept of "future generations" when discussing the management of high-level radioactive waste. However, this notion is generally not defined. In this context, we have to assume a wide definition of the concept of future generations, conceived as people who will live after the contemporary people are dead. This definition embraces thus each generation following ours, without any restriction in time. The aim of this paper is to show that, in the debate about nuclear waste, this broad notion should be further specified and to clarify the related implications for nuclear waste management policies. Therefore, we provide an ethical analysis of different management strategies for high-level waste in the light of two principles, protection of future generations-based on safety and security-and respect for their choice. This analysis shows that high-level waste management options have different ethical impacts across future generations, depending on whether the memory of the waste and its location is lost, or not. We suggest taking this distinction into account by introducing the notions of "close future generations" and "remote future generations", which has important implications on nuclear waste management policies insofar as it stresses that a retrievable disposal has fewer benefits than usually assumed.

  14. WE-AB-204-06: Pseudo-CT Generation Using Undersampled, Single-Acquisition UTE-MDixon and Direct-Mapping Artificial Neural Networks for MR-Based Attenuation Correction and Radiation Therapy Planning

    Energy Technology Data Exchange (ETDEWEB)

    Su, K; Kuo, J [Case Center for Imaging Research, Case Western Reserve University, Cleveland, Ohio (United States); Department of Radiology, University Hospitals Case Medical Center, Case Western Reserve University, Cleveland, Ohio (United States); Hu, L; Traughber, M [Philips Healthcare, Cleveland, Ohio (United States); Pereira, G; Traughber, B [Department of Radiation Oncology, University Hospitals Seidman Cancer Center, Case Western Reserve University, Cleveland, Ohio (United States); Herrmann, K [Department of Radiology, University Hospitals Case Medical Center, Case Western Reserve University, Cleveland, Ohio (United States); Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, Ohio (United States); Muzic, R [Case Center for Imaging Research, Case Western Reserve University, Cleveland, Ohio (United States); Department of Radiology, University Hospitals Case Medical Center, Case Western Reserve University, Cleveland, Ohio (United States); Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH (United States)

    2015-06-15

    Purpose: Emerging technologies such as dedicated PET/MRI and MR-therapy systems require robust and clinically practical methods for determining photon attenuation. Herein, we propose using novel MR acquisition methods and processing for the generation of pseudo-CTs. Methods: A single acquisition, 190-second UTE-mDixon sequence with 25% (angular) sampling density and 3D radial readout was performed on nine volunteers. Three water-filled tubes were placed in the FOV for trajectory-delay correction. The MR data were reconstructed to generate three primitive images acquired at TEs of 0.1, 1.5 and 2.8 ms. In addition, three derived MR images were generated, i.e. two-point Dixon water/fat separation and R2* (1/T2*) map. Furthermore, two spatial features, i.e. local binary pattern (S-1) and relative spatial coordinates (S-2), were incorporated. A direct-mapping operator was generated using Artificial Neural Networks (ANNs) for transforming the MR features to a pseudo-CT. CT images served as the training data and, using a leave-one-out method, for performance evaluation using mean prediction deviation (MPD), mean absolute prediction deviation (MAPD), and correlation coefficient (R). Results: The errors between measured CT and pseudo-CT declined dramatically when the spatial features, i.e. S-1 and S-2, were included. The MPD, MAPD, and R were, respectively, 5±57 HU, 141±41 HU, and 0.815±0.066 for results generated by the ANN trained without the spatial features and were 32±26 HU, 115±18 HU, and 0.869±0.035 with the spatial features. The estimation errors of the pseudo-CT were smaller when both the S-1 and S-2 were used together than when either the S-1 or the S-2 was used. Pseudo-CT generation (256×256×256 voxels) by ANN took < 0.5 s using a computer having an Intel i7 3.4GHz CPU and 16 GB RAM. Conclusion: The proposed direct-mapping ANN approach is a technically accurate, clinically practical method for pseudo-CT generation and can potentially help improve the

  15. WE-AB-204-06: Pseudo-CT Generation Using Undersampled, Single-Acquisition UTE-MDixon and Direct-Mapping Artificial Neural Networks for MR-Based Attenuation Correction and Radiation Therapy Planning

    International Nuclear Information System (INIS)

    Su, K; Kuo, J; Hu, L; Traughber, M; Pereira, G; Traughber, B; Herrmann, K; Muzic, R

    2015-01-01

    Purpose: Emerging technologies such as dedicated PET/MRI and MR-therapy systems require robust and clinically practical methods for determining photon attenuation. Herein, we propose using novel MR acquisition methods and processing for the generation of pseudo-CTs. Methods: A single acquisition, 190-second UTE-mDixon sequence with 25% (angular) sampling density and 3D radial readout was performed on nine volunteers. Three water-filled tubes were placed in the FOV for trajectory-delay correction. The MR data were reconstructed to generate three primitive images acquired at TEs of 0.1, 1.5 and 2.8 ms. In addition, three derived MR images were generated, i.e. two-point Dixon water/fat separation and R2* (1/T2*) map. Furthermore, two spatial features, i.e. local binary pattern (S-1) and relative spatial coordinates (S-2), were incorporated. A direct-mapping operator was generated using Artificial Neural Networks (ANNs) for transforming the MR features to a pseudo-CT. CT images served as the training data and, using a leave-one-out method, for performance evaluation using mean prediction deviation (MPD), mean absolute prediction deviation (MAPD), and correlation coefficient (R). Results: The errors between measured CT and pseudo-CT declined dramatically when the spatial features, i.e. S-1 and S-2, were included. The MPD, MAPD, and R were, respectively, 5±57 HU, 141±41 HU, and 0.815±0.066 for results generated by the ANN trained without the spatial features and were 32±26 HU, 115±18 HU, and 0.869±0.035 with the spatial features. The estimation errors of the pseudo-CT were smaller when both the S-1 and S-2 were used together than when either the S-1 or the S-2 was used. Pseudo-CT generation (256×256×256 voxels) by ANN took < 0.5 s using a computer having an Intel i7 3.4GHz CPU and 16 GB RAM. Conclusion: The proposed direct-mapping ANN approach is a technically accurate, clinically practical method for pseudo-CT generation and can potentially help improve the

  16. Generation of brain tumours in mice by Cre-mediated recombination of neural progenitors in situ with the tamoxifen metabolite endoxifen.

    Science.gov (United States)

    Benedykcinska, Anna; Ferreira, Andreia; Lau, Joanne; Broni, Jessica; Richard-Loendt, Angela; Henriquez, Nico V; Brandner, Sebastian

    2016-02-01

    Targeted cell- or region-specific gene recombination is widely used in the functional analysis of genes implicated in development and disease. In the brain, targeted gene recombination has become a mainstream approach to study neurodegeneration or tumorigenesis. The use of the Cre-loxP system to study tumorigenesis in the adult central nervous system (CNS) can be limited, when the promoter (such as GFAP) is also transiently expressed during development, which can result in the recombination of progenies of different lineages. Engineering of transgenic mice expressing Cre recombinase fused to a mutant of the human oestrogen receptor (ER) allows the circumvention of transient developmental Cre expression by inducing recombination in the adult organism. The recombination of loxP sequences occurs only in the presence of tamoxifen. Systemic administration of tamoxifen can, however, exhibit toxicity and might also recombine unwanted cell populations if the promoter driving Cre expression is active at the time of tamoxifen administration. Here, we report that a single site-specific injection of an active derivative of tamoxifen successfully activates Cre recombinase and selectively recombines tumour suppressor genes in neural progenitor cells of the subventricular zone in mice, and we demonstrate its application in a model for the generation of intrinsic brain tumours. © 2016. Published by The Company of Biologists Ltd.

  17. Generation of brain tumours in mice by Cre-mediated recombination of neural progenitors in situ with the tamoxifen metabolite endoxifen

    Directory of Open Access Journals (Sweden)

    Anna Benedykcinska

    2016-02-01

    Full Text Available Targeted cell- or region-specific gene recombination is widely used in the functional analysis of genes implicated in development and disease. In the brain, targeted gene recombination has become a mainstream approach to study neurodegeneration or tumorigenesis. The use of the Cre-loxP system to study tumorigenesis in the adult central nervous system (CNS can be limited, when the promoter (such as GFAP is also transiently expressed during development, which can result in the recombination of progenies of different lineages. Engineering of transgenic mice expressing Cre recombinase fused to a mutant of the human oestrogen receptor (ER allows the circumvention of transient developmental Cre expression by inducing recombination in the adult organism. The recombination of loxP sequences occurs only in the presence of tamoxifen. Systemic administration of tamoxifen can, however, exhibit toxicity and might also recombine unwanted cell populations if the promoter driving Cre expression is active at the time of tamoxifen administration. Here, we report that a single site-specific injection of an active derivative of tamoxifen successfully activates Cre recombinase and selectively recombines tumour suppressor genes in neural progenitor cells of the subventricular zone in mice, and we demonstrate its application in a model for the generation of intrinsic brain tumours.

  18. Sequential neural models with stochastic layers

    DEFF Research Database (Denmark)

    Fraccaro, Marco; Sønderby, Søren Kaae; Paquet, Ulrich

    2016-01-01

    How can we efficiently propagate uncertainty in a latent state representation with recurrent neural networks? This paper introduces stochastic recurrent neural networks which glue a deterministic recurrent neural network and a state space model together to form a stochastic and sequential neural...... generative model. The clear separation of deterministic and stochastic layers allows a structured variational inference network to track the factorization of the model's posterior distribution. By retaining both the nonlinear recursive structure of a recurrent neural network and averaging over...

  19. Neural cryptography with feedback.

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Shacham, Lanir; Kanter, Ido

    2004-04-01

    Neural cryptography is based on a competition between attractive and repulsive stochastic forces. A feedback mechanism is added to neural cryptography which increases the repulsive forces. Using numerical simulations and an analytic approach, the probability of a successful attack is calculated for different model parameters. Scaling laws are derived which show that feedback improves the security of the system. In addition, a network with feedback generates a pseudorandom bit sequence which can be used to encrypt and decrypt a secret message.

  20. A Typology of Agency in New Generation Learning Environments: Emerging Relational, Ecological and New Material Considerations

    Science.gov (United States)

    Charteris, Jennifer; Smardon, Dianne

    2018-01-01

    The impetus to move to a new generation learning environments places a spotlight on the relational dynamics of classroom spaces. A key feature is the notion of learner agency. A complex notion, learner agency involves both compliance with and resistance to classroom norms and therefore is far more sophisticated than acting in acquiescence to…

  1. An application of neural networks in microeconomics: input-output mapping in a power generation subsector of the US electricity industry

    NARCIS (Netherlands)

    Erbas, B.C.; Stefanou, S.E.

    2009-01-01

    The use of the artificial neural networks in economics and business goes back to 1950s, while the major bulk of the applications have been developed in more recent years. Reviewing this literature indicates that the field of business benefits from the neural networks in a wide spectrum from

  2. Semantic relation vs. surprise: the differential effects of related and unrelated co-verbal gestures on neural encoding and subsequent recognition.

    Science.gov (United States)

    Straube, Benjamin; Meyer, Lea; Green, Antonia; Kircher, Tilo

    2014-06-03

    Speech-associated gesturing leads to memory advantages for spoken sentences. However, unexpected or surprising events are also likely to be remembered. With this study we test the hypothesis that different neural mechanisms (semantic elaboration and surprise) lead to memory advantages for iconic and unrelated gestures. During fMRI-data acquisition participants were presented with video clips of an actor verbalising concrete sentences accompanied by iconic gestures (IG; e.g., circular gesture; sentence: "The man is sitting at the round table"), unrelated free gestures (FG; e.g., unrelated up down movements; same sentence) and no gestures (NG; same sentence). After scanning, recognition performance for the three conditions was tested. Videos were evaluated regarding semantic relation and surprise by a different group of participants. The semantic relationship between speech and gesture was rated higher for IG (IG>FG), whereas surprise was rated higher for FG (FG>IG). Activation of the hippocampus correlated with subsequent memory performance of both gesture conditions (IG+FG>NG). For the IG condition we found activation in the left temporal pole and middle cingulate cortex (MCC; IG>FG). In contrast, for the FG condition posterior thalamic structures (FG>IG) as well as anterior and posterior cingulate cortices were activated (FG>NG). Our behavioral and fMRI-data suggest different mechanisms for processing related and unrelated co-verbal gestures, both of them leading to enhanced memory performance. Whereas activation in MCC and left temporal pole for iconic co-verbal gestures may reflect semantic memory processes, memory enhancement for unrelated gestures relies on the surprise response, mediated by anterior/posterior cingulate cortex and thalamico-hippocampal structures. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. Can Older Adults Resist the Positivity Effect in Neural Responding: The Impact of Verbal Framing on Event-Related Brain Potentials Elicited by Emotional Images

    OpenAIRE

    Rehmert, Andrea E.; Kisley, Michael A.

