Patterns of synchrony in neural networks with spike adaptation.

abstract：:Experimental studies of reasoning and planned behavior have provided evidence that nervous systems use internal models to perform predictive motor control, imagery, inference, and planning. Classical (model-free) reinforcement learning approaches omit such a model; standard sensorimotor models account for forward and ...

journal_title：Neural computation

authors： Toussaint M

更新日期：2006-05-01 00:00:00

abstract：:When we move our body to perform a movement task, our central nervous system selects a movement trajectory from an infinite number of possible trajectories under constraints that have been acquired through evolution and learning. Minimization of the energy cost has been suggested as a potential candidate for a constra...

journal_title：Neural computation

authors： Taniai Y,Nishii J

更新日期：2015-08-01 00:00:00

abstract：:Neural networks are often employed as tools in classification tasks. The use of large networks increases the likelihood of the task's being learned, although it may also lead to increased complexity. Pruning is an effective way of reducing the complexity of large networks. We present discriminant components pruning (D...

journal_title：Neural computation

authors： Koene RA,Takane Y

更新日期：1999-04-01 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：:Much experimental evidence suggests that during decision making, neural circuits accumulate evidence supporting alternative options. A computational model well describing this accumulation for choices between two options assumes that the brain integrates the log ratios of the likelihoods of the sensory inputs given th...

journal_title：Neural computation

authors： Kurzawa N,Summerfield C,Bogacz R

更新日期：2017-02-01 00:00:00

abstract：:We develop a group-theoretical analysis of slow feature analysis for the case where the input data are generated by applying a set of continuous transformations to static templates. As an application of the theory, we analytically derive nonlinear visual receptive fields and show that their optimal stimuli, as well as...

journal_title：Neural computation

authors： Sprekeler H,Wiskott L

更新日期：2011-02-01 00:00:00

abstract：:Knowledge of synaptic input is crucial for understanding synaptic integration and ultimately neural function. However, in vivo, the rates at which synaptic inputs arrive are high, so that it is typically impossible to detect single events. We show here that it is nevertheless possible to extract the properties of the ...

journal_title：Neural computation

authors： Puggioni P,Jelitai M,Duguid I,van Rossum MCW

更新日期：2017-07-01 00:00:00

abstract：:This article presents a new theoretical framework to consider the dynamics of a stochastic spiking neuron model with general membrane response to input spike. We assume that the input spikes obey an inhomogeneous Poisson process. The stochastic process of the membrane potential then becomes a gaussian process. When a ...

journal_title：Neural computation

authors： Amemori KI,Ishii S

更新日期：2001-12-01 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：:Humans have the ability to learn novel motor tasks while manipulating the environment. Several models of motor learning have been proposed in the literature, but few of them address the problem of retention and interference of motor memory. The modular selection and identification for control (MOSAIC) model, originall...

journal_title：Neural computation

authors： Lonini L,Dipietro L,Zollo L,Guglielmelli E,Krebs HI

更新日期：2009-07-01 00:00:00

abstract：:Under the goal-driven paradigm, Yamins et al. ( 2014 ; Yamins & DiCarlo, 2016 ) have shown that by optimizing only the final eight-way categorization performance of a four-layer hierarchical network, not only can its top output layer quantitatively predict IT neuron responses but its penultimate layer can also automat...

journal_title：Neural computation

authors： Dong Q,Wang H,Hu Z

更新日期：2018-02-01 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：: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 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：:The expected free energy (EFE) is a central quantity in the theory of active inference. It is the quantity that all active inference agents are mandated to minimize through action, and its decomposition into extrinsic and intrinsic value terms is key to the balance of exploration and exploitation that active inference...

journal_title：Neural computation

authors： Millidge B,Tschantz A,Buckley CL

更新日期：2021-01-05 00:00:00

abstract：:Neural associative memories are perceptron-like single-layer networks with fast synaptic learning typically storing discrete associations between pairs of neural activity patterns. Previous work optimized the memory capacity for various models of synaptic learning: linear Hopfield-type rules, the Willshaw model employ...

