听力与言语-语言病理学

行为科学

医学伦理学

你正在浏览NEURAL COMPUTATION期刊下所有文献
  • Sparse coding on the spot: spontaneous retinal waves suffice for orientation selectivity.

    abstract::Ohshiro, Hussain, and Weliky (2011) recently showed that ferrets reared with exposure to flickering spot stimuli, in the absence of oriented visual experience, develop oriented receptive fields. They interpreted this as refutation of efficient coding models, which require oriented input in order to develop oriented re...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00333

    authors: Hunt JJ,Ibbotson M,Goodhill GJ

    更新日期:2012-09-01 00:00:00

  • Hebbian learning of recurrent connections: a geometrical perspective.

    abstract::We show how a Hopfield network with modifiable recurrent connections undergoing slow Hebbian learning can extract the underlying geometry of an input space. First, we use a slow and fast analysis to derive an averaged system whose dynamics derives from an energy function and therefore always converges to equilibrium p...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00322

    authors: Galtier MN,Faugeras OD,Bressloff PC

    更新日期:2012-09-01 00:00:00

  • Information recall using relative spike timing in a spiking neural network.

    abstract::We present a neural network that is capable of completing and correcting a spiking pattern given only a partial, noisy version. It operates in continuous time and represents information using the relative timing of individual spikes. The network is capable of correcting and recalling multiple patterns simultaneously. ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00306

    authors: Sterne P

    更新日期:2012-08-01 00:00:00

  • A neurocomputational approach to prepositional phrase attachment ambiguity resolution.

    abstract::A neurocomputational model based on emergent massively overlapping neural cell assemblies (CAs) for resolving prepositional phrase (PP) attachment ambiguity is described. PP attachment ambiguity is a well-studied task in natural language processing and is a case where semantics is used to determine the syntactic struc...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00290

    authors: Nadh K,Huyck C

    更新日期:2012-07-01 00:00:00

  • The successor representation and temporal context.

    abstract::The successor representation was introduced into reinforcement learning by Dayan ( 1993 ) as a means of facilitating generalization between states with similar successors. Although reinforcement learning in general has been used extensively as a model of psychological and neural processes, the psychological validity o...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00282

    authors: Gershman SJ,Moore CD,Todd MT,Norman KA,Sederberg PB

    更新日期:2012-06-01 00:00:00

  • Optimal sequential detection of stimuli from multiunit recordings taken in densely populated brain regions.

    abstract::We address the problem of detecting the presence of a recurring stimulus by monitoring the voltage on a multiunit electrode located in a brain region densely populated by stimulus reactive neurons. Published experimental results suggest that under these conditions, when a stimulus is present, the measurements are gaus...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00257

    authors: Nossenson N,Messer H

    更新日期:2012-04-01 00:00:00

  • Generalization and multirate models of motor adaptation.

    abstract::When subjects adapt their reaching movements in the setting of a systematic force or visual perturbation, generalization of adaptation can be assessed psychophysically in two ways: by testing untrained locations in the work space at the end of adaptation (slow postadaptation generalization) or by determining the influ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00262

    authors: Tanaka H,Krakauer JW,Sejnowski TJ

    更新日期:2012-04-01 00:00:00

  • Spiking neural P systems with astrocytes.

    abstract::In a biological nervous system, astrocytes play an important role in the functioning and interaction of neurons, and astrocytes have excitatory and inhibitory influence on synapses. In this work, with this biological inspiration, a class of computation devices that consist of neurons and astrocytes is introduced, call...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00238

    authors: Pan L,Wang J,Hoogeboom HJ

    更新日期:2012-03-01 00:00:00

  • Transmission of population-coded information.

    abstract::As neural activity is transmitted through the nervous system, neuronal noise degrades the encoded information and limits performance. It is therefore important to know how information loss can be prevented. We study this question in the context of neural population codes. Using Fisher information, we show how informat...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00227

    authors: Renart A,van Rossum MC

    更新日期:2012-02-01 00:00:00

  • On the relation of slow feature analysis and Laplacian eigenmaps.

    abstract::The past decade has seen a rise of interest in Laplacian eigenmaps (LEMs) for nonlinear dimensionality reduction. LEMs have been used in spectral clustering, in semisupervised learning, and for providing efficient state representations for reinforcement learning. Here, we show that LEMs are closely related to slow fea...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00214

    authors: Sprekeler H

    更新日期:2011-12-01 00:00:00

  • Computing confidence intervals for point process models.

