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 (and the improvement over standard regression models for such classifiers), we develop novel Fisher kernels based on mixture of mixed-effects models and use them in support vector machine classifiers. The hierarchical generative model allows us to handle variations in sequence length and sampling interval gracefully. We also give nonparametric kernels not based on generative models, but rather on the reproducing kernel Hilbert space. We apply the methods to detecting cognitive decline from longitudinal clinical data on motor and neuropsychological tests. The likelihood ratio classifiers based on the neuropsychological tests perform better than than classifiers based on the motor behavior. Discriminant classifiers performed better than likelihood ratio classifiers for the motor behavior tests.
journal_name
Neural Computjournal_title
Neural computationauthors
Lu Z,Leen TK,Kaye Jdoi
10.1162/NECO_a_00164subject
Has Abstractpub_date
2011-09-01 00:00:00pages
2390-420issue
9eissn
0899-7667issn
1530-888Xjournal_volume
23pub_type
杂志文章abstract::Many different types of integrate-and-fire models have been designed in order to explain how it is possible for a cortical neuron to integrate over many independent inputs while still producing highly variable spike trains. Within this context, the variability of spike trains has been almost exclusively measured using...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/0899766041732413
更新日期:2004-10-01 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
pub_type: 杂志文章
doi:10.1162/NECO_a_00090
更新日期:2011-03-01 00:00:00
abstract::Izhikevich (2003) proposed a new canonical neuron model of spike generation. The model was surprisingly simple yet able to accurately replicate the firing patterns of different types of cortical cell. Here, we derive a solution method that allows efficient simulation of the model. ...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/neco.2007.19.12.3216
更新日期:2007-12-01 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
pub_type: 杂志文章
doi:10.1162/089976600300015286
更新日期:2000-07-01 00:00:00
abstract::Recent experimental findings have shown the presence of robust and cell-type-specific intraburst firing patterns in bursting neurons. We address the problem of characterizing these patterns under the assumption that the bursts exhibit well-defined firing time distributions. We propose a method for estimating these dis...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/neco.2008.07-07-571
更新日期:2009-04-01 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
pub_type: 杂志文章
doi:10.1162/neco.2007.19.1.139
更新日期:2007-01-01 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::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
pub_type: 杂志文章
doi:10.1162/NECO_a_00519
更新日期:2013-12-01 00:00:00
abstract::A neuronal population is a computational unit that receives a multivariate, time-varying input signal and creates a related multivariate output. These neural signals are modeled as stochastic processes that transmit information in real time, subject to stochastic noise. In a stationary environment, where the input sig...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/neco_a_01057
更新日期:2018-04-01 00:00:00
abstract::We generalize recent theoretical work on the minimal number of layers of narrow deep belief networks that can approximate any probability distribution on the states of their visible units arbitrarily well. We relax the setting of binary units (Sutskever & Hinton, 2008 ; Le Roux & Bengio, 2008 , 2010 ; Montúfar & Ay, 2...
