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Sample records for neural populations code

  1. A thesaurus for a neural population code.

    Science.gov (United States)

    Ganmor, Elad; Segev, Ronen; Schneidman, Elad

    2015-09-08

    Information is carried in the brain by the joint spiking patterns of large groups of noisy, unreliable neurons. This noise limits the capacity of the neural code and determines how information can be transmitted and read-out. To accurately decode, the brain must overcome this noise and identify which patterns are semantically similar. We use models of network encoding noise to learn a thesaurus for populations of neurons in the vertebrate retina responding to artificial and natural videos, measuring the similarity between population responses to visual stimuli based on the information they carry. This thesaurus reveals that the code is organized in clusters of synonymous activity patterns that are similar in meaning but may differ considerably in their structure. This organization is highly reminiscent of the design of engineered codes. We suggest that the brain may use this structure and show how it allows accurate decoding of novel stimuli from novel spiking patterns.

  2. Information-Theoretic Bounds and Approximations in Neural Population Coding.

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    Huang, Wentao; Zhang, Kechen

    2018-01-17

    While Shannon's mutual information has widespread applications in many disciplines, for practical applications it is often difficult to calculate its value accurately for high-dimensional variables because of the curse of dimensionality. This article focuses on effective approximation methods for evaluating mutual information in the context of neural population coding. For large but finite neural populations, we derive several information-theoretic asymptotic bounds and approximation formulas that remain valid in high-dimensional spaces. We prove that optimizing the population density distribution based on these approximation formulas is a convex optimization problem that allows efficient numerical solutions. Numerical simulation results confirmed that our asymptotic formulas were highly accurate for approximating mutual information for large neural populations. In special cases, the approximation formulas are exactly equal to the true mutual information. We also discuss techniques of variable transformation and dimensionality reduction to facilitate computation of the approximations.

  3. Stimulus-dependent maximum entropy models of neural population codes.

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    Einat Granot-Atedgi

    Full Text Available Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. For large populations, direct sampling of these distributions is impossible, and so we must rely on constructing appropriate models. We show here that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. We introduce the stimulus-dependent maximum entropy (SDME model-a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. We find that the SDME model gives a more accurate account of single cell responses and in particular significantly outperforms uncoupled models in reproducing the distributions of population codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like average surprise and information transmission in a neural population.

  4. Knowledge extraction from evolving spiking neural networks with rank order population coding.

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    Soltic, Snjezana; Kasabov, Nikola

    2010-12-01

    This paper demonstrates how knowledge can be extracted from evolving spiking neural networks with rank order population coding. Knowledge discovery is a very important feature of intelligent systems. Yet, a disproportionally small amount of research is centered on the issue of knowledge extraction from spiking neural networks which are considered to be the third generation of artificial neural networks. The lack of knowledge representation compatibility is becoming a major detriment to end users of these networks. We show that a high-level knowledge can be obtained from evolving spiking neural networks. More specifically, we propose a method for fuzzy rule extraction from an evolving spiking network with rank order population coding. The proposed method was used for knowledge discovery on two benchmark taste recognition problems where the knowledge learnt by an evolving spiking neural network was extracted in the form of zero-order Takagi-Sugeno fuzzy IF-THEN rules.

  5. The role of stochasticity in an information-optimal neural population code

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    Stocks, N. G.; Nikitin, A. P.; McDonnell, M. D.; Morse, R. P.

    2009-12-01

    In this paper we consider the optimisation of Shannon mutual information (MI) in the context of two model neural systems. The first is a stochastic pooling network (population) of McCulloch-Pitts (MP) type neurons (logical threshold units) subject to stochastic forcing; the second is (in a rate coding paradigm) a population of neurons that each displays Poisson statistics (the so called 'Poisson neuron'). The mutual information is optimised as a function of a parameter that characterises the 'noise level'-in the MP array this parameter is the standard deviation of the noise; in the population of Poisson neurons it is the window length used to determine the spike count. In both systems we find that the emergent neural architecture and, hence, code that maximises the MI is strongly influenced by the noise level. Low noise levels leads to a heterogeneous distribution of neural parameters (diversity), whereas, medium to high noise levels result in the clustering of neural parameters into distinct groups that can be interpreted as subpopulations. In both cases the number of subpopulations increases with a decrease in noise level. Our results suggest that subpopulations are a generic feature of an information optimal neural population.

  6. The sign rule and beyond: boundary effects, flexibility, and noise correlations in neural population codes.

    Directory of Open Access Journals (Sweden)

    Yu Hu

    2014-02-01

    Full Text Available Over repeat presentations of the same stimulus, sensory neurons show variable responses. This "noise" is typically correlated between pairs of cells, and a question with rich history in neuroscience is how these noise correlations impact the population's ability to encode the stimulus. Here, we consider a very general setting for population coding, investigating how information varies as a function of noise correlations, with all other aspects of the problem - neural tuning curves, etc. - held fixed. This work yields unifying insights into the role of noise correlations. These are summarized in the form of theorems, and illustrated with numerical examples involving neurons with diverse tuning curves. Our main contributions are as follows. (1 We generalize previous results to prove a sign rule (SR - if noise correlations between pairs of neurons have opposite signs vs. their signal correlations, then coding performance will improve compared to the independent case. This holds for three different metrics of coding performance, and for arbitrary tuning curves and levels of heterogeneity. This generality is true for our other results as well. (2 As also pointed out in the literature, the SR does not provide a necessary condition for good coding. We show that a diverse set of correlation structures can improve coding. Many of these violate the SR, as do experimentally observed correlations. There is structure to this diversity: we prove that the optimal correlation structures must lie on boundaries of the possible set of noise correlations. (3 We provide a novel set of necessary and sufficient conditions, under which the coding performance (in the presence of noise will be as good as it would be if there were no noise present at all.

  7. Population-Level Neural Codes Are Robust to Single-Neuron Variability from a Multidimensional Coding Perspective.

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    Montijn, Jorrit S; Meijer, Guido T; Lansink, Carien S; Pennartz, Cyriel M A

    2016-08-30

    Sensory neurons are often tuned to particular stimulus features, but their responses to repeated presentation of the same stimulus can vary over subsequent trials. This presents a problem for understanding the functioning of the brain, because downstream neuronal populations ought to construct accurate stimulus representations, even upon singular exposure. To study how trial-by-trial fluctuations (i.e., noise) in activity influence cortical representations of sensory input, we performed chronic calcium imaging of GCaMP6-expressing populations in mouse V1. We observed that high-dimensional response correlations, i.e., dependencies in activation strength among multiple neurons, can be used to predict single-trial, single-neuron noise. These multidimensional correlations are structured such that variability in the response of single neurons is relatively harmless to population representations of visual stimuli. We propose that multidimensional coding may represent a canonical principle of cortical circuits, explaining why the apparent noisiness of neuronal responses is compatible with accurate neural representations of stimulus features. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

  8. Population-Level Neural Codes Are Robust to Single-Neuron Variability from a Multidimensional Coding Perspective

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    Jorrit S. Montijn

    2016-08-01

    Full Text Available Sensory neurons are often tuned to particular stimulus features, but their responses to repeated presentation of the same stimulus can vary over subsequent trials. This presents a problem for understanding the functioning of the brain, because downstream neuronal populations ought to construct accurate stimulus representations, even upon singular exposure. To study how trial-by-trial fluctuations (i.e., noise in activity influence cortical representations of sensory input, we performed chronic calcium imaging of GCaMP6-expressing populations in mouse V1. We observed that high-dimensional response correlations, i.e., dependencies in activation strength among multiple neurons, can be used to predict single-trial, single-neuron noise. These multidimensional correlations are structured such that variability in the response of single neurons is relatively harmless to population representations of visual stimuli. We propose that multidimensional coding may represent a canonical principle of cortical circuits, explaining why the apparent noisiness of neuronal responses is compatible with accurate neural representations of stimulus features.

  9. [Neural codes for perception].

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    Romo, R; Salinas, E; Hernández, A; Zainos, A; Lemus, L; de Lafuente, V; Luna, R

    This article describes experiments designed to show the neural codes associated with the perception and processing of tactile information. The results of these experiments have shown the neural activity correlated with tactile perception. The neurones of the primary somatosensory cortex (S1) represent the physical attributes of tactile perception. We found that these representations correlated with tactile perception. By means of intracortical microstimulation we demonstrated the causal relationship between S1 activity and tactile perception. In the motor areas of the frontal lobe is to be found the connection between sensorial and motor representation whilst decisions are being taken. S1 generates neural representations of the somatosensory stimuli which seen to be sufficient for tactile perception. These neural representations are subsequently processed by central areas to S1 and seem useful in perception, memory and decision making.

  10. Understanding Neural Population Coding: Information Theoretic Insights from the Auditory System

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    Arno Onken

    2014-01-01

    Full Text Available In recent years, our research in computational neuroscience has focused on understanding how populations of neurons encode naturalistic stimuli. In particular, we focused on how populations of neurons use the time domain to encode sensory information. In this focused review, we summarize this recent work from our laboratory. We focus in particular on the mathematical methods that we developed for the quantification of how information is encoded by populations of neurons and on how we used these methods to investigate the encoding of complex naturalistic sounds in auditory cortex. We review how these methods revealed a complementary role of low frequency oscillations and millisecond precise spike patterns in encoding complex sounds and in making these representations robust to imprecise knowledge about the timing of the external stimulus. Further, we discuss challenges in extending this work to understand how large populations of neurons encode sensory information. Overall, this previous work provides analytical tools and conceptual understanding necessary to study the principles of how neural populations reflect sensory inputs and achieve a stable representation despite many uncertainties in the environment.

  11. Indices for Testing Neural Codes

    OpenAIRE

    Jonathan D. Victor; Nirenberg, Sheila

    2008-01-01

    One of the most critical challenges in systems neuroscience is determining the neural code. A principled framework for addressing this can be found in information theory. With this approach, one can determine whether a proposed code can account for the stimulus-response relationship. Specifically, one can compare the transmitted information between the stimulus and the hypothesized neural code with the transmitted information between the stimulus and the behavioral response. If the former is ...

  12. L-type calcium channels refine the neural population code of sound level.

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    Grimsley, Calum Alex; Green, David Brian; Sivaramakrishnan, Shobhana

    2016-12-01

    The coding of sound level by ensembles of neurons improves the accuracy with which listeners identify how loud a sound is. In the auditory system, the rate at which neurons fire in response to changes in sound level is shaped by local networks. Voltage-gated conductances alter local output by regulating neuronal firing, but their role in modulating responses to sound level is unclear. We tested the effects of L-type calcium channels (CaL: CaV1.1-1.4) on sound-level coding in the central nucleus of the inferior colliculus (ICC) in the auditory midbrain. We characterized the contribution of CaL to the total calcium current in brain slices and then examined its effects on rate-level functions (RLFs) in vivo using single-unit recordings in awake mice. CaL is a high-threshold current and comprises ∼50% of the total calcium current in ICC neurons. In vivo, CaL activates at sound levels that evoke high firing rates. In RLFs that increase monotonically with sound level, CaL boosts spike rates at high sound levels and increases the maximum firing rate achieved. In different populations of RLFs that change nonmonotonically with sound level, CaL either suppresses or enhances firing at sound levels that evoke maximum firing. CaL multiplies the gain of monotonic RLFs with dynamic range and divides the gain of nonmonotonic RLFs with the width of the RLF. These results suggest that a single broad class of calcium channels activates enhancing and suppressing local circuits to regulate the sensitivity of neuronal populations to sound level. Copyright © 2016 the American Physiological Society.

  13. Understanding perception through neural "codes".

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    Freeman, Walter J

    2011-07-01

    A major challenge for cognitive scientists is to deduce and explain the neural mechanisms of the rapid transposition between stimulus energy and recalled memory-between the specific (sensation) and the generic (perception)-in both material and mental aspects. Researchers are attempting three explanations in terms of neural codes. The microscopic code: cellular neurobiologists correlate stimulus properties with the rates and frequencies of trains of action potentials induced by stimuli and carried by topologically organized axons. The mesoscopic code: cognitive scientists formulate symbolic codes in trains of action potentials from feature-detector neurons of phonemes, lines, odorants, vibrations, faces, etc., that object-detector neurons bind into representations of stimuli. The macroscopic code: neurodynamicists extract neural correlates of stimuli and associated behaviors in spatial patterns of oscillatory fields of dendritic activity, which self-organize and evolve on trajectories through high-dimensional brain state space. This multivariate code is expressed in landscapes of chaotic attractors. Unlike other scientific codes, such as DNA and the periodic table, these neural codes have no alphabet or syntax. They are epistemological metaphors that experimentalists need to measure neural activity and engineers need to model brain functions. My aim is to describe the main properties of the macroscopic code and the grand challenge it poses: how do very large patterns of textured synchronized oscillations form in cortex so quickly? © 2010 IEEE

  14. Neural Decoder for Topological Codes

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    Torlai, Giacomo; Melko, Roger G.

    2017-07-01

    We present an algorithm for error correction in topological codes that exploits modern machine learning techniques. Our decoder is constructed from a stochastic neural network called a Boltzmann machine, of the type extensively used in deep learning. We provide a general prescription for the training of the network and a decoding strategy that is applicable to a wide variety of stabilizer codes with very little specialization. We demonstrate the neural decoder numerically on the well-known two-dimensional toric code with phase-flip errors.

  15. Oscillatory multiplexing of neural population codes for interval timing and working memory

    NARCIS (Netherlands)

    Gu, Bon-Mi; van Rijn, Hedderik; Meck, Warren H.

    Interval timing and working memory are critical components of cognition that are supported by neural oscillations in prefrontal-striatal-hippocampal circuits. In this review, the properties of interval timing and working memory are explored in terms of behavioral, anatomical, pharmacological, and

  16. Modeling development of natural multi-sensory integration using neural self-organisation and probabilistic population codes

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    Bauer, Johannes; Dávila-Chacón, Jorge; Wermter, Stefan

    2015-10-01

    Humans and other animals have been shown to perform near-optimally in multi-sensory integration tasks. Probabilistic population codes (PPCs) have been proposed as a mechanism by which optimal integration can be accomplished. Previous approaches have focussed on how neural networks might produce PPCs from sensory input or perform calculations using them, like combining multiple PPCs. Less attention has been given to the question of how the necessary organisation of neurons can arise and how the required knowledge about the input statistics can be learned. In this paper, we propose a model of learning multi-sensory integration based on an unsupervised learning algorithm in which an artificial neural network learns the noise characteristics of each of its sources of input. Our algorithm borrows from the self-organising map the ability to learn latent-variable models of the input and extends it to learning to produce a PPC approximating a probability density function over the latent variable behind its (noisy) input. The neurons in our network are only required to perform simple calculations and we make few assumptions about input noise properties and tuning functions. We report on a neurorobotic experiment in which we apply our algorithm to multi-sensory integration in a humanoid robot to demonstrate its effectiveness and compare it to human multi-sensory integration on the behavioural level. We also show in simulations that our algorithm performs near-optimally under certain plausible conditions, and that it reproduces important aspects of natural multi-sensory integration on the neural level.

  17. Filling-In, Spatial Summation, and Radiation of Pain: Evidence for a Neural Population Code in the Nociceptive System

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    Quevedo, Alexandre S.

    2009-01-01

    The receptive field organization of nociceptive neurons suggests that noxious information may be encoded by population-based mechanisms. Electrophysiological evidence of population coding mechanisms has remained limited. However, psychophysical studies examining interactions between multiple noxious stimuli can provide indirect evidence that neuron population recruitment can contribute to both spatial and intensity-related percepts of pain. In the present study, pairs of thermal stimuli (35°C/49°C or 49°C/49°C) were delivered at different distances on the leg (0, 5, 10, 20, 40 cm) and abdomen (within and across dermatomes) and subjects evaluated pain intensity and perceived spatial attributes of stimuli. Reports of perceived pain spreading to involve areas that were not stimulated (radiation of pain) were most frequent at 5- and 10-cm distances (χ2 = 34.107, P dermatomes (P < 0.05), but was maximal at 5- and 10-cm separation distances. Taken together, all three of these phenomena suggest that interactions between recruited populations of neurons may support both spatial and intensity-related dimensions of the pain experience. PMID:19759320

  18. Degenerate coding in neural systems.

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    Leonardo, Anthony

    2005-11-01

    When the dimensionality of a neural circuit is substantially larger than the dimensionality of the variable it encodes, many different degenerate network states can produce the same output. In this review I will discuss three different neural systems that are linked by this theme. The pyloric network of the lobster, the song control system of the zebra finch, and the odor encoding system of the locust, while different in design, all contain degeneracies between their internal parameters and the outputs they encode. Indeed, although the dynamics of song generation and odor identification are quite different, computationally, odor recognition can be thought of as running the song generation circuitry backwards. In both of these systems, degeneracy plays a vital role in mapping a sparse neural representation devoid of correlations onto external stimuli (odors or song structure) that are strongly correlated. I argue that degeneracy between input and output states is an inherent feature of many neural systems, which can be exploited as a fault-tolerant method of reliably learning, generating, and discriminating closely related patterns.

  19. Structures of Neural Correlation and How They Favor Coding

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    Franke, Felix; Fiscella, Michele; Sevelev, Maksim; Roska, Botond; Hierlemann, Andreas; da Silveira, Rava Azeredo

    2017-01-01

    Summary The neural representation of information suffers from “noise”—the trial-to-trial variability in the response of neurons. The impact of correlated noise upon population coding has been debated, but a direct connection between theory and experiment remains tenuous. Here, we substantiate this connection and propose a refined theoretical picture. Using simultaneous recordings from a population of direction-selective retinal ganglion cells, we demonstrate that coding benefits from noise correlations. The effect is appreciable already in small populations, yet it is a collective phenomenon. Furthermore, the stimulus-dependent structure of correlation is key. We develop simple functional models that capture the stimulus-dependent statistics. We then use them to quantify the performance of population coding, which depends upon interplays of feature sensitivities and noise correlations in the population. Because favorable structures of correlation emerge robustly in circuits with noisy, nonlinear elements, they will arise and benefit coding beyond the confines of retina. PMID:26796692

  20. A neural code for looming and receding motion is distributed over a population of electrosensory ON and OFF contrast cells.

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    Clarke, Stephen E; Longtin, André; Maler, Leonard

    2014-04-16

    Object saliency is based on the relative local-to-background contrast in the physical signals that underlie perceptual experience. As such, contrast-detecting neurons (ON/OFF cells) are found in many sensory systems, responding respectively to increased or decreased intensity within their receptive field centers. This differential sensitivity suggests that ON and OFF cells initiate segregated streams of information for positive and negative sensory contrast. However, while recording in vivo from the ON and OFF cells of Apteronotus leptorhynchus, we report that the reversal of stimulus motion triggers paradoxical responses to electrosensory contrast. By considering the instantaneous firing rates of both ON and OFF cell populations, a bidirectionally symmetric representation of motion is achieved for both positive and negative contrast stimuli. Whereas the firing rates of the individual contrast detecting neurons convey scalar information, such as object distance, it is their sequential activation over longer timescales that track changes in the direction of movement.

  1. Coding stimulus amplitude by correlated neural activity.

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    Metzen, Michael G; Ávila-Åkerberg, Oscar; Chacron, Maurice J

    2015-04-01

    While correlated activity is observed ubiquitously in the brain, its role in neural coding has remained controversial. Recent experimental results have demonstrated that correlated but not single-neuron activity can encode the detailed time course of the instantaneous amplitude (i.e., envelope) of a stimulus. These have furthermore demonstrated that such coding required and was optimal for a nonzero level of neural variability. However, a theoretical understanding of these results is still lacking. Here we provide a comprehensive theoretical framework explaining these experimental findings. Specifically, we use linear response theory to derive an expression relating the correlation coefficient to the instantaneous stimulus amplitude, which takes into account key single-neuron properties such as firing rate and variability as quantified by the coefficient of variation. The theoretical prediction was in excellent agreement with numerical simulations of various integrate-and-fire type neuron models for various parameter values. Further, we demonstrate a form of stochastic resonance as optimal coding of stimulus variance by correlated activity occurs for a nonzero value of noise intensity. Thus, our results provide a theoretical explanation of the phenomenon by which correlated but not single-neuron activity can code for stimulus amplitude and how key single-neuron properties such as firing rate and variability influence such coding. Correlation coding by correlated but not single-neuron activity is thus predicted to be a ubiquitous feature of sensory processing for neurons responding to weak input.

  2. Grid cells generate an analog error-correcting code for singularly precise neural computation.

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    Sreenivasan, Sameet; Fiete, Ila

    2011-09-11

    Entorhinal grid cells in mammals fire as a function of animal location, with spatially periodic response patterns. This nonlocal periodic representation of location, a local variable, is unlike other neural codes. There is no theoretical explanation for why such a code should exist. We examined how accurately the grid code with noisy neurons allows an ideal observer to estimate location and found this code to be a previously unknown type of population code with unprecedented robustness to noise. In particular, the representational accuracy attained by grid cells over the coding range was in a qualitatively different class from what is possible with observed sensory and motor population codes. We found that a simple neural network can effectively correct the grid code. To the best of our knowledge, these results are the first demonstration that the brain contains, and may exploit, powerful error-correcting codes for analog variables. © 2011 Nature America, Inc. All rights reserved.

  3. Intrinsic gain modulation and adaptive neural coding.

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    Sungho Hong

    2008-07-01

    Full Text Available In many cases, the computation of a neural system can be reduced to a receptive field, or a set of linear filters, and a thresholding function, or gain curve, which determines the firing probability; this is known as a linear/nonlinear model. In some forms of sensory adaptation, these linear filters and gain curve adjust very rapidly to changes in the variance of a randomly varying driving input. An apparently similar but previously unrelated issue is the observation of gain control by background noise in cortical neurons: the slope of the firing rate versus current (f-I curve changes with the variance of background random input. Here, we show a direct correspondence between these two observations by relating variance-dependent changes in the gain of f-I curves to characteristics of the changing empirical linear/nonlinear model obtained by sampling. In the case that the underlying system is fixed, we derive relationships relating the change of the gain with respect to both mean and variance with the receptive fields derived from reverse correlation on a white noise stimulus. Using two conductance-based model neurons that display distinct gain modulation properties through a simple change in parameters, we show that coding properties of both these models quantitatively satisfy the predicted relationships. Our results describe how both variance-dependent gain modulation and adaptive neural computation result from intrinsic nonlinearity.

  4. Energy coding in neural network with inhibitory neurons.

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    Wang, Ziyin; Wang, Rubin; Fang, Ruiyan

    2015-04-01

    This paper aimed at assessing and comparing the effects of the inhibitory neurons in the neural network on the neural energy distribution, and the network activities in the absence of the inhibitory neurons to understand the nature of neural energy distribution and neural energy coding. Stimulus, synchronous oscillation has significant difference between neural networks with and without inhibitory neurons, and this difference can be quantitatively evaluated by the characteristic energy distribution. In addition, the synchronous oscillation difference of the neural activity can be quantitatively described by change of the energy distribution if the network parameters are gradually adjusted. Compared with traditional method of correlation coefficient analysis, the quantitative indicators based on nervous energy distribution characteristics are more effective in reflecting the dynamic features of the neural network activities. Meanwhile, this neural coding method from a global perspective of neural activity effectively avoids the current defects of neural encoding and decoding theory and enormous difficulties encountered. Our studies have shown that neural energy coding is a new coding theory with high efficiency and great potential.

  5. Decoding small surface codes with feedforward neural networks

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    Varsamopoulos, Savvas; Criger, Ben; Bertels, Koen

    2018-01-01

    Surface codes reach high error thresholds when decoded with known algorithms, but the decoding time will likely exceed the available time budget, especially for near-term implementations. To decrease the decoding time, we reduce the decoding problem to a classification problem that a feedforward neural network can solve. We investigate quantum error correction and fault tolerance at small code distances using neural network-based decoders, demonstrating that the neural network can generalize to inputs that were not provided during training and that they can reach similar or better decoding performance compared to previous algorithms. We conclude by discussing the time required by a feedforward neural network decoder in hardware.

  6. Pattern completion through phase coding in population neurodynamics.

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    Gutierrez-Galvez, A; Gutierrez-Osuna, R

    2003-01-01

    This article presents an alternative phase coding mechanism for Freeman's KIII model of population neurodynamics. Motivated by experimental evidence that supports the existence of a neural code based on synchronous oscillations, we propose an analogy between synchronization in neural populations and phase locking in KIII channels. An efficient method is proposed to extract phase differences across granule channels from their state-space trajectories. First, the scale invariance of the KIII model with respect to phase information is established. The phase code is then compared against the conventional amplitude code in terms of their bit-wise and across-fiber pattern recovery capabilities using decision-theoretic principles and a Hamming-distance classifier. Graph isomorphism in the Hebbian connections is exploited to perform an exhaustive evaluation of patterns on an 8-channel KIII model. Simulation results show that phase information outperforms amplitude information in the recovery of incomplete or corrupted stimuli.

  7. Critical Phenomena in Population Coding

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    Berkowitz, John; Sharpee, Tatyana

    2014-03-01

    Populations of neurons that code for sensory stimuli are often modeled as having sigmoidal tuning curves where the midpoint and slope of the curve represent, respectively, an intrinsic firing threshold and noise level. Recent studies have shown for two subpopulations of neurons that states below a critical noise level are associated with symmetry breaking between the populations' thresholds. In this work we consider the case of up to seven distinct subpopulations encoding a common gaussian stimulus. We optimized the mutual information between output patterns and stimuli by adjusting the thresholds for a fixed noise level. In the high-noise regime the optimal thresholds are fully redundant whereas the low noise limit predicts distinct threshold values that achieve histogram equalization of the input signal. Between the two limits, the thresholds exhibit a complex branching process that occur at successive values of the noise level. Each branch corresponds to a critical point of a continuous phase transition. The behavior of the system in the limit of a large number of subpopulations is also investigated, and critical phenomena are also present in the distribution of thresholds in this limit.

  8. On Decoding Grid Cell Population Codes Using Approximate Belief Propagation.

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    Yoo, Yongseok; Kim, Woori

    2017-03-01

    Neural systems are inherently noisy. One well-studied example of a noise reduction mechanism in the brain is the population code, where representing a variable with multiple neurons allows the encoded variable to be recovered with fewer errors. Studies have assumed ideal observer models for decoding population codes, and the manner in which information in the neural population can be retrieved remains elusive. This letter addresses a mechanism by which realistic neural circuits can recover encoded variables. Specifically, the decoding problem of recovering a spatial location from populations of grid cells is studied using belief propagation. We extend the belief propagation decoding algorithm in two aspects. First, beliefs are approximated rather than being calculated exactly. Second, decoding noises are introduced into the decoding circuits. Numerical simulations demonstrate that beliefs can be effectively approximated by combining polynomial nonlinearities with divisive normalization. This approximate belief propagation algorithm is tolerant to decoding noises. Thus, this letter presents a realistic model for decoding neural population codes and investigates fault-tolerant information retrieval mechanisms in the brain.

  9. Unfolding code for neutron spectrometry based on neural nets technology

    Energy Technology Data Exchange (ETDEWEB)

    Ortiz R, J. M.; Vega C, H. R., E-mail: morvymm@yahoo.com.mx [Universidad Autonoma de Zacatecas, Unidad Academica de Ingenieria Electrica, Apdo. Postal 336, 98000 Zacatecas (Mexico)

    2012-10-15

    The most delicate part of neutron spectrometry, is the unfolding process. The derivation of the spectral information is not simple because the unknown is not given directly as a result of the measurements. The drawbacks associated with traditional unfolding procedures have motivated the need of complementary approaches. Novel methods based on Artificial Neural Networks have been widely investigated. In this work, a neutron spectrum unfolding code based on neural nets technology is presented. This unfolding code called Neutron Spectrometry and Dosimetry by means of Artificial Neural Networks was designed in a graphical interface under LabVIEW programming environment. The core of the code is an embedded neural network architecture, previously optimized by the {sup R}obust Design of Artificial Neural Networks Methodology{sup .} The main features of the code are: is easy to use, friendly and intuitive to the user. This code was designed for a Bonner Sphere System based on a {sup 6}Lil(Eu) neutron detector and a response matrix expressed in 60 energy bins taken from an International Atomic Energy Agency compilation. The main feature of the code is that as entrance data, only seven rate counts measurement with a Bonner spheres spectrometer are required for simultaneously unfold the 60 energy bins of the neutron spectrum and to calculate 15 dosimetric quantities, for radiation protection porpoises. This code generates a full report in html format with all relevant information. (Author)

  10. How We Hear: The Perception and Neural Coding of Sound.

    Science.gov (United States)

    Oxenham, Andrew J

    2018-01-04

    Auditory perception is our main gateway to communication with others via speech and music, and it also plays an important role in alerting and orienting us to new events. This review provides an overview of selected topics pertaining to the perception and neural coding of sound, starting with the first stage of filtering in the cochlea and its profound impact on perception. The next topic, pitch, has been debated for millennia, but recent technical and theoretical developments continue to provide us with new insights. Cochlear filtering and pitch both play key roles in our ability to parse the auditory scene, enabling us to attend to one auditory object or stream while ignoring others. An improved understanding of the basic mechanisms of auditory perception will aid us in the quest to tackle the increasingly important problem of hearing loss in our aging population.

  11. Neural Code-Neural Self-information Theory on How Cell-Assembly Code Rises from Spike Time and Neuronal Variability.

    Science.gov (United States)

    Li, Meng; Tsien, Joe Z

    2017-01-01

    A major stumbling block to cracking the real-time neural code is neuronal variability - neurons discharge spikes with enormous variability not only across trials within the same experiments but also in resting states. Such variability is widely regarded as a noise which is often deliberately averaged out during data analyses. In contrast to such a dogma, we put forth the Neural Self-Information Theory that neural coding is operated based on the self-information principle under which variability in the time durations of inter-spike-intervals (ISI), or neuronal silence durations, is self-tagged with discrete information. As the self-information processor, each ISI carries a certain amount of information based on its variability-probability distribution; higher-probability ISIs which reflect the balanced excitation-inhibition ground state convey minimal information, whereas lower-probability ISIs which signify rare-occurrence surprisals in the form of extremely transient or prolonged silence carry most information. These variable silence durations are naturally coupled with intracellular biochemical cascades, energy equilibrium and dynamic regulation of protein and gene expression levels. As such, this silence variability-based self-information code is completely intrinsic to the neurons themselves, with no need for outside observers to set any reference point as typically used in the rate code, population code and temporal code models. Moreover, temporally coordinated ISI surprisals across cell population can inherently give rise to robust real-time cell-assembly codes which can be readily sensed by the downstream neural clique assemblies. One immediate utility of this self-information code is a general decoding strategy to uncover a variety of cell-assembly patterns underlying external and internal categorical or continuous variables in an unbiased manner.

  12. Triplet correlations among similarly tuned cells impact population coding

    Directory of Open Access Journals (Sweden)

    Natasha Alexandra Cayco Gajic

    2015-05-01

    Full Text Available Which statistical features of spiking activity matter for how stimuli are encoded in neural populations? A vast body of work has explored how firing rates in individual cells and correlations in the spikes of cell pairs impact coding. Recent experiments have shown evidence for the existence of higher-order spiking correlations, which describe simultaneous firing in triplets and larger ensembles of cells; however, little is known about their impact on encoded stimulus information. Here, we take a first step toward closing this gap. We vary triplet correlations in small (approximately 10 cell neural populations while keeping single cell and pairwise statistics fixed at typically reported values. This connection with empirically observed lower-order statistics important, as it places strong constraints on the level of triplet correlations that can occur. For each value of triplet correlations, we estimate the performance of the neural population on a two-stimulus discrimination task. We find that the allowed changes in the level of triplet correlations can significantly enhance coding, in particular if triplet correlations differ for the two stimuli. In this scenario, triplet correlations must be included in order to accurately quantify the functionality of neural populations. When both stimuli elicit similar triplet correlations, however, pairwise models provide relatively accurate descriptions of coding accuracy. We explain our findings geometrically via the skew that triplet correlations induce in population-wide distributions of neural responses. Finally, we calculate how many samples are necessary to accurately measure spiking correlations of this type, providing an estimate of the necessary recording times in future experiments.

  13. Stimulus reference frame and neural coding precision

    Czech Academy of Sciences Publication Activity Database

    Košťál, Lubomír

    2016-01-01

    Roč. 71, Apr 2016 (2016), s. 22-27 ISSN 0022-2496 R&D Projects: GA ČR(CZ) GA15-08066S Institutional support: RVO:67985823 Keywords : Fisher information * coding accuracy * measurement scale * Jeffreys prior Subject RIV: FH - Neurology Impact factor: 1.377, year: 2016

  14. Noise shaping in neural populations.

    Science.gov (United States)

    Avila Akerberg, Oscar; Chacron, Maurice J

    2009-01-01

    Many neurons display intrinsic interspike interval correlations in their spike trains. However, the effects of such correlations on information transmission in neural populations are not well understood. We quantified signal processing using linear response theory supported by numerical simulations in networks composed of two different models: One model generates a renewal process where interspike intervals are not correlated while the other generates a nonrenewal process where subsequent interspike intervals are negatively correlated. Our results show that the fractional rate of increase in information rate as a function of network size and stimulus intensity is lower for the nonrenewal model than for the renewal one. We show that this is mostly due to the lower amount of effective noise in the nonrenewal model. We also show the surprising result that coupling has opposite effects in renewal and nonrenewal networks: Excitatory (inhibitory coupling) will decrease (increase) the information rate in renewal networks while inhibitory (excitatory coupling) will decrease (increase) the information rate in nonrenewal networks. We discuss these results and their applicability to other classes of excitable systems.

  15. Optimal attentional modulation of neural population

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    Ali eBorji

    2014-03-01

    Full Text Available Top-down attention has often been separately studied in the contexts of eitheroptimal population coding or biasing of visual search. Yet, both are intimatelylinked, as they entail optimally modulating sensory variables in neural populationsaccording to top-down goals. Designing experiments to probe top-down attentionalmodulation is difficult because non-linear population dynamics are hardto predict in the absence of a concise theoretical framework. Here, we describea unified framework that encompasses both contexts. Our work sheds light ontothe ongoing debate on whether attention modulates neural response gain, tuningwidth, and/or preferred feature. We evaluate the framework by conducting simulationsfor two tasks: 1 classification (discrimination of two stimuli sa and sband 2 searching for a target T among distractors D. Results demonstrate that allof gain, tuning, and preferred feature modulation happen to different extents, dependingon stimulus conditions and task demands. The theoretical analysis showsthat task difficulty (linked to difference D between sa and sb, or T and D is acrucial factor in optimal modulation, with different effects in discrimination vs.search. Further, our framework allows us to quantify the relative utility of neuralparameters. In easy tasks (when D is large compared to the density of the neuralpopulation, modulating gains and preferred features is sufficient to yield nearlyoptimal performance; however, in difficult tasks (smaller D, modulating tuningwidth becomes necessary to improve performance. This suggests that the conflictingreports from different experimental studies may be due to differences intasks and in their difficulties. We further propose future electrophysiology experimentsto observe different types of attentional modulation in a same neuron.

  16. Synchrony and neural coding in cerebellar circuits

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    Abigail L Person

    2012-12-01

    Full Text Available The cerebellum regulates complex movements and is also implicated in cognitive tasks, and cerebellar dysfunction is consequently associated not only with movement disorders, but also with conditions like autism and dyslexia. How information is encoded by specific cerebellar firing patterns remains debated, however. A central question is how the cerebellar cortex transmits its integrated output to the cerebellar nuclei via GABAergic synapses from Purkinje neurons. Possible answers come from accumulating evidence that subsets of Purkinje cells synchronize their firing during behaviors that require the cerebellum. Consistent with models predicting that coherent activity of inhibitory networks has the capacity to dictate firing patterns of target neurons, recent experimental work supports the idea that inhibitory synchrony may regulate the response of cerebellar nuclear cells to Purkinje inputs, owing to the interplay between unusually fast inhibitory synaptic responses and high rates of intrinsic activity. Data from multiple laboratories lead to a working hypothesis that synchronous inhibitory input from Purkinje cells can set the timing and rate of action potentials produced by cerebellar nuclear cells, thereby relaying information out of the cerebellum. If so, then changing spatiotemporal patterns of Purkinje activity would allow different subsets of inhibitory neurons to control cerebellar output at different times. Here we explore the evidence for and against the idea that a synchrony code defines, at least in part, the input-output function between the cerebellar cortex and nuclei. We consider the literature on the existence of simple spike synchrony, convergence of Purkinje neurons onto nuclear neurons, and intrinsic properties of nuclear neurons that contribute to responses to inhibition. Finally, we discuss factors that may disrupt or modulate a synchrony code and describe the potential contributions of inhibitory synchrony to other motor

  17. Code generation: a strategy for neural network simulators.

    Science.gov (United States)

    Goodman, Dan F M

    2010-10-01

    We demonstrate a technique for the design of neural network simulation software, runtime code generation. This technique can be used to give the user complete flexibility in specifying the mathematical model for their simulation in a high level way, along with the speed of code written in a low level language such as C+ +. It can also be used to write code only once but target different hardware platforms, including inexpensive high performance graphics processing units (GPUs). Code generation can be naturally combined with computer algebra systems to provide further simplification and optimisation of the generated code. The technique is quite general and could be applied to any simulation package. We demonstrate it with the 'Brian' simulator ( http://www.briansimulator.org ).

  18. Understanding the Implications of Neural Population Activity on Behavior

    Science.gov (United States)

    Briguglio, John

    Learning how neural activity in the brain leads to the behavior we exhibit is one of the fundamental questions in Neuroscience. In this dissertation, several lines of work are presented to that use principles of neural coding to understand behavior. In one line of work, we formulate the efficient coding hypothesis in a non-traditional manner in order to test human perceptual sensitivity to complex visual textures. We find a striking agreement between how variable a particular texture signal is and how sensitive humans are to its presence. This reveals that the efficient coding hypothesis is still a guiding principle for neural organization beyond the sensory periphery, and that the nature of cortical constraints differs from the peripheral counterpart. In another line of work, we relate frequency discrimination acuity to neural responses from auditory cortex in mice. It has been previously observed that optogenetic manipulation of auditory cortex, in addition to changing neural responses, evokes changes in behavioral frequency discrimination. We are able to account for changes in frequency discrimination acuity on an individual basis by examining the Fisher information from the neural population with and without optogenetic manipulation. In the third line of work, we address the question of what a neural population should encode given that its inputs are responses from another group of neurons. Drawing inspiration from techniques in machine learning, we train Deep Belief Networks on fake retinal data and show the emergence of Garbor-like filters, reminiscent of responses in primary visual cortex. In the last line of work, we model the state of a cortical excitatory-inhibitory network during complex adaptive stimuli. Using a rate model with Wilson-Cowan dynamics, we demonstrate that simple non-linearities in the signal transferred from inhibitory to excitatory neurons can account for real neural recordings taken from auditory cortex. This work establishes and tests

  19. Pulse coded biologically motivated neural-type MOS circuits

    Science.gov (United States)

    1991-11-01

    This project has two aspects, one for ONR and one for AFOSR. The ONR portion is devoted to obtaining hardware implementations for the physiological representations used in the program SYNETSIM developed by the neurophysiologist Dr. D. Hartline of Bekesy Laboratories. The AFOSR portion is for evaluation capabilities of the pulse code philosophy of neural networks. On the ONR portion of the research, several chips have been fabricated for SYNETSIM pools and a neural arithmetic unit based upon the pools. Also, a number of modifications have been made to SYNETSIM to make it a much more user-friendly program. Several papers have been presented at international conferences and the DRIVER module is under continued investigation for VLSI realization. The means to implement long term potentiation are also under continued investigation. On the AFOSR portion, a means of realizing any Hopfield-type network via pulse coded circuits was obtained.

  20. Population Coding in Sparsely Connected Networks of Noisy Neurons

    Directory of Open Access Journals (Sweden)

    Bryan Patrick Tripp

    2012-05-01

    Full Text Available This study examines the relationship between population coding and spatial connection statistics in networks of noisy neurons. Encoding of sensory information in the neocortex is thought to require coordinated neural populations, because individual cortical neurons respond to a wide range of stimuli, and exhibit highly variable spiking in response to repeated stimuli. Population coding is rooted in network structure, because cortical neurons receive information only from other neurons, and because the information they encode must be decoded by other neurons, if it is to affect behaviour. However, population coding theory has often ignored network structure, or assumed discrete, fully-connected populations (in contrast with the sparsely connected, continuous sheet of the cortex. In this study, we model a sheet of cortical neurons with sparse, primarily local connections, and find that a network with this structure can encode multiple internal state variables with high signal-to-noise ratio. However, in our model, although connection probability varies with the distance between neurons, we find that the connections cannot be instantiated at random according to these probabilities, but must have additional structure if information is to be encoded with high fidelity.

  1. Bitter taste stimuli induce differential neural codes in mouse brain.

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    David M Wilson

    Full Text Available A growing literature suggests taste stimuli commonly classified as "bitter" induce heterogeneous neural and perceptual responses. Here, the central processing of bitter stimuli was studied in mice with genetically controlled bitter taste profiles. Using these mice removed genetic heterogeneity as a factor influencing gustatory neural codes for bitter stimuli. Electrophysiological activity (spikes was recorded from single neurons in the nucleus tractus solitarius during oral delivery of taste solutions (26 total, including concentration series of the bitter tastants quinine, denatonium benzoate, cycloheximide, and sucrose octaacetate (SOA, presented to the whole mouth for 5 s. Seventy-nine neurons were sampled; in many cases multiple cells (2 to 5 were recorded from a mouse. Results showed bitter stimuli induced variable gustatory activity. For example, although some neurons responded robustly to quinine and cycloheximide, others displayed concentration-dependent activity (p<0.05 to quinine but not cycloheximide. Differential activity to bitter stimuli was observed across multiple neurons recorded from one animal in several mice. Across all cells, quinine and denatonium induced correlated spatial responses that differed (p<0.05 from those to cycloheximide and SOA. Modeling spatiotemporal neural ensemble activity revealed responses to quinine/denatonium and cycloheximide/SOA diverged during only an early, at least 1 s wide period of the taste response. Our findings highlight how temporal features of sensory processing contribute differences among bitter taste codes and build on data suggesting heterogeneity among "bitter" stimuli, data that challenge a strict monoguesia model for the bitter quality.

  2. Neural Coding and the Basic Law of Psychophysics

    Science.gov (United States)

    JOHNSON, KENNETH O.; HSIAO, STEVEN S.; YOSHIOKA, TAKASHI

    2007-01-01

    There have been three main ideas about the basic law of psychophysics. In 1860, Fechner used Weber’s law to infer that the subjective sense of intensity is related to the physical intensity of a stimulus by a logarithmic function (the Weber-Fechner law). A hundred years later, Stevens refuted Fechner’s law by showing that direct reports of subjective intensity are related to the physical intensity of stimuli by a power law. MacKay soon showed, however, that the logarithmic and power laws are indistinguishable without examining the underlying neural mechanisms. Mountcastle and his colleagues did so, and, on the basis of transducer functions obeying power laws, inferred that subjective intensity must be related linearly to the neural coding measure on which it is based. In this review, we discuss these issues and we review a series of studies aimed at the neural mechanisms of a very complex form of subjective experience—the experience of roughness produced by a textured surface. The results, which are independent of any assumptions about the form of the psychophysical law, support the idea that the basic law of psychophysics is linearity between subjective experience and the neural activity on which it is based. PMID:11954556

  3. ANNA: A Convolutional Neural Network Code for Spectroscopic Analysis

    Science.gov (United States)

    Lee-Brown, Donald; Anthony-Twarog, Barbara J.; Twarog, Bruce A.

    2018-01-01

    We present ANNA, a Python-based convolutional neural network code for the automated analysis of stellar spectra. ANNA provides a flexible framework that allows atmospheric parameters such as temperature and metallicity to be determined with accuracies comparable to those of established but less efficient techniques. ANNA performs its parameterization extremely quickly; typically several thousand spectra can be analyzed in less than a second. Additionally, the code incorporates features which greatly speed up the training process necessary for the neural network to measure spectra accurately, resulting in a tool that can easily be run on a single desktop or laptop computer. Thus, ANNA is useful in an era when spectrographs increasingly have the capability to collect dozens to hundreds of spectra each night. This talk will cover the basic features included in ANNA and demonstrate its performance in two use cases: an open cluster abundance analysis involving several hundred spectra, and a metal-rich field star study. Applicability of the code to large survey datasets will also be discussed.

  4. Optimal population codes for space: grid cells outperform place cells.

    Science.gov (United States)

    Mathis, Alexander; Herz, Andreas V M; Stemmler, Martin

    2012-09-01

    Rodents use two distinct neuronal coordinate systems to estimate their position: place fields in the hippocampus and grid fields in the entorhinal cortex. Whereas place cells spike at only one particular spatial location, grid cells fire at multiple sites that correspond to the points of an imaginary hexagonal lattice. We study how to best construct place and grid codes, taking the probabilistic nature of neural spiking into account. Which spatial encoding properties of individual neurons confer the highest resolution when decoding the animal's position from the neuronal population response? A priori, estimating a spatial position from a grid code could be ambiguous, as regular periodic lattices possess translational symmetry. The solution to this problem requires lattices for grid cells with different spacings; the spatial resolution crucially depends on choosing the right ratios of these spacings across the population. We compute the expected error in estimating the position in both the asymptotic limit, using Fisher information, and for low spike counts, using maximum likelihood estimation. Achieving high spatial resolution and covering a large range of space in a grid code leads to a trade-off: the best grid code for spatial resolution is built of nested modules with different spatial periods, one inside the other, whereas maximizing the spatial range requires distinct spatial periods that are pairwisely incommensurate. Optimizing the spatial resolution predicts two grid cell properties that have been experimentally observed. First, short lattice spacings should outnumber long lattice spacings. Second, the grid code should be self-similar across different lattice spacings, so that the grid field always covers a fixed fraction of the lattice period. If these conditions are satisfied and the spatial "tuning curves" for each neuron span the same range of firing rates, then the resolution of the grid code easily exceeds that of the best possible place code with the

  5. Neural coding of sound envelope structure in songbirds.

    Science.gov (United States)

    Boari, Santiago; Amador, Ana

    2017-12-12

    Songbirds are a well-established animal model to study the neural basis of learning, perception and production of complex vocalizations. In this system, telencephalic neurons in HVC present a state-dependent, highly selective response to auditory presentations of the bird's own song (BOS). This property provides an opportunity to study the neural code behind a complex motor behavior. In this work, we explore whether changes in the temporal structure of the sound envelope can drive changes in the neural responses of highly selective HVC units. We generated an envelope-modified BOS (MOD) by reversing each syllable's envelope but leaving the overall temporal structure of syllable spectra unchanged, which resulted in a subtle modification for each song syllable. We conducted in vivo electrophysiological recordings of HVC neurons in anaesthetized zebra finches (Taeniopygia guttata). Units analyzed presented a high BOS selectivity and lower response to MOD, but preserved the profile response shape. These results show that the temporal evolution of the sound envelope is being sensed by the avian song system and suggest that the biomechanical properties of the vocal apparatus could play a role in enhancing subtle sound differences.

  6. A virtual retina for studying population coding.

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    Illya Bomash

    Full Text Available At every level of the visual system - from retina to cortex - information is encoded in the activity of large populations of cells. The populations are not uniform, but contain many different types of cells, each with its own sensitivities to visual stimuli. Understanding the roles of the cell types and how they work together to form collective representations has been a long-standing goal. This goal, though, has been difficult to advance, and, to a large extent, the reason is data limitation. Large numbers of stimulus/response relationships need to be explored, and obtaining enough data to examine even a fraction of them requires a great deal of experiments and animals. Here we describe a tool for addressing this, specifically, at the level of the retina. The tool is a data-driven model of retinal input/output relationships that is effective on a broad range of stimuli - essentially, a virtual retina. The results show that it is highly reliable: (1 the model cells carry the same amount of information as their real cell counterparts, (2 the quality of the information is the same - that is, the posterior stimulus distributions produced by the model cells closely match those of their real cell counterparts, and (3 the model cells are able to make very reliable predictions about the functions of the different retinal output cell types, as measured using Bayesian decoding (electrophysiology and optomotor performance (behavior. In sum, we present a new tool for studying population coding and test it experimentally. It provides a way to rapidly probe the actions of different cell classes and develop testable predictions. The overall aim is to build constrained theories about population coding and keep the number of experiments and animals to a minimum.

  7. Biological and bionic hands: natural neural coding and artificial perception.

    Science.gov (United States)

    Bensmaia, Sliman J

    2015-09-19

    The first decade and a half of the twenty-first century brought about two major innovations in neuroprosthetics: the development of anthropomorphic robotic limbs that replicate much of the function of a native human arm and the refinement of algorithms that decode intended movements from brain activity. However, skilled manipulation of objects requires somatosensory feedback, for which vision is a poor substitute. For upper-limb neuroprostheses to be clinically viable, they must therefore provide for the restoration of touch and proprioception. In this review, I discuss efforts to elicit meaningful tactile sensations through stimulation of neurons in somatosensory cortex. I focus on biomimetic approaches to sensory restoration, which leverage our current understanding about how information about grasped objects is encoded in the brain of intact individuals. I argue that not only can sensory neuroscience inform the development of sensory neuroprostheses, but also that the converse is true: stimulating the brain offers an exceptional opportunity to causally interrogate neural circuits and test hypotheses about natural neural coding.

  8. Efficient sensory encoding and Bayesian inference with heterogeneous neural populations.

    Science.gov (United States)

    Ganguli, Deep; Simoncelli, Eero P

    2014-10-01

    The efficient coding hypothesis posits that sensory systems maximize information transmitted to the brain about the environment. We develop a precise and testable form of this hypothesis in the context of encoding a sensory variable with a population of noisy neurons, each characterized by a tuning curve. We parameterize the population with two continuous functions that control the density and amplitude of the tuning curves, assuming that the tuning widths vary inversely with the cell density. This parameterization allows us to solve, in closed form, for the information-maximizing allocation of tuning curves as a function of the prior probability distribution of sensory variables. For the optimal population, the cell density is proportional to the prior, such that more cells with narrower tuning are allocated to encode higher-probability stimuli and that each cell transmits an equal portion of the stimulus probability mass. We also compute the stimulus discrimination capabilities of a perceptual system that relies on this neural representation and find that the best achievable discrimination thresholds are inversely proportional to the sensory prior. We examine how the prior information that is implicitly encoded in the tuning curves of the optimal population may be used for perceptual inference and derive a novel decoder, the Bayesian population vector, that closely approximates a Bayesian least-squares estimator that has explicit access to the prior. Finally, we generalize these results to sigmoidal tuning curves, correlated neural variability, and a broader class of objective functions. These results provide a principled embedding of sensory prior information in neural populations and yield predictions that are readily testable with environmental, physiological, and perceptual data.

  9. Deciphering neuronal population codes for acute thermal pain

    Science.gov (United States)

    Chen, Zhe; Zhang, Qiaosheng; Phuong Sieu Tong, Ai; Manders, Toby R.; Wang, Jing

    2017-06-01

    Objective. Pain is defined as an unpleasant sensory and emotional experience associated with actual or potential tissue damage, or described in terms of such damage. Current pain research mostly focuses on molecular and synaptic changes at the spinal and peripheral levels. However, a complete understanding of pain mechanisms requires the physiological study of the neocortex. Our goal is to apply a neural decoding approach to read out the onset of acute thermal pain signals, which can be used for brain-machine interface. Approach. We used micro wire arrays to record ensemble neuronal activities from the primary somatosensory cortex (S1) and anterior cingulate cortex (ACC) in freely behaving rats. We further investigated neural codes for acute thermal pain at both single-cell and population levels. To detect the onset of acute thermal pain signals, we developed a novel latent state-space framework to decipher the sorted or unsorted S1 and ACC ensemble spike activities, which reveal information about the onset of pain signals. Main results. The state space analysis allows us to uncover a latent state process that drives the observed ensemble spike activity, and to further detect the ‘neuronal threshold’ for acute thermal pain on a single-trial basis. Our method achieved good detection performance in sensitivity and specificity. In addition, our results suggested that an optimal strategy for detecting the onset of acute thermal pain signals may be based on combined evidence from S1 and ACC population codes. Significance. Our study is the first to detect the onset of acute pain signals based on neuronal ensemble spike activity. It is important from a mechanistic viewpoint as it relates to the significance of S1 and ACC activities in the regulation of the acute pain onset.

  10. Direction-Selective Circuits Shape Noise to Ensure a Precise Population Code.

    Science.gov (United States)

    Zylberberg, Joel; Cafaro, Jon; Turner, Maxwell H; Shea-Brown, Eric; Rieke, Fred

    2016-01-20

    Neural responses are noisy, and circuit structure can correlate this noise across neurons. Theoretical studies show that noise correlations can have diverse effects on population coding, but these studies rarely explore stimulus dependence of noise correlations. Here, we show that noise correlations in responses of ON-OFF direction-selective retinal ganglion cells are strongly stimulus dependent, and we uncover the circuit mechanisms producing this stimulus dependence. A population model based on these mechanistic studies shows that stimulus-dependent noise correlations improve the encoding of motion direction 2-fold compared to independent noise. This work demonstrates a mechanism by which a neural circuit effectively shapes its signal and noise in concert, minimizing corruption of signal by noise. Finally, we generalize our findings beyond direction coding in the retina and show that stimulus-dependent correlations will generally enhance information coding in populations of diversely tuned neurons. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?

    Science.gov (United States)

    Brinkman, Braden A W; Weber, Alison I; Rieke, Fred; Shea-Brown, Eric

    2016-10-01

    Neural circuits reliably encode and transmit signals despite the presence of noise at multiple stages of processing. The efficient coding hypothesis, a guiding principle in computational neuroscience, suggests that a neuron or population of neurons allocates its limited range of responses as efficiently as possible to best encode inputs while mitigating the effects of noise. Previous work on this question relies on specific assumptions about where noise enters a circuit, limiting the generality of the resulting conclusions. Here we systematically investigate how noise introduced at different stages of neural processing impacts optimal coding strategies. Using simulations and a flexible analytical approach, we show how these strategies depend on the strength of each noise source, revealing under what conditions the different noise sources have competing or complementary effects. We draw two primary conclusions: (1) differences in encoding strategies between sensory systems-or even adaptational changes in encoding properties within a given system-may be produced by changes in the structure or location of neural noise, and (2) characterization of both circuit nonlinearities as well as noise are necessary to evaluate whether a circuit is performing efficiently.

  12. How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?

    Directory of Open Access Journals (Sweden)

    Braden A W Brinkman

    2016-10-01

    Full Text Available Neural circuits reliably encode and transmit signals despite the presence of noise at multiple stages of processing. The efficient coding hypothesis, a guiding principle in computational neuroscience, suggests that a neuron or population of neurons allocates its limited range of responses as efficiently as possible to best encode inputs while mitigating the effects of noise. Previous work on this question relies on specific assumptions about where noise enters a circuit, limiting the generality of the resulting conclusions. Here we systematically investigate how noise introduced at different stages of neural processing impacts optimal coding strategies. Using simulations and a flexible analytical approach, we show how these strategies depend on the strength of each noise source, revealing under what conditions the different noise sources have competing or complementary effects. We draw two primary conclusions: (1 differences in encoding strategies between sensory systems-or even adaptational changes in encoding properties within a given system-may be produced by changes in the structure or location of neural noise, and (2 characterization of both circuit nonlinearities as well as noise are necessary to evaluate whether a circuit is performing efficiently.

  13. Dual roles for spike signaling in cortical neural populations

    Directory of Open Access Journals (Sweden)

    Dana eBallard

    2011-06-01

    Full Text Available A prominent feature of signaling in cortical neurons is that of randomness in the action potential. The output of a typical pyramidal cell can be well fit with a Poisson model, and variations in the Poisson rate repeatedly have been shown to be correlated with stimuli. However while the rate provides a very useful characterization of neural spike data, it may not be the most fundamental description of the signaling code. Recent data showing γ frequency range multi-cell action potential correlations, together with spike timing dependent plasticity, are spurring a re-examination of the classical model, since precise timing codes imply that the generation of spikes is essentially deterministic. Could the observed Poisson randomness and timing determinism reflect two separate modes of communication, or do they somehow derive from a single process? We investigate in a timing-based model whether the apparent incompatibility between these probabilistic and deterministic observations may be resolved by examining how spikes could be used in the underlying neural circuits. The crucial component of this model draws on dual roles for spike signaling. In learning receptive fields from ensembles of inputs, spikes need to behave probabilistically, whereas for fast signaling of individual stimuli, the spikes need to behave deterministically. Our simulations show that this combination is possible if deterministic signals using γ latency coding are probabilistically routed through different members of a cortical cell population at different times. This model exhibits standard features characteristic of Poisson models such as orientation tuning post-stimulus histograms and exponential interval histograms. In addition it makes testable predictions that follow from the γ latency coding.

  14. Mapping a complete neural population in the retina.

    Science.gov (United States)

    Marre, Olivier; Amodei, Dario; Deshmukh, Nikhil; Sadeghi, Kolia; Soo, Frederick; Holy, Timothy E; Berry, Michael J

    2012-10-24

    Recording simultaneously from essentially all of the relevant neurons in a local circuit is crucial to understand how they collectively represent information. Here we show that the combination of a large, dense multielectrode array and a novel, mostly automated spike-sorting algorithm allowed us to record simultaneously from a highly overlapping population of >200 ganglion cells in the salamander retina. By combining these methods with labeling and imaging, we showed that up to 95% of the ganglion cells over the area of the array were recorded. By measuring the coverage of visual space by the receptive fields of the recorded cells, we concluded that our technique captured a neural population that forms an essentially complete representation of a region of visual space. This completeness allowed us to determine the spatial layout of different cell types as well as identify a novel group of ganglion cells that responded reliably to a set of naturalistic and artificial stimuli but had no measurable receptive field. Thus, our method allows unprecedented access to the complete neural representation of visual information, a crucial step for the understanding of population coding in sensory systems.

  15. Neural coding of movement direction in the healthy human brain.

    Directory of Open Access Journals (Sweden)

    Christopher D Cowper-Smith

    2010-10-01

    Full Text Available Neurophysiological studies in monkeys show that activity of neurons in primary cortex (M1, pre-motor cortex (PMC, and cerebellum varies systematically with the direction of reaching movements. These neurons exhibit preferred direction tuning, where the level of neural activity is highest when movements are made in the preferred direction (PD, and gets progressively lower as movements are made at increasing degrees of offset from the PD. Using a functional magnetic resonance imaging adaptation (fMRI-A paradigm, we show that PD coding does exist in regions of the human motor system that are homologous to those observed in non-human primates. Consistent with predictions of the PD model, we show adaptation (i.e., a lower level of the blood oxygen level dependent (BOLD time-course signal in M1, PMC, SMA, and cerebellum when consecutive wrist movements were made in the same direction (0° offset relative to movements offset by 90° or 180°. The BOLD signal in dorsolateral prefrontal cortex adapted equally in all movement offset conditions, mitigating against the possibility that the present results are the consequence of differential task complexity or attention to action in each movement offset condition.

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

    Directory of Open Access Journals (Sweden)

    Julien eVitay

    2015-07-01

    Full Text Available 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.

  17. Retinal metric: a stimulus distance measure derived from population neural responses.

    Science.gov (United States)

    Tkačik, Gašper; Granot-Atedgi, Einat; Segev, Ronen; Schneidman, Elad

    2013-02-01

    The ability of an organism to distinguish between various stimuli is limited by the structure and noise in the population code of its sensory neurons. Here we infer a distance measure on the stimulus space directly from the recorded activity of 100 neurons in the salamander retina. In contrast to previously used measures of stimulus similarity, this "neural metric" tells us how distinguishable a pair of stimulus clips is to the retina, based on the similarity between the induced distributions of population responses. We show that the retinal distance strongly deviates from Euclidean, or any static metric, yet has a simple structure: we identify the stimulus features that the neural population is jointly sensitive to, and show the support-vector-machine-like kernel function relating the stimulus and neural response spaces. We show that the non-Euclidean nature of the retinal distance has important consequences for neural decoding.

  18. Simply Coded Evolutionary Artificial Neural Networks on a Mobile Robot Control Problem

    Science.gov (United States)

    Katada, Yoshiaki; Hidaka, Takuya

    One of the advantages of evolutionary robotics over other approaches in embodied cognitive science would be its parallel population search. Due to the population search, it takes a long time to evaluate all robot in a real environment. Thus, such techniques as to shorten the time are required for real robots to evolve in a real environment. This paper proposes to use simply coded evolutionary artificial neural networks for mobile robot control to make genetic search space as small as possible and investigates the performance of them using simulated and real robots. Two types of genetic algorithm (GA) are employed, one is the standard GA and the other is an extended GA, to achieve higher final fitnesses. The results suggest the benefits of the proposed method.

  19. Neural coding of cooperative vs. affective human interactions: 150 ms to code the action's purpose.

    Directory of Open Access Journals (Sweden)

    Alice Mado Proverbio

    Full Text Available The timing and neural processing of the understanding of social interactions was investigated by presenting scenes in which 2 people performed cooperative or affective actions. While the role of the human mirror neuron system (MNS in understanding actions and intentions is widely accepted, little is known about the time course within which these aspects of visual information are automatically extracted. Event-Related Potentials were recorded in 35 university students perceiving 260 pictures of cooperative (e.g., 2 people dragging a box or affective (e.g., 2 people smiling and holding hands interactions. The action's goal was automatically discriminated at about 150-170 ms, as reflected by occipito/temporal N170 response. The swLORETA inverse solution revealed the strongest sources in the right posterior cingulate cortex (CC for affective actions and in the right pSTS for cooperative actions. It was found a right hemispheric asymmetry that involved the fusiform gyrus (BA37, the posterior CC, and the medial frontal gyrus (BA10/11 for the processing of affective interactions, particularly in the 155-175 ms time window. In a later time window (200-250 ms the processing of cooperative interactions activated the left post-central gyrus (BA3, the left parahippocampal gyrus, the left superior frontal gyrus (BA10, as well as the right premotor cortex (BA6. Women showed a greater response discriminative of the action's goal compared to men at P300 and anterior negativity level (220-500 ms. These findings might be related to a greater responsiveness of the female vs. male MNS. In addition, the discriminative effect was bilateral in women and was smaller and left-sided in men. Evidence was provided that perceptually similar social interactions are discriminated on the basis of the agents' intentions quite early in neural processing, differentially activating regions devoted to face/body/action coding, the limbic system and the MNS.