journal_title：Neural computation

authors： Knoblauch A

更新日期：2011-06-01 00:00:00

abstract：:Correlated neural activity has been observed at various signal levels (e.g., spike count, membrane potential, local field potential, EEG, fMRI BOLD). Most of these signals can be considered as superpositions of spike trains filtered by components of the neural system (synapses, membranes) and the measurement process. ...

journal_title：Neural computation

authors： Tetzlaff T,Rotter S,Stark E,Abeles M,Aertsen A,Diesmann M

更新日期：2008-09-01 00:00:00

abstract：:This article presents new procedures for multisite spatiotemporal neuronal data analysis. A new statistical model - the diffusion model - is considered, whose parameters can be estimated from experimental data thanks to mean-field approximations. This work has been applied to optical recording of the guinea pig's audi...

journal_title：Neural computation

authors： François O,Abdallahi LM,Horikawa J,Taniguchi I,Hervé T

更新日期：2000-08-01 00:00:00

abstract：:Integrate-and-express models of synaptic plasticity propose that synapses integrate plasticity induction signals before expressing synaptic plasticity. By discerning trends in their induction signals, synapses can control destabilizing fluctuations in synaptic strength. In a feedforward perceptron framework with binar...

journal_title：Neural computation

authors： Elliott T

更新日期：2016-11-01 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

authors： Boegerhausen M,Suter P,Liu SC

更新日期：2003-02-01 00:00:00

abstract：:Pharmacologically isolated GABAergic irregular spiking and stuttering interneurons in the mouse visual cortex display highly irregular spike times, with high coefficients of variation approximately 0.9-3, in response to a depolarizing, constant current input. This is in marked contrast to cortical pyramidal cells, whi...

journal_title：Neural computation

authors： Englitz B,Stiefel KM,Sejnowski TJ

更新日期：2008-01-01 00:00:00

abstract：:Activities of sensory-specific cortices are known to be suppressed when presented with a different sensory modality stimulus. This is referred to as cross-modal inhibition, for which the conventional synaptic mechanism is unlikely to work. Interestingly, the cross-modal inhibition could be eliminated when presented wi...

journal_title：Neural computation

authors： Hoshino O

更新日期：2012-11-01 00:00:00

abstract：:The mutual information between a set of stimuli and the elicited neural responses is compared to the corresponding decoded information. The decoding procedure is presented as an artificial distortion of the joint probabilities between stimuli and responses. The information loss is quantified. Whenever the probabilitie...

journal_title：Neural computation

authors： Samengo I

更新日期：2002-04-01 00:00:00

abstract：:In this article, a biologically plausible and efficient object recognition system (called ORASSYLL) is introduced, based on a set of a priori constraints motivated by findings of developmental psychology and neurophysiology. These constraints are concerned with the organization of the input in local and corresponding ...

journal_title：Neural computation

authors： Krüger N

更新日期：2001-02-01 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：:The Nyström method is a well-known sampling-based technique for approximating the eigensystem of large kernel matrices. However, the chosen samples in the Nyström method are all assumed to be of equal importance, which deviates from the integral equation that defines the kernel eigenfunctions. Motivated by this observ...

journal_title：Neural computation

authors： Zhang K,Kwok JT

更新日期：2009-01-01 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：:Previous studies have combined analytical models of stochastic neural responses with signal detection theory (SDT) to predict psychophysical performance limits; however, these studies have typically been limited to simple models and simple psychophysical tasks. A companion article in this issue ("Evaluating Auditory P...

journal_title：Neural computation

authors： Heinz MG,Colburn HS,Carney LH

更新日期：2001-10-01 00:00:00

abstract：:The double traveling salesman problem is a variation of the basic traveling salesman problem where targets can be reached by two salespersons operating in parallel. The real problem addressed by this work concerns the optimization of the harvest sequence for the two independent arms of a fruit-harvesting robot. This a...

journal_title：Neural computation

authors： Plebe A,Anile AM

更新日期：2002-02-01 00:00:00

abstract：:Although the number of artificial neural network and machine learning architectures is growing at an exponential pace, more attention needs to be paid to theoretical guarantees of asymptotic convergence for novel, nonlinear, high-dimensional adaptive learning algorithms. When properly understood, such guarantees can g...

journal_title：Neural computation

authors： Golden RM

更新日期：2018-10-01 00:00:00