    abstract::Characterizing neural spiking activity as a function of intrinsic and extrinsic factors is important in neuroscience. Point process models are valuable for capturing such information; however, the process of fully applying these models is not always obvious. A complete model application has four broad steps: specifica...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00198

    authors: Sarma SV,Nguyen DP,Czanner G,Wirth S,Wilson MA,Suzuki W,Brown EN

    更新日期:2011-11-01 00:00:00

  • Characterization of minimum error linear coding with sensory and neural noise.

    abstract::Robust coding has been proposed as a solution to the problem of minimizing decoding error in the presence of neural noise. Many real-world problems, however, have degradation in the input signal, not just in neural representations. This generalized problem is more relevant to biological sensory coding where internal n...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00181

    authors: Doi E,Lewicki MS

    更新日期:2011-10-01 00:00:00

  • Kernels for longitudinal data with variable sequence length and sampling intervals.

    abstract::We develop several kernel methods for classification of longitudinal data and apply them to detect cognitive decline in the elderly. We first develop mixed-effects models, a type of hierarchical empirical Bayes generative models, for the time series. After demonstrating their utility in likelihood ratio classifiers (a...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00164

    authors: Lu Z,Leen TK,Kaye J

    更新日期:2011-09-01 00:00:00

  • Distributed control of uncertain systems using superpositions of linear operators.

    abstract::Control in the natural environment is difficult in part because of uncertainty in the effect of actions. Uncertainty can be due to added motor or sensory noise, unmodeled dynamics, or quantization of sensory feedback. Biological systems are faced with further difficulties, since control must be performed by networks o...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00151

    authors: Sanger TD

    更新日期:2011-08-01 00:00:00

  • A finite-sample, distribution-free, probabilistic lower bound on mutual information.

    abstract::For any memoryless communication channel with a binary-valued input and a one-dimensional real-valued output, we introduce a probabilistic lower bound on the mutual information given empirical observations on the channel. The bound is built on the Dvoretzky-Kiefer-Wolfowitz inequality and is distribution free. A quadr...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00144

    authors: VanderKraats ND,Banerjee A

    更新日期:2011-07-01 00:00:00

  • Neural associative memory with optimal Bayesian learning.

    abstract::Neural associative memories are perceptron-like single-layer networks with fast synaptic learning typically storing discrete associations between pairs of neural activity patterns. Previous work optimized the memory capacity for various models of synaptic learning: linear Hopfield-type rules, the Willshaw model employ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00127

    authors: Knoblauch A

    更新日期:2011-06-01 00:00:00

  • On the performance of voltage stepping for the simulation of adaptive, nonlinear integrate-and-fire neuronal networks.

    abstract::In traditional event-driven strategies, spike timings are analytically given or calculated with arbitrary precision (up to machine precision). Exact computation is possible only for simplified neuron models, mainly the leaky integrate-and-fire model. In a recent paper, Zheng, Tonnelier, and Martinez (2009) introduced ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00112

    authors: Kaabi MG,Tonnelier A,Martinez D

    更新日期:2011-05-01 00:00:00

  • Enhanced stimulus encoding capabilities with spectral selectivity in inhibitory circuits by STDP.

    abstract::The ability to encode and transmit a signal is an essential property that must demonstrate many neuronal circuits in sensory areas in addition to any processing they may provide. It is known that an appropriate level of lateral inhibition, as observed in these areas, can significantly improve the encoding ability of a...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00100

    authors: Coulon A,Beslon G,Soula HA

    更新日期:2011-04-01 00:00:00

  • Does high firing irregularity enhance learning?

    abstract::In this note, we demonstrate that the high firing irregularity produced by the leaky integrate-and-fire neuron with the partial somatic reset mechanism, which has been shown to be the most likely candidate to reflect the mechanism used in the brain for reproducing the highly irregular cortical neuron firing at high ra...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00090

    authors: Christodoulou C,Cleanthous A

    更新日期:2011-03-01 00:00:00

  • A theory of slow feature analysis for transformation-based input signals with an application to complex cells.

    abstract::We develop a group-theoretical analysis of slow feature analysis for the case where the input data are generated by applying a set of continuous transformations to static templates. As an application of the theory, we analytically derive nonlinear visual receptive fields and show that their optimal stimuli, as well as...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00072

    authors: Sprekeler H,Wiskott L

    更新日期:2011-02-01 00:00:00

  • Abstract stimulus-specific adaptation models.