    2013-01-01

    Older adults have demonstrated an avoidance of negative information presumably with a goal of greater emotional satisfaction. Understanding whether avoidance of negative information is a voluntary, motivated choice, or an involuntary, automatic response will be important to differentiate, as decision-making often involves emotional factors. With the use of an emotional framing event-related potential (ERP) paradigm, the present study investigated whether older adults could alter neural respon...

  4. Drought Resilience of Water Supplies for Shale Gas Extraction and Related Power Generation in Texas

    Science.gov (United States)

    Reedy, R. C.; Scanlon, B. R.; Nicot, J. P.; Uhlman, K.

    2014-12-01

    There is considerable concern about water availability to support energy production in Texas, particularly considering that many of the shale plays are in semiarid areas of Texas and the state experienced the most extreme drought on record in 2011. The Eagle Ford shale play provides an excellent case study. Hydraulic fracturing water use for shale gas extraction in the play totaled ~ 12 billion gallons (bgal) in 2012, representing ~7 - 10% of total water use in the 16 county play area. The dominant source of water is groundwater which is not highly vulnerable to drought from a recharge perspective because water is primarily stored in the confined portion of aquifers that were recharged thousands of years ago. Water supply drought vulnerability results primarily from increased water use for irrigation. Irrigation water use in the Eagle Ford play was 30 billion gallons higher in the 2011 drought year relative to 2010. Recent trends toward increased use of brackish groundwater for shale gas extraction in the Eagle Ford also reduce pressure on fresh water resources. Evaluating the impacts of natural gas development on water resources should consider the use of natural gas in power generation, which now represents 50% of power generation in Texas. Water consumed in extracting the natural gas required for power generation is equivalent to ~7% of the water consumed in cooling these power plants in the state. However, natural gas production from shale plays can be overall beneficial in terms of water resources in the state because natural gas combined cycle power generation decreases water consumption by ~60% relative to traditional coal, nuclear, and natural gas plants that use steam turbine generation. This reduced water consumption enhances drought resilience of power generation in the state. In addition, natural gas combined cycle plants provide peaking capacity that complements increasing renewable wind generation which has no cooling water requirement. However, water

  5. Generators, Relations and Symmetries in Pairs of 3x3 Unimodular Matrices

    OpenAIRE

    Lawton, Sean

    2006-01-01

    Denote the free group on two letters by F2 and the SL(3,C)-representation variety of F2 by R = Hom(F2, SL(3,C)). There is a SL(3,C)-action on the coordinate ring of R, and the geometric points of the subring of invariants is an affine variety X. We determine explicit minimal generators and defining relations for the subring of invariants and show X is a degree 6 hyper-surface in C9 mapping onto C8. Our choice of generators exhibit Out(F2) symmetries which allow for a succinct expression of th...

  6. Neural markers of age-related reserve and decline in visual processing speed and visual short-term memory capacity

    DEFF Research Database (Denmark)

    Wiegand, Iris

    2013-01-01

    Attentional performance is assumed to be a major source of general cognitive abilities in older age. The present study aimed at identifying neural markers of preserved and declined basic visual attention functions in aging individuals. For groups of younger and older adults, we modeled general ca...

  7. Effects of the BDNF Val66Met polymorphism and met allele load on declarative memory related neural networks

    DEFF Research Database (Denmark)

    Dodds, Chris M; Henson, Richard N; Suckling, John

    2013-01-01

    It has been suggested that the BDNF Val66Met polymorphism modulates episodic memory performance via effects on hippocampal neural circuitry. However, fMRI studies have yielded inconsistent results in this respect. Moreover, very few studies have examined the effect of met allele load on activatio...

  8. Generation of H1 PAX6WT/EGFP reporter cells to purify PAX6 positive neural stem/progenitor cells.

    Science.gov (United States)

    Wu, Wei; Liu, Juli; Su, Zhenghui; Li, Zhonghao; Ma, Ning; Huang, Ke; Zhou, Tiancheng; Wang, Linli

    2018-08-25

    Neural conversion from human pluripotent cells (hPSCs) is a potential therapy to neurological disease in the future. However, this is still limited by efficiency and stability of existed protocols used for neural induction from hPSCs. To overcome this obstacle, we developed a reporter system to screen PAX6 + neural progenitor/stem cells using transcription activator like effector nuclease (TALEN). We found that knock-in 2 A-EGFP cassette into PAX6 exon of human embryonic stem cells H1 with TALEN-based homology recombination could establish PAX6 WT/EGFP H1 reporter cell line fast and efficiently. This reporter cell line could differentiate into PAX6 and EGFP double positive neural progenitor/stem cells (NPCs/NSCs) after neural induction. Those PAX6 WT/EGFP NPCs could be purified, expanded and specified to post-mitotic neurons in vitro efficiently. With this reporter cell line, we also screened out 1 NPC-specific microRNA, hsa-miR-99a-5p, and 3 ESCs-enriched miRNAs, hsa-miR-302c-5p, hsa-miR-512-3p and hsa-miR-518 b. In conclusion, the TALEN-based neural stem cell screening system is safe and efficient and could help researcher to acquire adequate and pure neural progenitor cells for further application. Copyright © 2018 Elsevier Inc. All rights reserved.

  9. Neural plasticity and its initiating conditions in tinnitus.

    Science.gov (United States)

    Roberts, L E

    2018-03-01

    Deafferentation caused by cochlear pathology (which can be hidden from the audiogram) activates forms of neural plasticity in auditory pathways, generating tinnitus and its associated conditions including hyperacusis. This article discusses tinnitus mechanisms and suggests how these mechanisms may relate to those involved in normal auditory information processing. Research findings from animal models of tinnitus and from electromagnetic imaging of tinnitus patients are reviewed which pertain to the role of deafferentation and neural plasticity in tinnitus and hyperacusis. Auditory neurons compensate for deafferentation by increasing their input/output functions (gain) at multiple levels of the auditory system. Forms of homeostatic plasticity are believed to be responsible for this neural change, which increases the spontaneous and driven activity of neurons in central auditory structures in animals expressing behavioral evidence of tinnitus. Another tinnitus correlate, increased neural synchrony among the affected neurons, is forged by spike-timing-dependent neural plasticity in auditory pathways. Slow oscillations generated by bursting thalamic neurons verified in tinnitus animals appear to modulate neural plasticity in the cortex, integrating tinnitus neural activity with information in brain regions supporting memory, emotion, and consciousness which exhibit increased metabolic activity in tinnitus patients. The latter process may be induced by transient auditory events in normal processing but it persists in tinnitus, driven by phantom signals from the auditory pathway. Several tinnitus therapies attempt to suppress tinnitus through plasticity, but repeated sessions will likely be needed to prevent tinnitus activity from returning owing to deafferentation as its initiating condition.

  10. Characteristics of Helicopter-Generated and Volcano-Related Seismic Tremor Signals

    Science.gov (United States)

    Eibl, Eva P. S.; Lokmer, Ivan; Bean, Christopher J.; Akerlie, Eggert; Vogfjörd, Kristin S.

    2017-04-01

    In volcanic environments it is crucial to distinguish between man-made seismic signals and signals created by the volcano. We compare volcanic, seismic signals with helicopter generated, seismic signals recorded in the last 2.5 years in Iceland. In both cases a long-lasting, emergent seismic signal, that can be referred to as seismic tremor, was generated. In the case of a helicopter, the rotating blades generate pressure pulses that travel through the air and excite Rayleigh waves at up to 40 km distance depending on wind speed, wind direction and topographic features. The longest helicopter related seismic signal we recorded was at the order of 40 minutes long. The tremor usually has a fundamental frequency of more than 10 Hz and overtones at integers of the fundamental frequency. Changes in distance lead to either increases or decreases of the frequency due to the Doppler Effect and are strongest for small source-receiver distances. The volcanic tremor signal was recorded during the Bardarbunga eruption at Holuhraun in 2014/15. For volcano-related seismic signals it is usually more difficult to determine the source process that generated the tremor. The pre-eruptive tremor persists for 2 weeks, while the co-eruptive tremor lasted for 6 months. We observed no frequency changes, most energy between 1 and 2 Hz and no or very little energy above 5 Hz. We compare the different characteristics of helicopter-related and volcano-related seismic signals and discuss how they can be distinguished. In addition we discuss how we can determine if a frequency change is related to a moving source or change in repeat time or a change in the geometry of the resonating body.

  11. Workplace-related generational characteristics of nurses: A mixed-method systematic review.

    Science.gov (United States)

    Stevanin, Simone; Palese, Alvisa; Bressan, Valentina; Vehviläinen-Julkunen, Katri; Kvist, Tarja

    2018-06-01

    The aim of this study was to describe and summarize workplace characteristics of three nursing generations: Baby Boomers, Generations X and Y. Generational differences affect occupational well-being, nurses' performance, patient outcomes and safety; therefore, nurse managers, administrators and educators are interested increasingly in making evidence-based decisions about the multigenerational nursing workforce. Mixed-method systematic review. Medline, CINAHL, PsycINFO and Scopus (January 1991-January 2017). (1) The Joanna Briggs Institute's method for conducting mixed-method systematic reviews; (2) the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and (3) the Enhancing Transparency in Reporting the Synthesis of Qualitative Research guidelines. The studies' methodological quality was assessed with the Mixed-Methods Appraisal Tool. Quantitative and mixed-method studies were transformed into qualitative methods using a convergent qualitative synthesis and qualitative findings were combined with a narrative synthesis. Thirty-three studies were included with three main themes and 11 subthemes: (1) Job attitudes (work engagement; turnover intentions, reasons for leaving; reasons, incentives/disincentives to continue nursing); (2) Emotion-related job aspects (stress/resilience; well-being/job satisfaction; affective commitment; unit climate; work ethic) and (3) Practice and leadership-related aspects (autonomy; perceived competence; leadership relationships and perceptions). Baby Boomers reported lower levels of stress and burnout than did Generations X and Y, different work engagement, factors affecting workplace well-being and retention and greater intention to leave compared with Generation Y, which was less resilient, but more cohesive. Although several studies reported methodological limitations and conflicting findings, generational differences in nurses' job attitudes, emotional, practice and leadership factors should be considered to enhance

  12. A Mediator Role of Perceived Organizational Support in Workplace Deviance Behaviors, Organizational Citizenship and Job Satisfaction Relations: A Survey Conducted With Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Kürşad Zorlu

    2016-01-01

    Full Text Available The aim of the research is to estimate the effect of workplace deviance behavior on organizational citizenship and job satisfaction and to put forward the mediator role of the organizational support perception in possible relations. The information based on hypothetical and literature are provided in the research principally and then the research part including the questionnaire applied to the employees of Kirsehir Municipality is presented. The validity and reliability tests have been performed successfully and the artificial neural network method has been used as the analysis method. In parallel with the averages and correlation values of the variables in the analysis the Artificial Neural Networks have been modelled by determining the inputs and outputs. In accordance with the findings obtained the workplace deviance behavior has a negative impact on the organizational citizenship and job satisfaction and the organizational support perception can take the mediator role as a relative for eliminating the abovementioned effect. When the artificial neural networks’ being used as the analysis method and the difficulties in measuring the workplace deviance behavior are taken into consideration it can be stated that the findings obtained have at a certain level of originality in terms of management discipline.

