解剖学和形态学
麻醉学
听力与言语-语言病理学
行为科学
心脏和心血管系统
细胞和组织工程学
临床神经病学
危重症监护医学
牙科,口腔外科和医学
皮肤病学
急诊医学
内分泌学和新陈代谢
肠胃学和肝脏学
老人病学和老年医学
卫生保健科学和服务
血液学
免疫学
传染病
综合和补充性医学
医学伦理学
医学信息学
医学实验室技术
医学,全科和内科
医学,法律
医学,研究和试验
神经系统科学
护理
营养学和饮食学
产科医学和妇科医学
肿瘤学
眼科学
整形外科学
耳鼻喉科学
病理学
儿科学
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药理学和药剂学
生理学
基本医疗保健
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公共、环境和职业卫生
放射学,核医学和医学成像
康复学
生殖生物学
呼吸系统
风湿病学
运动科学
外科学
毒理学
热带医学
泌尿学和肾脏学
病毒学
老年医学
健康政策和服务
心理学,临床
abstract::We study both analytically and numerically the effect of presynaptic noise on the transmission of information in attractor neural networks. The noise occurs on a very short timescale compared to that for the neuron dynamics and it produces short-time synaptic depression. This is inspired in recent neurobiological find...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976606775623342
更新日期:2006-03-01 00:00:00
abstract::Slightly modified versions of an early Hebbian/anti-Hebbian neural network are shown to be capable of extracting the sparse, independent linear components of a prefiltered natural image set. An explanation for this capability in terms of a coupling between two hypothetical networks is presented. The simple networks pr...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976606775093891
更新日期:2006-02-01 00:00:00
abstract::Firing rates and synchronous firing are often simultaneously relevant signals, and they independently or cooperatively represent external sensory inputs, cognitive events, and environmental situations such as body position. However, how rates and synchrony comodulate and which aspects of inputs are effectively encoded...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976606774841521
更新日期:2006-01-01 00:00:00
abstract::Synaptically generated subthreshold membrane potential (Vm) fluctuations can be characterized within the framework of stochastic calculus. It is possible to obtain analytic expressions for the steady-state Vm distribution, even in the case of conductance-based synaptic currents. However, as we show here, the analytic ...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/0899766054796932
更新日期:2005-11-01 00:00:00
abstract::Learning in a neuronal network is often thought of as a linear superposition of synaptic modifications induced by individual stimuli. However, since biological synapses are naturally bounded, a linear superposition would cause fast forgetting of previously acquired memories. Here we show that this forgetting can be av...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/0899766054615644
更新日期:2005-10-01 00:00:00
abstract::We analyze convergence of the expectation maximization (EM) and variational Bayes EM (VBEM) schemes for parameter estimation in noisy linear models. The analysis shows that both schemes are inefficient in the low-noise limit. The linear model with additive noise includes as special cases independent component analysis...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/0899766054322991
更新日期:2005-09-01 00:00:00
abstract::For gradient descent learning to yield connectivity consistent with real biological networks, the simulated neurons would have to include more realistic intrinsic properties such as frequency adaptation. However, gradient descent learning cannot be used straightforwardly with adapting rate-model neurons because the de...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/0899766054323017
更新日期:2005-09-01 00:00:00
abstract::In this letter, we examine a general method of approximation, known as the Kikuchi approximation method, for finding the marginals of a product distribution, as well as the corresponding partition function. The Kikuchi approximation method defines a certain constrained optimization problem, called the Kikuchi problem,...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/0899766054026693
更新日期:2005-08-01 00:00:00
abstract::Particular levels of partial fault tolerance (PFT) in feedforward artificial neural networks of a given size can be obtained by redundancy (replicating a smaller normally trained network), by design (training specifically to increase PFT), and by a combination of the two (replicating a smaller PFT-trained network). Th...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/0899766053723096
更新日期:2005-07-01 00:00:00
abstract::Synchronized firings in the networks of class 1 excitable neurons with excitatory and inhibitory connections are investigated, and their dependences on the forms of interactions are analyzed. As the forms of interactions, we treat the double exponential coupling and the interactions derived from it: pulse coupling, ex...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/0899766053630387
更新日期:2005-06-01 00:00:00
abstract::Multiple adjacent, roughly mirror-image topographic maps are commonly observed in the sensory neocortex of many species. The cortical regions occupied by these maps are generally believed to be determined initially by genetically controlled chemical markers during development, with thalamocortical afferent activity su...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/0899766053491904
更新日期:2005-05-01 00:00:00
abstract::The Hebbian paradigm is perhaps the best-known unsupervised learning theory in connectionism. It has inspired wide research activity in the artificial neural network field because it embodies some interesting properties such as locality and the capability of being applicable to the basic weight-and-sum structure of ne...