  20. Spike-based population coding and working memory.

    Directory of Open Access Journals (Sweden)

    Martin Boerlin

    2011-02-01

    Full Text Available Compelling behavioral evidence suggests that humans can make optimal decisions despite the uncertainty inherent in perceptual or motor tasks. A key question in neuroscience is how populations of spiking neurons can implement such probabilistic computations. In this article, we develop a comprehensive framework for optimal, spike-based sensory integration and working memory in a dynamic environment. We propose that probability distributions are inferred spike-per-spike in recurrently connected networks of integrate-and-fire neurons. As a result, these networks can combine sensory cues optimally, track the state of a time-varying stimulus and memorize accumulated evidence over periods much longer than the time constant of single neurons. Importantly, we propose that population responses and persistent working memory states represent entire probability distributions and not only single stimulus values. These memories are reflected by sustained, asynchronous patterns of activity which make relevant information available to downstream neurons within their short time window of integration. Model neurons act as predictive encoders, only firing spikes which account for new information that has not yet been signaled. Thus, spike times signal deterministically a prediction error, contrary to rate codes in which spike times are considered to be random samples of an underlying firing rate. As a consequence of this coding scheme, a multitude of spike patterns can reliably encode the same information. This results in weakly correlated, Poisson-like spike trains that are sensitive to initial conditions but robust to even high levels of external neural noise. This spike train variability reproduces the one observed in cortical sensory spike trains, but cannot be equated to noise. On the contrary, it is a consequence of optimal spike-based inference. In contrast, we show that rate-based models perform poorly when implemented with stochastically spiking neurons.

  1. Dual Coding Theory Explains Biphasic Collective Computation in Neural Decision-Making.

    Science.gov (United States)

    Daniels, Bryan C; Flack, Jessica C; Krakauer, David C

    2017-01-01

    A central question in cognitive neuroscience is how unitary, coherent decisions at the whole organism level can arise from the distributed behavior of a large population of neurons with only partially overlapping information. We address this issue by studying neural spiking behavior recorded from a multielectrode array with 169 channels during a visual motion direction discrimination task. It is well known that in this task there are two distinct phases in neural spiking behavior. Here we show Phase I is a distributed or incompressible phase in which uncertainty about the decision is substantially reduced by pooling information from many cells. Phase II is a redundant or compressible phase in which numerous single cells contain all the information present at the population level in Phase I, such that the firing behavior of a single cell is enough to predict the subject's decision. Using an empirically grounded dynamical modeling framework, we show that in Phase I large cell populations with low redundancy produce a slow timescale of information aggregation through critical slowing down near a symmetry-breaking transition. Our model indicates that increasing collective amplification in Phase II leads naturally to a faster timescale of information pooling and consensus formation. Based on our results and others in the literature, we propose that a general feature of collective computation is a "coding duality" in which there are accumulation and consensus formation processes distinguished by different timescales.

  2. Neural Network Approach to Locating Cryptography in Object Code

    Energy Technology Data Exchange (ETDEWEB)

    Jason L. Wright; Milos Manic

    2009-09-01

    Finding and identifying cryptography is a growing concern in the malware analysis community. In this paper, artificial neural networks are used to classify functional blocks from a disassembled program as being either cryptography related or not. The resulting system, referred to as NNLC (Neural Net for Locating Cryptography) is presented and results of applying this system to various libraries are described.

  3. A neutron spectrum unfolding computer code based on artificial neural networks

    Science.gov (United States)

    Ortiz-Rodríguez, J. M.; Reyes Alfaro, A.; Reyes Haro, A.; Cervantes Viramontes, J. M.; Vega-Carrillo, H. R.

    2014-02-01

    The Bonner Spheres Spectrometer consists of a thermal neutron sensor placed at the center of a number of moderating polyethylene spheres of different diameters. From the measured readings, information can be derived about the spectrum of the neutron field where measurements were made. Disadvantages of the Bonner system are the weight associated with each sphere and the need to sequentially irradiate the spheres, requiring long exposure periods. Provided a well-established response matrix and adequate irradiation conditions, the most delicate part of neutron spectrometry, is the unfolding process. The derivation of the spectral information is not simple because the unknown is not given directly as a result of the measurements. The drawbacks associated with traditional unfolding procedures have motivated the need of complementary approaches. Novel methods based on Artificial Intelligence, mainly Artificial Neural Networks, have been widely investigated. In this work, a neutron spectrum unfolding code based on neural nets technology is presented. This code is called Neutron Spectrometry and Dosimetry with Artificial Neural networks unfolding code that was designed in a graphical interface. The core of the code is an embedded neural network architecture previously optimized using the robust design of artificial neural networks methodology. The main features of the code are: easy to use, friendly and intuitive to the user. This code was designed for a Bonner Sphere System based on a 6LiI(Eu) neutron detector and a response matrix expressed in 60 energy bins taken from an International Atomic Energy Agency compilation. The main feature of the code is that as entrance data, for unfolding the neutron spectrum, only seven rate counts measured with seven Bonner spheres are required; simultaneously the code calculates 15 dosimetric quantities as well as the total flux for radiation protection purposes. This code generates a full report with all information of the unfolding in

  4. Mechanisms of Long Non-Coding RNAs in the Assembly and Plasticity of Neural Circuitry.

    Science.gov (United States)

    Wang, Andi; Wang, Junbao; Liu, Ying; Zhou, Yan

    2017-01-01

    The mechanisms underlying development processes and functional dynamics of neural circuits are far from understood. Long non-coding RNAs (lncRNAs) have emerged as essential players in defining identities of neural cells, and in modulating neural activities. In this review, we summarized latest advances concerning roles and mechanisms of lncRNAs in assembly, maintenance and plasticity of neural circuitry, as well as lncRNAs' implications in neurological disorders. We also discussed technical advances and challenges in studying functions and mechanisms of lncRNAs in neural circuitry. Finally, we proposed that lncRNA studies would advance our understanding on how neural circuits develop and function in physiology and disease conditions.

  5. SiNC: Saliency-injected neural codes for representation and efficient retrieval of medical radiographs.

    Science.gov (United States)

    Ahmad, Jamil; Sajjad, Muhammad; Mehmood, Irfan; Baik, Sung Wook

    2017-01-01

    Medical image collections contain a wealth of information which can assist radiologists and medical experts in diagnosis and disease detection for making well-informed decisions. However, this objective can only be realized if efficient access is provided to semantically relevant cases from the ever-growing medical image repositories. In this paper, we present an efficient method for representing medical images by incorporating visual saliency and deep features obtained from a fine-tuned convolutional neural network (CNN) pre-trained on natural images. Saliency detector is employed to automatically identify regions of interest like tumors, fractures, and calcified spots in images prior to feature extraction. Neuronal activation features termed as neural codes from different CNN layers are comprehensively studied to identify most appropriate features for representing radiographs. This study revealed that neural codes from the last fully connected layer of the fine-tuned CNN are found to be the most suitable for representing medical images. The neural codes extracted from the entire image and salient part of the image are fused to obtain the saliency-injected neural codes (SiNC) descriptor which is used for indexing and retrieval. Finally, locality sensitive hashing techniques are applied on the SiNC descriptor to acquire short binary codes for allowing efficient retrieval in large scale image collections. Comprehensive experimental evaluations on the radiology images dataset reveal that the proposed framework achieves high retrieval accuracy and efficiency for scalable image retrieval applications and compares favorably with existing approaches.

  6. SiNC: Saliency-injected neural codes for representation and efficient retrieval of medical radiographs.

    Directory of Open Access Journals (Sweden)

    Jamil Ahmad

    Full Text Available Medical image collections contain a wealth of information which can assist radiologists and medical experts in diagnosis and disease detection for making well-informed decisions. However, this objective can only be realized if efficient access is provided to semantically relevant cases from the ever-growing medical image repositories. In this paper, we present an efficient method for representing medical images by incorporating visual saliency and deep features obtained from a fine-tuned convolutional neural network (CNN pre-trained on natural images. Saliency detector is employed to automatically identify regions of interest like tumors, fractures, and calcified spots in images prior to feature extraction. Neuronal activation features termed as neural codes from different CNN layers are comprehensively studied to identify most appropriate features for representing radiographs. This study revealed that neural codes from the last fully connected layer of the fine-tuned CNN are found to be the most suitable for representing medical images. The neural codes extracted from the entire image and salient part of the image are fused to obtain the saliency-injected neural codes (SiNC descriptor which is used for indexing and retrieval. Finally, locality sensitive hashing techniques are applied on the SiNC descriptor to acquire short binary codes for allowing efficient retrieval in large scale image collections. Comprehensive experimental evaluations on the radiology images dataset reveal that the proposed framework achieves high retrieval accuracy and efficiency for scalable image retrieval applications and compares favorably with existing approaches.

  7. POPCORN: A comparison of binary population synthesis codes

    Science.gov (United States)

    Claeys, J. S. W.; Toonen, S.; Mennekens, N.

    2013-01-01

    We compare the results of three binary population synthesis codes to understand the differences in their results. As a first result we find that when equalizing the assumptions the results are similar. The main differences arise from deviating physical input.

  8. The neural code for auditory space depends on sound frequency and head size in an optimal manner.

    Directory of Open Access Journals (Sweden)

    Nicol S Harper

    Full Text Available A major cue to the location of a sound source is the interaural time difference (ITD-the difference in sound arrival time at the two ears. The neural representation of this auditory cue is unresolved. The classic model of ITD coding, dominant for a half-century, posits that the distribution of best ITDs (the ITD evoking a neuron's maximal response is unimodal and largely within the range of ITDs permitted by head-size. This is often interpreted as a place code for source location. An alternative model, based on neurophysiology in small mammals, posits a bimodal distribution of best ITDs with exquisite sensitivity to ITDs generated by means of relative firing rates between the distributions. Recently, an optimal-coding model was proposed, unifying the disparate features of these two models under the framework of efficient coding by neural populations. The optimal-coding model predicts that distributions of best ITDs depend on head size and sound frequency: for high frequencies and large heads it resembles the classic model, for low frequencies and small head sizes it resembles the bimodal model. The optimal-coding model makes key, yet unobserved, predictions: for many species, including humans, both forms of neural representation are employed, depending on sound frequency. Furthermore, novel representations are predicted for intermediate frequencies. Here, we examine these predictions in neurophysiological data from five mammalian species: macaque, guinea pig, cat, gerbil and kangaroo rat. We present the first evidence supporting these untested predictions, and demonstrate that different representations appear to be employed at different sound frequencies in the same species.

  9. Psychophysiological analyses demonstrate the importance of neural envelope coding for speech perception in noise

    Science.gov (United States)

    Swaminathan, Jayaganesh; Heinz, Michael G.

    2012-01-01

    Understanding speech in noisy environments is often taken for granted; however, this task is particularly challenging for people with cochlear hearing loss, even with hearing aids or cochlear implants. A significant limitation to improving auditory prostheses is our lack of understanding of the neural basis for robust speech perception in noise. Perceptual studies suggest the slowly varying component of the acoustic waveform (envelope, ENV) is sufficient for understanding speech in quiet, but the rapidly varying temporal fine structure (TFS) is important in noise. These perceptual findings have important implications for cochlear implants, which currently only provide ENV; however, neural correlates have been difficult to evaluate due to cochlear transformations between acoustic TFS and recovered neural ENV. Here, we demonstrate the relative contributions of neural ENV and TFS by quantitatively linking neural coding, predicted from a computational auditory-nerve model, with perception of vocoded speech in noise measured from normal-hearing human listeners. Regression models with ENV and TFS coding as independent variables predicted speech identification and phonetic-feature reception at both positive and negative signal-to-noise ratios. We found that 1) neural ENV coding was a primary contributor to speech perception, even in noise, and 2) neural TFS contributed in noise mainly in the presence of neural ENV, but rarely as the primary cue itself. These results suggest neural TFS has less perceptual salience than previously thought due to cochlear signal-processing transformations between TFS and ENV. Because these transformations differ between normal and impaired ears, these findings have important translational implications for auditory prostheses. PMID:22302814

  10. Clustering of neural code words revealed by a first-order phase transition.

    Science.gov (United States)

    Huang, Haiping; Toyoizumi, Taro

    2016-06-01

    A network of neurons in the central nervous system collectively represents information by its spiking activity states. Typically observed states, i.e., code words, occupy only a limited portion of the state space due to constraints imposed by network interactions. Geometrical organization of code words in the state space, critical for neural information processing, is poorly understood due to its high dimensionality. Here, we explore the organization of neural code words using retinal data by computing the entropy of code words as a function of Hamming distance from a particular reference codeword. Specifically, we report that the retinal code words in the state space are divided into multiple distinct clusters separated by entropy-gaps, and that this structure is shared with well-known associative memory networks in a recallable phase. Our analysis also elucidates a special nature of the all-silent state. The all-silent state is surrounded by the densest cluster of code words and located within a reachable distance from most code words. This code-word space structure quantitatively predicts typical deviation of a state-trajectory from its initial state. Altogether, our findings reveal a non-trivial heterogeneous structure of the code-word space that shapes information representation in a biological network.

  11. Clustering of neural code words revealed by a first-order phase transition

    Science.gov (United States)

    Huang, Haiping; Toyoizumi, Taro

    2016-06-01

    A network of neurons in the central nervous system collectively represents information by its spiking activity states. Typically observed states, i.e., code words, occupy only a limited portion of the state space due to constraints imposed by network interactions. Geometrical organization of code words in the state space, critical for neural information processing, is poorly understood due to its high dimensionality. Here, we explore the organization of neural code words using retinal data by computing the entropy of code words as a function of Hamming distance from a particular reference codeword. Specifically, we report that the retinal code words in the state space are divided into multiple distinct clusters separated by entropy-gaps, and that this structure is shared with well-known associative memory networks in a recallable phase. Our analysis also elucidates a special nature of the all-silent state. The all-silent state is surrounded by the densest cluster of code words and located within a reachable distance from most code words. This code-word space structure quantitatively predicts typical deviation of a state-trajectory from its initial state. Altogether, our findings reveal a non-trivial heterogeneous structure of the code-word space that shapes information representation in a biological network.

  12. Rapid three dimensional two photon neural population scanning.

    Science.gov (United States)

    Schuck, Renaud; Quicke, Peter; Copeland, Caroline; Garasto, Stefania; Annecchino, Luca A; Hwang, June Kyu; Schultz, Simon R

    2015-08-01

    Recording the activity of neural populations at high sampling rates is a fundamental requirement for understanding computation in neural circuits. Two photon microscopy provides one promising approach towards this. However, neural circuits are three dimensional, and functional imaging in two dimensions fails to capture the 3D nature of neural dynamics. Electrically tunable lenses (ETLs) provide a simple and cheap method to extend laser scanning microscopy into the relatively unexploited third dimension. We have therefore incorporated them into our Adaptive Spiral Scanning (SSA) algorithm, which calculates kinematically efficient scanning strategies using radially modulated spiral paths. We characterised the response of the ETL, incorporated its dynamics using MATLAB models of the SSA algorithm and tested the models on populations of Izhikevich neurons of varying size and density. From this, we show that our algorithms can theoretically at least achieve sampling rates of 36.2Hz compared to 21.6Hz previously reported for 3D scanning techniques.

  13. Intensity Coding in Two-Dimensional Excitable Neural Networks

    CERN Document Server

    Copelli, Mauro

    2016-01-01

    In the light of recent experimental findings that gap junctions are essential for low level intensity detection in the sensory periphery, the Greenberg-Hastings cellular automaton is employed to model the response of a two-dimensional sensory network to external stimuli. We show that excitable elements (sensory neurons) that have a small dynamical range are shown to give rise to a collective large dynamical range. Therefore the network transfer (gain) function (which is Hill or Stevens law-like) is an emergent property generated from a pool of small dynamical range cells, providing a basis for a "neural psychophysics". The growth of the dynamical range with the system size is approximately logarithmic, suggesting a functional role for electrical coupling. For a fixed number of neurons, the dynamical range displays a maximum as a function of the refractory period, which suggests experimental tests for the model. A biological application to ephaptic interactions in olfactory nerve fascicles is proposed.

  14. The neural code in developing cultured networks: experiments and advanced simulation models

    NARCIS (Netherlands)

    Rutten, Wim; Gritsun, T.; Stoyanova, Irina; le Feber, Jakob

    2012-01-01

    Understanding the neural code of cultured neuronal networks may help to forward our understanding of human brain processes.The most striking property of spontaneously firing cultures is their regular bursting activity, a burst being defined as synchronized firing of groups of neurons spread

  15. Real-Coded Quantum-Inspired Genetic Algorithm-Based BP Neural Network Algorithm

    Directory of Open Access Journals (Sweden)

    Jianyong Liu

    2015-01-01

    Full Text Available The method that the real-coded quantum-inspired genetic algorithm (RQGA used to optimize the weights and threshold of BP neural network is proposed to overcome the defect that the gradient descent method makes the algorithm easily fall into local optimal value in the learning process. Quantum genetic algorithm (QGA is with good directional global optimization ability, but the conventional QGA is based on binary coding; the speed of calculation is reduced by the coding and decoding processes. So, RQGA is introduced to explore the search space, and the improved varied learning rate is adopted to train the BP neural network. Simulation test shows that the proposed algorithm is effective to rapidly converge to the solution conformed to constraint conditions.

  16. Cracking the neural code, treating paralysis and the future of bioelectronic medicine.

    Science.gov (United States)

    Bouton, C

    2017-07-01

    The human nervous system is a vast network carrying not only sensory and movement information, but also information to and from our organs, intimately linking it to our overall health. Scientists and engineers have been working for decades to tap into this network and 'crack the neural code' by decoding neural signals and learning how to 'speak' the language of the nervous system. Progress has been made in developing neural decoding methods to decipher brain activity and bioelectronic technologies to treat rheumatoid arthritis, paralysis, epilepsy and for diagnosing brain-related diseases such as Parkinson's and Alzheimer's disease. In a recent first-in-human study involving paralysis, a paralysed male study participant regained movement in his hand, years after his injury, through the use of a bioelectronic neural bypass. This work combined neural decoding and neurostimulation methods to translate and re-route signals around damaged neural pathways within the central nervous system. By extending these methods to decipher neural messages in the peripheral nervous system, status information from our bodily functions and specific organs could be gained. This, one day, could allow real-time diagnostics to be performed to give us a deeper insight into a patient's condition, or potentially even predict disease or allow early diagnosis. The future of bioelectronic medicine is extremely bright and is wide open as new diagnostic and treatment options are developed for patients around the world. © 2017 The Association for the Publication of the Journal of Internal Medicine.

  17. A skin colour code for the Nigerian (Negroid) population SUMMARY ...

    African Journals Online (AJOL)

    kemrilib

    SUMMARY. Some researchers have codified various people of different racial and pigment backgrounds into skin types. The West African native population generally falls into type VI – least likely to burn. There is a need for skin colour code in a multiethnic country like Nigeria especially for the purpose of health matters.

  18. Authorship attribution of source code by using back propagation neural network based on particle swarm optimization.

    Science.gov (United States)

    Yang, Xinyu; Xu, Guoai; Li, Qi; Guo, Yanhui; Zhang, Miao

    2017-01-01

    Authorship attribution is to identify the most likely author of a given sample among a set of candidate known authors. It can be not only applied to discover the original author of plain text, such as novels, blogs, emails, posts etc., but also used to identify source code programmers. Authorship attribution of source code is required in diverse applications, ranging from malicious code tracking to solving authorship dispute or software plagiarism detection. This paper aims to propose a new method to identify the programmer of Java source code samples with a higher accuracy. To this end, it first introduces back propagation (BP) neural network based on particle swarm optimization (PSO) into authorship attribution of source code. It begins by computing a set of defined feature metrics, including lexical and layout metrics, structure and syntax metrics, totally 19 dimensions. Then these metrics are input to neural network for supervised learning, the weights of which are output by PSO and BP hybrid algorithm. The effectiveness of the proposed method is evaluated on a collected dataset with 3,022 Java files belong to 40 authors. Experiment results show that the proposed method achieves 91.060% accuracy. And a comparison with previous work on authorship attribution of source code for Java language illustrates that this proposed method outperforms others overall, also with an acceptable overhead.

  19. Neural coding of basic reward terms of animal learning theory, game theory, microeconomics and behavioural ecology.

    Science.gov (United States)

    Schultz, Wolfram

    2004-04-01

    Neurons in a small number of brain structures detect rewards and reward-predicting stimuli and are active during the expectation of predictable food and liquid rewards. These neurons code the reward information according to basic terms of various behavioural theories that seek to explain reward-directed learning, approach behaviour and decision-making. The involved brain structures include groups of dopamine neurons, the striatum including the nucleus accumbens, the orbitofrontal cortex and the amygdala. The reward information is fed to brain structures involved in decision-making and organisation of behaviour, such as the dorsolateral prefrontal cortex and possibly the parietal cortex. The neural coding of basic reward terms derived from formal theories puts the neurophysiological investigation of reward mechanisms on firm conceptual grounds and provides neural correlates for the function of rewards in learning, approach behaviour and decision-making.

  20. Models of neural networks temporal aspects of coding and information processing in biological systems

    CERN Document Server

    Hemmen, J; Schulten, Klaus

    1994-01-01

    Since the appearance of Vol. 1 of Models of Neural Networks in 1991, the theory of neural nets has focused on two paradigms: information coding through coherent firing of the neurons and functional feedback. Information coding through coherent neuronal firing exploits time as a cardinal degree of freedom. This capacity of a neural network rests on the fact that the neuronal action potential is a short, say 1 ms, spike, localized in space and time. Spatial as well as temporal correlations of activity may represent different states of a network. In particular, temporal correlations of activity may express that neurons process the same "object" of, for example, a visual scene by spiking at the very same time. The traditional description of a neural network through a firing rate, the famous S-shaped curve, presupposes a wide time window of, say, at least 100 ms. It thus fails to exploit the capacity to "bind" sets of coherently firing neurons for the purpose of both scene segmentation and figure-ground segregatio...

  1. A neutron spectrum unfolding code based on generalized regression artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Ortiz R, J. M.; Martinez B, M. R.; Castaneda M, R.; Solis S, L. O. [Universidad Autonoma de Zacatecas, Unidad Academica de Ingenieria Electrica, Av. Ramon Lopez Velarde 801, Col. Centro, 98000 Zacatecas, Zac. (Mexico); Vega C, H. R., E-mail: morvymm@yahoo.com.mx [Universidad Autonoma de Zacatecas, Unidad Academica de Estudios Nucleares, Cipres No. 10, Fracc. La Penuela, 98068 Zacatecas, Zac. (Mexico)

    2015-10-15

    The most delicate part of neutron spectrometry, is the unfolding process. Then derivation of the spectral information is not simple because the unknown is not given directly as result of the measurements. Novel methods based on Artificial Neural Networks have been widely investigated. In prior works, back propagation neural networks (BPNN) have been used to solve the neutron spectrometry problem, however, some drawbacks still exist using this kind of neural nets, as the optimum selection of the network topology and the long training time. Compared to BPNN, is usually much faster to train a generalized regression neural network (GRNN). That is mainly because spread constant is the only parameter used in GRNN. Another feature is that the network will converge to a global minimum. In addition, often are more accurate than BPNN in prediction. These characteristics make GRNN be of great interest in the neutron spectrometry domain. In this work is presented a computational tool based on GRNN, capable to solve the neutron spectrometry problem. This computational code, automates the pre-processing, training and testing stages, the statistical analysis and the post-processing of the information, using 7 Bonner spheres rate counts as only entrance data. The code was designed for a Bonner Spheres System based on a {sup 6}LiI(Eu) neutron detector and a response matrix expressed in 60 energy bins taken from an International Atomic Energy Agency compilation. (Author)

  2. Neural dynamics of reward probability coding: a Magnetoencephalographic study in humans

    Directory of Open Access Journals (Sweden)

    Julie eThomas

    2013-11-01

    Full Text Available Prediction of future rewards and discrepancy between actual and expected outcomes (prediction error are crucial signals for adaptive behavior. In humans, a number of fMRI studies demonstrated that reward probability modulates these two signals in a large brain network. Yet, the spatio-temporal dynamics underlying the neural coding of reward probability remains unknown. Here, using magnetoencephalography, we investigated the neural dynamics of prediction and reward prediction error computations while subjects learned to associate cues of slot machines with monetary rewards with different probabilities. We showed that event-related magnetic fields (ERFs arising from the visual cortex coded the expected reward value 155 ms after the cue, demonstrating that reward value signals emerge early in the visual stream. Moreover, a prediction error was reflected in ERF peaking 300 ms after the rewarded outcome and showing decreasing amplitude with higher reward probability. This prediction error signal was generated in a network including the anterior and posterior cingulate cortex. These findings pinpoint the spatio-temporal characteristics underlying reward probability coding. Together, our results provide insights into the neural dynamics underlying the ability to learn probabilistic stimuli-reward contingencies.

  3. The effects of cultural learning in populations of neural networks.

    Science.gov (United States)

    Curran, Dara; O'Riordan, Colm

    2007-01-01

    Population learning can be described as the iterative Darwinian process of fitness-based selection and genetic transfer of information leading to populations of higher fitness and is often simulated using genetic algorithms. Cultural learning describes the process of information transfer between individuals in a population through non-genetic means. Cultural learning has been simulated by combining genetic algorithms and neural networks using a teacher-pupil scenario where highly fit individuals are selected as teachers and instruct the next generation. By examining the innate fitness of a population (i.e., the fitness of the population measured before any cultural learning takes place), it is possible to examine the effects of cultural learning on the population's genetic makeup. Our model explores the effect of cultural learning on a population and employs three benchmark sequential decision tasks as the evolutionary task for the population: connect-four, tic-tac-toe, and blackjack. Experiments are conducted with populations employing population learning alone and populations combining population and cultural learning. The article presents results showing the gradual transfer of knowledge from genes to the cultural process, illustrated by the simultaneous decrease in the population's innate fitness and the increase of its acquired fitness measured after learning takes place.

  4. Sensorineural hearing loss amplifies neural coding of envelope information in the central auditory system of chinchillas.

    Science.gov (United States)

    Zhong, Ziwei; Henry, Kenneth S; Heinz, Michael G

    2014-03-01

    People with sensorineural hearing loss often have substantial difficulty understanding speech under challenging listening conditions. Behavioral studies suggest that reduced sensitivity to the temporal structure of sound may be responsible, but underlying neurophysiological pathologies are incompletely understood. Here, we investigate the effects of noise-induced hearing loss on coding of envelope (ENV) structure in the central auditory system of anesthetized chinchillas. ENV coding was evaluated noninvasively using auditory evoked potentials recorded from the scalp surface in response to sinusoidally amplitude modulated tones with carrier frequencies of 1, 2, 4, and 8 kHz and a modulation frequency of 140 Hz. Stimuli were presented in quiet and in three levels of white background noise. The latency of scalp-recorded ENV responses was consistent with generation in the auditory midbrain. Hearing loss amplified neural coding of ENV at carrier frequencies of 2 kHz and above. This result may reflect enhanced ENV coding from the periphery and/or an increase in the gain of central auditory neurons. In contrast to expectations, hearing loss was not associated with a stronger adverse effect of increasing masker intensity on ENV coding. The exaggerated neural representation of ENV information shown here at the level of the auditory midbrain helps to explain previous findings of enhanced sensitivity to amplitude modulation in people with hearing loss under some conditions. Furthermore, amplified ENV coding may potentially contribute to speech perception problems in people with cochlear hearing loss by acting as a distraction from more salient acoustic cues, particularly in fluctuating backgrounds. Copyright © 2013 Elsevier B.V. All rights reserved.

  5. Evaluating the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks

    Science.gov (United States)

    Ortiz-Rodríguez, J. M.; Reyes Alfaro, A.; Reyes Haro, A.; Solís Sánches, L. O.; Miranda, R. Castañeda; Cervantes Viramontes, J. M.; Vega-Carrillo, H. R.

    2013-07-01

    In this work the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks is evaluated. The first one code based on traditional iterative procedures and called Neutron spectrometry and dosimetry from the Universidad Autonoma de Zacatecas (NSDUAZ) use the SPUNIT iterative algorithm and was designed to unfold neutron spectrum and calculate 15 dosimetric quantities and 7 IAEA survey meters. The main feature of this code is the automated selection of the initial guess spectrum trough a compendium of neutron spectrum compiled by the IAEA. The second one code known as Neutron spectrometry and dosimetry with artificial neural networks (NDSann) is a code designed using neural nets technology. The artificial intelligence approach of neural net does not solve mathematical equations. By using the knowledge stored at synaptic weights on a neural net properly trained, the code is capable to unfold neutron spectrum and to simultaneously calculate 15 dosimetric quantities, needing as entrance data, only the rate counts measured with a Bonner spheres system. Similarities of both NSDUAZ and NSDann codes are: they follow the same easy and intuitive user's philosophy and were designed in a graphical interface under the LabVIEW programming environment. Both codes unfold the neutron spectrum expressed in 60 energy bins, calculate 15 dosimetric quantities and generate a full report in HTML format. Differences of these codes are: NSDUAZ code was designed using classical iterative approaches and needs an initial guess spectrum in order to initiate the iterative procedure. In NSDUAZ, a programming routine was designed to calculate 7 IAEA instrument survey meters using the fluence-dose conversion coefficients. NSDann code use artificial neural networks for solving the ill-conditioned equation system of neutron spectrometry problem through synaptic weights of a properly trained neural network. Contrary to iterative procedures, in neural

  6. Neural Population Dynamics Modeled by Mean-Field Graphs

    Science.gov (United States)

    Kozma, Robert; Puljic, Marko

    2011-09-01

    In this work we apply random graph theory approach to describe neural population dynamics. There are important advantages of using random graph theory approach in addition to ordinary and partial differential equations. The mathematical theory of large-scale random graphs provides an efficient tool to describe transitions between high- and low-dimensional spaces. Recent advances in studying neural correlates of higher cognition indicate the significance of sudden changes in space-time neurodynamics, which can be efficiently described as phase transitions in the neuropil medium. Phase transitions are rigorously defined mathematically on random graph sequences and they can be naturally generalized to a class of percolation processes called neuropercolation. In this work we employ mean-field graphs with given vertex degree distribution and edge strength distribution. We demonstrate the emergence of collective oscillations in the style of brains.

  7. Emerging role of non-coding RNA in neural plasticity, cognitive function, and neuropsychiatric disorders

    Directory of Open Access Journals (Sweden)

    Paola eSpadaro

    2012-07-01

    Full Text Available Non-coding RNAs have emerged as critical regulators of transcription, epigenetic processes, and gene silencing, which make them ideal candidates for insight into molecular evolution and a better understanding of the molecular pathways of neuropsychiatric disease. Here we provide an overview of the current state of knowledge regarding various classes of ncRNAs and their role in neural plasticity and cognitive function, and highlight the potential contribution they may make to the development of a variety of neuropsychiatric disorders, including schizophrenia, addiction and fear-related anxiety disorders.

  8. Adaptation in Coding by Large Populations of Neurons in the Retina

    Science.gov (United States)

    Ioffe, Mark L.

    A comprehensive theory of neural computation requires an understanding of the statistical properties of the neural population code. The focus of this work is the experimental study and theoretical analysis of the statistical properties of neural activity in the tiger salamander retina. This is an accessible yet complex system, for which we control the visual input and record from a substantial portion--greater than a half--of the ganglion cell population generating the spiking output. Our experiments probe adaptation of the retina to visual statistics: a central feature of sensory systems which have to adjust their limited dynamic range to a far larger space of possible inputs. In Chapter 1 we place our work in context with a brief overview of the relevant background. In Chapter 2 we describe the experimental methodology of recording from 100+ ganglion cells in the tiger salamander retina. In Chapter 3 we first present the measurements of adaptation of individual cells to changes in stimulation statistics and then investigate whether pairwise correlations in fluctuations of ganglion cell activity change across different stimulation conditions. We then transition to a study of the population-level probability distribution of the retinal response captured with maximum-entropy models. Convergence of the model inference is presented in Chapter 4. In Chapter 5 we first test the empirical presence of a phase transition in such models fitting the retinal response to different experimental conditions, and then proceed to develop other characterizations which are sensitive to complexity in the interaction matrix. This includes an analysis of the dynamics of sampling at finite temperature, which demonstrates a range of subtle attractor-like properties in the energy landscape. These are largely conserved when ambient illumination is varied 1000-fold, a result not necessarily apparent from the measured low-order statistics of the distribution. Our results form a consistent

  9. Neural code alterations and abnormal time patterns in Parkinson’s disease

    Science.gov (United States)

    Andres, Daniela Sabrina; Cerquetti, Daniel; Merello, Marcelo

    2015-04-01

    Objective. The neural code used by the basal ganglia is a current question in neuroscience, relevant for the understanding of the pathophysiology of Parkinson’s disease. While a rate code is known to participate in the communication between the basal ganglia and the motor thalamus/cortex, different lines of evidence have also favored the presence of complex time patterns in the discharge of the basal ganglia. To gain insight into the way the basal ganglia code information, we studied the activity of the globus pallidus pars interna (GPi), an output node of the circuit. Approach. We implemented the 6-hydroxydopamine model of Parkinsonism in Sprague-Dawley rats, and recorded the spontaneous discharge of single GPi neurons, in head-restrained conditions at full alertness. Analyzing the temporal structure function, we looked for characteristic scales in the neuronal discharge of the GPi. Main results. At a low-scale, we observed the presence of dynamic processes, which allow the transmission of time patterns. Conversely, at a middle-scale, stochastic processes force the use of a rate code. Regarding the time patterns transmitted, we measured the word length and found that it is increased in Parkinson’s disease. Furthermore, it showed a positive correlation with the frequency of discharge, indicating that an exacerbation of this abnormal time pattern length can be expected, as the dopamine depletion progresses. Significance. We conclude that a rate code and a time pattern code can co-exist in the basal ganglia at different temporal scales. However, their normal balance is progressively altered and replaced by pathological time patterns in Parkinson’s disease.

  10. Fast Prediction of HCCI Combustion with an Artificial Neural Network Linked to a Fluid Mechanics Code

    Energy Technology Data Exchange (ETDEWEB)

    Aceves, S M; Flowers, D L; Chen, J; Babaimopoulos, A

    2006-08-29

    We have developed an artificial neural network (ANN) based combustion model and have integrated it into a fluid mechanics code (KIVA3V) to produce a new analysis tool (titled KIVA3V-ANN) that can yield accurate HCCI predictions at very low computational cost. The neural network predicts ignition delay as a function of operating parameters (temperature, pressure, equivalence ratio and residual gas fraction). KIVA3V-ANN keeps track of the time history of the ignition delay during the engine cycle to evaluate the ignition integral and predict ignition for each computational cell. After a cell ignites, chemistry becomes active, and a two-step chemical kinetic mechanism predicts composition and heat generation in the ignited cells. KIVA3V-ANN has been validated by comparison with isooctane HCCI experiments in two different engines. The neural network provides reasonable predictions for HCCI combustion and emissions that, although typically not as good as obtained with the more physically representative multi-zone model, are obtained at a much reduced computational cost. KIVA3V-ANN can perform reasonably accurate HCCI calculations while requiring only 10% more computational effort than a motored KIVA3V run. It is therefore considered a valuable tool for evaluation of engine maps or other performance analysis tasks requiring multiple individual runs.

  11. A neural network model of general olfactory coding in the insect antennal lobe.

    Science.gov (United States)

    Getz, W M; Lutz, A

    1999-08-01

    A central problem in olfaction is understanding how the quality of olfactory stimuli is encoded in the insect antennal lobe (or in the analogously structured vertebrate olfactory bulb) for perceptual processing in the mushroom bodies of the insect protocerebrum (or in the vertebrate olfactory cortex). In the study reported here, a relatively simple neural network model, inspired by our current knowledge of the insect antennal lobes, is used to investigate how each of several features and elements of the network, such as synapse strengths, feedback circuits and the steepness of neural activation functions, influences the formation of an olfactory code in neurons that project from the antennal lobes to the mushroom bodies (or from mitral cells to olfactory cortex). An optimal code in these projection neurons (PNs) should minimize potential errors by the mushroom bodies in misidentifying the quality of an odor across a range of concentrations while maximizing the ability of the mushroom bodies to resolve odors of different quality. Simulation studies demonstrate that the network is able to produce codes independent or virtually independent of concentration over a given range. The extent of this range is moderately dependent on a parameter that characterizes how long it takes for the voltage in an activated neuron to decay back to its resting potential, strongly dependent on the strength of excitatory feedback by the PNs onto antennal lobe intrinsic neurons (INs), and overwhelmingly dependent on the slope of the activation function that transforms the voltage of depolarized neurons into the rate at which spikes are produced. Although the code in the PNs is degraded by large variations in the concentration of odor stimuli, good performance levels are maintained when the complexity of stimuli, as measured by the number of component odorants, is doubled. When excitatory feedback from the PNs to the INs is strong, the activity in the PNs undergoes transitions from initial

  12. Degraded attentional modulation of cortical neural populations in strabismic amblyopia

    Science.gov (United States)

    Hou, Chuan; Kim, Yee-Joon; Lai, Xin Jie; Verghese, Preeti

    2016-01-01

    Behavioral studies have reported reduced spatial attention in amblyopia, a developmental disorder of spatial vision. However, the neural populations in the visual cortex linked with these behavioral spatial attention deficits have not been identified. Here, we use functional MRI–informed electroencephalography source imaging to measure the effect of attention on neural population activity in the visual cortex of human adult strabismic amblyopes who were stereoblind. We show that compared with controls, the modulatory effects of selective visual attention on the input from the amblyopic eye are substantially reduced in the primary visual cortex (V1) as well as in extrastriate visual areas hV4 and hMT+. Degraded attentional modulation is also found in the normal-acuity fellow eye in areas hV4 and hMT+ but not in V1. These results provide electrophysiological evidence that abnormal binocular input during a developmental critical period may impact cortical connections between the visual cortex and higher level cortices beyond the known amblyopic losses in V1 and V2, suggesting that a deficit of attentional modulation in the visual cortex is an important component of the functional impairment in amblyopia. Furthermore, we find that degraded attentional modulation in V1 is correlated with the magnitude of interocular suppression and the depth of amblyopia. These results support the view that the visual suppression often seen in strabismic amblyopia might be a form of attentional neglect of the visual input to the amblyopic eye. PMID:26885628

  13. Nonlinear modeling of neural population dynamics for hippocampal prostheses.

    Science.gov (United States)

    Song, Dong; Chan, Rosa H M; Marmarelis, Vasilis Z; Hampson, Robert E; Deadwyler, Sam A; Berger, Theodore W

    2009-11-01

    Developing a neural prosthesis for the damaged hippocampus requires restoring the transformation of population neural activities performed by the hippocampal circuitry. To bypass a damaged region, output spike trains need to be predicted from the input spike trains and then reinstated through stimulation. We formulate a multiple-input, multiple-output (MIMO) nonlinear dynamic model for the input-output transformation of spike trains. In this approach, a MIMO model comprises a series of physiologically-plausible multiple-input, single-output (MISO) neuron models that consist of five components each: (1) feedforward Volterra kernels transforming the input spike trains into the synaptic potential, (2) a feedback kernel transforming the output spikes into the spike-triggered after-potential, (3) a noise term capturing the system uncertainty, (4) an adder generating the pre-threshold potential, and (5) a threshold function generating output spikes. It is shown that this model is equivalent to a generalized linear model with a probit link function. To reduce model complexity and avoid overfitting, statistical model selection and cross-validation methods are employed to choose the significant inputs and interactions between inputs. The model is applied successfully to the hippocampal CA3-CA1 population dynamics. Such a model can serve as a computational basis for the development of hippocampal prostheses.

  14. A Neural Code That Is Isometric to Vocal Output and Correlates with Its Sensory Consequences.

    Directory of Open Access Journals (Sweden)

    Alexei L Vyssotski

    2016-10-01

    Full Text Available What cortical inputs are provided to motor control areas while they drive complex learned behaviors? We study this question in the nucleus interface of the nidopallium (NIf, which is required for normal birdsong production and provides the main source of auditory input to HVC, the driver of adult song. In juvenile and adult zebra finches, we find that spikes in NIf projection neurons precede vocalizations by several tens of milliseconds and are insensitive to distortions of auditory feedback. We identify a local isometry between NIf output and vocalizations: quasi-identical notes produced in different syllables are preceded by highly similar NIf spike patterns. NIf multiunit firing during song precedes responses in auditory cortical neurons by about 50 ms, revealing delayed congruence between NIf spiking and a neural representation of auditory feedback. Our findings suggest that NIf codes for imminent acoustic events within vocal performance.

  15. Mild KCC2 hypofunction causes inconspicuous chloride dysregulation that degrades neural coding

    Directory of Open Access Journals (Sweden)

    Nicolas eDoyon

    2016-01-01

    Full Text Available Disinhibition caused by Cl- dysregulation is implicated in several neurological disorders. This form of disinhibition, which stems primarily from impaired Cl- extrusion through the co-transporter KCC2, is typically identified by a depolarizing shift in GABA reversal potential (EGABA. Here we show, using computer simulations, that intracellular [Cl-] exhibits exaggerated fluctuations during transient Cl- loads and recovers more slowly to baseline when KCC2 level is even modestly reduced. Using information theory and signal detection theory, we show that increased Cl- lability and settling time degrade neural coding. Importantly, these deleterious effects manifest after less KCC2 reduction than needed to produce the gross changes in EGABA required for detection by most experiments, which assess KCC2 function under weak Cl- load conditions. By demonstrating the existence and functional consequences of occult Cl- dysregulation, these results suggest that modest KCC2 hypofunction plays a greater role in neurological disorders than previously believed.

  16. The Effect of Inhibitory Neuron on the Evolution Model of Higher-Order Coupling Neural Oscillator Population

    Science.gov (United States)

    Qi, Yi; Wang, Rubin; Jiao, Xianfa; Du, Ying

    2014-01-01

    We proposed a higher-order coupling neural network model including the inhibitory neurons and examined the dynamical evolution of average number density and phase-neural coding under the spontaneous activity and external stimulating condition. The results indicated that increase of inhibitory coupling strength will cause decrease of average number density, whereas increase of excitatory coupling strength will cause increase of stable amplitude of average number density. Whether the neural oscillator population is able to enter the new synchronous oscillation or not is determined by excitatory and inhibitory coupling strength. In the presence of external stimulation, the evolution of the average number density is dependent upon the external stimulation and the coupling term in which the dominator will determine the final evolution. PMID:24516505

  17. The Effect of Inhibitory Neuron on the Evolution Model of Higher-Order Coupling Neural Oscillator Population

    Directory of Open Access Journals (Sweden)

    Yi Qi

    2014-01-01

    Full Text Available We proposed a higher-order coupling neural network model including the inhibitory neurons and examined the dynamical evolution of average number density and phase-neural coding under the spontaneous activity and external stimulating condition. The results indicated that increase of inhibitory coupling strength will cause decrease of average number density, whereas increase of excitatory coupling strength will cause increase of stable amplitude of average number density. Whether the neural oscillator population is able to enter the new synchronous oscillation or not is determined by excitatory and inhibitory coupling strength. In the presence of external stimulation, the evolution of the average number density is dependent upon the external stimulation and the coupling term in which the dominator will determine the final evolution.

  18. Neural Computation via Neural Geometry: A Place Code for Inter-whisker Timing in the Barrel Cortex?

    Science.gov (United States)

    Wilson, Stuart P.; Bednar, James A.; Prescott, Tony J.; Mitchinson, Ben

    2011-01-01

    The place theory proposed by Jeffress (1948) is still the dominant model of how the brain represents the movement of sensory stimuli between sensory receptors. According to the place theory, delays in signalling between neurons, dependent on the distances between them, compensate for time differences in the stimulation of sensory receptors. Hence the location of neurons, activated by the coincident arrival of multiple signals, reports the stimulus movement velocity. Despite its generality, most evidence for the place theory has been provided by studies of the auditory system of auditory specialists like the barn owl, but in the study of mammalian auditory systems the evidence is inconclusive. We ask to what extent the somatosensory systems of tactile specialists like rats and mice use distance dependent delays between neurons to compute the motion of tactile stimuli between the facial whiskers (or ‘vibrissae’). We present a model in which synaptic inputs evoked by whisker deflections arrive at neurons in layer 2/3 (L2/3) somatosensory ‘barrel’ cortex at different times. The timing of synaptic inputs to each neuron depends on its location relative to sources of input in layer 4 (L4) that represent stimulation of each whisker. Constrained by the geometry and timing of projections from L4 to L2/3, the model can account for a range of experimentally measured responses to two-whisker stimuli. Consistent with that data, responses of model neurons located between the barrels to paired stimulation of two whiskers are greater than the sum of the responses to either whisker input alone. The model predicts that for neurons located closer to either barrel these supralinear responses are tuned for longer inter-whisker stimulation intervals, yielding a topographic map for the inter-whisker deflection interval across the surface of L2/3. This map constitutes a neural place code for the relative timing of sensory stimuli. PMID:22022245

  19. Neural computation via neural geometry: a place code for inter-whisker timing in the barrel cortex?

    Directory of Open Access Journals (Sweden)

    Stuart P Wilson

    2011-10-01

    Full Text Available The place theory proposed by Jeffress (1948 is still the dominant model of how the brain represents the movement of sensory stimuli between sensory receptors. According to the place theory, delays in signalling between neurons, dependent on the distances between them, compensate for time differences in the stimulation of sensory receptors. Hence the location of neurons, activated by the coincident arrival of multiple signals, reports the stimulus movement velocity. Despite its generality, most evidence for the place theory has been provided by studies of the auditory system of auditory specialists like the barn owl, but in the study of mammalian auditory systems the evidence is inconclusive. We ask to what extent the somatosensory systems of tactile specialists like rats and mice use distance dependent delays between neurons to compute the motion of tactile stimuli between the facial whiskers (or 'vibrissae'. We present a model in which synaptic inputs evoked by whisker deflections arrive at neurons in layer 2/3 (L2/3 somatosensory 'barrel' cortex at different times. The timing of synaptic inputs to each neuron depends on its location relative to sources of input in layer 4 (L4 that represent stimulation of each whisker. Constrained by the geometry and timing of projections from L4 to L2/3, the model can account for a range of experimentally measured responses to two-whisker stimuli. Consistent with that data, responses of model neurons located between the barrels to paired stimulation of two whiskers are greater than the sum of the responses to either whisker input alone. The model predicts that for neurons located closer to either barrel these supralinear responses are tuned for longer inter-whisker stimulation intervals, yielding a topographic map for the inter-whisker deflection interval across the surface of L2/3. This map constitutes a neural place code for the relative timing of sensory stimuli.

  20. Noise in neural populations accounts for errors in working memory.

    Science.gov (United States)

    Bays, Paul M

    2014-03-05

    Errors in short-term memory increase with the quantity of information stored, limiting the complexity of cognition and behavior. In visual memory, attempts to account for errors in terms of allocation of a limited pool of working memory resources have met with some success, but the biological basis for this cognitive architecture is unclear. An alternative perspective attributes recall errors to noise in tuned populations of neurons that encode stimulus features in spiking activity. I show that errors associated with decreasing signal strength in probabilistically spiking neurons reproduce the pattern of failures in human recall under increasing memory load. In particular, deviations from the normal distribution that are characteristic of working memory errors and have been attributed previously to guesses or variability in precision are shown to arise as a natural consequence of decoding populations of tuned neurons. Observers possess fine control over memory representations and prioritize accurate storage of behaviorally relevant information, at a cost to lower priority stimuli. I show that changing the input drive to neurons encoding a prioritized stimulus biases population activity in a manner that reproduces this empirical tradeoff in memory precision. In a task in which predictive cues indicate stimuli most probable for test, human observers use the cues in an optimal manner to maximize performance, within the constraints imposed by neural noise.

  1. Slow Temporal Integration Enables Robust Neural Coding and Perception of a Cue to Sound Source Location.

    Science.gov (United States)

    Brown, Andrew D; Tollin, Daniel J

    2016-09-21

    In mammals, localization of sound sources in azimuth depends on sensitivity to interaural differences in sound timing (ITD) and level (ILD). Paradoxically, while typical ILD-sensitive neurons of the auditory brainstem require millisecond synchrony of excitatory and inhibitory inputs for the encoding of ILDs, human and animal behavioral ILD sensitivity is robust to temporal stimulus degradations (e.g., interaural decorrelation due to reverberation), or, in humans, bilateral clinical device processing. Here we demonstrate that behavioral ILD sensitivity is only modestly degraded with even complete decorrelation of left- and right-ear signals, suggesting the existence of a highly integrative ILD-coding mechanism. Correspondingly, we find that a majority of auditory midbrain neurons in the central nucleus of the inferior colliculus (of chinchilla) effectively encode ILDs despite complete decorrelation of left- and right-ear signals. We show that such responses can be accounted for by relatively long windows of bilateral excitatory-inhibitory interaction, which we explicitly measure using trains of narrowband clicks. Neural and behavioral data are compared with the outputs of a simple model of ILD processing with a single free parameter, the duration of excitatory-inhibitory interaction. Behavioral, neural, and modeling data collectively suggest that ILD sensitivity depends on binaural integration of excitation and inhibition within a ≳3 ms temporal window, significantly longer than observed in lower brainstem neurons. This relatively slow integration potentiates a unique role for the ILD system in spatial hearing that may be of particular importance when informative ITD cues are unavailable. In mammalian hearing, interaural differences in the timing (ITD) and level (ILD) of impinging sounds carry critical information about source location. However, natural sounds are often decorrelated between the ears by reverberation and background noise, degrading the fidelity of

  2. Population red blood cell folate concentrations for prevention of neural tube defects: Bayesian model.

    Science.gov (United States)

    Crider, Krista S; Devine, Owen; Hao, Ling; Dowling, Nicole F; Li, Song; Molloy, Anne M; Li, Zhu; Zhu, Jianghui; Berry, Robert J

    2014-07-29

    To determine an optimal population red blood cell (RBC) folate concentration for the prevention of neural tube birth defects. Bayesian model. Data from two population based studies in China. 247,831 participants in a prospective community intervention project in China (1993-95) to prevent neural tube defects with 400 μg/day folic acid supplementation and 1194 participants in a population based randomized trial (2003-05) to evaluate the effect of folic acid supplementation on blood folate concentration among Chinese women of reproductive age. Folic acid supplementation (400 μg/day). Estimated RBC folate concentration at time of neural tube closure (day 28 of gestation) and risk of neural tube defects. Risk of neural tube defects was high at the lowest estimated RBC folate concentrations (for example, 25.4 (95% uncertainty interval 20.8 to 31.2) neural tube defects per 10,000 births at 500 nmol/L) and decreased as estimated RBC folate concentration increased. Risk of neural tube defects was substantially attenuated at estimated RBC folate concentrations above about 1000 nmol/L (for example, 6 neural tube defects per 10,000 births at 1180 (1050 to 1340) nmol/L). The modeled dose-response relation was consistent with the existing literature. In addition, neural tube defect risk estimates developed using the proposed model and population level RBC information were consistent with the prevalence of neural tube defects in the US population before and after food fortification with folic acid. A threshold for "optimal" population RBC folate concentration for the prevention of neural tube defects could be defined (for example, approximately 1000 nmol/L). Population based RBC folate concentrations, as a biomarker for risk of neural tube defects, can be used to facilitate evaluation of prevention programs as well as to identify subpopulations at elevated risk for a neural tube defect affected pregnancy due to folate insufficiency. © Crider et al 2014.

  3. Neural coding of reward magnitude in the orbitofrontal cortex of the rat during a five-odor olfactory discrimination task.

    NARCIS (Netherlands)

    van Duuren, E.; Escamez, F.A.N.; Joosten, R.N.J.M.A.; Visser, R.; Mulder, A.B.; Pennartz, C.M.A.

    2007-01-01

    The orbitofrontal cortex (OBFc) has been suggested to code the motivational value of environmental stimuli and to use this information for the flexible guidance of goal-directed behavior. To examine whether information regarding reward prediction is quantitatively represented in the rat OBFc, neural

  4. Data-driven inference of network connectivity for modeling the dynamics of neural codes in the insect antennal lobe

    Directory of Open Access Journals (Sweden)

    Eli eShlizerman

    2014-08-01

    Full Text Available The antennal lobe (AL, olfactory processing center in insects, is able to process stimuli into distinct neural activity patterns, called olfactory neural codes. To model their dynamics we perform multichannel recordings from the projection neurons in the AL driven by different odorants. We then derive a dynamic neuronal network from the electrophysiological data. The network consists of lateral-inhibitory neurons and excitatory neurons (modeled as firing-rate units, and is capable of producing unique olfactory neural codes for the tested odorants. To construct the network, we (i design a projection, an odor space, for the neural recording from the AL, which discriminates between distinct odorants trajectories (ii characterize scent recognition, i.e., decision-making based on olfactory signals and (iii infer the wiring of the neural circuit, the connectome of the AL. We show that the constructed model is consistent with biological observations, such as contrast enhancement and robustness to noise. The study suggests a data-driven approach to answer a key biological question in identifying how lateral inhibitory neurons can be wired to excitatory neurons to permit robust activity patterns.

  5. Data-driven inference of network connectivity for modeling the dynamics of neural codes in the insect antennal lobe.

    Science.gov (United States)

    Shlizerman, Eli; Riffell, Jeffrey A; Kutz, J Nathan

    2014-01-01

    The antennal lobe (AL), olfactory processing center in insects, is able to process stimuli into distinct neural activity patterns, called olfactory neural codes. To model their dynamics we perform multichannel recordings from the projection neurons in the AL driven by different odorants. We then derive a dynamic neuronal network from the electrophysiological data. The network consists of lateral-inhibitory neurons and excitatory neurons (modeled as firing-rate units), and is capable of producing unique olfactory neural codes for the tested odorants. To construct the network, we (1) design a projection, an odor space, for the neural recording from the AL, which discriminates between distinct odorants trajectories (2) characterize scent recognition, i.e., decision-making based on olfactory signals and (3) infer the wiring of the neural circuit, the connectome of the AL. We show that the constructed model is consistent with biological observations, such as contrast enhancement and robustness to noise. The study suggests a data-driven approach to answer a key biological question in identifying how lateral inhibitory neurons can be wired to excitatory neurons to permit robust activity patterns.

  6. The neural dynamics of reward value and risk coding in the human orbitofrontal cortex.

    Science.gov (United States)

    Li, Yansong; Vanni-Mercier, Giovanna; Isnard, Jean; Mauguière, François; Dreher, Jean-Claude

    2016-04-01

    The orbitofrontal cortex is known to carry information regarding expected reward, risk and experienced outcome. Yet, due to inherent limitations in lesion and neuroimaging methods, the neural dynamics of these computations has remained elusive in humans. Here, taking advantage of the high temporal definition of intracranial recordings, we characterize the neurophysiological signatures of the intact orbitofrontal cortex in processing information relevant for risky decisions. Local field potentials were recorded from the intact orbitofrontal cortex of patients suffering from drug-refractory partial epilepsy with implanted depth electrodes as they performed a probabilistic reward learning task that required them to associate visual cues with distinct reward probabilities. We observed three successive signals: (i) around 400 ms after cue presentation, the amplitudes of the local field potentials increased with reward probability; (ii) a risk signal emerged during the late phase of reward anticipation and during the outcome phase; and (iii) an experienced value signal appeared at the time of reward delivery. Both the medial and lateral orbitofrontal cortex encoded risk and reward probability while the lateral orbitofrontal cortex played a dominant role in coding experienced value. The present study provides the first evidence from intracranial recordings that the human orbitofrontal cortex codes reward risk both during late reward anticipation and during the outcome phase at a time scale of milliseconds. Our findings offer insights into the rapid mechanisms underlying the ability to learn structural relationships from the environment. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  7. Cellular and circuit mechanisms maintain low spike co-variability and enhance population coding in somatosensory cortex

    Directory of Open Access Journals (Sweden)

    Cheng eLy

    2012-03-01

    Full Text Available The responses of cortical neurons are highly variable across repeated presentations of a stimulus. Understanding this variability is critical for theories of both sensory and motor processing, since response variance affects the accuracy of neural codes. Despite this influence, the cellular and circuit mechanisms that shape the trial-to-trial variability of population responses remain poorly understood. We used a combination of experimental and computational techniques to uncover the mechanisms underlying response variability of populations of pyramidal (E cells in layer 2/3 of rat whisker barrel cortex. Spike trains recorded from pairs of E-cells during either spontaneous activity or whisker deflected responses show similarly low levels of spiking co-variability, despite large differences in network activation between the two states. We developed network models that show how spike threshold nonlinearities dilutes E-cell spiking co-variability during spontaneous activity and low velocity whisker deflections. In contrast, during high velocity whisker deflections, cancelation mechanisms mediated by feedforward inhibition maintain low E-cell pairwise co-variability. Thus, the combination of these two mechanisms ensure low E-cell population variability over a wide range of whisker deflection velocities. Finally, we show how this active decorrelation of population variability leads to a drastic increase in the population information about whisker velocity. The canonical cellular and circuit components of our study suggest that low network variability over a broad range of neural states may generalize across the nervous system.

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

    Directory of Open Access Journals (Sweden)

    Oran Zohar

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

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

    Science.gov (United States)

    Zohar, Oran; Shackleton, Trevor M; Palmer, Alan R; Shamir, Maoz

    2013-01-01

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

  10. Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks.

    Science.gov (United States)

    Kelley, David R; Snoek, Jasper; Rinn, John L

    2016-07-01

    The complex language of eukaryotic gene expression remains incompletely understood. Despite the importance suggested by many noncoding variants statistically associated with human disease, nearly all such variants have unknown mechanisms. Here, we address this challenge using an approach based on a recent machine learning advance-deep convolutional neural networks (CNNs). We introduce the open source package Basset to apply CNNs to learn the functional activity of DNA sequences from genomics data. We trained Basset on a compendium of accessible genomic sites mapped in 164 cell types by DNase-seq, and demonstrate greater predictive accuracy than previous methods. Basset predictions for the change in accessibility between variant alleles were far greater for Genome-wide association study (GWAS) SNPs that are likely to be causal relative to nearby SNPs in linkage disequilibrium with them. With Basset, a researcher can perform a single sequencing assay in their cell type of interest and simultaneously learn that cell's chromatin accessibility code and annotate every mutation in the genome with its influence on present accessibility and latent potential for accessibility. Thus, Basset offers a powerful computational approach to annotate and interpret the noncoding genome. © 2016 Kelley et al.; Published by Cold Spring Harbor Laboratory Press.

  11. A skin colour code for the Nigerian (Negroid) population | George ...

    African Journals Online (AJOL)

    ... for the Negroid skin in Nigeria including the Nigerian albino. The chart can be laminated using thin transparent plastic film to prevent transmission of infection from skin to skin in different people. A skin colour code can be useful for clinical evaluation of disease conditions like vitiligo as well as for epidemiological studies.

  12. Neural network river forecasting through baseflow separation and binary-coded swarm optimization

    Science.gov (United States)

    Taormina, Riccardo; Chau, Kwok-Wing; Sivakumar, Bellie

    2015-10-01

    The inclusion of expert knowledge in data-driven streamflow modeling is expected to yield more accurate estimates of river quantities. Modular models (MMs) designed to work on different parts of the hydrograph are preferred ways to implement such approach. Previous studies have suggested that better predictions of total streamflow could be obtained via modular Artificial Neural Networks (ANNs) trained to perform an implicit baseflow separation. These MMs fit separately the baseflow and excess flow components as produced by a digital filter, and reconstruct the total flow by adding these two signals at the output. The optimization of the filter parameters and ANN architectures is carried out through global search techniques. Despite the favorable premises, the real effectiveness of such MMs has been tested only on a few case studies, and the quality of the baseflow separation they perform has never been thoroughly assessed. In this work, we compare the performance of MM against global models (GMs) for nine different gaging stations in the northern United States. Binary-coded swarm optimization is employed for the identification of filter parameters and model structure, while Extreme Learning Machines, instead of ANN, are used to drastically reduce the large computational times required to perform the experiments. The results show that there is no evidence that MM outperform global GM for predicting the total flow. In addition, the baseflow produced by the MM largely underestimates the actual baseflow component expected for most of the considered gages. This occurs because the values of the filter parameters maximizing overall accuracy do not reflect the geological characteristics of the river basins. The results indeed show that setting the filter parameters according to expert knowledge results in accurate baseflow separation but lower accuracy of total flow predictions, suggesting that these two objectives are intrinsically conflicting rather than compatible.

