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  • Multiple model-based reinforcement learning.

    abstract::We propose a modular reinforcement learning architecture for nonlinear, nonstationary control tasks, which we call multiple model-based reinforcement learning (MMRL). The basic idea is to decompose a complex task into multiple domains in space and time based on the predictability of the environmental dynamics. The sys...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976602753712972

    authors: Doya K,Samejima K,Katagiri K,Kawato M

    更新日期:2002-06-01 00:00:00

  • Bayesian framework for least-squares support vector machine classifiers, gaussian processes, and kernel Fisher discriminant analysis.

    abstract::The Bayesian evidence framework has been successfully applied to the design of multilayer perceptrons (MLPs) in the work of MacKay. Nevertheless, the training of MLPs suffers from drawbacks like the nonconvex optimization problem and the choice of the number of hidden units. In support vector machines (SVMs) for class...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976602753633411

    authors: Van Gestel T,Suykens JA,Lanckriet G,Lambrechts A,De Moor B,Vandewalle J

    更新日期:2002-05-01 00:00:00

  • Information loss in an optimal maximum likelihood decoding.

    abstract::The mutual information between a set of stimuli and the elicited neural responses is compared to the corresponding decoded information. The decoding procedure is presented as an artificial distortion of the joint probabilities between stimuli and responses. The information loss is quantified. Whenever the probabilitie...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976602317318947

    authors: Samengo I

    更新日期:2002-04-01 00:00:00

  • An amplitude equation approach to contextual effects in visual cortex.

    abstract::A mathematical theory of interacting hypercolumns in primary visual cortex (V1) is presented that incorporates details concerning the anisotropic nature of long-range lateral connections. Each hypercolumn is modeled as a ring of interacting excitatory and inhibitory neural populations with orientation preferences over...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976602317250870

    authors: Bressloff PC,Cowan JD

    更新日期:2002-03-01 00:00:00

  • A neural-network-based approach to the double traveling salesman problem.

    abstract::The double traveling salesman problem is a variation of the basic traveling salesman problem where targets can be reached by two salespersons operating in parallel. The real problem addressed by this work concerns the optimization of the harvest sequence for the two independent arms of a fruit-harvesting robot. This a...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/08997660252741194

    authors: Plebe A,Anile AM

    更新日期:2002-02-01 00:00:00

  • Gaussian process approach to spiking neurons for inhomogeneous Poisson inputs.

    abstract::This article presents a new theoretical framework to consider the dynamics of a stochastic spiking neuron model with general membrane response to input spike. We assume that the input spikes obey an inhomogeneous Poisson process. The stochastic process of the membrane potential then becomes a gaussian process. When a ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976601317098529

    authors: Amemori KI,Ishii S

    更新日期:2001-12-01 00:00:00

  • Random embedding machines for pattern recognition.

    abstract::Real classification problems involve structured data that can be essentially grouped into a relatively small number of clusters. It is shown that, under a local clustering condition, a set of points of a given class, embedded in binary space by a set of randomly parameterized surfaces, is linearly separable from other...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976601753196012

    authors: Baram Y

    更新日期:2001-11-01 00:00:00

  • Evaluating auditory performance limits: II. One-parameter discrimination with random-level variation.

    abstract::Previous studies have combined analytical models of stochastic neural responses with signal detection theory (SDT) to predict psychophysical performance limits; however, these studies have typically been limited to simple models and simple psychophysical tasks. A companion article in this issue ("Evaluating Auditory P...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976601750541813

    authors: Heinz MG,Colburn HS,Carney LH

    更新日期:2001-10-01 00:00:00

  • Training nu-support vector classifiers: theory and algorithms.

    abstract::The nu-support vector machine (nu-SVM) for classification proposed by Schölkopf, Smola, Williamson, and Bartlett (2000) has the advantage of using a parameter nu on controlling the number of support vectors. In this article, we investigate the relation between nu-SVM and C-SVM in detail. We show that in general they a...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976601750399335

    authors: Chang CC,Lin CJ

    更新日期:2001-09-01 00:00:00

  • A hierarchical dynamical map as a basic frame for cortical mapping and its application to priming.

    abstract::A hierarchical dynamical map is proposed as the basic framework for sensory cortical mapping. To show how the hierarchical dynamical map works in cognitive processes, we applied it to a typical cognitive task known as priming, in which cognitive performance is facilitated as a consequence of prior experience. Prior to...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/08997660152469341

    authors: Hoshino O,Inoue S,Kashimori Y,Kambara T

    更新日期:2001-08-01 00:00:00

  • Attractive periodic sets in discrete-time recurrent networks (with emphasis on fixed-point stability and bifurcations in two-neuron networks).