journal_title:Neural computation
pub_type: 杂志文章,评审
doi:10.1162/0899766053429381
更新日期:2005-04-01 00:00:00
abstract::Inner-product operators, often referred to as kernels in statistical learning, define a mapping from some input space into a feature space. The focus of this letter is the construction of biologically motivated kernels for cortical activities. The kernels we derive, termed Spikernels, map spike count sequences into an...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/0899766053019944
更新日期:2005-03-01 00:00:00
abstract::In this review, we compare methods for temporal sequence learning (TSL) across the disciplines machine-control, classical conditioning, neuronal models for TSL as well as spike-timing-dependent plasticity (STDP). This review introduces the most influential models and focuses on two questions: To what degree are reward...
journal_title:Neural computation
pub_type: 杂志文章,评审
doi:10.1162/0899766053011555
更新日期:2005-02-01 00:00:00
abstract::In this letter, we propose a noisy nonlinear version of independent component analysis (ICA). Assuming that the probability density function (p. d. f.) of sources is known, a learning rule is derived based on maximum likelihood estimation (MLE). Our model involves some algorithms of noisy linear ICA (e. g., Bermond & ...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/0899766052530866
更新日期:2005-01-01 00:00:00
abstract::An iterative reweighted least squares (IRWLS) procedure recently proposed is shown to converge to the support vector machine solution. The convergence to a stationary point is ensured by modifying the original IRWLS procedure. ...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/0899766052530875
更新日期:2005-01-01 00:00:00
abstract::Tangential neurons in the fly brain are sensitive to the typical optic flow patterns generated during egomotion. In this study, we examine whether a simplified linear model based on the organization principles in tangential neurons can be used to estimate egomotion from the optic flow. We present a theory for the cons...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/0899766041941899
更新日期:2004-11-01 00:00:00
abstract::Many different types of integrate-and-fire models have been designed in order to explain how it is possible for a cortical neuron to integrate over many independent inputs while still producing highly variable spike trains. Within this context, the variability of spike trains has been almost exclusively measured using...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/0899766041732413
更新日期:2004-10-01 00:00:00
abstract::Decision trees and neural networks are widely used tools for pattern classification. Decision trees provide highly localized representation, whereas neural networks provide a distributed but compact representation of the decision space. Decision trees cannot be induced in the online mode, and they are not adaptive to ...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/0899766041336396
更新日期:2004-09-01 00:00:00
abstract::Generalized discriminant analysis (GDA) is an extension of the classical linear discriminant analysis (LDA) from linear domain to a nonlinear domain via the kernel trick. However, in the previous algorithm of GDA, the solutions may suffer from the degenerate eigenvalue problem (i.e., several eigenvectors with the same...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976604773717612
更新日期:2004-06-01 00:00:00
abstract::In this letter, we investigate the impact of choosing different loss functions from the viewpoint of statistical learning theory. We introduce a convexity assumption, which is met by all loss functions commonly used in the literature, and study how the bound on the estimation error changes with the loss. We also deriv...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976604773135104
更新日期:2004-05-01 00:00:00
abstract::We study a model of the cortical macrocolumn consisting of a collection of inhibitorily coupled minicolumns. The proposed system overcomes several severe deficits of systems based on single neurons as cerebral functional units, notably limited robustness to damage and unrealistically large computation time. Motivated ...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976604772744893
更新日期:2004-03-01 00:00:00
abstract::Natural gradient learning is known to be efficient in escaping plateau, which is a main cause of the slow learning speed of neural networks. The adaptive natural gradient learning method for practical implementation also has been developed, and its advantage in real-world problems has been confirmed. In this letter, w...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976604322742065
更新日期:2004-02-01 00:00:00
abstract::We present a reduction of a Hodgkin-Huxley (HH)--style bursting model to a hybridized integrate-and-fire (IF) formalism based on a thorough bifurcation analysis of the neuron's dynamics. The model incorporates HH--style equations to evolve the subthreshold currents and includes IF mechanisms to characterize spike even...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976603322518768
更新日期:2003-12-01 00:00:00
abstract::Temporal slowness is a learning principle that allows learning of invariant representations by extracting slowly varying features from quickly varying input signals. Slow feature analysis (SFA) is an efficient algorithm based on this principle and has been applied to the learning of translation, scale, and other invar...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976603322297331
更新日期:2003-09-01 00:00:00
abstract::A spiking neuron "computes" by transforming a complex dynamical input into a train of action potentials, or spikes. The computation performed by the neuron can be formulated as dimensional reduction, or feature detection, followed by a nonlinear decision function over the low-dimensional space. Generalizations of the ...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/08997660360675017