  13. Reward cues in space: commonalities and differences in neural coding by hippocampal and ventral striatal ensembles.

    Science.gov (United States)

    Lansink, Carien S; Jackson, Jadin C; Lankelma, Jan V; Ito, Rutsuko; Robbins, Trevor W; Everitt, Barry J; Pennartz, Cyriel M A

    2012-09-05

    Forming place-reward associations critically depends on the integrity of the hippocampal-ventral striatal system. The ventral striatum (VS) receives a strong hippocampal input conveying spatial-contextual information, but it is unclear how this structure integrates this information to invigorate reward-directed behavior. Neuronal ensembles in rat hippocampus (HC) and VS were simultaneously recorded during a conditioning task in which navigation depended on path integration. In contrast to HC, ventral striatal neurons showed low spatial selectivity, but rather coded behavioral task phases toward reaching goal sites. Outcome-predicting cues induced a remapping of firing patterns in the HC, consistent with its role in episodic memory. VS remapped in conjunction with the HC, indicating that remapping can take place in multiple brain regions engaged in the same task. Subsets of ventral striatal neurons showed a "flip" from high activity when cue lights were illuminated to low activity in intertrial intervals, or vice versa. The cues induced an increase in spatial information transmission and sparsity in both structures. These effects were paralleled by an enhanced temporal specificity of ensemble coding and a more accurate reconstruction of the animal's position from population firing patterns. Altogether, the results reveal strong differences in spatial processing between hippocampal area CA1 and VS, but indicate similarities in how discrete cues impact on this processing.

  14. Spikes not slots: noise in neural populations limits working memory.

    Science.gov (United States)

    Bays, Paul M

    2015-08-01

    This opinion article argues that noise (randomness) in neural activity is the limiting factor in visual working memory (WM), determining how accurately we can maintain stable internal representations of external stimuli. Sharing of a fixed amount of neural activity between items in memory explains why WM can be successfully described as a continuous resource. This contrasts with the popular conception of WM as comprising a limited number of memory slots, each holding a representation of one stimulus - I argue that this view is challenged by computational theory and the latest neurophysiological evidence. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. Niche-dependent development of functional neuronal networks from embryonic stem cell-derived neural populations

    Directory of Open Access Journals (Sweden)

    Siebler Mario

    2009-08-01

    Full Text Available Abstract Background The present work was performed to investigate the ability of two different embryonic stem (ES cell-derived neural precursor populations to generate functional neuronal networks in vitro. The first ES cell-derived neural precursor population was cultivated as free-floating neural aggregates which are known to form a developmental niche comprising different types of neural cells, including neural precursor cells (NPCs, progenitor cells and even further matured cells. This niche provides by itself a variety of different growth factors and extracellular matrix proteins that influence the proliferation and differentiation of neural precursor and progenitor cells. The second population was cultivated adherently in monolayer cultures to control most stringently the extracellular environment. This population comprises highly homogeneous NPCs which are supposed to represent an attractive way to provide well-defined neuronal progeny. However, the ability of these different ES cell-derived immature neural cell populations to generate functional neuronal networks has not been assessed so far. Results While both precursor populations were shown to differentiate into sufficient quantities of mature NeuN+ neurons that also express GABA or vesicular-glutamate-transporter-2 (vGlut2, only aggregate-derived neuronal populations exhibited a synchronously oscillating network activity 2–4 weeks after initiating the differentiation as detected by the microelectrode array technology. Neurons derived from homogeneous NPCs within monolayer cultures did merely show uncorrelated spiking activity even when differentiated for up to 12 weeks. We demonstrated that these neurons exhibited sparsely ramified neurites and an embryonic vGlut2 distribution suggesting an inhibited terminal neuronal maturation. In comparison, neurons derived from heterogeneous populations within neural aggregates appeared as fully mature with a dense neurite network and punctuated

  16. Neural coding of time-varying interaural time differences and time-varying amplitude in the inferior colliculus.

    Science.gov (United States)

    Zuk, Nathaniel; Delgutte, Bertrand

    2017-07-01

    Binaural cues occurring in natural environments are frequently time varying, either from the motion of a sound source or through interactions between the cues produced by multiple sources. Yet, a broad understanding of how the auditory system processes dynamic binaural cues is still lacking. In the current study, we directly compared neural responses in the inferior colliculus (IC) of unanesthetized rabbits to broadband noise with time-varying interaural time differences (ITD) with responses to noise with sinusoidal amplitude modulation (SAM) over a wide range of modulation frequencies. On the basis of prior research, we hypothesized that the IC, one of the first stages to exhibit tuning of firing rate to modulation frequency, might use a common mechanism to encode time-varying information in general. Instead, we found weaker temporal coding for dynamic ITD compared with amplitude modulation and stronger effects of adaptation for amplitude modulation. The differences in temporal coding of dynamic ITD compared with SAM at the single-neuron level could be a neural correlate of "binaural sluggishness," the inability to perceive fluctuations in time-varying binaural cues at high modulation frequencies, for which a physiological explanation has so far remained elusive. At ITD-variation frequencies of 64 Hz and above, where a temporal code was less effective, noise with a dynamic ITD could still be distinguished from noise with a constant ITD through differences in average firing rate in many neurons, suggesting a frequency-dependent tradeoff between rate and temporal coding of time-varying binaural information.NEW & NOTEWORTHY Humans use time-varying binaural cues to parse auditory scenes comprising multiple sound sources and reverberation. However, the neural mechanisms for doing so are poorly understood. Our results demonstrate a potential neural correlate for the reduced detectability of fluctuations in time-varying binaural information at high speeds, as occurs in

  17. Task-specific codes for face recognition: how they shape the neural representation of features for detection and individuation.

    Science.gov (United States)

    Nestor, Adrian; Vettel, Jean M; Tarr, Michael J

    2008-01-01

    The variety of ways in which faces are categorized makes face recognition challenging for both synthetic and biological vision systems. Here we focus on two face processing tasks, detection and individuation, and explore whether differences in task demands lead to differences both in the features most effective for automatic recognition and in the featural codes recruited by neural processing. Our study appeals to a computational framework characterizing the features representing object categories as sets of overlapping image fragments. Within this framework, we assess the extent to which task-relevant information differs across image fragments. Based on objective differences we find among task-specific representations, we test the sensitivity of the human visual system to these different face descriptions independently of one another. Both behavior and functional magnetic resonance imaging reveal effects elicited by objective task-specific levels of information. Behaviorally, recognition performance with image fragments improves with increasing task-specific information carried by different face fragments. Neurally, this sensitivity to the two tasks manifests as differential localization of neural responses across the ventral visual pathway. Fragments diagnostic for detection evoke larger neural responses than non-diagnostic ones in the right posterior fusiform gyrus and bilaterally in the inferior occipital gyrus. In contrast, fragments diagnostic for individuation evoke larger responses than non-diagnostic ones in the anterior inferior temporal gyrus. Finally, for individuation only, pattern analysis reveals sensitivity to task-specific information within the right "fusiform face area". OUR RESULTS DEMONSTRATE: 1) information diagnostic for face detection and individuation is roughly separable; 2) the human visual system is independently sensitive to both types of information; 3) neural responses differ according to the type of task-relevant information

  18. Predicting CYP2C19 catalytic parameters for enantioselective oxidations using artificial neural networks and a chirality code.

    Science.gov (United States)

    Hartman, Jessica H; Cothren, Steven D; Park, Sun-Ha; Yun, Chul-Ho; Darsey, Jerry A; Miller, Grover P

    2013-07-01

    Cytochromes P450 (CYP for isoforms) play a central role in biological processes especially metabolism of chiral molecules; thus, development of computational methods to predict parameters for chiral reactions is important for advancing this field. In this study, we identified the most optimal artificial neural networks using conformation-independent chirality codes to predict CYP2C19 catalytic parameters for enantioselective reactions. Optimization of the neural networks required identifying the most suitable representation of structure among a diverse array of training substrates, normalizing distribution of the corresponding catalytic parameters (k(cat), K(m), and k(cat)/K(m)), and determining the best topology for networks to make predictions. Among different structural descriptors, the use of partial atomic charges according to the CHelpG scheme and inclusion of hydrogens yielded the most optimal artificial neural networks. Their training also required resolution of poorly distributed output catalytic parameters using a Box-Cox transformation. End point leave-one-out cross correlations of the best neural networks revealed that predictions for individual catalytic parameters (k(cat) and K(m)) were more consistent with experimental values than those for catalytic efficiency (k(cat)/K(m)). Lastly, neural networks predicted correctly enantioselectivity and comparable catalytic parameters measured in this study for previously uncharacterized CYP2C19 substrates, R- and S-propranolol. Taken together, these seminal computational studies for CYP2C19 are the first to predict all catalytic parameters for enantioselective reactions using artificial neural networks and thus provide a foundation for expanding the prediction of cytochrome P450 reactions to chiral drugs, pollutants, and other biologically active compounds. Copyright © 2013 Elsevier Ltd. All rights reserved.

  19. PopCORN: Hunting down the differences between binary population synthesis codes

    Science.gov (United States)

    Toonen, S.; Claeys, J. S. W.; Mennekens, N.; Ruiter, A. J.

    2014-02-01

    Context. Binary population synthesis (BPS) modelling is a very effective tool to study the evolution and properties of various types of close binary systems. The uncertainty in the parameters of the model and their effect on a population can be tested in a statistical way, which then leads to a deeper understanding of the underlying (sometimes poorly understood) physical processes involved. Several BPS codes exist that have been developed with different philosophies and aims. Although BPS has been very successful for studies of many populations of binary stars, in the particular case of the study of the progenitors of supernovae Type Ia, the predicted rates and ZAMS progenitors vary substantially between different BPS codes. Aims: To understand the predictive power of BPS codes, we study the similarities and differences in the predictions of four different BPS codes for low- and intermediate-mass binaries. We investigate the differences in the characteristics of the predicted populations, and whether they are caused by different assumptions made in the BPS codes or by numerical effects, e.g. a lack of accuracy in BPS codes. Methods: We compare a large number of evolutionary sequences for binary stars, starting with the same initial conditions following the evolution until the first (and when applicable, the second) white dwarf (WD) is formed. To simplify the complex problem of comparing BPS codes that are based on many (often different) assumptions, we equalise the assumptions as much as possible to examine the inherent differences of the four BPS codes. Results: We find that the simulated populations are similar between the codes. Regarding the population of binaries with one WD, there is very good agreement between the physical characteristics, the evolutionary channels that lead to the birth of these systems, and their birthrates. Regarding the double WD population, there is a good agreement on which evolutionary channels exist to create double WDs and a rough

  20. Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size.

    Directory of Open Access Journals (Sweden)

    Tilo Schwalger

    2017-04-01

    Full Text Available Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50-2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations.

  1. Population coding in area V4 during rapid shape detections

    Science.gov (United States)

    Weiner, Katherine F.

    2015-01-01

    While previous studies have suggested that neuronal correlations are common in visual cortex over a range of timescales, the effect of correlations on rapid visually based decisions has received little attention. We trained Macaca mulatta to saccade to a peripherally presented shape embedded in dynamic noise as soon as the shape appeared. While the monkeys performed the task, we recorded from neuronal populations (5–29 cells) using a microelectrode array implanted in area V4, a visual area thought to be involved in form perception. While modest correlations were present between cells during visual stimulation, their magnitude did not change significantly subsequent to the appearance of a shape. We quantified the reliability and temporal precision with which neuronal populations signaled the appearance of the shape and predicted the animals' choices using mutual information analyses. To study the impact of correlations, we shuffled the activity from each cell across observations while retaining stimulus-dependent modulations in firing rate. We found that removing correlations by shuffling across trials minimally affected the reliability or timing with which pairs, or larger groups of cells, signaled the presence of a shape. To assess the downstream impact of correlations, we also studied how shuffling affected the ability of V4 populations to predict behavioral choices. Surprisingly, shuffling created a modest increase in the accuracy of such predictions, suggesting that the reliability of downstream neurons is slightly compromised by activity correlations. Our findings are consistent with neuronal correlations having a minimal effect on the reliability and timing of rapid perceptual decisions. PMID:25787961

  2. Bilingualism provides a neural reserve for aging populations.

    Science.gov (United States)

    Abutalebi, Jubin; Guidi, Lucia; Borsa, Virginia; Canini, Matteo; Della Rosa, Pasquale A; Parris, Ben A; Weekes, Brendan S

    2015-03-01

    It has been postulated that bilingualism may act as a cognitive reserve and recent behavioral evidence shows that bilinguals are diagnosed with dementia about 4-5 years later compared to monolinguals. In the present study, we investigated the neural basis of these putative protective effects in a group of aging bilinguals as compared to a matched monolingual control group. For this purpose, participants completed the Erikson Flanker task and their performance was correlated to gray matter (GM) volume in order to investigate if cognitive performance predicts GM volume specifically in areas affected by aging. We performed an ex-Gaussian analysis on the resulting RTs and report that aging bilinguals performed better than aging monolinguals on the Flanker task. Bilingualism was overall associated with increased GM in the ACC. Likewise, aging induced effects upon performance correlated only for monolinguals to decreased gray matter in the DLPFC. Taken together, these neural regions might underlie the benefits of bilingualism and act as a neural reserve that protects against the cognitive decline that occurs during aging. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. A Perceptual-Like Population-Coding Mechanism of Approximate Numerical Averaging.

    Science.gov (United States)

    Brezis, Noam; Bronfman, Zohar Z; Usher, Marius

    2018-02-01

    Humans possess a remarkable ability to rapidly form coarse estimations of numerical averages. This ability is important for making decisions that are based on streams of numerical or value-based information, as well as for preference formation. Nonetheless, the mechanism underlying rapid approximate numerical averaging remains unknown, and several competing mechanism may account for it. Here, we tested the hypothesis that approximate numerical averaging relies on perceptual-like processes, instantiated by population coding. Participants were presented with rapid sequences of numerical values (four items per second) and were asked to convey the sequence average. We manipulated the sequences' length, variance, and mean magnitude and found that similar to perceptual averaging, the precision of the estimations improves with the length and deteriorates with (higher) variance or (higher) magnitude. To account for the results, we developed a biologically plausible population-coding model and showed that it is mathematically equivalent to a population vector. Using both quantitative and qualitative model comparison methods, we compared the population-coding model to several competing models, such as a step-by-step running average (based on leaky integration) and a midrange model. We found that the data support the population-coding model. We conclude that humans' ability to rapidly form estimations of numerical averages has many properties of the perceptual (intuitive) system rather than the arithmetic, linguistic-based (analytic) system and that population coding is likely to be its underlying mechanism.

  4. Neural network-based brain tissue segmentation in MR images using extracted features from intraframe coding in H.264

    Science.gov (United States)

    Jafari, Mehdi; Kasaei, Shohreh

    2012-01-01

    Automatic brain tissue segmentation is a crucial task in diagnosis and treatment of medical images. This paper presents a new algorithm to segment different brain tissues, such as white matter (WM), gray matter (GM), cerebral spinal fluid (CSF), background (BKG), and tumor tissues. The proposed technique uses the modified intraframe coding yielded from H.264/(AVC), for feature extraction. Extracted features are then imposed to an artificial back propagation neural network (BPN) classifier to assign each block to its appropriate class. Since the newest coding standard, H.264/AVC, has the highest compression ratio, it decreases the dimension of extracted features and thus yields to a more accurate classifier with low computational complexity. The performance of the BPN classifier is evaluated using the classification accuracy and computational complexity terms. The results show that the proposed technique is more robust and effective with low computational complexity compared to other recent works.

  5. LEARNING ALGORITHM EFFECT ON MULTILAYER FEED FORWARD ARTIFICIAL NEURAL NETWORK PERFORMANCE IN IMAGE CODING

    Directory of Open Access Journals (Sweden)

    OMER MAHMOUD

    2007-08-01

    Full Text Available One of the essential factors that affect the performance of Artificial Neural Networks is the learning algorithm. The performance of Multilayer Feed Forward Artificial Neural Network performance in image compression using different learning algorithms is examined in this paper. Based on Gradient Descent, Conjugate Gradient, Quasi-Newton techniques three different error back propagation algorithms have been developed for use in training two types of neural networks, a single hidden layer network and three hidden layers network. The essence of this study is to investigate the most efficient and effective training methods for use in image compression and its subsequent applications. The obtained results show that the Quasi-Newton based algorithm has better performance as compared to the other two algorithms.

  6. Single neuron and population coding of natural sounds in auditory cortex.

    Science.gov (United States)

    Mizrahi, Adi; Shalev, Amos; Nelken, Israel

    2014-02-01

    The auditory system drives behavior using information extracted from sounds. Early in the auditory hierarchy, circuits are highly specialized for detecting basic sound features. However, already at the level of the auditory cortex the functional organization of the circuits and the underlying coding principles become different. Here, we review some recent progress in our understanding of single neuron and population coding in primary auditory cortex, focusing on natural sounds. We discuss possible mechanisms explaining why single neuron responses to simple sounds cannot predict responses to natural stimuli. We describe recent work suggesting that structural features like local subnetworks rather than smoothly mapped tonotopy are essential components of population coding. Finally, we suggest a synthesis of how single neurons and subnetworks may be involved in coding natural sounds. Copyright © 2013 Elsevier Ltd. All rights reserved.

  7. Comparison of various NLTE codes in computing the charge-state populations of an argon plasma

    Energy Technology Data Exchange (ETDEWEB)

    Stone, S.R.; Weisheit, J.C.

    1984-11-01

    A comparison among nine computer codes shows surprisingly large differences where it had been believed that the theroy was well understood. Each code treats an argon plasma, optically thin and with no external photon flux; temperatures vary around 1 keV and ion densities vary from 6 x 10/sup 17/ cm/sup -3/ to 6 x 10/sup 21/ cm/sup -3/. At these conditions most ions have three or fewer bound electrons. The calculated populations of 0-, 1-, 2-, and 3-electron ions differ from code to code by typical factors of 2, in some cases by factors greater than 300. These differences depend as sensitively on how may Rydberg states a code allows as they do on variations among computed collision rates. 29 refs., 23 figs.

  8. The neural coding of feedback learning across child and adolescent development

    NARCIS (Netherlands)

    Peters, S.; Braams, B.R.; Raijmakers, M.E.J.; Koolschijn, P.C.M.P.; Crone, E.A.

    2014-01-01

    The ability to learn from environmental cues is an important contributor to successful performance in a variety of settings, including school. Despite the progress in unraveling the neural correlates of cognitive control in childhood and adolescence, relatively little is known about how these brain

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

    NARCIS (Netherlands)

    Kleibeuker, S.W.; Koolschijn, P.C.M.P.; Jolles, D.D.; de Dreu, C.K.W.; Crone, E.A.

    2013-01-01

    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 years) and adolescents (15-17 years).

  10. Sequential Sparsening by Successive Adaptation in Neural Populations

    CERN Document Server

    Farkhooi, Farzad; Nawrot, Martin P; 10.1186/1471-2202-10-S1-O10

    2010-01-01

    In the principal cells of the insect mushroom body, the Kenyon cells (KC), olfactory information is represented by a spatially and temporally sparse code. Each odor stimulus will activate only a small portion of neurons and each stimulus leads to only a short phasic response following stimulus onset irrespective of the actual duration of a constant stimulus. The mechanisms responsible for the sparse code in the KCs are yet unresolved. Here, we explore the role of the neuron-intrinsic mechanism of spike-frequency adaptation (SFA) in producing temporally sparse responses to sensory stimulation in higher processing stages. Our single neuron model is defined through a conductance-based integrate-and-fire neuron with spike-frequency adaptation [1]. We study a fully connected feed-forward network architecture in coarse analogy to the insect olfactory pathway. A first layer of ten neurons represents the projection neurons (PNs) of the antenna lobe. All PNs receive a step-like input from the olfactory receptor neuron...

  11. Plasticity in the neural coding of auditory space in the mammalian brain

    Science.gov (United States)

    King, Andrew J.; Parsons, Carl H.; Moore, David R.

    2000-10-01

    Sound localization relies on the neural processing of monaural and binaural spatial cues that arise from the way sounds interact with the head and external ears. Neurophysiological studies of animals raised with abnormal sensory inputs show that the map of auditory space in the superior colliculus is shaped during development by both auditory and visual experience. An example of this plasticity is provided by monaural occlusion during infancy, which leads to compensatory changes in auditory spatial tuning that tend to preserve the alignment between the neural representations of visual and auditory space. Adaptive changes also take place in sound localization behavior, as demonstrated by the fact that ferrets raised and tested with one ear plugged learn to localize as accurately as control animals. In both cases, these adjustments may involve greater use of monaural spectral cues provided by the other ear. Although plasticity in the auditory space map seems to be restricted to development, adult ferrets show some recovery of sound localization behavior after long-term monaural occlusion. The capacity for behavioral adaptation is, however, task dependent, because auditory spatial acuity and binaural unmasking (a measure of the spatial contribution to the "cocktail party effect") are permanently impaired by chronically plugging one ear, both in infancy but especially in adulthood. Experience-induced plasticity allows the neural circuitry underlying sound localization to be customized to individual characteristics, such as the size and shape of the head and ears, and to compensate for natural conductive hearing losses, including those associated with middle ear disease in infancy.

  12. Magnified Neural Envelope Coding Predicts Deficits in Speech Perception in Noise.

    Science.gov (United States)

    Millman, Rebecca E; Mattys, Sven L; Gouws, André D; Prendergast, Garreth

    2017-08-09

    Verbal communication in noisy backgrounds is challenging. Understanding speech in background noise that fluctuates in intensity over time is particularly difficult for hearing-impaired listeners with a sensorineural hearing loss (SNHL). The reduction in fast-acting cochlear compression associated with SNHL exaggerates the perceived fluctuations in intensity in amplitude-modulated sounds. SNHL-induced changes in the coding of amplitude-modulated sounds may have a detrimental effect on the ability of SNHL listeners to understand speech in the presence of modulated background noise. To date, direct evidence for a link between magnified envelope coding and deficits in speech identification in modulated noise has been absent. Here, magnetoencephalography was used to quantify the effects of SNHL on phase locking to the temporal envelope of modulated noise (envelope coding) in human auditory cortex. Our results show that SNHL enhances the amplitude of envelope coding in posteromedial auditory cortex, whereas it enhances the fidelity of envelope coding in posteromedial and posterolateral auditory cortex. This dissociation was more evident in the right hemisphere, demonstrating functional lateralization in enhanced envelope coding in SNHL listeners. However, enhanced envelope coding was not perceptually beneficial. Our results also show that both hearing thresholds and, to a lesser extent, magnified cortical envelope coding in left posteromedial auditory cortex predict speech identification in modulated background noise. We propose a framework in which magnified envelope coding in posteromedial auditory cortex disrupts the segregation of speech from background noise, leading to deficits in speech perception in modulated background noise.SIGNIFICANCE STATEMENT People with hearing loss struggle to follow conversations in noisy environments. Background noise that fluctuates in intensity over time poses a particular challenge. Using magnetoencephalography, we demonstrate

  13. Enrichment of skin-derived neural precursor cells from dermal cell populations by altering culture conditions.

    Science.gov (United States)

    Bayati, Vahid; Gazor, Rohoullah; Nejatbakhsh, Reza; Negad Dehbashi, Fereshteh

    2016-01-01

    As stem cells play a critical role in tissue repair, their manipulation for being applied in regenerative medicine is of great importance. Skin-derived precursors (SKPs) may be good candidates for use in cell-based therapy as the only neural stem cells which can be isolated from an accessible tissue, skin. Herein, we presented a simple protocol to enrich neural SKPs by monolayer adherent cultivation to prove the efficacy of this method. To enrich neural SKPs from dermal cell populations, we have found that a monolayer adherent cultivation helps to increase the numbers of neural precursor cells. Indeed, we have cultured dermal cells as monolayer under serum-supplemented (control) and serum-supplemented culture, followed by serum free cultivation (test) and compared. Finally, protein markers of SKPs were assessed and compared in both experimental groups and differentiation potential was evaluated in enriched culture. The cells of enriched culture concurrently expressed fibronectin, vimentin and nestin, an intermediate filament protein expressed in neural and skeletal muscle precursors as compared to control culture. In addition, they possessed a multipotential capacity to differentiate into neurogenic, glial, adipogenic, osteogenic and skeletal myogenic cell lineages. It was concluded that serum-free adherent culture reinforced by growth factors have been shown to be effective on proliferation of skin-derived neural precursor cells (skin-NPCs) and drive their selective and rapid expansion.

  14. Neural Coding of Relational Invariance in Speech: Human Language Analogs to the Barn Owl.

    Science.gov (United States)

    Sussman, Harvey M.

    1989-01-01

    The neuronal model shown to code sound-source azimuth in the barn owl by H. Wagner et al. in 1987 is used as the basis for a speculative brain-based human model, which can establish contrastive phonetic categories to solve the problem of perception "non-invariance." (SLD)

  15. Relating population-code representations between man, monkey, and computational models

    Directory of Open Access Journals (Sweden)

    Nikolaus Kriegeskorte

    2009-12-01

    Full Text Available Perceptual and cognitive content is thought to be represented in the brain by patterns of activity across populations of neurons. In order to test whether a computational model can explain a given population code and whether corresponding codes in man and monkey convey the same information, we need to quantitatively relate population-code representations. Here I give a brief introduction to representational similarity analysis (RSA, a particular approach to this problem. A population code is characterized by a representational dissimilarity matrix (RDM, which contains a dissimilarity for each pair of activity patterns elicited by a given stimulus set. The RDM encapsulates which distinctions the representation emphasizes and which it deemphasizes. By analyzing correlations between RDMs we can test models and compare different species. Moreover, we can study how representations are transformed across stages of processing and how they relate to behavioral measures of object similarity. We use an example from object vision to illustrate the method’s potential to bridge major divides that have hampered progress in systems neuroscience.

  16. Population equations for degree-heterogenous neural networks

    Science.gov (United States)

    Kähne, M.; Sokolov, I. M.; Rüdiger, S.

    2017-11-01

    We develop a statistical framework for studying recurrent networks with broad distributions of the number of synaptic links per neuron. We treat each group of neurons with equal input degree as one population and derive a system of equations determining the population-averaged firing rates. The derivation rests on an assumption of a large number of neurons and, additionally, an assumption of a large number of synapses per neuron. For the case of binary neurons, analytical solutions can be constructed, which correspond to steps in the activity versus degree space. We apply this theory to networks with degree-correlated topology and show that complex, multi-stable regimes can result for increasing correlations. Our work is motivated by the recent finding of subnetworks of highly active neurons and the fact that these neurons tend to be connected to each other with higher probability.

  17. 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.

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

    Science.gov (United States)

    Kleibeuker, Sietske W; Koolschijn, P Cédric M P; Jolles, Dietsje D; De Dreu, Carsten K W; Crone, Eveline A

    2013-01-01

    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 years) and adolescents (15-17 years). 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 AU 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.

  19. The neural coding of feedback learning across child and adolescent development.

    Science.gov (United States)

    Peters, Sabine; Braams, Barbara R; Raijmakers, Maartje E J; Koolschijn, P Cédric M P; Crone, Eveline A

    2014-08-01

    The ability to learn from environmental cues is an important contributor to successful performance in a variety of settings, including school. Despite the progress in unraveling the neural correlates of cognitive control in childhood and adolescence, relatively little is known about how these brain regions contribute to learning. In this study, 268 participants aged 8-25 years performed a rule-learning task with performance feedback in a 3T MRI scanner. We examined the development of the frontoparietal network during feedback learning by exploring contributions of age and pubertal development. The pFC showed more activation following negative compared with positive feedback with increasing age. In contrast, our data suggested that the parietal cortex demonstrated a shift from sensitivity to positive feedback in young children to negative feedback in adolescents and adults. These findings were interpreted in terms of separable contributions of the frontoparietal network in childhood to more integrated functions in adulthood. Puberty (testosterone, estradiol, and self-report) did not explain additional variance in neural activation patterns above age, suggesting that development of the frontoparietal network occurs relatively independently from hormonal development. This study presents novel insights into the development of learning, moving beyond a simple frontoparietal immaturity hypothesis.

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

    Science.gov (United States)

    Kleibeuker, Sietske W.; Koolschijn, P. Cédric M. P.; Jolles, Dietsje D.; De Dreu, Carsten K. W.; Crone, Eveline A.

    2013-01-01

    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 years) and adolescents (15–17 years). 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 AU 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. PMID:24416008

  1. Neural Substrates of Visual Spatial Coding and Visual Feedback Control for Hand Movements in Allocentric and Target-Directed Tasks

    Science.gov (United States)

    Thaler, Lore; Goodale, Melvyn A.

    2011-01-01

    Neuropsychological evidence suggests that different brain areas may be involved in movements that are directed at visual targets (e.g., pointing or reaching), and movements that are based on allocentric visual information (e.g., drawing or copying). Here we used fMRI to investigate the neural correlates of these two types of movements in healthy volunteers. Subjects (n = 14) performed right hand movements in either a target-directed task (moving a cursor to a target dot) or an allocentric task (moving a cursor to reproduce the distance and direction between two distal target dots) with or without visual feedback about their hand movement. Movements were monitored with an MR compatible touch panel. A whole brain analysis revealed that movements in allocentric conditions led to an increase in activity in the fundus of the left intra-parietal sulcus (IPS), in posterior IPS, in bilateral dorsal premotor cortex (PMd), and in the lateral occipital complex (LOC). Visual feedback in both target-directed and allocentric conditions led to an increase in activity in area MT+, superior parietal–occipital cortex (SPOC), and posterior IPS (all bilateral). In addition, we found that visual feedback affected brain activity differently in target-directed as compared to allocentric conditions, particularly in the pre-supplementary motor area, PMd, IPS, and parieto-occipital cortex. Our results, in combination with previous findings, suggest that the LOC is essential for allocentric visual coding and that SPOC is involved in visual feedback control. The differences in brain activity between target-directed and allocentric visual feedback conditions may be related to behavioral differences in visual feedback control. Our results advance the understanding of the visual coordinate frame used by the LOC. In addition, because of the nature of the allocentric task, our results have relevance for the understanding of neural substrates of magnitude estimation and vector coding of

  2. Finite population analysis of the effect of horizontal gene transfer on the origin of an universal and optimal genetic code

    Science.gov (United States)

    Aggarwal, Neha; Vishwa Bandhu, Ashutosh; Sengupta, Supratim

    2016-06-01

    The origin of a universal and optimal genetic code remains a compelling mystery in molecular biology and marks an essential step in the origin of DNA and protein based life. We examine a collective evolution model of genetic code origin that allows for unconstrained horizontal transfer of genetic elements within a finite population of sequences each of which is associated with a genetic code selected from a pool of primordial codes. We find that when horizontal transfer of genetic elements is incorporated in this more realistic model of code-sequence coevolution in a finite population, it can increase the likelihood of emergence of a more optimal code eventually leading to its universality through fixation in the population. The establishment of such an optimal code depends on the probability of HGT events. Only when the probability of HGT events is above a critical threshold, we find that the ten amino acid code having a structure that is most consistent with the standard genetic code (SGC) often gets fixed in the population with the highest probability. We examine how the threshold is determined by factors like the population size, length of the sequences and selection coefficient. Our simulation results reveal the conditions under which sharing of coding innovations through horizontal transfer of genetic elements may have facilitated the emergence of a universal code having a structure similar to that of the SGC.

  3. Neural coding merges sex and habitat chemosensory signals in an insect herbivore.

    Science.gov (United States)

    Trona, Federica; Anfora, Gianfranco; Balkenius, Anna; Bengtsson, Marie; Tasin, Marco; Knight, Alan; Janz, Niklas; Witzgall, Peter; Ignell, Rickard

    2013-06-07

    Understanding the processing of odour mixtures is a focus in olfaction research. Through a neuroethological approach, we demonstrate that different odour types, sex and habitat cues are coded together in an insect herbivore. Stronger flight attraction of codling moth males, Cydia pomonella, to blends of female sex pheromone and plant odour, compared with single compounds, was corroborated by functional imaging of the olfactory centres in the insect brain, the antennal lobes (ALs). The macroglomerular complex (MGC) in the AL, which is dedicated to pheromone perception, showed an enhanced response to blends of pheromone and plant signals, whereas the response in glomeruli surrounding the MGC was suppressed. Intracellular recordings from AL projection neurons that transmit odour information to higher brain centres, confirmed this synergistic interaction in the MGC. These findings underscore that, in nature, sex pheromone and plant odours are perceived as an ensemble. That mating and habitat cues are coded as blends in the MGC of the AL highlights the dual role of plant signals in habitat selection and in premating sexual communication. It suggests that the MGC is a common target for sexual and natural selection in moths, facilitating ecological speciation.

  4. Neural coding in antennal olfactory cells of tsetse flies (Glossina spp.).

    Science.gov (United States)

    Voskamp, K E; Noorman, N; Mastebroek, H A; Van Schoot, N E; Den Otter, C J

    1998-10-01

    Spike trains from individual antennal olfactory cells of tsetse flies (Glossina spp.) obtained during steady-state conditions (spontaneous as well as during stimulation with 1-octen-3-ol) and dynamic stimulation with repetitive pulses of 1-octen-3-ol were investigated by studying the spike frequency and the temporal structure of the trains. In general, stimulation changes the intensity of the spike activity but leaves the underlying stochastic structure unaffected. This structure turns out to be a renewal process. The only independently varying parameter in this process is the mean interspike interval length, suggesting that olfactory cells of tsetse flies may transmit information via a frequency coding. In spike records with high firing rates, however, the stationary records had significant negative first-order serial correlation coefficients and were non-renewal. Some cells in this study were capable of precisely encoding the onset of the odour pulses at frequencies up to at least 3 Hz. Cells with a rapid return to pre-stimulus activity at the end of stimulation responded more adequately to pulsed stimuli than cells with a long increased spike frequency. While short-firing cells process information via a frequency code, long-firing cells responded with two distinctive phases: a phasic, non-renewal response and a tonic, renewal response which may function as a memory of previous stimulations.

  5. Neural coding of assessing another person's knowledge based on nonverbal cues.

    Science.gov (United States)

    Kuhlen, Anna K; Bogler, Carsten; Swerts, Marc; Haynes, John-Dylan

    2015-05-01

    For successful communication, conversational partners need to estimate each other's current knowledge state. Nonverbal facial and bodily cues can reveal relevant information about how confident a speaker is about what they are saying. Using functional magnetic resonance imaging, we aimed to identify brain regions that encode how confident a speaker is perceived to be. Participants viewed videos of people answering general knowledge questions and judged each respondent's confidence in their answer. Our results suggest a distinct role of two neural networks known to support social inferences, the so-called mentalizing and the mirroring network. While activation in both networks underlies the processing of nonverbal cues, only activity in the mentalizing network, most notably the medial prefrontal cortex and the bilateral temporoparietal junction, is modulated by how confident the respondent is judged to be. Our results support an integrative account of the mirroring and mentalizing network, in which the two systems support each other in aiding pragmatic processing. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  6. Consequences of converting graded to action potentials upon neural information coding and energy efficiency.

    Directory of Open Access Journals (Sweden)

    Biswa Sengupta

    2014-01-01

    Full Text Available Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na(+ and K(+ channels, with generator potential and graded potential models lacking voltage-gated Na(+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1 the voltage-gated Na(+ channels necessary for action potential generation increase intrinsic noise and (2 introduce non-linearities, and (3 the finite duration of the action potential creates a 'footprint' in the generator potential that obscures incoming signals. These three processes reduce information rates by ∼50% in generator potentials, to ∼3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation.

  7. Occupational self-coding and automatic recording (OSCAR): a novel web-based tool to collect and code lifetime job histories in large population-based studies.

    Science.gov (United States)

    De Matteis, Sara; Jarvis, Deborah; Young, Heather; Young, Alan; Allen, Naomi; Potts, James; Darnton, Andrew; Rushton, Lesley; Cullinan, Paul

    2017-03-01

    Objectives The standard approach to the assessment of occupational exposures is through the manual collection and coding of job histories. This method is time-consuming and costly and makes it potentially unfeasible to perform high quality analyses on occupational exposures in large population-based studies. Our aim was to develop a novel, efficient web-based tool to collect and code lifetime job histories in the UK Biobank, a population-based cohort of over 500 000 participants. Methods We developed OSCAR (occupations self-coding automatic recording) based on the hierarchical structure of the UK Standard Occupational Classification (SOC) 2000, which allows individuals to collect and automatically code their lifetime job histories via a simple decision-tree model. Participants were asked to find each of their jobs by selecting appropriate job categories until they identified their job title, which was linked to a hidden 4-digit SOC code. For each occupation a job title in free text was also collected to estimate Cohen's kappa (κ) inter-rater agreement between SOC codes assigned by OSCAR and an expert manual coder. Results OSCAR was administered to 324 653 UK Biobank participants with an existing email address between June and September 2015. Complete 4-digit SOC-coded lifetime job histories were collected for 108 784 participants (response rate: 34%). Agreement between the 4-digit SOC codes assigned by OSCAR and the manual coder for a random sample of 400 job titles was moderately good [κ=0.45, 95% confidence interval (95% CI) 0.42-0.49], and improved when broader job categories were considered (κ=0.64, 95% CI 0.61-0.69 at a 1-digit SOC-code level). Conclusions OSCAR is a novel, efficient, and reasonably reliable web-based tool for collecting and automatically coding lifetime job histories in large population-based studies. Further application in other research projects for external validation purposes is warranted.

  8. The neural coding of expected and unexpected monetary performance outcomes: dissociations between active and observational learning.

    Science.gov (United States)

    Bellebaum, C; Jokisch, D; Gizewski, E R; Forsting, M; Daum, I

    2012-02-01

    Successful adaptation to the environment requires the learning of stimulus-response-outcome associations. Such associations can be learned actively by trial and error or by observing the behaviour and accompanying outcomes in other persons. The present study investigated similarities and differences in the neural mechanisms of active and observational learning from monetary feedback using functional magnetic resonance imaging. Two groups of 15 subjects each - active and observational learners - participated in the experiment. On every trial, active learners chose between two stimuli and received monetary feedback. Each observational learner observed the choices and outcomes of one active learner. Learning performance as assessed via active test trials without feedback was comparable between groups. Different activation patterns were observed for the processing of unexpected vs. expected monetary feedback in active and observational learners, particularly for positive outcomes. Activity for unexpected vs. expected reward was stronger in the right striatum in active learning, while activity in the hippocampus was bilaterally enhanced in observational and reduced in active learning. Modulation of activity by prediction error (PE) magnitude was observed in the right putamen in both types of learning, whereas PE related activations in the right anterior caudate nucleus and in the medial orbitofrontal cortex were stronger for active learning. The striatum and orbitofrontal cortex thus appear to link reward stimuli to own behavioural reactions and are less strongly involved when the behavioural outcome refers to another person's action. Alternative explanations such as differences in reward value between active and observational learning are also discussed. Copyright © 2011 Elsevier B.V. All rights reserved.

  9. HLA-E regulatory and coding region variability and haplotypes in a Brazilian population sample.

    Science.gov (United States)

    Ramalho, Jaqueline; Veiga-Castelli, Luciana C; Donadi, Eduardo A; Mendes-Junior, Celso T; Castelli, Erick C

    2017-11-01

    The HLA-E gene is characterized by low but wide expression on different tissues. HLA-E is considered a conserved gene, being one of the least polymorphic class I HLA genes. The HLA-E molecule interacts with Natural Killer cell receptors and T lymphocytes receptors, and might activate or inhibit immune responses depending on the peptide associated with HLA-E and with which receptors HLA-E interacts to. Variable sites within the HLA-E regulatory and coding segments may influence the gene function by modifying its expression pattern or encoded molecule, thus, influencing its interaction with receptors and the peptide. Here we propose an approach to evaluate the gene structure, haplotype pattern and the complete HLA-E variability, including regulatory (promoter and 3'UTR) and coding segments (with introns), by using massively parallel sequencing. We investigated the variability of 420 samples from a very admixed population such as Brazilians by using this approach. Considering a segment of about 7kb, 63 variable sites were detected, arranged into 75 extended haplotypes. We detected 37 different promoter sequences (but few frequent ones), 27 different coding sequences (15 representing new HLA-E alleles) and 12 haplotypes at the 3'UTR segment, two of them presenting a summed frequency of 90%. Despite the number of coding alleles, they encode mainly two different full-length molecules, known as E*01:01 and E*01:03, which corresponds to about 90% of all. In addition, differently from what has been previously observed for other non classical HLA genes, the relationship among the HLA-E promoter, coding and 3'UTR haplotypes is not straightforward because the same promoter and 3'UTR haplotypes were many times associated with different HLA-E coding haplotypes. This data reinforces the presence of only two main full-length HLA-E molecules encoded by the many HLA-E alleles detected in our population sample. In addition, this data does indicate that the distal HLA-E promoter is by

  10. Predicting Motivation: Computational Models of PFC Can Explain Neural Coding of Motivation and Effort-based Decision-making in Health and Disease.

    Science.gov (United States)

    Vassena, Eliana; Deraeve, James; Alexander, William H

    2017-10-01

    Human behavior is strongly driven by the pursuit of rewards. In daily life, however, benefits mostly come at a cost, often requiring that effort be exerted to obtain potential benefits. Medial PFC (MPFC) and dorsolateral PFC (DLPFC) are frequently implicated in the expectation of effortful control, showing increased activity as a function of predicted task difficulty. Such activity partially overlaps with expectation of reward and has been observed both during decision-making and during task preparation. Recently, novel computational frameworks have been developed to explain activity in these regions during cognitive control, based on the principle of prediction and prediction error (predicted response-outcome [PRO] model [Alexander, W. H., & Brown, J. W. Medial prefrontal cortex as an action-outcome predictor. Nature Neuroscience, 14, 1338-1344, 2011], hierarchical error representation [HER] model [Alexander, W. H., & Brown, J. W. Hierarchical error representation: A computational model of anterior cingulate and dorsolateral prefrontal cortex. Neural Computation, 27, 2354-2410, 2015]). Despite the broad explanatory power of these models, it is not clear whether they can also accommodate effects related to the expectation of effort observed in MPFC and DLPFC. Here, we propose a translation of these computational frameworks to the domain of effort-based behavior. First, we discuss how the PRO model, based on prediction error, can explain effort-related activity in MPFC, by reframing effort-based behavior in a predictive context. We propose that MPFC activity reflects monitoring of motivationally relevant variables (such as effort and reward), by coding expectations and discrepancies from such expectations. Moreover, we derive behavioral and neural model-based predictions for healthy controls and clinical populations with impairments of motivation. Second, we illustrate the possible translation to effort-based behavior of the HER model, an extended version of PRO

  11. Identification of neural firing patterns, frequency and temporal coding mechanisms in individual aortic baroreceptors

    Directory of Open Access Journals (Sweden)

    Huaguang eGu

    2015-08-01

    Full Text Available In rabbit depressor nerve fibers, an on-off firing pattern, period-1 firing, and integer multiple firing with quiescent state were observed as the static pressure level was increased. A bursting pattern with bursts at the systolic phase of blood pressure, continuous firing, and bursting with burst at diastolic phase and quiescent state at systolic phase were observed as the mean level of the dynamic blood pressure was increased. For both static and dynamic pressures, the firing frequency of the first two firing patterns increased and of the last firing pattern decreased due to the quiescent state. If the quiescent state is disregarded, the spike frequency becomes an increasing trend. The instantaneous spike frequency of the systolic phase bursting, continuous firing, and diastolic phase bursting can reflect the temporal process of the systolic phase, whole procedure, and diastolic phase of the dynamic blood pressure signal, respectively. With increasing the static current corresponding to pressure level, the deterministic Hodgkin-Huxley (HH model manifests a process from a resting state first to period-1 firing via a subcritical Hopf bifurcation and then to a resting state via a supercritical Hopf bifurcation, and the firing frequency increases. The on-off firing and integer multiple firing were here identified as noise-induced firing patterns near the subcritical and supercritical Hopf bifurcation points, respectively, using the stochastic HH model. The systolic phase bursting and diastolic phase bursting were identified as pressure-induced firings near the subcritical and supercritical Hopf bifurcation points, respectively, using an HH model with a dynamic signal. The firing, spike frequency, and instantaneous spike frequency observed in the experiment were simulated and explained using HH models. The results illustrate the dynamics of different firing patterns and the frequency and temporal coding mechanisms of aortic baroreceptor.

  12. A neural population model incorporating dopaminergic neurotransmission during complex voluntary behaviors.

    Directory of Open Access Journals (Sweden)

    Stefan Fürtinger

    2014-11-01

    Full Text Available Assessing brain activity during complex voluntary motor behaviors that require the recruitment of multiple neural sites is a field of active research. Our current knowledge is primarily based on human brain imaging studies that have clear limitations in terms of temporal and spatial resolution. We developed a physiologically informed non-linear multi-compartment stochastic neural model to simulate functional brain activity coupled with neurotransmitter release during complex voluntary behavior, such as speech production. Due to its state-dependent modulation of neural firing, dopaminergic neurotransmission plays a key role in the organization of functional brain circuits controlling speech and language and thus has been incorporated in our neural population model. A rigorous mathematical proof establishing existence and uniqueness of solutions to the proposed model as well as a computationally efficient strategy to numerically approximate these solutions are presented. Simulated brain activity during the resting state and sentence production was analyzed using functional network connectivity, and graph theoretical techniques were employed to highlight differences between the two conditions. We demonstrate that our model successfully reproduces characteristic changes seen in empirical data between the resting state and speech production, and dopaminergic neurotransmission evokes pronounced changes in modeled functional connectivity by acting on the underlying biological stochastic neural model. Specifically, model and data networks in both speech and rest conditions share task-specific network features: both the simulated and empirical functional connectivity networks show an increase in nodal influence and segregation in speech over the resting state. These commonalities confirm that dopamine is a key neuromodulator of the functional connectome of speech control. Based on reproducible characteristic aspects of empirical data, we suggest a number

  13. The opponent channel population code of sound location is an efficient representation of natural binaural sounds.

    Science.gov (United States)

    Młynarski, Wiktor

    2015-05-01

    In mammalian auditory cortex, sound source position is represented by a population of broadly tuned neurons whose firing is modulated by sounds located at all positions surrounding the animal. Peaks of their tuning curves are concentrated at lateral position, while their slopes are steepest at the interaural midline, allowing for the maximum localization accuracy in that area. These experimental observations contradict initial assumptions that the auditory space is represented as a topographic cortical map. It has been suggested that a "panoramic" code has evolved to match specific demands of the sound localization task. This work provides evidence suggesting that properties of spatial auditory neurons identified experimentally follow from a general design principle- learning a sparse, efficient representation of natural stimuli. Natural binaural sounds were recorded and served as input to a hierarchical sparse-coding model. In the first layer, left and right ear sounds were separately encoded by a population of complex-valued basis functions which separated phase and amplitude. Both parameters are known to carry information relevant for spatial hearing. Monaural input converged in the second layer, which learned a joint representation of amplitude and interaural phase difference. Spatial selectivity of each second-layer unit was measured by exposing the model to natural sound sources recorded at different positions. Obtained tuning curves match well tuning characteristics of neurons in the mammalian auditory cortex. This study connects neuronal coding of the auditory space with natural stimulus statistics and generates new experimental predictions. Moreover, results presented here suggest that cortical regions with seemingly different functions may implement the same computational strategy-efficient coding.

  14. The opponent channel population code of sound location is an efficient representation of natural binaural sounds.

    Directory of Open Access Journals (Sweden)

    Wiktor Młynarski

    2015-05-01

    Full Text Available In mammalian auditory cortex, sound source position is represented by a population of broadly tuned neurons whose firing is modulated by sounds located at all positions surrounding the animal. Peaks of their tuning curves are concentrated at lateral position, while their slopes are steepest at the interaural midline, allowing for the maximum localization accuracy in that area. These experimental observations contradict initial assumptions that the auditory space is represented as a topographic cortical map. It has been suggested that a "panoramic" code has evolved to match specific demands of the sound localization task. This work provides evidence suggesting that properties of spatial auditory neurons identified experimentally follow from a general design principle- learning a sparse, efficient representation of natural stimuli. Natural binaural sounds were recorded and served as input to a hierarchical sparse-coding model. In the first layer, left and right ear sounds were separately encoded by a population of complex-valued basis functions which separated phase and amplitude. Both parameters are known to carry information relevant for spatial hearing. Monaural input converged in the second layer, which learned a joint representation of amplitude and interaural phase difference. Spatial selectivity of each second-layer unit was measured by exposing the model to natural sound sources recorded at different positions. Obtained tuning curves match well tuning characteristics of neurons in the mammalian auditory cortex. This study connects neuronal coding of the auditory space with natural stimulus statistics and generates new experimental predictions. Moreover, results presented here suggest that cortical regions with seemingly different functions may implement the same computational strategy-efficient coding.

  15. The Opponent Channel Population Code of Sound Location Is an Efficient Representation of Natural Binaural Sounds

    Science.gov (United States)

    Młynarski, Wiktor

    2015-01-01

    In mammalian auditory cortex, sound source position is represented by a population of broadly tuned neurons whose firing is modulated by sounds located at all positions surrounding the animal. Peaks of their tuning curves are concentrated at lateral position, while their slopes are steepest at the interaural midline, allowing for the maximum localization accuracy in that area. These experimental observations contradict initial assumptions that the auditory space is represented as a topographic cortical map. It has been suggested that a “panoramic” code has evolved to match specific demands of the sound localization task. This work provides evidence suggesting that properties of spatial auditory neurons identified experimentally follow from a general design principle- learning a sparse, efficient representation of natural stimuli. Natural binaural sounds were recorded and served as input to a hierarchical sparse-coding model. In the first layer, left and right ear sounds were separately encoded by a population of complex-valued basis functions which separated phase and amplitude. Both parameters are known to carry information relevant for spatial hearing. Monaural input converged in the second layer, which learned a joint representation of amplitude and interaural phase difference. Spatial selectivity of each second-layer unit was measured by exposing the model to natural sound sources recorded at different positions. Obtained tuning curves match well tuning characteristics of neurons in the mammalian auditory cortex. This study connects neuronal coding of the auditory space with natural stimulus statistics and generates new experimental predictions. Moreover, results presented here suggest that cortical regions with seemingly different functions may implement the same computational strategy-efficient coding. PMID:25996373

  16. Functional analysis of PCSK2 coding variants: A founder effect in the Old Order Amish population.

    Science.gov (United States)

    Winters, Alexandra; Ramos-Molina, Bruno; Jarvela, Timothy S; Yerges-Armstrong, Laura; Pollin, Toni I; Lindberg, Iris

    2017-09-01

    In humans, noncoding variants of PCSK2, the gene encoding prohormone convertase 2 (PC2), have been previously associated with risk for and age of onset of type 2 diabetes (T2D). The aims of this study were to identify coding variants in PCSK2; to determine their possible association with glucose handling; and to determine functional outcomes for coding variants in biochemical studies. Exome-wide genotyping was performed on 1725 Old Order Amish (OOA) subjects. PCSK2 coding variants were tested for association with diabetes-related phenotypes. In vitro analyses using transfected human PC2-encoding constructs were performed to determine the impact of each mutation on PC2 activity. We identified 10 rare missense coding variants in PCSK2 in various genomic databases. R430W (rs200711626) is greatly enriched in the OOA population (MAF 4.3%). This variant is almost twice as common (MAF 7.4%) in OOA individuals with T2D as in OOA individuals with normal or with normal/impaired glucose tolerance (MAF 3.9% and 2.9%, respectively; p=0.25 and p=0.10). In vitro experiments revealed a broadening of the pH optimum for the R430W variant, which may result in increased activity against PCSK2 substrates. Although the association of the R430W variation with T2D in the OOA population did not reach significance, based upon the broadened pH profile of R430W PC2, we speculate that the presence of this substitution may result in altered processing of PCSK2 substrates, ultimately leading to increased conversion to diabetes. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Physical activity and influenza-coded outpatient visits, a population-based cohort study.

    Directory of Open Access Journals (Sweden)

    Eric Siu

    Full Text Available Although the benefits of physical activity in preventing chronic medical conditions are well established, its impacts on infectious diseases, and seasonal influenza in particular, are less clearly defined. We examined the association between physical activity and influenza-coded outpatient visits, as a proxy for influenza infection.We conducted a cohort study of Ontario respondents to Statistics Canada's population health surveys over 12 influenza seasons. We assessed physical activity levels through survey responses, and influenza-coded physician office and emergency department visits through physician billing claims. We used logistic regression to estimate the risk of influenza-coded outpatient visits during influenza seasons. The cohort comprised 114,364 survey respondents who contributed 357,466 person-influenza seasons of observation. Compared to inactive individuals, moderately active (OR 0.83; 95% CI 0.74-0.94 and active (OR 0.87; 95% CI 0.77-0.98 individuals were less likely to experience an influenza-coded visit. Stratifying by age, the protective effect of physical activity remained significant for individuals <65 years (active OR 0.86; 95% CI 0.75-0.98, moderately active: OR 0.85; 95% CI 0.74-0.97 but not for individuals ≥ 65 years. The main limitations of this study were the use of influenza-coded outpatient visits rather than laboratory-confirmed influenza as the outcome measure, the reliance on self-report for assessing physical activity and various covariates, and the observational study design.Moderate to high amounts of physical activity may be associated with reduced risk of influenza for individuals <65 years. Future research should use laboratory-confirmed influenza outcomes to confirm the association between physical activity and influenza.

  18. Forecasting influenza-like illness dynamics for military populations using neural networks and social media.

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    Svitlana Volkova

    Full Text Available This work is the first to take advantage of recurrent neural networks to predict influenza-like illness (ILI dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of historical ILI data and the state-of-the-art machine learning models, we build and evaluate the predictive power of neural network architectures based on Long Short Term Memory (LSTMs units capable of nowcasting (predicting in "real-time" and forecasting (predicting the future ILI dynamics in the 2011 - 2014 influenza seasons. To build our models we integrate information people post in social media e.g., topics, embeddings, word ngrams, stylistic patterns, and communication behavior using hashtags and mentions. We then quantitatively evaluate the predictive power of different social media signals and contrast the performance of the-state-of-the-art regression models with neural networks using a diverse set of evaluation metrics. Finally, we combine ILI and social media signals to build a joint neural network model for ILI dynamics prediction. Unlike the majority of the existing work, we specifically focus on developing models for local rather than national ILI surveillance, specifically for military rather than general populations in 26 U.S. and six international locations., and analyze how model performance depends on the amount of social media data available per location. Our approach demonstrates several advantages: (a Neural network architectures that rely on LSTM units trained on social media data yield the best performance compared to previously used regression models. (b Previously under-explored language and communication behavior features are more predictive of ILI dynamics than stylistic and topic signals expressed in social media. (c Neural network models learned exclusively from social media signals yield comparable or better performance to the models learned from ILI historical data, thus

  19. Forecasting influenza-like illness dynamics for military populations using neural networks and social media.

    Science.gov (United States)

    Volkova, Svitlana; Ayton, Ellyn; Porterfield, Katherine; Corley, Courtney D

    2017-01-01

    This work is the first to take advantage of recurrent neural networks to predict influenza-like illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of historical ILI data and the state-of-the-art machine learning models, we build and evaluate the predictive power of neural network architectures based on Long Short Term Memory (LSTMs) units capable of nowcasting (predicting in "real-time") and forecasting (predicting the future) ILI dynamics in the 2011 - 2014 influenza seasons. To build our models we integrate information people post in social media e.g., topics, embeddings, word ngrams, stylistic patterns, and communication behavior using hashtags and mentions. We then quantitatively evaluate the predictive power of different social media signals and contrast the performance of the-state-of-the-art regression models with neural networks using a diverse set of evaluation metrics. Finally, we combine ILI and social media signals to build a joint neural network model for ILI dynamics prediction. Unlike the majority of the existing work, we specifically focus on developing models for local rather than national ILI surveillance, specifically for military rather than general populations in 26 U.S. and six international locations., and analyze how model performance depends on the amount of social media data available per location. Our approach demonstrates several advantages: (a) Neural network architectures that rely on LSTM units trained on social media data yield the best performance compared to previously used regression models. (b) Previously under-explored language and communication behavior features are more predictive of ILI dynamics than stylistic and topic signals expressed in social media. (c) Neural network models learned exclusively from social media signals yield comparable or better performance to the models learned from ILI historical data, thus, signals from

  20. Inverted Encoding Models of Human Population Response Conflate Noise and Neural Tuning Width.

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    Liu, Taosheng; Cable, Dylan; Gardner, Justin L

    2018-01-10

    Channel-encoding models offer the ability to bridge different scales of neuronal measurement by interpreting population responses, typically measured with BOLD imaging in humans, as linear sums of groups of neurons (channels) tuned for visual stimulus properties. Inverting these models to form predicted channel responses from population measurements in humans seemingly offers the potential to infer neuronal tuning properties. Here, we test the ability to make inferences about neural tuning width from inverted encoding models. We examined contrast invariance of orientation selectivity in human V1 (both sexes) and found that inverting the encoding model resulted in channel response functions that became broader with lower contrast, thus apparently violating contrast invariance. Simulations showed that this broadening could be explained by contrast-invariant single-unit tuning with the measured decrease in response amplitude at lower contrast. The decrease in response lowers the signal-to-noise ratio of population responses that results in poorer population representation of orientation. Simulations further showed that increasing signal to noise makes channel response functions less sensitive to underlying neural tuning width, and in the limit of zero noise will reconstruct the channel function assumed by the model regardless of the bandwidth of single units. We conclude that our data are consistent with contrast-invariant orientation tuning in human V1. More generally, our results demonstrate that population selectivity measures obtained by encoding models can deviate substantially from the behavior of single units because they conflate neural tuning width and noise and are therefore better used to estimate the uncertainty of decoded stimulus properties.SIGNIFICANCE STATEMENT It is widely recognized that perceptual experience arises from large populations of neurons, rather than a few single units. Yet, much theory and experiment have examined links between single

  1. A population of caudally migrating cranial neural crest cells: functional and evolutionary implications.

    Science.gov (United States)

    McGonnell, I M; McKay, I J; Graham, A

    2001-08-15

    The deployment of the cranial neural crest is central to the patterning of the skeletomuscular elements of the vertebrate head, with cranial muscles invariably attaching to skeletal elements formed by crest from the same axial level. Here we demonstrate, through gene expression analysis, ablation studies and fate-mapping, the existence of a population of caudally migrating cranial crest that arise from the postotic neural tube. As with the rest of the postotic crest, these cells express the transcription factor Mafb, and this marker can be used to highlight their posterior migration. They pass out between the anterior somite and the otic vesicle, before turning caudally and running along the base of the somites. With long-term fate mapping, we show that these cells migrate to the clavicle and settle at the site of formation of the attachment point for the cleidohyoid muscle. As such, the influence of the cranial neural crest in organising skeletomuscular connectivity seems to extend beyond the head into the trunk. These results are of further importance as they help explain how, even though the pectoral girdle and the skull became physically dissociated during tetrapod evolution, skeletomuscular connectivity has been maintained. Copyright 2001 Academic Press.

  2. Cross-species analyses of the cortical GABAergic and subplate neural populations

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    Barbara Clancy

    2009-10-01

    Full Text Available Cortical GABAergic (γ-aminobutyric acidergic neurons include a recently identified subset whose projections extend over relatively long distances in adult rodents and primates. A number of these inhibitory projection neurons are located in and above the conventionally identified white matter, suggesting their persistence from, or a correspondence with, the developmental subplate. GABAergic and subplate neurons share some unique properties unlike those of the more prevalent pyramidal neurons. To better understand the GABAergic and subplate populations, we constructed a database of neural developmental events common to the three species most frequently used in experimental studies: rat, mouse, and macaque, using data from the online database www.translatingtime.net as well as GABAergic and subplate developmental data from the empirical literature. We used a general linear model to test for similarities and differences, a valid approach because the sequence of most neurodevelopmental events is remarkably conserved across mammalian species. Similarities between the two rodent populations are striking, permitting us to identify developmental dates for GABAergic and subplate neural events in rats that were previously identified only in mice, as well as the timing in mouse development for events previously identified in rats. Primate comparative data are also compelling, although slight variability in statistical error measurement indicates differences in primate GABAergic and subplate events when compared to rodents. Although human extrapolations are challenging because fewer empirical data points are available, and because human data display more variability, we also produce estimates of dates for GABAergic and subplate neural events that have not yet been, or cannot be, determined empirically in humans.

  3. A population genetics-phylogenetics approach to inferring natural selection in coding sequences.

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    Daniel J Wilson

    2011-12-01

    Full Text Available Through an analysis of polymorphism within and divergence between species, we can hope to learn about the distribution of selective effects of mutations in the genome, changes in the fitness landscape that occur over time, and the location of sites involved in key adaptations that distinguish modern-day species. We introduce a novel method for the analysis of variation in selection pressures within and between species, spatially along the genome and temporally between lineages. We model codon evolution explicitly using a joint population genetics-phylogenetics approach that we developed for the construction of multiallelic models with mutation, selection, and drift. Our approach has the advantage of performing direct inference on coding sequences, inferring ancestral states probabilistically, utilizing allele frequency information, and generalizing to multiple species. We use a Bayesian sliding window model for intragenic variation in selection coefficients that efficiently combines information across sites and captures spatial clustering within the genome. To demonstrate the utility of the method, we infer selective pressures acting in Drosophila melanogaster and D. simulans from polymorphism and divergence data for 100 X-linked coding regions.