  13. A Mediator Role of Perceived Organizational Support in Workplace Deviance Behaviors, Organizational Citizenship and Job Satisfaction Relations: A Survey Conducted With Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Kursad Zorlu

    2014-07-01

    Full Text Available The aim of the research is to estimate the effect of workplace deviance behavior on organizational citizenship and job satisfaction and to put forward the mediator role of the organizational support perception in possible relations. The information based on hypothetical and literature are provided in the research principally and then the research part including the questionnaire applied to the employees of Kirsehir Municipality is presented. The validity and reliability tests have been performed successfully and the artificial neural network method has been used as the analysis method. In parallel with the averages and correlation values of the variables in the analysis the Artificial Neural Networks have been modelled by determining the inputs and outputs. In accordance with the findings obtained the workplace deviance behavior has a negative impact on the organizational citizenship and job satisfaction and the organizational support perception can take the mediator role as a relative for eliminating the abovementioned effect. When the artificial neural networks’ being used as the analysis method and the difficulties in measuring the workplace deviance behavior are taken into consideration it can be stated that the findings obtained have at a certain level of originality in terms of management discipline.

  14. Can older adults resist the positivity effect in neural responding? The impact of verbal framing on event-related brain potentials elicited by emotional images.

    Science.gov (United States)

    Rehmert, Andrea E; Kisley, Michael A

    2013-10-01

    Older adults have demonstrated an avoidance of negative information, presumably with a goal of greater emotional satisfaction. Understanding whether avoidance of negative information is a voluntary, motivated choice or an involuntary, automatic response will be important to differentiate, as decision making often involves emotional factors. With the use of an emotional framing event-related potential (ERP) paradigm, the present study investigated whether older adults could alter neural responses to negative stimuli through verbal reframing of evaluative response options. The late positive potential (LPP) response of 50 older adults and 50 younger adults was recorded while participants categorized emotional images in one of two framing conditions: positive ("more or less positive") or negative ("more or less negative"). It was hypothesized that older adults would be able to overcome a presumed tendency to down-regulate neural responding to negative stimuli in the negative framing condition, thus leading to larger LPP wave amplitudes to negative images. A similar effect was predicted for younger adults, but for positively valenced images, such that LPP responses would be increased in the positive framing condition compared with the negative framing condition. Overall, younger adults' LPP wave amplitudes were modulated by framing condition, including a reduction in the negativity bias in the positive frame. Older adults' neural responses were not significantly modulated, even though task-related behavior supported the notion that older adults were able to successfully adopt the negative framing condition.

  15. Can Older Adults Resist the Positivity Effect in Neural Responding: The Impact of Verbal Framing on Event-Related Brain Potentials Elicited by Emotional Images

    Science.gov (United States)

    Rehmert, Andrea E.; Kisley, Michael A.

    2014-01-01

    Older adults have demonstrated an avoidance of negative information presumably with a goal of greater emotional satisfaction. Understanding whether avoidance of negative information is a voluntary, motivated choice, or an involuntary, automatic response will be important to differentiate, as decision-making often involves emotional factors. With the use of an emotional framing event-related potential (ERP) paradigm, the present study investigated whether older adults could alter neural responses to negative stimuli through verbal reframing of evaluative response options. The late-positive potential (LPP) response of 50 older adults and 50 younger adults was recorded while participants categorized emotional images in one of two framing conditions: positive (“more or less positive”) or negative (“more or less negative”). It was hypothesized that older adults would be able to overcome a presumed tendency to down-regulate neural responding to negative stimuli in the negative framing condition thus leading to larger LPP wave amplitudes to negative images. A similar effect was predicted for younger adults but for positively valenced images such that LPP responses would be increased in the positive framing condition compared to the negative framing condition. Overall, younger adults' LPP wave amplitudes were modulated by framing condition, including a reduction in the negativity bias in the positive frame. Older adults' neural responses were not significantly modulated even though task-related behavior supported the notion that older adults were able to successfully adopt the negative framing condition. PMID:23731435

  16. Dynamics of neural cryptography.

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

    2007-05-01

    Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible.

  17. Dynamics of neural cryptography

    International Nuclear Information System (INIS)

    Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

    2007-01-01

    Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible

  18. Dynamics of neural cryptography

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

    2007-05-01

    Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible.

  19. Two-phase strategy of neural control for planar reaching movements: II--relation to spatiotemporal characteristics of movement trajectory.

    Science.gov (United States)

    Rand, Miya K; Shimansky, Yury P

    2013-09-01

    In the companion paper utilizing a quantitative model of optimal motor coordination (Part I, Rand and Shimansky, in Exp Brain Res 225:55-73, 2013), we examined coordination between X and Y movement directions (XYC) during reaching movements performed under three prescribed speeds, two movement amplitudes, and two target sizes. The obtained results indicated that the central nervous system (CNS) utilizes a two-phase strategy, where the initial and the final phases correspond to lower and higher precision of information processing, respectively, for controlling goal-directed reach-type movements to optimize the total cost of task performance including the cost of neural computations. The present study investigates how two different well-known concepts used for describing movement performance relate to the concepts of optimal XYC and two-phase control strategy. First, it is examined to what extent XYC is equivalent to movement trajectory straightness. The data analysis results show that the variability, the movement trajectory's deviation from the straight line, increases with an increase in prescribed movement speed. In contrast, the dependence of XYC strength on movement speed is opposite (in total agreement with an assumption of task performance optimality), suggesting that XYC is a feature of much higher level of generality than trajectory straightness. Second, it is tested how well the ballistic and the corrective components described in the traditional concept of two-component model of movement performance match with the initial and the final phase of the two-phase control strategy, respectively. In fast reaching movements, the percentage of trials with secondary corrective submovement was smaller under larger-target shorter-distance conditions. In slower reaching movements, meaningful parsing was impossible due to massive fluctuations in the kinematic profile throughout the movement. Thus, the parsing points determined by the conventional submovement analysis

  20. Classification of G-protein coupled receptors based on a rich generation of convolutional neural network, N-gram transformation and multiple sequence alignments.

    Science.gov (United States)

    Li, Man; Ling, Cheng; Xu, Qi; Gao, Jingyang

    2018-02-01

    Sequence classification is crucial in predicting the function of newly discovered sequences. In recent years, the prediction of the incremental large-scale and diversity of sequences has heavily relied on the involvement of machine-learning algorithms. To improve prediction accuracy, these algorithms must confront the key challenge of extracting valuable features. In this work, we propose a feature-enhanced protein classification approach, considering the rich generation of multiple sequence alignment algorithms, N-gram probabilistic language model and the deep learning technique. The essence behind the proposed method is that if each group of sequences can be represented by one feature sequence, composed of homologous sites, there should be less loss when the sequence is rebuilt, when a more relevant sequence is added to the group. On the basis of this consideration, the prediction becomes whether a query sequence belonging to a group of sequences can be transferred to calculate the probability that the new feature sequence evolves from the original one. The proposed work focuses on the hierarchical classification of G-protein Coupled Receptors (GPCRs), which begins by extracting the feature sequences from the multiple sequence alignment results of the GPCRs sub-subfamilies. The N-gram model is then applied to construct the input vectors. Finally, these vectors are imported into a convolutional neural network to make a prediction. The experimental results elucidate that the proposed method provides significant performance improvements. The classification error rate of the proposed method is reduced by at least 4.67% (family level I) and 5.75% (family Level II), in comparison with the current state-of-the-art methods. The implementation program of the proposed work is freely available at: https://github.com/alanFchina/CNN .

  1. Multiplicative congruential generators, their lattice structure, its relation to lattice-sublattice transformations and applications in crystallography

    Science.gov (United States)

    Hornfeck, W.; Harbrecht, B.

    2009-11-01

    An analysis of certain types of multiplicative congruential generators - otherwise known for their application to the sequential generation of pseudo-random numbers - reveals their relation to lattice-sublattice transformations and the coordinate description of crystal structures.

  2. Study of dissolution precipitation phenomena related to heat generated by underground disposal

    International Nuclear Information System (INIS)

    Fabriol, R.

    1987-01-01

    This study is composed of two parts developed in two separated volumes. The first part is a bibliographical research concerning the behaviour of waste analog elements during hydrothermal alteration in active geothermal fields. The second part is an experimental and theoretical simulation of dissolution-precipitation phenomena related to heat generated in the vicinity of a nuclear waste repository located in granitic formations. This work is part of the CEC project MIRAGE on natural geological migration systems [fr

  3. Quantifying the relative contributions of divisive and subtractive feedback to rhythm generation.

    Directory of Open Access Journals (Sweden)

    Joël Tabak

    2011-04-01

    Full Text Available Biological systems are characterized by a high number of interacting components. Determining the role of each component is difficult, addressed here in the context of biological oscillations. Rhythmic behavior can result from the interplay of positive feedback that promotes bistability between high and low activity, and slow negative feedback that switches the system between the high and low activity states. Many biological oscillators include two types of negative feedback processes: divisive (decreases the gain of the positive feedback loop and subtractive (increases the input threshold that both contribute to slowly move the system between the high- and low-activity states. Can we determine the relative contribution of each type of negative feedback process to the rhythmic activity? Does one dominate? Do they control the active and silent phase equally? To answer these questions we use a neural network model with excitatory coupling, regulated by synaptic depression (divisive and cellular adaptation (subtractive feedback. We first attempt to apply standard experimental methodologies: either passive observation to correlate the variations of a variable of interest to system behavior, or deletion of a component to establish whether a component is critical for the system. We find that these two strategies can lead to contradictory conclusions, and at best their interpretive power is limited. We instead develop a computational measure of the contribution of a process, by evaluating the sensitivity of the active (high activity and silent (low activity phase durations to the time constant of the process. The measure shows that both processes control the active phase, in proportion to their speed and relative weight. However, only the subtractive process plays a major role in setting the duration of the silent phase. This computational method can be used to analyze the role of negative feedback processes in a wide range of biological rhythms.

  4. Fatigue sensation induced by the sounds associated with mental fatigue and its related neural activities: revealed by magnetoencephalography

    OpenAIRE

    Ishii, Akira; Tanaka, Masaaki; Iwamae, Masayoshi; Kim, Chongsoo; Yamano, Emi; Watanabe, Yasuyoshi

    2013-01-01

    Background It has been proposed that an inappropriately conditioned fatigue sensation could be one cause of chronic fatigue. Although classical conditioning of the fatigue sensation has been reported in rats, there have been no reports in humans. Our aim was to examine whether classical conditioning of the mental fatigue sensation can take place in humans and to clarify the neural mechanisms of fatigue sensation using magnetoencephalography (MEG). Methods Ten and 9 healthy volunteers particip...

  5. Effects of the BDNF Val66Met Polymorphism and Met Allele Load on Declarative Memory Related Neural Networks

    OpenAIRE

    Dodds, Chris M.; Henson, Richard N.; Suckling, John; Miskowiak, Kamilla W.; Ooi, Cinly; Tait, Roger; Soltesz, Fruzsina; Lawrence, Phil; Bentley, Graham; Maltby, Kay; Skeggs, Andrew; Miller, Sam R.; McHugh, Simon; Bullmore, Edward T.; Nathan, Pradeep J.

    2013-01-01

    It has been suggested that the BDNF Val66Met polymorphism modulates episodic memory performance via effects on hippocampal neural circuitry. However, fMRI studies have yielded inconsistent results in this respect. Moreover, very few studies have examined the effect of met allele load on activation of memory circuitry. In the present study, we carried out a comprehensive analysis of the effects of the BDNF polymorphism on brain responses during episodic memory encoding and retrieval, including...

  6. Revealing the neural networks associated with processing of natural social interaction and the related effects of actor-orientation and face-visibility.