    abstract::Many neurons that initially respond to a stimulus stop responding if the stimulus is presented repeatedly but recover their response if a different stimulus is presented. This phenomenon is referred to as stimulus-specific adaptation (SSA). SSA has been investigated extensively using oddball experiments, which measure...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00077

    authors: Mill R,Coath M,Wennekers T,Denham SL

    更新日期:2011-02-01 00:00:00

  • A graphical model framework for decoding in the visual ERP-based BCI speller.

    abstract::We present a graphical model framework for decoding in the visual ERP-based speller system. The proposed framework allows researchers to build generative models from which the decoding rules are obtained in a straightforward manner. We suggest two models for generating brain signals conditioned on the stimulus events....

    journal_title:Neural computation

    pub_type: 信件

    doi:10.1162/NECO_a_00066

    authors: Martens SM,Mooij JM,Hill NJ,Farquhar J,Schölkopf B

    更新日期:2011-01-01 00:00:00

  • Change-based inference in attractor nets: linear analysis.

    abstract::One standard interpretation of networks of cortical neurons is that they form dynamical attractors. Computations such as stimulus estimation are performed by mapping inputs to points on the networks' attractive manifolds. These points represent population codes for the stimulus values. However, this standard interpret...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00051

    authors: Moazzezi R,Dayan P

    更新日期:2010-12-01 00:00:00

  • The neuronal replicator hypothesis.

    abstract::We propose that replication (with mutation) of patterns of neuronal activity can occur within the brain using known neurophysiological processes. Thereby evolutionary algorithms implemented by neuro- nal circuits can play a role in cognition. Replication of structured neuronal representations is assumed in several cog...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00031

    authors: Fernando C,Goldstein R,Szathmáry E

    更新日期:2010-11-01 00:00:00

  • Spiking neural P systems with weights.

    abstract::A variant of spiking neural P systems with positive or negative weights on synapses is introduced, where the rules of a neuron fire when the potential of that neuron equals a given value. The involved values-weights, firing thresholds, potential consumed by each rule-can be real (computable) numbers, rational numbers,...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00022

    authors: Wang J,Hoogeboom HJ,Pan L,Păun G,Pérez-Jiménez MJ

    更新日期:2010-10-01 00:00:00

  • Topographic mapping of large dissimilarity data sets.

    abstract::Topographic maps such as the self-organizing map (SOM) or neural gas (NG) constitute powerful data mining techniques that allow simultaneously clustering data and inferring their topological structure, such that additional features, for example, browsing, become available. Both methods have been introduced for vectori...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00012

    authors: Hammer B,Hasenfuss A

    更新日期:2010-09-01 00:00:00

  • Estimating a state-space model from point process observations: a note on convergence.

    abstract::Physiological signals such as neural spikes and heartbeats are discrete events in time, driven by continuous underlying systems. A recently introduced data-driven model to analyze such a system is a state-space model with point process observations, parameters of which and the underlying state sequence are simultaneou...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2010.07-09-1047

    authors: Yuan K,Niranjan M

    更新日期:2010-08-01 00:00:00

  • Learning spike-based population codes by reward and population feedback.

    abstract::We investigate a recently proposed model for decision learning in a population of spiking neurons where synaptic plasticity is modulated by a population signal in addition to reward feedback. For the basic model, binary population decision making based on spike/no-spike coding, a detailed computational analysis is giv...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2010.05-09-1010

    authors: Friedrich J,Urbanczik R,Senn W

    更新日期:2010-07-01 00:00:00

  • General Poisson exact breakdown of the mutual information to study the role of correlations in populations of neurons.

    abstract::We present an integrative formalism of mutual information expansion, the general Poisson exact breakdown, which explicitly evaluates the informational contribution of correlations in the spike counts both between and within neurons. The formalism was validated on simulated data and applied to real neurons recorded fro...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2010.04-09-989

    authors: Scaglione A,Moxon KA,Foffani G

    更新日期:2010-06-01 00:00:00

  • Representation sharpening can explain perceptual priming.

    abstract::Perceiving and identifying an object is improved by prior exposure to the object. This perceptual priming phenomenon is accompanied by reduced neural activity. But whether suppression of neuronal activity with priming is responsible for the improvement in perception is unclear. To address this problem, we developed a ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2009.04-09-999

    authors: Moldakarimov S,Bazhenov M,Sejnowski TJ

    更新日期:2010-05-01 00:00:00

  • A Gaussian attractor network for memory and recognition with experience-dependent learning.