    abstract::We perform a detailed fixed-point analysis of two-unit recurrent neural networks with sigmoid-shaped transfer functions. Using geometrical arguments in the space of transfer function derivatives, we partition the network state-space into distinct regions corresponding to stability types of the fixed points. Unlike in ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/08997660152002898

    authors: Tino P,Horne BG,Giles CL

    更新日期:2001-06-01 00:00:00

  • Patterns of synchrony in neural networks with spike adaptation.

    abstract::We study the emergence of synchronized burst activity in networks of neurons with spike adaptation. We show that networks of tonically firing adapting excitatory neurons can evolve to a state where the neurons burst in a synchronized manner. The mechanism leading to this burst activity is analyzed in a network of inte...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/08997660151134280

    authors: van Vreeswijk C,Hansel D

    更新日期:2001-05-01 00:00:00

  • Metabolically efficient information processing.

    abstract::Energy-efficient information transmission may be relevant to biological sensory signal processing as well as to low-power electronic devices. We explore its consequences in two different regimes. In an "immediate" regime, we argue that the information rate should be maximized subject to a power constraint, and in an "...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976601300014358

    authors: Balasubramanian V,Kimber D,Berry MJ 2nd

    更新日期:2001-04-01 00:00:00

  • Learning Hough transform: a neural network model.

    abstract::A single-layered Hough transform network is proposed that accepts image coordinates of each object pixel as input and produces a set of outputs that indicate the belongingness of the pixel to a particular structure (e.g., a straight line). The network is able to learn adaptively the parametric forms of the linear segm...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976601300014501

    authors: Basak J

    更新日期:2001-03-01 00:00:00

  • Learning object representations using a priori constraints within ORASSYLL.

    abstract::In this article, a biologically plausible and efficient object recognition system (called ORASSYLL) is introduced, based on a set of a priori constraints motivated by findings of developmental psychology and neurophysiology. These constraints are concerned with the organization of the input in local and corresponding ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976601300014583

    authors: Krüger N

    更新日期:2001-02-01 00:00:00

  • Minimal model for intracellular calcium oscillations and electrical bursting in melanotrope cells of Xenopus laevis.

    abstract::A minimal model is presented to explain changes in frequency, shape, and amplitude of Ca2+ oscillations in the neuroendocrine melanotrope cell of Xenopus Laevis. It describes the cell as a plasma membrane oscillator with influx of extracellular Ca2+ via voltage-gated Ca2+ channels in the plasma membrane. The Ca2+ osci...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976601300014655

    authors: Cornelisse LN,Scheenen WJ,Koopman WJ,Roubos EW,Gielen SC

    更新日期:2001-01-01 00:00:00

  • Incremental active learning for optimal generalization.

    abstract::The problem of designing input signals for optimal generalization is called active learning. In this article, we give a two-stage sampling scheme for reducing both the bias and variance, and based on this scheme, we propose two active learning methods. One is the multipoint search method applicable to arbitrary models...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976600300014773

    authors: Sugiyama M,Ogawa H

    更新日期:2000-12-01 00:00:00

  • Neural coding: higher-order temporal patterns in the neurostatistics of cell assemblies.

    abstract::Recent advances in the technology of multiunit recordings make it possible to test Hebb's hypothesis that neurons do not function in isolation but are organized in assemblies. This has created the need for statistical approaches to detecting the presence of spatiotemporal patterns of more than two neurons in neuron sp...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976600300014872

    authors: Martignon L,Deco G,Laskey K,Diamond M,Freiwald W,Vaadia E

    更新日期:2000-11-01 00:00:00

  • Generalization and selection of examples in feedforward neural networks.

    abstract::In this work, we study how the selection of examples affects the learning procedure in a boolean neural network and its relationship with the complexity of the function under study and its architecture. We analyze the generalization capacity for different target functions with particular architectures through an analy...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976600300014999

    authors: Franco L,Cannas SA

    更新日期:2000-10-01 00:00:00

  • Estimating functions of independent component analysis for temporally correlated signals.

    abstract::This article studies a general theory of estimating functions of independent component analysis when the independent source signals are temporarily correlated. Estimating functions are used for deriving both batch and on-line learning algorithms, and they are applicable to blind cases where spatial and temporal probab...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976600300015079

    authors: Amari S

    更新日期:2000-09-01 00:00:00

  • Statistical procedures for spatiotemporal neuronal data with applications to optical recording of the auditory cortex.