    Science.gov (United States)

    Saggar, Manish; Shelly, Elizabeth Walter; Lepage, Jean-Francois; Hoeft, Fumiko; Reiss, Allan L

    2014-01-01

    Understanding the intentions and desires of those around us is vital for adapting to a dynamic social environment. In this paper, a novel event-related functional Magnetic Resonance Imaging (fMRI) paradigm with dynamic and natural stimuli (2s video clips) was developed to directly examine the neural networks associated with processing of gestures with social intent as compared to nonsocial intent. When comparing social to nonsocial gestures, increased activation in both the mentalizing (or theory of mind) and amygdala networks was found. As a secondary aim, a factor of actor-orientation was included in the paradigm to examine how the neural mechanisms differ with respect to personal engagement during a social interaction versus passively observing an interaction. Activity in the lateral occipital cortex and precentral gyrus was found sensitive to actor-orientation during social interactions. Lastly, by manipulating face-visibility we tested whether facial information alone is the primary driver of neural activation differences observed between social and nonsocial gestures. We discovered that activity in the posterior superior temporal sulcus (pSTS) and fusiform gyrus (FFG) was partially driven by observing facial expressions during social gestures. Altogether, using multiple factors associated with processing of natural social interaction, we conceptually advance our understanding of how social stimuli is processed in the brain and discuss the application of this paradigm to clinical populations where atypical social cognition is manifested as a key symptom. © 2013.

  7. Revealing the neural networks associated with processing of natural social interaction and the related effects of actor-orientation and face-visibility

    Science.gov (United States)

    Saggar, Manish; Shelly, Elizabeth Walter; Lepage, Jean-Francois; Hoeft, Fumiko; Reiss, Allan L.

    2013-01-01

    Understanding the intentions and desires of those around us is vital for adapting to a dynamic social environment. In this paper, a novel event-related functional Magnetic Resonance Imaging (fMRI) paradigm with dynamic and natural stimuli (2s video clips) was developed to directly examine the neural networks associated with processing of gestures with social intent as compared to nonsocial intent. When comparing social to nonsocial gestures, increased activation in both the mentalizing (or theory of mind) and amygdala networks were found. As a secondary aim, a factor of actor-orientation was included in the paradigm to examine how the neural mechanisms differ with respect to personal engagement during a social interaction versus passively observing an interaction. Activity in the lateral occipital cortex and precentral gyrus were found sensitive to actor-orientation during social interactions. Lastly, by manipulating face-visibility we tested whether facial information alone is the primary driver of neural activation differences observed between social and nonsocial gestures. We discovered that activity in the posterior superior temporal sulcus (pSTS) and fusiform gyrus (FFG) were partially driven by observing facial expressions during social gestures. Altogether, using multiple factors associated with processing of natural social interaction, we conceptually advance our understanding of how social stimuli is processed in the brain and discuss the application of this paradigm to clinical populations where atypical social cognition is manifested as a key symptom. PMID:24084068

  8. Awareness of the general public relations strategy for nuclear power generation in Korea

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Chano-Ok

    1989-02-01

    Ten years has passed since the first nuclear power plant was established in Korea. During the period, the total nuclear power generation capacity has increased to 5,716,000 kW, and additional two 950,000 kW plants currently under construction will start operating in 1988 and 1989, respectively. As of the end of 1987, nuclear power generation accounted for 53.1 % of the total power generated in the nation. The average utilization rate of the plants increased continuously from 46.3 % ten years ago up to 79.7 % in 1987. Public opinion polls were conducted in August and October of 1986, the year when the Chernobyl accident took place. The first survey covered 2,000 residents in urban and rural areas while the second one covered a total 1,000 nuclear-related engineers, scientists, administrative officials, businessmen, journalists and writers. The surveys have shown that 74.4 % of the general public agree on the construction of more nuclear power plants. The corresponding figure was 75 % for engineers and 50 % for journalists and writers. However, 73 % of the respondents who are for their construction did not want such a plant to be constructed near their residences. Concerning the safety of these plants, 79.5 % of the experts gave a positive reply while the corresponding figure was only 48.3 % for the general public. It is concluded that more active public relations activities are required in the future. (Nogami, K.).

  9. Awareness of the general public relations strategy for nuclear power generation in Korea

    International Nuclear Information System (INIS)

    Kim, Chano-Ok

    1989-01-01

    Ten years has passed since the first nuclear power plant was established in Korea. During the period, the total nuclear power generation capacity has increased to 5,716,000 kW, and additional two 950,000 kW plants currently under construction will start operating in 1988 and 1989, respectively. As of the end of 1987, nuclear power generation accounted for 53.1 % of the total power generated in the nation. The average utilization rate of the plants increased continuously from 46.3 % ten years ago up to 79.7 % in 1987. Public opinion polls were conducted in August and October of 1986, the year when the Chernobyl accident took place. The first survey covered 2,000 residents in urban and rural areas while the second one covered a total 1,000 nuclear-related engineers, scientists, administrative officials, businessmen, journalists and writers. The surveys have shown that 74.4 % of the general public agree on the construction of more nuclear power plants. The corresponding figure was 75 % for engineers and 50 % for journalists and writers. However, 73 % of the respondents who are for their construction did not want such a plant to be constructed near their residences. Concerning the safety of these plants, 79.5 % of the experts gave a positive reply while the corresponding figure was only 48.3 % for the general public. It is concluded that more active public relations activities are required in the future. (Nogami, K.)

  10. The Neural Correlates of Humor Creativity

    OpenAIRE

    Amir, Ori; Biederman, Irving

    2016-01-01

    Unlike passive humor appreciation, the neural correlates of real-time humor creation have been unexplored. As a case study for creativity, humor generation uniquely affords a reliable assessment of a creative product’s quality with a clear and relatively rapid beginning and end, rendering it amenable to neuroimaging that has the potential for reflecting individual differences in expertise. Professional and amateur “improv” comedians and controls viewed New Yorker cartoon drawings while being ...

  11. Surface Modeling, Grid Generation, and Related Issues in Computational Fluid Dynamic (CFD) Solutions

    Science.gov (United States)

    Choo, Yung K. (Compiler)

    1995-01-01

    The NASA Steering Committee for Surface Modeling and Grid Generation (SMAGG) sponsored a workshop on surface modeling, grid generation, and related issues in Computational Fluid Dynamics (CFD) solutions at Lewis Research Center, Cleveland, Ohio, May 9-11, 1995. The workshop provided a forum to identify industry needs, strengths, and weaknesses of the five grid technologies (patched structured, overset structured, Cartesian, unstructured, and hybrid), and to exchange thoughts about where each technology will be in 2 to 5 years. The workshop also provided opportunities for engineers and scientists to present new methods, approaches, and applications in SMAGG for CFD. This Conference Publication (CP) consists of papers on industry overview, NASA overview, five grid technologies, new methods/ approaches/applications, and software systems.

  12. In vitro generation of three-dimensional substrate-adherent embryonic stem cell-derived neural aggregates for application in animal models of neurological disorders.

    Science.gov (United States)

    Hargus, Gunnar; Cui, Yi-Fang; Dihné, Marcel; Bernreuther, Christian; Schachner, Melitta

    2012-05-01

    In vitro-differentiated embryonic stem (ES) cells comprise a useful source for cell replacement therapy, but the efficiency and safety of a translational approach are highly dependent on optimized protocols for directed differentiation of ES cells into the desired cell types in vitro. Furthermore, the transplantation of three-dimensional ES cell-derived structures instead of a single-cell suspension may improve graft survival and function by providing a beneficial microenvironment for implanted cells. To this end, we have developed a new method to efficiently differentiate mouse ES cells into neural aggregates that consist predominantly (>90%) of postmitotic neurons, neural progenitor cells, and radial glia-like cells. When transplanted into the excitotoxically lesioned striatum of adult mice, these substrate-adherent embryonic stem cell-derived neural aggregates (SENAs) showed significant advantages over transplanted single-cell suspensions of ES cell-derived neural cells, including improved survival of GABAergic neurons, increased cell migration, and significantly decreased risk of teratoma formation. Furthermore, SENAs mediated functional improvement after transplantation into animal models of Parkinson's disease and spinal cord injury. This unit describes in detail how SENAs are efficiently derived from mouse ES cells in vitro and how SENAs are isolated for transplantation. Furthermore, methods are presented for successful implantation of SENAs into animal models of Huntington's disease, Parkinson's disease, and spinal cord injury to study the effects of stem cell-derived neural aggregates in a disease context in vivo.

  13. Third generation constructivism and the rhetoric of inquiry in international relations

    OpenAIRE

    Michel, Torsten

    2016-01-01

    This article argues that third generation constructivism can make a central and overdue contribution to the practice of meta-theorising in IR. Meta-theory has so far restricted itself to exercises of observational re ection or de nitional sedimentation of content, or in Patrick Jackson’s words, to an elaboration of the ‘conduct of inquiry’. It has thereby failed, to its detriment, to re ect on and recognise the central importance of the deep and intricate relation between the content of meta-...

  14. Statistical analysis of events related to emergency diesel generators failures in the nuclear industry

    Energy Technology Data Exchange (ETDEWEB)

    Kančev, Duško, E-mail: dusko.kancev@ec.europa.eu [European Commission, DG-JRC, Institute for Energy and Transport, P.O. Box 2, NL-1755 ZG Petten (Netherlands); Duchac, Alexander; Zerger, Benoit [European Commission, DG-JRC, Institute for Energy and Transport, P.O. Box 2, NL-1755 ZG Petten (Netherlands); Maqua, Michael [Gesellschaft für Anlagen-und-Reaktorsicherheit (GRS) mbH, Schwetnergasse 1, 50667 Köln (Germany); Wattrelos, Didier [Institut de Radioprotection et de Sûreté Nucléaire (IRSN), BP 17 - 92262 Fontenay-aux-Roses Cedex (France)

    2014-07-01

    Highlights: • Analysis of operating experience related to emergency diesel generators events at NPPs. • Four abundant operating experience databases screened. • Delineating important insights and conclusions based on the operating experience. - Abstract: This paper is aimed at studying the operating experience related to emergency diesel generators (EDGs) events at nuclear power plants collected from the past 20 years. Events related to EDGs failures and/or unavailability as well as all the supporting equipment are in the focus of the analysis. The selected operating experience was analyzed in detail in order to identify the type of failures, attributes that contributed to the failure, failure modes potential or real, discuss risk relevance, summarize important lessons learned, and provide recommendations. The study in this particular paper is tightly related to the performing of statistical analysis of the operating experience. For the purpose of this study EDG failure is defined as EDG failure to function on demand (i.e. fail to start, fail to run) or during testing, or an unavailability of an EDG, except of unavailability due to regular maintenance. The Gesellschaft für Anlagen und Reaktorsicherheit mbH (GRS) and Institut de Radioprotection et de Sûreté Nucléaire (IRSN) databases as well as the operating experience contained in the IAEA/NEA International Reporting System for Operating Experience and the U.S. Licensee Event Reports were screened. The screening methodology applied for each of the four different databases is presented. Further on, analysis aimed at delineating the causes, root causes, contributing factors and consequences are performed. A statistical analysis was performed related to the chronology of events, types of failures, the operational circumstances of detection of the failure and the affected components/subsystems. The conclusions and results of the statistical analysis are discussed. The main findings concerning the testing

  15. Statistical analysis of events related to emergency diesel generators failures in the nuclear industry

    International Nuclear Information System (INIS)

    Kančev, Duško; Duchac, Alexander; Zerger, Benoit; Maqua, Michael; Wattrelos, Didier

    2014-01-01

    Highlights: • Analysis of operating experience related to emergency diesel generators events at NPPs. • Four abundant operating experience databases screened. • Delineating important insights and conclusions based on the operating experience. - Abstract: This paper is aimed at studying the operating experience related to emergency diesel generators (EDGs) events at nuclear power plants collected from the past 20 years. Events related to EDGs failures and/or unavailability as well as all the supporting equipment are in the focus of the analysis. The selected operating experience was analyzed in detail in order to identify the type of failures, attributes that contributed to the failure, failure modes potential or real, discuss risk relevance, summarize important lessons learned, and provide recommendations. The study in this particular paper is tightly related to the performing of statistical analysis of the operating experience. For the purpose of this study EDG failure is defined as EDG failure to function on demand (i.e. fail to start, fail to run) or during testing, or an unavailability of an EDG, except of unavailability due to regular maintenance. The Gesellschaft für Anlagen und Reaktorsicherheit mbH (GRS) and Institut de Radioprotection et de Sûreté Nucléaire (IRSN) databases as well as the operating experience contained in the IAEA/NEA International Reporting System for Operating Experience and the U.S. Licensee Event Reports were screened. The screening methodology applied for each of the four different databases is presented. Further on, analysis aimed at delineating the causes, root causes, contributing factors and consequences are performed. A statistical analysis was performed related to the chronology of events, types of failures, the operational circumstances of detection of the failure and the affected components/subsystems. The conclusions and results of the statistical analysis are discussed. The main findings concerning the testing

  16. Easy and low-cost identification of metabolic syndrome in patients treated with second-generation antipsychotics: artificial neural network and logistic regression models.

