Downstream Effect of Ramping Neuronal Activity through Synapses with Short-Term Plasticity.

abstract：:A neurocomputational model based on emergent massively overlapping neural cell assemblies (CAs) for resolving prepositional phrase (PP) attachment ambiguity is described. PP attachment ambiguity is a well-studied task in natural language processing and is a case where semantics is used to determine the syntactic struc...

journal_title：Neural computation

authors： Nadh K,Huyck C

更新日期：2012-07-01 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

abstract：:Reservoir computing is a biologically inspired class of learning algorithms in which the intrinsic dynamics of a recurrent neural network are mined to produce target time series. Most existing reservoir computing algorithms rely on fully supervised learning rules, which require access to an exact copy of the target re...

journal_title：Neural computation

authors： Pyle R,Rosenbaum R

更新日期：2019-07-01 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：: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：: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：:Different analytical expressions for the membrane potential distribution of membranes subject to synaptic noise have been proposed and can be very helpful in analyzing experimental data. However, all of these expressions are either approximations or limit cases, and it is not clear how they compare and which expressio...

journal_title：Neural computation

authors： Rudolph M,Destexhe A

更新日期：2006-12-01 00:00:00

abstract：:Function approximation in online, incremental, reinforcement learning needs to deal with two fundamental problems: biased sampling and nonstationarity. In this kind of task, biased sampling occurs because samples are obtained from specific trajectories dictated by the dynamics of the environment and are usually concen...

journal_title：Neural computation

authors： Agostini A,Celaya E

更新日期：2017-01-01 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

authors： Franz MO,Chahl JS,Krapp HG

更新日期：2004-11-01 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：:Recently there has been great interest in sparse representations of signals under the assumption that signals (data sets) can be well approximated by a linear combination of few elements of a known basis (dictionary). Many algorithms have been developed to find such representations for one-dimensional signals (vectors...

journal_title：Neural computation

authors： Caiafa CF,Cichocki A

更新日期：2013-01-01 00:00:00

abstract：:A study of a general central pattern generator (CPG) is carried out by means of a measure of the gain of information between the number of available topology configurations and the output rhythmic activity. The neurons of the CPG are chaotic Hindmarsh-Rose models that cooperate dynamically to generate either chaotic o...

journal_title：Neural computation

authors： Stiesberg GR,Reyes MB,Varona P,Pinto RD,Huerta R

更新日期：2007-04-01 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：:The bias/variance decomposition of mean-squared error is well understood and relatively straightforward. In this note, a similar simple decomposition is derived, valid for any kind of error measure that, when using the appropriate probability model, can be derived from a Kullback-Leibler divergence or log-likelihood. ...

journal_title：Neural computation

authors： Heskes T

更新日期：1998-07-28 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：: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

authors： Zheng W,Zhao L,Zou C

更新日期：2004-06-01 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

authors： Hanson SJ,Negishi M

更新日期：2002-09-01 00:00:00

abstract：:We propose a scalable semiparametric Bayesian model to capture dependencies among multiple neurons by detecting their cofiring (possibly with some lag time) patterns over time. After discretizing time so there is at most one spike at each interval, the resulting sequence of 1s (spike) and 0s (silence) for each neuron ...

journal_title：Neural computation

authors： Shahbaba B,Zhou B,Lan S,Ombao H,Moorman D,Behseta S

更新日期：2014-09-01 00:00:00

abstract：:We study active learning (AL) based on gaussian processes (GPs) for efficiently enumerating all of the local minimum solutions of a black-box function. This problem is challenging because local solutions are characterized by their zero gradient and positive-definite Hessian properties, but those derivatives cannot be ...

journal_title：Neural computation

authors： Inatsu Y,Sugita D,Toyoura K,Takeuchi I

更新日期：2020-10-01 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：:Binocular fusion takes place over a limited region smaller than one degree of visual angle (Panum's fusional area), which is on the order of the range of preferred disparities measured in populations of disparity-tuned neurons in the visual cortex. However, the actual range of binocular disparities encountered in natu...

journal_title：Neural computation

authors： Tsang EK,Shi BE

更新日期：2008-10-01 00:00:00

abstract：:Recurrent neural architectures having oscillatory dynamics use rhythmic network activity to represent patterns stored in short-term memory. Multiple stored patterns can be retained in memory over the same neural substrate because the network's state persistently switches between them. Here we present a simple oscillat...

journal_title：Neural computation

authors： Winder RK,Reggia JA,Weems SA,Bunting MF

更新日期：2009-03-01 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：:We discuss robustness against mislabeling in multiclass labels for classification problems and propose two algorithms of boosting, the normalized Eta-Boost.M and Eta-Boost.M, based on the Eta-divergence. Those two boosting algorithms are closely related to models of mislabeling in which the label is erroneously exchan...

journal_title：Neural computation

authors： Takenouchi T,Eguchi S,Murata N,Kanamori T

更新日期：2008-06-01 00:00:00

abstract：:We address the problem of detecting the presence of a recurring stimulus by monitoring the voltage on a multiunit electrode located in a brain region densely populated by stimulus reactive neurons. Published experimental results suggest that under these conditions, when a stimulus is present, the measurements are gaus...

journal_title：Neural computation

authors： Nossenson N,Messer H

更新日期：2012-04-01 00:00:00

abstract：:Physiological signals such as neural spikes and heartbeats are discrete events in time, driven by continuous underlying systems. A recently introduced data-driven model to analyze such a system is a state-space model with point process observations, parameters of which and the underlying state sequence are simultaneou...

journal_title：Neural computation

authors： Yuan K,Niranjan M

更新日期：2010-08-01 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

authors： Rudolph M,Destexhe A

更新日期：2005-11-01 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：: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：: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