    abstract::This article presents new procedures for multisite spatiotemporal neuronal data analysis. A new statistical model - the diffusion model - is considered, whose parameters can be estimated from experimental data thanks to mean-field approximations. This work has been applied to optical recording of the guinea pig's audi...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976600300015150

    authors: François O,Abdallahi LM,Horikawa J,Taniguchi I,Hervé T

    更新日期:2000-08-01 00:00:00

  • Synchrony in heterogeneous networks of spiking neurons.

    abstract::The emergence of synchrony in the activity of large, heterogeneous networks of spiking neurons is investigated. We define the robustness of synchrony by the critical disorder at which the asynchronous state becomes linearly unstable. We show that at low firing rates, synchrony is more robust in excitatory networks tha...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976600300015286

    authors: Neltner L,Hansel D,Mato G,Meunier C

    更新日期:2000-07-01 00:00:00

  • Nonmonotonic generalization bias of Gaussian mixture models.

    abstract::Theories of learning and generalization hold that the generalization bias, defined as the difference between the training error and the generalization error, increases on average with the number of adaptive parameters. This article, however, shows that this general tendency is violated for a gaussian mixture model. Fo...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976600300015439

    authors: Akaho S,Kappen HJ

    更新日期:2000-06-01 00:00:00

  • The number of synaptic inputs and the synchrony of large, sparse neuronal networks.

    abstract::The prevalence of coherent oscillations in various frequency ranges in the central nervous system raises the question of the mechanisms that synchronize large populations of neurons. We study synchronization in models of large networks of spiking neurons with random sparse connectivity. Synchrony occurs only when the ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976600300015529

    authors: Golomb D,Hansel D

    更新日期:2000-05-01 00:00:00

  • Minimizing binding errors using learned conjunctive features.

    abstract::We have studied some of the design trade-offs governing visual representations based on spatially invariant conjunctive feature detectors, with an emphasis on the susceptibility of such systems to false-positive recognition errors-Malsburg's classical binding problem. We begin by deriving an analytical model that make...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976600300015574

    authors: Mel BW,Fiser J

    更新日期:2000-04-01 00:00:00

  • Local and global gating of synaptic plasticity.

    abstract::Mechanisms influencing learning in neural networks are usually investigated on either a local or a global scale. The former relates to synaptic processes, the latter to unspecific modulatory systems. Here we study the interaction of a local learning rule that evaluates coincidences of pre- and postsynaptic action pote...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976600300015682

    authors: Sánchez-Montañés MA,Verschure PF,König P

    更新日期:2000-03-01 00:00:00

  • A general probability estimation approach for neural comp.

    abstract::We describe an analytical framework for the adaptations of neural systems that adapt its internal structure on the basis of subjective probabilities constructed by computation of randomly received input signals. A principled approach is provided with the key property that it defines a probability density model that al...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976600300015862

    authors: Khaikine M,Holthausen K

    更新日期:2000-02-01 00:00:00

  • Reinforcement learning in continuous time and space.

    abstract::This article presents a reinforcement learning framework for continuous-time dynamical systems without a priori discretization of time, state, and action. Based on the Hamilton-Jacobi-Bellman (HJB) equation for infinite-horizon, discounted reward problems, we derive algorithms for estimating value functions and improv...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976600300015961

    authors: Doya K

    更新日期:2000-01-01 00:00:00

  • Independent component analysis: A flexible nonlinearity and decorrelating manifold approach.

    abstract::Independent component analysis (ICA) finds a linear transformation to variables that are maximally statistically independent. We examine ICA and algorithms for finding the best transformation from the point of view of maximizing the likelihood of the data. In particular, we discuss the way in which scaling of the unmi...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976699300016043

    authors: Everson R,Roberts S

    更新日期:1999-11-15 00:00:00

  • Synchrony and desynchrony in integrate-and-fire oscillators.

    abstract::Due to many experimental reports of synchronous neural activity in the brain, there is much interest in understanding synchronization in networks of neural oscillators and its potential for computing perceptual organization. Contrary to Hopfield and Herz (1995), we find that networks of locally coupled integrate-and-f...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976699300016160

    authors: Campbell SR,Wang DL,Jayaprakash C

    更新日期:1999-10-01 00:00:00

  • The relationship between synchronization among neuronal populations and their mean activity levels.