    Science.gov (United States)

    Lin, Chao-Cheng; Bai, Ya-Mei; Chen, Jen-Yeu; Hwang, Tzung-Jeng; Chen, Tzu-Ting; Chiu, Hung-Wen; Li, Yu-Chuan

    2010-03-01

    Metabolic syndrome (MetS) is an important side effect of second-generation antipsychotics (SGAs). However, many SGA-treated patients with MetS remain undetected. In this study, we trained and validated artificial neural network (ANN) and multiple logistic regression models without biochemical parameters to rapidly identify MetS in patients with SGA treatment. A total of 383 patients with a diagnosis of schizophrenia or schizoaffective disorder (DSM-IV criteria) with SGA treatment for more than 6 months were investigated to determine whether they met the MetS criteria according to the International Diabetes Federation. The data for these patients were collected between March 2005 and September 2005. The input variables of ANN and logistic regression were limited to demographic and anthropometric data only. All models were trained by randomly selecting two-thirds of the patient data and were internally validated with the remaining one-third of the data. The models were then externally validated with data from 69 patients from another hospital, collected between March 2008 and June 2008. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of all models. Both the final ANN and logistic regression models had high accuracy (88.3% vs 83.6%), sensitivity (93.1% vs 86.2%), and specificity (86.9% vs 83.8%) to identify MetS in the internal validation set. The mean +/- SD AUC was high for both the ANN and logistic regression models (0.934 +/- 0.033 vs 0.922 +/- 0.035, P = .63). During external validation, high AUC was still obtained for both models. Waist circumference and diastolic blood pressure were the common variables that were left in the final ANN and logistic regression models. Our study developed accurate ANN and logistic regression models to detect MetS in patients with SGA treatment. The models are likely to provide a noninvasive tool for large-scale screening of MetS in this group of patients. (c) 2010 Physicians

  17. Comparison of multiple linear regression, partial least squares and artificial neural networks for prediction of gas chromatographic relative retention times of trimethylsilylated anabolic androgenic steroids.

    Science.gov (United States)

    Fragkaki, A G; Farmaki, E; Thomaidis, N; Tsantili-Kakoulidou, A; Angelis, Y S; Koupparis, M; Georgakopoulos, C

    2012-09-21

    The comparison among different modelling techniques, such as multiple linear regression, partial least squares and artificial neural networks, has been performed in order to construct and evaluate models for prediction of gas chromatographic relative retention times of trimethylsilylated anabolic androgenic steroids. The performance of the quantitative structure-retention relationship study, using the multiple linear regression and partial least squares techniques, has been previously conducted. In the present study, artificial neural networks models were constructed and used for the prediction of relative retention times of anabolic androgenic steroids, while their efficiency is compared with that of the models derived from the multiple linear regression and partial least squares techniques. For overall ranking of the models, a novel procedure [Trends Anal. Chem. 29 (2010) 101-109] based on sum of ranking differences was applied, which permits the best model to be selected. The suggested models are considered useful for the estimation of relative retention times of designer steroids for which no analytical data are available. Copyright © 2012 Elsevier B.V. All rights reserved.

  18. The relative impact of sizing errors on steam generator tube failure probability

    International Nuclear Information System (INIS)

    Cizelj, L.; Dvorsek, T.

    1998-01-01

    The Outside Diameter Stress Corrosion Cracking (ODSCC) at tube support plates is currently the major degradation mechanism affecting the steam generator tubes made of Inconel 600. This caused development and licensing of degradation specific maintenance approaches, which addressed two main failure modes of the degraded piping: tube rupture; and excessive leakage through degraded tubes. A methodology aiming at assessing the efficiency of a given set of possible maintenance approaches has already been proposed by the authors. It pointed out better performance of the degradation specific over generic approaches in (1) lower probability of single and multiple steam generator tube rupture (SGTR), (2) lower estimated accidental leak rates and (3) less tubes plugged. A sensitivity analysis was also performed pointing out the relative contributions of uncertain input parameters to the tube rupture probabilities. The dominant contribution was assigned to the uncertainties inherent to the regression models used to correlate the defect size and tube burst pressure. The uncertainties, which can be estimated from the in-service inspections, are further analysed in this paper. The defect growth was found to have significant and to some extent unrealistic impact on the probability of single tube rupture. Since the defect growth estimates were based on the past inspection records they strongly depend on the sizing errors. Therefore, an attempt was made to filter out the sizing errors and to arrive at more realistic estimates of the defect growth. The impact of different assumptions regarding sizing errors on the tube rupture probability was studied using a realistic numerical example. The data used is obtained from a series of inspection results from Krsko NPP with 2 Westinghouse D-4 steam generators. The results obtained are considered useful in safety assessment and maintenance of affected steam generators. (author)

  19. The neural substrates of cognitive flexibility are related to individual differences in preschool irritability: A fNIRS investigation

    Directory of Open Access Journals (Sweden)

    Yanwei Li

    2017-06-01

    Full Text Available Preschool (age 3–5 is a phase of rapid development in both cognition and emotion, making this a period in which the neurodevelopment of each domain is particularly sensitive to that of the other. During this period, children rapidly learn how to flexibly shift their attention between competing demands and, at the same time, acquire critical emotion regulation skills to respond to negative affective challenges. The integration of cognitive flexibility and individual differences in irritability may be an important developmental process of early childhood maturation. However, at present it is unclear if they share common neural substrates in early childhood. Our main goal was to examine the neural correlates of cognitive flexibility in preschool children and test for associations with irritability. Forty-six preschool aged children completed a novel, child-appropriate, Stroop task while dorsolateral prefrontal cortex (DLPFC activation was recorded using functional Near Infrared Spectroscopy (fNIRS. Parents rated their child’s irritability. Results indicated that left DLPFC activation was associated with cognitive flexibility and positively correlated with irritability. Right DLPFC activation was also positively correlated with irritability. Results suggest the entwined nature of cognitive and emotional neurodevelopment during a developmental period of rapid and mutual acceleration.

  20. A Neural Circuit Mechanism for the Involvements of Dopamine in Effort-Related Choices: Decay of Learned Values, Secondary Effects of Depletion, and Calculation of Temporal Difference Error

    Science.gov (United States)

    2018-01-01

    Abstract Dopamine has been suggested to be crucially involved in effort-related choices. Key findings are that dopamine depletion (i) changed preference for a high-cost, large-reward option to a low-cost, small-reward option, (ii) but not when the large-reward option was also low-cost or the small-reward option gave no reward, (iii) while increasing the latency in all the cases but only transiently, and (iv) that antagonism of either dopamine D1 or D2 receptors also specifically impaired selection of the high-cost, large-reward option. The underlying neural circuit mechanisms remain unclear. Here we show that findings i–iii can be explained by the dopaminergic representation of temporal-difference reward-prediction error (TD-RPE), whose mechanisms have now become clarified, if (1) the synaptic strengths storing the values of actions mildly decay in time and (2) the obtained-reward-representing excitatory input to dopamine neurons increases after dopamine depletion. The former is potentially caused by background neural activity–induced weak synaptic plasticity, and the latter is assumed to occur through post-depletion increase of neural activity in the pedunculopontine nucleus, where neurons representing obtained reward exist and presumably send excitatory projections to dopamine neurons. We further show that finding iv, which is nontrivial given the suggested distinct functions of the D1 and D2 corticostriatal pathways, can also be explained if we additionally assume a proposed mechanism of TD-RPE calculation, in which the D1 and D2 pathways encode the values of actions with a temporal difference. These results suggest a possible circuit mechanism for the involvements of dopamine in effort-related choices and, simultaneously, provide implications for the mechanisms of TD-RPE calculation. PMID:29468191

  1. The neural mechanisms of semantic and response conflicts: an fMRI study of practice-related effects in the Stroop task.

    Science.gov (United States)

    Chen, Zhencai; Lei, Xu; Ding, Cody; Li, Hong; Chen, Antao

    2013-02-01

    Previous studies have demonstrated that there are separate neural mechanisms underlying semantic and response conflicts in the Stroop task. However, the practice effects of these conflicts need to be elucidated and the possible involvements of common neural mechanisms are yet to be established. We employed functional magnetic resonance imaging (fMRI) in a 4-2 mapping practice-related Stroop task to determine the neural substrates under these conflicts. Results showed that different patterns of brain activations are associated with practice in the attentional networks (e.g., dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC), and posterior parietal cortex (PPC)) for both conflicts, response control regions (e.g., inferior frontal junction (IFJ), inferior frontal gyrus (IFG)/insula, and pre-supplementary motor areas (pre-SMA)) for semantic conflict, and posterior cortex for response conflict. We also found areas of common activation in the left hemisphere within the attentional networks, for the early practice stage in semantic conflict and the late stage in "pure" response conflict using conjunction analysis. The different practice effects indicate that there are distinct mechanisms underlying these two conflict types: semantic conflict practice effects are attributable to the automation of stimulus processing, conflict and response control; response conflict practice effects are attributable to the proportional increase of conflict-related cognitive resources. In addition, the areas of common activation suggest that the semantic conflict effect may contain a partial response conflict effect, particularly at the beginning of the task. These findings indicate that there are two kinds of response conflicts contained in the key-pressing Stroop task: the vocal-level (mainly in the early stage) and key-pressing (mainly in the late stage) response conflicts; thus, the use of the subtraction method for the exploration of semantic and response conflicts

  2. Health-related quality of life of infants from ethnic minority groups: the Generation R Study.

    Science.gov (United States)

    Flink, Ilse J E; Beirens, Tinneke M J; Looman, Caspar; Landgraf, Jeanne M; Tiemeier, Henning; Mol, Henriette A; Jaddoe, Vincent W V; Hofman, Albert; Mackenbach, Johan P; Raat, Hein

    2013-04-01

    To assess whether the health-related quality of life of infants from ethnic minority groups differs from the health-related quality of life of native Dutch infants and to evaluate whether infant health and family characteristics explain the potential differences. We included 4,506 infants participating in the Generation R Study, a longitudinal birth cohort. When the child was 12 months, parents completed the Infant Toddler Quality of Life Questionnaire (ITQOL); ITQOL scale scores in each ethnic subgroup were compared with scores in the Dutch reference population. Influence of infant health and family characteristics on ITQOL scale scores were evaluated using multivariate regression models. Infants from ethnic minority groups presented significantly lower ITQOL scale scores compared to the Dutch subgroup (e.g., Temperament and Moods scale: median score of Turkish subgroup, 70.8 (IQR, 15.3); median score of Dutch subgroup, 80.6 (IQR, 13.9; P ethnic minority status and infant health-related quality of life. However, these factors could not fully explain all the differences in the ITQOL scale scores. Parent-reported health-related quality of life is lower in infants from ethnic minority groups compared to native Dutch infants, which could partly be explained by infant health and by family characteristics.