更新日期:2003-08-01 00:00:00
abstract::We investigate the approximation ability of a multilayer perceptron (MLP) network when it is extended to the complex domain. The main challenge for processing complex data with neural networks has been the lack of bounded and analytic complex nonlinear activation functions in the complex domain, as stated by Liouville...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976603321891846
更新日期:2003-07-01 00:00:00
abstract::The new time-organized map (TOM) is presented for a better understanding of the self-organization and geometric structure of cortical signal representations. The algorithm extends the common self-organizing map (SOM) from the processing of purely spatial signals to the processing of spatiotemporal signals. The main ad...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976603765202695
更新日期:2003-05-01 00:00:00
abstract::In "Isotropic Sequence Order Learning" (pp. 831-864 in this issue), we introduced a novel algorithm for temporal sequence learning (ISO learning). Here, we embed this algorithm into a formal nonevaluating (teacher free) environment, which establishes a sensor-motor feedback. The system is initially guided by a fixed r...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/08997660360581930
更新日期:2003-04-01 00:00:00
abstract::The richness and complexity of recurrent cortical circuits is an inexhaustible source of inspiration for thinking about high-level biological computation. In past theoretical studies, constraints on the synaptic connection patterns of threshold-linear networks were found that guaranteed bounded network dynamics, conve...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976603321192103
更新日期:2003-03-01 00:00:00
abstract::We derive analytically the solution for the output rate of the ideal coincidence detector. The solution is for an arbitrary number of input spike trains with identical binomial count distributions (which includes Poisson statistics as a special case) and identical arbitrary pairwise cross-correlations, from zero corre...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976603321192068
更新日期:2003-03-01 00:00:00
abstract::We describe a model of short-term synaptic depression that is derived from a circuit implementation. The dynamics of this circuit model is similar to the dynamics of some theoretical models of short-term depression except that the recovery dynamics of the variable describing the depression is nonlinear and it also dep...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976603762552942
更新日期:2003-02-01 00:00:00
abstract::Pairwise correlations among spike trains recorded in vivo have been frequently reported. It has been argued that correlated activity could play an important role in the brain, because it efficiently modulates the response of a postsynaptic neuron. We show here that a neuron's output firing rate critically depends on t...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976603321043702
更新日期:2003-01-01 00:00:00
abstract::The hypothesis of invariant maximization of interaction (IMI) is formulated within the setting of random fields. According to this hypothesis, learning processes maximize the stochastic interaction of the neurons subject to constraints. We consider the extrinsic constraint in terms of a fixed input distribution on the...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976602760805368
更新日期:2002-12-01 00:00:00
abstract::This article addresses the relationship between long-term reward predictions and slow-timescale neural activity in temporal difference (TD) models of the dopamine system. Such models attempt to explain how the activity of dopamine (DA) neurons relates to errors in the prediction of future rewards. Previous models have...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976602760407973
更新日期:2002-11-01 00:00:00
abstract::In this work, we discuss practical methods for the assessment, comparison, and selection of complex hierarchical Bayesian models. A natural way to assess the goodness of the model is to estimate its future predictive capability by estimating expected utilities. Instead of just making a point estimate, it is important ...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/08997660260293292
更新日期:2002-10-01 00:00:00
abstract::We outline a hybrid analog-digital scheme for computing with three important features that enable it to scale to systems of large complexity: First, like digital computation, which uses several one-bit precise logical units to collectively compute a precise answer to a computation, the hybrid scheme uses several moder...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976602320263971
更新日期:2002-09-01 00:00:00
abstract::A simple associationist neural network learns to factor abstract rules (i.e., grammars) from sequences of arbitrary input symbols by inventing abstract representations that accommodate unseen symbol sets as well as unseen but similar grammars. The neural network is shown to have the ability to transfer grammatical kno...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976602320264079
更新日期:2002-09-01 00:00:00
abstract::In considering a statistical model selection of neural networks and radial basis functions under an overrealizable case, the problem of unidentifiability emerges. Because the model selection criterion is an unbiased estimator of the generalization error based on the training error, this article analyzes the expected t...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976602760128090
更新日期:2002-08-01 00:00:00
abstract::Field models provide an elegant mathematical framework to analyze large-scale patterns of neural activity. On the microscopic level, these models are usually based on either a firing-rate picture or integrate-and-fire dynamics. This article shows that in spite of the large conceptual differences between the two types ...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/08997660260028656
更新日期:2002-07-01 00:00:00