An extended analytic expression for the membrane potential distribution of conductance-based synaptic noise.

abstract：:Spiking neural networks (SNNs) with the event-driven manner of transmitting spikes consume ultra-low power on neuromorphic chips. However, training deep SNNs is still challenging compared to convolutional neural networks (CNNs). The SNN training algorithms have not achieved the same performance as CNNs. In this letter...

journal_title：Neural computation

authors： Chen R,Li L

更新日期：2020-12-01 00:00:00

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

authors： Sanger TD

更新日期：2011-08-01 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

authors： Basak J

更新日期：2004-09-01 00:00:00

abstract：:In a pioneering classic, Warren McCulloch and Walter Pitts proposed a model of the central nervous system. Motivated by EEG recordings of normal brain activity, Chvátal and Goldsmith asked whether these dynamical systems can be engineered to produce trajectories that are irregular, disorderly, and apparently unpredict...

journal_title：Neural computation

authors： Chvátal V,Goldsmith M,Yang N

更新日期：2016-06-01 00:00:00

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

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

更新日期：2000-11-01 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：: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：: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

authors： Porr B,von Ferber C,Wörgötter F

更新日期：2003-04-01 00:00:00

abstract：:We extend the neural Turing machine (NTM) model into a dynamic neural Turing machine (D-NTM) by introducing trainable address vectors. This addressing scheme maintains for each memory cell two separate vectors, content and address vectors. This allows the D-NTM to learn a wide variety of location-based addressing stra...

journal_title：Neural computation

authors： Gulcehre C,Chandar S,Cho K,Bengio Y

更新日期：2018-04-01 00:00:00

abstract：:We present formal specification and verification of a robot moving in a complex network, using temporal sequence learning to avoid obstacles. Our aim is to demonstrate the benefit of using a formal approach to analyze such a system as a complementary approach to simulation. We first describe a classical closed-loop si...

journal_title：Neural computation

authors： Kirwan R,Miller A,Porr B,Di Prodi P

更新日期：2013-11-01 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

authors： Hagiwara K

更新日期：2002-08-01 00:00:00

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

authors： Famulare M,Fairhall A

更新日期：2010-03-01 00:00:00

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

authors： Coulon A,Beslon G,Soula HA

更新日期：2011-04-01 00:00:00

abstract：:We formulate an equivalence between machine learning and the formulation of statistical data assimilation as used widely in physical and biological sciences. The correspondence is that layer number in a feedforward artificial network setting is the analog of time in the data assimilation setting. This connection has b...

journal_title：Neural computation

authors： Abarbanel HDI,Rozdeba PJ,Shirman S

更新日期：2018-08-01 00:00:00

abstract：:We present a system for the automatic interpretation of cluttered scenes containing multiple partly occluded objects in front of unknown, complex backgrounds. The system is based on an extended elastic graph matching algorithm that allows the explicit modeling of partial occlusions. Our approach extends an earlier sys...

journal_title：Neural computation

authors： Eckes C,Triesch J,von der Malsburg C

更新日期：2006-06-01 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：: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

authors： Miller DA,Zucker SW

更新日期：1999-01-01 00:00:00

abstract：:In a recent paper, Poggio and Girosi (1990) proposed a class of neural networks obtained from the theory of regularization. Regularized networks are capable of approximating arbitrarily well any continuous function on a compactum. In this paper we consider in detail the learning problem for the one-dimensional case. W...

journal_title：Neural computation

authors： Corradi V,White H

更新日期：1995-11-01 00:00:00

abstract：:Current research on discrete and rhythmic movements differs in both experimental procedures and theory, despite the ubiquitous overlap between discrete and rhythmic components in everyday behaviors. Models of rhythmic movements usually use oscillatory systems mimicking central pattern generators (CPGs). In contrast, m...

journal_title：Neural computation

authors： Ronsse R,Sternad D,Lefèvre P

更新日期：2009-05-01 00:00:00

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

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

更新日期：2010-02-01 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

authors： Kim T,Adali T

更新日期：2003-07-01 00:00:00

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

authors： Tanaka H,Krakauer JW,Sejnowski TJ

更新日期：2012-04-01 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

authors： Shpigelman L,Singer Y,Paz R,Vaadia E

更新日期：2005-03-01 00:00:00

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

authors： Lu Z,Leen TK,Kaye J

更新日期：2011-09-01 00:00:00

abstract：:Mild traumatic brain injury (mTBI) presents a significant health concern with potential persisting deficits that can last decades. Although a growing body of literature improves our understanding of the brain network response and corresponding underlying cellular alterations after injury, the effects of cellular disru...

journal_title：Neural computation

authors： Gabrieli D,Schumm SN,Vigilante NF,Meaney DF

更新日期：2021-01-01 00:00:00

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

authors： Amari S

更新日期：2000-09-01 00:00:00

abstract：:We considered a gamma distribution of interspike intervals as a statistical model for neuronal spike generation. A gamma distribution is a natural extension of the Poisson process taking the effect of a refractory period into account. The model is specified by two parameters: a time-dependent firing rate and a shape p...

journal_title：Neural computation

authors： Miura K,Okada M,Amari S

更新日期：2006-10-01 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：: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

authors： Haslinger R,Klinkner KL,Shalizi CR

更新日期：2010-01-01 00:00:00

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

authors： Christodoulou C,Cleanthous A

更新日期：2011-03-01 00:00:00