  3. Using affective knowledge to generate and validate a set of emotion-related, action words

    Directory of Open Access Journals (Sweden)

    Emma Portch

    2015-07-01

    Full Text Available Emotion concepts are built through situated experience. Abstract word meaning is grounded in this affective knowledge, giving words the potential to evoke emotional feelings and reactions (e.g., Vigliocco et al., 2009. In the present work we explore whether words differ in the extent to which they evoke ‘specific’ emotional knowledge. Using a categorical approach, in which an affective ‘context’ is created, it is possible to assess whether words proportionally activate knowledge relevant to different emotional states (e.g., ‘sadness’, ‘anger’, Stevenson, Mikels & James, 2007a. We argue that this method may be particularly effective when assessing the emotional meaning of action words (e.g., Schacht & Sommer, 2009. In study 1 we use a constrained feature generation task to derive a set of action words that participants associated with six, basic emotional states (see full list in Appendix S1. Generation frequencies were taken to indicate the likelihood that the word would evoke emotional knowledge relevant to the state to which it had been paired. In study 2 a rating task was used to assess the strength of association between the six most frequently generated, or ‘typical’, action words and corresponding emotion labels. Participants were presented with a series of sentences, in which action words (typical and atypical and labels were paired e.g., “If you are feeling ‘sad’ how likely would you be to act in the following way?” … ‘cry.’ Findings suggest that typical associations were robust. Participants always gave higher ratings to typical vs. atypical action word and label pairings, even when (a rating direction was manipulated (the label or verb appeared first in the sentence, and (b the typical behaviours were to be performed by the rater themselves, or others. Our findings suggest that emotion-related action words vary in the extent to which they evoke knowledge relevant for different emotional states. When

  4. Using affective knowledge to generate and validate a set of emotion-related, action words.

    Science.gov (United States)

    Portch, Emma; Havelka, Jelena; Brown, Charity; Giner-Sorolla, Roger

    2015-01-01

    Emotion concepts are built through situated experience. Abstract word meaning is grounded in this affective knowledge, giving words the potential to evoke emotional feelings and reactions (e.g., Vigliocco et al., 2009). In the present work we explore whether words differ in the extent to which they evoke 'specific' emotional knowledge. Using a categorical approach, in which an affective 'context' is created, it is possible to assess whether words proportionally activate knowledge relevant to different emotional states (e.g., 'sadness', 'anger', Stevenson, Mikels & James, 2007a). We argue that this method may be particularly effective when assessing the emotional meaning of action words (e.g., Schacht & Sommer, 2009). In study 1 we use a constrained feature generation task to derive a set of action words that participants associated with six, basic emotional states (see full list in Appendix S1). Generation frequencies were taken to indicate the likelihood that the word would evoke emotional knowledge relevant to the state to which it had been paired. In study 2 a rating task was used to assess the strength of association between the six most frequently generated, or 'typical', action words and corresponding emotion labels. Participants were presented with a series of sentences, in which action words (typical and atypical) and labels were paired e.g., "If you are feeling 'sad' how likely would you be to act in the following way?" … 'cry.' Findings suggest that typical associations were robust. Participants always gave higher ratings to typical vs. atypical action word and label pairings, even when (a) rating direction was manipulated (the label or verb appeared first in the sentence), and (b) the typical behaviours were to be performed by the rater themselves, or others. Our findings suggest that emotion-related action words vary in the extent to which they evoke knowledge relevant for different emotional states. When measuring affective grounding, it may then be

  5. Neural correlates of face and object perception in an awake chimpanzee (Pan troglodytes examined by scalp-surface event-related potentials.

    Directory of Open Access Journals (Sweden)

    Hirokata Fukushima

    Full Text Available BACKGROUND: The neural system of our closest living relative, the chimpanzee, is a topic of increasing research interest. However, electrophysiological examinations of neural activity during visual processing in awake chimpanzees are currently lacking. METHODOLOGY/PRINCIPAL FINDINGS: In the present report, skin-surface event-related brain potentials (ERPs were measured while a fully awake chimpanzee observed photographs of faces and objects in two experiments. In Experiment 1, human faces and stimuli composed of scrambled face images were displayed. In Experiment 2, three types of pictures (faces, flowers, and cars were presented. The waveforms evoked by face stimuli were distinguished from other stimulus types, as reflected by an enhanced early positivity appearing before 200 ms post stimulus, and an enhanced late negativity after 200 ms, around posterior and occipito-temporal sites. Face-sensitive activity was clearly observed in both experiments. However, in contrast to the robustly observed face-evoked N170 component in humans, we found that faces did not elicit a peak in the latency range of 150-200 ms in either experiment. CONCLUSIONS/SIGNIFICANCE: Although this pilot study examined a single subject and requires further examination, the observed scalp voltage patterns suggest that selective processing of faces in the chimpanzee brain can be detected by recording surface ERPs. In addition, this non-invasive method for examining an awake chimpanzee can be used to extend our knowledge of the characteristics of visual cognition in other primate species.

  6. Higher serum cholesterol is associated with intensified age-related neural network decoupling and cognitive decline in early- to mid-life.

    Science.gov (United States)

    Spielberg, Jeffrey M; Sadeh, Naomi; Leritz, Elizabeth C; McGlinchey, Regina E; Milberg, William P; Hayes, Jasmeet P; Salat, David H

    2017-06-01

    Mounting evidence indicates that serum cholesterol and other risk factors for cardiovascular disease intensify normative trajectories of age-related cognitive decline. However, the neural mechanisms by which this occurs remain largely unknown. To understand the impact of cholesterol on brain networks, we applied graph theory to resting-state fMRI in a large sample of early- to mid-life Veterans (N = 206, Mean age  = 32). A network emerged (centered on the banks of the superior temporal sulcus) that evidenced age-related decoupling (i.e., decreased network connectivity with age), but only in participants with clinically-elevated total cholesterol (≥180 mg/dL). Crucially, decoupling in this network corresponded to greater day-to-day disability and mediated age-related declines in psychomotor speed. Finally, examination of network organization revealed a pattern of age-related dedifferentiation for the banks of the superior temporal sulcus, again present only with higher cholesterol. More specifically, age was related to decreasing within-module communication (indexed by Within-Module Degree Z-Score) and increasing between-module communication (indexed by Participation Coefficient), but only in participants with clinically-elevated cholesterol. Follow-up analyses indicated that all findings were driven by low-density lipoprotein (LDL) levels, rather than high-density lipoprotein (HDL) or triglycerides, which is interesting as LDL levels have been linked to increased risk for cardiovascular disease, whereas HDL levels appear inversely related to such disease. These findings provide novel insight into the deleterious effects of cholesterol on brain health and suggest that cholesterol accelerates the impact of age on neural trajectories by disrupting connectivity in circuits implicated in integrative processes and behavioral control. Hum Brain Mapp 38:3249-3261, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  7. Effect of task complexity on intelligence and neural efficiency in children: an event-related potential study.

    Science.gov (United States)

    Zhang, Qiong; Shi, Jiannong; Luo, Yuejia; Liu, Sainan; Yang, Jie; Shen, Mowei

    2007-10-08

    The present study investigates the effects of task complexity, intelligence and neural efficiency on children's performance on an Elementary Cognitive Task. Twenty-three children were divided into two groups on the basis of their Raven Progressive Matrix scores and were then asked to complete a choice reaction task with two test conditions. We recorded the electroencephalogram and calculated the peak latencies and amplitudes for anteriorly distributed P225, N380 and late positive component. Our results suggested shorter late positive component latencies in brighter children, possibly reflecting a higher processing speed in these individuals. Increased P225 amplitude and increased N380 amplitudes for brighter children may indicate a more efficient allocation of attention for brighter children. No moderating effect of task complexity on brain-intelligence relationship was found.

  8. Impact of BDNF Val66Met and 5-HTTLPR polymorphism variants on neural substrates related to sadness and executive function.

    Science.gov (United States)

    Wang, L; Ashley-Koch, A; Steffens, D C; Krishnan, K R R; Taylor, W D

    2012-04-01

    The brain-derived neurotrophic factor (BDNF) Val(66) Met allelic variation is linked to both the occurrence of mood disorders and antidepressant response. These findings are not universally observed, and the mechanism by which this variation results in increased risk for mood disorders is unclear. One possible explanation is an epistatic relationship with other neurotransmitter genes associated with depression risk, such as the serotonin-transporter-linked promotor region (5-HTTLPR). Further, it is unclear how the coexistence of the BDNF Met and 5-HTTLPR S variants affects the function of the affective and cognitive control systems. To address this question, we conducted a functional magnetic resonance imaging (fMRI) study in 38 older adults (20 healthy and 18 remitted from major depressive disorder). Subjects performed an emotional oddball task during the fMRI scan and provided blood samples for genotyping. Our analyses examined the relationship between genotypes and brain activation to sad distractors and attentional targets. We found that 5-HTTLPR S allele carriers exhibited stronger activation in the amygdala in response to sad distractors, whereas BDNF Met carriers exhibited increased activation to sad stimuli but decreased activation to attentional targets in the dorsolateral prefrontal and dorsomedial prefrontal cortices. In addition, subjects with both the S allele and Met allele genes exhibited increased activation to sad stimuli in the subgenual cingulate and posterior cingulate. Our results indicate that the Met allele alone or in combination with 5-HTTLPR S allele may increase reactivity to sad stimuli, which might represent a neural mechanism underlying increased depression vulnerability. © 2012 The Authors. Genes, Brain and Behavior © 2012 Blackwell Publishing Ltd and International Behavioural and Neural Genetics Society.

  9. [Neural activity related to emotional and empathic deficits in subjects with post-traumatic stress disorder who survived the L'Aquila (Central Italy) 2009 earthquake].

    Science.gov (United States)

    Mazza, Monica; Pino, Maria Chiara; Tempesta, Daniela; Catalucci, Alessia; Masciocchi, Carlo; Ferrara, Michele

    2016-01-01

    Post-Traumatic Stress Disorder (PTSD) is a chronic anxiety disorder. The continued efforts to control the distressing memories by traumatized individuals, together with the reduction of responsiveness to the outside world, are called Emotional Numbing (EN). The EN is one of the central symptoms in PTSD and it plays an integral role not only in the development and maintenance of post-traumatic symptomatology, but also in the disability of emotional regulation. This disorder shows an abnormal response of cortical and limbic regions which are normally involved in understanding emotions since the very earliest stages of the development of processing ability. Patients with PTSD exhibit exaggerated brain responses to emotionally negative stimuli. Identifying the neural correlates of emotion regulation in these subjects is important for elucidating the neural circuitry involved in emotional and empathic dysfunction. We showed that PTSD patients, all survivors of the L'Aquila 2009 earthquake, have a higher sensitivity to negative emotion and lower empathy levels. These emotional and empathic deficits are accompanied by neural brain functional correlates. Indeed PTSD subjects exhibit functional abnormalities in brain regions that are involved in stress regulation and emotional responses. The reduced activation of the frontal areas and a stronger activation of the limbic areas when responding to emotional stimuli could lead the subjects to enact coping strategies aimed at protecting themselves from the re-experience of pain related to traumatic events. This would result in a dysfunctional hyperactivation of subcortical areas, which may cause emotional distress and, consequently, impaired social relationships often reported by PTSD patients.

  10. AGE RELATED DEGRADATION OF STEAM GENERATOR INTERNALS BASED ON INDUSTRY RESPONSES TO GENERIC LETTER 97-06

    International Nuclear Information System (INIS)

    SUBUDHI, M.; SULLIVAN, JR. E.J.

    2002-01-01

    THIS PAPER PRESENTS THE RESULTS OF AN AGING ASSESSMENT OF THE NUCLEAR POWER INDUSTRY RESPONSES TO NRC GENERIC LETTER 97-06 ON THE DEGRADATION OF STEAM GENERATOR INTERNALS EXPERIENCED AT ELECTRICITE DE FRANCE (EDF) PLANTS IN FRANCE AND AT A UNITED STATES PRESSURIZED WATER REACTOR (PWR). WESTINGHOUSE (W), COMBUSTION ENGINEERING (CE), AND BABCOCK AND WILCOX (BW) STEAM GENERATOR MODELS, CURRENTLY IN SERVICE AT U.S. NUCLEAR POWER PLANTS, POTENTIALLY COULD EXPERIENCE DEGRADATION SIMILAR TO THATFOUND AT EDF PLANTS AND THE U.S. PLANT. THE STEAM GENERATORS IN MANY OF THE U.S. PWRS HAVE BEEN REPLACED WITH STEAM GENERATORS WITH STEAM GENERATORS WITH IMPROVED DESIGNS AND MATERIALS. THESE REPLACEMENT STEAM GENERATORS HAVE BEEN MANUFACTURED IN THE U.S. AND ABROAD. DURING THIS ASSESSMENT, EACH OF THE THREE OWNERS GROUPS (W,CE, AND BW) IDENTIFIED FOR ITS STEAM GENERATOR, MODELS ALL THE POTENTIAL INTERNAL COMPONENTS THAT ARE VULNERABLE TO DEGRADATION WHILE IN SERVICE. EACH OWNERS GROUPDEVELOPED INSPEC TION AND MONITORING GUIDANCE AND RECOMMENDATIONS FOR ITS PARTICULAR STEAM GENERATOR MODELS. THE NUCLEAR ENERGY INSTITUTE INCORPORATED IN NEI 97-06 STEAM GENERATOR PROGRAM GUIDELINES, A REQUIREMENT TO MONITOR SECONDARY SIDE STEAM GENERATOR COMPONENTS IF THEIR FAILURE COULD PREVENT THE STEAM GENERATOR FROM FULFILLING ITS INTENDED SAFETY-RELATED FUNCTION. LICENSEES INDICATED THAT THEY IMPLEMENTED OR PLANNED TO IMPLEMENT, AS APPROPRIATE FOR THEIR STEAM GENERATORS, THEIR OWNERS GROUPRECOMMENDATIONS TO ADDRESS THE LONG-TERM EFFECTS OF THE POTENTIAL DEGRADATION MECHANISMS ASSOCIATED WITH THE STEAM GENERATOR INTERNALS

  11. A Trial Intercomparison of Humidity Generators at Extremes of Range Using Relative Humidity Transmitters

    Science.gov (United States)

    Stevens, M.; Benyon, R.; Bell, S. A.; Vicente, T.