    abstract::Attractor networks are widely believed to underlie the memory systems of animals across different species. Existing models have succeeded in qualitatively modeling properties of attractor dynamics, but their computational abilities often suffer from poor representations for realistic complex patterns, spurious attract...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2010.02-09-957

    authors: Hu X,Zhang B

    更新日期:2010-05-01 00:00:00

  • Feature selection in simple neurons: how coding depends on spiking dynamics.

    abstract::The relationship between a neuron's complex inputs and its spiking output defines the neuron's coding strategy. This is frequently and effectively modeled phenomenologically by one or more linear filters that extract the components of the stimulus that are relevant for triggering spikes and a nonlinear function that r...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2009.02-09-956

    authors: Famulare M,Fairhall A

    更新日期:2010-03-01 00:00:00

  • Derivatives of logarithmic stationary distributions for policy gradient reinforcement learning.

    abstract::Most conventional policy gradient reinforcement learning (PGRL) algorithms neglect (or do not explicitly make use of) a term in the average reward gradient with respect to the policy parameter. That term involves the derivative of the stationary state distribution that corresponds to the sensitivity of its distributio...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2009.12-08-922

    authors: Morimura T,Uchibe E,Yoshimoto J,Peters J,Doya K

    更新日期:2010-02-01 00:00:00

  • Discrete states of synaptic strength in a stochastic model of spike-timing-dependent plasticity.

    abstract::A stochastic model of spike-timing-dependent plasticity (STDP) postulates that single synapses presented with a single spike pair exhibit all-or-none quantal jumps in synaptic strength. The amplitudes of the jumps are independent of spiking timing, but their probabilities do depend on spiking timing. By making the amp...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2009.07-08-814

    authors: Elliott T

    更新日期:2010-01-01 00:00:00

  • The computational structure of spike trains.

    abstract::Neurons perform computations, and convey the results of those computations through the statistical structure of their output spike trains. Here we present a practical method, grounded in the information-theoretic analysis of prediction, for inferring a minimal representation of that structure and for characterizing it...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2009.12-07-678

    authors: Haslinger R,Klinkner KL,Shalizi CR

    更新日期:2010-01-01 00:00:00

  • Making the error-controlling algorithm of observable operator models constructive.

    abstract::Observable operator models (OOMs) are a class of models for stochastic processes that properly subsumes the class that can be modeled by finite-dimensional hidden Markov models (HMMs). One of the main advantages of OOMs over HMMs is that they admit asymptotically correct learning algorithms. A series of learning algor...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2009.10-08-878

    authors: Zhao MJ,Jaeger H,Thon M

    更新日期:2009-12-01 00:00:00

  • A neurocomputational model for cocaine addiction.

    abstract::Based on the dopamine hypotheses of cocaine addiction and the assumption of decrement of brain reward system sensitivity after long-term drug exposure, we propose a computational model for cocaine addiction. Utilizing average reward temporal difference reinforcement learning, we incorporate the elevation of basal rewa...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2009.10-08-882

    authors: Dezfouli A,Piray P,Keramati MM,Ekhtiari H,Lucas C,Mokri A

    更新日期:2009-10-01 00:00:00

  • An integral upper bound for neural network approximation.

    abstract::Complexity of one-hidden-layer networks is studied using tools from nonlinear approximation and integration theory. For functions with suitable integral representations in the form of networks with infinitely many hidden units, upper bounds are derived on the speed of decrease of approximation error as the number of n...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2009.04-08-745

    authors: Kainen PC,Kůrková V

    更新日期:2009-10-01 00:00:00

  • Constraint on the number of synaptic inputs to a visual cortical neuron controls receptive field formation.

    abstract::To date, Hebbian learning combined with some form of constraint on synaptic inputs has been demonstrated to describe well the development of neural networks. The previous models revealed mathematically the importance of synaptic constraints to reproduce orientation selectivity in the visual cortical neurons, but biolo...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2009.04-08-752

    authors: Tanaka S,Miyashita M

    更新日期:2009-09-01 00:00:00

  • Time-varying perturbations can distinguish among integrate-to-threshold models for perceptual decision making in reaction time tasks.

    abstract::Several integrate-to-threshold models with differing temporal integration mechanisms have been proposed to describe the accumulation of sensory evidence to a prescribed level prior to motor response in perceptual decision-making tasks. An experiment and simulation studies have shown that the introduction of time-varyi...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2009.07-08-817

    authors: Zhou X,Wong-Lin K,Philip H

    更新日期:2009-08-01 00:00:00

262 条记录 3/7 页 « 1234567 »