    abstract::In the past decade the importance of synchronized dynamics in the brain has emerged from both empirical and theoretical perspectives. Fast dynamic synchronous interactions of an oscillatory or nonoscillatory nature may constitute a form of temporal coding that underlies feature binding and perceptual synthesis. The re...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976699300016287

    authors: Chawla D,Lumer ED,Friston KJ

    更新日期:1999-08-15 00:00:00

  • On the role of biophysical properties of cortical neurons in binding and segmentation of visual scenes.

    abstract::Neuroscience is progressing vigorously, and knowledge at different levels of description is rapidly accumulating. To establish relationships between results found at these different levels is one of the central challenges. In this simulation study, we demonstrate how microscopic cellular properties, taking the example...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976699300016377

    authors: Verschure PF,König P

    更新日期:1999-07-01 00:00:00

  • The Ornstein-Uhlenbeck process does not reproduce spiking statistics of neurons in prefrontal cortex.

    abstract::Cortical neurons of behaving animals generate irregular spike sequences. Recently, there has been a heated discussion about the origin of this irregularity. Softky and Koch (1993) pointed out the inability of standard single-neuron models to reproduce the irregularity of the observed spike sequences when the model par...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976699300016511

    authors: Shinomoto S,Sakai Y,Funahashi S

    更新日期:1999-05-15 00:00:00

  • Discriminant component pruning. Regularization and interpretation of multi-layered back-propagation networks.

    abstract::Neural networks are often employed as tools in classification tasks. The use of large networks increases the likelihood of the task's being learned, although it may also lead to increased complexity. Pruning is an effective way of reducing the complexity of large networks. We present discriminant components pruning (D...

    journal_title:Neural computation

    pub_type: 杂志文章,评审

    doi:10.1162/089976699300016665

    authors: Koene RA,Takane Y

    更新日期:1999-04-01 00:00:00

  • Boosted mixture of experts: an ensemble learning scheme.

    abstract::We present a new supervised learning procedure for ensemble machines, in which outputs of predictors, trained on different distributions, are combined by a dynamic classifier combination model. This procedure may be viewed as either a version of mixture of experts (Jacobs, Jordan, Nowlan, & Hintnon, 1991), applied to ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976699300016737

    authors: Avnimelech R,Intrator N

    更新日期:1999-02-15 00:00:00

  • Propagating distributions up directed acyclic graphs.

    abstract::In a previous article, we considered game trees as graphical models. Adopting an evaluation function that returned a probability distribution over values likely to be taken at a given position, we described how to build a model of uncertainty and use it for utility-directed growth of the search tree and for deciding o...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976699300016881

    authors: Baum EB,Smith WD

    更新日期:1999-01-01 00:00:00

  • Computing with self-excitatory cliques: A model and an application to hyperacuity-scale computation in visual cortex.

    abstract::We present a model of visual computation based on tightly inter-connected cliques of pyramidal cells. It leads to a formal theory of cell assemblies, a specific relationship between correlated firing patterns and abstract functionality, and a direct calculation relating estimates of cortical cell counts to orientation...

    journal_title:Neural computation

    pub_type: 杂志文章,评审

    doi:10.1162/089976699300016782

    authors: Miller DA,Zucker SW

    更新日期:1999-01-01 00:00:00

  • Connecting cortical and behavioral dynamics: bimanual coordination.

    abstract::For the paradigmatic case of bimanual coordination, we review levels of organization of behavioral dynamics and present a description in terms of modes of behavior. We briefly review a recently developed model of spatiotemporal brain activity that is based on short- and long-range connectivity of neural ensembles. Thi...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976698300016954

    authors: Jirsa VK,Fuchs A,Kelso JA

    更新日期:1998-11-15 00:00:00

  • Classification of temporal patterns in dynamic biological networks.

    abstract::A general method is presented to classify temporal patterns generated by rhythmic biological networks when synaptic connections and cellular properties are known. The method is discrete in nature and relies on algebraic properties of state transitions and graph theory. Elements of the set of rhythms generated by a net...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976698300017160

    authors: Roberts PD

    更新日期:1998-10-01 00:00:00

  • Employing the zeta-transform to optimize the calculation of the synaptic conductance of NMDA and other synaptic channels in network simulations.

    abstract::Calculation of the total conductance change induced by multiple synapses at a given membrane compartment remains one of the most time-consuming processes in biophysically realistic neural network simulations. Here we show that this calculation can be achieved in a highly efficient way even for multiply converging syna...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976698300017061

    authors: Köhn J,Wörgötter F

    更新日期:1998-10-01 00:00:00

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