    2008-10-01

    In order to effectively implement the Mutual Recognition Arrangement (MRA) of the International Committee for Weights and Measures (CIPM), national metrology institutes (NMIs) are required to support their claims of calibration and measurement capability (CMC) with a quality system compliant with ISO/IEC 17025, and with suitable evidence of participation in key or supplementary comparisons. The CMC review process, both at regional and inter-regional levels, uses criteria that combine the provisions mentioned above, together with additional evidence demonstrating scientific and technical competence of the institutes. For dew-point temperatures, there are key comparisons in progress under the Consultative Committee for Thermometry (CCT) and under the European regional metrology organisation (EUROMET), together with information available on past regional supplementary comparisons. However, for relative humidity there are, to date, no such comparisons available to support CMC entries. This paper presents and discusses the results of a preliminary investigation of the use of relative humidity and temperature transmitters in order to determine their suitability for the intercomparison of standard humidity generators in support of CMC claims for the calibration of relative humidity instruments. The results of a recent bilateral comparison between 2 NMIs at the extremes of the range up to 98%rh at 70 °C, and down to 1%rh at -40 °C are reported. Specific precautions and recommendations on the use of the devices as transfer standards are presented.

  12. Education and public relations in nuclear power toward the next generation in Korea

    International Nuclear Information System (INIS)

    I, Han-Joo; Seo, Doo-Han.

    1989-01-01

    The report outlines the education in nuclear engineering in colleges and universities in Korea, experiments and training in nuclear reactor operation, research project for education in peaceful utilization of nuclear power, and public relations activities and special plans intended for the new generation in the nation. Programs covering the education of students in nuclear engineering in colleges and universities in Korea, and public relations toward some selected groups and brackets have been conducted successfully, producing good results. On the other hand, some improvements in educational activities, including the revision of textbooks, are required in such a field of education of pupils in primary, middle and high schools. Specially-designed introductory courses and advanced courses in the peaceful utilization of nuclear power should be established to ensure that students in scientific or technological fields other than nuclear engineering will gain deeper understanding of the issue. For this, the preparation of textbooks are currently under way. It is hoped that public relations activities will be expanded on a more continuous and consistent basis, instead of the current intermittent basis, by making good use of the mass media to distribute information among the general public. (Nogami. K.)

  13. Evaporation Kinetics of Laboratory Generated Secondary Organic Aerosols at Elevated Relative Humidity

    Energy Technology Data Exchange (ETDEWEB)

    Wilson, Jacqueline M.; Imre, D.; Beranek, Josef; Shrivastava, ManishKumar B.; Zelenyuk, Alla

    2015-01-06

    Secondary organic aerosols (SOA) dominate atmospheric organic aerosols that affect climate, air quality, and health. Recent studies indicate that, contrary to previously held assumptions, at low relative humidity (RH) these particles are semi-solid and evaporate orders of magnitude slower than expected. Elevated relative humidity has the potential to affect significantly formation, properties, and atmospheric evolution of SOA particles. Here we present a study of the effect of RH on the room-temperature evaporation kinetics of SOA particles formed by ozonolysis of α-pinene and limonene. Experiments were carried out on SOA particles generated, evaporated, and aged at 0%, 50% and 90% RH. We find that in all cases evaporation begins with a relatively fast phase, during which 30% to 70% of the particle mass evaporates in 2 hours, followed by a much slower evaporation rate. Evaporation kinetics at 0% and 50% RH are nearly the same, while at 90% RH a slightly larger fraction evaporates. In all cases, aging the particles prior to inducing evaporation reduces the evaporative losses, with aging at elevated RH leading to more significant effect. In all cases, SOA evaporation is nearly size-independent, providing direct evidence that oligomers play a crucial role in determining the evaporation kinetics.

  14. Secondary immunization generates clonally related antigen-specific plasma cells and memory B cells.

    Science.gov (United States)

    Frölich, Daniela; Giesecke, Claudia; Mei, Henrik E; Reiter, Karin; Daridon, Capucine; Lipsky, Peter E; Dörner, Thomas

    2010-09-01

    Rechallenge with T cell-dependent Ags induces memory B cells to re-enter germinal centers (GCs) and undergo further expansion and differentiation into plasma cells (PCs) and secondary memory B cells. It is currently not known whether the expanded population of memory B cells and PCs generated in secondary GCs are clonally related, nor has the extent of proliferation and somatic hypermutation of their precursors been delineated. In this study, after secondary tetanus toxoid (TT) immunization, TT-specific PCs increased 17- to 80-fold on days 6-7, whereas TT-specific memory B cells peaked (delayed) on day 14 with a 2- to 22-fold increase. Molecular analyses of V(H)DJ(H) rearrangements of individual cells revealed no major differences of gene usage and CDR3 length between TT-specific PCs and memory B cells, and both contained extensive evidence of somatic hypermutation with a pattern consistent with GC reactions. This analysis identified clonally related TT-specific memory B cells and PCs. Within clusters of clonally related cells, sequences shared a number of mutations but also could contain additional base pair changes. The data indicate that although following secondary immunization PCs can derive from memory B cells without further somatic hypermutation, in some circumstances, likely within GC reactions, asymmetric mutation can occur. These results suggest that after the fate decision to differentiate into secondary memory B cells or PCs, some committed precursors continue to proliferate and mutate their V(H) genes.

  15. Education and public relations in nuclear power toward the next generation in Korea

    Energy Technology Data Exchange (ETDEWEB)

    I, Han-Joo; Seo, Doo-Han.

    1989-02-01

    The report outlines the education in nuclear engineering in colleges and universities in Korea, experiments and training in nuclear reactor operation, research project for education in peaceful utilization of nuclear power, and public relations activities and special plans intended for the new generation in the nation. Programs covering the education of students in nuclear engineering in colleges and universities in Korea, and public relations toward some selected groups and brackets have been conducted successfully, producing good results. On the other hand, some improvements in educational activities, including the revision of textbooks, are required in such a field of education of pupils in primary, middle and high schools. Specially-designed introductory courses and advanced courses in the peaceful utilization of nuclear power should be established to ensure that students in scientific or technological fields other than nuclear engineering will gain deeper understanding of the issue. For this, the preparation of textbooks are currently under way. It is hoped that public relations activities will be expanded on a more continuous and consistent basis, instead of the current intermittent basis, by making good use of the mass media to distribute information among the general public. (Nogami. K.).

  16. SOFTWARE SOLUTIONS FOR MEASURING AND FORECASTING THE CASH GENERATING UNIT FLOWS RELATED TO INTANGIBLE ASSETS

    Directory of Open Access Journals (Sweden)

    Veronica R GROSU

    2016-08-01

    Full Text Available In light of the difficulties encountered in assessing the value of the CGU (Cash Generating Unit and of the cash flows associated with goodwill or other intangible assets of a company and after performing the impairment test as provided by the IAS 36-Intangibile Asset and the forecasts related to it, the aim of this paper is to identify and suggest software instruments that would assist in the measurement and forecasting of these elements. The employment of the SPSS and the NeuroShell programmes in analyzing and forecasting the changes in CGU and CGU flows has helped compare the results and the ensuing error margins, thus giving the business entity the possibility to select the best software option, depending on certain variables identified on a micro or a macroeconomic level that may affect the depreciation or the increases in value of the underlying assets for CGU or CGU flows.

  17. Chemistry, materials and related problems in steam generators of power stations

    International Nuclear Information System (INIS)

    Mathur, P.K.

    2000-01-01

    The operational reliability and availability of power plants are considerably influenced by chemical factors. Researches all over the world indicate that several difficulties in power plants can be traced to off-normal or abnormal water chemistry conditions. Whatever the source of energy, be it fossil fuel or nuclear fuel, the ultimate aim is steam generation to drive a turbine. It is, therefore, natural that problems of water chemistry and material compatibility are similar in thermal and nuclear power stations. The present paper discusses various types of problems in the form of corrosion damages, taking place in the boiler-turbine cycles and describes different types of boiler feed water/boiler water treatments that have been in use both in nuclear and thermal power stations. Current positions in relation to requirements of boiler feed water, boiler water and steam quality have been described

  18. Management of uncertainties related to renewable generation participation in electricity markets

    International Nuclear Information System (INIS)

    Bourry, Franck

    2009-01-01

    The operation of Renewable Energy Sources (RES) units, such as wind or solar plants, is intrinsically dependent on the variability of the wind or solar resource. This makes large scale integration of RES into power systems particularly challenging. The research work in the frame of this thesis focuses on the participation of renewable power producers in liberalized electricity markets, and more precisely on the management of the regulation costs incurred by the producer for any imbalance between the contracted and delivered energy. In such context, the main objective of the thesis is to model and evaluate different methods for the management of imbalance penalties related to the participation of renewable power producers in short-term electricity markets. First, the thesis gives a classification of the existing solutions for the management of these imbalance penalties. A distinction is made between physical solutions which are related to the generation portfolio, and financial solutions which are based on market products. The physical solutions are considered in the frame of a Virtual Power Plant. A generic model of the imbalance penalty resulting from the use of physical or financial solutions is formulated, based on a market rule model. Then, the decision-making problem relative to both physical and financial solutions is formulated as an optimization problem under uncertainty. The approach is based on a loss function derived from the generic imbalance penalty model. Finally, the uncertainty related to the RES production is considered in the risk-based decision making process. The methods are illustrated using case studies based on real world data. (author)

  19. Shame and Alienation Related to Child Maltreatment: Links to Symptoms Across Generations.

    Science.gov (United States)

    Babcock Fenerci, Rebecca L; DePrince, Anne P

    2017-11-20

    The current study investigated associations between appraisals of shame and alienation related to mothers' own experiences of child maltreatment and symptoms across generations-in mothers themselves as well as their toddler/preschool-aged children. Mothers who survived maltreatment (N = 113) with a child between the ages of 2 and 5 were recruited to participate in an online study on Maternal Coping, Attachment and Health. Mother participants completed a series of questionnaires, including those that asked about posttrauma appraisals of their own maltreatment experiences as well as their child's and their own mental health symptoms. When taking into account other posttrauma appraisals (e.g., fear, betrayal, anger, self-blame), maternal shame and alienation were both significantly associated with maternal trauma-related distress (a composite of anxiety, PTSD, dissociation, and depressive symptoms). Maternal shame was also significantly linked to child internalizing symptoms and externalizing symptoms. Lower levels of fear and higher levels of betrayal were associated with externalizing symptoms as well. Maternal trauma-related distress mediated the relationship between maternal shame and child externalizing symptoms, and partially mediated the relationship between shame and internalizing symptoms. This study is the first of its kind to examine the role of posttrauma appraisals among mother survivors of maltreatment as they relate to symptoms in their young children. Although additional research is necessary, findings suggest that mothers' posttrauma appraisals, such as shame, could be a relevant factor in the early social-emotional development of survivors' children. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  20. Next Generation 9-1-1: Policy Implications of Incident Related Imagery on the Public Safety Answering Point

    Science.gov (United States)

    2017-03-01

    personal-photos-videos- user - generated - content -statistics/. 98 Ibid. 99 Christopher Ratcliff, “23 Up-to-Date Stats and Facts about Instagram You Need to...percentage of users of smartphone-related technology.87 User generated content in the form of pre-recorded and streaming video has also emerged as...active shooters, etc.) have the potential for generating significantly more graphic content , resulting in an extreme emotional toll on the call takers

  1. Steam generator thermal hydraulic design & functional architecture features and related operational and reliability issues requiring consideration

    International Nuclear Information System (INIS)

    Klarner, R.G.