  4. PARKIN-coding polymorphisms are not associated with Parkinson's disease in a population from northeastern Mexico.

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    Martínez, Héctor R; González-González, Humberto; Cantú-Martínez, Leonel; Rangel-Guerra, Ricardo; Hernández-Castillo, Carlos D; Vergara-Saavedra, Juan J J; Ramos-Gonzalez, Martin R; Cerda-Flores, Ricardo M; Morales-Garza, Marco A; Guerrero-Muñoz, Marcos J; Montes-de-Oca-Luna, Roberto; Saucedo-Cárdenas, Odila

    2010-01-14

    Early- and late-onset Parkinson's disease (EOPD and LOPD) have been associated with mutations in the PARKIN gene. Several studies have reported association of Parkinson's disease (PD) with different polymorphisms in different ethnic populations. To study the role of PARKIN polymorphisms as risk factors for PD in a genetically homogeneous northeastern Mexican population, four previously described coding polymorphisms (Ser167Asn, Val380Leu, Arg366Trp, and Asp394Asn) were analyzed by using the PCR-RFLP technique. This case-control study comprised 117 unrelated patients (mean age 59+/-12 years, range 25-83 years) and 122 healthy unrelated control subjects (mean age 50+/-15 years, range 25-85 years). The homozygous Trp366 and Asn394 genotypes were not present in our study. The Ser167Asn and Val380Leu polymorphisms were not associated with this disease. For the control group, Ser167Asn and Val380Leu were in Hardy-Weinberg disequilibrium. Given that the main causes of Hardy-Weinberg disequilibrium in controls are selection bias or genotyping error, a competing risk of death associated with the mutant gene could be an explanation of this disequilibrium and lack of association. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

  5. A Unifying Framework of Synaptic and Intrinsic Plasticity in Neural Populations.

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    Leugering, Johannes; Pipa, Gordon

    2018-01-17

    A neuronal population is a computational unit that receives a multivariate, time-varying input signal and creates a related multivariate output. These neural signals are modeled as stochastic processes that transmit information in real time, subject to stochastic noise. In a stationary environment, where the input signals can be characterized by constant statistical properties, the systematic relationship between its input and output processes determines the computation carried out by a population. When these statistical characteristics unexpectedly change, the population needs to adapt to its new environment if it is to maintain stable operation. Based on the general concept of homeostatic plasticity, we propose a simple compositional model of adaptive networks that achieve invariance with regard to undesired changes in the statistical properties of their input signals and maintain outputs with well-defined joint statistics. To achieve such invariance, the network model combines two functionally distinct types of plasticity. An abstract stochastic process neuron model implements a generalized form of intrinsic plasticity that adapts marginal statistics, relying only on mechanisms locally confined within each neuron and operating continuously in time, while a simple form of Hebbian synaptic plasticity operates on synaptic connections, thus shaping the interrelation between neurons as captured by a copula function. The combined effect of both mechanisms allows a neuron population to discover invariant representations of its inputs that remain stable under a wide range of transformations (e.g., shifting, scaling and (affine linear) mixing). The probabilistic model of homeostatic adaptation on a population level as presented here allows us to isolate and study the individual and the interaction dynamics of both mechanisms of plasticity and could guide the future search for computationally beneficial types of adaptation.

  6. Electrosensory processing in Apteronotus albifrons: implications for general and specific neural coding strategies across wave-type weakly electric fish species.

    Science.gov (United States)

    Martinez, Diana; Metzen, Michael G; Chacron, Maurice J

    2016-12-01

    Understanding how the brain processes sensory input to generate behavior remains an important problem in neuroscience. Towards this end, it is useful to compare results obtained across multiple species to gain understanding as to the general principles of neural coding. Here we investigated hindbrain pyramidal cell activity in the weakly electric fish Apteronotus albifrons We found strong heterogeneities when looking at baseline activity. Additionally, ON- and OFF-type cells responded to increases and decreases of sinusoidal and noise stimuli, respectively. While both cell types displayed band-pass tuning, OFF-type cells were more broadly tuned than their ON-type counterparts. The observed heterogeneities in baseline activity as well as the greater broadband tuning of OFF-type cells were both similar to those previously reported in other weakly electric fish species, suggesting that they constitute general features of sensory processing. However, we found that peak tuning occurred at frequencies ∼15 Hz in A. albifrons, which is much lower than values reported in the closely related species Apteronotus leptorhynchus and the more distantly related species Eigenmannia virescens In response to stimuli with time-varying amplitude (i.e., envelope), ON- and OFF-type cells displayed similar high-pass tuning curves characteristic of fractional differentiation and possibly indicate optimized coding. These tuning curves were qualitatively similar to those of pyramidal cells in the closely related species A. leptorhynchus In conclusion, comparison between our and previous results reveals general and species-specific neural coding strategies. We hypothesize that differences in coding strategies, when observed, result from different stimulus distributions in the natural/social environment. Copyright © 2016 the American Physiological Society.

  7. Enhancement of Cognitive and Neural Functions through Complex Reasoning Training: Evidence from Normal and Clinical Populations

    Directory of Open Access Journals (Sweden)

    Sandra Bond Chapman

    2014-04-01

    Full Text Available Public awareness of cognitive health is fairly recent compared to physical health. Growing evidence suggests that cognitive training offers promise in augmenting cognitive brain performance in normal and clinical populations. Targeting higher-order cognitive functions, such as reasoning in particular, may promote generalized cognitive changes necessary for supporting the complexities of daily life. This data-driven perspective highlights cognitive and brain changes measured in randomized clinical trials that trained gist reasoning strategies in populations ranging from teenagers to healthy older adults, individuals with brain injury to those at-risk for Alzheimer’s disease. The evidence presented across studies support the potential for Gist reasoning training to strengthen cognitive performance in trained and untrained domains and to engage more efficient communication across widespread neural networks that support higher-order cognition. The meaningful benefits of Gist training provide compelling motivation to examine optimal dose for sustained benefits as well as to explore additive benefits of meditation, physical exercise, and/or improved sleep in future studies.

  8. A computational model incorporating neural stem cell dynamics reproduces glioma incidence across the lifespan in the human population.

    Directory of Open Access Journals (Sweden)

    Roman Bauer

    Full Text Available Glioma is the most common form of primary brain tumor. Demographically, the risk of occurrence increases until old age. Here we present a novel computational model to reproduce the probability of glioma incidence across the lifespan. Previous mathematical models explaining glioma incidence are framed in a rather abstract way, and do not directly relate to empirical findings. To decrease this gap between theory and experimental observations, we incorporate recent data on cellular and molecular factors underlying gliomagenesis. Since evidence implicates the adult neural stem cell as the likely cell-of-origin of glioma, we have incorporated empirically-determined estimates of neural stem cell number, cell division rate, mutation rate and oncogenic potential into our model. We demonstrate that our model yields results which match actual demographic data in the human population. In particular, this model accounts for the observed peak incidence of glioma at approximately 80 years of age, without the need to assert differential susceptibility throughout the population. Overall, our model supports the hypothesis that glioma is caused by randomly-occurring oncogenic mutations within the neural stem cell population. Based on this model, we assess the influence of the (experimentally indicated decrease in the number of neural stem cells and increase of cell division rate during aging. Our model provides multiple testable predictions, and suggests that different temporal sequences of oncogenic mutations can lead to tumorigenesis. Finally, we conclude that four or five oncogenic mutations are sufficient for the formation of glioma.

  9. Premotor neural correlates of predictive motor timing for speech production and hand movement: evidence for a temporal predictive code in the motor system.

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    Johari, Karim; Behroozmand, Roozbeh

    2017-05-01

    The predictive coding model suggests that neural processing of sensory information is facilitated for temporally-predictable stimuli. This study investigated how temporal processing of visually-presented sensory cues modulates movement reaction time and neural activities in speech and hand motor systems. Event-related potentials (ERPs) were recorded in 13 subjects while they were visually-cued to prepare to produce a steady vocalization of a vowel sound or press a button in a randomized order, and to initiate the cued movement following the onset of a go signal on the screen. Experiment was conducted in two counterbalanced blocks in which the time interval between visual cue and go signal was temporally-predictable (fixed delay at 1000 ms) or unpredictable (variable between 1000 and 2000 ms). Results of the behavioral response analysis indicated that movement reaction time was significantly decreased for temporally-predictable stimuli in both speech and hand modalities. We identified premotor ERP activities with a left-lateralized parietal distribution for hand and a frontocentral distribution for speech that were significantly suppressed in response to temporally-predictable compared with unpredictable stimuli. The premotor ERPs were elicited approximately -100 ms before movement and were significantly correlated with speech and hand motor reaction times only in response to temporally-predictable stimuli. These findings suggest that the motor system establishes a predictive code to facilitate movement in response to temporally-predictable sensory stimuli. Our data suggest that the premotor ERP activities are robust neurophysiological biomarkers of such predictive coding mechanisms. These findings provide novel insights into the temporal processing mechanisms of speech and hand motor systems.

  10. Analysis of non-synonymous-coding variants of Parkinson's disease-related pathogenic and susceptibility genes in East Asian populations.

    Science.gov (United States)

    Foo, Jia Nee; Tan, Louis C; Liany, Herty; Koh, Tat Hung; Irwan, Ishak D; Ng, Yen Yek; Ahmad-Annuar, Azlina; Au, Wing-Lok; Aung, Tin; Chan, Anne Y Y; Chong, Siow-Ann; Chung, Sun Ju; Jung, Yusun; Khor, Chiea Chuen; Kim, Juyeon; Lee, Jimmy; Lim, Shen-Yang; Mok, Vincent; Prakash, Kumar-M; Song, Kyuyoung; Tai, E-Shyong; Vithana, Eranga N; Wong, Tien-Yin; Tan, Eng-King; Liu, Jianjun

    2014-07-15

    To evaluate the contribution of non-synonymous-coding variants of known familial and genome-wide association studies (GWAS)-linked genes for Parkinson's disease (PD) to PD risk in the East Asian population, we sequenced all the coding exons of 39 PD-related disease genes and evaluated the accumulation of rare non-synonymous-coding variants in 375 early-onset PD cases and 399 controls. We also genotyped 782 non-synonymous-coding variants of these genes in 710 late-onset PD cases and 9046 population controls. Significant enrichment of LRRK2 variants was observed in both early- and late-onset PD (odds ratio = 1.58; 95% confidence interval = 1.29-1.93; P = 8.05 × 10(-6)). Moderate enrichment was also observed in FGF20, MCCC1, GBA and ITGA8. Half of the rare variants anticipated to cause loss of function of these genes were present in healthy controls. Overall, non-synonymous-coding variants of known familial and GWAS-linked genes appear to make a limited contribution to PD risk, suggesting that clinical sequencing of these genes will provide limited information for risk prediction and molecular diagnosis. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  11. A stochastic model of chromatin modification: cell population coding of winter memory in plants.

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    Satake, Akiko; Iwasa, Yoh

    2012-06-07

    Biological memory, a sustained cellular response to a transient stimulus, has been found in many natural systems. The best example in plants is the winter memory by which plants can flower in favorable conditions in spring. For this winter memory, epigenetic regulation of FLOWERING LOCUS C (FLC), which acts as a floral repressor, plays a key role. Exposure to prolonged periods of cold results in the gradual suppression of FLC, which allows plants to measure the length of cold and to flower only after a sufficiently long winter. Although many genes involved in histone modifications have been isolated, molecular mechanisms of winter memory are not well understood. Here, we develop a model for chromatin modification, in which the dynamics of a single nucleosome are aggregated to on/off behavior of FLC expression at the cellular level and further integrated to a change of FLC expression at the whole-plant level. We propose cell-population coding of winter memory: each cell is described as a bistable system that shows heterogeneous timing of the transition from on to off in FLC expression under cold and measures the length of cold as the proportion of cells in the off state. This mechanism well explains robust FLC regulation and stable inheritance of winter memory after cell division in response to noisy signals. Winter memory lasts longer if deposition of the repressive histone mark occurs faster. A difference in deposition speed would discriminate between stable maintenance of FLC repression in annuals and transient expression in perennials. Copyright © 2012 Elsevier Ltd. All rights reserved.

  12. Population coding of forelimb joint kinematics by peripheral afferents in monkeys.

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    Tatsuya Umeda

    Full Text Available Various peripheral receptors provide information concerning position and movement to the central nervous system to achieve complex and dexterous movements of forelimbs in primates. The response properties of single afferent receptors to movements at a single joint have been examined in detail, but the population coding of peripheral afferents remains poorly defined. In this study, we obtained multichannel recordings from dorsal root ganglion (DRG neurons in cervical segments of monkeys. We applied the sparse linear regression (SLiR algorithm to the recordings, which selects useful input signals to reconstruct movement kinematics. Multichannel recordings of peripheral afferents were performed by inserting multi-electrode arrays into the DRGs of lower cervical segments in two anesthetized monkeys. A total of 112 and 92 units were responsive to the passive joint movements or the skin stimulation with a painting brush in Monkey 1 and Monkey 2, respectively. Using the SLiR algorithm, we reconstructed the temporal changes of joint angle, angular velocity, and acceleration at the elbow, wrist, and finger joints from temporal firing patterns of the DRG neurons. By automatically selecting a subset of recorded units, the SLiR achieved superior generalization performance compared with a regularized linear regression algorithm. The SLiR selected not only putative muscle units that were responsive to only the passive movements, but also a number of putative cutaneous units responsive to the skin stimulation. These results suggested that an ensemble of peripheral primary afferents that contains both putative muscle and cutaneous units encode forelimb joint kinematics of non-human primates.

  13. Scaling Properties of Dimensionality Reduction for Neural Populations and Network Models.

    Directory of Open Access Journals (Sweden)

    Ryan C Williamson

    2016-12-01

    Full Text Available Recent studies have applied dimensionality reduction methods to understand how the multi-dimensional structure of neural population activity gives rise to brain function. It is unclear, however, how the results obtained from dimensionality reduction generalize to recordings with larger numbers of neurons and trials or how these results relate to the underlying network structure. We address these questions by applying factor analysis to recordings in the visual cortex of non-human primates and to spiking network models that self-generate irregular activity through a balance of excitation and inhibition. We compared the scaling trends of two key outputs of dimensionality reduction-shared dimensionality and percent shared variance-with neuron and trial count. We found that the scaling properties of networks with non-clustered and clustered connectivity differed, and that the in vivo recordings were more consistent with the clustered network. Furthermore, recordings from tens of neurons were sufficient to identify the dominant modes of shared variability that generalize to larger portions of the network. These findings can help guide the interpretation of dimensionality reduction outputs in regimes of limited neuron and trial sampling and help relate these outputs to the underlying network structure.

  14. Putting the tritone paradox into context: insights from neural population decoding and human psychophysics.

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    Englitz, Bernhard; Akram, S; David, S V; Chambers, C; Pressnitzer, Daniel; Depireux, D; Fritz, J B; Shamma, Shihab A

    2013-01-01

    The context in which a stimulus occurs can influence its perception. We study contextual effects in audition using the tritone paradox, where a pair of complex (Shepard) tones separated by half an octave can be perceived as ascending or descending. While ambiguous in isolation, they are heard with a clear upward or downward change in pitch, when preceded by spectrally matched biasing sequences. We presented these biased Shepard pairs to awake ferrets and obtained neuronal responses from primary auditory cortex. Using dimensionality reduction from the neural population response, we decode the perceived pitch for each tone. The bias sequence is found to reliably shift the perceived pitch of the tones away from its central frequency. Using human psychophysics, we provide evidence that this shift in pitch is present in active human perception as well. These results are incompatible with the standard absolute distance decoder for Shepard tones, which would have predicted the bias to attract the tones. We propose a relative decoder that takes the stimulus history into account and is consistent with the present and other data sets.

  15. In silico lineage tracing through single cell transcriptomics identifies a neural stem cell population in planarians.

    Science.gov (United States)

    Molinaro, Alyssa M; Pearson, Bret J

    2016-04-27

    The planarian Schmidtea mediterranea is a master regenerator with a large adult stem cell compartment. The lack of transgenic labeling techniques in this animal has hindered the study of lineage progression and has made understanding the mechanisms of tissue regeneration a challenge. However, recent advances in single-cell transcriptomics and analysis methods allow for the discovery of novel cell lineages as differentiation progresses from stem cell to terminally differentiated cell. Here we apply pseudotime analysis and single-cell transcriptomics to identify adult stem cells belonging to specific cellular lineages and identify novel candidate genes for future in vivo lineage studies. We purify 168 single stem and progeny cells from the planarian head, which were subjected to single-cell RNA sequencing (scRNAseq). Pseudotime analysis with Waterfall and gene set enrichment analysis predicts a molecularly distinct neoblast sub-population with neural character (νNeoblasts) as well as a novel alternative lineage. Using the predicted νNeoblast markers, we demonstrate that a novel proliferative stem cell population exists adjacent to the brain. scRNAseq coupled with in silico lineage analysis offers a new approach for studying lineage progression in planarians. The lineages identified here are extracted from a highly heterogeneous dataset with minimal prior knowledge of planarian lineages, demonstrating that lineage purification by transgenic labeling is not a prerequisite for this approach. The identification of the νNeoblast lineage demonstrates the usefulness of the planarian system for computationally predicting cellular lineages in an adult context coupled with in vivo verification.

  16. Periodic population codes: From a single circular variable to higher dimensions, multiple nested scales, and conceptual spaces.

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    Herz, Andreas Vm; Mathis, Alexander; Stemmler, Martin

    2017-10-01

    Across the nervous system, neurons often encode circular stimuli using tuning curves that are not sine or cosine functions, but that belong to the richer class of von Mises functions, which are periodic variants of Gaussians. For a population of neurons encoding a single circular variable with such canonical tuning curves, computing a simple population vector is the optimal read-out of the most likely stimulus. We argue that the advantages of population vector read-outs are so compelling that even the neural representation of the outside world's flat Euclidean geometry is curled up into a torus (a circle times a circle), creating the hexagonal activity patterns of mammalian grid cells. Here, the circular scale is not set a priori, so the nervous system can use multiple scales and gain fields to overcome the ambiguity inherent in periodic representations of linear variables. We review the experimental evidence for this framework and discuss its testable predictions and generalizations to more abstract grid-like neural representations. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Approaches to the study of neural coding of sound source location and sound envelope in real environments

    Science.gov (United States)

    Kuwada, Shigeyuki; Bishop, Brian; Kim, Duck O.

    2012-01-01

    The major functions of the auditory system are recognition (what is the sound) and localization (where is the sound). Although each of these has received considerable attention, rarely are they studied in combination. Furthermore, the stimuli used in the bulk of studies did not represent sound location in real environments and ignored the effects of reverberation. Another ignored dimension is the distance of a sound source. Finally, there is a scarcity of studies conducted in unanesthetized animals. We illustrate a set of efficient methods that overcome these shortcomings. We use the virtual auditory space method (VAS) to efficiently present sounds at different azimuths, different distances and in different environments. Additionally, this method allows for efficient switching between binaural and monaural stimulation and alteration of acoustic cues singly or in combination to elucidate neural mechanisms underlying localization and recognition. Such procedures cannot be performed with real sound field stimulation. Our research is designed to address the following questions: Are IC neurons specialized to process what and where auditory information? How does reverberation and distance of the sound source affect this processing? How do IC neurons represent sound source distance? Are neural mechanisms underlying envelope processing binaural or monaural? PMID:22754505

  18. Approaches to the study of neural coding of sound source location and sound envelope in real environments.

    Directory of Open Access Journals (Sweden)

    Shigeyuki eKuwada

    2012-06-01

    Full Text Available The major functions of the auditory system are recognition (what is the sound and localization (where is the sound. Although each of these has received considerable attention, rarely are they studied in combination. Furthermore, the stimuli used in the bulk of studies did not represent sound location in real environments and ignored the effects of reverberation. Another ignored dimension is the distance of a sound source. Finally, there is a scarcity of studies conducted in unanesthetized animals. We illustrate a set of efficient methods that overcome these shortcomings. We use the virtual auditory space method (VAS to efficiently present sounds at different azimuths, different distances and in different environments. Additionally, this method allows for efficient switching between binaural and monaural stimulation and alteration of acoustic cues singly or in combination to elucidate neural mechanisms underlying localization and recognition. Such procedures cannot be performed with real sound field stimulation. Our research is designed to address the following questions: Are IC neurons specialized to process what and where auditory information? How does reverberation and distance of the sound source affect this processing? How do IC neurons represent sound source distance? Are neural mechanisms underlying envelope processing binaural or monaural ?

  19. Feedforward Neural Network for Force Coding of an MRI-Compatible Tactile Sensor Array Based on Fiber Bragg Grating

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    Paola Saccomandi

    2015-01-01

    Full Text Available This work shows the development and characterization of a fiber optic tactile sensor based on Fiber Bragg Grating (FBG technology. The sensor is a 3 × 3 array of FBGs encapsulated in a PDMS compliant polymer. The strain experienced by each FBG is transduced into a Bragg wavelength shift and the inverse characteristics of the sensor were computed by means of a feedforward neural network. A 21 mN RMSE error was achieved in estimating the force over the 8 N experimented load range while including all probing sites in the neural network training procedure, whereas the median force RMSE was 199 mN across the 200 instances of a Monte Carlo randomized selection of experimental sessions to evaluate the calibration under generalized probing conditions. The static metrological properties and the possibility to fabricate sensors with relatively high spatial resolution make the proposed design attractive for the sensorization of robotic hands. Furthermore, the proved MRI-compatibility of the sensor opens other application scenarios, such as the possibility to employ the array for force measurement during functional MRI-measured brain activation.

  20. Artificial neural network for predicting pathological stage of clinically localized prostate cancer in a Taiwanese population.

    Science.gov (United States)

    Tsao, Chih-Wei; Liu, Ching-Yu; Cha, Tai-Lung; Wu, Sheng-Tang; Sun, Guang-Huan; Yu, Dah-Shyong; Chen, Hong-I; Chang, Sun-Yran; Chen, Shih-Chang; Hsu, Chien-Yeh

    2014-10-01

    We developed an artificial neural network (ANN) model to predict prostate cancer pathological staging in patients prior to when they received radical prostatectomy as this is more effective than logistic regression (LR), or combined use of age, prostate-specific antigen (PSA), body mass index (BMI), digital rectal examination (DRE), trans-rectal ultrasound (TRUS), biopsy Gleason sum, and primary biopsy Gleason grade. Our study evaluated 299 patients undergoing retro-pubic radical prostatectomy or robotic-assisted laparoscopic radical prostatectomy surgical procedures with pelvic lymph node dissection. The results were intended to predict the pathological stage of prostate cancer (T2 or T3) after radical surgery. The predictive ability of ANN was compared with LR and validation of the 2007 Partin Tables was estimated by the areas under the receiving operating characteristic curve (AUCs). Of the 299 patients we evaluated, 109 (36.45%) displayed prostate cancer with extra-capsular extension (ECE), and 190 (63.55%) displayed organ-confined disease (OCD). LR analysis showed that only PSA and BMI were statistically significant predictors of prostate cancer with capsule invasion. Overall, ANN outperformed LR significantly (0.795 ± 0.023 versus 0.746 ± 0.025, p = 0.016). Validation using the current Partin Tables for the participants of our study was assessed, and the predictive capacity of AUC for OCD was 0.695. ANN was superior to LR at predicting OCD in prostate cancer. Compared with the validation of current Partin Tables for the Taiwanese population, the ANN model resulted in larger AUCs and more accurate prediction of the pathologic stage of prostate cancer. Copyright © 2014. Published by Elsevier B.V.

  1. A novel lead design enables selective deep brain stimulation of neural populations in the subthalamic region

    Science.gov (United States)

    van Dijk, Kees J.; Verhagen, Rens; Chaturvedi, Ashutosh; McIntyre, Cameron C.; Bour, Lo J.; Heida, Ciska; Veltink, Peter H.

    2015-08-01

    Objective. The clinical effects of deep brain stimulation (DBS) of the subthalamic nucleus (STN-DBS) as a treatment for Parkinson’s disease are sensitive to the location of the DBS lead within the STN. New high density (HD) lead designs have been created which are hypothesized to provide additional degrees of freedom in shaping the stimulating electric field. The objective of this study is to compare the performances of a new HD lead with a conventional cylindrical contact (CC) lead. Approach. A computational model, consisting of a finite element electric field model combined with multi-compartment neuron and axon models representing different neural populations in the subthalamic region, was used to evaluate the two leads. We compared ring-mode and steering-mode stimulation with the HD lead to single contact stimulation with the CC lead. These stimulation modes were tested for the lead: (1) positioned in the centroid of the STN, (2) shifted 1 mm towards the internal capsule (IC), and (3) shifted 2 mm towards the IC. Under these conditions, we quantified the number of STN neurons that were activated without activating IC fibers, which are known to cause side-effects. Main results. The modeling results show that the HD lead is able to mimic the stimulation effect of the CC lead. Additionally, in steering-mode stimulation there was a significant increase of activated STN neurons compared to the CC mode. Significance. From the model simulations we conclude that the HD lead in steering-mode with optimized stimulation parameter selection can stimulate more STN cells. Next, the clinical impact of the increased number of activated STN cells should be tested and balanced across the increased complexity of identifying the optimized stimulation parameter settings for the HD lead.

  2. The emergence of "us and them" in 80 lines of code: modeling group genesis in homogeneous populations.

    Science.gov (United States)

    Gray, Kurt; Rand, David G; Ert, Eyal; Lewis, Kevin; Hershman, Steve; Norton, Michael I

    2014-04-01

    Psychological explanations of group genesis often require population heterogeneity in identity or other characteristics, whether deep (e.g., religion) or superficial (e.g., eye color). We used agent-based models to explore group genesis in homogeneous populations and found robust group formation with just two basic principles: reciprocity and transitivity. These emergent groups demonstrated in-group cooperation and out-group defection, even though agents lacked common identity. Group formation increased individual payoffs, and group number and size were robust to varying levels of reciprocity and transitivity. Increasing population size increased group size more than group number, and manipulating baseline trust in a population had predictable effects on group genesis. An interactive demonstration of the parameter space and source code for implementing the model are available online.

  3. Coding of Barrett's oesophagus with high-grade dysplasia in national administrative databases: a population-based cohort study.

    Science.gov (United States)

    Chadwick, Georgina; Varagunam, Mira; Brand, Christian; Riley, Stuart A; Maynard, Nick; Crosby, Tom; Michalowski, Julie; Cromwell, David A

    2017-06-09

    The International Classification of Diseases 10th Revision (ICD-10) system used in the English hospital administrative database (Hospital Episode Statistics (HES)) does not contain a specific code for oesophageal high-grade dysplasia (HGD). The aim of this paper was to examine how patients with HGD were coded in HES and whether it was done consistently. National population-based cohort study of patients with newly diagnosed with HGD in England. The study used data collected prospectively as part of the National Oesophago-Gastric Cancer Audit (NOGCA). These records were linked to HES to investigate the pattern of ICD-10 codes recorded for these patients at the time of diagnosis. All patients with a new diagnosis of HGD between 1 April 2013 and 31 March 2014 in England, who had data submitted to the NOGCA. The main outcome assessed was the pattern of primary and secondary ICD-10 diagnostic codes recorded in the HES records at endoscopy at the time of diagnosis of HGD. Among 452 patients with a new diagnosis of HGD between 1 April 2013 and 31 March 2014, Barrett's oesophagus was the only condition coded in 200 (44.2%) HES records. Records for 59 patients (13.1%) contained no oesophageal conditions. The remaining 193 patients had various diagnostic codes recorded, 93 included a diagnosis of Barrett's oesophagus and 57 included a diagnosis of oesophageal/gastric cardia cancer. HES is not suitable to support national studies looking at the management of HGD. This is one reason for the UK to adopt an extended ICD system (akin to ICD-10-CM). © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  4. Robust information propagation through noisy neural circuits.

    Science.gov (United States)

    Zylberberg, Joel; Pouget, Alexandre; Latham, Peter E; Shea-Brown, Eric

    2017-04-01

    Sensory neurons give highly variable responses to stimulation, which can limit the amount of stimulus information available to downstream circuits. Much work has investigated the factors that affect the amount of information encoded in these population responses, leading to insights about the role of covariability among neurons, tuning curve shape, etc. However, the informativeness of neural responses is not the only relevant feature of population codes; of potentially equal importance is how robustly that information propagates to downstream structures. For instance, to quantify the retina's performance, one must consider not only the informativeness of the optic nerve responses, but also the amount of information that survives the spike-generating nonlinearity and noise corruption in the next stage of processing, the lateral geniculate nucleus. Our study identifies the set of covariance structures for the upstream cells that optimize the ability of information to propagate through noisy, nonlinear circuits. Within this optimal family are covariances with "differential correlations", which are known to reduce the information encoded in neural population activities. Thus, covariance structures that maximize information in neural population codes, and those that maximize the ability of this information to propagate, can be very different. Moreover, redundancy is neither necessary nor sufficient to make population codes robust against corruption by noise: redundant codes can be very fragile, and synergistic codes can-in some cases-optimize robustness against noise.

  5. Robust information propagation through noisy neural circuits.

    Directory of Open Access Journals (Sweden)

    Joel Zylberberg

    2017-04-01

    Full Text Available Sensory neurons give highly variable responses to stimulation, which can limit the amount of stimulus information available to downstream circuits. Much work has investigated the factors that affect the amount of information encoded in these population responses, leading to insights about the role of covariability among neurons, tuning curve shape, etc. However, the informativeness of neural responses is not the only relevant feature of population codes; of potentially equal importance is how robustly that information propagates to downstream structures. For instance, to quantify the retina's performance, one must consider not only the informativeness of the optic nerve responses, but also the amount of information that survives the spike-generating nonlinearity and noise corruption in the next stage of processing, the lateral geniculate nucleus. Our study identifies the set of covariance structures for the upstream cells that optimize the ability of information to propagate through noisy, nonlinear circuits. Within this optimal family are covariances with "differential correlations", which are known to reduce the information encoded in neural population activities. Thus, covariance structures that maximize information in neural population codes, and those that maximize the ability of this information to propagate, can be very different. Moreover, redundancy is neither necessary nor sufficient to make population codes robust against corruption by noise: redundant codes can be very fragile, and synergistic codes can-in some cases-optimize robustness against noise.

  6. Polygenic risk for five psychiatric disorders and cross-disorder and disorder-specific neural connectivity in two independent populations

    Directory of Open Access Journals (Sweden)

    Tianqi Wang

    2017-01-01

    Full Text Available Major psychiatric disorders, including attention deficit hyperactivity disorder (ADHD, autism (AUT, bipolar disorder (BD, major depressive disorder (MDD, and schizophrenia (SZ, are highly heritable and polygenic. Evidence suggests that these five disorders have both shared and distinct genetic risks and neural connectivity abnormalities. To measure aggregate genetic risks, the polygenic risk score (PGRS was computed. Two independent general populations (N = 360 and N = 323 were separately examined to investigate whether the cross-disorder PGRS and PGRS for a specific disorder were associated with individual variability in functional connectivity. Consistent altered functional connectivity was found with the bilateral insula: for the left supplementary motor area and the left superior temporal gyrus with the cross-disorder PGRS, for the left insula and right middle and superior temporal lobe associated with the PGRS for autism, for the bilateral midbrain, posterior cingulate, cuneus, and precuneus associated with the PGRS for BD, and for the left angular gyrus and the left dorsolateral prefrontal cortex associated with the PGRS for schizophrenia. No significant functional connectivity was found associated with the PGRS for ADHD and MDD. Our findings indicated that genetic effects on the cross-disorder and disorder-specific neural connectivity of common genetic risk loci are detectable in the general population. Our findings also indicated that polygenic risk contributes to the main neurobiological phenotypes of psychiatric disorders and that identifying cross-disorder and specific functional connectivity related to polygenic risks may elucidate the neural pathways for these disorders.

  7. Metastable differentially methylated regions within Arabidopsis inbred populations are associated with modified expression of non-coding transcripts.

    Directory of Open Access Journals (Sweden)

    Ericka R Havecker

    Full Text Available Individual plants within a population may vary at both genetic and epigenetic levels. The rate of genetic divergence and its underlying mechanisms is well understood. Less is known about the factors contributing to epigenetic divergence among isogenic populations except that, despite the presence of mechanisms that faithfully maintain epigenetic marks, epigenetic differences are more frequent than genetic variation. Epigenetically divergent stretches of isogenic DNA sequence are called epialleles. Currently, it is not clear why certain regions exhibit variable epigenetic status. We identified and characterised two long RNA transcripts with altered expression and DNA methylation in an ago5 mutant. However, further investigation revealed that these changes were not dependent upon AGO5. Rather, the variable transcription of these loci in Arabidopsis mutant and wild-type populations corresponds to spontaneous differential methylated regions (DMRs or epialleles. These two DMRs are delineated by RNAs which are highly expressed when the DMR is hypomethylated. Furthermore, they control the expression of 5' transcriptional start site mRNA variants of nearby protein coding genes. Our data support the recent observations that meiotically stable DMRs exist within inbred populations. We further demonstrate that DMR boundaries can be defined by putative non-coding promoter-associated transcripts.

  8. Three-dimensional grammar in the brain: Dissociating the neural correlates of natural sign language and manually coded spoken language.

    Science.gov (United States)

    Jednoróg, Katarzyna; Bola, Łukasz; Mostowski, Piotr; Szwed, Marcin; Boguszewski, Paweł M; Marchewka, Artur; Rutkowski, Paweł

    2015-05-01

    In several countries natural sign languages were considered inadequate for education. Instead, new sign-supported systems were created, based on the belief that spoken/written language is grammatically superior. One such system called SJM (system językowo-migowy) preserves the grammatical and lexical structure of spoken Polish and since 1960s has been extensively employed in schools and on TV. Nevertheless, the Deaf community avoids using SJM for everyday communication, its preferred language being PJM (polski język migowy), a natural sign language, structurally and grammatically independent of spoken Polish and featuring classifier constructions (CCs). Here, for the first time, we compare, with fMRI method, the neural bases of natural vs. devised communication systems. Deaf signers were presented with three types of signed sentences (SJM and PJM with/without CCs). Consistent with previous findings, PJM with CCs compared to either SJM or PJM without CCs recruited the parietal lobes. The reverse comparison revealed activation in the anterior temporal lobes, suggesting increased semantic combinatory processes in lexical sign comprehension. Finally, PJM compared with SJM engaged left posterior superior temporal gyrus and anterior temporal lobe, areas crucial for sentence-level speech comprehension. We suggest that activity in these two areas reflects greater processing efficiency for naturally evolved sign language. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Imaging a population code for odor identity in the Drosophila mushroom body

    National Research Council Canada - National Science Library

    Campbell, Robert A A; Honegger, Kyle S; Qin, Hongtao; Li, Wanhe; Demir, Ebru; Turner, Glenn C

    2013-01-01

    ... from >100 neurons simultaneously in the Drosophila mushroom body (MB). For the first time, we demonstrate quantitatively that MB population responses contain substantial information on odor identity...

  10. PopCORN : Hunting down the differences between binary population synthesis codes

    NARCIS (Netherlands)

    Toonen, S.G.M.; Claeys, J.S.W.: Mennekens N.: Ruiter A.J.

    2014-01-01

    Context. Binary population synthesis (BPS) modelling is a very effective tool to study the evolution and properties of various types of close binary systems. The uncertainty in the parameters of the model and their effect on a population can be tested in a statistical way, which then leads to a

  11. Neural synchrony in ventral cochlear nucleus neuron populations is not mediated by intrinsic processes but is stimulus induced: implications for auditory brainstem implants.

    Science.gov (United States)

    Shivdasani, Mohit N; Mauger, Stefan J; Rathbone, Graeme D; Paolini, Antonio G

    2009-12-01

    The aim of this investigation was to elucidate if neural synchrony forms part of the spike time-based theory for coding of sound information in the ventral cochlear nucleus (VCN) of the auditory brainstem. Previous research attempts to quantify the degree of neural synchrony at higher levels of the central auditory system have indicated that synchronized firing of neurons during presentation of an acoustic stimulus could play an important role in coding complex sound features. However, it is unknown whether this synchrony could in fact arise from the VCN as it is the first station in the central auditory pathway. Cross-correlation analysis was conducted on 499 pairs of multiunit clusters recorded in the urethane-anesthetized rat VCN in response to pure tones and combinations of two tones to determine the presence of neural synchrony. The shift predictor correlogram was used as a measure for determining the synchrony owing to the effects of the stimulus. Without subtraction of the shift predictor, over 65% of the pairs of multiunit clusters exhibited significant correlation in neural firing when the frequencies of the tones presented matched their characteristic frequencies (CFs). In addition, this stimulus-evoked neural synchrony was dependent on the physical distance between electrode sites, and the CF difference between multiunit clusters as the number of correlated pairs dropped significantly for electrode sites greater than 800 microm apart and for multiunit cluster pairs with a CF difference greater than 0.5 octaves. However, subtraction of the shift predictor correlograms from the raw correlograms resulted in no remaining correlation between all VCN pairs. These results suggest that while neural synchrony may be a feature of sound coding in the VCN, it is stimulus induced and not due to intrinsic neural interactions within the nucleus. These data provide important implications for stimulation strategies for the auditory brainstem implant, which is used to

  12. Heterogeneity in genetic diversity among non-coding loci fails to fit neutral coalescent models of population history.

    Directory of Open Access Journals (Sweden)

    Jeffrey L Peters

    Full Text Available Inferring aspects of the population histories of species using coalescent analyses of non-coding nuclear DNA has grown in popularity. These inferences, such as divergence, gene flow, and changes in population size, assume that genetic data reflect simple population histories and neutral evolutionary processes. However, violating model assumptions can result in a poor fit between empirical data and the models. We sampled 22 nuclear intron sequences from at least 19 different chromosomes (a genomic transect to test for deviations from selective neutrality in the gadwall (Anas strepera, a Holarctic duck. Nucleotide diversity among these loci varied by nearly two orders of magnitude (from 0.0004 to 0.029, and this heterogeneity could not be explained by differences in substitution rates alone. Using two different coalescent methods to infer models of population history and then simulating neutral genetic diversity under these models, we found that the observed among-locus heterogeneity in nucleotide diversity was significantly higher than expected for these simple models. Defining more complex models of population history demonstrated that a pre-divergence bottleneck was also unlikely to explain this heterogeneity. However, both selection and interspecific hybridization could account for the heterogeneity observed among loci. Regardless of the cause of the deviation, our results illustrate that violating key assumptions of coalescent models can mislead inferences of population history.

  13. Long term trends in prevalence of neural tube defects in Europe : population based study

    NARCIS (Netherlands)

    Khoshnood, Babak; Loane, Maria; de Walle, Hermien; Arriola, Larraitz; Addor, Marie-Claude; Barisic, Ingeborg; Beres, Judit; Bianchi, Fabrizio; Dias, Carlos; Draper, Elizabeth; Garne, Ester; Gatt, Miriam; Haeusler, Martin; Klungsoyr, Kari; Latos-Bielenska, Anna; Lynch, Catherine; McDonnell, Bob; Nelen, Vera; Neville, Amanda J.; O'Mahony, Mary T.; Queisser-Luft, Annette; Rankin, Judith; Rissmann, Anke; Ritvanen, Annukka; Rounding, Catherine; Sipek, Antonin; Tucker, David; Verellen-Dumoulin, Christine; Wellesley, Diana; Dolk, Helen

    2015-01-01

    STUDY QUESTION What are the long term trends in the total (live births, fetal deaths, and terminations of pregnancy for fetal anomaly) and live birth prevalence of neural tube defects (NTD) in Europe, where many countries have issued recommendations for folic acid supplementation but a policy for

  14. Novel Mutation of LRP6 Identified in Chinese Han Population Links Canonical WNT Signaling to Neural Tube Defects.

    Science.gov (United States)

    Shi, Zhiwen; Yang, Xueyan; Li, Bin-Bin; Chen, Shuxia; Yang, Luming; Cheng, Liangping; Zhang, Ting; Wang, Hongyan; Zheng, Yufang

    2017-09-29

    Neural tube defects (NTDs), the second most frequent cause of human congenital abnormalities, are debilitating birth defects due to failure of neural tube closure. It has been shown that noncanonical WNT/planar cell polarity (PCP) signaling is required for convergent extension (CE), the initiation step of neural tube closure (NTC). But the effect of canonical WNT//β-catenin signaling during NTC is still elusive. LRP6 (low density lipoprotein receptor related proteins 6) was identified as a co-receptor for WNT/β-catenin signaling, but recent studies showed that it also can mediate WNT/PCP signaling. In this study, we screened mutations in the LRP6 gene in 343 NTDs and 215 ethnically matched normal controls of Chinese Han population. Three rare missense mutations (c.1514A>G, p.Y505C); c.2984A>G, p.D995G; and c.4280C>A, p.P1427Q) of the LRP6 gene were identified in Chinese NTD patients. The Y505C mutation is a loss-of-function mutation on both WNT/β-catenin and PCP signaling. The D995G mutation only partially lost inhibition on PCP signaling without affecting WNT/β-catenin signaling. The P1427Q mutation dramatically increased WNT/β-catenin signaling but only mildly loss of inhibition on PCP signaling. All three mutations failed to rescue CE defects caused by lrp6 morpholino oligos knockdown in zebrafish. Of interest, when overexpressed, D995G did not induce any defects, but Y505C and P1427Q caused more severe CE defects in zebrafish. Our results suggested that over-active canonical WNT signaling induced by gain-of-function mutation in LRP6 could also contribute to human NTDs, and a balanced WNT/β-catenin and PCP signaling is probably required for proper neural tube development. Birth Defects Research, 2017.© 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  15. Neural population dynamics in human motor cortex during movements in people with ALS.

    Science.gov (United States)

    Pandarinath, Chethan; Gilja, Vikash; Blabe, Christine H; Nuyujukian, Paul; Sarma, Anish A; Sorice, Brittany L; Eskandar, Emad N; Hochberg, Leigh R; Henderson, Jaimie M; Shenoy, Krishna V

    2015-06-23

    The prevailing view of motor cortex holds that motor cortical neural activity represents muscle or movement parameters. However, recent studies in non-human primates have shown that neural activity does not simply represent muscle or movement parameters; instead, its temporal structure is well-described by a dynamical system where activity during movement evolves lawfully from an initial pre-movement state. In this study, we analyze neuronal ensemble activity in motor cortex in two clinical trial participants diagnosed with Amyotrophic Lateral Sclerosis (ALS). We find that activity in human motor cortex has similar dynamical structure to that of non-human primates, indicating that human motor cortex contains a similar underlying dynamical system for movement generation.

  16. Neural substrates of child irritability in typically developing and psychiatric populations

    Directory of Open Access Journals (Sweden)

    Susan B. Perlman

    2015-08-01

    Full Text Available Irritability is an aspect of the negative affectivity domain of temperament, but in severe and dysregulated forms is a symptom of a range of psychopathologies. Better understanding of the neural underpinnings of irritability, outside the context of specific disorders, can help to understand normative variation but also characterize its clinical salience in psychopathology diagnosis. This study assessed brain activation during reward and frustration, domains of behavioral deficits in childhood irritability. Children (age 6–9 presenting in mental health clinics for extreme and impairing irritability (n = 26 were compared to healthy children (n = 28. Using developmentally sensitive methods, neural activation was measured via a negative mood induction paradigm during fMRI scanning. The clinical group displayed more activation of the anterior cingulate and middle frontal gyrus during reward, but less activation during frustration, than healthy comparison children. The opposite pattern was found in the posterior cingulate. Further, in clinical subjects, parent report of irritability was dimensionally related to decreased activation of the anterior cingulate and striatum during frustration. The results of this study indicate neural dysfunction within brain regions related to reward processing, error monitoring, and emotion regulation underlying clinically impairing irritability. Results are discussed in the context of a growing field of neuroimaging research investigating irritable children.

  17. Fluorescent probes as a tool for cell population tracking in spontaneously active neural networks derived from human pluripotent stem cells.

    Science.gov (United States)

    Mäkinen, M; Joki, T; Ylä-Outinen, L; Skottman, H; Narkilahti, S; Aänismaa, R

    2013-04-30

    Applications such as 3D cultures and tissue modelling require cell tracking with non-invasive methods. In this work, the suitability of two fluorescent probes, CellTracker, CT, and long chain carbocyanine dye, DiD, was investigated for long-term culturing of labeled human pluripotent stem cell-derived neural cells. We found that these dyes did not affect the cell viability. However, proliferation was decreased in DiD labeled cell population. With both dyes the labeling was stable up to 4 weeks. CT and DiD labeled cells could be co-cultured and, importantly, these mixed populations had their normal ability to form spontaneous electrical network activity. In conclusion, human neural cells can be successfully labeled with these two fluorescent probes without significantly affecting the cell characteristics. These labeled cells could be utilized further in e.g. building controlled neuronal networks for neurotoxicity screening platforms, combining cells with biomaterials for 3D studies, and graft development. Copyright © 2013 Elsevier B.V. All rights reserved.

  18. Collection of regulatory texts relative to radiation protection. Part 2: orders and decisions taken in application of the Public Health Code and Labour Code concerning the protection of populations, patients and workers against the risks of ionizing radiations; Recueil de textes reglementaires relatifs a la radioprotection. Partie 2: arretes et decisions pris en application du Code de Sante Publique et du Code du Travail concernant la protection de la population, des patients et des travailleurs contre les dangers des rayonnements ionisants

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2007-05-15

    This collection of texts includes the general measures of population protection, exposure to natural radiations, general system of authorizations and statements, protection of persons exposed to ionizing radiations for medical purpose, situations of radiological emergency and long exposure to ionizing radiations, penal dispositions, application of the Public Health code and application of the Labour code. Chronological contents by date of publication is given. (N.C.)

  19. Nucleotide sequence analyses of the MRP1 gene in four populations suggest negative selection on its coding region

    Directory of Open Access Journals (Sweden)

    Ryan Stephen

    2006-05-01

    Full Text Available Abstract Background The MRP1 gene encodes the 190 kDa multidrug resistance-associated protein 1 (MRP1/ABCC1 and effluxes diverse drugs and xenobiotics. Sequence variations within this gene might account for differences in drug response in different individuals. To facilitate association studies of this gene with diseases and/or drug response, exons and flanking introns of MRP1 were screened for polymorphisms in 142 DNA samples from four different populations. Results Seventy-one polymorphisms, including 60 biallelic single nucleotide polymorphisms (SNPs, ten insertions/deletions (indel and one short tandem repeat (STR were identified. Thirty-four of these polymorphisms have not been previously reported. Interestingly, the STR polymorphism at the 5' untranslated region (5'UTR occurs at high but different frequencies in the different populations. Frequencies of common polymorphisms in our populations were comparable to those of similar populations in HAPMAP or Perlegen. Nucleotide diversity indices indicated that the coding region of MRP1 may have undergone negative selection or recent population expansion. SNPs E10/1299 G>T (R433S and E16/2012 G>T (G671V which occur at low frequency in only one or two of four populations examined were predicted to be functionally deleterious and hence are likely to be under negative selection. Conclusion Through in silico approaches, we identified two rare SNPs that are potentially negatively selected. These SNPs may be useful for studies associating this gene with rare events including adverse drug reactions.

  20. Population genomic analysis of gibberellin-responsive long non-coding RNAs in Populus.

    Science.gov (United States)

    Tian, Jiaxing; Song, Yuepeng; Du, Qingzhang; Yang, Xiaohui; Ci, Dong; Chen, Jinhui; Xie, Jianbo; Li, Bailian; Zhang, Deqiang

    2016-04-01

    Long non-coding RNAs (lncRNAs) participate in a wide range of biological processes, but lncRNAs in plants remain largely unknown; in particular, we lack a systematic identification of plant lncRNAs involved in hormone responses. Moreover, allelic variation in lncRNAs remains poorly characterized at a large scale. Here, we conducted high-throughput RNA-sequencing of leaves from control and gibberellin (GA)-treated Populus tomentosa and identified 7655 reliably expressed lncRNAs. Among the 7655 lncRNAs, the levels of 410 lncRNAs changed in response to GA. Seven GA-responsive lncRNAs were predicted to be putative targets of 18 miRNAs, and one GA-responsive lncRNA (TCONS_00264314) was predicted to be a target mimic of ptc-miR6459b. Computational analysis predicted 939 potential cis-regulated target genes and 965 potential trans-regulated target genes for GA-responsive lncRNAs. Functional annotation of these potential target genes showed that they participate in many different biological processes, including auxin signal transduction and synthesis of cellulose and pectin, indicating that GA-responsive lncRNAs may influence growth and wood properties. Finally, single nucleotide polymorphism (SNP)-based association analysis showed that 112 SNPs from 52 GA-responsive lncRNAs and 1014 SNPs from 296 potential target genes were significantly associated with growth and wood properties. Epistasis analysis also provided evidence for interactions between lncRNAs and their potential target genes. Our study provides a comprehensive view of P. tomentosa lncRNAs and offers insights into the potential functions and regulatory interactions of GA-responsive lncRNAs, thus forming the foundation for future functional analysis of GA-responsive lncRNAs in P. tomentosa. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  1. Up-regulation of neural indicators of empathic concern in an offender population.

    Science.gov (United States)

    Arbuckle, Nathan L; Shane, Matthew S

    2017-08-01

    Empathic concern has traditionally been conceived of as a spontaneous reaction to others experiencing pain or distress. As such, the potential role of more deliberate control over empathic responses has frequently been overlooked. The present fMRI study evaluated the role of such deliberate control in empathic concern by examining the extent to which a sample of offenders recruited through probation/parole could voluntarily modulate their neural activity to another person in pain. Offenders were asked to either passively view pictures of other people in painful or non-painful situations, or to actively modulate their level of concern for the person in pain. During passive viewing of painful versus non-painful pictures, offenders showed minimal neural activity in regions previously linked to empathy for pain (e.g., dorsal anterior cingulate cortex and bilateral insula). However, when instructed to try to increase their concern for the person in pain, offenders demonstrated significant increases within these regions. These findings are consistent with recent theories of empathy as motivational in nature, and suggest that limitations in empathic concern may include a motivational component.

  2. Deconvolution using a neural network

    Energy Technology Data Exchange (ETDEWEB)

    Lehman, S.K.

    1990-11-15

    Viewing one dimensional deconvolution as a matrix inversion problem, we compare a neural network backpropagation matrix inverse with LMS, and pseudo-inverse. This is a largely an exercise in understanding how our neural network code works. 1 ref.

  3. Epigenetic marks define the lineage and differentiation potential of two distinct neural crest-derived intermediate odontogenic progenitor populations.

    Science.gov (United States)

    Gopinathan, Gokul; Kolokythas, Antonia; Luan, Xianghong; Diekwisch, Thomas G H

    2013-06-15

    Epigenetic mechanisms, such as histone modifications, play an active role in the differentiation and lineage commitment of mesenchymal stem cells. In the present study, epigenetic states and differentiation profiles of two odontogenic neural crest-derived intermediate progenitor populations were compared: dental pulp (DP) and dental follicle (DF). ChIP on chip assays revealed substantial H3K27me3-mediated repression of odontoblast lineage genes DSPP and dentin matrix protein 1 (DMP1) in DF cells, but not in DP cells. Mineralization inductive conditions caused steep increases of mineralization and patterning gene expression levels in DP cells when compared to DF cells. In contrast, mineralization induction resulted in a highly dynamic histone modification response in DF cells, while there was only a subdued effect in DP cells. Both DF and DP progenitors featured H3K4me3-active marks on the promoters of early mineralization genes RUNX2, MSX2, and DLX5, while OSX, IBSP, and BGLAP promoters were enriched for H3K9me3 or H3K27me3. Compared to DF cells, DP cells expressed higher levels of three pluripotency-associated genes, OCT4, NANOG, and SOX2. Finally, gene ontology comparison of bivalent marks unique for DP and DF cells highlighted cell-cell attachment genes in DP cells and neurogenesis genes in DF cells. In conclusion, the present study indicates that the DF intermediate odontogenic neural crest lineage is distinguished from its DP counterpart by epigenetic repression of DSPP and DMP1 genes and through dynamic histone enrichment responses to mineralization induction. Findings presented here highlight the crucial role of epigenetic regulatory mechanisms in the terminal differentiation of odontogenic neural crest lineages.

  4. Artificial Neural Network (ANN) Model to Predict Depression among Geriatric Population at a Slum in Kolkata, India.

    Science.gov (United States)

    Sau, Arkaprabha; Bhakta, Ishita

    2017-05-01

    Depression is one of the most important causes of mortality and morbidity among the geriatric population. Although, the aging brain is more vulnerable to depression, it cannot be considered as physiological and an inevitable part of ageing. Various sociodemographic and morbidity factors are responsible for the depression among them. Using Artificial Neural Network (ANN) model depression can be predicted from various sociodemographic variables and co morbid conditions even at community level by the grass root level health care workers. To predict depression among geriatric population from sociodemographic and morbidity attributes using ANN. An observational descriptive study with cross-sectional design was carried out at a slum under the service area of Bagbazar Urban Health and Training Centre (UHTC) in Kolkata. Among 126 elderlies under Bagbazar UHTC, 105 were interviewed using predesigned and pretested schedule. Depression status was assessed using 30 item Geriatric Depression Scale. WEKA 3.8.0 was used to develop the ANN model and test its performance. Prevalence of depression among the study population was 45.7%. Various sociodemographic variables like age, gender, literacy, living spouse, working status, personal income, family type, substance abuse and co morbid conditions like visual problem, mobility problem, hearing problem and sleeping problem were taken into consideration to develop the model. Prediction accuracy of this ANN model was 97.2%. Depression among geriatric population can be predicted accurately using ANN model from sociodemographic and morbidity attributes.

  5. Neural Coding Mechanisms in Gustation.

    Science.gov (United States)

    1980-09-15

    typologies in the rat gustatory system . Brain Research, in press. 5. Erickson, R. P., and Covey, E. On the singularity of taste systems : What is a taste...gustation. (In preparation for publication) ZZ. Erickson, R. P., Covey, E., and Doetsch, G. S. Neuron and stimulus typologies in the rat gustatory system ... gustatory neurons (1,2, 12). 4 SECURITY CLASSIFICATION OF THIS PAQG(Wr o, Date Etemt) 3a. Publications 1. VanBuskirk, R. L., and Erickson, R. P. Odorant

  6. Neural representation of probabilities for Bayesian inference.

    Science.gov (United States)

    Rich, Dylan; Cazettes, Fanny; Wang, Yunyan; Peña, José Luis; Fischer, Brian J

    2015-04-01

    Bayesian models are often successful in describing perception and behavior, but the neural representation of probabilities remains in question. There are several distinct proposals for the neural representation of probabilities, but they have not been directly compared in an example system. Here we consider three models: a non-uniform population code where the stimulus-driven activity and distribution of preferred stimuli in the population represent a likelihood function and a prior, respectively; the sampling hypothesis which proposes that the stimulus-driven activity over time represents a posterior probability and that the spontaneous activity represents a prior; and the class of models which propose that a population of neurons represents a posterior probability in a distributed code. It has been shown that the non-uniform population code model matches the representation of auditory space generated in the owl's external nucleus of the inferior colliculus (ICx). However, the alternative models have not been tested, nor have the three models been directly compared in any system. Here we tested the three models in the owl's ICx. We found that spontaneous firing rate and the average stimulus-driven response of these neurons were not consistent with predictions of the sampling hypothesis. We also found that neural activity in ICx under varying levels of sensory noise did not reflect a posterior probability. On the other hand, the responses of ICx neurons were consistent with the non-uniform population code model. We further show that Bayesian inference can be implemented in the non-uniform population code model using one spike per neuron when the population is large and is thus able to support the rapid inference that is necessary for sound localization.

  7. Does arsenic increase the risk of neural tube defects among a highly exposed population? A new case-control study in Bangladesh.

    Science.gov (United States)

    Mazumdar, Maitreyi

    2017-01-30

    Neural tube defects are debilitating birth defects that occur when the developing neural plate fails to close in early gestation. Arsenic induces neural tube defects in animal models, but whether environmental arsenic exposure increases risk of neural tube defects in humans is unknown. We describe a new case-control study in Bangladesh, a country currently experiencing an epidemic of arsenic poisoning through contaminated drinking water. We plan to understand how arsenic influences risk of neural tube defects in humans through mechanisms that include disruption of maternal glucose and folate metabolism, as well as epigenetic effects. We also investigate whether sweat chloride concentration, a potential new biomarker for arsenic toxicity, can be used to identify women at higher risk for having a child affected by neural tube defect. We will collect dural tissue from cases, obtained at the time of surgical closure of the defect, and believe investigation of these samples will provide insight into the epigenetic mechanisms by which prenatal arsenic exposure affects the developing nervous system. These studies explore mechanisms by which arsenic may increase risk of neural tube defects in humans and use a unique population with high arsenic exposure to test hypotheses. If successful, these studies may assist countries with high arsenic exposure such as Bangladesh to identify populations at high risk of neural tube defects, as well as direct development of novel screening strategies for maternal risk.Birth Defects Research 109:92-98, 2017.© 2016 The Authors Birth Defects Research Published by Wiley Periodicals, Inc. © 2016 The Authors Birth Defects Research Published by Wiley Periodicals, Inc.

  8. A prospective crossover comparison of neurally adjusted ventilatory assist and pressure-support ventilation in a pediatric and neonatal intensive care unit population.

    LENUS (Irish Health Repository)

    Breatnach, Cormac

    2012-02-01

    OBJECTIVE: To compare neurally adjusted ventilatory assist ventilation with pressure-support ventilation. DESIGN: Prospective, crossover comparison study. SETTING: Tertiary care pediatric and neonatal intensive care unit. PATIENTS: Sixteen ventilated infants and children: mean age = 9.7 months (range = 2 days-4 yrs) and mean weight = 6.2 kg (range = 2.4-13.7kg). INTERVENTIONS: A modified nasogastric tube was inserted and correct positioning was confirmed. Patients were ventilated in pressure-support mode with a pneumatic trigger for a 30-min period and then in neurally adjusted ventilatory assist mode for up to 4 hrs. MEASUREMENTS AND MAIN RESULTS: Data collected for comparison included activating trigger (neural vs. pneumatic), peak and mean airway pressures, expired minute and tidal volumes, heart rate, respiratory rate, pulse oximetry, end-tidal CO2 and arterial blood gases. Synchrony was improved in neurally adjusted ventilatory assist mode with 65% (+\\/-21%) of breaths triggered neurally vs. 35% pneumatically (p < .001) and 85% (+\\/-8%) of breaths cycled-off neurally vs. 15% pneumatically (p = .0001). The peak airway pressure in neurally adjusted ventilatory assist mode was significantly lower than in pressure-support mode with a 28% decrease in pressure after 30 mins (p = .003) and 32% decrease after 3 hrs (p < .001). Mean airway pressure was reduced by 11% at 30 mins (p = .13) and 9% at 3 hrs (p = .31) in neurally adjusted ventilatory assist mode although this did not reach statistical significance. Patient hemodynamics and gas exchange remained stable for the study period. No adverse patient events or device effects were noted. CONCLUSIONS: In a neonatal and pediatric intensive care unit population, ventilation in neurally adjusted ventilatory assist mode was associated with improved patient-ventilator synchrony and lower peak airway pressure when compared with pressure-support ventilation with a pneumatic trigger. Ventilating patients in this new mode

  9. Artificial neural network for predicting pathological stage of clinically localized prostate cancer in a Taiwanese population

    Directory of Open Access Journals (Sweden)

    Chih-Wei Tsao

    2014-10-01

    Conclusion: ANN was superior to LR at predicting OCD in prostate cancer. Compared with the validation of current Partin Tables for the Taiwanese population, the ANN model resulted in larger AUCs and more accurate prediction of the pathologic stage of prostate cancer.

  10. Application of convolutional artificial neural networks to echocardiograms for differentiating congenital heart diseases in a pediatric population

    Science.gov (United States)

    Perrin, Douglas P.; Bueno, Alejandra; Rodriguez, Andrea; Marx, Gerald R.; del Nido, Pedro J.

    2017-03-01

    In this paper we describe a pilot study, where machine learning methods are used to differentiate between congenital heart diseases. Our approach was to apply convolutional neural networks (CNNs) to echocardiographic images from five different pediatric populations: normal, coarctation of the aorta (CoA), hypoplastic left heart syndrome (HLHS), transposition of the great arteries (TGA), and single ventricle (SV). We used a single network topology that was trained in a pairwise fashion in order to evaluate the potential to differentiate between patient populations. In total we used 59,151 echo frames drawn from 1,666 clinical sequences. Approximately 80% of the data was used for training, and the remainder for validation. Data was split at sequence boundaries to avoid having related images in the training and validation sets. While training was done with echo images/frames, evaluation was performed for both single frame discrimination as well as sequence discrimination (by majority voting). In total 10 networks were generated and evaluated. Unlike other domains where this network topology has been used, in ultrasound there is low visual variation between classes. This work shows the potential for CNNs to be applied to this low-variation domain of medical imaging for disease discrimination.

  11. The 745.5 issue in code-based, adult congenital heart disease population studies: Relevance to current and future ICD-9-CM and ICD-10-CM studies.

    Science.gov (United States)

    Rodriguez, Fred H; Ephrem, Georges; Gerardin, Jennifer F; Raskind-Hood, Cheryl; Hogue, Carol; Book, Wendy

    2018-01-01

    Although the ICD-9-CM code 745.5 is widely used to indicate the presence of a secundum atrial septal defect (ASD), it is also used for patent foramen ovale (PFO) which is a normal variant and for "rule-out" congenital heart disease (CHD). The ICD-10-CM code Q21.1 perpetuates this issue. The objective of this study was to assess whether code 745.5 in isolation or in combination with unspecified CHD codes 746.9 or 746.89 miscodes for CHD, and if true CHD positives decrease with age. Echocardiograms of patients with an ICD-9-CM code of 745.5 in isolation or in combination with unspecified CHD codes 746.9 or 746.89 were reviewed to validate the true incidence of an ASD. This observational, cross-sectional record review included patients between 11 and 64 years of age. Medical charts and echocardiograms of 190 patients (47.9% males) were reviewed. The number of falsely coded patients with 745.5 (no ASD) was high (76.3%). Forty-five (23.7%) patients had a true ASD. Among the 145 patients without an ASD, 100 (52.6%) were classified as having a PFO, 37 (19.5%) had a normal non-CHD echocardiogram, and 8 (4.2%) had some other CHD anomaly. The likelihood that 745.5 coded for a true ASD was higher in children aged 11-20 (64.3%) than adults aged 21-64 years (20.6%). This validation study demonstrates that 745.5 performed poorly across all ages. As 745.5 is widely used in population-level investigations and ICD-10-CM perpetuates the problem, future analyses utilizing CHD codes should consider separate analysis of those identified only through code 745.5. © 2017 Wiley Periodicals, Inc.