journal_title:Neural computation
pub_type: 信件
doi:10.1162/NECO_a_00601
更新日期:2014-07-01 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
pub_type: 杂志文章
doi:10.1162/NECO_a_00306
更新日期:2012-08-01 00:00:00
abstract::Multiple adjacent, roughly mirror-image topographic maps are commonly observed in the sensory neocortex of many species. The cortical regions occupied by these maps are generally believed to be determined initially by genetically controlled chemical markers during development, with thalamocortical afferent activity su...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/0899766053491904
更新日期:2005-05-01 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::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
pub_type: 杂志文章
doi:10.1162/neco.2009.02-09-956
更新日期:2010-03-01 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::In this letter, we propose a noisy nonlinear version of independent component analysis (ICA). Assuming that the probability density function (p. d. f.) of sources is known, a learning rule is derived based on maximum likelihood estimation (MLE). Our model involves some algorithms of noisy linear ICA (e. g., Bermond & ...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/0899766052530866
更新日期:2005-01-01 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
pub_type: 杂志文章
doi:10.1162/089976606774841521
更新日期:2006-01-01 00:00:00
abstract::A hippocampal prosthesis is a very large scale integration (VLSI) biochip that needs to be implanted in the biological brain to solve a cognitive dysfunction. In this letter, we propose a novel low-complexity, small-area, and low-power programmable hippocampal neural network application-specific integrated circuit (AS...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/neco_a_01107
更新日期:2018-09-01 00:00:00
abstract::We perform a detailed fixed-point analysis of two-unit recurrent neural networks with sigmoid-shaped transfer functions. Using geometrical arguments in the space of transfer function derivatives, we partition the network state-space into distinct regions corresponding to stability types of the fixed points. Unlike in ...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/08997660152002898
更新日期:2001-06-01 00:00:00
abstract::A representational scheme under which the ranking between represented similarities is isomorphic to the ranking between the corresponding shape similarities can support perfectly correct shape classification because it preserves the clustering of shapes according to the natural kinds prevailing in the external world. ...
journal_title:Neural computation
pub_type: 杂志文章,评审
doi:10.1162/neco.1997.9.4.701
更新日期:1997-05-15 00:00:00
abstract::In this letter, we develop a gaussian process model for clustering. The variances of predictive values in gaussian processes learned from a training data are shown to comprise an estimate of the support of a probability density function. The constructed variance function is then applied to construct a set of contours ...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/neco.2007.19.11.3088
更新日期:2007-11-01 00:00:00
abstract::In signal restoration by Bayesian inference, one typically uses a parametric model of the prior distribution of the signal. Here, we consider how the parameters of a prior model should be estimated from observations of uncorrupted signals. A lot of recent work has implicitly assumed that maximum likelihood estimation ...
journal_title:Neural computation
pub_type: 信件
doi:10.1162/neco.2008.10-06-384
更新日期:2008-12-01 00:00:00
abstract::For the paradigmatic case of bimanual coordination, we review levels of organization of behavioral dynamics and present a description in terms of modes of behavior. We briefly review a recently developed model of spatiotemporal brain activity that is based on short- and long-range connectivity of neural ensembles. Thi...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976698300016954
更新日期:1998-11-15 00:00:00
abstract::In this letter, we perform a complete and in-depth analysis of Lorentzian noises, such as those arising from [Formula: see text] and [Formula: see text] channel kinetics, in order to identify the source of [Formula: see text]-type noise in neurological membranes. We prove that the autocovariance of Lorentzian noise de...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/NECO_a_01067
更新日期:2018-07-01 00:00:00
abstract::In this letter, we investigate the impact of choosing different loss functions from the viewpoint of statistical learning theory. We introduce a convexity assumption, which is met by all loss functions commonly used in the literature, and study how the bound on the estimation error changes with the loss. We also deriv...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976604773135104
更新日期:2004-05-01 00:00:00
abstract::In this letter, a standard postnonlinear blind source separation algorithm is proposed, based on the MISEP method, which is widely used in linear and nonlinear independent component analysis. To best suit a wide class of postnonlinear mixtures, we adapt the MISEP method to incorporate a priori information of the mixtu...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/neco.2007.19.9.2557
更新日期:2007-09-01 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
pub_type: 杂志文章
doi:10.1162/089976602760128090
更新日期:2002-08-01 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
pub_type: 杂志文章
doi:10.1162/neco_a_01039
更新日期:2018-02-01 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
pub_type: 杂志文章
doi:10.1162/08997660360581930
更新日期:2003-04-01 00:00:00
abstract::In a previous article, we considered game trees as graphical models. Adopting an evaluation function that returned a probability distribution over values likely to be taken at a given position, we described how to build a model of uncertainty and use it for utility-directed growth of the search tree and for deciding o...
journal_title:Neural computation
pub_type: 杂志文章
doi:10.1162/089976699300016881
更新日期:1999-01-01 00:00:00