    2012-01-01

    Proper thermal hydraulic design and functional architecture are critical to successful steam generator operation and long term reliability. The evolution of steam generators has been a gradual learning process that has benefited from continuous industry operational experience (OPEX). Inadequate thermal hydraulic design can lead to numerous degradation mechanisms such as excessive deposition, corrosion, flow and level instabilities, fluid-elastic instabilities and tube wear. The functional architecture determines the health of the tube bundle and the other internals during manufacturing, handling and operation. It also determines thermal performance as well as establishing global thermal-hydraulic characteristics such as water level shrink and swell response. This paper discusses the range of operational and reliability issues and relates them to the thermal hydraulic attributes and functional architecture of steam generators (many SG reliability issues are further discussed in other presentations at this conference). In pursuing such issues, the paper focuses on the four major features of the equipment, identifying in each case the goals and requirements such features must meet. Typical approaches and the means by which such requirements are addressed in current equipment are discussed. The four features are: 1. Tubing Material and Tube Bundle Heat Transfer Performance; a. Two materials are in current use – Alloy 690 TT and Alloy 800. Both are good materials with excellent performance records which serve their owners very well (the reliability attributes of Alloy 800 and 690 are discussed in other papers at this conference). Caution is advised in the supply of any material: – material quality is only assured by what is specified to material suppliers in procurement specifications – i.e. - all the knowledge and research in the world assures nothing if its findings are not reflected in procurement requirements. b. Heat transfer performance in addition to being

  2. Investigating Theoretical PV Energy Generation Patterns with Their Relation to the Power Load Curve in Poland

    Directory of Open Access Journals (Sweden)

    Jakub Jurasz

    2016-01-01

    Full Text Available Polish energy sector is (almost from its origin dominated by fossil fuel feed power. This situation results from an abundance of relatively cheap coal (hard and lignite. Brown coal due to its nature is the cheapest energy source in Poland. However, hard coal which fuels 60% of polish power plants is picking up on prices and is susceptible to the coal imported from neighboring countries. Forced by the European Union (EU regulations, Poland is struggling at achieving its goal of reaching 15% of energy consumption from renewable energy sources (RES by 2020. Over the year 2015, RES covered 11.3% of gross energy consumption but this generation was dominated by solid biomass (over 80%. The aim of this paper was to answer the following research questions: What is the relation of irradiation values to the power load on a yearly and daily basis? and how should photovoltaics (PV be integrated in the polish power system? Conducted analysis allowed us to state that there exists a negative correlation between power demand and irradiation values on a yearly basis, but this is likely to change in the future. Secondly, on average, daily values of irradiation tend to follow power load curve over the first hours of the day.

  3. Examining the Relations between Subjective Social Class, Academics, and Well-Being in First-Generation College Student Veterans

    Science.gov (United States)

    Colbow, Alexander James

    2017-01-01

    The aim of this study was to examine the relations between aspects of subjective social class, academic performance, and subjective wellbeing in first-generation and veteran students. In recent years, both student veterans and first-generation students have become topics of interest for universities, counselors, and researchers, as they are…

  4. Evolvable synthetic neural system

    Science.gov (United States)

    Curtis, Steven A. (Inventor)

    2009-01-01

    An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

  5. Relative cortico-subcortical shift in brain activity but preserved training-induced neural modulation in older adults during bimanual motor learning.

    Science.gov (United States)

    Santos Monteiro, Thiago; Beets, Iseult A M; Boisgontier, Matthieu P; Gooijers, Jolien; Pauwels, Lisa; Chalavi, Sima; King, Brad; Albouy, Geneviève; Swinnen, Stephan P

    2017-10-01

    To study age-related differences in neural activation during motor learning, functional magnetic resonance imaging scans were acquired from 25 young (mean 21.5-year old) and 18 older adults (mean 68.6-year old) while performing a bimanual coordination task before (pretest) and after (posttest) a 2-week training intervention on the task. We studied whether task-related brain activity and training-induced brain activation changes differed between age groups, particularly with respect to the hyperactivation typically observed in older adults. Findings revealed that older adults showed lower performance levels than younger adults but similar learning capability. At the cerebral level, the task-related hyperactivation in parietofrontal areas and underactivation in subcortical areas observed in older adults were not differentially modulated by the training intervention. However, brain activity related to task planning and execution decreased from pretest to posttest in temporo-parieto-frontal areas and subcortical areas in both age groups, suggesting similar processes of enhanced activation efficiency with advanced skill level. Furthermore, older adults who displayed higher activity in prefrontal regions at pretest demonstrated larger training-induced performance gains. In conclusion, in spite of prominent age-related brain activation differences during movement planning and execution, the mechanisms of learning-related reduction of brain activation appear to be similar in both groups. Importantly, cerebral activity during early learning can differentially predict the amplitude of the training-induced performance benefit between young and older adults. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. Distinct Neural-Functional Effects of Treatments With Selective Serotonin Reuptake Inhibitors, Electroconvulsive Therapy, and Transcranial Magnetic Stimulation and Their Relations to Regional Brain Function in Major Depression: A Meta-analysis.

    Science.gov (United States)

    Chau, David T; Fogelman, Phoebe; Nordanskog, Pia; Drevets, Wayne C; Hamilton, J Paul

    2017-05-01

    Functional neuroimaging studies have examined the neural substrates of treatments for major depressive disorder (MDD). Low sample size and methodological heterogeneity, however, undermine the generalizability of findings from individual studies. We conducted a meta-analysis to identify reliable neural changes resulting from different modes of treatment for MDD and compared them with each other and with reliable neural functional abnormalities observed in depressed versus control samples. We conducted a meta-analysis of studies reporting changes in brain activity (e.g., as indexed by positron emission tomography) following treatments with selective serotonin reuptake inhibitors (SSRIs), electroconvulsive therapy (ECT), or transcranial magnetic stimulation. Additionally, we examined the statistical reliability of overlap among thresholded meta-analytic SSRI, ECT, and transcranial magnetic stimulation maps as well as a map of abnormal neural function in MDD. Our meta-analysis revealed that 1) SSRIs decrease activity in the anterior insula, 2) ECT decreases activity in central nodes of the default mode network, 3) transcranial magnetic stimulation does not result in reliable neural changes, and 4) regional effects of these modes of treatment do not significantly overlap with each other or with regions showing reliable functional abnormality in MDD. SSRIs and ECT produce neurally distinct effects relative to each other and to the functional abnormalities implicated in depression. These treatments therefore may exert antidepressant effects by diminishing neural functions not implicated in depression but that nonetheless impact mood. We discuss how the distinct neural changes resulting from SSRIs and ECT can account for both treatment effects and side effects from these therapies as well as how to individualize these treatments. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  7. The neural determinants of age-related changes in fluid intelligence: a pre-registered, longitudinal analysis in UK Biobank.

    Science.gov (United States)

    Kievit, Rogier A; Fuhrmann, Delia; Borgeest, Gesa Sophia; Simpson-Kent, Ivan L; Henson, Richard N A

    2018-01-01

    Background:  Fluid intelligence declines with advancing age, starting in early adulthood. Within-subject declines in fluid intelligence are highly correlated with contemporaneous declines in the ability to live and function independently. To support healthy aging, the mechanisms underlying these declines need to be better understood. Methods:  In this pre-registered analysis, we applied latent growth curve modelling to investigate the neural determinants of longitudinal changes in fluid intelligence across three time points in 185,317 individuals (N=9,719 two waves, N=870 three waves) from the UK Biobank (age range: 39-73 years). Results:  We found a weak but significant effect of cross-sectional age on the mean fluid intelligence score, such that older individuals scored slightly lower. However, the mean longitudinal slope was positive, rather than negative, suggesting improvement across testing occasions. Despite the considerable sample size, the slope variance was non-significant, suggesting no reliable individual differences in change over time. This null-result is likely due to the nature of the cognitive test used. In a subset of individuals, we found that white matter microstructure (N=8839, as indexed by fractional anisotropy) and grey-matter volume (N=9931) in pre-defined regions-of-interest accounted for complementary and unique variance in mean fluid intelligence scores. The strongest effects were such that higher grey matter volume in the frontal pole and greater white matter microstructure in the posterior thalamic radiations were associated with higher fluid intelligence scores. Conclusions:  In a large preregistered analysis, we demonstrate a weak but significant negative association between age and fluid intelligence. However, we did not observe plausible longitudinal patterns, instead observing a weak increase across testing occasions, and no significant individual differences in rates of change, likely due to the suboptimal task design

  8. Effects of ketone bodies in Alzheimer's disease in relation to neural hypometabolism, β-amyloid toxicity, and astrocyte function

    DEFF Research Database (Denmark)

    Hertz, Leif; Chen, Ye; Waagepetersen, Helle S

    2015-01-01

    Diet supplementation with ketone bodies (acetoacetate and β-hydroxybuturate) or medium-length fatty acids generating ketone bodies has consistently been found to cause modest improvement of mental function in Alzheimer's patients. It was suggested that the therapeutic effect might be more...

  9. Can I relate? A review and guide for nurse managers in leading generations.

    Science.gov (United States)

    Christensen, Scott S; Wilson, Barbara L; Edelman, Linda S

    2018-01-30

    The purpose of this review is to help the nurse leader develop an understanding of the five generations currently in the health care workforce by providing defining characteristics, general behaviours, and strategies for the nurse manager to employ for each generational cohort. Generations are groups of people born during the same 15-20 year time period who share similar experiences before adulthood, which shape long-term behaviours. Key descriptors and characteristics are provided. The current generational cohorts in the health care workforce are Traditionalists (born between 1922 and 1945), baby boomers (born between 1946 and 1964), Generation X (born between 1965 and 1979), millennials (born between 1980 and 1995), and Generation Z (born after 1995). Health care teams often comprise members of three or more generations. Intergenerational differences in team members can result in challenges; however, different perspectives provided by multiple generations can be used advantageously to strengthen the team's efficiency and outcomes. There are strengths in each generation. Key differences can be harnessed to build stronger teams through comprehensive communication strategies, customized reward systems, and workplace flexibility. Examples are provided for each area. Managers can use intergenerational differences to create a rich environment that bridges generational differences and fosters workforce cohesion. © 2018 John Wiley & Sons Ltd.

  10. Automated biphasic morphological assessment of hepatitis B-related liver fibrosis using second harmonic generation microscopy

    Science.gov (United States)

    Wang, Tong-Hong; Chen, Tse-Ching; Teng, Xiao; Liang, Kung-Hao; Yeh, Chau-Ting

    2015-08-01

    Liver fibrosis assessment by biopsy and conventional staining scores is based on histopathological criteria. Variations in sample preparation and the use of semi-quantitative histopathological methods commonly result in discrepancies between medical centers. Thus, minor changes in liver fibrosis might be overlooked in multi-center clinical trials, leading to statistically non-significant data. Here, we developed a computer-assisted, fully automated, staining-free method for hepatitis B-related liver fibrosis assessment. In total, 175 liver biopsies were divided into training (n = 105) and verification (n = 70) cohorts. Collagen was observed using second harmonic generation (SHG) microscopy without prior staining, and hepatocyte morphology was recorded using two-photon excitation fluorescence (TPEF) microscopy. The training cohort was utilized to establish a quantification algorithm. Eleven of 19 computer-recognizable SHG/TPEF microscopic morphological features were significantly correlated with the ISHAK fibrosis stages (P 0.82 for liver cirrhosis