Abstract:
:The need to reason about uncertainty in large, complex, and multimodal data sets has become increasingly common across modern scientific environments. The ability to transform samples from one distribution
journal_name
Neural Computjournal_title
Neural computationauthors
Mesa DA,Tantiongloc J,Mendoza M,Kim S,P Coleman Tdoi
10.1162/neco_a_01172subject
Has Abstractpub_date
2019-04-01 00:00:00pages
613-652issue
4eissn
0899-7667issn
1530-888Xjournal_volume
31pub_type
杂志文章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
pub_type: 杂志文章
doi:10.1162/neco.1996.8.8.1611
更新日期:1996-11-15 00:00:00
abstract::A mathematical model, of general character for the dynamic description of coupled neural oscillators is presented. The population approach that is employed applies equally to coupled cells as to populations of such coupled cells. The formulation includes stochasticity and preserves details of precisely firing neurons....
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/neco.2007.03-07-482
更新日期:2008-05-01 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
pub_type: 杂志文章
doi:10.1162/089976698300017160
更新日期:1998-10-01 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
pub_type: 杂志文章
doi:10.1162/08997660260293292
更新日期:2002-10-01 00:00:00
abstract::A single-layered Hough transform network is proposed that accepts image coordinates of each object pixel as input and produces a set of outputs that indicate the belongingness of the pixel to a particular structure (e.g., a straight line). The network is able to learn adaptively the parametric forms of the linear segm...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976601300014501
更新日期:2001-03-01 00:00:00
abstract::Modeling stereo transparency with physiologically plausible mechanisms is challenging because in such frameworks, large receptive fields mix up overlapping disparities, whereas small receptive fields can reliably compute only small disparities. It seems necessary to combine information across scales. A coarse-to-fine ...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/NECO_a_00722
更新日期:2015-05-01 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
pub_type: 杂志文章
doi:10.1162/neco.2010.07-09-1047
更新日期:2010-08-01 00:00:00
abstract::Recent experiments indicate that the calcium store (e.g., endoplasmic reticulum) is involved in electrical bursting and [Ca2+]i oscillation in bursting neuronal cells. In this paper, we formulate a mathematical model for bursting neurons, which includes Ca2+ in the intracellular Ca2+ stores and a voltage-independent c...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/neco.1996.8.5.951
更新日期:1996-07-01 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
pub_type: 杂志文章
doi:10.1162/NECO_a_00764
更新日期:2015-09-01 00:00:00
abstract::Numerous animal behaviors, such as locomotion in vertebrates, are produced by rhythmic contractions that alternate between two muscle groups. The neuronal networks generating such alternate rhythmic activity are generally thought to rely on pacemaker cells or well-designed circuits consisting of inhibitory and excitat...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976698300017449
更新日期:1998-07-01 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
pub_type: 杂志文章
doi:10.1162/08997660260028656
更新日期:2002-07-01 00:00:00
abstract::For any memoryless communication channel with a binary-valued input and a one-dimensional real-valued output, we introduce a probabilistic lower bound on the mutual information given empirical observations on the channel. The bound is built on the Dvoretzky-Kiefer-Wolfowitz inequality and is distribution free. A quadr...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/NECO_a_00144
更新日期:2011-07-01 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
pub_type: 杂志文章
doi:10.1162/neco.2009.04-08-752
更新日期:2009-09-01 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
pub_type: 杂志文章
doi:10.1162/neco.1995.7.6.1225
更新日期:1995-11-01 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
pub_type: 杂志文章
doi:10.1162/neco.2009.12-08-922
更新日期:2010-02-01 00:00:00
abstract::The Hebbian paradigm is perhaps the best-known unsupervised learning theory in connectionism. It has inspired wide research activity in the artificial neural network field because it embodies some interesting properties such as locality and the capability of being applicable to the basic weight-and-sum structure of ne...
journal_title:Neural computation
pub_type: 杂志文章,评审
doi:10.1162/0899766053429381
更新日期:2005-04-01 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
pub_type: 杂志文章
doi:10.1162/NECO_a_00502
更新日期:2013-11-01 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
pub_type: 杂志文章
doi:10.1162/089976601300014583
更新日期:2001-02-01 00:00:00
abstract::Learning in a neuronal network is often thought of as a linear superposition of synaptic modifications induced by individual stimuli. However, since biological synapses are naturally bounded, a linear superposition would cause fast forgetting of previously acquired memories. Here we show that this forgetting can be av...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/0899766054615644
更新日期:2005-10-01 00:00:00
abstract::Intracortical brain computer interfaces can enable individuals with paralysis to control external devices through voluntarily modulated brain activity. Decoding quality has been previously shown to degrade with signal nonstationarities-specifically, the changes in the statistics of the data between training and testin...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/neco_a_01129
更新日期:2018-11-01 00:00:00
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
pub_type: 信件
doi:10.1162/NECO_a_00066
更新日期:2011-01-01 00:00:00
abstract::A minimal model is presented to explain changes in frequency, shape, and amplitude of Ca2+ oscillations in the neuroendocrine melanotrope cell of Xenopus Laevis. It describes the cell as a plasma membrane oscillator with influx of extracellular Ca2+ via voltage-gated Ca2+ channels in the plasma membrane. The Ca2+ osci...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976601300014655
更新日期:2001-01-01 00:00:00
abstract::Pairwise correlations among spike trains recorded in vivo have been frequently reported. It has been argued that correlated activity could play an important role in the brain, because it efficiently modulates the response of a postsynaptic neuron. We show here that a neuron's output firing rate critically depends on t...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976603321043702
更新日期:2003-01-01 00:00:00
abstract::Ohshiro, Hussain, and Weliky (2011) recently showed that ferrets reared with exposure to flickering spot stimuli, in the absence of oriented visual experience, develop oriented receptive fields. They interpreted this as refutation of efficient coding models, which require oriented input in order to develop oriented re...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/NECO_a_00333
更新日期:2012-09-01 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
pub_type: 杂志文章
doi:10.1162/0899766054322991
更新日期:2005-09-01 00:00:00
abstract::In this review, we compare methods for temporal sequence learning (TSL) across the disciplines machine-control, classical conditioning, neuronal models for TSL as well as spike-timing-dependent plasticity (STDP). This review introduces the most influential models and focuses on two questions: To what degree are reward...
journal_title:Neural computation
pub_type: 杂志文章,评审
doi:10.1162/0899766053011555
更新日期:2005-02-01 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
pub_type: 杂志文章
doi:10.1162/089976600300015286
更新日期:2000-07-01 00:00:00
abstract::This article presents a reinforcement learning framework for continuous-time dynamical systems without a priori discretization of time, state, and action. Based on the Hamilton-Jacobi-Bellman (HJB) equation for infinite-horizon, discounted reward problems, we derive algorithms for estimating value functions and improv...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976600300015961
更新日期:2000-01-01 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
pub_type: 杂志文章
doi:10.1162/NECO_a_00588
更新日期:2014-06-01 00:00:00
abstract::Complexity of one-hidden-layer networks is studied using tools from nonlinear approximation and integration theory. For functions with suitable integral representations in the form of networks with infinitely many hidden units, upper bounds are derived on the speed of decrease of approximation error as the number of n...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/neco.2009.04-08-745
更新日期:2009-10-01 00:00:00