  12. Clique of functional hubs orchestrates population bursts in developmentally regulated neural networks.

    Directory of Open Access Journals (Sweden)

    Stefano Luccioli

    2014-09-01

    Full Text Available It has recently been discovered that single neuron stimulation can impact network dynamics in immature and adult neuronal circuits. Here we report a novel mechanism which can explain in neuronal circuits, at an early stage of development, the peculiar role played by a few specific neurons in promoting/arresting the population activity. For this purpose, we consider a standard neuronal network model, with short-term synaptic plasticity, whose population activity is characterized by bursting behavior. The addition of developmentally inspired constraints and correlations in the distribution of the neuronal connectivities and excitabilities leads to the emergence of functional hub neurons, whose stimulation/deletion is critical for the network activity. Functional hubs form a clique, where a precise sequential activation of the neurons is essential to ignite collective events without any need for a specific topological architecture. Unsupervised time-lagged firings of supra-threshold cells, in connection with coordinated entrainments of near-threshold neurons, are the key ingredients to orchestrate population activity.

  13. Network Modeling and Assessment of Ecosystem Health by a Multi-Population Swarm Optimized Neural Network Ensemble

    Directory of Open Access Journals (Sweden)

    Rong Shan

    2016-06-01

    Full Text Available Society is more and more interested in developing mathematical models to assess and forecast the environmental and biological health conditions of our planet. However, most existing models cannot determine the long-range impacts of potential policies without considering the complex global factors and their cross effects in biological systems. In this paper, the Markov property and Neural Network Ensemble (NNE are utilized to construct an estimated matrix that combines the interaction of the different local factors. With such an estimation matrix, we could obtain estimated variables that could reflect the global influence. The ensemble weights are trained by multiple population algorithms. Our prediction could fit the real trend of the two predicted measures, namely Morbidity Rate and Gross Domestic Product (GDP. It could be an effective method of reflecting the relationship between input factors and predicted measures of the health of ecosystems. The method can perform a sensitivity analysis, which could help determine the critical factors that could be adjusted to move the ecosystem in a sustainable direction.

  14. Search for the Missing lncs: Gene Regulatory Networks in Neural Crest Development and Long Non-coding RNA Biomarkers of Hirschsprung's Disease

    Science.gov (United States)

    Hirschsprung’s disease (HSCR), a birth defect characterized by variable aganglionosis of the gut, affects about 1 in 5000 births, and is a consequence of abnormal development of neural crest cells, from which enteric ganglia derive. In the companion article in this issue (S...

  15. Search for the Missing lncs: Gene Regulatory Networks in Neural Crest Development and Long Non-coding RNA Biomarkers of Hirschsprung's Disease

    Science.gov (United States)

    Hirschsprung’s disease (HSCR), a birth defect characterized by variable aganglionosis of the gut, affects about 1 in 5000 births, and is a consequence of abnormal development of neural crest cells, from which enteric ganglia derive. In the companion article in this issue (Shen et...

  16. Orion: Detecting regions of the human non-coding genome that are intolerant to variation using population genetics.

    Science.gov (United States)

    Gussow, Ayal B; Copeland, Brett R; Dhindsa, Ryan S; Wang, Quanli; Petrovski, Slavé; Majoros, William H; Allen, Andrew S; Goldstein, David B

    2017-01-01

    There is broad agreement that genetic mutations occurring outside of the protein-coding regions play a key role in human disease. Despite this consensus, we are not yet capable of discerning which portions of non-coding sequence are important in the context of human disease. Here, we present Orion, an approach that detects regions of the non-coding genome that are depleted of variation, suggesting that the regions are intolerant of mutations and subject to purifying selection in the human lineage. We show that Orion is highly correlated with known intolerant regions as well as regions that harbor putatively pathogenic variation. This approach provides a mechanism to identify pathogenic variation in the human non-coding genome and will have immediate utility in the diagnostic interpretation of patient genomes and in large case control studies using whole-genome sequences.

  17. Population-based evaluation of a suggested anatomic and clinical classification of congenital heart defects based on the International Paediatric and Congenital Cardiac Code

    Directory of Open Access Journals (Sweden)

    Goffinet François

    2011-10-01

    Full Text Available Abstract Background Classification of the overall spectrum of congenital heart defects (CHD has always been challenging, in part because of the diversity of the cardiac phenotypes, but also because of the oft-complex associations. The purpose of our study was to establish a comprehensive and easy-to-use classification of CHD for clinical and epidemiological studies based on the long list of the International Paediatric and Congenital Cardiac Code (IPCCC. Methods We coded each individual malformation using six-digit codes from the long list of IPCCC. We then regrouped all lesions into 10 categories and 23 subcategories according to a multi-dimensional approach encompassing anatomic, diagnostic and therapeutic criteria. This anatomic and clinical classification of congenital heart disease (ACC-CHD was then applied to data acquired from a population-based cohort of patients with CHD in France, made up of 2867 cases (82% live births, 1.8% stillbirths and 16.2% pregnancy terminations. Results The majority of cases (79.5% could be identified with a single IPCCC code. The category "Heterotaxy, including isomerism and mirror-imagery" was the only one that typically required more than one code for identification of cases. The two largest categories were "ventricular septal defects" (52% and "anomalies of the outflow tracts and arterial valves" (20% of cases. Conclusion Our proposed classification is not new, but rather a regrouping of the known spectrum of CHD into a manageable number of categories based on anatomic and clinical criteria. The classification is designed to use the code numbers of the long list of IPCCC but can accommodate ICD-10 codes. Its exhaustiveness, simplicity, and anatomic basis make it useful for clinical and epidemiologic studies, including those aimed at assessment of risk factors and outcomes.

  18. Genetic diversity of the HLA-G coding region in Amerindian populations from the Brazilian Amazon: a possible role of natural selection.

    Science.gov (United States)

    Mendes-Junior, C T; Castelli, E C; Meyer, D; Simões, A L; Donadi, E A

    2013-12-01

    HLA-G has an important role in the modulation of the maternal immune system during pregnancy, and evidence that balancing selection acts in the promoter and 3'UTR regions has been previously reported. To determine whether selection acts on the HLA-G coding region in the Amazon Rainforest, exons 2, 3 and 4 were analyzed in a sample of 142 Amerindians from nine villages of five isolated tribes that inhabit the Central Amazon. Six previously described single-nucleotide polymorphisms (SNPs) were identified and the Expectation-Maximization (EM) and PHASE algorithms were used to computationally reconstruct SNP haplotypes (HLA-G alleles). A new HLA-G allele, which originated in Amerindian populations by a crossing-over event between two widespread HLA-G alleles, was identified in 18 individuals. Neutrality tests evidenced that natural selection has a complex part in the HLA-G coding region. Although balancing selection is the type of selection that shapes variability at a local level (Native American populations), we have also shown that purifying selection may occur on a worldwide scale. Moreover, the balancing selection does not seem to act on the coding region as strongly as it acts on the flanking regulatory regions, and such coding signature may actually reflect a hitchhiking effect.

  19. Predicting symptomatic cerebral vasospasm after aneurysmal subarachnoid hemorrhage with an artificial neural network in a pediatric population.

    Science.gov (United States)

    Skoch, Jesse; Tahir, Rizwan; Abruzzo, Todd; Taylor, John M; Zuccarello, Mario; Vadivelu, Sudhakar

    2017-12-01

    Artificial neural networks (ANN) are increasingly applied to complex medical problem solving algorithms because their outcome prediction performance is superior to existing multiple regression models. ANN can successfully identify symptomatic cerebral vasospasm (SCV) in adults presenting after aneurysmal subarachnoid hemorrhage (aSAH). Although SCV is unusual in children with aSAH, the clinical consequences are severe. Consequently, reliable tools to predict patients at greatest risk for SCV may have significant value. We applied ANN modeling to a consecutive cohort of pediatric aSAH cases to assess its ability to predict SCV. A retrospective chart review was conducted to identify patients < 21 years of age who presented with spontaneously ruptured, non-traumatic, non-mycotic, non-flow-related intracranial arterial aneurysms to our institution between January 2002 and January 2015. Demographics, clinical, radiographic, and outcome data were analyzed using an adapted ANN model using learned value nodes from the adult aneurysmal SAH dataset previously reported. The strength of the ANN prediction was measured between - 1 and 1 with - 1 representing no likelihood of SCV and 1 representing high likelihood of SCV. Sixteen patients met study inclusion criteria. The median age for aSAH patients was 15 years. Ten underwent surgical clipping and 6 underwent endovascular coiling for definitive treatment. One patient experienced SCV and 15 did not. The ANN applied here was able to accurately predict all 16 outcomes. The mean strength of prediction for those who did not exhibit SCV was - 0.86. The strength for the one patient who did exhibit SCV was 0.93. Adult-derived aneurysmal SAH value nodes can be applied to a simple AAN model to accurately predict SCV in children presenting with aSAH. Further work is needed to determine if ANN models can prospectively predict SCV in the pediatric aSAH population in toto; adapted to include mycotic, traumatic, and flow

  20. The emergence of two anti-phase oscillatory neural populations in a computational model of the Parkinsonian globus pallidus

    Directory of Open Access Journals (Sweden)

    Robert John Merrison-Hort

    2013-12-01

    Full Text Available Experiments in rodent models of Parkinson's Disease have demonstrated a prominent increase of oscillatory firing patterns in neurons within the Parkinsonian globus pallidus (GP which may underlie some of the motor symptoms of the disease. There are two main pathways from the cortex to GP: via the striatum and via the subthalamic nucleus (STN, but it is not known how these inputs sculpt the pathological pallidal firing patterns. To study this we developed a novel neural network model of conductance-based spiking pallidal neurons with cortex-modulated input from STN neurons. Our results support the hypothesis that entrainment occurs primarily via the subthalamic pathway. We find that as a result of the interplay between excitatory input from the STN and mutual inhibitory coupling between GP neurons, a homogeneous population of GP neurons demonstrates a self-organising dynamical behaviour where two groups of neurons emerge: one spiking in-phase with the cortical rhythm and the other in anti-phase. This finding mirrors what is seen in recordings from the GP of rodents that have had Parkinsonism induced via brain lesions. Our model also includes downregulation of Hyperpolarization-activated Cyclic Nucleotide-gated (HCN channels in response to burst firing of GP neurons, since this has been suggested as a possible mechanism for the emergence of Parkinsonian activity. We found that the downregulation of HCN channels provides even better correspondence with experimental data but that it is not essential in order for the two groups of oscillatory neurons to appear. We discuss how the influence of inhibitory striatal input will strengthen our results.

  1. Closed-loop control of epileptiform activities in a neural population model using a proportional-derivative controller

    Science.gov (United States)

    Wang, Jun-Song; Wang, Mei-Li; Li, Xiao-Li; Ernst, Niebur

    2015-03-01

    Epilepsy is believed to be caused by a lack of balance between excitation and inhibitation in the brain. A promising strategy for the control of the disease is closed-loop brain stimulation. How to determine the stimulation control parameters for effective and safe treatment protocols remains, however, an unsolved question. To constrain the complex dynamics of the biological brain, we use a neural population model (NPM). We propose that a proportional-derivative (PD) type closed-loop control can successfully suppress epileptiform activities. First, we determine the stability of root loci, which reveals that the dynamical mechanism underlying epilepsy in the NPM is the loss of homeostatic control caused by the lack of balance between excitation and inhibition. Then, we design a PD type closed-loop controller to stabilize the unstable NPM such that the homeostatic equilibriums are maintained; we show that epileptiform activities are successfully suppressed. A graphical approach is employed to determine the stabilizing region of the PD controller in the parameter space, providing a theoretical guideline for the selection of the PD control parameters. Furthermore, we establish the relationship between the control parameters and the model parameters in the form of stabilizing regions to help understand the mechanism of suppressing epileptiform activities in the NPM. Simulations show that the PD-type closed-loop control strategy can effectively suppress epileptiform activities in the NPM. Project supported by the National Natural Science Foundation of China (Grant Nos. 61473208, 61025019, and 91132722), ONR MURI N000141010278, and NIH grant R01EY016281.

  2. Traditional marriage and family relations of the Albanian population from Kosovo and Metohia in the light of Leka Dukajini Code

    Directory of Open Access Journals (Sweden)

    Predojević Jelena R.

    2002-01-01

    Full Text Available The Leka Dukajini Code (LDC influenced the way of life of Albanian population to a great extent. It represents a set of rules and norms by which they regulated their relations, and it is believed that they still do so presently as well to some extent. Taking into consideration that LDC includes almost all social, economic and moral spheres of life, this paper analyzes the fields which contribute to the familiarization with the conditions in which the Kosovo and Metohia population developed, such as the organization of the patriarchal family, marriage relations, the position of women, inheritance, and similar. The patriarchy with Albanians is still present today, especially in the villages, and here and there in towns, despite the escalated process of urbanization and industrialization. Manifestations of this patriarchal way of life are reflected through the maintenance of the institutions of family clans, whose characteristics are a large number of families, mutual property and production means, mutual production and consumption as well as communal living. A large number of authors believes that in the ethno-psyche of every Albanian there are still roots of will and sympathy towards clans. A clan is governed by its head, and his authority, although established on the interests of the group, presents limited individual freedom for the members of the family because it is expected from them to respect the will of the head of the family. Family clans in the eyes of others represents a secure way of life. Common law arose and developed under cruel life conditions, codified the way of life and in that way neglected individuality yet imposed the group, large families, solidarity and submissiveness to authority. The whole LDC is imbued with religious spirit, which is most obviously expressed with the institution of marriage. It also puts the woman in the worst position, who is not respected as a women, who has no right in decision making, and the more

  3. Signatures of demography and recombination at coding genes in naturally-distributed populations of Arabidopsis lyrata subsp. petraea.

    Directory of Open Access Journals (Sweden)

    Cynthia C Vigueira

    Full Text Available Demography impacts the observed standing level of genetic diversity present in populations. Distinguishing the relative impacts of demography from selection requires a baseline of expressed gene variation in naturally occurring populations. Six nuclear genes were sequenced to estimate the patterns and levels of genetic diversity in natural Arabidopsis lyrata subsp. petraea populations that differ in demographic histories since the Pleistocene. As expected, northern European populations have genetic signatures of a strong population bottleneck likely due to glaciation during the Pleistocene. Levels of diversity in the northern populations are about half of that in central European populations. Bayesian estimates of historical population size changes indicate that central European populations also have signatures of population size change since the last glacial maxima, suggesting that these populations are not as stable as previously thought. Time since divergence amongst northern European populations is higher than amongst central European populations, suggesting that the northern European populations were established before the Pleistocene and survived glaciation in small separated refugia. Estimates of demography based on expressed genes are complementary to estimates based on microsatellites and transposable elements, elucidating temporal shifts in population dynamics and confirming the importance of marker selection for tests of demography.

  4. Neural networks for the analysis of margins of safety through code BE+U; Redes neuronales para el analisis de margenes de seguridad mediante codigos be+u

    Energy Technology Data Exchange (ETDEWEB)

    Villamizar, M.; Martorell, S.; Villanueva, J. F.; Carlos, S.; Sanchez, A.; Serradell, V.; Mendizabal, R.; Pelayo, F.; Sol, I.

    2011-07-01

    This paper presents the use of tools {sup S}oft Computing{sup ,} in particular the use of artificial neural networks and the method of decomposition of variance as sensitivity analysis, which allows understanding and modeling the relations between variables uncertain input inputs (defined by functions of distribution of Thermo-hydraulic model parameters) and output outputs variable presentation takes place on LOCA accident in a PWR as application.

  5. Importance of ICD-10 coding directive change for acute gastroenteritis (unspecified) for rotavirus vaccine impact studies: illustration from a population-based cohort study from Ontario, Canada.

    Science.gov (United States)

    Wilson, Sarah E; Deeks, Shelley L; Rosella, Laura C

    2015-09-15

    In Ontario, Canada, we conducted an evaluation of rotavirus (RV) vaccine on hospitalizations and Emergency Department (ED) visitations for acute gastroenteritis (AGE). In our original analysis, any one of the International Classification of Disease, Version 10 (ICD-10) codes was used for outcome ascertainment: RV-specific- (A08.0), viral- (A08.3, A08. 4, A08.5), and unspecified infectious- gastroenteritis (A09). Annual age-specific rates per 10,000 population were calculated. The average monthly rate of AGE hospitalization for children under age two increased from 0.82 per 10,000 from January 2003 to March 2009, to 2.35 over the period of April 2009 to March 31, 2013. Similar trends were found for ED consultations and in other age groups. A rise in events corresponding to the A09 code was found when the outcome definition was disaggregated by ICD-10 code. Documentation obtained from the World Health Organization confirmed that a change in directive for the classification of unspecified gastroenteritis occurred with the release of ICD-10 in April 2009. AGE events previously classified under the code K52.9, are now classified under code A09.9. Based on change in the classification of unspecified gastroenteritis we modified our outcome definition to also include unspecified non-infectious-gastroenteritis (K52.9). We recommend other investigators consider using both A09.9 and K52.9 ICD-10 codes for outcome ascertainment in future rotavirus vaccine impact studies to ensure that all unspecified cases of AGE are captured, especially if the study period spans 2009.

  6. Controlling the elements: an optogenetic approach to understanding the neural circuits of fear.

    Science.gov (United States)

    Johansen, Joshua P; Wolff, Steffen B E; Lüthi, Andreas; LeDoux, Joseph E

    2012-06-15

    Neural circuits underlie our ability to interact in the world and to learn adaptively from experience. Understanding neural circuits and how circuit structure gives rise to neural firing patterns or computations is fundamental to our understanding of human experience and behavior. Fear conditioning is a powerful model system in which to study neural circuits and information processing and relate them to learning and behavior. Until recently, technological limitations have made it difficult to study the causal role of specific circuit elements during fear conditioning. However, newly developed optogenetic tools allow researchers to manipulate individual circuit components such as anatomically or molecularly defined cell populations, with high temporal precision. Applying these tools to the study of fear conditioning to control specific neural subpopulations in the fear circuit will facilitate a causal analysis of the role of these circuit elements in fear learning and memory. By combining this approach with in vivo electrophysiological recordings in awake, behaving animals, it will also be possible to determine the functional contribution of specific cell populations to neural processing in the fear circuit. As a result, the application of optogenetics to fear conditioning could shed light on how specific circuit elements contribute to neural coding and to fear learning and memory. Furthermore, this approach may reveal general rules for how circuit structure and neural coding within circuits gives rise to sensory experience and behavior. Copyright © 2012 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  7. Validation of diagnostic codes for intussusception and quantification of childhood intussusception incidence in Ontario, Canada: a population-based study.

    Science.gov (United States)

    Ducharme, Robin; Benchimol, Eric I; Deeks, Shelley L; Hawken, Steven; Fergusson, Dean A; Wilson, Kumanan

    2013-10-01

    To validate an algorithm to identify cases of intussusception using the health administrative data of Ontario, Canada, and to apply the algorithm to estimate provincial incidence of intussusception, preceding the introduction of the universal rotavirus vaccination program. We determined the accuracy of various combinations of diagnostic, procedural, and billing codes using the chart-abstracted diagnoses of patients of the Children's Hospital of Eastern Ontario as the reference standard. We selected an algorithm that maximized positive predictive value while maintaining a high sensitivity and used it to ascertain annual incidence of intussusception for fiscal years 1995-2010. We explored temporal trends in incidence using Poisson regression. The selected algorithm included only the International Classification of Diseases (ICD)-9 or ICD-10 code for intussusception in the hospitalization database and was sensitive (89.3%) and highly specific (>99.9%). The positive predictive value of the ICD code was 72.4%, and the negative predictive value was >99.9%. We observed the highest mean incidence (34 per 100000) in male children health administrative data using validated algorithms. We have described changes in temporal trends in intussusception incidence in Ontario and established a baseline to allow ongoing monitoring as part of vaccine safety surveillance. Copyright © 2013 Mosby, Inc. All rights reserved.

  8. Evolvable Neural Software System

    Science.gov (United States)

    Curtis, Steven A.

    2009-01-01

    The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.

  9. Building Neural Net Software

    OpenAIRE

    Neto, João Pedro; Costa, José Félix

    1999-01-01

    In a recent paper [Neto et al. 97] we showed that programming languages can be translated on recurrent (analog, rational weighted) neural nets. The goal was not efficiency but simplicity. Indeed we used a number-theoretic approach to machine programming, where (integer) numbers were coded in a unary fashion, introducing a exponential slow down in the computations, with respect to a two-symbol tape Turing machine. Implementation of programming languages in neural nets turns to be not only theo...

  10. Human population doses: Comparative analysis of CREAM code results with currently computer codes of Nuclear Regulatory Authority; Dosis en la poblacion: comparacion de los resultados del codigo CREAM con resultados de modelos vigentes en la ARN

    Energy Technology Data Exchange (ETDEWEB)

    Alonso Jimenez, Maria Teresa; Curti, Adriana [Autoridad Regulatoria Nuclear, Buenos Aires (Argentina)]. E-mail: mtalonso@sede.arn.gov.ar; acurti@sede.arn.gov.ar

    2001-07-01

    The Nuclear Regulatory Authority is performing an analysis with PC CREAM, developed at the NRPB, for updating computer programs and models used for calculating the transfer of radionuclides through the environment. For CREAM dose assessment verification for local scenarios, this paper presents a comparison of population doses assessed with the computer codes used nowadays and with CREAM, for unitary releases of main radionuclides in nuclear power plant discharges. The results of atmospheric dispersion processes and the transfer of radionuclides through the environment for local scenarios are analysed. The programs used are PLUME for atmospheric dispersion, FARMLAND for the transfer of radionuclides into foodstuffs following atmospheric deposition in the terrestrial environment and ASSESSOR for individual and collective dose assessments.This paper presents the general assumptions made for dose assessments. The results show some differences between doses due to differences in models, in the complexity level of the same models, or in parameters. (author)

  11. Time trends in the prevalence and epidemiological characteristics of neural tube defects in Liaoning Province, China, 2006-2015: A population-based study.

    Science.gov (United States)

    Zhang, Tie-Ning; Gong, Ting-Ting; Chen, Yan-Ling; Wu, Qi-Jun; Zhang, Yuan; Jiang, Cheng-Zhi; Li, Jing; Li, Li-Li; Zhou, Chen; Huang, Yan-Hong

    2017-03-07

    To evaluate the time trends in the prevalence of neural tube defects and all their subtypes as well as to identify the epidemiological characteristics of these malformations documented in the Liaoning Province of northeast China from 2006 to 2015. This was a population-based observational study using data from 3,248,954 live births as well as from 6217 cases of neural tube defects, 1,600 cases of anencephaly, 2,029 cases of spina bifida, 404 cases of encephalocele, and 3,008 cases of congenital hydrocephalus from 14 cities in Liaoning Province from 2006 to 2015. All analyses were conducted using SPSS software. During the observational period, the prevalence of neural tube defects, anencephaly, spina bifida, encephalocele, and congenital hydrocephalus was 19.1, 4.9, 6.2, 1.2, and 9.3 per 10,000 live births, respectively. Significantly decreasing trends were observed in the prevalence of all these malformations except for encephalocele. Notably, relatively higher prevalence rates were found in isolated compared with non-isolated malformations, with significant differences in selected characteristics (e.g., prognosis status, gestational age, and birth weight) between isolated and non-isolated cases of these malformations. The prevalence of neural tube defects showed a downward trend in Liaoning Province from 2006 to 2015. However, more attention should be focused on non-isolated cases in the future because of the severe clinical manifestations. Future prevention efforts should be strengthened to reduce the risk of these malformations, especially the non-isolated subtype, in areas with high prevalence.

  12. Association of Long Non-Coding RNA HOTAIR Polymorphisms with Cervical Cancer Risk in a Chinese Population.

    Directory of Open Access Journals (Sweden)

    Liangsheng Guo

    Full Text Available Long non-coding RNAs (lncRNAs, HOTAIR has been reported to be upregulated in cervical cancer development and progression. However, SNPs (single nucleotide polymorphisms in the lncRNAs and their associations with cervical cancer susceptibility have not been reported. In the current study, we hypothesized that SNPs within the lncRNA HOTAIR may influence the risk of cervical cancer. We performed a case-control study including 510 cervical cancer patients (cases and 713 cancer-free individuals (controls to investigate the association between three haplotype-tagging SNPs (rs920778, rs1899663 and rs4759314 in the lncRNA HOTAIR and the risk of cervical cancer. We found a strong association between the SNP rs920778 in the intronic enhancer of the HOTAIR and cervical cancer (P<10-4. Moreover, the cervical cancer patients with homozygous TT genotype were significantly associated with tumor-node-metastasis (TNM stage. In vitro assays with allele-specific reporter constructs indicated that the reporter constructs bearing rs920778T allele conferred elevated reporter gene transcriptional activity when compared to the reporter constructs containing rs920778C allele. Furthermore, HOTAIR expression was higher in cervical cancer tissues than that in corresponding normal tissues, and the high expression was associated with the risk-associated allele T. In summary, our studies provide strong functional evidence that functional SNP rs920778 regulates HOTAIR expression, and may ultimately influence the predisposition for cervical cancer.

  13. With or without you: predictive coding and Bayesian inference in the brain.

    Science.gov (United States)

    Aitchison, Laurence; Lengyel, Máté

    2017-10-01

    Two theoretical ideas have emerged recently with the ambition to provide a unifying functional explanation of neural population coding and dynamics: predictive coding and Bayesian inference. Here, we describe the two theories and their combination into a single framework: Bayesian predictive coding. We clarify how the two theories can be distinguished, despite sharing core computational concepts and addressing an overlapping set of empirical phenomena. We argue that predictive coding is an algorithmic/representational motif that can serve several different computational goals of which Bayesian inference is but one. Conversely, while Bayesian inference can utilize predictive coding, it can also be realized by a variety of other representations. We critically evaluate the experimental evidence supporting Bayesian predictive coding and discuss how to test it more directly. Copyright © 2017. Published by Elsevier Ltd.

  14. Sensorimotor transformation via sparse coding

    Science.gov (United States)

    Takiyama, Ken

    2015-01-01

    Sensorimotor transformation is indispensable to the accurate motion of the human body in daily life. For instance, when we grasp an object, the distance from our hands to an object needs to be calculated by integrating multisensory inputs, and our motor system needs to appropriately activate the arm and hand muscles to minimize the distance. The sensorimotor transformation is implemented in our neural systems, and recent advances in measurement techniques have revealed an important property of neural systems: a small percentage of neurons exhibits extensive activity while a large percentage shows little activity, i.e., sparse coding. However, we do not yet know the functional role of sparse coding in sensorimotor transformation. In this paper, I show that sparse coding enables complete and robust learning in sensorimotor transformation. In general, if a neural network is trained to maximize the performance on training data, the network shows poor performance on test data. Nevertheless, sparse coding renders compatible the performance of the network on both training and test data. Furthermore, sparse coding can reproduce reported neural activities. Thus, I conclude that sparse coding is necessary and a biologically plausible factor in sensorimotor transformation. PMID:25923980

  15. Efficacy of physical activity interventions in post-natal populations: systematic review, meta-analysis and content coding of behaviour change techniques.

    Science.gov (United States)

    Gilinsky, Alyssa Sara; Dale, Hannah; Robinson, Clare; Hughes, Adrienne R; McInnes, Rhona; Lavallee, David

    2015-01-01

    This systematic review and meta-analysis reports the efficacy of post-natal physical activity change interventions with content coding of behaviour change techniques (BCTs). Electronic databases (MEDLINE, CINAHL and PsychINFO) were searched for interventions published from January 1980 to July 2013. Inclusion criteria were: (i) interventions including ≥1 BCT designed to change physical activity behaviour, (ii) studies reporting ≥1 physical activity outcome, (iii) interventions commencing later than four weeks after childbirth and (iv) studies including participants who had given birth within the last year. Controlled trials were included in the meta-analysis. Interventions were coded using the 40-item Coventry, Aberdeen & London - Refined (CALO-RE) taxonomy of BCTs and study quality assessment was conducted using Cochrane criteria. Twenty studies were included in the review (meta-analysis: n = 14). Seven were interventions conducted with healthy inactive post-natal women. Nine were post-natal weight management studies. Two studies included women with post-natal depression. Two studies focused on improving general well-being. Studies in healthy populations but not for weight management successfully changed physical activity. Interventions increased frequency but not volume of physical activity or walking behaviour. Efficacious interventions always included the BCTs 'goal setting (behaviour)' and 'prompt self-monitoring of behaviour'.

  16. [Artificial neural networks in Neurosciences].

    Science.gov (United States)

    Porras Chavarino, Carmen; Salinas Martínez de Lecea, José María

    2011-11-01

    This article shows that artificial neural networks are used for confirming the relationships between physiological and cognitive changes. Specifically, we explore the influence of a decrease of neurotransmitters on the behaviour of old people in recognition tasks. This artificial neural network recognizes learned patterns. When we change the threshold of activation in some units, the artificial neural network simulates the experimental results of old people in recognition tasks. However, the main contributions of this paper are the design of an artificial neural network and its operation inspired by the nervous system and the way the inputs are coded and the process of orthogonalization of patterns.

  17. The C677T polymorphism of the methylenetetrahydrofolate reductase gene in Mexican mestizo neural-tube defect parents, control mestizo and native populations.

    Science.gov (United States)

    Dávalos, I P; Olivares, N; Castillo, M T; Cantú, J M; Ibarra, B; Sandoval, L; Morán, M C; Gallegos, M P; Chakraborty, R; Rivas, F

    2000-01-01

    The C677T mutation of the methylenetetrahydrofolate reductase (MTHFR) gene, associated with the thermolabile form of the enzyme, has reportedly been found to be increased in neural-tube defects (NTD), though this association is still unclear. A group of 107 mestizo parents of NTD children and five control populations: 101 mestizo (M), 50 Huichol (H), 38 Tarahumara (T), 21 Purepecha (P) and 20 Caucasian (C) individuals were typed for the MTHFR C677T variant by the PCR/RFLP (HinfI) method. Genotype frequencies were in agreement with the Hardy-Weinberg expectations in all six populations. Allele frequency (%) of the C677T variant was 45 in NTD, 44 in M, 56 in H, 36 in T, 57 in P, 35 in C. Pairwise inter-population comparisons of allele frequency disclosed a very similar distribution between NTD and M groups (exact test, P=0.92). Among controls, differences between M and individual native groups were NS (0.06Huichol and Purepecha natives, as compared with other groups world wide.

  18. Cyclone Codes

    OpenAIRE

    Schindelhauer, Christian; Jakoby, Andreas; Köhler, Sven

    2016-01-01

    We introduce Cyclone codes which are rateless erasure resilient codes. They combine Pair codes with Luby Transform (LT) codes by computing a code symbol from a random set of data symbols using bitwise XOR and cyclic shift operations. The number of data symbols is chosen according to the Robust Soliton distribution. XOR and cyclic shift operations establish a unitary commutative ring if data symbols have a length of $p-1$ bits, for some prime number $p$. We consider the graph given by code sym...

  19. The place of 'codes' in nonlinear neurodynamics.

    Science.gov (United States)

    Freeman, Walter J

    2007-01-01

    A key problem in cognitive science is to explain the neural mechanisms of the rapid transposition between stimulus energy and abstract concept--between the specific and the generic--in both material and conceptual aspects, not between neural and psychic aspects. Three approaches by researchers to a solution in terms of neural codes are considered. Materialists seek rate and frequency codes in the interspike intervals of trains of action potentials induced by stimuli and carried by topologically organized axonal lines. Cognitivists refer to the symbol grounding problem and search for symbolic codes in firings of hierarchically organized feature-detector neurons of phonemes, lines, odorants, pressures, etc., that object-detector neurons bind into representations of probabilities of stimulus occurrence. Dynamicists seek neural correlates of stimuli and associated behaviors in spatial patterns of oscillatory fields of dendritic activity that self-organize and evolve as trajectories through high-dimensional brain state space; the codes are landscapes of chaotic attractors. Unlike codes in DNA and the periodic table, these codes have neither alphabet nor syntax. They are epistemological metaphors required by experimentalists to measure neural activity and by engineers to model brain functions. Here I review the central neural mechanisms of olfaction as a paradigm for use of codes to explain how brains create cortical activities that mediate sensation, perception, comprehension, prediction, decision, and action or inaction.

  20. Coding Partitions

    Directory of Open Access Journals (Sweden)

    Fabio Burderi

    2007-05-01

    Full Text Available Motivated by the study of decipherability conditions for codes weaker than Unique Decipherability (UD, we introduce the notion of coding partition. Such a notion generalizes that of UD code and, for codes that are not UD, allows to recover the ``unique decipherability" at the level of the classes of the partition. By tacking into account the natural order between the partitions, we define the characteristic partition of a code X as the finest coding partition of X. This leads to introduce the canonical decomposition of a code in at most one unambiguouscomponent and other (if any totally ambiguouscomponents. In the case the code is finite, we give an algorithm for computing its canonical partition. This, in particular, allows to decide whether a given partition of a finite code X is a coding partition. This last problem is then approached in the case the code is a rational set. We prove its decidability under the hypothesis that the partition contains a finite number of classes and each class is a rational set. Moreover we conjecture that the canonical partition satisfies such a hypothesis. Finally we consider also some relationships between coding partitions and varieties of codes.

  1. Coding Class

    DEFF Research Database (Denmark)

    Ejsing-Duun, Stine; Hansbøl, Mikala

    Sammenfatning af de mest væsentlige pointer fra hovedrapporten: Dokumentation og evaluering af Coding Class......Sammenfatning af de mest væsentlige pointer fra hovedrapporten: Dokumentation og evaluering af Coding Class...

  2. code {poems}

    Directory of Open Access Journals (Sweden)

    Ishac Bertran

    2012-08-01

    Full Text Available "Exploring the potential of code to communicate at the level of poetry," the code­ {poems} project solicited submissions from code­writers in response to the notion of a poem, written in a software language which is semantically valid. These selections reveal the inner workings, constitutive elements, and styles of both a particular software and its authors.

  3. Recent advances in coding theory for near error-free communications

    Science.gov (United States)

    Cheung, K.-M.; Deutsch, L. J.; Dolinar, S. J.; Mceliece, R. J.; Pollara, F.; Shahshahani, M.; Swanson, L.

    1991-01-01

    Channel and source coding theories are discussed. The following subject areas are covered: large constraint length convolutional codes (the Galileo code); decoder design (the big Viterbi decoder); Voyager's and Galileo's data compression scheme; current research in data compression for images; neural networks for soft decoding; neural networks for source decoding; finite-state codes; and fractals for data compression.

  4. Diagnosis-based and external cause-based criteria to identify adverse drug reactions in hospital ICD-coded data: application to an Australia population-based study

    Directory of Open Access Journals (Sweden)

    Wei Du

    2017-04-01

    Full Text Available Objectives: External cause International Classification of Diseases (ICD codes are commonly used to ascertain adverse drug reactions (ADRs related to hospitalisation. We quantified ascertainment of ADR-related hospitalisation using external cause codes and additional ICD-based hospital diagnosis codes. Methods: We reviewed the scientific literature to identify different ICD-based criteria for ADR-related hospitalisations, developed algorithms to capture ADRs based on candidate hospital ICD-10 diagnoses and external cause codes (Y40–Y59, and incorporated previously published causality ratings estimating the probability that a specific diagnosis was ADR related. We applied the algorithms to the NSW Admitted Patient Data Collection records of 45 and Up Study participants (2011–2013. Results: Of 493 442 hospitalisations among 267 153 study participants during 2011–2013, 18.8% (n = 92 953 had hospital diagnosis codes that were potentially ADR related; 1.1% (n = 5305 had high/very high–probability ADR-related diagnosis codes (causality ratings: A1 and A2; and 2.0% (n = 10 039 had ADR-related external cause codes. Overall, 2.2% (n = 11 082 of cases were classified as including an ADR-based hospitalisation on either external cause codes or high/very high–probability ADR-related diagnosis codes. Hence, adding high/very high–probability ADR-related hospitalisation codes to standard external cause codes alone (Y40–Y59 increased the number of hospitalisations classified as having an ADR-related diagnosis by 10.4%. Only 6.7% of cases with high-probability ADR-related mental symptoms were captured by external cause codes. Conclusion: Selective use of high-probability ADR-related hospital diagnosis codes in addition to external cause codes yielded a modest increase in hospitalised ADR incidence, which is of potential clinical significance. Clinically validated combinations of diagnosis codes could potentially further enhance capture.

  5. A neural coding scheme reproducing foraging trajectories

    Science.gov (United States)

    Gutiérrez, Esther D.; Cabrera, Juan Luis

    2015-12-01

    The movement of many animals may follow Lévy patterns. The underlying generating neuronal dynamics of such a behavior is unknown. In this paper we show that a novel discovery of multifractality in winnerless competition (WLC) systems reveals a potential encoding mechanism that is translatable into two dimensional superdiffusive Lévy movements. The validity of our approach is tested on a conductance based neuronal model showing WLC and through the extraction of Lévy flights inducing fractals from recordings of rat hippocampus during open field foraging. Further insights are gained analyzing mice motor cortex neurons and non motor cell signals. The proposed mechanism provides a plausible explanation for the neuro-dynamical fundamentals of spatial searching patterns observed in animals (including humans) and illustrates an until now unknown way to encode information in neuronal temporal series.

  6. Populism

    OpenAIRE

    Abts, Koenraad; Van Kessel, Stijn

    2015-01-01

    Populism is a concept applied to a wide range of political movements and actors across the globe. There is, at the same time, considerable confusion about the attributes and manifestation of populism, as well as its impact on democracy. This contribution identifies the defining elements of the populist ideology and discusses the varieties in which populism manifests itself, for instance as a component of certain party families. We finally discuss various normative interpretations of populism,...

  7. Use of geographic information systems technology to track critical health code violations in retail facilities available to populations of different socioeconomic status and demographics.

    Science.gov (United States)

    Darcey, Valerie L; Quinlan, Jennifer J

    2011-09-01

    Research shows that community socioeconomic status (SES) predicts, based on food service types available, whether a population has access to healthy food. It is not known, however, if a relationship exists between SES and risk for foodborne illness (FBI) at the community level. Geographic information systems (GIS) give researchers the ability to pinpoint health indicators to specific geographic locations and detect resulting environmental gradients. It has been used extensively to characterize the food environment, with respect to access to healthy foods. This research investigated the utility of GIS in determining whether community SES and/or demographics relate to access to safe food, as measured by food service critical health code violations (CHV) as a proxy for risk for FBI. Health inspection records documenting CHV for 10,859 food service facilities collected between 2005 and 2008 in Philadelphia, PA, were accessed. Using an overlay analysis through GIS, CHV were plotted over census tracts of the corresponding area. Census tracts (n = 368) were categorized into quintiles, based on poverty level. Overall, food service facilities in higher poverty areas had a greater number of facilities (with at least one CHV) and had more frequent inspections than facilities in lower poverty areas. The facilities in lower poverty areas, however, had a higher average number of CHV per inspection. Analysis of CHV rates in census tracts with high concentrations of minority populations found Hispanic facilities had more CHV than other demographics, and Hispanic and African American facilities had fewer days between inspections. This research demonstrates the potential for utilization of GIS mapping for tracking risks for FBI. Conversely, it sheds light on the subjective nature of health inspections, and indicates that underlying factors might be affecting inspection frequency and identification of CHV, such that CHV might not be a true proxy for risk for FBI.

  8. Melanin-concentrating hormone receptor 1 polymorphisms are associated with components of energy balance in the Complex Diseases in the Newfoundland Population: Environment and Genetics (CODING) study.

    Science.gov (United States)

    Fontaine-Bisson, Bénédicte; Thorburn, James; Gregory, Anne; Zhang, Hongwei; Sun, Guang

    2014-02-01

    The melanin-concentrating hormone receptor 1 (MCHR1) is a G protein-coupled receptor that regulates energy balance and body composition in animal models. Inconsistent effects of MCHR1 polymorphisms on energy homeostasis in humans may partly be attributable to environmental factors. We examined the effect of 4 single nucleotide polymorphisms (rs133073, rs133074, rs9611386, and rs882111) in the MCHR1 gene on body composition as well as energy-related lifestyle factors (diet and physical activity). We also examined the effect of gene-lifestyle interactions on body composition. A total of 1153 participants (248 men and 905 women) from the cross-sectional Complex Diseases in the Newfoundland Population: Environment and Genetics (CODING) study were genotyped by using probe-based chemistry validated assays. Diet and physical activity were estimated by using validated frequency questionnaires, and body composition was assessed by using dual-energy X-ray absorptiometry. Three polymorphisms (rs9611386, rs882111, and rs133073) were associated with differences in body-composition measurements (all P physical activity score on body-composition measurements (all P composition and interact with physiologic and energy-related lifestyle factors.

  9. Precise spatial coding is preserved along the longitudinal hippocampal axis.

    Science.gov (United States)

    Keinath, Alexander T; Wang, Melissa E; Wann, Ellen G; Yuan, Robin K; Dudman, Joshua T; Muzzio, Isabel A

    2014-12-01

    Compared with the dorsal hippocampus, relatively few studies have characterized neuronal responses in the ventral hippocampus. In particular, it is unclear whether and how cells in the ventral region represent space and/or respond to contextual changes. We recorded from dorsal and ventral CA1 neurons in freely moving mice exposed to manipulations of visuospatial and olfactory contexts. We found that ventral cells respond to alterations of the visuospatial environment such as exposure to novel local cues, cue rotations, and contextual expansion in similar ways to dorsal cells, with the exception of cue rotations. Furthermore, we found that ventral cells responded to odors much more strongly than dorsal cells, particularly to odors of high valence. Similar to earlier studies recording from the ventral hippocampus in CA3, we also found increased scaling of place cell field size along the longitudinal hippocampal axis. Although the increase in place field size observed toward the ventral pole has previously been taken to suggest a decrease in spatial information coded by ventral place cells, we hypothesized that a change in spatial scaling could instead signal a shift in representational coding that preserves the resolution of spatial information. To explore this possibility, we examined population activity using principal component analysis (PCA) and neural location reconstruction techniques. Our results suggest that ventral populations encode a distributed representation of space, and that the resolution of spatial information at the population level is comparable to that of dorsal populations of similar size. Finally, through the use of neural network modeling, we suggest that the redundancy in spatial representation along the longitudinal hippocampal axis may allow the hippocampus to overcome the conflict between memory interference and generalization inherent in neural network memory. Our results indicate that ventral population activity is well suited for

  10. Sharing code.

    Science.gov (United States)

    Kubilius, Jonas

    2014-01-01

    Sharing code is becoming increasingly important in the wake of Open Science. In this review I describe and compare two popular code-sharing utilities, GitHub and Open Science Framework (OSF). GitHub is a mature, industry-standard tool but lacks focus towards researchers. In comparison, OSF offers a one-stop solution for researchers but a lot of functionality is still under development. I conclude by listing alternative lesser-known tools for code and materials sharing.

  11. Neural tuning for face wholes and parts in human fusiform gyrus revealed by FMRI adaptation.

    Science.gov (United States)

    Harris, Alison; Aguirre, Geoffrey Karl

    2010-07-01

    Although the right fusiform face area (FFA) is often linked to holistic processing, new data suggest this region also encodes part-based face representations. We examined this question by assessing the metric of neural similarity for faces using a continuous carryover functional MRI (fMRI) design. Using faces varying along dimensions of eye and mouth identity, we tested whether these axes are coded independently by separate part-tuned neural populations or conjointly by a single population of holistically tuned neurons. Consistent with prior results, we found a subadditive adaptation response in the right FFA, as predicted for holistic processing. However, when holistic processing was disrupted by misaligning the halves of the face, the right FFA continued to show significant adaptation, but in an additive pattern indicative of part-based neural tuning. Thus this region seems to contain neural populations capable of representing both individual parts and their integration into a face gestalt. A third experiment, which varied the asymmetry of changes in the eye and mouth identity dimensions, also showed part-based tuning from the right FFA. In contrast to the right FFA, the left FFA consistently showed a part-based pattern of neural tuning across all experiments. Together, these data support the existence of both part-based and holistic neural tuning within the right FFA, further suggesting that such tuning is surprisingly flexible and dynamic.

  12. Neural network technologies

    Science.gov (United States)

    Villarreal, James A.

    1991-01-01

    A whole new arena of computer technologies is now beginning to form. Still in its infancy, neural network technology is a biologically inspired methodology which draws on nature's own cognitive processes. The Software Technology Branch has provided a software tool, Neural Execution and Training System (NETS), to industry, government, and academia to facilitate and expedite the use of this technology. NETS is written in the C programming language and can be executed on a variety of machines. Once a network has been debugged, NETS can produce a C source code which implements the network. This code can then be incorporated into other software systems. Described here are various software projects currently under development with NETS and the anticipated future enhancements to NETS and the technology.

  13. Analog Coding.

    Science.gov (United States)

    CODING, ANALOG SYSTEMS), INFORMATION THEORY, DATA TRANSMISSION SYSTEMS , TRANSMITTER RECEIVERS, WHITE NOISE, PROBABILITY, ERRORS, PROBABILITY DENSITY FUNCTIONS, DIFFERENTIAL EQUATIONS, SET THEORY, COMPUTER PROGRAMS

  14. Evolution of naturally occurring 5'non-coding region variants of Hepatitis C virus in human populations of the South American region

    Directory of Open Access Journals (Sweden)

    García-Aguirre Laura

    2007-08-01

    Full Text Available Abstract Background Hepatitis C virus (HCV has been the subject of intense research and clinical investigation as its major role in human disease has emerged. Previous and recent studies have suggested a diversification of type 1 HCV in the South American region. The degree of genetic variation among HCV strains circulating in Bolivia and Colombia is currently unknown. In order to get insight into these matters, we performed a phylogenetic analysis of HCV 5' non-coding region (5'NCR sequences from strains isolated in Bolivia, Colombia and Uruguay, as well as available comparable sequences of HCV strains isolated in South America. Methods Phylogenetic tree analysis was performed using the neighbor-joining method under a matrix of genetic distances established under the Kimura-two parameter model. Signature pattern analysis, which identifies particular sites in nucleic acid alignments of variable sequences that are distinctly representative relative to a background set, was performed using the method of Korber & Myers, as implemented in the VESPA program. Prediction of RNA secondary structures was done by the method of Zuker & Turner, as implemented in the mfold program. Results Phylogenetic tree analysis of HCV strains isolated in the South American region revealed the presence of a distinct genetic lineage inside genotype 1. Signature pattern analysis revealed that the presence of this lineage is consistent with the presence of a sequence signature in the 5'NCR of HCV strains isolated in South America. Comparisons of these results with the ones found for Europe or North America revealed that this sequence signature is characteristic of the South American region. Conclusion Phylogentic analysis revealed the presence of a sequence signature in the 5'NCR of type 1 HCV strains isolated in South America. This signature is frequent enough in type 1 HCV populations circulating South America to be detected in a phylogenetic tree analysis as a distinct

  15. Divergence coding for convolutional codes

    Directory of Open Access Journals (Sweden)

    Valery Zolotarev

    2017-01-01

    Full Text Available In the paper we propose a new coding/decoding on the divergence principle. A new divergent multithreshold decoder (MTD for convolutional self-orthogonal codes contains two threshold elements. The second threshold element decodes the code with the code distance one greater than for the first threshold element. Errorcorrecting possibility of the new MTD modification have been higher than traditional MTD. Simulation results show that the performance of the divergent schemes allow to approach area of its effective work to channel capacity approximately on 0,5 dB. Note that we include the enough effective Viterbi decoder instead of the first threshold element, the divergence principle can reach more. Index Terms — error-correcting coding, convolutional code, decoder, multithreshold decoder, Viterbi algorithm.

  16. Speaking Code

    DEFF Research Database (Denmark)

    Cox, Geoff

    Speaking Code begins by invoking the “Hello World” convention used by programmers when learning a new language, helping to establish the interplay of text and code that runs through the book. Interweaving the voice of critical writing from the humanities with the tradition of computing and software...... development, Speaking Code unfolds an argument to undermine the distinctions between criticism and practice, and to emphasize the aesthetic and political aspects of software studies. Not reducible to its functional aspects, program code mirrors the instability inherent in the relationship of speech......; alternatives to mainstream development, from performances of the live-coding scene to the organizational forms of commons-based peer production; the democratic promise of social media and their paradoxical role in suppressing political expression; and the market’s emptying out of possibilities for free...

  17. Theory of mind: a neural prediction problem.

    Science.gov (United States)

    Koster-Hale, Jorie; Saxe, Rebecca

    2013-09-04

    Predictive coding posits that neural systems make forward-looking predictions about incoming information. Neural signals contain information not about the currently perceived stimulus, but about the difference between the observed and the predicted stimulus. We propose to extend the predictive coding framework from high-level sensory processing to the more abstract domain of theory of mind; that is, to inferences about others' goals, thoughts, and personalities. We review evidence that, across brain regions, neural responses to depictions of human behavior, from biological motion to trait descriptions, exhibit a key signature of predictive coding: reduced activity to predictable stimuli. We discuss how future experiments could distinguish predictive coding from alternative explanations of this response profile. This framework may provide an important new window on the neural computations underlying theory of mind. Copyright © 2013 Elsevier Inc. All rights reserved.

  18. Neural Representation of Concurrent Vowels in Macaque Primary Auditory Cortex.

    Science.gov (United States)

    Fishman, Yonatan I; Micheyl, Christophe; Steinschneider, Mitchell

    2016-01-01

    Successful speech perception in real-world environments requires that the auditory system segregate competing voices that overlap in frequency and time into separate streams. Vowels are major constituents of speech and are comprised of frequencies (harmonics) that are integer multiples of a common fundamental frequency (F0). The pitch and identity of a vowel are determined by its F0 and spectral envelope (formant structure), respectively. When two spectrally overlapping vowels differing in F0 are presented concurrently, they can be readily perceived as two separate "auditory objects" with pitches at their respective F0s. A difference in pitch between two simultaneous vowels provides a powerful cue for their segregation, which in turn, facilitates their individual identification. The neural mechanisms underlying the segregation of concurrent vowels based on pitch differences are poorly understood. Here, we examine neural population responses in macaque primary auditory cortex (A1) to single and double concurrent vowels (/a/ and /i/) that differ in F0 such that they are heard as two separate auditory objects with distinct pitches. We find that neural population responses in A1 can resolve, via a rate-place code, lower harmonics of both single and double concurrent vowels. Furthermore, we show that the formant structures, and hence the identities, of single vowels can be reliably recovered from the neural representation of double concurrent vowels. We conclude that A1 contains sufficient spectral information to enable concurrent vowel segregation and identification by downstream cortical areas.

  19. A comparative analysis of neural taste processing in animals

    Science.gov (United States)

    de Brito Sanchez, Gabriela; Giurfa, Martin

    2011-01-01

    Understanding taste processing in the nervous system is a fundamental challenge of modern neuroscience. Recent research on the neural bases of taste coding in invertebrates and vertebrates allows discussion of whether labelled-line or across-fibre pattern encoding applies to taste perception. While the former posits that each gustatory receptor responds to one stimulus or a very limited range of stimuli and sends a direct ‘line’ to the central nervous system to communicate taste information, the latter postulates that each gustatory receptor responds to a wider range of stimuli so that the entire population of taste-responsive neurons participates in the taste code. Tastes are represented in the brain of the fruitfly and of the rat by spatial patterns of neural activity containing both distinct and overlapping regions, which are in accord with both labelled-line and across-fibre pattern processing of taste, respectively. In both animal models, taste representations seem to relate to the hedonic value of the tastant (e.g. palatable versus non-palatable). Thus, although the labelled-line hypothesis can account for peripheral taste processing, central processing remains either unknown or differs from a pure labelled-line coding. The essential task for a neuroscience of taste is, therefore, to determine the connectivity of taste-processing circuits in central nervous systems. Such connectivity may determine coding strategies that differ significantly from both the labelled-line and the across-fibre pattern models. PMID:21690133

  20. A neural model of retrospective attention in visual working memory.

    Science.gov (United States)

    Bays, Paul M; Taylor, Robert

    2018-02-01

    An informative cue that directs attention to one of several items in working memory improves subsequent recall of that item. Here we examine the mechanism of this retro-cue effect using a model of short-term memory based on neural population coding. Our model describes recalled feature values as the output of an optimal decoding of spikes generated by a tuned population of neurons. This neural model provides a better account of human recall data than an influential model that assumes errors can be described as a mixture of normally distributed noise and random guesses. The retro-cue benefit is revealed to be consistent with a higher firing rate of the population encoding the cued versus uncued items, with no difference in tuning specificity. Additionally, a retro-cued item is less likely to be swapped with another item in memory, an effect that can also be explained by greater activity of the underlying population. These results provide a parsimonious account of the effects of retrospective attention on recall and demonstrate a principled method for investigating neural representations with behavioral tasks. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  1. Coding Labour

    Directory of Open Access Journals (Sweden)

    Anthony McCosker

    2014-03-01

    Full Text Available As well as introducing the Coding Labour section, the authors explore the diffusion of code across the material contexts of everyday life, through the objects and tools of mediation, the systems and practices of cultural production and organisational management, and in the material conditions of labour. Taking code beyond computation and software, their specific focus is on the increasingly familiar connections between code and labour with a focus on the codification and modulation of affect through technologies and practices of management within the contemporary work organisation. In the grey literature of spreadsheets, minutes, workload models, email and the like they identify a violence of forms through which workplace affect, in its constant flux of crisis and ‘prodromal’ modes, is regulated and governed.

  2. Coding labour

    National Research Council Canada - National Science Library

    McCosker, Anthony; Milne, Esther

    2014-01-01

    ... software. Code encompasses the laws that regulate human affairs and the operation of capital, behavioural mores and accepted ways of acting, but it also defines the building blocks of life as DNA...

  3. Fast dynamics of odor rate coding in the insect antennal lobe

    CERN Document Server

    Nawrot, Martin Paul; Farkhooi, Farzad; Menzel, Randolf

    2011-01-01

    Insects identify and evaluate behaviorally relevant odorants in complex natural scenes where odor concentrations and mixture composition can change rapidly. In the honeybee, a combinatorial code of activated and inactivated projection neurons (PNs) develops rapidly within tens of milliseconds at the first level of neural integration, the antennal lobe (AL). The phasic-tonic stimulus-response dynamics observed in the neural population code and in the firing rate profiles of single neurons is faithfully captured by two alternative models which rely either on short-term synaptic depression, or on spike frequency adaptation. Both mechanisms work independently and possibly in parallel to lateral inhibition. Short response latencies in local interneurons indicate that local processing within the AL network relies on fast lateral inhibition that can suppress effectively and specifically odor responses in single PNs. Reviewing recent findings obtained in different insect species, we conclude that the insect olfactory...

  4. The effect of fever, febrile illnesses, and heat exposures on the risk of neural tube defects in a Texas-Mexico border population.

    Science.gov (United States)

    Suarez, Lucina; Felkner, Marilyn; Hendricks, Kate

    2004-10-01

    Hyperthermia produces neural tube defects (NTDs) in a variety of animal species. Elevated maternal body temperatures may also place the developing human embryo at risk. We examined the relation between maternal hyperthermia and the development of NTDs in a high-risk Mexican-American population. Case-women were Mexican-American women with NTD-affected pregnancies who resided and delivered in any of the 14 Texas counties bordering Mexico, during 1995-2000. Control-women were randomly selected from study area residents delivering normal live births, frequency-matched to cases by hospital and year. Information on maternal fevers, febrile illnesses, exposures to heat generated from external sources, and hyperthermia-inducing activities was gathered through in-person interviews, conducted about six weeks postpartum. The risk effect (OR) associated with maternal fever in the first trimester, compared to no fever, was 2.9 (95% CI, 1.5-5.7). Women taking fever-reducing medications showed a lower risk effect (OR, 2.4; 95% CI, 1.0-5.6) than those who did not (OR, 3.8; 95% CI, 1.4-10.9). First-trimester maternal exposures to heat devices such as hot tubs, saunas, or electric blankets were associated with an OR of 3.6 (95% CI, 1.1-15.9). Small insignificant effects were observed for activities such as cooking in a hot kitchen (OR, 1.6; 95% CI, 1.0-2.6) and working or exercising in the sun (OR, 1.4; 95% CI, 0.9-2.2). Maternal hyperthermia increases the risk for NTD-affected offspring. Women intending to become pregnant should avoid intense heat exposures, carefully monitor and manage their febrile illnesses, and routinely consume folic acid supplements. (c) 2004 Wiley-Liss, Inc.

  5. Effects of lower body quadrant neural mobilization in healthy and low back pain populations: A systematic review and meta-analysis.

    Science.gov (United States)

    Neto, Tiago; Freitas, Sandro R; Marques, Marta; Gomes, Luis; Andrade, Ricardo; Oliveira, Raúl

    2017-02-01

    Neural mobilization (NM) is widely used to assess and treat several neuromuscular disorders. However, information regarding the NM effects targeting the lower body quadrant is scarce. To determine the effects of NM techniques targeting the lower body quadrant in healthy and low back pain (LBP) populations. Systematic review with meta-analysis. Randomized controlled trials were included if any form of NM was applied to the lower body quadrant. Pain, disability, and lower limb flexibility were the main outcomes. PEDro scale was used to assess methodological quality. Forty-five studies were selected for full-text analysis, and ten were included in the meta-analysis, involving 502 participants. Overall, studies presented fair to good quality, with a mean PEDro score of 6.3 (from 4 to 8). Five studies used healthy participants, and five targeted people with LBP. A moderate effect size (g = 0.73, 95% CI: 0.48-0.98) was determined, favoring the use of NM to increase flexibility in healthy adults. Larger effect sizes were found for the effect of NM in pain reduction (g = 0.82, 95% CI 0.56-1.08) and disability improvement (g = 1.59, 95% CI: 1.14-2.03), in people with LBP. Evidence suggests that there are positive effects from the application of NM to the lower body quadrant. Specifically, NM shows moderate effects on flexibility in healthy participants, and large effects on pain and disability in people with LBP. Nevertheless, more studies with high methodological quality are necessary to support these conclusions. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. Prevalence of neural tube defects in a rural area of north india from 2001 to 2014: A population-based survey.

    Science.gov (United States)

    Kant, Shashi; Malhotra, Sumit; Singh, Arvind Kumar; Haldar, Partha; Kaur, Ravneet; Misra, Puneet; Gupta, Neerja

    2017-02-15

    Neural tube defects (NTDs) are one of the commonest birth defects. There was paucity of community-based data on occurrence of NTDs in India, especially from rural parts of the country. Against this background, the current study was carried out with main objectives to determine the prevalence of NTDs and its specific types (anencephaly, spina bifida and encephalocele) in a rural community setting over the time period 2001 to 2014. This was a community-based cross-sectional study carried out in 28 villages of Ballabgarh Tehsil of Faridabad district in north India (population ∼ 96,000). A household survey was undertaken by trained multi-purpose workers who enquired ever-married women about history of conception with outcome as NTD during the study period. The probable case of NTD was determined using a colored pictorial card with photographs of different types of NTDs. These cases were confirmed by doctors. A total of 26,946 live births occurred during the years 2001 to 2014. A total of 140 confirmed cases of NTDs were identified. The live birth prevalence of NTDs was 24.1 per 10,000 live births (95% confidence interval, 18.8-30.6). The birth prevalence of NTDs for the years 2008 to 2014 was 50.8 (95% confidence interval, 39.9-63.8) per 10,000 live and stillbirths. The most common type of NTD was found to be spina bifida followed by anencephaly and encephalocele. We found high prevalence of NTDs in rural community settings from north India for years 2001 to 2014.Birth Defects Research 109:203-210, 2017.© 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  7. Population-based case-control study of the association between weather-related extreme heat events and neural tube defects.

    Science.gov (United States)

    Soim, Aida; Lin, Shao; Sheridan, Scott C; Hwang, Syni-An; Hsu, Wan-Hsiang; Luben, Thomas J; Shaw, Gary M; Feldkamp, Marcia L; Romitti, Paul A; Reefhuis, Jennita; Langlois, Peter H; Browne, Marilyn L

    2017-11-01

    Elevated body core temperature has been shown to have teratogenic effects in animal studies. Our study evaluated the association between weather-related extreme heat events (EHEs) in the summer season and neural tube defects (NTDs), and further investigated whether pregnant women with a high pregestational body mass index (BMI) have a greater risk of having a child with NTDs associated with exposure to EHE than women with a normal BMI. We conducted a population-based case-control study among mothers of infants with NTDs and mothers of infants without major birth defects, who participated in the National Birth Defects Prevention Study and had at least 1 day of the third or fourth week postconception during summer months. EHEs were defined using the 95th and the 90th percentiles of the daily maximum universal apparent temperature. Adjusted odds ratios and 95% confidence intervals were calculated using unconditional logistic regression models with Firth's penalized likelihood method while controlling for other known risk factors. Overall, we did not observe a significant association between EHEs and NTDs. At the climate region level, consistently elevated but not statistically significant estimates were observed for at least 2 consecutive days with daily universal apparent maximum temperature above the 95th percentile of the UATmax distribution for the season, year, and weather monitoring station in New York (Northeast), North Carolina and Georgia (Southeast), and Iowa (Upper Midwest). No effect modification by BMI was observed. EHEs occurring during the relevant developmental window of embryogenesis do not appear to appreciably affect the risk of NTDs. Future studies should refine exposure assessment, and more completely account for maternal activities that may modify the effects of weather exposure. Birth Defects Research 109:1482-1493, 2017.© 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  8. Multiplexed coding in the human basal ganglia

    Science.gov (United States)

    Andres, D. S.; Cerquetti, D.; Merello, M.

