Classification of temporal patterns in dynamic biological networks.

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

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

更新日期：2011-01-01 00:00:00

abstract：:The dynamic formation of groups of neurons--neuronal assemblies--is believed to mediate cognitive phenomena at many levels, but their detailed operation and mechanisms of interaction are still to be uncovered. One hypothesis suggests that synchronized oscillations underpin their formation and functioning, with a focus...

journal_title：Neural computation

authors： Moioli RC,Husbands P

更新日期：2013-11-01 00:00:00

abstract：:In this letter, we investigate the fundamental limits on how the interspike time of a neuron oscillator can be perturbed by the application of a bounded external control input (a current stimulus) with zero net electric charge accumulation. We use phase models to study the dynamics of neurons and derive charge-balance...

journal_title：Neural computation

authors： Dasanayake IS,Li JS

更新日期：2014-10-01 00:00:00

abstract：:A significant threat to the recent, wide deployment of machine learning-based systems, including deep neural networks (DNNs), is adversarial learning attacks. The main focus here is on evasion attacks against DNN-based classifiers at test time. While much work has focused on devising attacks that make small perturbati...

journal_title：Neural computation

authors： Miller D,Wang Y,Kesidis G

更新日期：2019-08-01 00:00:00

abstract：:We have created a network that allocates a new computational unit whenever an unusual pattern is presented to the network. This network forms compact representations, yet learns easily and rapidly. The network can be used at any time in the learning process and the learning patterns do not have to be repeated. The uni...

journal_title：Neural computation

authors： Platt J

更新日期：1991-07-01 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

authors： Cremers D,Herz AV

更新日期：2002-07-01 00:00:00

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

authors： Sterne P

更新日期：2012-08-01 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

authors： Kanamaru T,Sekine M

更新日期：2005-06-01 00:00:00

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

authors： Chang CC,Lin CJ

更新日期：2001-09-01 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：:We explicitly analyze the trajectories of learning near singularities in hierarchical networks, such as multilayer perceptrons and radial basis function networks, which include permutation symmetry of hidden nodes, and show their general properties. Such symmetry induces singularities in their parameter space, where t...

journal_title：Neural computation

authors： Wei H,Zhang J,Cousseau F,Ozeki T,Amari S

更新日期：2008-03-01 00:00:00

abstract：:The motion of an object (such as a wheel rotating) is seen as consistent independent of its position and size on the retina. Neurons in higher cortical visual areas respond to these global motion stimuli invariantly, but neurons in early cortical areas with small receptive fields cannot represent this motion, not only...

journal_title：Neural computation

authors： Rolls ET,Stringer SM

更新日期：2007-01-01 00:00:00

abstract：:The role of correlations between neuronal responses is crucial to understanding the neural code. A framework used to study this role comprises a breakdown of the mutual information between stimuli and responses into terms that aim to account for different coding modalities and the distinction between different notions...

journal_title：Neural computation

authors： Chicharro D

更新日期：2014-06-01 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：:We consider the problem of training a linear feedforward neural network by using a gradient descent-like LMS learning algorithm. The objective is to find a weight matrix for the network, by repeatedly presenting to it a finite set of examples, so that the sum of the squares of the errors is minimized. Kohonen showed t...

journal_title：Neural computation

authors： Luo ZQ

更新日期：1991-07-01 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

authors： Agüera y Arcas B,Fairhall AL,Bialek W

更新日期：2003-08-01 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：:Disparity tuning of visual cells in the brain depends on the structure of their binocular receptive fields (RFs). Freeman and coworkers have found that binocular RFs of a typical simple cell can be quantitatively described by two Gabor functions with the same gaussian envelope but different phase parameters in the sin...

journal_title：Neural computation

authors： Zhu YD,Qian N

更新日期：1996-11-15 00:00:00

abstract：:Linear-nonlinear (LN) models and their extensions have proven successful in describing transformations from stimuli to spiking responses of neurons in early stages of sensory hierarchies. Neural responses at later stages are highly nonlinear and have generally been better characterized in terms of their decoding perfo...

journal_title：Neural computation

authors： Pagan M,Simoncelli EP,Rust NC

更新日期：2016-11-01 00:00:00

abstract：:The important task of generating the minimum number of sequential triangle strips (tristrips) for a given triangulated surface model is motivated by applications in computer graphics. This hard combinatorial optimization problem is reduced to the minimum energy problem in Hopfield nets by a linear-size construction. I...

journal_title：Neural computation

authors： Síma J,Lnĕnicka R

更新日期：2009-02-01 00:00:00

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

authors： van Vreeswijk C,Hansel D

更新日期：2001-05-01 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：: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

authors： Campbell SR,Wang DL,Jayaprakash C

更新日期：1999-10-01 00:00:00

abstract：:To understand the interspike interval (ISI) variability displayed by visual cortical neurons (Softky & Koch, 1993), it is critical to examine the dynamics of their neuronal integration, as well as the variability in their synaptic input current. Most previous models have focused on the latter factor. We match a simple...

journal_title：Neural computation

authors： Troyer TW,Miller KD

更新日期：1997-07-01 00:00:00

abstract：:Volterra and Wiener series are perhaps the best-understood nonlinear system representations in signal processing. Although both approaches have enjoyed a certain popularity in the past, their application has been limited to rather low-dimensional and weakly nonlinear systems due to the exponential growth of the number...

journal_title：Neural computation

authors： Franz MO,Schölkopf B

更新日期：2006-12-01 00:00:00

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

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

更新日期：2000-07-01 00:00:00

abstract：:Place cells in the rat hippocampus play a key role in creating the animal's internal representation of the world. During active navigation, these cells spike only in discrete locations, together encoding a map of the environment. Electrophysiological recordings have shown that the animal can revisit this map mentally ...

journal_title：Neural computation

authors： Dabaghian Y

更新日期：2016-06-01 00:00:00

abstract：:Integrate-and-fire neurons are time encoding machines that convert the amplitude of an analog signal into a nonuniform, strictly increasing sequence of spike times. Under certain conditions, the encoded signals can be reconstructed from the nonuniform spike time sequences using a time decoding machine. Time encoding a...

journal_title：Neural computation

authors： Florescu D,Coca D

更新日期：2015-09-01 00:00:00

abstract：:Visual navigation requires the estimation of self-motion as well as the segmentation of objects from the background. We suggest a definition of local velocity gradients to compute types of self-motion, segment objects, and compute local properties of optical flow fields, such as divergence, curl, and shear. Such veloc...

journal_title：Neural computation

authors： Raudies F,Ringbauer S,Neumann H

更新日期：2013-09-01 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