An integral upper bound for neural network approximation.

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

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

更新日期：2010-10-01 00:00:00

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

authors： Roberts PD

更新日期：1998-10-01 00:00:00

abstract：:We consider learning a causal ordering of variables in a linear nongaussian acyclic model called LiNGAM. Several methods have been shown to consistently estimate a causal ordering assuming that all the model assumptions are correct. But the estimation results could be distorted if some assumptions are violated. In thi...

journal_title：Neural computation

authors： Tashiro T,Shimizu S,Hyvärinen A,Washio T

更新日期：2014-01-01 00:00:00

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

authors： Fernando C,Goldstein R,Szathmáry E

更新日期：2010-11-01 00:00:00

abstract：:The free-energy principle is a candidate unified theory for learning and memory in the brain that predicts that neurons, synapses, and neuromodulators work in a manner that minimizes free energy. However, electrophysiological data elucidating the neural and synaptic bases for this theory are lacking. Here, we propose ...

journal_title：Neural computation

authors： Isomura T,Sakai K,Kotani K,Jimbo Y

更新日期：2016-09-01 00:00:00

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

authors： Hu X,Zhang B

更新日期：2010-05-01 00:00:00

abstract：:We consider the effect of the effective timing of a delayed feedback on the excitatory neuron in a recurrent inhibitory loop, when biological realities of firing and absolute refractory period are incorporated into a phenomenological spiking linear or quadratic integrate-and-fire neuron model. We show that such models...

journal_title：Neural computation

authors： Ma J,Wu J

更新日期：2007-08-01 00:00:00

abstract：:The brain is known to be active even when not performing any overt cognitive tasks, and often it engages in involuntary mind wandering. This resting state has been extensively characterized in terms of fMRI-derived brain networks. However, an alternate method has recently gained popularity: EEG microstate analysis. Pr...

journal_title：Neural computation

authors： Shaw SB,Dhindsa K,Reilly JP,Becker S

更新日期：2019-11-01 00:00:00

abstract：:Temporal coding is studied for an oscillatory neural network model with synchronization and acceleration. The latter mechanism refers to increasing (decreasing) the phase velocity of each unit for stronger (weaker) or more coherent (decoherent) input from the other units. It has been demonstrated that acceleration gen...

journal_title：Neural computation

authors： Burwick T

更新日期：2008-07-01 00:00:00

abstract：:We present a first-order nonhomogeneous Markov model for the interspike-interval density of a continuously stimulated spiking neuron. The model allows the conditional interspike-interval density and the stationary interspike-interval density to be expressed as products of two separate functions, one of which describes...

journal_title：Neural computation

authors： Tapson J,Jin C,van Schaik A,Etienne-Cummings R

更新日期：2009-06-01 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

authors： Breen BJ,Gerken WC,Butera RJ Jr

更新日期：2003-12-01 00:00:00

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

authors： Tanaka S,Miyashita M

更新日期：2009-09-01 00:00:00

abstract：:Synaptic runaway denotes the formation of erroneous synapses and premature functional decline accompanying activity-dependent learning in neural networks. This work studies synaptic runaway both analytically and numerically in binary-firing associative memory networks. It turns out that synaptic runaway is of fairly m...

journal_title：Neural computation

authors： Greenstein-Messica A,Ruppin E

更新日期：1998-02-15 00:00:00

abstract：:Common representation learning (CRL), wherein different descriptions (or views) of the data are embedded in a common subspace, has been receiving a lot of attention recently. Two popular paradigms here are canonical correlation analysis (CCA)-based approaches and autoencoder (AE)-based approaches. CCA-based approaches...

journal_title：Neural computation

authors： Chandar S,Khapra MM,Larochelle H,Ravindran B

更新日期：2016-02-01 00:00:00

abstract：:Controlling for multiple hypothesis tests using standard spike resampling techniques often requires prohibitive amounts of computation. Importance sampling techniques can be used to accelerate the computation. The general theory is presented, along with specific examples for testing differences across conditions using...

journal_title：Neural computation

authors： Harrison MT

更新日期：2013-02-01 00:00:00

abstract：:This article reviews statistical techniques for combining multiple probability distributions. The framework is that of a decision maker who consults several experts regarding some events. The experts express their opinions in the form of probability distributions. The decision maker must aggregate the experts' distrib...

journal_title：Neural computation

authors： Jacobs RA

更新日期：1995-09-01 00:00:00

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

authors： Cortes JM,Torres JJ,Marro J,Garrido PL,Kappen HJ

更新日期：2006-03-01 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

authors： Wiemer JC

更新日期：2003-05-01 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

authors： Vehtari A,Lampinen J

更新日期：2002-10-01 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

authors： Fortier PA,Guigon E,Burnod Y

更新日期：2005-09-01 00:00:00

abstract：:We examined how the depression of intracortical inhibition due to a reduction in ambient GABA concentration impairs perceptual information processing in schizophrenia. A neural network model with a gliotransmission-mediated ambient GABA regulatory mechanism was simulated. In the network, interneuron-to-glial-cell and ...

journal_title：Neural computation

authors： Hoshino O

更新日期：2013-12-01 00:00:00

abstract：:This letter proposes a multichannel source separation technique, the multichannel variational autoencoder (MVAE) method, which uses a conditional VAE (CVAE) to model and estimate the power spectrograms of the sources in a mixture. By training the CVAE using the spectrograms of training examples with source-class label...

journal_title：Neural computation

authors： Kameoka H,Li L,Inoue S,Makino S

更新日期：2019-09-01 00:00:00

abstract：:Recent experimental and computational evidence suggests that several dynamical properties may characterize the operating point of functioning neural networks: critical branching, neutral stability, and production of a wide range of firing patterns. We seek the simplest setting in which these properties emerge, clarify...

journal_title：Neural computation

authors： Cayco-Gajic NA,Shea-Brown E

更新日期：2013-07-01 00:00:00

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

authors： Moazzezi R,Dayan P

更新日期：2010-12-01 00:00:00

abstract：:Lossy compression and clustering fundamentally involve a decision about which features are relevant and which are not. The information bottleneck method (IB) by Tishby, Pereira, and Bialek ( 1999 ) formalized this notion as an information-theoretic optimization problem and proposed an optimal trade-off between throwin...

journal_title：Neural computation

authors： Strouse DJ,Schwab DJ

更新日期：2017-06-01 00:00:00

abstract：:The visual systems of many mammals, including humans, are able to integrate the geometric information of visual stimuli and perform cognitive tasks at the first stages of the cortical processing. This is thought to be the result of a combination of mechanisms, which include feature extraction at the single cell level ...

journal_title：Neural computation

authors： Cocci G,Barbieri D,Citti G,Sarti A

更新日期：2015-06-01 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

authors： Petersen KB,Winther O,Hansen LK

更新日期：2005-09-01 00:00:00

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

authors： Avnimelech R,Intrator N

更新日期：1999-02-15 00:00:00

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

authors： Doi E,Lewicki MS

更新日期：2011-10-01 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

authors： Masuda N

更新日期：2006-01-01 00:00:00