    2016-04-01

    A classic controversy in neuroscience is whether information carried by spike trains is encoded by a time averaged measure (e.g. a rate code), or by complex time patterns (i.e. a time code). Here we apply a tool to quantitatively analyze the neural code. We make use of an algorithm based on the calculation of the temporal structure function, which permits to distinguish what scales of a signal are dominated by a complex temporal organization or a randomly generated process. In terms of the neural code, this kind of analysis makes it possible to detect temporal scales at which a time patterns coding scheme or alternatively a rate code are present. Additionally, finding the temporal scale at which the correlation between interspike intervals fades, the length of the basic information unit of the code can be established, and hence the word length of the code can be found. We apply this algorithm to neuronal recordings obtained from the Globus Pallidus pars interna from a human patient with Parkinson’s disease, and show that a time pattern coding and a rate coding scheme co-exist at different temporal scales, offering a new example of multiplexed neuronal coding.

  9. Speech coding

    Energy Technology Data Exchange (ETDEWEB)

    Ravishankar, C., Hughes Network Systems, Germantown, MD

    1998-05-08

    Speech is the predominant means of communication between human beings and since the invention of the telephone by Alexander Graham Bell in 1876, speech services have remained to be the core service in almost all telecommunication systems. Original analog methods of telephony had the disadvantage of speech signal getting corrupted by noise, cross-talk and distortion Long haul transmissions which use repeaters to compensate for the loss in signal strength on transmission links also increase the associated noise and distortion. On the other hand digital transmission is relatively immune to noise, cross-talk and distortion primarily because of the capability to faithfully regenerate digital signal at each repeater purely based on a binary decision. Hence end-to-end performance of the digital link essentially becomes independent of the length and operating frequency bands of the link Hence from a transmission point of view digital transmission has been the preferred approach due to its higher immunity to noise. The need to carry digital speech became extremely important from a service provision point of view as well. Modem requirements have introduced the need for robust, flexible and secure services that can carry a multitude of signal types (such as voice, data and video) without a fundamental change in infrastructure. Such a requirement could not have been easily met without the advent of digital transmission systems, thereby requiring speech to be coded digitally. The term Speech Coding is often referred to techniques that represent or code speech signals either directly as a waveform or as a set of parameters by analyzing the speech signal. In either case, the codes are transmitted to the distant end where speech is reconstructed or synthesized using the received set of codes. A more generic term that is applicable to these techniques that is often interchangeably used with speech coding is the term voice coding. This term is more generic in the sense that the

  10. Prevention of neural tube defects by the fortification of flour with folic acid: a population-based retrospective study in Brazil.

    Science.gov (United States)

    Santos, Leonor Maria Pacheco; Lecca, Roberto Carlos Reyes; Cortez-Escalante, Juan Jose; Sanchez, Mauro Niskier; Rodrigues, Humberto Gabriel

    2016-01-01

    To determine if the fortification of wheat and maize flours with iron and folic acid - which became mandatory in Brazil from June 2004 - is effective in the prevention of neural tube defects. Using data from national information systems on births in central, south-eastern and southern Brazil, we determined the prevalence of neural tube defects among live births and stillbirths in a pre-fortification period - i.e. 2001-2004 - and in a post-fortification period - i.e. 2005-2014. We distinguished between anencephaly, encephalocele, meningocele, myelomeningocele and other forms of spina bifida. There were 8554 neural tube defects for 17,925,729 live births notified between 2001 and 2014. For the same period, 2673 neural tube defects were reported for 194,858 stillbirths. The overall prevalence of neural tube defects fell from 0.79 per 1000 pre-fortification to 0.55 per 1000 post-fortification (prevalence ratio, PR: 1.43; 95% confidence interval, CI: 1.38-1.50). For stillbirths, prevalence fell from 17.74 per 1000 stillbirths pre-fortification to 11.70 per 1000 stillbirths post-fortification. The corresponding values among live births were 0.57 and 0.44, respectively. The introduction of the mandatory fortification of flour with iron and folic acid in Brazil was followed by a significant reduction in the prevalence of neural tube defects in our study area.

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

    Science.gov (United States)

    Sokoloski, Sacha

    2017-09-01

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

  12. Diminished behavioral and neural sensitivity to sound modulation is associated with moderate developmental hearing loss.

    Directory of Open Access Journals (Sweden)

    Merri J Rosen

    Full Text Available The acoustic rearing environment can alter central auditory coding properties, yet altered neural coding is seldom linked with specific deficits to adult perceptual skills. To test whether developmental hearing loss resulted in comparable changes to perception and sensory coding, we examined behavioral and neural detection thresholds for sinusoidally amplitude modulated (sAM stimuli. Behavioral sAM detection thresholds for slow (5 Hz modulations were significantly worse for animals reared with bilateral conductive hearing loss (CHL, as compared to controls. This difference could not be attributed to hearing thresholds, proficiency at the task, or proxies for attention. Detection thresholds across the groups did not differ for fast (100 Hz modulations, a result paralleling that seen in humans. Neural responses to sAM stimuli were recorded in single auditory cortex neurons from separate groups of awake animals. Neurometric analyses indicated equivalent thresholds for the most sensitive neurons, but a significantly poorer detection threshold for slow modulations across the population of CHL neurons as compared to controls. The magnitude of the neural deficit matched that of the behavioral differences, suggesting that a reduction of sensory information can account for limitations to perceptual skills.

  13. An Application Specific Instruction Set Processor (ASIP) for Adaptive Filters in Neural Prosthetics.

    Science.gov (United States)

    Xin, Yao; Li, Will X Y; Zhang, Zhaorui; Cheung, Ray C C; Song, Dong; Berger, Theodore W

    2015-01-01

    Neural coding is an essential process for neuroprosthetic design, in which adaptive filters have been widely utilized. In a practical application, it is needed to switch between different filters, which could be based on continuous observations or point process, when the neuron models, conditions, or system requirements have changed. As candidates of coding chip for neural prostheses, low-power general purpose processors are not computationally efficient especially for large scale neural population coding. Application specific integrated circuits (ASICs) do not have flexibility to switch between different adaptive filters while the cost for design and fabrication is formidable. In this research work, we explore an application specific instruction set processor (ASIP) for adaptive filters in neural decoding activity. The proposed architecture focuses on efficient computation for the most time-consuming matrix/vector operations among commonly used adaptive filters, being able to provide both flexibility and throughput. Evaluation and implementation results are provided to demonstrate that the proposed ASIP design is area-efficient while being competitive to commercial CPUs in computational performance.

  14. Visual Coding of Human Bodies: Perceptual Aftereffects Reveal Norm-Based, Opponent Coding of Body Identity

    Science.gov (United States)

    Rhodes, Gillian; Jeffery, Linda; Boeing, Alexandra; Calder, Andrew J.

    2013-01-01

    Despite the discovery of body-selective neural areas in occipitotemporal cortex, little is known about how bodies are visually coded. We used perceptual adaptation to determine how body identity is coded. Brief exposure to a body (e.g., anti-Rose) biased perception toward an identity with opposite properties (Rose). Moreover, the size of this…

  15. Evolving Spiking Neural Networks for Control of Artificial Creatures

    Directory of Open Access Journals (Sweden)

    Arash Ahmadi

    2013-10-01

    Full Text Available To understand and analysis behavior of complicated and intelligent organisms, scientists apply bio-inspired concepts including evolution and learning to mathematical models and analyses. Researchers utilize these perceptions in different applications, searching for improved methods andapproaches for modern computational systems. This paper presents a genetic algorithm based evolution framework in which Spiking Neural Network (SNN of artificial creatures are evolved for higher chance of survival in a virtual environment. The artificial creatures are composed ofrandomly connected Izhikevich spiking reservoir neural networks using population activity rate coding. Inspired by biological neurons, the neuronal connections are considered with different axonal conduction delays. Simulations results prove that the evolutionary algorithm has thecapability to find or synthesis artificial creatures which can survive in the environment successfully.

  16. Neural dynamics of the cognitive map in the hippocampus.

    Science.gov (United States)

    Wagatsuma, Hiroaki; Yamaguchi, Yoko

    2007-06-01

    The rodent hippocampus has been thought to represent the spatial environment as a cognitive map. In the classical theory, the cognitive map has been explained as a consequence of the fact that different spatial regions are assigned to different cell populations in the framework of rate coding. Recently, the relation between place cell firing and local field oscillation theta in terms of theta phase precession was experimentally discovered and suggested as a temporal coding mechanism leading to memory formation of behavioral sequences accompanied with asymmetric Hebbian plasticity. The cognitive map theory is apparently outside of the sequence memory view. Therefore, theoretical analysis is necessary to consider the biological neural dynamics for the sequence encoding of the memory of behavioral sequences, providing the cognitive map formation. In this article, we summarize the theoretical neural dynamics of the real-time sequence encoding by theta phase precession, called theta phase coding, and review a series of theoretical models with the theta phase coding that we previously reported. With respect to memory encoding functions, instantaneous memory formation of one-time experience was first demonstrated, and then the ability of integration of memories of behavioral sequences into a network of the cognitive map was shown. In terms of memory retrieval functions, theta phase coding enables the hippocampus to represent the spatial location in the current behavioral context even with ambiguous sensory input when multiple sequences were coded. Finally, for utilization, retrieved temporal sequences in the hippocampus can be available for action selection, through the process of reverting theta rhythm-dependent activities to information in the behavioral time scale. This theoretical approach allows us to investigate how the behavioral sequences are encoded, updated, retrieved and used in the hippocampus, as the real-time interaction with the external environment. It may

  17. The Aster code; Code Aster

    Energy Technology Data Exchange (ETDEWEB)

    Delbecq, J.M

    1999-07-01

    The Aster code is a 2D or 3D finite-element calculation code for structures developed by the R and D direction of Electricite de France (EdF). This dossier presents a complete overview of the characteristics and uses of the Aster code: introduction of version 4; the context of Aster (organisation of the code development, versions, systems and interfaces, development tools, quality assurance, independent validation); static mechanics (linear thermo-elasticity, Euler buckling, cables, Zarka-Casier method); non-linear mechanics (materials behaviour, big deformations, specific loads, unloading and loss of load proportionality indicators, global algorithm, contact and friction); rupture mechanics (G energy restitution level, restitution level in thermo-elasto-plasticity, 3D local energy restitution level, KI and KII stress intensity factors, calculation of limit loads for structures), specific treatments (fatigue, rupture, wear, error estimation); meshes and models (mesh generation, modeling, loads and boundary conditions, links between different modeling processes, resolution of linear systems, display of results etc..); vibration mechanics (modal and harmonic analysis, dynamics with shocks, direct transient dynamics, seismic analysis and aleatory dynamics, non-linear dynamics, dynamical sub-structuring); fluid-structure interactions (internal acoustics, mass, rigidity and damping); linear and non-linear thermal analysis; steels and metal industry (structure transformations); coupled problems (internal chaining, internal thermo-hydro-mechanical coupling, chaining with other codes); products and services. (J.S.)

  18. Network Coding

    Indian Academy of Sciences (India)

    Network coding is a technique to increase the amount of information °ow in a network by mak- ing the key observation that information °ow is fundamentally different from commodity °ow. Whereas, under traditional methods of opera- tion of data networks, intermediate nodes are restricted to simply forwarding their incoming.

  19. Coding Class

    DEFF Research Database (Denmark)

    Ejsing-Duun, Stine; Hansbøl, Mikala

    Denne rapport rummer evaluering og dokumentation af Coding Class projektet1. Coding Class projektet blev igangsat i skoleåret 2016/2017 af IT-Branchen i samarbejde med en række medlemsvirksomheder, Københavns kommune, Vejle Kommune, Styrelsen for IT- og Læring (STIL) og den frivillige forening...... Coding Pirates2. Rapporten er forfattet af Docent i digitale læringsressourcer og forskningskoordinator for forsknings- og udviklingsmiljøet Digitalisering i Skolen (DiS), Mikala Hansbøl, fra Institut for Skole og Læring ved Professionshøjskolen Metropol; og Lektor i læringsteknologi, interaktionsdesign......, design tænkning og design-pædagogik, Stine Ejsing-Duun fra Forskningslab: It og Læringsdesign (ILD-LAB) ved Institut for kommunikation og psykologi, Aalborg Universitet i København. Vi har fulgt og gennemført evaluering og dokumentation af Coding Class projektet i perioden november 2016 til maj 2017...

  20. Network Coding

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 15; Issue 7. Network Coding. K V Rashmi Nihar B Shah P Vijay Kumar. General Article Volume 15 Issue 7 July 2010 pp 604-621. Fulltext. Click here to view fulltext PDF. Permanent link: http://www.ias.ac.in/article/fulltext/reso/015/07/0604-0621. Keywords.

  1. Expander Codes

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 10; Issue 1. Expander Codes - The Sipser–Spielman Construction. Priti Shankar. General Article Volume 10 ... Author Affiliations. Priti Shankar1. Department of Computer Science and Automation, Indian Institute of Science Bangalore 560 012, India.

  2. Collection of legislative and regulatory arrangements relative to radiation protection. Part 1: laws and decrees of the Public Health Code and Labour Code concerning the protection of populations, patients and workers against the risks of ionizing radiations; Recueil des dispositions legislatives et reglementaires relatives a la radioprotection. Partie 1: lois et decrets du code de la sante publique et du code du travail concernant la protection de la population, des patients et des travailleurs contre les dangers des rayonnements ionisants

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2007-05-15

    This collection concerns on one hand the protection of the population and on the other hand the protection of the workers against ionizing radiations. As regards the protection of the populations, there is a quality control of waters, a control of the medical devices for the protection of patients. For the protection of the workers it is the employment law which serves as reference. (N.C.)

  3. FLYCHK Collisional-Radiative Code

    Science.gov (United States)

    SRD 160 FLYCHK Collisional-Radiative Code (Web, free access)   FLYCHK provides a capability to generate atomic level populations and charge state distributions for low-Z to mid-Z elements under NLTE conditions.

  4. Efficiency of a model human image code

    Science.gov (United States)

    Watson, Andrew B.

    1987-01-01

    Hypothetical schemes for neural representation of visual information can be expressed as explicit image codes. Here, a code modeled on the simple cells of the primate striate cortex is explored. The Cortex transform maps a digital image into a set of subimages (layers) that are bandpass in spatial frequency and orientation. The layers are sampled so as to minimize the number of samples and still avoid aliasing. Samples are quantized in a manner that exploits the bandpass contrast-masking properties of human vision. The entropy of the samples is computed to provide a lower bound on the code size. Finally, the image is reconstructed from the code. Psychophysical methods are derived for comparing the original and reconstructed images to evaluate the sufficiency of the code. When each resolution is coded at the threshold for detection artifacts, the image-code size is about 1 bit/pixel.

  5. Social behaviour shapes hypothalamic neural ensemble representations of conspecific sex

    Science.gov (United States)

    Remedios, Ryan; Kennedy, Ann; Zelikowsky, Moriel; Grewe, Benjamin F.; Schnitzer, Mark J.; Anderson, David J.

    2017-10-01

    All animals possess a repertoire of innate (or instinctive) behaviours, which can be performed without training. Whether such behaviours are mediated by anatomically distinct and/or genetically specified neural pathways remains unknown. Here we report that neural representations within the mouse hypothalamus, that underlie innate social behaviours, are shaped by social experience. Oestrogen receptor 1-expressing (Esr1+) neurons in the ventrolateral subdivision of the ventromedial hypothalamus (VMHvl) control mating and fighting in rodents. We used microendoscopy to image Esr1+ neuronal activity in the VMHvl of male mice engaged in these social behaviours. In sexually and socially experienced adult males, divergent and characteristic neural ensembles represented male versus female conspecifics. However, in inexperienced adult males, male and female intruders activated overlapping neuronal populations. Sex-specific neuronal ensembles gradually separated as the mice acquired social and sexual experience. In mice permitted to investigate but not to mount or attack conspecifics, ensemble divergence did not occur. However, 30 minutes of sexual experience with a female was sufficient to promote the separation of male and female ensembles and to induce an attack response 24 h later. These observations uncover an unexpected social experience-dependent component to the formation of hypothalamic neural assemblies controlling innate social behaviours. More generally, they reveal plasticity and dynamic coding in an evolutionarily ancient deep subcortical structure that is traditionally viewed as a ‘hard-wired’ system.

  6. Polar Codes

    Science.gov (United States)

    2014-12-01

    added by the decoder is K/ρ+Td. By the last assumption, Td and Te are both ≤ K/ρ, so the total latency added is between 2K/ρ and 4K /ρ. For example...better resolution near the decision point. Reference [12] showed that in decoding a (1024, 512) polar code, using 6-bit LLRs resulted in per- formance

  7. 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.

  8. A novel population of CD4+CD56+ myelin-reactive T cells lyses target cells expressing CD56/neural cell adhesion molecule

    NARCIS (Netherlands)

    Vergelli, M.; Le, H.; Noort, J.M. van; Dhib-Jalbut, S.; McFarland, H.; Martin, R.

    1996-01-01

    CD56 is a member of the neural cell adhesion molecule family expressed on cells of the central nervous system and also on NK cells. Previous studies suggest the involvement of CD56 in effector-to-target cell conjugation mediated by NK cells. It was shown recently that CD56 is also expressed by

  9. The predictive value of ICD-10 diagnostic coding used to assess Charlson comorbidity index conditions in the population-based Danish National Registry of Patients

    Directory of Open Access Journals (Sweden)

    Lash Timothy L

    2011-05-01

    Full Text Available Abstract Background The Charlson comorbidity index is often used to control for confounding in research based on medical databases. There are few studies of the accuracy of the codes obtained from these databases. We examined the positive predictive value (PPV of the ICD-10 diagnostic coding in the Danish National Registry of Patients (NRP for the 19 Charlson conditions. Methods Among all hospitalizations in Northern Denmark between 1 January 1998 and 31 December 2007 with a first-listed diagnosis of a Charlson condition in the NRP, we selected 50 hospital contacts for each condition. We reviewed discharge summaries and medical records to verify the NRP diagnoses, and computed the PPV as the proportion of confirmed diagnoses. Results A total of 950 records were reviewed. The overall PPV for the 19 Charlson conditions was 98.0% (95% CI; 96.9, 98.8. The PPVs ranged from 82.0% (95% CI; 68.6%, 91.4% for diabetes with diabetic complications to 100% (one-sided 97.5% CI; 92.9%, 100% for congestive heart failure, peripheral vascular disease, chronic pulmonary disease, mild and severe liver disease, hemiplegia, renal disease, leukaemia, lymphoma, metastatic tumour, and AIDS. Conclusion The PPV of NRP coding of the Charlson conditions was consistently high.

  10. Computational Account of Spontaneous Activity as a Signature of Predictive Coding.

    Directory of Open Access Journals (Sweden)

    Veronika Koren

    2017-01-01

    Full Text Available Spontaneous activity is commonly observed in a variety of cortical states. Experimental evidence suggested that neural assemblies undergo slow oscillations with Up ad Down states even when the network is isolated from the rest of the brain. Here we show that these spontaneous events can be generated by the recurrent connections within the network and understood as signatures of neural circuits that are correcting their internal representation. A noiseless spiking neural network can represent its input signals most accurately when excitatory and inhibitory currents are as strong and as tightly balanced as possible. However, in the presence of realistic neural noise and synaptic delays, this may result in prohibitively large spike counts. An optimal working regime can be found by considering terms that control firing rates in the objective function from which the network is derived and then minimizing simultaneously the coding error and the cost of neural activity. In biological terms, this is equivalent to tuning neural thresholds and after-spike hyperpolarization. In suboptimal working regimes, we observe spontaneous activity even in the absence of feed-forward inputs. In an all-to-all randomly connected network, the entire population is involved in Up states. In spatially organized networks with local connectivity, Up states spread through local connections between neurons of similar selectivity and take the form of a traveling wave. Up states are observed for a wide range of parameters and have similar statistical properties in both active and quiescent state. In the optimal working regime, Up states are vanishing, leaving place to asynchronous activity, suggesting that this working regime is a signature of maximally efficient coding. Although they result in a massive increase in the firing activity, the read-out of spontaneous Up states is in fact orthogonal to the stimulus representation, therefore interfering minimally with the network

  11. Convolutional-Code-Specific CRC Code Design

    OpenAIRE

    Lou, Chung-Yu; Daneshrad, Babak; Wesel, Richard D.

    2015-01-01

    Cyclic redundancy check (CRC) codes check if a codeword is correctly received. This paper presents an algorithm to design CRC codes that are optimized for the code-specific error behavior of a specified feedforward convolutional code. The algorithm utilizes two distinct approaches to computing undetected error probability of a CRC code used with a specific convolutional code. The first approach enumerates the error patterns of the convolutional code and tests if each of them is detectable. Th...

  12. Rank Order Coding: a Retinal Information Decoding Strategy Revealed by Large-Scale Multielectrode Array Retinal Recordings.

    Science.gov (United States)

    Portelli, Geoffrey; Barrett, John M; Hilgen, Gerrit; Masquelier, Timothée; Maccione, Alessandro; Di Marco, Stefano; Berdondini, Luca; Kornprobst, Pierre; Sernagor, Evelyne

    2016-01-01

    How a population of retinal ganglion cells (RGCs) encodes the visual scene remains an open question. Going beyond individual RGC coding strategies, results in salamander suggest that the relative latencies of a RGC pair encode spatial information. Thus, a population code based on this concerted spiking could be a powerful mechanism to transmit visual information rapidly and efficiently. Here, we tested this hypothesis in mouse by recording simultaneous light-evoked responses from hundreds of RGCs, at pan-retinal level, using a new generation of large-scale, high-density multielectrode array consisting of 4096 electrodes. Interestingly, we did not find any RGCs exhibiting a clear latency tuning to the stimuli, suggesting that in mouse, individual RGC pairs may not provide sufficient information. We show that a significant amount of information is encoded synergistically in the concerted spiking of large RGC populations. Thus, the RGC population response described with relative activities, or ranks, provides more relevant information than classical independent spike count- or latency- based codes. In particular, we report for the first time that when considering the relative activities across the whole population, the wave of first stimulus-evoked spikes is an accurate indicator of stimulus content. We show that this coding strategy coexists with classical neural codes, and that it is more efficient and faster. Overall, these novel observations suggest that already at the level of the retina, concerted spiking provides a reliable and fast strategy to rapidly transmit new visual scenes.

  13. From concatenated codes to graph codes

    DEFF Research Database (Denmark)

    Justesen, Jørn; Høholdt, Tom

    2004-01-01

    We consider codes based on simple bipartite expander graphs. These codes may be seen as the first step leading from product type concatenated codes to more complex graph codes. We emphasize constructions of specific codes of realistic lengths, and study the details of decoding by message passing...

  14. Concatenated codes with convolutional inner codes

    DEFF Research Database (Denmark)

    Justesen, Jørn; Thommesen, Christian; Zyablov, Viktor

    1988-01-01

    The minimum distance of concatenated codes with Reed-Solomon outer codes and convolutional inner codes is studied. For suitable combinations of parameters the minimum distance can be lower-bounded by the product of the minimum distances of the inner and outer codes. For a randomized ensemble...... of concatenated codes a lower bound of the Gilbert-Varshamov type is proved...

  15. Cracking the code of oscillatory activity.

    Directory of Open Access Journals (Sweden)

    Philippe G Schyns

    2011-05-01

    Full Text Available Neural oscillations are ubiquitous measurements of cognitive processes and dynamic routing and gating of information. The fundamental and so far unresolved problem for neuroscience remains to understand how oscillatory activity in the brain codes information for human cognition. In a biologically relevant cognitive task, we instructed six human observers to categorize facial expressions of emotion while we measured the observers' EEG. We combined state-of-the-art stimulus control with statistical information theory analysis to quantify how the three parameters of oscillations (i.e., power, phase, and frequency code the visual information relevant for behavior in a cognitive task. We make three points: First, we demonstrate that phase codes considerably more information (2.4 times relating to the cognitive task than power. Second, we show that the conjunction of power and phase coding reflects detailed visual features relevant for behavioral response--that is, features of facial expressions predicted by behavior. Third, we demonstrate, in analogy to communication technology, that oscillatory frequencies in the brain multiplex the coding of visual features, increasing coding capacity. Together, our findings about the fundamental coding properties of neural oscillations will redirect the research agenda in neuroscience by establishing the differential role of frequency, phase, and amplitude in coding behaviorally relevant information in the brain.

  16. Artificial neural networks analysis of surface-enhanced laser desorption/ionization mass spectra of serum protein pattern distinguishes colorectal cancer from healthy population.

    Science.gov (United States)

    Chen, Yi-ding; Zheng, Shu; Yu, Jie-kai; Hu, Xun

    2004-12-15

    The low specificity and sensitivity of the carcinoembryonic antigen test makes it not an ideal biomarker for the detection of colorectal cancer. We developed and evaluated a proteomic approach for the simultaneous detection and analysis of multiple proteins for distinguishing individuals with colorectal cancer from healthy individuals. We subjected serum samples (including 55 colorectal cancer patients and 92 age- and sex-matched healthy individuals) from 147 individuals, for analysis by surface-enhanced laser desorption/ionization (SELDI) mass spectrometry. Peaks were detected with Ciphergen SELDI software version 3.0. Using a multilayer artificial neural network with a back propagation algorithm, we developed a classifier for separating the colorectal cancer groups from the healthy groups. The artificial neural network classifier separated the colorectal cancer from the healthy samples, with a sensitivity of 91% and specificity of 93%. Four top-scored peaks, at m/z of 5,911, 8,930, 8,817, and 4,476, were finally selected as the potential "fingerprints" for detection of colorectal cancer. The combination of SELDI-TOF mass spectrometry with the artificial neural networks in the analysis of serum protein yields significantly higher sensitivity and specificity values for the detection and diagnosis of colorectal cancer.

  17. Animal-to-Animal Variation in Odor Preference and Neural Representation of Odors

    Science.gov (United States)

    Honegger, Kyle; Smith, Matthew; Turner, Glenn; de Bivort, Benjamin

    Across any population of animals, individuals exhibit diverse behaviors and reactions to sensory stimuli like tastes and odors. While idiosyncratic behavior is ubiquitous, its biological basis is poorly understood. In this talk, I will present evidence that individual fruit flies (Drosophila melanogaster) display idiosyncratic olfactory behaviors and discuss our ongoing efforts to map these behavioral differences to variation in neural circuits. Using a high-throughput, single-fly assay for odor preference, we have demonstrated that highly inbred flies display substantial animal-to-animal variability, beyond that expected from experimental error, and that these preferences persist over days. Using in vivo two-photon calcium imaging, we are beginning to examine the idiosyncrasy of neural coding in the fly olfactory pathway and find that the odor responses of individual processing channels in the antennal lobe can vary substantially from fly to fly. These results imply that individual differences in neural coding may be used to predict the idiosyncratic behavior of an individual - a hypothesis we are currently testing by imaging neural activity from flies after measuring their odor preferences.

  18. Cortical Neural Computation by Discrete Results Hypothesis.

    Science.gov (United States)

    Castejon, Carlos; Nuñez, Angel

    2016-01-01

    One of the most challenging problems we face in neuroscience is to understand how the cortex performs computations. There is increasing evidence that the power of the cortical processing is produced by populations of neurons forming dynamic neuronal ensembles. Theoretical proposals and multineuronal experimental studies have revealed that ensembles of neurons can form emergent functional units. However, how these ensembles are implicated in cortical computations is still a mystery. Although cell ensembles have been associated with brain rhythms, the functional interaction remains largely unclear. It is still unknown how spatially distributed neuronal activity can be temporally integrated to contribute to cortical computations. A theoretical explanation integrating spatial and temporal aspects of cortical processing is still lacking. In this Hypothesis and Theory article, we propose a new functional theoretical framework to explain the computational roles of these ensembles in cortical processing. We suggest that complex neural computations underlying cortical processing could be temporally discrete and that sensory information would need to be quantized to be computed by the cerebral cortex. Accordingly, we propose that cortical processing is produced by the computation of discrete spatio-temporal functional units that we have called "Discrete Results" (Discrete Results Hypothesis). This hypothesis represents a novel functional mechanism by which information processing is computed in the cortex. Furthermore, we propose that precise dynamic sequences of "Discrete Results" is the mechanism used by the cortex to extract, code, memorize and transmit neural information. The novel "Discrete Results" concept has the ability to match the spatial and temporal aspects of cortical processing. We discuss the possible neural underpinnings of these functional computational units and describe the empirical evidence supporting our hypothesis. We propose that fast-spiking (FS

  19. Self-Control in Sparsely Coded Networks

    Science.gov (United States)

    Dominguez, D. R. C.; Bollé, D.

    1998-03-01

    A complete self-control mechanism is proposed in the dynamics of neural networks through the introduction of a time-dependent threshold, determined in function of both the noise and the pattern activity in the network. Especially for sparsely coded models this mechanism is shown to considerably improve the storage capacity, the basins of attraction, and the mutual information content.

  20. A Neural Substrate for Rapid Timbre Recognition? Neural and Behavioral Discrimination of Very Brief Acoustic Vowels.

    Science.gov (United States)

    Occelli, F; Suied, C; Pressnitzer, D; Edeline, J-M; Gourévitch, B

    2016-06-01

    The timbre of a sound plays an important role in our ability to discriminate between behaviorally relevant auditory categories, such as different vowels in speech. Here, we investigated, in the primary auditory cortex (A1) of anesthetized guinea pigs, the neural representation of vowels with impoverished timbre cues. Five different vowels were presented with durations ranging from 2 to 128 ms. A psychophysical experiment involving human listeners showed that identification performance was near ceiling for the longer durations and degraded close to chance level for the shortest durations. This was likely due to spectral splatter, which reduced the contrast between the spectral profiles of the vowels at short durations. Effects of vowel duration on cortical responses were well predicted by the linear frequency responses of A1 neurons. Using mutual information, we found that auditory cortical neurons in the guinea pig could be used to reliably identify several vowels for all durations. Information carried by each cortical site was low on average, but the population code was accurate even for durations where human behavioral performance was poor. These results suggest that a place population code is available at the level of A1 to encode spectral profile cues for even very short sounds. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  1. Applications of Pulse-Coupled Neural Networks

    CERN Document Server

    Ma, Yide; Wang, Zhaobin

    2011-01-01

    "Applications of Pulse-Coupled Neural Networks" explores the fields of image processing, including image filtering, image segmentation, image fusion, image coding, image retrieval, and biometric recognition, and the role of pulse-coupled neural networks in these fields. This book is intended for researchers and graduate students in artificial intelligence, pattern recognition, electronic engineering, and computer science. Prof. Yide Ma conducts research on intelligent information processing, biomedical image processing, and embedded system development at the School of Information Sci

  2. Death and rebirth of neural activity in sparse inhibitory networks

    Science.gov (United States)

    Angulo-Garcia, David; Luccioli, Stefano; Olmi, Simona; Torcini, Alessandro

    2017-05-01

    Inhibition is a key aspect of neural dynamics playing a fundamental role for the emergence of neural rhythms and the implementation of various information coding strategies. Inhibitory populations are present in several brain structures, and the comprehension of their dynamics is strategical for the understanding of neural processing. In this paper, we clarify the mechanisms underlying a general phenomenon present in pulse-coupled heterogeneous inhibitory networks: inhibition can induce not only suppression of neural activity, as expected, but can also promote neural re-activation. In particular, for globally coupled systems, the number of firing neurons monotonically reduces upon increasing the strength of inhibition (neuronal death). However, the random pruning of connections is able to reverse the action of inhibition, i.e. in a random sparse network a sufficiently strong synaptic strength can surprisingly promote, rather than depress, the activity of neurons (neuronal rebirth). Thus, the number of firing neurons reaches a minimum value at some intermediate synaptic strength. We show that this minimum signals a transition from a regime dominated by neurons with a higher firing activity to a phase where all neurons are effectively sub-threshold and their irregular firing is driven by current fluctuations. We explain the origin of the transition by deriving a mean field formulation of the problem able to provide the fraction of active neurons as well as the first two moments of their firing statistics. The introduction of a synaptic time scale does not modify the main aspects of the reported phenomenon. However, for sufficiently slow synapses the transition becomes dramatic, and the system passes from a perfectly regular evolution to irregular bursting dynamics. In this latter regime the model provides predictions consistent with experimental findings for a specific class of neurons, namely the medium spiny neurons in the striatum.

  3. Changes is genes coding for laccases 1 and 2 may contribute to deformation and reduction of wings in apollo butterfly (Parnassius apollo, Lepidoptera: Papilionidae) from the isolated population in Pieniny National Park (Poland).

    Science.gov (United States)

    Łukasiewicz, Kinga; Węgrzyn, Grzegorz

    2016-01-01

    An isolated population of apollo butterfly (Parnassius apollo, Lepidoptera: Papilionidae) occurs in Pieniny National Park (Poland). Deformations and reductions of wings in a relatively large number of individuals from this population is found, yet the reasons for these defects are unknown. During studies devoted to identify cause(s) of this phenomenon, we found that specific regions of genes coding of enzymes laccases 1 and 2 could not be amplified from DNA samples isolated from large fractions of malformed insects while expected PCR products were detected in almost all (with one exception) normal butterflies. Laccases (p-diphenol:dioxygen oxidoreductases) are oxidases containing several copper atoms. They catalyse single-electron oxidations of phenolic or other compounds with concomitant reduction of oxygen to water. In insects, their enzymatic activities were found previously in epidermis, midgut, Malpighian tubules, salivary glands, and reproductive tissues. Therefore, we suggest that defects in genes coding for laccases might contribute to deformation and reduction of wings in apollo butterflies, though it seems obvious that deficiency in these enzymes could not be the sole cause of these developmental improperties in P. apollo from Pieniny National Park.

  4. Prevention of neural tube defects by the fortification of flour with folic acid: a population-based retrospective study in Brazil/Prevention des anomalies du tube neural par l'enrichissement en acide folique des farines: etude retrospective en population au Bresil/La prevencion de los defectos del tubo neural mediante el enriquecimiento de la harina con acido folico: un estudio poblacional retrospectivo en Brasil

    National Research Council Canada - National Science Library

    Santos, Leonor Maria Pacheco; Lecca, Roberto Carlos Reyes; Cortez-Escalante, Juan Jose; Sanchez, Mauro Niskier; Rodrigues, Humberto Gabriel

    2016-01-01

    Objective To determine if the fortification of wheat and maize flours with iron and folic acid--which became mandatory in Brazil from June 2004--is effective in the prevention of neural tube defects...

  5. Effects of natural selection and gene conversion on the evolution of human glycophorins coding for MNS blood polymorphisms in malaria-endemic African populations.

    Science.gov (United States)

    Ko, Wen-Ya; Kaercher, Kristin A; Giombini, Emanuela; Marcatili, Paolo; Froment, Alain; Ibrahim, Muntaser; Lema, Godfrey; Nyambo, Thomas B; Omar, Sabah A; Wambebe, Charles; Ranciaro, Alessia; Hirbo, Jibril B; Tishkoff, Sarah A

    2011-06-10

    Malaria has been a very strong selection pressure in recent human evolution, particularly in Africa. Of the one million deaths per year due to malaria, more than 90% are in sub-Saharan Africa, a region with high levels of genetic variation and population substructure. However, there have been few studies of nucleotide variation at genetic loci that are relevant to malaria susceptibility across geographically and genetically diverse ethnic groups in Africa. Invasion of erythrocytes by Plasmodium falciparum parasites is central to the pathology of malaria. Glycophorin A (GYPA) and B (GYPB), which determine MN and Ss blood types, are two major receptors that are expressed on erythrocyte surfaces and interact with parasite ligands. We analyzed nucleotide diversity of the glycophorin gene family in 15 African populations with different levels of malaria exposure. High levels of nucleotide diversity and gene conversion were found at these genes. We observed divergent patterns of genetic variation between these duplicated genes and between different extracellular domains of GYPA. Specifically, we identified fixed adaptive changes at exons 3-4 of GYPA. By contrast, we observed an allele frequency spectrum skewed toward a significant excess of intermediate-frequency alleles at GYPA exon 2 in many populations; the degree of spectrum distortion is correlated with malaria exposure, possibly because of the joint effects of gene conversion and balancing selection. We also identified a haplotype causing three amino acid changes in the extracellular domain of glycophorin B. This haplotype might have evolved adaptively in five populations with high exposure to malaria. Copyright © 2011 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

  6. Neural Networks

    Directory of Open Access Journals (Sweden)

    Schwindling Jerome

    2010-04-01

    Full Text Available This course presents an overview of the concepts of the neural networks and their aplication in the framework of High energy physics analyses. After a brief introduction on the concept of neural networks, the concept is explained in the frame of neuro-biology, introducing the concept of multi-layer perceptron, learning and their use as data classifer. The concept is then presented in a second part using in more details the mathematical approach focussing on typical use cases faced in particle physics. Finally, the last part presents the best way to use such statistical tools in view of event classifers, putting the emphasis on the setup of the multi-layer perceptron. The full article (15 p. corresponding to this lecture is written in french and is provided in the proceedings of the book SOS 2008.

  7. A genome-wide association study for diabetic retinopathy in a Japanese population: potential association with a long intergenic non-coding RNA.

    Directory of Open Access Journals (Sweden)

    Takuya Awata

    Full Text Available Elucidation of the genetic susceptibility factors for diabetic retinopathy (DR is important to gain insight into the pathogenesis of DR, and may help to define genetic risk factors for this condition. In the present study, we conducted a three-stage genome-wide association study (GWAS to identify DR susceptibility loci in Japanese patients, which comprised a total of 837 type 2 diabetes patients with DR (cases and 1,149 without DR (controls. From the stage 1 genome-wide scan of 446 subjects (205 cases and 241 controls on 614,216 SNPs, 249 SNPs were selected for the stage 2 replication in 623 subjects (335 cases and 288 controls. Eight SNPs were further followed up in a stage 3 study of 297 cases and 620 controls. The top signal from the present association analysis was rs9362054 in an intron of RP1-90L14.1 showing borderline genome-wide significance (Pmet = 1.4×10(-7, meta-analysis of stage 1 and stage 2, allele model. RP1-90L14.1 is a long intergenic non-coding RNA (lincRNA adjacent to KIAA1009/QN1/CEP162 gene; CEP162 plays a critical role in ciliary transition zone formation before ciliogenesis. The present study raises the possibility that the dysregulation of ciliary-associated genes plays a role in susceptibility to DR.

  8. Analysis of polyglutamine-coding repeats in the TATA-binding protein in different human populations and in patients with schizophrenia an bipolar affective disorder

    Energy Technology Data Exchange (ETDEWEB)

    Rubinsztein, D.C.; Leggo, J. [Addenbrooke`s National Health Service Trust, Cambridge (United Kingdom); Crow, T.J. [Cambridge Univ. (United Kingdom)] [and others

    1996-09-20

    A new class of disease (including Huntington disease, Kennedy disease, and spinocerebellar ataxias types 1 and 3) results from abnormal expansions of CAG trinucleotides in the coding regions of genes. In all of these diseases the CAG repeats are thought to be translated into polyglutamine tracts. There is accumulating evidence arguing for CAG trinucleotide expansions as one of the causative disease mutations in schizophrenia and bipolar affective disorder. We and others believe that the TATA-binding protein (TBP) is an important candidate to investigate in these diseases as it contains a highly polymorphic stretch of glutamine codons, which are close to the threshold length where the polyglutamine tracts start to be associated with disease. Thus, we examined the lengths of this polyglutamine repeat in normal unrelated East Anglians, South African Blacks, sub-Saharan Africans mainly from Nigeria, and Asian Indians. We also examined 43 bipolar affective disorder patients and 65 schizophrenic patients. The range of polyglutamine tract-lengths that we found in humans was from 26-42 codons. No patients with bipolar affective disorder and schizophrenia had abnormal expansions at this locus. 22 refs., 1 tab.

  9. Fundamentals of convolutional coding

    CERN Document Server

    Johannesson, Rolf

    2015-01-01

    Fundamentals of Convolutional Coding, Second Edition, regarded as a bible of convolutional coding brings you a clear and comprehensive discussion of the basic principles of this field * Two new chapters on low-density parity-check (LDPC) convolutional codes and iterative coding * Viterbi, BCJR, BEAST, list, and sequential decoding of convolutional codes * Distance properties of convolutional codes * Includes a downloadable solutions manual

  10. Supervised Learning in Spiking Neural Networks for Precise Temporal Encoding

    National Research Council Canada - National Science Library

    Gardner, Brian; Grüning, André

    2016-01-01

    Precise spike timing as a means to encode information in neural networks is biologically supported, and is advantageous over frequency-based codes by processing input features on a much shorter time-scale...

  11. Spike Timing Matters in Novel Neuronal Code Involved in Vibrotactile Frequency Perception.

    Science.gov (United States)

    Birznieks, Ingvars; Vickery, Richard M

    2017-05-22

    Skin vibrations sensed by tactile receptors contribute significantly to the perception of object properties during tactile exploration [1-4] and to sensorimotor control during object manipulation [5]. Sustained low-frequency skin vibration (perception of frequency is still unknown. Measures based on mean spike rates of neurons in the primary somatosensory cortex are sufficient to explain performance in some frequency discrimination tasks [7-11]; however, there is emerging evidence that stimuli can be distinguished based also on temporal features of neural activity [12, 13]. Our study's advance is to demonstrate that temporal features are fundamental for vibrotactile frequency perception. Pulsatile mechanical stimuli were used to elicit specified temporal spike train patterns in tactile afferents, and subsequently psychophysical methods were employed to characterize human frequency perception. Remarkably, the most salient temporal feature determining vibrotactile frequency was not the underlying periodicity but, rather, the duration of the silent gap between successive bursts of neural activity. This burst gap code for frequency represents a previously unknown form of neural coding in the tactile sensory system, which parallels auditory pitch perception mechanisms based on purely temporal information where longer inter-pulse intervals receive higher perceptual weights than short intervals [14]. Our study also demonstrates that human perception of stimuli can be determined exclusively by temporal features of spike trains independent of the mean spike rate and without contribution from population response factors. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Neural Representation of Concurrent Vowels in Macaque Primary Auditory Cortex123

    Science.gov (United States)

    Micheyl, Christophe; Steinschneider, Mitchell

    2016-01-01

    Abstract Successful speech perception in real-world environments requires that the auditory system segregate competing voices that overlap in frequency and time into separate streams. Vowels are major constituents of speech and are comprised of frequencies (harmonics) that are integer multiples of a common fundamental frequency (F0). The pitch and identity of a vowel are determined by its F0 and spectral envelope (formant structure), respectively. When two spectrally overlapping vowels differing in F0 are presented concurrently, they can be readily perceived as two separate “auditory objects” with pitches at their respective F0s. A difference in pitch between two simultaneous vowels provides a powerful cue for their segregation, which in turn, facilitates their individual identification. The neural mechanisms underlying the segregation of concurrent vowels based on pitch differences are poorly understood. Here, we examine neural population responses in macaque primary auditory cortex (A1) to single and double concurrent vowels (/a/ and /i/) that differ in F0 such that they are heard as two separate auditory objects with distinct pitches. We find that neural population responses in A1 can resolve, via a rate-place code, lower harmonics of both single and double concurrent vowels. Furthermore, we show that the formant structures, and hence the identities, of single vowels can be reliably recovered from the neural representation of double concurrent vowels. We conclude that A1 contains sufficient spectral information to enable concurrent vowel segregation and identification by downstream cortical areas. PMID:27294198

  13. Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback.

    Science.gov (United States)

    Orhan, A Emin; Ma, Wei Ji

    2017-07-26

    Animals perform near-optimal probabilistic inference in a wide range of psychophysical tasks. Probabilistic inference requires trial-to-trial representation of the uncertainties associated with task variables and subsequent use of this representation. Previous work has implemented such computations using neural networks with hand-crafted and task-dependent operations. We show that generic neural networks trained with a simple error-based learning rule perform near-optimal probabilistic inference in nine common psychophysical tasks. In a probabilistic categorization task, error-based learning in a generic network simultaneously explains a monkey's learning curve and the evolution of qualitative aspects of its choice behavior. In all tasks, the number of neurons required for a given level of performance grows sublinearly with the input population size, a substantial improvement on previous implementations of probabilistic inference. The trained networks develop a novel sparsity-based probabilistic population code. Our results suggest that probabilistic inference emerges naturally in generic neural networks trained with error-based learning rules.Behavioural tasks often require probability distributions to be inferred about task specific variables. Here, the authors demonstrate that generic neural networks can be trained using a simple error-based learning rule to perform such probabilistic computations efficiently without any need for task specific operations.

  14. Temporal and Spatial Simulation of Atmospheric Pollutant PM2.5 Changes and Risk Assessment of Population Exposure to Pollution Using Optimization Algorithms of the Back Propagation-Artificial Neural Network Model and GIS

    Science.gov (United States)

    Zhang, Ping; Hong, Bo; He, Liang; Cheng, Fei; Zhao, Peng; Wei, Cailiang; Liu, Yunhui

    2015-01-01

    PM2.5 pollution has become of increasing public concern because of its relative importance and sensitivity to population health risks. Accurate predictions of PM2.5 pollution and population exposure risks are crucial to developing effective air pollution control strategies. We simulated and predicted the temporal and spatial changes of PM2.5 concentration and population exposure risks, by coupling optimization algorithms of the Back Propagation-Artificial Neural Network (BP-ANN) model and a geographical information system (GIS) in Xi’an, China, for 2013, 2020, and 2025. Results indicated that PM2.5 concentration was positively correlated with GDP, SO2, and NO2, while it was negatively correlated with population density, average temperature, precipitation, and wind speed. Principal component analysis of the PM2.5 concentration and its influencing factors’ variables extracted four components that accounted for 86.39% of the total variance. Correlation coefficients of the Levenberg-Marquardt (trainlm) and elastic (trainrp) algorithms were more than 0.8, the index of agreement (IA) ranged from 0.541 to 0.863 and from 0.502 to 0.803 by trainrp and trainlm algorithms, respectively; mean bias error (MBE) and Root Mean Square Error (RMSE) indicated that the predicted values were very close to the observed values, and the accuracy of trainlm algorithm was better than the trainrp. Compared to 2013, temporal and spatial variation of PM2.5 concentration and risk of population exposure to pollution decreased in 2020 and 2025. The high-risk areas of population exposure to PM2.5 were mainly distributed in the northern region, where there is downtown traffic, abundant commercial activity, and more exhaust emissions. A moderate risk zone was located in the southern region associated with some industrial pollution sources, and there were mainly low-risk areas in the western and eastern regions, which are predominantly residential and educational areas. PMID:26426030

  15. Temporal and Spatial Simulation of Atmospheric Pollutant PM2.5 Changes and Risk Assessment of Population Exposure to Pollution Using Optimization Algorithms of the Back Propagation-Artificial Neural Network Model and GIS

    Directory of Open Access Journals (Sweden)

    Ping Zhang

    2015-09-01

    Full Text Available PM2.5 pollution has become of increasing public concern because of its relative importance and sensitivity to population health risks. Accurate predictions of PM2.5 pollution and population exposure risks are crucial to developing effective air pollution control strategies. We simulated and predicted the temporal and spatial changes of PM2.5 concentration and population exposure risks, by coupling optimization algorithms of the Back Propagation-Artificial Neural Network (BP-ANN model and a geographical information system (GIS in Xi’an, China, for 2013, 2020, and 2025. Results indicated that PM2.5 concentration was positively correlated with GDP, SO2, and NO2, while it was negatively correlated with population density, average temperature, precipitation, and wind speed. Principal component analysis of the PM2.5 concentration and its influencing factors’ variables extracted four components that accounted for 86.39% of the total variance. Correlation coefficients of the Levenberg-Marquardt (trainlm and elastic (trainrp algorithms were more than 0.8, the index of agreement (IA ranged from 0.541 to 0.863 and from 0.502 to 0.803 by trainrp and trainlm algorithms, respectively; mean bias error (MBE and Root Mean Square Error (RMSE indicated that the predicted values were very close to the observed values, and the accuracy of trainlm algorithm was better than the trainrp. Compared to 2013, temporal and spatial variation of PM2.5 concentration and risk of population exposure to pollution decreased in 2020 and 2025. The high-risk areas of population exposure to PM2.5 were mainly distributed in the northern region, where there is downtown traffic, abundant commercial activity, and more exhaust emissions. A moderate risk zone was located in the southern region associated with some industrial pollution sources, and there were mainly low-risk areas in the western and eastern regions, which are predominantly residential and educational areas.

  16. Temporal and Spatial Simulation of Atmospheric Pollutant PM2.5 Changes and Risk Assessment of Population Exposure to Pollution Using Optimization Algorithms of the Back Propagation-Artificial Neural Network Model and GIS.

    Science.gov (United States)

    Zhang, Ping; Hong, Bo; He, Liang; Cheng, Fei; Zhao, Peng; Wei, Cailiang; Liu, Yunhui

    2015-09-29

    PM2.5 pollution has become of increasing public concern because of its relative importance and sensitivity to population health risks. Accurate predictions of PM2.5 pollution and population exposure risks are crucial to developing effective air pollution control strategies. We simulated and predicted the temporal and spatial changes of PM2.5 concentration and population exposure risks, by coupling optimization algorithms of the Back Propagation-Artificial Neural Network (BP-ANN) model and a geographical information system (GIS) in Xi'an, China, for 2013, 2020, and 2025. Results indicated that PM2.5 concentration was positively correlated with GDP, SO₂, and NO₂, while it was negatively correlated with population density, average temperature, precipitation, and wind speed. Principal component analysis of the PM2.5 concentration and its influencing factors' variables extracted four components that accounted for 86.39% of the total variance. Correlation coefficients of the Levenberg-Marquardt (trainlm) and elastic (trainrp) algorithms were more than 0.8, the index of agreement (IA) ranged from 0.541 to 0.863 and from 0.502 to 0.803 by trainrp and trainlm algorithms, respectively; mean bias error (MBE) and Root Mean Square Error (RMSE) indicated that the predicted values were very close to the observed values, and the accuracy of trainlm algorithm was better than the trainrp. Compared to 2013, temporal and spatial variation of PM2.5 concentration and risk of population exposure to pollution decreased in 2020 and 2025. The high-risk areas of population exposure to PM2.5 were mainly distributed in the northern region, where there is downtown traffic, abundant commercial activity, and more exhaust emissions. A moderate risk zone was located in the southern region associated with some industrial pollution sources, and there were mainly low-risk areas in the western and eastern regions, which are predominantly residential and educational areas.

  17. Neuron's eye view: Inferring features of complex stimuli from neural responses.

    Directory of Open Access Journals (Sweden)

    Xin Chen

    2017-08-01

    Full Text Available Experiments that study neural encoding of stimuli at the level of individual neurons typically choose a small set of features present in the world-contrast and luminance for vision, pitch and intensity for sound-and assemble a stimulus set that systematically varies along these dimensions. Subsequent analysis of neural responses to these stimuli typically focuses on regression models, with experimenter-controlled features as predictors and spike counts or firing rates as responses. Unfortunately, this approach requires knowledge in advance about the relevant features coded by a given population of neurons. For domains as complex as social interaction or natural movement, however, the relevant feature space is poorly understood, and an arbitrary a priori choice of features may give rise to confirmation bias. Here, we present a Bayesian model for exploratory data analysis that is capable of automatically identifying the features present in unstructured stimuli based solely on neuronal responses. Our approach is unique within the class of latent state space models of neural activity in that it assumes that firing rates of neurons are sensitive to multiple discrete time-varying features tied to the stimulus, each of which has Markov (or semi-Markov dynamics. That is, we are modeling neural activity as driven by multiple simultaneous stimulus features rather than intrinsic neural dynamics. We derive a fast variational Bayesian inference algorithm and show that it correctly recovers hidden features in synthetic data, as well as ground-truth stimulus features in a prototypical neural dataset. To demonstrate the utility of the algorithm, we also apply it to cluster neural responses and demonstrate successful recovery of features corresponding to monkeys and faces in the image set.

  18. Neural Tube Defects

    Science.gov (United States)

    ... vitamin, before and during pregnancy prevents most neural tube defects. Neural tube defects are usually diagnosed before the infant is ... or imaging tests. There is no cure for neural tube defects. The nerve damage and loss of function ...

  19. Neural crest contributions to the lamprey head

    Science.gov (United States)

    McCauley, David W.; Bronner-Fraser, Marianne

    2003-01-01

    The neural crest is a vertebrate-specific cell population that contributes to the facial skeleton and other derivatives. We have performed focal DiI injection into the cranial neural tube of the developing lamprey in order to follow the migratory pathways of discrete groups of cells from origin to destination and to compare neural crest migratory pathways in a basal vertebrate to those of gnathostomes. The results show that the general pathways of cranial neural crest migration are conserved throughout the vertebrates, with cells migrating in streams analogous to the mandibular and hyoid streams. Caudal branchial neural crest cells migrate ventrally as a sheet of cells from the hindbrain and super-pharyngeal region of the neural tube and form a cylinder surrounding a core of mesoderm in each pharyngeal arch, similar to that seen in zebrafish and axolotl. In addition to these similarities, we also uncovered important differences. Migration into the presumptive caudal branchial arches of the lamprey involves both rostral and caudal movements of neural crest cells that have not been described in gnathostomes, suggesting that barriers that constrain rostrocaudal movement of cranial neural crest cells may have arisen after the agnathan/gnathostome split. Accordingly, neural crest cells from a single axial level contributed to multiple arches and there was extensive mixing between populations. There was no apparent filling of neural crest derivatives in a ventral-to-dorsal order, as has been observed in higher vertebrates, nor did we find evidence of a neural crest contribution to cranial sensory ganglia. These results suggest that migratory constraints and additional neural crest derivatives arose later in gnathostome evolution.

  20. A chemical screen in zebrafish embryonic cells establishes that Akt activation is required for neural crest development

    NARCIS (Netherlands)

    Ciarlo, Christie; Kaufman, Charles K.; Kinikoglu, Beste; Michael, Jonathan; Yang, Song; D’Amato, Christopher; Blokzijl-Franke, Sasja; den Hertog, Jeroen|info:eu-repo/dai/nl/096717696; Schlaeger, Thorsten M.; Zhou, Yi; Liao, Eric C; Zon, Leonard I.

    2017-01-01

    The neural crest is a dynamic progenitor cell population that arises at the border of neural and non-neural ectoderm. The inductive roles of FGF, Wnt, and BMP at the neural plate border are well established, but the signals required for subsequent neural crest development remain poorly

  1. Affine Grassmann codes

    DEFF Research Database (Denmark)

    Høholdt, Tom; Beelen, Peter; Ghorpade, Sudhir Ramakant

    2010-01-01

    We consider a new class of linear codes, called affine Grassmann codes. These can be viewed as a variant of generalized Reed-Muller codes and are closely related to Grassmann codes.We determine the length, dimension, and the minimum distance of any affine Grassmann code. Moreover, we show...

  2. Expectation violation and attention to pain jointly modulate neural gain in somatosensory cortex

    DEFF Research Database (Denmark)

    Fardo, Francesca; Auksztulewicz, Ryszard; Allen, Micah

    2017-01-01

    The neural processing and experience of pain are influenced by both expectations and attention. For example, the amplitude of event-related pain responses is enhanced by both novel and unexpected pain, and by moving the focus of attention towards a painful stimulus. Under predictive coding...... be mapped onto changes in effective connectivity between or within specific neuronal populations, using a canonical microcircuit (CMC) model of hierarchical processing. We thus implemented a CMC within dynamic causal modelling (DCM) for magnetoencephalography in human subjects, to investigate how...

  3. Cognitive And Neural Sciences Division 1992 Programs

    Science.gov (United States)

    1992-08-01

    Neuronal Micronets as Nodal Elements PRINCIPAL INVESTIGATOR: Thomas H. Brown Yale University Department of Psychology (203) 432-7008 R&T PROJECT CODE...of neural nets, and to develop a micronet architecture which captures the computations in neurons. Approach: Simulations will be conducted of the

  4. Turbo Codes Extended with Outer BCH Code

    DEFF Research Database (Denmark)

    Andersen, Jakob Dahl

    1996-01-01

    The "error floor" observed in several simulations with the turbo codes is verified by calculation of an upper bound to the bit error rate for the ensemble of all interleavers. Also an easy way to calculate the weight enumerator used in this bound is presented. An extended coding scheme is propose...... including an outer BCH code correcting a few bit errors.......The "error floor" observed in several simulations with the turbo codes is verified by calculation of an upper bound to the bit error rate for the ensemble of all interleavers. Also an easy way to calculate the weight enumerator used in this bound is presented. An extended coding scheme is proposed...

  5. Rateless feedback codes

    DEFF Research Database (Denmark)

    Sørensen, Jesper Hemming; Koike-Akino, Toshiaki; Orlik, Philip

    2012-01-01

    This paper proposes a concept called rateless feedback coding. We redesign the existing LT and Raptor codes, by introducing new degree distributions for the case when a few feedback opportunities are available. We show that incorporating feedback to LT codes can significantly decrease both...... the coding overhead and the encoding/decoding complexity. Moreover, we show that, at the price of a slight increase in the coding overhead, linear complexity is achieved with Raptor feedback coding....

  6. Generalized concatenated quantum codes

    Science.gov (United States)

    Grassl, Markus; Shor, Peter; Smith, Graeme; Smolin, John; Zeng, Bei

    2009-05-01

    We discuss the concept of generalized concatenated quantum codes. This generalized concatenation method provides a systematical way for constructing good quantum codes, both stabilizer codes and nonadditive codes. Using this method, we construct families of single-error-correcting nonadditive quantum codes, in both binary and nonbinary cases, which not only outperform any stabilizer codes for finite block length but also asymptotically meet the quantum Hamming bound for large block length.

  7. Electrosensory neural responses to natural electro-communication stimuli are distributed along a continuum.

    Science.gov (United States)

    Sproule, Michael K J; Chacron, Maurice J

    2017-01-01

    Neural heterogeneities are seen ubiquitously within the brain and greatly complicate classification efforts. Here we tested whether the responses of an anatomically well-characterized sensory neuron population to natural stimuli could be used for functional classification. To do so, we recorded from pyramidal cells within the electrosensory lateral line lobe (ELL) of the weakly electric fish Apteronotus leptorhynchus in response to natural electro-communication stimuli as these cells can be anatomically classified into six different types. We then used two independent methodologies to functionally classify responses: one relies of reducing the dimensionality of a feature space while the other directly compares the responses themselves. Both methodologies gave rise to qualitatively similar results: while ON and OFF-type cells could easily be distinguished from one another, ELL pyramidal neuron responses are actually distributed along a continuum rather than forming distinct clusters due to heterogeneities. We discuss the implications of our results for neural coding and highlight some potential advantages.

  8. Advanced video coding systems

    CERN Document Server

    Gao, Wen

    2015-01-01

    This comprehensive and accessible text/reference presents an overview of the state of the art in video coding technology. Specifically, the book introduces the tools of the AVS2 standard, describing how AVS2 can help to achieve a significant improvement in coding efficiency for future video networks and applications by incorporating smarter coding tools such as scene video coding. Topics and features: introduces the basic concepts in video coding, and presents a short history of video coding technology and standards; reviews the coding framework, main coding tools, and syntax structure of AV

  9. Coding for dummies

    CERN Document Server

    Abraham, Nikhil

    2015-01-01

    Hands-on exercises help you learn to code like a pro No coding experience is required for Coding For Dummies,your one-stop guide to building a foundation of knowledge inwriting computer code for web, application, and softwaredevelopment. It doesn't matter if you've dabbled in coding or neverwritten a line of code, this book guides you through the basics.Using foundational web development languages like HTML, CSS, andJavaScript, it explains in plain English how coding works and whyit's needed. Online exercises developed by Codecademy, a leading online codetraining site, help hone coding skill

  10. [Neural repair].

    Science.gov (United States)

    Kitada, Masaaki; Dezawa, Mari

    2008-05-01

    Recent progress of stem cell biology gives us the hope for neural repair. We have established methods to specifically induce functional Schwann cells and neurons from bone marrow stromal cells (MSCs). The effectiveness of these induced cells was evaluated by grafting them either into peripheral nerve injury, spinal cord injury, or Parkinson' s disease animal models. MSCs-derived Schwann cells supported axonal regeneration and re-constructed myelin to facilitate the functional recovery in peripheral and spinal cord injury. MSCs-derived dopaminergic neurons integrated into host striatum and contributed to behavioral repair. In this review, we introduce the differentiation potential of MSCs and finally discuss about their benefits and drawbacks of these induction systems for cell-based therapy in neuro-traumatic and neuro-degenerative diseases.

  11. Correlation between patients' reasons for encounters/health problems and population density in Japan: a systematic review of observational studies coded by the International Classification of Health Problems in Primary Care (ICHPPC) and the International Classification of Primary care (ICPC).

    Science.gov (United States)

    Kaneko, Makoto; Ohta, Ryuichi; Nago, Naoki; Fukushi, Motoharu; Matsushima, Masato

    2017-09-13

    The Japanese health care system has yet to establish structured training for primary care physicians; therefore, physicians who received an internal medicine based training program continue to play a principal role in the primary care setting. To promote the development of a more efficient primary health care system, the assessment of its current status in regard to the spectrum of patients' reasons for encounters (RFEs) and health problems is an important step. Recognizing the proportions of patients' RFEs and health problems, which are not generally covered by an internist, can provide valuable information to promote the development of a primary care physician-centered system. We conducted a systematic review in which we searched six databases (PubMed, the Cochrane Library, Google Scholar, Ichushi-Web, JDreamIII and CiNii) for observational studies in Japan coded by International Classification of Health Problems in Primary Care (ICHPPC) and International Classification of Primary Care (ICPC) up to March 2015. We employed population density as index of accessibility. We calculated Spearman's rank correlation coefficient to examine the correlation between the proportion of "non-internal medicine-related" RFEs and health problems in each study area in consideration of the population density. We found 17 studies with diverse designs and settings. Among these studies, "non-internal medicine-related" RFEs, which was not thought to be covered by internists, ranged from about 4% to 40%. In addition, "non-internal medicine-related" health problems ranged from about 10% to 40%. However, no significant correlation was found between population density and the proportion of "non-internal medicine-related" RFEs and health problems. This is the first systematic review on RFEs and health problems coded by ICHPPC and ICPC undertaken to reveal the diversity of health problems in Japanese primary care. These results suggest that primary care physicians in some rural areas of Japan

  12. Behavior and neural basis of near-optimal visual search

    Science.gov (United States)

    Ma, Wei Ji; Navalpakkam, Vidhya; Beck, Jeffrey M; van den Berg, Ronald; Pouget, Alexandre

    2013-01-01

    The ability to search efficiently for a target in a cluttered environment is one of the most remarkable functions of the nervous system. This task is difficult under natural circumstances, as the reliability of sensory information can vary greatly across space and time and is typically a priori unknown to the observer. In contrast, visual-search experiments commonly use stimuli of equal and known reliability. In a target detection task, we randomly assigned high or low reliability to each item on a trial-by-trial basis. An optimal observer would weight the observations by their trial-to-trial reliability and combine them using a specific nonlinear integration rule. We found that humans were near-optimal, regardless of whether distractors were homogeneous or heterogeneous and whether reliability was manipulated through contrast or shape. We present a neural-network implementation of near-optimal visual search based on probabilistic population coding. The network matched human performance. PMID:21552276

  13. Owl's behavior and neural representation predicted by Bayesian inference.

    Science.gov (United States)

    Fischer, Brian J; Peña, José Luis

    2011-07-03

    The owl captures prey using sound localization. In the classical model, the owl infers sound direction from the position of greatest activity in a brain map of auditory space. However, this model fails to describe the actual behavior. Although owls accurately localize sources near the center of gaze, they systematically underestimate peripheral source directions. We found that this behavior is predicted by statistical inference, formulated as a Bayesian model that emphasizes central directions. We propose that there is a bias in the neural coding of auditory space, which, at the expense of inducing errors in the periphery, achieves high behavioral accuracy at the ethologically relevant range. We found that the owl's map of auditory space decoded by a population vector is consistent with the behavioral model. Thus, a probabilistic model describes both how the map of auditory space supports behavior and why this representation is optimal.

  14. Short-term synaptic plasticity and heterogeneity in neural systems

    Science.gov (United States)

    Mejias, J. F.; Kappen, H. J.; Longtin, A.; Torres, J. J.

    2013-01-01

    We review some recent results on neural dynamics and information processing which arise when considering several biophysical factors of interest, in particular, short-term synaptic plasticity and neural heterogeneity. The inclusion of short-term synaptic plasticity leads to enhanced long-term memory capacities, a higher robustness of memory to noise, and irregularity in the duration of the so-called up cortical states. On the other hand, considering some level of neural heterogeneity in neuron models allows neural systems to optimize information transmission in rate coding and temporal coding, two strategies commonly used by neurons to codify information in many brain areas. In all these studies, analytical approximations can be made to explain the underlying dynamics of these neural systems.

  15. Two Perspectives on the Origin of the Standard Genetic Code

    Science.gov (United States)

    Sengupta, Supratim; Aggarwal, Neha; Bandhu, Ashutosh Vishwa

    2014-12-01

    The origin of a genetic code made it possible to create ordered sequences of amino acids. In this article we provide two perspectives on code origin by carrying out simulations of code-sequence coevolution in finite populations with the aim of examining how the standard genetic code may have evolved from more primitive code(s) encoding a small number of amino acids. We determine the efficacy of the physico-chemical hypothesis of code origin in the absence and presence of horizontal gene transfer (HGT) by allowing a diverse collection of code-sequence sets to compete with each other. We find that in the absence of horizontal gene transfer, natural selection between competing codes distinguished by differences in the degree of physico-chemical optimization is unable to explain the structure of the standard genetic code. However, for certain probabilities of the horizontal transfer events, a universal code emerges having a structure that is consistent with the standard genetic code.

  16. Discussion on LDPC Codes and Uplink Coding

    Science.gov (United States)

    Andrews, Ken; Divsalar, Dariush; Dolinar, Sam; Moision, Bruce; Hamkins, Jon; Pollara, Fabrizio

    2007-01-01

    This slide presentation reviews the progress that the workgroup on Low-Density Parity-Check (LDPC) for space link coding. The workgroup is tasked with developing and recommending new error correcting codes for near-Earth, Lunar, and deep space applications. Included in the presentation is a summary of the technical progress of the workgroup. Charts that show the LDPC decoder sensitivity to symbol scaling errors are reviewed, as well as a chart showing the performance of several frame synchronizer algorithms compared to that of some good codes and LDPC decoder tests at ESTL. Also reviewed is a study on Coding, Modulation, and Link Protocol (CMLP), and the recommended codes. A design for the Pseudo-Randomizer with LDPC Decoder and CRC is also reviewed. A chart that summarizes the three proposed coding systems is also presented.

  17. Locally orderless registration code

    DEFF Research Database (Denmark)

    2012-01-01

    This is code for the TPAMI paper "Locally Orderless Registration". The code requires intel threadding building blocks installed and is provided for 64 bit on mac, linux and windows.......This is code for the TPAMI paper "Locally Orderless Registration". The code requires intel threadding building blocks installed and is provided for 64 bit on mac, linux and windows....

  18. Algebraic geometric codes

    Science.gov (United States)

    Shahshahani, M.

    1991-01-01

    The performance characteristics are discussed of certain algebraic geometric codes. Algebraic geometric codes have good minimum distance properties. On many channels they outperform other comparable block codes; therefore, one would expect them eventually to replace some of the block codes used in communications systems. It is suggested that it is unlikely that they will become useful substitutes for the Reed-Solomon codes used by the Deep Space Network in the near future. However, they may be applicable to systems where the signal to noise ratio is sufficiently high so that block codes would be more suitable than convolutional or concatenated codes.

  19. Monomial-like codes

    CERN Document Server

    Martinez-Moro, Edgar; Ozbudak, Ferruh; Szabo, Steve

    2010-01-01

    As a generalization of cyclic codes of length p^s over F_{p^a}, we study n-dimensional cyclic codes of length p^{s_1} X ... X p^{s_n} over F_{p^a} generated by a single "monomial". Namely, we study multi-variable cyclic codes of the form in F_{p^a}[x_1...x_n] / . We call such codes monomial-like codes. We show that these codes arise from the product of certain single variable codes and we determine their minimum Hamming distance. We determine the dual of monomial-like codes yielding a parity check matrix. We also present an alternative way of constructing a parity check matrix using the Hasse derivative. We study the weight hierarchy of certain monomial like codes. We simplify an expression that gives us the weight hierarchy of these codes.

  20. QR Codes 101

    Science.gov (United States)

    Crompton, Helen; LaFrance, Jason; van 't Hooft, Mark

    2012-01-01

    A QR (quick-response) code is a two-dimensional scannable code, similar in function to a traditional bar code that one might find on a product at the supermarket. The main difference between the two is that, while a traditional bar code can hold a maximum of only 20 digits, a QR code can hold up to 7,089 characters, so it can contain much more…

  1. Spatiotemporal Coding of Individual Chemicals by the Gustatory System.

    Science.gov (United States)

    Reiter, Sam; Campillo Rodriguez, Chelsey; Sun, Kui; Stopfer, Mark

    2015-09-02

    Four of the five major sensory systems (vision, olfaction, somatosensation, and audition) are thought to use different but partially overlapping sets of neurons to form unique representations of vast numbers of stimuli. The only exception is gustation, which is thought to represent only small numbers of basic taste categories. However, using new methods for delivering tastant chemicals and making electrophysiological recordings from the tractable gustatory system of the moth Manduca sexta, we found chemical-specific information is as follows: (1) initially encoded in the population of gustatory receptor neurons as broadly distributed spatiotemporal patterns of activity; (2) dramatically integrated and temporally transformed as it propagates to monosynaptically connected second-order neurons; and (3) observed in tastant-specific behavior. Our results are consistent with an emerging view of the gustatory system: rather than constructing basic taste categories, it uses a spatiotemporal population code to generate unique neural representations of individual tastant chemicals. Our results provide a new view of taste processing. Using a new, relatively simple model system and a new set of techniques to deliver taste stimuli and to examine gustatory receptor neurons and their immediate followers, we found no evidence for labeled line connectivity, or basic taste categories such as sweet, salty, bitter, and sour. Rather, individual tastant chemicals are represented as patterns of spiking activity distributed across populations of receptor neurons. These representations are transformed substantially as multiple types of receptor neurons converge upon follower neurons, leading to a combinatorial coding format that uniquely, rapidly, and efficiently represents individual taste chemicals. Finally, we found that the information content of these neurons can drive tastant-specific behavior. Copyright © 2015 the authors 0270-6474/15/3512309-13$15.00/0.

  2. Adaptive coding of orofacial and speech actions in motor and somatosensory spaces with and without overt motor behavior.

    Science.gov (United States)

    Sato, Marc; Vilain, Coriandre; Lamalle, Laurent; Grabski, Krystyna

    2015-02-01

    Studies of speech motor control suggest that articulatory and phonemic goals are defined in multidimensional motor, somatosensory, and auditory spaces. To test whether motor simulation might rely on sensory-motor coding common with those for motor execution, we used a repetition suppression (RS) paradigm while measuring neural activity with sparse sampling fMRI during repeated overt and covert orofacial and speech actions. RS refers to the phenomenon that repeated stimuli or motor acts lead to decreased activity in specific neural populations and are associated with enhanced adaptive learning related to the repeated stimulus attributes. Common suppressed neural responses were observed in motor and posterior parietal regions in the achievement of both repeated overt and covert orofacial and speech actions, including the left premotor cortex and inferior frontal gyrus, the superior parietal cortex and adjacent intraprietal sulcus, and the left IC and the SMA. Interestingly, reduced activity of the auditory cortex was observed during overt but not covert speech production, a finding likely reflecting a motor rather an auditory imagery strategy by the participants. By providing evidence for adaptive changes in premotor and associative somatosensory brain areas, the observed RS suggests online state coding of both orofacial and speech actions in somatosensory and motor spaces with and without motor behavior and sensory feedback.

  3. Toward a unified theory of efficient, predictive, and sparse coding.

    Science.gov (United States)

    Chalk, Matthew; Marre, Olivier; Tkačik, Gašper

    2018-01-02

    A central goal in theoretical neuroscience is to predict the response properties of sensory neurons from first principles. To this end, "efficient coding" posits that sensory neurons encode maximal information about their inputs given internal constraints. There exist, however, many variants of efficient coding (e.g., redundancy reduction, different formulations of predictive coding, robust coding, sparse coding, etc.), differing in their regimes of applicability, in the relevance of signals to be encoded, and in the choice of constraints. It is unclear how these types of efficient coding relate or what is expected when different coding objectives are combined. Here we present a unified framework that encompasses previously proposed efficient coding models and extends to unique regimes. We show that optimizing neural responses to encode predictive information can lead them to either correlate or decorrelate their inputs, depending on the stimulus statistics; in contrast, at low noise, efficiently encoding the past always predicts decorrelation. Later, we investigate coding of naturalistic movies and show that qualitatively different types of visual motion tuning and levels of response sparsity are predicted, depending on whether the objective is to recover the past or predict the future. Our approach promises a way to explain the observed diversity of sensory neural responses, as due to multiple functional goals and constraints fulfilled by different cell types and/or circuits.

  4. Genetic Algorithm Optimization of Artificial Neural Networks for Hydrological Modelling

    Science.gov (United States)

    Abrahart, R. J.

    2004-05-01

    operational specialization. The standard approach to neural-evolution is at the network level such that a population of working solutions is manipulated until the fittest member is found. SANE [Symbiotic Adaptive Neuro-Evolution]1 source code offers an alternative method based on co-operative co-evolution in which a population of hidden neurons is evolved. The task of each hidden neuron is to establish appropriate connections that will provide: [i] a functional solution and [ii] performance improvements. Each member of the population attempts to optimize one particular aspect of the overall modelling process and evolution can lead to several different forms of specialization. This method of adaptive evolution also facilitates the creation of symbiotic relationships in which individual members must co-operate with others - who must be present - to permit survival. 1http://www.cs.utexas.edu/users/nn/pages/software/abstracts.html#sane-c

  5. Neural Darwinism and consciousness.

    Science.gov (United States)

    Seth, Anil K; Baars, Bernard J

    2005-03-01

    Neural Darwinism (ND) is a large scale selectionist theory of brain development and function that has been hypothesized to relate to consciousness. According to ND, consciousness is entailed by reentrant interactions among neuronal populations in the thalamocortical system (the 'dynamic core'). These interactions, which permit high-order discriminations among possible core states, confer selective advantages on organisms possessing them by linking current perceptual events to a past history of value-dependent learning. Here, we assess the consistency of ND with 16 widely recognized properties of consciousness, both physiological (for example, consciousness is associated with widespread, relatively fast, low amplitude interactions in the thalamocortical system), and phenomenal (for example, consciousness involves the existence of a private flow of events available only to the experiencing subject). While no theory accounts fully for all of these properties at present, we find that ND and its recent extensions fare well.

  6. Cortical neural prosthetics.

    Science.gov (United States)

    Schwartz, Andrew B

    2004-01-01

    Control of prostheses using cortical signals is based on three elements: chronic microelectrode arrays, extraction algorithms, and prosthetic effectors. Arrays of microelectrodes are permanently implanted in cerebral cortex. These arrays must record populations of single- and multiunit activity indefinitely. Information containing position and velocity correlates of animate movement needs to be extracted continuously in real time from the recorded activity. Prosthetic arms, the current effectors used in this work, need to have the agility and configuration of natural arms. Demonstrations using closed-loop control show that subjects change their neural activity to improve performance with these devices. Adaptive-learning algorithms that capitalize on these improvements show that this technology has the capability of restoring much of the arm movement lost with immobilizing deficits.

  7. How Moral Codes Evolve in a Trust Game

    Directory of Open Access Journals (Sweden)

    Jean Paul Rabanal

    2015-06-01

    Full Text Available This paper analyzes the dynamic stability of moral codes in a two population trust game. Guided by a moral code, members of one population, the Trustors, are willing to punish members of the other population, the Trustees, who defect. Under replicator dynamics, adherence to the moral code has unstable oscillations around an interior Nash Equilibrium (NE, but under smoothed best response dynamics we obtain convergence to Quantal Response Equilibrium (QRE.

  8. TIPONLINE Code Table

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Coded items are entered in the tiponline data entry program. The codes and their explanations are necessary in order to use the data

  9. Coding for optical channels

    CERN Document Server

    Djordjevic, Ivan; Vasic, Bane

    2010-01-01

    This unique book provides a coherent and comprehensive introduction to the fundamentals of optical communications, signal processing and coding for optical channels. It is the first to integrate the fundamentals of coding theory and optical communication.

  10. Introduction to neural networks

    CERN Document Server

    James, Frederick E

    1994-02-02

    1. Introduction and overview of Artificial Neural Networks. 2,3. The Feed-forward Network as an inverse Problem, and results on the computational complexity of network training. 4.Physics applications of neural networks.

  11. Morphological neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Ritter, G.X.; Sussner, P. [Univ. of Florida, Gainesville, FL (United States)

    1996-12-31

    The theory of artificial neural networks has been successfully applied to a wide variety of pattern recognition problems. In this theory, the first step in computing the next state of a neuron or in performing the next layer neural network computation involves the linear operation of multiplying neural values by their synaptic strengths and adding the results. Thresholding usually follows the linear operation in order to provide for nonlinearity of the network. In this paper we introduce a novel class of neural networks, called morphological neural networks, in which the operations of multiplication and addition are replaced by addition and maximum (or minimum), respectively. By taking the maximum (or minimum) of sums instead of the sum of products, morphological network computation is nonlinear before thresholding. As a consequence, the properties of morphological neural networks are drastically different than those of traditional neural network models. In this paper we consider some of these differences and provide some particular examples of morphological neural network.

  12. ARC Code TI: ROC Curve Code Augmentation

    Data.gov (United States)

    National Aeronautics and Space Administration — ROC (Receiver Operating Characteristic) curve Code Augmentation was written by Rodney Martin and John Stutz at NASA Ames Research Center and is a modification of ROC...

  13. Gauge color codes

    DEFF Research Database (Denmark)

    Bombin Palomo, Hector

    2015-01-01

    Color codes are topological stabilizer codes with unusual transversality properties. Here I show that their group of transversal gates is optimal and only depends on the spatial dimension, not the local geometry. I also introduce a generalized, subsystem version of color codes. In 3D they allow...

  14. Refactoring test code

    NARCIS (Netherlands)

    A. van Deursen (Arie); L.M.F. Moonen (Leon); A. van den Bergh; G. Kok

    2001-01-01

    textabstractTwo key aspects of extreme programming (XP) are unit testing and merciless refactoring. Given the fact that the ideal test code / production code ratio approaches 1:1, it is not surprising that unit tests are being refactored. We found that refactoring test code is different from

  15. The Procions` code; Le code Procions

    Energy Technology Data Exchange (ETDEWEB)

    Deck, D.; Samba, G.

    1994-12-19

    This paper presents a new code to simulate plasmas generated by inertial confinement. This multi-kinds kinetic code is done with no angular approximation concerning ions and will work in plan and spherical geometry. First, the physical model is presented, using Fokker-Plank. Then, the numerical model is introduced in order to solve the Fokker-Plank operator under the Rosenbluth form. At the end, several numerical tests are proposed. (TEC). 17 refs., 27 figs.

  16. The materiality of Code

    DEFF Research Database (Denmark)

    Soon, Winnie

    2014-01-01

    , Twitter and Facebook). The focus is not to investigate the functionalities and efficiencies of the code, but to study and interpret the program level of code in order to trace the use of various technological methods such as third-party libraries and platforms’ interfaces. These are important...... to understand the socio-technical side of a changing network environment. Through the study of code, including but not limited to source code, technical specifications and other materials in relation to the artwork production, I would like to explore the materiality of code that goes beyond technical...

  17. Unsupervised clustering with spiking neurons by sparse temporal coding and multi-layer RBF networks

    NARCIS (Netherlands)

    S.M. Bohte (Sander); J.A. La Poutré (Han); J.N. Kok (Joost)

    2000-01-01

    textabstractWe demonstrate that spiking neural networks encoding information in spike times are capable of computing and learning clusters from realistic data. We show how a spiking neural network based on spike-time coding and Hebbian learning can successfully perform unsupervised clustering on

  18. An efficient coding theory for a dynamic trajectory predicts non-uniform allocation of entorhinal grid cells to modules

    Science.gov (United States)

    Mosheiff, Noga; Agmon, Haggai; Moriel, Avraham

    2017-01-01

    Grid cells in the entorhinal cortex encode the position of an animal in its environment with spatially periodic tuning curves with different periodicities. Recent experiments established that these cells are functionally organized in discrete modules with uniform grid spacing. Here we develop a theory for efficient coding of position, which takes into account the temporal statistics of the animal’s motion. The theory predicts a sharp decrease of module population sizes with grid spacing, in agreement with the trend seen in the experimental data. We identify a simple scheme for readout of the grid cell code by neural circuitry, that can match in accuracy the optimal Bayesian decoder. This readout scheme requires persistence over different timescales, depending on the grid cell module. Thus, we propose that the brain may employ an efficient representation of position which takes advantage of the spatiotemporal statistics of the encoded variable, in similarity to the principles that govern early sensory processing. PMID:28628647

  19. Clipboard: Neural coding of temporal information and its topography ...

    Indian Academy of Sciences (India)

    2010-11-09

    Nov 9, 2010 ... Thomas A Terleph1 Raphael Pinaud2. Department of Biology, Sacred Heart University, Fairfield, CT 06825, USA; Departments of Physiology, Geriatric Medicine and Reynolds Oklahoma Center on Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA ...

  20. DLLExternalCode

    Energy Technology Data Exchange (ETDEWEB)

    2014-05-14

    DLLExternalCode is the a general dynamic-link library (DLL) interface for linking GoldSim (www.goldsim.com) with external codes. The overall concept is to use GoldSim as top level modeling software with interfaces to external codes for specific calculations. The DLLExternalCode DLL that performs the linking function is designed to take a list of code inputs from GoldSim, create an input file for the external application, run the external code, and return a list of outputs, read from files created by the external application, back to GoldSim. Instructions for creating the input file, running the external code, and reading the output are contained in an instructions file that is read and interpreted by the DLL.

  1. Noisy Network Coding

    CERN Document Server

    Lim, Sung Hoon; Gamal, Abbas El; Chung, Sae-Young

    2010-01-01

    A noisy network coding scheme for sending multiple sources over a general noisy network is presented. For multi-source multicast networks, the scheme naturally extends both network coding over noiseless networks by Ahlswede, Cai, Li, and Yeung, and compress-forward coding for the relay channel by Cover and El Gamal to general discrete memoryless and Gaussian networks. The scheme also recovers as special cases the results on coding for wireless relay networks and deterministic networks by Avestimehr, Diggavi, and Tse, and coding for wireless erasure networks by Dana, Gowaikar, Palanki, Hassibi, and Effros. The scheme involves message repetition coding, relay signal compression, and simultaneous decoding. Unlike previous compress--forward schemes, where independent messages are sent over multiple blocks, the same message is sent multiple times using independent codebooks as in the network coding scheme for cyclic networks. Furthermore, the relays do not use Wyner--Ziv binning as in previous compress-forward sch...

  2. Simulation of Code Spectrum and Code Flow of Cultured Neuronal Networks.

    Science.gov (United States)

    Tamura, Shinichi; Nishitani, Yoshi; Hosokawa, Chie; Miyoshi, Tomomitsu; Sawai, Hajime

    2016-01-01

    It has been shown that, in cultured neuronal networks on a multielectrode, pseudorandom-like sequences (codes) are detected, and they flow with some spatial decay constant. Each cultured neuronal network is characterized by a specific spectrum curve. That is, we may consider the spectrum curve as a "signature" of its associated neuronal network that is dependent on the characteristics of neurons and network configuration, including the weight distribution. In the present study, we used an integrate-and-fire model of neurons with intrinsic and instantaneous fluctuations of characteristics for performing a simulation of a code spectrum from multielectrodes on a 2D mesh neural network. We showed that it is possible to estimate the characteristics of neurons such as the distribution of number of neurons around each electrode and their refractory periods. Although this process is a reverse problem and theoretically the solutions are not sufficiently guaranteed, the parameters seem to be consistent with those of neurons. That is, the proposed neural network model may adequately reflect the behavior of a cultured neuronal network. Furthermore, such prospect is discussed that code analysis will provide a base of communication within a neural network that will also create a base of natural intelligence.

  3. Neural networks for data compression and invariant image recognition

    Science.gov (United States)

    Gardner, Sheldon

    1989-01-01

    An approach to invariant image recognition (I2R), based upon a model of biological vision in the mammalian visual system (MVS), is described. The complete I2R model incorporates several biologically inspired features: exponential mapping of retinal images, Gabor spatial filtering, and a neural network associative memory. In the I2R model, exponentially mapped retinal images are filtered by a hierarchical set of Gabor spatial filters (GSF) which provide compression of the information contained within a pixel-based image. A neural network associative memory (AM) is used to process the GSF coded images. We describe a 1-D shape function method for coding of scale and rotationally invariant shape information. This method reduces image shape information to a periodic waveform suitable for coding as an input vector to a neural network AM. The shape function method is suitable for near term applications on conventional computing architectures equipped with VLSI FFT chips to provide a rapid image search capability.

  4. Stage-specific control of neural crest stem cell proliferation by the small rho GTPases Cdc42 and Rac1

    DEFF Research Database (Denmark)

    Fuchs, Sebastian; Herzog, Dominik; Sumara, Grzegorz

    2009-01-01

    The neural crest (NC) generates a variety of neural and non-neural tissues during vertebrate development. Both migratory NC cells and their target structures contain cells with stem cell features. Here we show that these populations of neural crest-derived stem cells (NCSCs) are differentially re...

  5. Dual-Coding Theory and Connectionist Lexical Selection

    CERN Document Server

    Wang, Y Y

    1994-01-01

    We introduce the bilingual dual-coding theory as a model for bilingual mental representation. Based on this model, lexical selection neural networks are implemented for a connectionist transfer project in machine translation. This lexical selection approach has two advantages. First, it is learnable. Little human effort on knowledge engineering is required. Secondly, it is psycholinguistically well-founded.

  6. Permutation coding technique for image recognition systems.

    Science.gov (United States)

    Kussul, Ernst M; Baidyk, Tatiana N; Wunsch, Donald C; Makeyev, Oleksandr; Martín, Anabel

    2006-11-01

    A feature extractor and neural classifier for image recognition systems are proposed. The proposed feature extractor is based on the concept of random local descriptors (RLDs). It is followed by the encoder that is based on the permutation coding technique that allows to take into account not only detected features but also the position of each feature on the image and to make the recognition process invariant to small displacements. The combination of RLDs and permutation coding permits us to obtain a sufficiently general description of the image to be recognized. The code generated by the encoder is used as an input data for the neural classifier. Different types of images were used to test the proposed image recognition system. It was tested in the handwritten digit recognition problem, the face recognition problem, and the microobject shape recognition problem. The results of testing are very promising. The error rate for the Modified National Institute of Standards and Technology (MNIST) database is 0.44% and for the Olivetti Research Laboratory (ORL) database it is 0.1%.

  7. Screening for Open Neural Tube Defects.

    Science.gov (United States)

    Krantz, David A; Hallahan, Terrence W; Carmichael, Jonathan B

    2016-06-01

    Biochemical prenatal screening was initiated with the use of maternal serum alpha fetoprotein to screen for open neural tube defects. Screening now includes multiple marker and sequential screening protocols involving serum and ultrasound markers to screen for aneuploidy. Recently cell-free DNA screening for aneuploidy has been initiated, but does not screen for neural tube defects. Although ultrasound is highly effective in identifying neural tube defects in high-risk populations, in decentralized health systems maternal serum screening still plays a significant role. Abnormal maternal serum alpha fetoprotein alone or in combination with other markers may indicate adverse pregnancy outcome in the absence of open neural tube defects. Copyright © 2016 Elsevier Inc. All rights reserved.

  8. The Aesthetics of Coding

    DEFF Research Database (Denmark)

    Andersen, Christian Ulrik

    2007-01-01

    Computer art is often associated with computer-generated expressions (digitally manipulated audio/images in music, video, stage design, media facades, etc.). In recent computer art, however, the code-text itself – not the generated output – has become the artwork (Perl Poetry, ASCII Art, obfuscated...... code, etc.). The presentation relates this artistic fascination of code to a media critique expressed by Florian Cramer, claiming that the graphical interface represents a media separation (of text/code and image) causing alienation to the computer’s materiality. Cramer is thus the voice of a new ‘code...... avant-garde’. In line with Cramer, the artists Alex McLean and Adrian Ward (aka Slub) declare: “art-oriented programming needs to acknowledge the conditions of its own making – its poesis.” By analysing the Live Coding performances of Slub (where they program computer music live), the presentation...

  9. Opening up codings?

    DEFF Research Database (Denmark)

    Steensig, Jakob; Heinemann, Trine

    2015-01-01

    doing formal coding and when doing more “traditional” conversation analysis research based on collections. We are more wary, however, of the implication that coding-based research is the end result of a process that starts with qualitative investigations and ends with categories that can be coded......We welcome Tanya Stivers’s discussion (Stivers, 2015/this issue) of coding social interaction and find that her descriptions of the processes of coding open up important avenues for discussion, among other things of the precise ad hoc considerations that researchers need to bear in mind, both when....... Instead we propose that the promise of coding-based research lies in its ability to open up new qualitative questions....

  10. Overview of Code Verification

    Science.gov (United States)

    1983-01-01

    The verified code for the SIFT Executive is not the code that executes on the SIFT system as delivered. The running versions of the SIFT Executive contain optimizations and special code relating to the messy interface to the hardware broadcast interface and to packing of data to conserve space in the store of the BDX930 processors. The running code was in fact developed prior to and without consideration of any mechanical verification. This was regarded as necessary experimentation with the SIFT hardware and special purpose Pascal compiler. The Pascal code sections cover: the selection of a schedule from the global executive broadcast, scheduling, dispatching, three way voting, and error reporting actions of the SIFT Executive. Not included in these sections of Pascal code are: the global executive, five way voting, clock synchronization, interactive consistency, low level broadcasting, and program loading, initialization, and schedule construction.

  11. Phonological coding during reading

    Science.gov (United States)

    Leinenger, Mallorie

    2014-01-01

    The exact role that phonological coding (the recoding of written, orthographic information into a sound based code) plays during silent reading has been extensively studied for more than a century. Despite the large body of research surrounding the topic, varying theories as to the time course and function of this recoding still exist. The present review synthesizes this body of research, addressing the topics of time course and function in tandem. The varying theories surrounding the function of phonological coding (e.g., that phonological codes aid lexical access, that phonological codes aid comprehension and bolster short-term memory, or that phonological codes are largely epiphenomenal in skilled readers) are first outlined, and the time courses that each maps onto (e.g., that phonological codes come online early (pre-lexical) or that phonological codes come online late (post-lexical)) are discussed. Next the research relevant to each of these proposed functions is reviewed, discussing the varying methodologies that have been used to investigate phonological coding (e.g., response time methods, reading while eyetracking or recording EEG and MEG, concurrent articulation) and highlighting the advantages and limitations of each with respect to the study of phonological coding. In response to the view that phonological coding is largely epiphenomenal in skilled readers, research on the use of phonological codes in prelingually, profoundly deaf readers is reviewed. Finally, implications for current models of word identification (activation-verification model (Van Order, 1987), dual-route model (e.g., Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001), parallel distributed processing model (Seidenberg & McClelland, 1989)) are discussed. PMID:25150679

  12. The aeroelastic code FLEXLAST

    Energy Technology Data Exchange (ETDEWEB)

    Visser, B. [Stork Product Eng., Amsterdam (Netherlands)

    1996-09-01

    To support the discussion on aeroelastic codes, a description of the code FLEXLAST was given and experiences within benchmarks and measurement programmes were summarized. The code FLEXLAST has been developed since 1982 at Stork Product Engineering (SPE). Since 1992 FLEXLAST has been used by Dutch industries for wind turbine and rotor design. Based on the comparison with measurements, it can be concluded that the main shortcomings of wind turbine modelling lie in the field of aerodynamics, wind field and wake modelling. (au)

  13. Generating code adapted for interlinking legacy scalar code and extended vector code

    Science.gov (United States)

    Gschwind, Michael K

    2013-06-04

    Mechanisms for intermixing code are provided. Source code is received for compilation using an extended Application Binary Interface (ABI) that extends a legacy ABI and uses a different register configuration than the legacy ABI. First compiled code is generated based on the source code, the first compiled code comprising code for accommodating the difference in register configurations used by the extended ABI and the legacy ABI. The first compiled code and second compiled code are intermixed to generate intermixed code, the second compiled code being compiled code that uses the legacy ABI. The intermixed code comprises at least one call instruction that is one of a call from the first compiled code to the second compiled code or a call from the second compiled code to the first compiled code. The code for accommodating the difference in register configurations is associated with the at least one call instruction.

  14. Decoding of Cyclic Codes,

    Science.gov (United States)

    INFORMATION THEORY, *DECODING), (* DATA TRANSMISSION SYSTEMS , DECODING), STATISTICAL ANALYSIS, STOCHASTIC PROCESSES, CODING, WHITE NOISE, NUMBER THEORY, CORRECTIONS, BINARY ARITHMETIC, SHIFT REGISTERS, CONTROL SYSTEMS, USSR

  15. ARC Code TI: ACCEPT

    Data.gov (United States)

    National Aeronautics and Space Administration — ACCEPT consists of an overall software infrastructure framework and two main software components. The software infrastructure framework consists of code written to...

  16. Diameter Perfect Lee Codes

    CERN Document Server

    Horak, Peter

    2011-01-01

    Lee codes have been intensively studied for more than 40 years. Interest in these codes has been triggered by the Golomb-Welch conjecture on the existence of perfect error-correcting Lee codes. In this paper we deal with the existence and enumeration of diameter perfect Lee codes. As main results we determine all q for which there exists a linear diameter-4 perfect Lee code of word length n over Z_{q}, and prove that for each n\\geq3 there are unaccountably many diameter-4 perfect Lee codes of word length n over Z. This is in a strict contrast with perfect error-correcting Lee codes of word length n over Z as there is a unique such code for n=3, and its is conjectured that this is always the case when 2n+1 is a prime. Diameter perfect Lee codes will be constructed by an algebraic construction that is based on a group homomorphism. This will allow us to design an efficient algorithm for their decoding.

  17. Expander chunked codes

    Science.gov (United States)

    Tang, Bin; Yang, Shenghao; Ye, Baoliu; Yin, Yitong; Lu, Sanglu

    2015-12-01

    Chunked codes are efficient random linear network coding (RLNC) schemes with low computational cost, where the input packets are encoded into small chunks (i.e., subsets of the coded packets). During the network transmission, RLNC is performed within each chunk. In this paper, we first introduce a simple transfer matrix model to characterize the transmission of chunks and derive some basic properties of the model to facilitate the performance analysis. We then focus on the design of overlapped chunked codes, a class of chunked codes whose chunks are non-disjoint subsets of input packets, which are of special interest since they can be encoded with negligible computational cost and in a causal fashion. We propose expander chunked (EC) codes, the first class of overlapped chunked codes that have an analyzable performance, where the construction of the chunks makes use of regular graphs. Numerical and simulation results show that in some practical settings, EC codes can achieve rates within 91 to 97 % of the optimum and outperform the state-of-the-art overlapped chunked codes significantly.

  18. QR codes for dummies

    CERN Document Server

    Waters, Joe

    2012-01-01

    Find out how to effectively create, use, and track QR codes QR (Quick Response) codes are popping up everywhere, and businesses are reaping the rewards. Get in on the action with the no-nonsense advice in this streamlined, portable guide. You'll find out how to get started, plan your strategy, and actually create the codes. Then you'll learn to link codes to mobile-friendly content, track your results, and develop ways to give your customers value that will keep them coming back. It's all presented in the straightforward style you've come to know and love, with a dash of humor thrown

  19. Identifying temporal codes in spontaneously active sensory neurons.

    Directory of Open Access Journals (Sweden)

    Alexander B Neiman

    Full Text Available The manner in which information is encoded in neural signals is a major issue in Neuroscience. A common distinction is between rate codes, where information in neural responses is encoded as the number of spikes within a specified time frame (encoding window, and temporal codes, where the position of spikes within the encoding window carries some or all of the information about the stimulus. One test for the existence of a temporal code in neural responses is to add artificial time jitter to each spike in the response, and then assess whether or not information in the response has been degraded. If so, temporal encoding might be inferred, on the assumption that the jitter is small enough to alter the position, but not the number, of spikes within the encoding window. Here, the effects of artificial jitter on various spike train and information metrics were derived analytically, and this theory was validated using data from afferent neurons of the turtle vestibular and paddlefish electrosensory systems, and from model neurons. We demonstrate that the jitter procedure will degrade information content even when coding is known to be entirely by rate. For this and additional reasons, we conclude that the jitter procedure by itself is not sufficient to establish the presence of a temporal code.

  20. On {\\sigma}-LCD codes

    OpenAIRE

    Carlet, Claude; Mesnager, Sihem; Tang, Chunming; Qi, Yanfeng

    2017-01-01

    Linear complementary pairs (LCP) of codes play an important role in armoring implementations against side-channel attacks and fault injection attacks. One of the most common ways to construct LCP of codes is to use Euclidean linear complementary dual (LCD) codes. In this paper, we first introduce the concept of linear codes with $\\sigma$ complementary dual ($\\sigma$-LCD), which includes known Euclidean LCD codes, Hermitian LCD codes, and Galois LCD codes. As Euclidean LCD codes, $\\sigma$-LCD ...

  1. Identifying personal microbiomes using metagenomic codes.

    Science.gov (United States)

    Franzosa, Eric A; Huang, Katherine; Meadow, James F; Gevers, Dirk; Lemon, Katherine P; Bohannan, Brendan J M; Huttenhower, Curtis

    2015-06-02

    Community composition within the human microbiome varies across individuals, but it remains unknown if this variation is sufficient to uniquely identify individuals within large populations or stable enough to identify them over time. We investigated this by developing a hitting set-based coding algorithm and applying it to the Human Microbiome Project population. Our approach defined body site-specific metagenomic codes: sets of microbial taxa or genes prioritized to uniquely and stably identify individuals. Codes capturing strain variation in clade-specific marker genes were able to distinguish among 100s of individuals at an initial sampling time point. In comparisons with follow-up samples collected 30-300 d later, ∼30% of individuals could still be uniquely pinpointed using metagenomic codes from a typical body site; coincidental (false positive) matches were rare. Codes based on the gut microbiome were exceptionally stable and pinpointed >80% of individuals. The failure of a code to match its owner at a later time point was largely explained by the loss of specific microbial strains (at current limits of detection) and was only weakly associated with the length of the sampling interval. In addition to highlighting patterns of temporal variation in the ecology of the human microbiome, this work demonstrates the feasibility of microbiome-based identifiability-a result with important ethical implications for microbiome study design. The datasets and code used in this work are available for download from huttenhower.sph.harvard.edu/idability.

  2. Consciousness and neural plasticity

    DEFF Research Database (Denmark)

    In contemporary consciousness studies the phenomenon of neural plasticity has received little attention despite the fact that neural plasticity is of still increased interest in neuroscience. We will, however, argue that neural plasticity could be of great importance to consciousness studies....... If consciousness is related to neural processes it seems, at least prima facie, that the ability of the neural structures to change should be reflected in a theory of this relationship "Neural plasticity" refers to the fact that the brain can change due to its own activity. The brain is not static but rather...... a dynamic entity, which physical structure changes according to its use and environment. This change may take the form of growth of new neurons, the creation of new networks and structures, and change within network structures, that is, changes in synaptic strengths. Plasticity raises questions about...

  3. Scrum Code Camps

    DEFF Research Database (Denmark)

    Pries-Heje, Jan; Pries-Heje, Lene; Dahlgaard, Bente

    2013-01-01

    is required. In this paper we present the design of such a new approach, the Scrum Code Camp, which can be used to assess agile team capability in a transparent and consistent way. A design science research approach is used to analyze properties of two instances of the Scrum Code Camp where seven agile teams...

  4. Error Correcting Codes

    Indian Academy of Sciences (India)

    be fixed to define codes over such domains). New decoding schemes that take advantage of such connections can be devised. These may soon show up in a technique called code division multiple access (CDMA) which is proposed as a basis for digital cellular communication. CDMA provides a facility for many users to ...

  5. Codes of Conduct

    Science.gov (United States)

    Million, June

    2004-01-01

    Most schools have a code of conduct, pledge, or behavioral standards, set by the district or school board with the school community. In this article, the author features some schools that created a new vision of instilling code of conducts to students based on work quality, respect, safety and courtesy. She suggests that communicating the code…

  6. Error Correcting Codes

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 3. Error Correcting Codes - Reed Solomon Codes. Priti Shankar. Series Article Volume 2 Issue 3 March 1997 pp 33-47. Fulltext. Click here to view fulltext PDF. Permanent link: http://www.ias.ac.in/article/fulltext/reso/002/03/0033-0047 ...

  7. Code Generation = A* + BURS

    NARCIS (Netherlands)

    Nymeyer, Albert; Katoen, Joost P.; Westra, Ymte; Alblas, H.; Gyimóthy, Tibor

    1996-01-01

    A system called BURS that is based on term rewrite systems and a search algorithm A* are combined to produce a code generator that generates optimal code. The theory underlying BURS is re-developed, formalised and explained in this work. The search algorithm uses a cost heuristic that is derived

  8. Dress Codes for Teachers?

    Science.gov (United States)

    Million, June

    2004-01-01

    In this article, the author discusses an e-mail survey of principals from across the country regarding whether or not their school had a formal staff dress code. The results indicate that most did not have a formal dress code, but agreed that professional dress for teachers was not only necessary, but showed respect for the school and had a…

  9. Informal control code logic

    NARCIS (Netherlands)

    Bergstra, J.A.

    2010-01-01

    General definitions as well as rules of reasoning regarding control code production, distribution, deployment, and usage are described. The role of testing, trust, confidence and risk analysis is considered. A rationale for control code testing is sought and found for the case of safety critical

  10. Interleaved Product LDPC Codes

    OpenAIRE

    Baldi, Marco; Cancellieri, Giovanni; Chiaraluce, Franco

    2011-01-01

    Product LDPC codes take advantage of LDPC decoding algorithms and the high minimum distance of product codes. We propose to add suitable interleavers to improve the waterfall performance of LDPC decoding. Interleaving also reduces the number of low weight codewords, that gives a further advantage in the error floor region.

  11. Nuremberg code turns 60

    OpenAIRE

    Thieren, Michel; Mauron, Alexandre

    2007-01-01

    This month marks sixty years since the Nuremberg code – the basic text of modern medical ethics – was issued. The principles in this code were articulated in the context of the Nuremberg trials in 1947. We would like to use this anniversary to examine its ability to address the ethical challenges of our time.

  12. Error Correcting Codes

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 1. Error Correcting Codes The Hamming Codes. Priti Shankar. Series Article Volume 2 Issue 1 January ... Author Affiliations. Priti Shankar1. Department of Computer Science and Automation, Indian Institute of Science, Bangalore 560 012, India ...

  13. Fuzzy and neural control

    Science.gov (United States)

    Berenji, Hamid R.

    1992-01-01

    Fuzzy logic and neural networks provide new methods for designing control systems. Fuzzy logic controllers do not require a complete analytical model of a dynamic system and can provide knowledge-based heuristic controllers for ill-defined and complex systems. Neural networks can be used for learning control. In this chapter, we discuss hybrid methods using fuzzy logic and neural networks which can start with an approximate control knowledge base and refine it through reinforcement learning.

  14. Design of FPGA Based Neural Network Controller for Earth Station Power System

    OpenAIRE

    Hassen T. Dorrah; Ninet M. A. El-Rahman; Faten H. Fahmy; Hanaa T. El-Madany

    2012-01-01

    Automation of generating hardware description language code from neural networks models can highly decrease time of implementation those networks into a digital devices, thus significant money savings. To implement the neural network into hardware designer, it is required to translate generated model into device structure. VHDL language is used to describe those networks into hardware. VHDL code has been proposed to implement ANNs as well as to present simulation results with floating point a...

  15. What Is Neural Plasticity?

    Science.gov (United States)

    von Bernhardi, Rommy; Bernhardi, Laura Eugenín-von; Eugenín, Jaime

    2017-01-01

    "Neural plasticity" refers to the capacity of the nervous system to modify itself, functionally and structurally, in response to experience and injury. As the various chapters in this volume show, plasticity is a key component of neural development and normal functioning of the nervous system, as well as a response to the changing environment, aging, or pathological insult. This chapter discusses how plasticity is necessary not only for neural networks to acquire new functional properties, but also for them to remain robust and stable. The article also reviews the seminal proposals developed over the years that have driven experiments and strongly influenced concepts of neural plasticity.

  16. Neural Systems Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — As part of the Electrical and Computer Engineering Department and The Institute for System Research, the Neural Systems Laboratory studies the functionality of the...

  17. A neural flow estimator

    DEFF Research Database (Denmark)

    Jørgensen, Ivan Harald Holger; Bogason, Gudmundur; Bruun, Erik

    1995-01-01

    is implemented using switched-current technique and is capable of estimating flow in the μl/s range. The neural estimator is built around a multiplierless neural network, containing 96 synaptic weights which are updated using the LMS1-algorithm. An experimental chip has been designed that operates at 5 V......This paper proposes a new way to estimate the flow in a micromechanical flow channel. A neural network is used to estimate the delay of random temperature fluctuations induced in a fluid. The design and implementation of a hardware efficient neural flow estimator is described. The system...

  18. Evaluation Codes from an Affine Veriety Code Perspective

    DEFF Research Database (Denmark)

    Geil, Hans Olav

    2008-01-01

    Evaluation codes (also called order domain codes) are traditionally introduced as generalized one-point geometric Goppa codes. In the present paper we will give a new point of view on evaluation codes by introducing them instead as particular nice examples of affine variety codes. Our study...... . . . . . . . . . . . . . . . . . . . . . . . 171 4.9 Codes form order domains . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 4.10 One-point geometric Goppa codes . . . . . . . . . . . . . . . . . . . . . . . . 176 4.11 Bibliographical Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178 References...

  19. Quantum Synchronizable Codes From Quadratic Residue Codes and Their Supercodes

    OpenAIRE

    Xie, Yixuan; Yuan, Jinhong; Fujiwara, Yuichiro

    2014-01-01

    Quantum synchronizable codes are quantum error-correcting codes designed to correct the effects of both quantum noise and block synchronization errors. While it is known that quantum synchronizable codes can be constructed from cyclic codes that satisfy special properties, only a few classes of cyclic codes have been proved to give promising quantum synchronizable codes. In this paper, using quadratic residue codes and their supercodes, we give a simple construction for quantum synchronizable...

  20. Membrane Biophysics Define Neuron and Astrocyte Progenitors in the Neural Lineage

    National Research Council Canada - National Science Library

    Nourse, J.L; Prieto, J.L; Dickson, A.R; Lu, J; Pathak, M.M; Tombola, F; Demetriou, M; Lee, A.P; Flanagan, L.A

    2014-01-01

    Neural stem and progenitor cells (NSPCs) are heterogeneous populations of self‐renewing stem cells and more committed progenitors that differentiate into neurons, astrocytes, and oligodendrocytes...

  1. An overview of Bayesian methods for neural spike train analysis.

    Science.gov (United States)

    Chen, Zhe

    2013-01-01

    Neural spike train analysis is an important task in computational neuroscience which aims to understand neural mechanisms and gain insights into neural circuits. With the advancement of multielectrode recording and imaging technologies, it has become increasingly demanding to develop statistical tools for analyzing large neuronal ensemble spike activity. Here we present a tutorial overview of Bayesian methods and their representative applications in neural spike train analysis, at both single neuron and population levels. On the theoretical side, we focus on various approximate Bayesian inference techniques as applied to latent state and parameter estimation. On the application side, the topics include spike sorting, tuning curve estimation, neural encoding and decoding, deconvolution of spike trains from calcium imaging signals, and inference of neuronal functional connectivity and synchrony. Some research challenges and opportunities for neural spike train analysis are discussed.

  2. An Overview of Bayesian Methods for Neural Spike Train Analysis

    Directory of Open Access Journals (Sweden)

    Zhe Chen

    2013-01-01

    Full Text Available Neural spike train analysis is an important task in computational neuroscience which aims to understand neural mechanisms and gain insights into neural circuits. With the advancement of multielectrode recording and imaging technologies, it has become increasingly demanding to develop statistical tools for analyzing large neuronal ensemble spike activity. Here we present a tutorial overview of Bayesian methods and their representative applications in neural spike train analysis, at both single neuron and population levels. On the theoretical side, we focus on various approximate Bayesian inference techniques as applied to latent state and parameter estimation. On the application side, the topics include spike sorting, tuning curve estimation, neural encoding and decoding, deconvolution of spike trains from calcium imaging signals, and inference of neuronal functional connectivity and synchrony. Some research challenges and opportunities for neural spike train analysis are discussed.

  3. Central neural pathways for thermoregulation

    Science.gov (United States)

    Morrison, Shaun F.; Nakamura, Kazuhiro

    2010-01-01

    Central neural circuits orchestrate a homeostatic repertoire to maintain body temperature during environmental temperature challenges and to alter body temperature during the inflammatory response. This review summarizes the functional organization of the neural pathways through which cutaneous thermal receptors alter thermoregulatory effectors: the cutaneous circulation for heat loss, the brown adipose tissue, skeletal muscle and heart for thermogenesis and species-dependent mechanisms (sweating, panting and saliva spreading) for evaporative heat loss. These effectors are regulated by parallel but distinct, effector-specific neural pathways that share a common peripheral thermal sensory input. The thermal afferent circuits include cutaneous thermal receptors, spinal dorsal horn neurons and lateral parabrachial nucleus neurons projecting to the preoptic area to influence warm-sensitive, inhibitory output neurons which control thermogenesis-promoting neurons in the dorsomedial hypothalamus that project to premotor neurons in the rostral ventromedial medulla, including the raphe pallidus, that descend to provide the excitation necessary to drive thermogenic thermal effectors. A distinct population of warm-sensitive preoptic neurons controls heat loss through an inhibitory input to raphe pallidus neurons controlling cutaneous vasoconstriction. PMID:21196160

  4. Convolutional Neural Networks - Generalizability and Interpretations

    DEFF Research Database (Denmark)

    Malmgren-Hansen, David

    from data despite it being limited in amount or context representation. Within Machine Learning this thesis focuses on Convolutional Neural Networks for Computer Vision. The research aims to answer how to explore a model's generalizability to the whole population of data samples and how to interpret...

  5. Neural Networks: Implementations and Applications

    NARCIS (Netherlands)

    Vonk, E.; Veelenturf, L.P.J.; Jain, L.C.

    1996-01-01

    Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas

  6. Pyramid image codes

    Science.gov (United States)

    Watson, Andrew B.

    1990-01-01

    All vision systems, both human and machine, transform the spatial image into a coded representation. Particular codes may be optimized for efficiency or to extract useful image features. Researchers explored image codes based on primary visual cortex in man and other primates. Understanding these codes will advance the art in image coding, autonomous vision, and computational human factors. In cortex, imagery is coded by features that vary in size, orientation, and position. Researchers have devised a mathematical model of this transformation, called the Hexagonal oriented Orthogonal quadrature Pyramid (HOP). In a pyramid code, features are segregated by size into layers, with fewer features in the layers devoted to large features. Pyramid schemes provide scale invariance, and are useful for coarse-to-fine searching and for progressive transmission of images. The HOP Pyramid is novel in three respects: (1) it uses a hexagonal pixel lattice, (2) it uses oriented features, and (3) it accurately models most of the prominent aspects of primary visual cortex. The transform uses seven basic features (kernels), which may be regarded as three oriented edges, three oriented bars, and one non-oriented blob. Application of these kernels to non-overlapping seven-pixel neighborhoods yields six oriented, high-pass pyramid layers, and one low-pass (blob) layer.

  7. Report number codes

    Energy Technology Data Exchange (ETDEWEB)

    Nelson, R.N. (ed.)

    1985-05-01

    This publication lists all report number codes processed by the Office of Scientific and Technical Information. The report codes are substantially based on the American National Standards Institute, Standard Technical Report Number (STRN)-Format and Creation Z39.23-1983. The Standard Technical Report Number (STRN) provides one of the primary methods of identifying a specific technical report. The STRN consists of two parts: The report code and the sequential number. The report code identifies the issuing organization, a specific program, or a type of document. The sequential number, which is assigned in sequence by each report issuing entity, is not included in this publication. Part I of this compilation is alphabetized by report codes followed by issuing installations. Part II lists the issuing organization followed by the assigned report code(s). In both Parts I and II, the names of issuing organizations appear for the most part in the form used at the time the reports were issued. However, for some of the more prolific installations which have had name changes, all entries have been merged under the current name.

  8. Cellular adaptation facilitates sparse and reliable coding in sensory pathways.

    Science.gov (United States)

    Farkhooi, Farzad; Froese, Anja; Muller, Eilif; Menzel, Randolf; Nawrot, Martin P

    2013-01-01

    Most neurons in peripheral sensory pathways initially respond vigorously when a preferred stimulus is presented, but adapt as stimulation continues. It is unclear how this phenomenon affects stimulus coding in the later stages of sensory processing. Here, we show that a temporally sparse and reliable stimulus representation develops naturally in sequential stages of a sensory network with adapting neurons. As a modeling framework we employ a mean-field approach together with an adaptive population density treatment, accompanied by numerical simulations of spiking neural networks. We find that cellular adaptation plays a critical role in the dynamic reduction of the trial-by-trial variability of cortical spike responses by transiently suppressing self-generated fast fluctuations in the cortical balanced network. This provides an explanation for a widespread cortical phenomenon by a simple mechanism. We further show that in the insect olfactory system cellular adaptation is sufficient to explain the emergence of the temporally sparse and reliable stimulus representation in the mushroom body. Our results reveal a generic, biophysically plausible mechanism that can explain the emergence of a temporally sparse and reliable stimulus representation within a sequential processing architecture.

  9. Neural crest development in fetal alcohol syndrome.

    Science.gov (United States)

    Smith, Susan M; Garic, Ana; Flentke, George R; Berres, Mark E

    2014-09-01

    Fetal alcohol spectrum disorder (FASD) is a leading cause of neurodevelopmental disability. Some affected individuals possess distinctive craniofacial deficits, but many more lack overt facial changes. An understanding of the mechanisms underlying these deficits would inform their diagnostic utility. Our understanding of these mechanisms is challenged because ethanol lacks a single receptor when redirecting cellular activity. This review summarizes our current understanding of how ethanol alters neural crest development. Ample evidence shows that ethanol causes the "classic" fetal alcohol syndrome (FAS) face (short palpebral fissures, elongated upper lip, deficient philtrum) because it suppresses prechordal plate outgrowth, thereby reducing neuroectoderm and neural crest induction and causing holoprosencephaly. Prenatal alcohol exposure (PAE) at premigratory stages elicits a different facial appearance, indicating FASD may represent a spectrum of facial outcomes. PAE at this premigratory period initiates a calcium transient that activates CaMKII and destabilizes transcriptionally active β-catenin, thereby initiating apoptosis within neural crest populations. Contributing to neural crest vulnerability are their low antioxidant responses. Ethanol-treated neural crest produce reactive oxygen species and free radical scavengers attenuate their production and prevent apoptosis. Ethanol also significantly impairs neural crest migration, causing cytoskeletal rearrangements that destabilize focal adhesion formation; their directional migratory capacity is also lost. Genetic factors further modify vulnerability to ethanol-induced craniofacial dysmorphology and include genes important for neural crest development, including shh signaling, PDFGA, vangl2, and ribosomal biogenesis. Because facial and brain development are mechanistically and functionally linked, research into ethanol's effects on neural crest also informs our understanding of ethanol's CNS pathologies. © 2014

  10. Cryptography cracking codes

    CERN Document Server

    2014-01-01

    While cracking a code might seem like something few of us would encounter in our daily lives, it is actually far more prevalent than we may realize. Anyone who has had personal information taken because of a hacked email account can understand the need for cryptography and the importance of encryption-essentially the need to code information to keep it safe. This detailed volume examines the logic and science behind various ciphers, their real world uses, how codes can be broken, and the use of technology in this oft-overlooked field.

  11. Quantum coding theorems

    Science.gov (United States)

    Holevo, A. S.

    1998-12-01

    ContentsI. IntroductionII. General considerations § 1. Quantum communication channel § 2. Entropy bound and channel capacity § 3. Formulation of the quantum coding theorem. Weak conversionIII. Proof of the direct statement of the coding theorem § 1. Channels with pure signal states § 2. Reliability function § 3. Quantum binary channel § 4. Case of arbitrary states with bounded entropyIV. c-q channels with input constraints § 1. Coding theorem § 2. Gauss channel with one degree of freedom § 3. Classical signal on quantum background noise Bibliography

  12. Critical Branching Neural Networks

    Science.gov (United States)

    Kello, Christopher T.

    2013-01-01

    It is now well-established that intrinsic variations in human neural and behavioral activity tend to exhibit scaling laws in their fluctuations and distributions. The meaning of these scaling laws is an ongoing matter of debate between isolable causes versus pervasive causes. A spiking neural network model is presented that self-tunes to critical…

  13. Kunstige neurale net

    DEFF Research Database (Denmark)

    Hørning, Annette

    1994-01-01

    Artiklen beskæftiger sig med muligheden for at anvende kunstige neurale net i forbindelse med datamatisk procession af naturligt sprog, specielt automatisk talegenkendelse.......Artiklen beskæftiger sig med muligheden for at anvende kunstige neurale net i forbindelse med datamatisk procession af naturligt sprog, specielt automatisk talegenkendelse....

  14. Noise activated bistable sensor based on chaotic system with output defined by temporal coding and firing rate

    Science.gov (United States)

    Korneta, Wojciech; Gomes, Iacyel

    2017-11-01

    Traditional bistable sensors use external bias signal to drive its response between states and their detection strategy is based on the output power spectral density or the residence time difference (RTD) in two sensor states. Recently, the noise activated nonlinear dynamic sensors driven only by noise based on RTD technique have been proposed. Here, we present experimental results of dc voltage measurements by noise-driven bistable sensor based on electronic Chua's circuit operating in a chaotic regime where two single scroll attractors coexist. The output of the sensor is quantified by the proportion of the time the sensor stays in one state to the total observation time and by the spike-count rate with spikes defined by crossings between attractors. The relationship between the stimuli and particular observable for different noise intensities is obtained, the usefulness of each coding scheme is discussed, and the optimal noise intensity for detection is indicated. It is shown that the obtained relationship is the same for any observation time when population coding is used. The optimal time window for both detection and the number of units in population coding is found. Our results may be useful for analyses and understanding of the neural activity and in designing bistable storage elements at length scales where thermal fluctuations drastically increase and the effect of noise must be taken into consideration.

  15. Fulcrum Network Codes

    DEFF Research Database (Denmark)

    2015-01-01

    Fulcrum network codes, which are a network coding framework, achieve three objectives: (i) to reduce the overhead per coded packet to almost 1 bit per source packet; (ii) to operate the network using only low field size operations at intermediate nodes, dramatically reducing complexity...... in the network; and (iii) to deliver an end-to-end performance that is close to that of a high field size network coding system for high-end receivers while simultaneously catering to low-end ones that can only decode in a lower field size. Sources may encode using a high field size expansion to increase...... the number of dimensions seen by the network using a linear mapping. Receivers can tradeoff computational effort with network delay, decoding in the high field size, the low field size, or a combination thereof....

  16. VT ZIP Code Areas

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) A ZIP Code Tabulation Area (ZCTA) is a statistical geographic entity that approximates the delivery area for a U.S. Postal Service five-digit...

  17. Bandwidth efficient coding

    CERN Document Server

    Anderson, John B

    2017-01-01

    Bandwidth Efficient Coding addresses the major challenge in communication engineering today: how to communicate more bits of information in the same radio spectrum. Energy and bandwidth are needed to transmit bits, and bandwidth affects capacity the most. Methods have been developed that are ten times as energy efficient at a given bandwidth consumption as simple methods. These employ signals with very complex patterns and are called "coding" solutions. The book begins with classical theory before introducing new techniques that combine older methods of error correction coding and radio transmission in order to create narrowband methods that are as efficient in both spectrum and energy as nature allows. Other topics covered include modulation techniques such as CPM, coded QAM and pulse design.

  18. OCA Code Enforcement

    Data.gov (United States)

    Montgomery County of Maryland — The Office of the County Attorney (OCA) processes Code Violation Citations issued by County agencies. The citations can be viewed by issued department, issued date...

  19. Coded Random Access

    DEFF Research Database (Denmark)

    Paolini, Enrico; Stefanovic, Cedomir; Liva, Gianluigi

    2015-01-01

    , in which the structure of the access protocol can be mapped to a structure of an erasure-correcting code defined on graph. This opens the possibility to use coding theory and tools for designing efficient random access protocols, offering markedly better performance than ALOHA. Several instances of coded......The rise of machine-to-machine communications has rekindled the interest in random access protocols as a support for a massive number of uncoordinatedly transmitting devices. The legacy ALOHA approach is developed under a collision model, where slots containing collided packets are considered...... as waste. However, if the common receiver (e.g., base station) is capable to store the collision slots and use them in a transmission recovery process based on successive interference cancellation, the design space for access protocols is radically expanded. We present the paradigm of coded random access...

  20. Code Disentanglement: Initial Plan

    Energy Technology Data Exchange (ETDEWEB)

    Wohlbier, John Greaton [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Kelley, Timothy M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Rockefeller, Gabriel M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Calef, Matthew Thomas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2015-01-27

    The first step to making more ambitious changes in the EAP code base is to disentangle the code into a set of independent, levelized packages. We define a package as a collection of code, most often across a set of files, that provides a defined set of functionality; a package a) can be built and tested as an entity and b) fits within an overall levelization design. Each package contributes one or more libraries, or an application that uses the other libraries. A package set is levelized if the relationships between packages form a directed, acyclic graph and each package uses only packages at lower levels of the diagram (in Fortran this relationship is often describable by the use relationship between modules). Independent packages permit independent- and therefore parallel|development. The packages form separable units for the purposes of development and testing. This is a proven path for enabling finer-grained changes to a complex code.

  1. The fast code

    Energy Technology Data Exchange (ETDEWEB)

    Freeman, L.N.; Wilson, R.E. [Oregon State Univ., Dept. of Mechanical Engineering, Corvallis, OR (United States)

    1996-09-01

    The FAST Code which is capable of determining structural loads on a flexible, teetering, horizontal axis wind turbine is described and comparisons of calculated loads with test data are given at two wind speeds for the ESI-80. The FAST Code models a two-bladed HAWT with degrees of freedom for blade bending, teeter, drive train flexibility, yaw, and windwise and crosswind tower motion. The code allows blade dimensions, stiffnesses, and weights to differ and models tower shadow, wind shear, and turbulence. Additionally, dynamic stall is included as are delta-3 and an underslung rotor. Load comparisons are made with ESI-80 test data in the form of power spectral density, rainflow counting, occurrence histograms, and azimuth averaged bin plots. It is concluded that agreement between the FAST Code and test results is good. (au)

  2. Coded Splitting Tree Protocols

    DEFF Research Database (Denmark)

    Sørensen, Jesper Hemming; Stefanovic, Cedomir; Popovski, Petar

    2013-01-01

    This paper presents a novel approach to multiple access control called coded splitting tree protocol. The approach builds on the known tree splitting protocols, code structure and successive interference cancellation (SIC). Several instances of the tree splitting protocol are initiated, each...... as possible. Evaluations show that the proposed protocol provides considerable gains over the standard tree splitting protocol applying SIC. The improvement comes at the expense of an increased feedback and receiver complexity....

  3. Code de conduite

    International Development Research Centre (IDRC) Digital Library (Canada)

    irocca

    son point de vue, dans un esprit d'accueil et de respect. NOTRE CODE DE CONDUITE. Le CRDI s'engage à adopter un comportement conforme aux normes d'éthique les plus strictes dans toutes ses activités. Le Code de conduite reflète notre mission, notre philosophie en matière d'emploi et les résultats des discussions ...

  4. Open Coding Descriptions

    Directory of Open Access Journals (Sweden)

    Barney G. Glaser, PhD, Hon PhD

    2016-12-01

    Full Text Available Open coding is a big source of descriptions that must be managed and controlled when doing GT research. The goal of generating a GT is to generate an emergent set of concepts and their properties that fit and work with relevancy to be integrated into a theory. To achieve this goal, the researcher begins his research with open coding, that is coding all his data in every possible way. The consequence of this open coding is a multitude of descriptions for possible concepts that often do not fit in the emerging theory. Thus in this case the researcher ends up with many irrelevant descriptions for concepts that do not apply. To dwell on descriptions for inapplicable concepts ruins the GT theory as it starts. It is hard to stop. Confusion easily sets in. Switching the study to a QDA is a simple rescue. Rigorous focusing on emerging concepts is vital before being lost in open coding descriptions. It is important, no matter how interesting the description may become. Once a core is possible, selective coding can start which will help control against being lost in multiple descriptions.

  5. Implementing Signature Neural Networks with Spiking Neurons.

    Science.gov (United States)

    Carrillo-Medina, José Luis; Latorre, Roberto

    2016-01-01

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

  6. Implementing Signature Neural Networks with Spiking Neurons

    Science.gov (United States)

    Carrillo-Medina, José Luis; Latorre, Roberto

    2016-01-01

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

  7. Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks

    Directory of Open Access Journals (Sweden)

    Daniel ede Santos-Sierra

    2015-11-01

    Full Text Available Synchronization is one of the central phenomena involved in information processing in living systems. It is known that the nervous system requires the coordinated activity of both local and distant neural populations. Such an interplay allows to merge different information modalities in a whole processing supporting high-level mental skills as understanding, memory, abstraction, etc. Though the biological processes underlying synchronization in the brain are not fully understood there have been reported a variety of mechanisms supporting different types of synchronization both at theoretical and experimental level. One of the more intriguing of these phenomena is the anticipating synchronization, which has been recently reported in a pair of unidirectionally coupled artificial neurons under simple conditions cite{Pyragas}, where the slave neuron is able to anticipate in time the behaviour of the master one. In this paper we explore the effect of spike anticipation over the information processing performed by a neural network at functional and structural level. We show that the introduction of intermediary neurons in the network enhances spike anticipation and analyse how these variations in spike anticipation can significantly change the firing regime of the neural network according to its functional and structural properties. In addition we show that the interspike interval (ISI, one of the main features of the neural response associated to the information coding, can be closely related to spike anticipation by each spike, and how synaptic plasticity can be modulated through that relationship. This study has been performed through numerical simulation of a coupled system of Hindmarsh-Rose neurons.

  8. Neutron spectrometry with artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Vega C, H.R.; Hernandez D, V.M.; Manzanares A, E.; Rodriguez, J.M.; Mercado S, G.A. [Universidad Autonoma de Zacatecas, A.P. 336, 98000 Zacatecas (Mexico); Iniguez de la Torre Bayo, M.P. [Universidad de Valladolid, Valladolid (Spain); Barquero, R. [Hospital Universitario Rio Hortega, Valladolid (Spain); Arteaga A, T. [Envases de Zacatecas, S.A. de C.V., Zacatecas (Mexico)]. e-mail: rvega@cantera.reduaz.mx

    2005-07-01

    An artificial neural network has been designed to obtain the neutron spectra from the Bonner spheres spectrometer's count rates. The neural network was trained using 129 neutron spectra. These include isotopic neutron sources; reference and operational spectra from accelerators and nuclear reactors, spectra from mathematical functions as well as few energy groups and monoenergetic spectra. The spectra were transformed from lethargy to energy distribution and were re-bin ned to 31 energy groups using the MCNP 4C code. Re-binned spectra and UTA4 response matrix were used to calculate the expected count rates in Bonner spheres spectrometer. These count rates were used as input and the respective spectrum was used as output during neural network training. After training the network was tested with the Bonner spheres count rates produced by a set of neutron spectra. This set contains data used during network training as well as data not used. Training and testing was carried out in the Mat lab program. To verify the network unfolding performance the original and unfolded spectra were compared using the {chi}{sup 2}-test and the total fluence ratios. The use of Artificial Neural Networks to unfold neutron spectra in neutron spectrometry is an alternative procedure that overcomes the drawbacks associated in this ill-conditioned problem. (Author)

  9. Neutron spectrometry using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Vega-Carrillo, Hector Rene [Unidad Academica de Estudios Nucleares, Universidad Autonoma de Zacatecas, Apdo. Postal 336, 98000 Zacatecas, Zac. (Mexico)]|[Unidad Academica de Ing. Electrica, Universidad Autonoma de Zacatecas, Apdo. Postal 336, 98000 Zacatecas, Zac. (Mexico)]|[Unidad Academica de Matematicas, Universidad Autonoma de Zacatecas, Apdo. Postal 336, 98000 Zacatecas, Zac. (Mexico)]. E-mail: fermineutron@yahoo.com; Martin Hernandez-Davila, Victor [Unidad Academica de Estudios Nucleares, Universidad Autonoma de Zacatecas, Apdo. Postal 336, 98000 Zacatecas, Zac. (Mexico)]|[Unidad Academica de Ing. Electrica, Universidad Autonoma de Zacatecas, Apdo. Postal 336, 98000 Zacatecas, Zac. (Mexico); Manzanares-Acuna, Eduardo [Unidad Academica de Estudios Nucleares, Universidad Autonoma de Zacatecas, Apdo. Postal 336, 98000 Zacatecas, Zac. (Mexico); Mercado Sanchez, Gema A. [Unidad Academica de Matematicas, Universidad Autonoma de Zacatecas, Apdo. Postal 336, 98000 Zacatecas, Zac. (Mexico); Pilar Iniguez de la Torre, Maria [Depto. Fisica Teorica, Molecular y Nuclear, Universidad de Valladolid, Valladolid (Spain); Barquero, Raquel [Hospital Universitario Rio Hortega, Valladolid (Spain); Palacios, Francisco; Mendez Villafane, Roberto [Depto. Fisica Teorica, Molecular y Nuclear, Universidad de Valladolid, Valladolid (Spain)]|[Universidad Europea Miguel de Cervantes, C. Padre Julio Chevalier No. 2, 47012 Valladolid (Spain); Arteaga Arteaga, Tarcicio [Unidad Academica de Estudios Nucleares, Universidad Autonoma de Zacatecas, Apdo. Postal 336, 98000 Zacatecas, Zac. (Mexico)]|[Envases de Zacatecas, SA de CV, Parque Industrial de Calera de Victor Rosales, Zac. (Mexico); Manuel Ortiz Rodriguez, Jose [Unidad Academica de Estudios Nucleares, Universidad Autonoma de Zacatecas, Apdo. Postal 336, 98000 Zacatecas, Zac. (Mexico)]|[Unidad Academica de Ing. Electrica, Universidad Autonoma de Zacatecas, Apdo. Postal 336, 98000 Zacatecas, Zac. (Mexico)

    2006-04-15

    An artificial neural network has been designed to obtain neutron spectra from Bonner spheres spectrometer count rates. The neural network was trained using 129 neutron spectra. These include spectra from isotopic neutron sources; reference and operational spectra from accelerators and nuclear reactors, spectra based on mathematical functions as well as few energy groups and monoenergetic spectra. The spectra were transformed from lethargy to energy distribution and were re-binned to 31 energy groups using the MCNP 4C code. The re-binned spectra and the UTA4 response matrix were used to calculate the expected count rates in Bonner spheres spectrometer. These count rates were used as input and their respective spectra were used as output during the neural network training. After training, the network was tested with the Bonner spheres count rates produced by folding a set of neutron spectra with the response matrix. This set contains data used during network training as well as data not used. Training and testing was carried out using the Matlab{sup (R)} program. To verify the network unfolding performance, the original and unfolded spectra were compared using the root mean square error. The use of artificial neural networks to unfold neutron spectra in neutron spectrometry is an alternative procedure that overcomes the drawbacks associated with this ill-conditioned problem.

  10. Artificial neural networks in neutron dosimetry

    Energy Technology Data Exchange (ETDEWEB)

    Vega C, H.R.; Hernandez D, V.M.; Manzanares A, E.; Mercado, G.A.; Perales M, W.A.; Robles R, J.A. [Unidades Academicas de Estudios Nucleares, UAZ, A.P. 336, 98000 Zacatecas (Mexico); Gallego, E.; Lorente, A. [Depto. de Ingenieria Nuclear, Universidad Politecnica de Madrid, (Spain)

    2005-07-01

    An artificial neural network has been designed to obtain the neutron doses using only the Bonner spheres spectrometer's count rates. Ambient, personal and effective neutron doses were included. 187 neutron spectra were utilized to calculate the Bonner count rates and the neutron doses. The spectra were transformed from lethargy to energy distribution and were re-binned to 31 energy groups using the MCNP 4C code. Re-binned spectra, UTA4 response matrix and fluence-to-dose coefficients were used to calculate the count rates in Bonner spheres spectrometer and the doses. Count rates were used as input and the respective doses were used as output during neural network training. Training and testing was carried out in Mat lab environment. The artificial neural network performance was evaluated using the {chi}{sup 2}- test, where the original and calculated doses were compared. The use of Artificial Neural Networks in neutron dosimetry is an alternative procedure that overcomes the drawbacks associated in this ill-conditioned problem. (Author)

  11. 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.

  12. Some new ternary linear codes

    Directory of Open Access Journals (Sweden)

    Rumen Daskalov

    2017-07-01

    Full Text Available Let an $[n,k,d]_q$ code be a linear code of length $n$, dimension $k$ and minimum Hamming distance $d$ over $GF(q$. One of the most important problems in coding theory is to construct codes with optimal minimum distances. In this paper 22 new ternary linear codes are presented. Two of them are optimal. All new codes improve the respective lower bounds in [11].

  13. ANT Advanced Neural Tool

    Energy Technology Data Exchange (ETDEWEB)

    Labrador, I.; Carrasco, R.; Martinez, L.

    1996-07-01

    This paper describes a practical introduction to the use of Artificial Neural Networks. Artificial Neural Nets are often used as an alternative to the traditional symbolic manipulation and first order logic used in Artificial Intelligence, due the high degree of difficulty to solve problems that can not be handled by programmers using algorithmic strategies. As a particular case of Neural Net a Multilayer Perception developed by programming in C language on OS9 real time operating system is presented. A detailed description about the program structure and practical use are included. Finally, several application examples that have been treated with the tool are presented, and some suggestions about hardware implementations. (Author) 15 refs.

  14. Temporal-pattern learning in neural models

    CERN Document Server

    Genís, Carme Torras

    1985-01-01

    While the ability of animals to learn rhythms is an unquestionable fact, the underlying neurophysiological mechanisms are still no more than conjectures. This monograph explores the requirements of such mechanisms, reviews those previously proposed and postulates a new one based on a direct electric coding of stimulation frequencies. Experi­ mental support for the option taken is provided both at the single neuron and neural network levels. More specifically, the material presented divides naturally into four parts: a description of the experimental and theoretical framework where this work becomes meaningful (Chapter 2), a detailed specifica­ tion of the pacemaker neuron model proposed together with its valida­ tion through simulation (Chapter 3), an analytic study of the behavior of this model when submitted to rhythmic stimulation (Chapter 4) and a description of the neural network model proposed for learning, together with an analysis of the simulation results obtained when varying seve­ ral factors r...

  15. Forecasting of Market Clearing Price by Using GA Based Neural Network

    Science.gov (United States)

    Yang, Bo; Chen, Yun-Ping; Zhao, Zun-Lian; Han, Qi-Ye

    Forecasting of Market Clearing Price (MCP) is important to economic benefits of electricity market participants. To accurately forecast MCP, a novel two-stage GA-based neural network model (GA-NN) is proposed. In the first stage, GA chromosome is designed into two parts: boolean coding part for neural network topology and real coding part for connection weights. By hybrid genetic operation of selection, crossover and mutation under the criterion of error minimization between the actual output and the desired output, optimal architecture of neural network is obtained. In the second stage, gradient learning algorithm with momentum rate is imposed on neural network with optimal architecture. After learning process, optimal connection weights are obtained. The proposed model is tested on MCP forecasting in California electricity market. The test results show that GA-NN has self-adaptive ability in its topology and connection weights and can obtain more accurate MCP forecasting values than BP neural network.

  16. Research on the Application of Artificial Neural Networks in Tender Offer for Construction Projects

    Science.gov (United States)

    Minli, Zhang; Shanshan, Qiao

    The BP model in artificial neural network is used in this paper. Various factors that affect the tender offer is identified and these factors as the input nodes of network to conduct iterated operation in the network is applied in this paper. Through taking advantage of the self-learning function of network, this paper constantly modifies the weight matrix to achieve the objective error of the network error to achieve the function of predicting offer. As a software support tool, MATLAB is used in artificial neural network, the neural network toolbox helps to reduce the workload of writing code greatly and make the application of neural network more widely.

  17. Code blue: seizures.

    Science.gov (United States)

    Hoerth, Matthew T; Drazkowski, Joseph F; Noe, Katherine H; Sirven, Joseph I

    2011-06-01

    Eyewitnesses frequently perceive seizures as life threatening. If an event occurs on the hospital premises, a "code blue" can be called which consumes considerable resources. The purpose of this study was to determine the frequency and characteristics of code blue calls for seizures and seizure mimickers. A retrospective review of a code blue log from 2001 through 2008 identified 50 seizure-like events, representing 5.3% of all codes. Twenty-eight (54%) occurred in inpatients; the other 22 (44%) events involved visitors or employees on the hospital premises. Eighty-six percent of the events were epileptic seizures. Seizure mimickers, particularly psychogenic nonepileptic seizures, were more common in the nonhospitalized group. Only five (17.9%) inpatients had a known diagnosis of epilepsy, compared with 17 (77.3%) of the nonhospitalized patients. This retrospective survey provides insights into how code blues are called on hospitalized versus nonhospitalized patients for seizure-like events. Copyright © 2011. Published by Elsevier Inc.

  18. Error coding simulations

    Science.gov (United States)

    Noble, Viveca K.

    1993-11-01

    There are various elements such as radio frequency interference (RFI) which may induce errors in data being transmitted via a satellite communication link. When a transmission is affected by interference or other error-causing elements, the transmitted data becomes indecipherable. It becomes necessary to implement techniques to recover from these disturbances. The objective of this research is to develop software which simulates error control circuits and evaluate the performance of these modules in various bit error rate environments. The results of the evaluation provide the engineer with information which helps determine the optimal error control scheme. The Consultative Committee for Space Data Systems (CCSDS) recommends the use of Reed-Solomon (RS) and convolutional encoders and Viterbi and RS decoders for error correction. The use of forward error correction techniques greatly reduces the received signal to noise needed for a certain desired bit error rate. The use of concatenated coding, e.g. inner convolutional code and outer RS code, provides even greater coding gain. The 16-bit cyclic redundancy check (CRC) code is recommended by CCSDS for error detection.

  19. Twisted Reed-Solomon Codes

    DEFF Research Database (Denmark)

    Beelen, Peter; Puchinger, Sven; Rosenkilde ne Nielsen, Johan

    2017-01-01

    We present a new general construction of MDS codes over a finite field Fq. We describe two explicit subclasses which contain new MDS codes of length at least q/2 for all values of q ≥ 11. Moreover, we show that most of the new codes are not equivalent to a Reed-Solomon code.......We present a new general construction of MDS codes over a finite field Fq. We describe two explicit subclasses which contain new MDS codes of length at least q/2 for all values of q ≥ 11. Moreover, we show that most of the new codes are not equivalent to a Reed-Solomon code....

  20. Optical coding theory with Prime

    CERN Document Server

    Kwong, Wing C

    2013-01-01

    Although several books cover the coding theory of wireless communications and the hardware technologies and coding techniques of optical CDMA, no book has been specifically dedicated to optical coding theory-until now. Written by renowned authorities in the field, Optical Coding Theory with Prime gathers together in one volume the fundamentals and developments of optical coding theory, with a focus on families of prime codes, supplemented with several families of non-prime codes. The book also explores potential applications to coding-based optical systems and networks. Learn How to Construct

  1. Manufacturer Identification Code (MID) - ACE

    Data.gov (United States)

    Department of Homeland Security — The ACE Manufacturer Identification Code (MID) application is used to track and control identifications codes for manufacturers. A manufacturer is identified on an...

  2. Algebraic and stochastic coding theory

    CERN Document Server

    Kythe, Dave K

    2012-01-01

    Using a simple yet rigorous approach, Algebraic and Stochastic Coding Theory makes the subject of coding theory easy to understand for readers with a thorough knowledge of digital arithmetic, Boolean and modern algebra, and probability theory. It explains the underlying principles of coding theory and offers a clear, detailed description of each code. More advanced readers will appreciate its coverage of recent developments in coding theory and stochastic processes. After a brief review of coding history and Boolean algebra, the book introduces linear codes, including Hamming and Golay codes.

  3. Speech coding code- excited linear prediction

    CERN Document Server

    Bäckström, Tom

    2017-01-01

    This book provides scientific understanding of the most central techniques used in speech coding both for advanced students as well as professionals with a background in speech audio and or digital signal processing. It provides a clear connection between the whys hows and whats thus enabling a clear view of the necessity purpose and solutions provided by various tools as well as their strengths and weaknesses in each respect Equivalently this book sheds light on the following perspectives for each technology presented Objective What do we want to achieve and especially why is this goal important Resource Information What information is available and how can it be useful and Resource Platform What kind of platforms are we working with and what are their capabilities restrictions This includes computational memory and acoustic properties and the transmission capacity of devices used. The book goes on to address Solutions Which solutions have been proposed and how can they be used to reach the stated goals and ...

  4. Code query by example

    Science.gov (United States)

    Vaucouleur, Sebastien

    2011-02-01

    We introduce code query by example for customisation of evolvable software products in general and of enterprise resource planning systems (ERPs) in particular. The concept is based on an initial empirical study on practices around ERP systems. We motivate our design choices based on those empirical results, and we show how the proposed solution helps with respect to the infamous upgrade problem: the conflict between the need for customisation and the need for upgrade of ERP systems. We further show how code query by example can be used as a form of lightweight static analysis, to detect automatically potential defects in large software products. Code query by example as a form of lightweight static analysis is particularly interesting in the context of ERP systems: it is often the case that programmers working in this field are not computer science specialists but more of domain experts. Hence, they require a simple language to express custom rules.

  5. Graph Codes with Reed-Solomon Component Codes

    DEFF Research Database (Denmark)

    Høholdt, Tom; Justesen, Jørn

    2006-01-01

    We treat a specific case of codes based on bipartite expander graphs coming from finite geometries. The code symbols are associated with the branches and the symbols connected to a given node are restricted to be codewords in a Reed-Solomon code. We give results on the parameters of the codes...

  6. Hidden neural networks

    DEFF Research Database (Denmark)

    Krogh, Anders Stærmose; Riis, Søren Kamaric

    1999-01-01

    A general framework for hybrids of hidden Markov models (HMMs) and neural networks (NNs) called hidden neural networks (HNNs) is described. The article begins by reviewing standard HMMs and estimation by conditional maximum likelihood, which is used by the HNN. In the HNN, the usual HMM probability...... parameters are replaced by the outputs of state-specific neural networks. As opposed to many other hybrids, the HNN is normalized globally and therefore has a valid probabilistic interpretation. All parameters in the HNN are estimated simultaneously according to the discriminative conditional maximum...... likelihood criterion. The HNN can be viewed as an undirected probabilistic independence network (a graphical model), where the neural networks provide a compact representation of the clique functions. An evaluation of the HNN on the task of recognizing broad phoneme classes in the TIMIT database shows clear...

  7. Neural Oscillators Programming Simplified

    Directory of Open Access Journals (Sweden)

    Patrick McDowell

    2012-01-01

    Full Text Available The neurological mechanism used for generating rhythmic patterns for functions such as swallowing, walking, and chewing has been modeled computationally by the neural oscillator. It has been widely studied by biologists to model various aspects of organisms and by computer scientists and robotics engineers as a method for controlling and coordinating the gaits of walking robots. Although there has been significant study in this area, it is difficult to find basic guidelines for programming neural oscillators. In this paper, the authors approach neural oscillators from a programmer’s point of view, providing background and examples for developing neural oscillators to generate rhythmic patterns that can be used in biological modeling and robotics applications.

  8. Code of Medical Ethics

    Directory of Open Access Journals (Sweden)

    . SZD-SZZ

    2017-03-01

    Full Text Available Te Code was approved on December 12, 1992, at the 3rd regular meeting of the General Assembly of the Medical Chamber of Slovenia and revised on April 24, 1997, at the 27th regular meeting of the General Assembly of the Medical Chamber of Slovenia. The Code was updated and harmonized with the Medical Association of Slovenia and approved on October 6, 2016, at the regular meeting of the General Assembly of the Medical Chamber of Slovenia.

  9. Physical Layer Network Coding

    DEFF Research Database (Denmark)

    Fukui, Hironori; Yomo, Hironori; Popovski, Petar

    2013-01-01

    Physical layer network coding (PLNC) has the potential to improve throughput of multi-hop networks. However, most of the works are focused on the simple, three-node model with two-way relaying, not taking into account the fact that there can be other neighboring nodes that can cause/receive inter......Physical layer network coding (PLNC) has the potential to improve throughput of multi-hop networks. However, most of the works are focused on the simple, three-node model with two-way relaying, not taking into account the fact that there can be other neighboring nodes that can cause...

  10. Principles of speech coding

    CERN Document Server

    Ogunfunmi, Tokunbo

    2010-01-01

    It is becoming increasingly apparent that all forms of communication-including voice-will be transmitted through packet-switched networks based on the Internet Protocol (IP). Therefore, the design of modern devices that rely on speech interfaces, such as cell phones and PDAs, requires a complete and up-to-date understanding of the basics of speech coding. Outlines key signal processing algorithms used to mitigate impairments to speech quality in VoIP networksOffering a detailed yet easily accessible introduction to the field, Principles of Speech Coding provides an in-depth examination of the

  11. Securing mobile code.

    Energy Technology Data Exchange (ETDEWEB)

    Link, Hamilton E.; Schroeppel, Richard Crabtree; Neumann, William Douglas; Campbell, Philip LaRoche; Beaver, Cheryl Lynn; Pierson, Lyndon George; Anderson, William Erik

    2004-10-01

    If software is designed so that the software can issue functions that will move that software from one computing platform to another, then the software is said to be 'mobile'. There are two general areas of security problems associated with mobile code. The 'secure host' problem involves protecting the host from malicious mobile code. The 'secure mobile code' problem, on the other hand, involves protecting the code from malicious hosts. This report focuses on the latter problem. We have found three distinct camps of opinions regarding how to secure mobile code. There are those who believe special distributed hardware is necessary, those who believe special distributed software is necessary, and those who believe neither is necessary. We examine all three camps, with a focus on the third. In the distributed software camp we examine some commonly proposed techniques including Java, D'Agents and Flask. For the specialized hardware camp, we propose a cryptographic technique for 'tamper-proofing' code over a large portion of the software/hardware life cycle by careful modification of current architectures. This method culminates by decrypting/authenticating each instruction within a physically protected CPU, thereby protecting against subversion by malicious code. Our main focus is on the camp that believes that neither specialized software nor hardware is necessary. We concentrate on methods of code obfuscation to render an entire program or a data segment on which a program depends incomprehensible. The hope is to prevent or at least slow down reverse engineering efforts and to prevent goal-oriented attacks on the software and execution. The field of obfuscation is still in a state of development with the central problem being the lack of a basis for evaluating the protection schemes. We give a brief introduction to some of the main ideas in the field, followed by an in depth analysis of a technique called &apos

  12. 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.

  13. 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.

  14. Neural network applications

    Science.gov (United States)

    Padgett, Mary L.; Desai, Utpal; Roppel, T.A.; White, Charles R.

    1993-01-01

    A design procedure is suggested for neural networks which accommodates the inclusion of such knowledge-based systems techniques as fuzzy logic and pairwise comparisons. The use of these procedures in the design of applications combines qualitative and quantitative factors with empirical data to yield a model with justifiable design and parameter selection procedures. The procedure is especially relevant to areas of back-propagation neural network design which are highly responsive to the use of precisely recorded expert knowledge.

  15. NEMEFO: NEural MEteorological FOrecast

    Energy Technology Data Exchange (ETDEWEB)

    Pasero, E.; Moniaci, W.; Meindl, T.; Montuori, A. [Polytechnic of Turin (Italy). Dept. of Electronics

    2004-07-01

    Artificial Neural Systems are a well-known technique used to classify and recognize objects. Introducing the time dimension they can be used to forecast numerical series. NEMEFO is a ''nowcasting'' tool, which uses both statistical and neural systems to forecast meteorological data in a restricted area close to a meteorological weather station in a short time range (3 hours). Ice, fog, rain are typical events which can be anticipated by NEMEFO. (orig.)

  16. Signaling and transcriptional regulation in neural crest specification and migration: lessons from xenopus embryos.

    Science.gov (United States)

    Pegoraro, Caterina; Monsoro-Burq, Anne H

    2013-01-01

    The neural crest is a population of highly migratory and multipotent cells, which arises from the border of the neural plate in vertebrate embryos. In the last few years, the molecular actors of neural crest early development have been intensively studied, notably by using the frog embryo, as a prime model for the analysis of the earliest embryonic inductions. In addition, tremendous progress has been made in understanding the molecular and cellular basis of Xenopus cranial neural crest migration, by combining in vitro and in vivo analysis. In this review, we examine how the action of previously known neural crest-inducing signals [bone morphogenetic protein (BMP), wingless-int (Wnt), fibroblast growth factor (FGF)] is controlled by newly discovered modulators during early neural plate border patterning and neural crest specification. This regulation controls the induction of key transcription factors that cooperate to pattern the premigratory neural crest progenitors. These data are discussed in the perspective of the gene regulatory network that controls neural and neural crest patterning. We then address recent findings on noncanonical Wnt signaling regulation, cell polarization, and collective cell migration which highlight how cranial neural crest cells populate their target tissue, the branchial arches, in vivo. More than ever, the neural crest stands as a powerful and attractive model to decipher complex vertebrate regulatory circuits in vivo. Copyright © 2012 Wiley Periodicals, Inc.

  17. The Criticality Hypothesis in Neural Systems

    Science.gov (United States)

    Karimipanah, Yahya

    There is mounting evidence that neural networks of the cerebral cortex exhibit scale invariant dynamics. At the larger scale, fMRI recordings have shown evidence for spatiotemporal long range correlations. On the other hand, at the smaller scales this scale invariance is marked by the power law distribution of the size and duration of spontaneous bursts of activity, which are referred as neuronal avalanches. The existence of such avalanches has been confirmed by several studies in vitro and in vivo, among different species and across multiple scales, from spatial scale of MEG and EEG down to single cell resolution. This prevalent scale free nature of cortical activity suggests the hypothesis that the cortex resides at a critical state between two phases of order (short-lasting activity) and disorder (long-lasting activity). In addition, it has been shown, both theoretically and experimentally, that being at criticality brings about certain functional advantages for information processing. However, despite the plenty of evidence and plausibility of the neural criticality hypothesis, still very little is known on how the brain may leverage such criticality to facilitate neural coding. Moreover, the emergent functions that may arise from critical dynamics is poorly understood. In the first part of this thesis, we review several pieces of evidence for the neural criticality hypothesis at different scales, as well as some of the most popular theories of self-organized criticality (SOC). Thereafter, we will focus on the most prominent evidence from small scales, namely neuronal avalanches. We will explore the effect of adaptation and how it can maintain scale free dynamics even at the presence of external stimuli. Using calcium imaging we also experimentally demonstrate the existence of scale free activity at the cellular resolution in vivo. Moreover, by exploring the subsampling issue in neural data, we will find some fundamental constraints of the conventional methods

  18. Neural crest specification: tissues, signals, and transcription factors.

    Science.gov (United States)

    Rogers, C D; Jayasena, C S; Nie, S; Bronner, M E

    2012-01-01

    The neural crest is a transient population of multipotent and migratory cells unique to vertebrate embryos. Initially derived from the borders of the neural plate, these cells undergo an epithelial to mesenchymal transition to leave the central nervous system, migrate extensively in the periphery, and differentiate into numerous diverse derivatives. These include but are not limited to craniofacial cartilage, pigment cells, and peripheral neurons and glia. Attractive for their similarities to stem cells and metastatic cancer cells, neural crest cells are a popular model system for studying cell/tissue interactions and signaling factors that influence cell fate decisions and lineage transitions. In this review, we discuss the mechanisms required for neural crest formation in various vertebrate species, focusing on the importance of signaling factors from adjacent tissues and conserved gene regulatory interactions, which are required for induction and specification of the ectodermal tissue that will become neural crest. Copyright © 2011 Wiley Periodicals, Inc.

  19. Ptolemy Coding Style

    Science.gov (United States)

    2014-09-05

    because this would combine Ptolemy II with the GPL’d code and thus encumber Ptolemy II with the GPL. Another GNU license is the GNU Library General...permission on the source.eecs.berkeley.edu repositories, then use your local repository. bash-3.2$ svn co svn+ ssh ://source.eecs.berkeley.edu/chess

  20. Error Correcting Codes

    Indian Academy of Sciences (India)

    The images, which came from Oailleo's flyby of the moon on June 26-27. 1996 are reported to be 20 times better than those obtained from the Voyager. Priti Shankar .... a systematic way. Thus was born a brand new field,which has since been ..... mathematically oriented, compact book on coding, containing a few topics not ...

  1. Ready, steady… Code!

    CERN Multimedia

    Anaïs Schaeffer

    2013-01-01

    This summer, CERN took part in the Google Summer of Code programme for the third year in succession. Open to students from all over the world, this programme leads to very successful collaborations for open source software projects.   Image: GSoC 2013. Google Summer of Code (GSoC) is a global programme that offers student developers grants to write code for open-source software projects. Since its creation in 2005, the programme has brought together some 6,000 students from over 100 countries worldwide. The students selected by Google are paired with a mentor from one of the participating projects, which can be led by institutes, organisations, companies, etc. This year, CERN PH Department’s SFT (Software Development for Experiments) Group took part in the GSoC programme for the third time, submitting 15 open-source projects. “Once published on the Google Summer for Code website (in April), the projects are open to applications,” says Jakob Blomer, one of the o...

  2. (Almost) practical tree codes

    KAUST Repository

    Khina, Anatoly

    2016-08-15

    We consider the problem of stabilizing an unstable plant driven by bounded noise over a digital noisy communication link, a scenario at the heart of networked control. To stabilize such a plant, one needs real-time encoding and decoding with an error probability profile that decays exponentially with the decoding delay. The works of Schulman and Sahai over the past two decades have developed the notions of tree codes and anytime capacity, and provided the theoretical framework for studying such problems. Nonetheless, there has been little practical progress in this area due to the absence of explicit constructions of tree codes with efficient encoding and decoding algorithms. Recently, linear time-invariant tree codes were proposed to achieve the desired result under maximum-likelihood decoding. In this work, we take one more step towards practicality, by showing that these codes can be efficiently decoded using sequential decoding algorithms, up to some loss in performance (and with some practical complexity caveats). We supplement our theoretical results with numerical simulations that demonstrate the effectiveness of the decoder in a control system setting.

  3. New code of conduct

    CERN Multimedia

    Laëtitia Pedroso

    2010-01-01

    During his talk to the staff at the beginning of the year, the Director-General mentioned that a new code of conduct was being drawn up. What exactly is it and what is its purpose? Anne-Sylvie Catherin, Head of the Human Resources (HR) Department, talked to us about the whys and wherefores of the project.   Drawing by Georges Boixader from the cartoon strip “The World of Particles” by Brian Southworth. A code of conduct is a general framework laying down the behaviour expected of all members of an organisation's personnel. “CERN is one of the very few international organisations that don’t yet have one", explains Anne-Sylvie Catherin. “We have been thinking about introducing a code of conduct for a long time but lacked the necessary resources until now”. The call for a code of conduct has come from different sources within the Laboratory. “The Equal Opportunities Advisory Panel (read also the "Equal opportuni...

  4. Error Correcting Codes

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 10. Error Correcting Codes How Numbers Protect Themselves. Priti Shankar. Series Article Volume 1 ... Author Affiliations. Priti Shankar1. Department of Computer Science and Automation, Indian Institute of Science, Bangalore 560 012, India ...

  5. Video Coding for ESL.

    Science.gov (United States)

    King, Kevin

    1992-01-01

    Coding tasks, a valuable technique for teaching English as a Second Language, are presented that enable students to look at patterns and structures of marital communication as well as objectively evaluate the degree of happiness or distress in the marriage. (seven references) (JL)

  6. Physical layer network coding

    DEFF Research Database (Denmark)

    Fukui, Hironori; Popovski, Petar; Yomo, Hiroyuki

    2014-01-01

    Physical layer network coding (PLNC) has been proposed to improve throughput of the two-way relay channel, where two nodes communicate with each other, being assisted by a relay node. Most of the works related to PLNC are focused on a simple three-node model and they do not take into account...

  7. Decoding Codes on Graphs

    Indian Academy of Sciences (India)

    Computer Science and. Automation, liSe. Their research addresses various aspects of algebraic and combinatorial coding theory. 1 low Density Parity Check ..... lustrating how the variable Xd is decoded. As mentioned earlier, this algorithm runs iteratively. To start with, in the first iteration, only bits in the first level of the ...

  8. Broadcast Coded Slotted ALOHA

    DEFF Research Database (Denmark)

    Ivanov, Mikhail; Brännström, Frederik; Graell i Amat, Alexandre

    2016-01-01

    We propose an uncoordinated medium access control (MAC) protocol, called all-to-all broadcast coded slotted ALOHA (B-CSA) for reliable all-to-all broadcast with strict latency constraints. In B-CSA, each user acts as both transmitter and receiver in a half-duplex mode. The half-duplex mode gives...

  9. Student Dress Codes.

    Science.gov (United States)

    Uerling, Donald F.

    School officials see a need for regulations that prohibit disruptive and inappropriate forms of expression and attire; students see these regulations as unwanted restrictions on their freedom. This paper reviews court litigation involving constitutional limitations on school authority, dress and hair codes, state law constraints, and school…

  10. Dress Codes and Uniforms.

    Science.gov (United States)

    Lumsden, Linda; Miller, Gabriel

    2002-01-01

    Students do not always make choices that adults agree with in their choice of school dress. Dress-code issues are explored in this Research Roundup, and guidance is offered to principals seeking to maintain a positive school climate. In "Do School Uniforms Fit?" Kerry White discusses arguments for and against school uniforms and summarizes the…

  11. Dress Codes. Legal Brief.

    Science.gov (United States)

    Zirkel, Perry A.

    2000-01-01

    As illustrated by two recent decisions, the courts in the past decade have demarcated wide boundaries for school officials considering dress codes, whether in the form of selective prohibitions or required uniforms. Administrators must warn the community, provide legitimate justification and reasonable clarity, and comply with state law. (MLH)

  12. Decoding Codes on Graphs

    Indian Academy of Sciences (India)

    titled 'A Mathematical Theory of Communication' in the Bell Systems Technical Journal in 1948. The paper set up a ... 'existential' result but nota 'constructive' one. The construction of such a code evolved from the work ... several papers on hyperbolic geometry. He shifted to the Department of Pure Mathematics at Calcutta.

  13. Cracking the Codes

    Science.gov (United States)

    Heathcote, Dorothy

    1978-01-01

    Prescribes an attitude that teachers can take to help students "crack the code" of a dramatic work, combining a flexible teaching strategy, the suspension of beliefs or preconceived notions about the work, focusing on the drams's text, and choosing a reading strategy appropriate to the dramatic work. (RL)

  14. Corporate governance through codes

    NARCIS (Netherlands)

    Haxhi, I.; Aguilera, R.V.; Vodosek, M.; den Hartog, D.; McNett, J.M.

    2014-01-01

    The UK's 1992 Cadbury Report defines corporate governance (CG) as the system by which businesses are directed and controlled. CG codes are a set of best practices designed to address deficiencies in the formal contracts and institutions by suggesting prescriptions on the preferred role and

  15. Coded SQUID arrays

    NARCIS (Netherlands)

    Podt, M.; Weenink, J.; Weenink, J.; Flokstra, Jakob; Rogalla, Horst

    2001-01-01

    We report on a superconducting quantum interference device (SQUID) system to read out large arrays of cryogenic detectors. In order to reduce the number of SQUIDs required for an array of these detectors, we used code-division multiplexing. This simplifies the electronics because of a significantly

  16. Reed-Solomon convolutional codes

    NARCIS (Netherlands)

    Gluesing-Luerssen, H; Schmale, W

    2005-01-01

    In this paper we will introduce a specific class of cyclic convolutional codes. The construction is based on Reed-Solomon block codes. The algebraic parameters as well as the distance of these codes are determined. This shows that some of these codes are optimal or near optimal.

  17. Feature-coding transitions to conjunction-coding with progression through human visual cortex.

    Science.gov (United States)

    Cowell, Rosemary A; Leger, Krystal R; Serences, John T

    2017-12-01

    Identifying an object and distinguishing it from similar items depends upon the ability to perceive its component parts as conjoined into a cohesive whole, but the brain mechanisms underlying this ability remain elusive. The ventral visual processing pathway in primates is organized hierarchically: Neuronal responses in early stages are sensitive to the manipulation of simple visual features, whereas neuronal responses in subsequent stages are tuned to increasingly complex stimulus attributes. It is widely assumed that feature-coding dominates in early visual cortex whereas later visual regions employ conjunction-coding in which object representations are different from the sum of their simple feature parts. However, no study in humans has demonstrated that putative object-level codes in higher visual cortex cannot be accounted for by feature-coding and that putative feature codes in regions prior to ventral temporal cortex are not equally well characterized as object-level codes. Thus the existence of a transition from feature- to conjunction-coding in human visual cortex remains unconfirmed, and if a transition does occur its location remains unknown. By employing multivariate analysis of functional imaging data, we measure both feature-coding and conjunction-coding directly, using the same set of visual stimuli, and pit them against each other to reveal the relative dominance of one vs. the other throughout cortex. Our results reveal a transition from feature-coding in early visual cortex to conjunction-coding in both inferior temporal and posterior parietal cortices. This novel method enables the use of experimentally controlled stimulus features to investigate population-level feature and conjunction codes throughout human cortex. NEW & NOTEWORTHY We use a novel analysis of neuroimaging data to assess representations throughout visual cortex, revealing a transition from feature-coding to conjunction-coding along both ventral and dorsal pathways. Occipital

  18. Water cycle algorithm: A detailed standard code

    Science.gov (United States)

    Sadollah, Ali; Eskandar, Hadi; Lee, Ho Min; Yoo, Do Guen; Kim, Joong Hoon

    Inspired by the observation of the water cycle process and movements of rivers and streams toward the sea, a population-based metaheuristic algorithm, the water cycle algorithm (WCA) has recently been proposed. Lately, an increasing number of WCA applications have appeared and the WCA has been utilized in different optimization fields. This paper provides detailed open source code for the WCA, of which the performance and efficiency has been demonstrated for solving optimization problems. The WCA has an interesting and simple concept and this paper aims to use its source code to provide a step-by-step explanation of the process it follows.

  19. Cardiovascular Development and the Colonizing Cardiac Neural Crest Lineage

    Directory of Open Access Journals (Sweden)

    Paige Snider

    2007-01-01

    Full Text Available Although it is well established that transgenic manipulation of mammalian neural crest-related gene expression and microsurgical removal of premigratory chicken and Xenopus embryonic cardiac neural crest progenitors results in a wide spectrum of both structural and functional congenital heart defects, the actual functional mechanism of the cardiac neural crest cells within the heart is poorly understood. Neural crest cell migration and appropriate colonization of the pharyngeal arches and outflow tract septum is thought to be highly dependent on genes that regulate cell-autonomous polarized movement (i.e., gap junctions, cadherins, and noncanonical Wnt1 pathway regulators. Once the migratory cardiac neural crest subpopulation finally reaches the heart, they have traditionally been thought to participate in septation of the common outflow tract into separate aortic and pulmonary arteries. However, several studies have suggested these colonizing neural crest cells may also play additional unexpected roles during cardiovascular development and may even contribute to a crest-derived stem cell population. Studies in both mice and chick suggest they can also enter the heart from the venous inflow as well as the usual arterial outflow region, and may contribute to the adult semilunar and atrioventricular valves as well as part of the cardiac conduction system. Furthermore, although they are not usually thought to give rise to the cardiomyocyte lineage, neural crest cells in the zebrafish (Danio rerio can contribute to the myocardium and may have different functions in a species-dependent context. Intriguingly, both ablation of chick and Xenopus premigratory neural crest cells, and a transgenic deletion of mouse neural crest cell migration or disruption of the normal mammalian neural crest gene expression profiles, disrupts ventral myocardial function and/or cardiomyocyte proliferation. Combined, this suggests that either the cardiac neural crest

  20. A Plastic Temporal Brain Code for Conscious State Generation

    Directory of Open Access Journals (Sweden)

    Birgitta Dresp-Langley

    2009-01-01

    Full Text Available Consciousness is known to be limited in processing capacity and often described in terms of a unique processing stream across a single dimension: time. In this paper, we discuss a purely temporal pattern code, functionally decoupled from spatial signals, for conscious state generation in the brain. Arguments in favour of such a code include Dehaene et al.'s long-distance reverberation postulate, Ramachandran's remapping hypothesis, evidence for a temporal coherence index and coincidence detectors, and Grossberg's Adaptive Resonance Theory. A time-bin resonance model is developed, where temporal signatures of conscious states are generated on the basis of signal reverberation across large distances in highly plastic neural circuits. The temporal signatures are delivered by neural activity patterns which, beyond a certain statistical threshold, activate, maintain, and terminate a conscious brain state like a bar code would activate, maintain, or inactivate the electronic locks of a safe. Such temporal resonance would reflect a higher level of neural processing, independent from sensorial or perceptual brain mechanisms.

  1. Causation, constructors and codes.

    Science.gov (United States)

    Hofmeyr, Jan-Hendrik S

    2017-09-13

    Relational biology relies heavily on the enriched understanding of causal entailment that Robert Rosen's formalisation of Aristotle's four causes has made possible, although to date efficient causes and the rehabilitation of final cause have been its main focus. Formal cause has been paid rather scant attention, but, as this paper demonstrates, is crucial to our understanding of many types of processes, not necessarily biological. The graph-theoretic relational diagram of a mapping has played a key role in relational biology, and the first part of the paper is devoted to developing an explicit representation of formal cause in the diagram and how it acts in combination with efficient cause to form a mapping. I then use these representations to show how Von Neumann's universal constructor can be cast into a relational diagram in a way that avoids the logical paradox that Rosen detected in his own representation of the constructor in terms of sets and mappings. One aspect that was absent from both Von Neumann's and Rosen's treatments was the necessity of a code to translate the description (the formal cause) of the automaton to be constructed into the construction process itself. A formal definition of codes in general, and organic codes in particular, allows the relational diagram to be extended so as to capture this translation of formal cause into process. The extended relational diagram is used to exemplify causal entailment in a diverse range of processes, such as enzyme action, construction of automata, communication through the Morse code, and ribosomal polypeptide synthesis through the genetic code. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. Categorization in neural networks and prosopagnosia

    Science.gov (United States)

    Virasoro, M. A.

    1989-12-01

    Prosopagnosia is a syndrome characterized by a generalized difficulty to visually recognize individual patterns among those that are similar, and can therefore be said to belong to the same category. I suggest that the existence of this disfunction may be an important clue for understanding the categorization process in the brain. In this direction the performance of neural networks under random destruction of synapses is analysed. It is found that in almost every network that stores correlated patterns the coding of the discriminating details between individuals inside a class is more sensitive to noise or to random destruction than the coding that distinguishes between classes. It follows that a process of death and/or deterioration at an intermediate level of intensity, even if it acts randomly on the network may lead to a malfunctioning of the network that resembles prosopagnosia.

  3. Essential idempotents and simplex codes

    Directory of Open Access Journals (Sweden)

    Gladys Chalom

    2017-01-01

    Full Text Available We define essential idempotents in group algebras and use them to prove that every mininmal abelian non-cyclic code is a repetition code. Also we use them to prove that every minimal abelian code is equivalent to a minimal cyclic code of the same length. Finally, we show that a binary cyclic code is simplex if and only if is of length of the form $n=2^k-1$ and is generated by an essential idempotent.

  4. Coding Theory and Projective Spaces

    Science.gov (United States)

    Silberstein, Natalia

    2008-05-01

    The projective space of order n over a finite field F_q is a set of all subspaces of the vector space F_q^{n}. In this work, we consider error-correcting codes in the projective space, focusing mainly on constant dimension codes. We start with the different representations of subspaces in the projective space. These representations involve matrices in reduced row echelon form, associated binary vectors, and Ferrers diagrams. Based on these representations, we provide a new formula for the computation of the distance between any two subspaces in the projective space. We examine lifted maximum rank distance (MRD) codes, which are nearly optimal constant dimension codes. We prove that a lifted MRD code can be represented in such a way that it forms a block design known as a transversal design. The incidence matrix of the transversal design derived from a lifted MRD code can be viewed as a parity-check matrix of a linear code in the Hamming space. We find the properties of these codes which can be viewed also as LDPC codes. We present new bounds and constructions for constant dimension codes. First, we present a multilevel construction for constant dimension codes, which can be viewed as a generalization of a lifted MRD codes construction. This construction is based on a new type of rank-metric codes, called Ferrers diagram rank-metric codes. Then we derive upper bounds on the size of constant dimension codes which contain the lifted MRD code, and provide a construction for two families of codes, that attain these upper bounds. We generalize the well-known concept of a punctured code for a code in the projective space to obtain large codes which are not constant dimension. We present efficient enumerative encoding and decoding techniques for the Grassmannian. Finally we describe a search method for constant dimension lexicodes.

  5. Rate-adaptive BCH codes for distributed source coding

    DEFF Research Database (Denmark)

    Salmistraro, Matteo; Larsen, Knud J.; Forchhammer, Søren

    2013-01-01

    This paper considers Bose-Chaudhuri-Hocquenghem (BCH) codes for distributed source coding. A feedback channel is employed to adapt the rate of the code during the decoding process. The focus is on codes with short block lengths for independently coding a binary source X and decoding it given its...... correlated side information Y. The proposed codes have been analyzed in a high-correlation scenario, where the marginal probability of each symbol, Xi in X, given Y is highly skewed (unbalanced). Rate-adaptive BCH codes are presented and applied to distributed source coding. Adaptive and fixed checking...... strategies for improving the reliability of the decoded result are analyzed, and methods for estimating the performance are proposed. In the analysis, noiseless feedback and noiseless communication are assumed. Simulation results show that rate-adaptive BCH codes achieve better performance than low...

  6. Opponent Coding of Sound Location (Azimuth) in Planum Temporale is Robust to Sound-Level Variations.

    Science.gov (United States)

    Derey, Kiki; Valente, Giancarlo; de Gelder, Beatrice; Formisano, Elia

    2016-01-01

    Coding of sound location in auditory cortex (AC) is only partially understood. Recent electrophysiological research suggests that neurons in mammalian auditory cortex are characterized by broad spatial tuning and a preference for the contralateral hemifield, that is, a nonuniform sampling of sound azimuth. Additionally, spatial selectivity decreases with increasing sound intensity. To accommodate these findings, it has been proposed that sound location is encoded by the integrated activity of neuronal populations with opposite hemifield tuning ("opponent channel model"). In this study, we investigated the validity of such a model in human AC with functional magnetic resonance imaging (fMRI) and a phase-encoding paradigm employing binaural stimuli recorded individually for each participant. In all subjects, we observed preferential fMRI responses to contralateral azimuth positions. Additionally, in most AC locations, spatial tuning was broad and not level invariant. We derived an opponent channel model of the fMRI responses by subtracting the activity of contralaterally tuned regions in bilateral planum temporale. This resulted in accurate decoding of sound azimuth location, which was unaffected by changes in sound level. Our data thus support opponent channel coding as a neural mechanism for representing acoustic azimuth in human AC. © The Author 2015. Published by Oxford University Press.

  7. Synaptic learning rules and sparse coding in a model sensory system.

    Directory of Open Access Journals (Sweden)

    Luca A Finelli

    2008-04-01

    Full Text Available Neural circuits exploit numerous strategies for encoding information. Although the functional significance of individual coding mechanisms has been investigated, ways in which multiple mechanisms interact and integrate are not well understood. The locust olfactory system, in which dense, transiently synchronized spike trains across ensembles of antenna lobe (AL neurons are transformed into a sparse representation in the mushroom body (MB; a region associated with memory, provides a well-studied preparation for investigating the interaction of multiple coding mechanisms. Recordings made in vivo from the insect MB demonstrated highly specific responses to odors in Kenyon cells (KCs. Typically, only a few KCs from the recorded population of neurons responded reliably when a specific odor was presented. Different odors induced responses in different KCs. Here, we explored with a biologically plausible model the possibility that a form of plasticity may control and tune synaptic weights of inputs to the mushroom body to ensure the specificity of KCs' responses to familiar or meaningful odors. We found that plasticity at the synapses between the AL and the MB efficiently regulated the delicate tuning necessary to selectively filter the intense AL oscillatory output and condense it to a sparse representation in the MB. Activity-dependent plasticity drove the observed specificity, reliability, and expected persistence of odor representations, suggesting a role for plasticity in information processing and making a testable prediction about synaptic plasticity at AL-MB synapses.

  8. NMTPY: A Flexible Toolkit for Advanced Neural Machine Translation Systems

    Directory of Open Access Journals (Sweden)

    Caglayan Ozan

    2017-10-01

    Full Text Available In this paper, we present nmtpy, a flexible Python toolkit based on Theano for training Neural Machine Translation and other neural sequence-to-sequence architectures. nmtpy decouples the specification of a network from the training and inference utilities to simplify the addition of a new architecture and reduce the amount of boilerplate code to be written. nmtpy has been used for LIUM’s top-ranked submissions to WMT Multimodal Machine Translation and News Translation tasks in 2016 and 2017.

  9. Entanglement-assisted quantum MDS codes constructed from negacyclic codes

    Science.gov (United States)

    Chen, Jianzhang; Huang, Yuanyuan; Feng, Chunhui; Chen, Riqing

    2017-12-01

    Recently, entanglement-assisted quantum codes have been constructed from cyclic codes by some scholars. However, how to determine the number of shared pairs required to construct entanglement-assisted quantum codes is not an easy work. In this paper, we propose a decomposition of the defining set of negacyclic codes. Based on this method, four families of entanglement-assisted quantum codes constructed in this paper satisfy the entanglement-assisted quantum Singleton bound, where the minimum distance satisfies q+1 ≤ d≤ n+2/2. Furthermore, we construct two families of entanglement-assisted quantum codes with maximal entanglement.

  10. Coding vs non-coding: Translatability of short ORFs found in putative non-coding transcripts.

    Science.gov (United States)

    Kageyama, Yuji; Kondo, Takefumi; Hashimoto, Yoshiko

    2011-11-01

    Genome analysis has identified a number of putative non-protein-coding transcripts that do not contain ORFs longer than 100 codons. Although evidence strongly suggests that non-coding RNAs are important in a variety of biological phenomena, the discovery of small peptide-coding mRNAs confirms that some transcripts that have been assumed to be non-coding actually have coding potential. Their abundance and importance in biological phenomena makes the sorting of non-coding RNAs from small peptide-coding mRNAs a key issue in functional genomics. However, validating the coding potential of small peptide-coding RNAs is complicated, because their ORF sequences are usually too short for computational analysis. In this review, we discuss computational and experimental methods for validating the translatability of these non-coding RNAs. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

  11. Feed-Forward Propagation of Temporal and Rate Information between Cortical Populations during Coherent Activation in Engineered In Vitro Networks.

    Science.gov (United States)

    DeMarse, Thomas B; Pan, Liangbin; Alagapan, Sankaraleengam; Brewer, Gregory J; Wheeler, Bruce C

    2016-01-01

    Transient propagation of information across neuronal assembles is thought to underlie many cognitive processes. However, the nature of the neural code that is embedded within these transmissions remains uncertain. Much of our understanding of how information is transmitted among these assemblies has been derived from computational models. While these models have been instrumental in understanding these processes they often make simplifying assumptions about the biophysical properties of neurons that may influence the nature and properties expressed. To address this issue we created an in vitro analog of a feed-forward network composed of two small populations (also referred to as assemblies or layers) of living dissociated rat cortical neurons. The populations were separated by, and communicated through, a microelectromechanical systems (MEMS) device containing a strip of microscale tunnels. Delayed culturing of one population in the first layer followed by the second a few days later induced the unidirectional growth of axons through the microtunnels resulting in a primarily feed-forward communication between these two small neural populations. In this study we systematically manipulated the number of tunnels that connected each layer and hence, the number of axons providing communication between those populations. We then assess the effect of reducing the number of tunnels has upon the properties of between-layer communication capacity and fidelity of neural transmission among spike trains transmitted across and within layers. We show evidence based on Victor-Purpura's and van Rossum's spike train similarity metrics supporting the presence of both rate and temporal information embedded within these transmissions whose fidelity increased during communication both between and within layers when the number of tunnels are increased. We also provide evidence reinforcing the role of synchronized activity upon transmission fidelity during the spontaneous synchronized

  12. Feed-Forward Propagation of Temporal and Rate Information between Cortical Populations during Coherent Activation in Engineered In Vitro Networks

    Science.gov (United States)

    DeMarse, Thomas B.; Pan, Liangbin; Alagapan, Sankaraleengam; Brewer, Gregory J.; Wheeler, Bruce C.

    2016-01-01

    Transient propagation of information across neuronal assembles is thought to underlie many cognitive processes. However, the nature of the neural code that is embedded within these transmissions remains uncertain. Much of our understanding of how information is transmitted among these assemblies has been derived from computational models. While these models have been instrumental in understanding these processes they often make simplifying assumptions about the biophysical properties of neurons that may influence the nature and properties expressed. To address this issue we created an in vitro analog of a feed-forward network composed of two small populations (also referred to as assemblies or layers) of living dissociated rat cortical neurons. The populations were separated by, and communicated through, a microelectromechanical systems (MEMS) device containing a strip of microscale tunnels. Delayed culturing of one population in the first layer followed by the second a few days later induced the unidirectional growth of axons through the microtunnels resulting in a primarily feed-forward communication between these two small neural populations. In this study we systematically manipulated the number of tunnels that connected each layer and hence, the number of axons providing communication between those populations. We then assess the effect of reducing the number of tunnels has upon the properties of between-layer communication capacity and fidelity of neural transmission among spike trains transmitted across and within layers. We show evidence based on Victor-Purpura’s and van Rossum’s spike train similarity metrics supporting the presence of both rate and temporal information embedded within these transmissions whose fidelity increased during communication both between and within layers when the number of tunnels are increased. We also provide evidence reinforcing the role of synchronized activity upon transmission fidelity during the spontaneous

  13. Code status and resuscitation options in the electronic health record.

    Science.gov (United States)

    Bhatia, Haresh L; Patel, Neal R; Choma, Neesha N; Grande, Jonathan; Giuse, Dario A; Lehmann, Christoph U

    2015-02-01

    The advance discussion and documentation of code-status is important in preventing undesired cardiopulmonary resuscitation and related end of life interventions. Code-status documentation remains infrequent and paper-based, which limits its usefulness. This study evaluates a tool to document code-status in the electronic health records at a large teaching hospital, and analyzes the corresponding data. Encounter data for patients admitted to the Medical Center were collected over a period of 12 months (01-APR-2012-31-MAR-2013) and the code-status attribute was tracked for individual patients. The code-status data were analyzed separately for adult and pediatric patient populations. We considered 131,399 encounters for 83,248 adult patients and 80,778 encounters for 55,656 pediatric patients in this study. 71% of the adult patients and 30% of the pediatric patients studied had a documented code-status. Age and severity of illness influenced the decision to document code-status. Demographics such as gender, race, ethnicity, and proximity of primary residence were also associated with the documentation of code-status. Absence of a recorded code-status may result in unnecessary interventions. Code-status in paper charts may be difficult to access in cardiopulmonary arrest situations and may result in unnecessary and unwanted interventions and procedures. Documentation of code-status in electronic records creates a readily available reference for care providers. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  14. Codes of Good Governance

    DEFF Research Database (Denmark)

    Beck Jørgensen, Torben; Sørensen, Ditte-Lene

    2013-01-01

    Good governance is a broad concept used by many international organizations to spell out how states or countries should be governed. Definitions vary, but there is a clear core of common public values, such as transparency, accountability, effectiveness, and the rule of law. It is quite likely......, however, that national views of good governance reflect different political cultures and institutional heritages. Fourteen national codes of conduct are analyzed. The findings suggest that public values converge and that they match model codes from the United Nations and the European Council as well...... as conceptions of good governance from other international organizations. While values converge, they are balanced and communicated differently, and seem to some extent to be translated into the national cultures. The set of global public values derived from this analysis include public interest, regime dignity...

  15. Synthetic histone code.

    Science.gov (United States)

    Fischle, Wolfgang; Mootz, Henning D; Schwarzer, Dirk

    2015-10-01

    Chromatin is the universal template of genetic information in all eukaryotic cells. This complex of DNA and histone proteins not only packages and organizes genomes but also regulates gene expression. A multitude of posttranslational histone modifications and their combinations are thought to constitute a code for directing distinct structural and functional states of chromatin. Methods of protein chemistry, including protein semisynthesis, amber suppression technology, and cysteine bioconjugation, have enabled the generation of so-called designer chromatin containing histones in defined and homogeneous modification states. Several of these approaches have matured from proof-of-concept studies into efficient tools and technologies for studying the biochemistry of chromatin regulation and for interrogating the histone code. We summarize pioneering experiments and recent developments in this exciting field of chemical biology. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Efficient convolutional sparse coding

    Science.gov (United States)

    Wohlberg, Brendt

    2017-06-20

    Computationally efficient algorithms may be applied for fast dictionary learning solving the convolutional sparse coding problem in the Fourier domain. More specifically, efficient convolutional sparse coding may be derived within an alternating direction method of multipliers (ADMM) framework that utilizes fast Fourier transforms (FFT) to solve the main linear system in the frequency domain. Such algorithms may enable a significant reduction in computational cost over conventional approaches by implementing a linear solver for the most critical and computationally expensive component of the conventional iterative algorithm. The theoretical computational cost of the algorithm may be reduced from O(M.sup.3N) to O(MN log N), where N is the dimensionality of the data and M is the number of elements in the dictionary. This significant improvement in efficiency may greatly increase the range of problems that can practically be addressed via convolutional sparse representations.

  17. Conducting Polymers for Neural Prosthetic and Neural Interface Applications

    Science.gov (United States)

    2015-01-01

    Neural interfacing devices are an artificial mechanism for restoring or supplementing the function of the nervous system lost as a result of injury or disease. Conducting polymers (CPs) are gaining significant attention due to their capacity to meet the performance criteria of a number of neuronal therapies including recording and stimulating neural activity, the regeneration of neural tissue and the delivery of bioactive molecules for mediating device-tissue interactions. CPs form a flexible platform technology that enables the development of tailored materials for a range of neuronal diagnostic and treatment therapies. In this review the application of CPs for neural prostheses and other neural interfacing devices are discussed, with a specific focus on neural recording, neural stimulation, neural regeneration, and therapeutic drug delivery. PMID:26414302

  18. Accuracy comparison among different machine learning techniques for detecting malicious codes

    Science.gov (United States)

    Narang, Komal

    2016-03-01

    In this paper, a machine learning based model for malware detection is proposed. It can detect newly released malware i.e. zero day attack by analyzing operation codes on Android operating system. The accuracy of Naïve Bayes, Support Vector Machine (SVM) and Neural Network for detecting malicious code has been compared for the proposed model. In the experiment 400 benign files, 100 system files and 500 malicious files have been used to construct the model. The model yields the best accuracy 88.9% when neural network is used as classifier and achieved 95% and 82.8% accuracy for sensitivity and specificity respectively.

  19. Status of MARS Code

    Energy Technology Data Exchange (ETDEWEB)

    N.V. Mokhov

    2003-04-09

    Status and recent developments of the MARS 14 Monte Carlo code system for simulation of hadronic and electromagnetic cascades in shielding, accelerator and detector components in the energy range from a fraction of an electronvolt up to 100 TeV are described. these include physics models both in strong and electromagnetic interaction sectors, variance reduction techniques, residual dose, geometry, tracking, histograming. MAD-MARS Beam Line Build and Graphical-User Interface.

  20. Hydra Code Release

    OpenAIRE

    Couchman, H. M. P.; Pearce, F. R.; Thomas, P. A.

    1996-01-01

    Comment: A new version of the AP3M-SPH code, Hydra, is now available as a tar file from the following sites; http://coho.astro.uwo.ca/pub/hydra/hydra.html , http://star-www.maps.susx.ac.uk/~pat/hydra/hydra.html . The release now also contains a cosmological initial conditions generator, documentation, an installation guide and installation tests. A LaTex version of the documentation is included here