abstract：:The free-energy principle is a candidate unified theory for learning and memory in the brain that predicts that neurons, synapses, and neuromodulators work in a manner that minimizes free energy. However, electrophysiological data elucidating the neural and synaptic bases for this theory are lacking. Here, we propose ...

journal_title：Neural computation

authors： Isomura T,Sakai K,Kotani K,Jimbo Y

更新日期：2016-09-01 00:00:00

abstract：:Large-scale data collection efforts to map the brain are underway at multiple spatial and temporal scales, but all face fundamental problems posed by high-dimensional data and intersubject variability. Even seemingly simple problems, such as identifying a neuron/brain region across animals/subjects, become exponential...

journal_title：Neural computation

authors： Frady EP,Kapoor A,Horvitz E,Kristan WB Jr

更新日期：2016-08-01 00:00:00

abstract：:In a pioneering classic, Warren McCulloch and Walter Pitts proposed a model of the central nervous system. Motivated by EEG recordings of normal brain activity, Chvátal and Goldsmith asked whether these dynamical systems can be engineered to produce trajectories that are irregular, disorderly, and apparently unpredict...

journal_title：Neural computation

authors： Chvátal V,Goldsmith M,Yang N

更新日期：2016-06-01 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：:We derive a synaptic weight update rule for learning temporally precise spike train-to-spike train transformations in multilayer feedforward networks of spiking neurons. The framework, aimed at seamlessly generalizing error backpropagation to the deterministic spiking neuron setting, is based strictly on spike timing ...

journal_title：Neural computation

authors： Banerjee A

更新日期：2016-05-01 00:00:00

abstract：:Ramping neuronal activity refers to spiking activity with a rate that increases quasi-linearly over time. It has been observed in multiple cortical areas and is correlated with evidence accumulation processes or timing. In this work, we investigated the downstream effect of ramping neuronal activity through synapses t...

journal_title：Neural computation

authors： Wei W,Wang XJ

更新日期：2016-04-01 00:00:00

abstract：:Common representation learning (CRL), wherein different descriptions (or views) of the data are embedded in a common subspace, has been receiving a lot of attention recently. Two popular paradigms here are canonical correlation analysis (CCA)-based approaches and autoencoder (AE)-based approaches. CCA-based approaches...

journal_title：Neural computation

authors： Chandar S,Khapra MM,Larochelle H,Ravindran B

更新日期：2016-02-01 00:00:00

abstract：:We argue that when faced with big data sets, learning and inference algorithms should compute updates using only subsets of data items. We introduce algorithms that use sequential hypothesis tests to adaptively select such a subset of data points. The statistical properties of this subsampling process can be used to c...

journal_title：Neural computation

authors： Korattikara A,Chen Y,Welling M

更新日期：2016-01-01 00:00:00

abstract：:We study the expressive power of positive neural networks. The model uses positive connection weights and multiple input neurons. Different behaviors can be expressed by varying the connection weights. We show that in discrete time and in the absence of noise, the class of positive neural networks captures the so-call...

journal_title：Neural computation

authors： Ameloot TJ,Van den Bussche J

更新日期：2015-12-01 00:00:00

abstract：:Humans learn categories of complex objects quickly and from a few examples. Random projection has been suggested as a means to learn and categorize efficiently. We investigate how random projection affects categorization by humans and by very simple neural networks on the same stimuli and categorization tasks, and how...

journal_title：Neural computation

authors： Arriaga RI,Rutter D,Cakmak M,Vempala SS

更新日期：2015-10-01 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：: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：:Primary visual cortical complex cells are thought to serve as invariant feature detectors and to provide input to higher cortical areas. We propose a single model for learning the connectivity required by complex cells that integrates two factors that have been hypothesized to play a role in the development of invaria...

journal_title：Neural computation

authors： Chandrapala TN,Shi BE

更新日期：2015-07-01 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：: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

authors： Li Z,Qian N

更新日期：2015-05-01 00:00:00

abstract：:Independent component analysis (ICA) aims at separating a multivariate signal into independent nongaussian signals by optimizing a contrast function with no knowledge on the mixing mechanism. Despite the availability of a constellation of contrast functions, a Hartley-entropy-based ICA contrast endowed with the discri...

journal_title：Neural computation

authors： Selvan SE,George ST,Balakrishnan R

更新日期：2015-03-01 00:00:00

abstract：:In learning theory, the training and test sets are assumed to be drawn from the same probability distribution. This assumption is also followed in practical situations, where matching the training and test distributions is considered desirable. Contrary to conventional wisdom, we show that mismatched training and test...

journal_title：Neural computation

authors： González CR,Abu-Mostafa YS

更新日期：2015-02-01 00:00:00

abstract：:Regression aims at estimating the conditional mean of output given input. However, regression is not informative enough if the conditional density is multimodal, heteroskedastic, and asymmetric. In such a case, estimating the conditional density itself is preferable, but conditional density estimation (CDE) is challen...

journal_title：Neural computation

authors： Tangkaratt V,Xie N,Sugiyama M

更新日期：2015-01-01 00:00:00

abstract：:Spiking neural P systems (SN P systems) are a class of distributed parallel computing devices inspired by spiking neurons, where the spiking rules are usually used in a sequential way (an applicable rule is applied one time at a step) or an exhaustive way (an applicable rule is applied as many times as possible at a s...

journal_title：Neural computation

authors： Zhang X,Wang B,Pan L

更新日期：2014-12-01 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 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：:A firing rate map, also known as a tuning curve, describes the nonlinear relationship between a neuron's spike rate and a low-dimensional stimulus (e.g., orientation, head direction, contrast, color). Here we investigate Bayesian active learning methods for estimating firing rate maps in closed-loop neurophysiology ex...

journal_title：Neural computation

authors： Park M,Weller JP,Horwitz GD,Pillow JW

更新日期：2014-08-01 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

authors： Montúfar GF

更新日期：2014-07-01 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：:Nondeclarative memory and novelty processing in the brain is an actively studied field of neuroscience, and reducing neural activity with repetition of a stimulus (repetition suppression) is a commonly observed phenomenon. Recent findings of an opposite trend-specifically, rising activity for unfamiliar stimuli-questi...

journal_title：Neural computation

authors： Makukhin K,Bolland S

更新日期：2014-04-01 00:00:00

abstract：:Ordinal classification (also known as ordinal regression) is a supervised learning task that consists of estimating the rating of a data item on a fixed, discrete rating scale. This problem is receiving increased attention from the sentiment analysis and opinion mining community due to the importance of automatically ...

journal_title：Neural computation

authors： Baccianella S,Esuli A,Sebastiani F

更新日期：2014-03-01 00:00:00

abstract：:We consider learning a causal ordering of variables in a linear nongaussian acyclic model called LiNGAM. Several methods have been shown to consistently estimate a causal ordering assuming that all the model assumptions are correct. But the estimation results could be distorted if some assumptions are violated. In thi...

journal_title：Neural computation

authors： Tashiro T,Shimizu S,Hyvärinen A,Washio T

更新日期：2014-01-01 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：: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：:We present formal specification and verification of a robot moving in a complex network, using temporal sequence learning to avoid obstacles. Our aim is to demonstrate the benefit of using a formal approach to analyze such a system as a complementary approach to simulation. We first describe a classical closed-loop si...

journal_title：Neural computation

authors： Kirwan R,Miller A,Porr B,Di Prodi P

更新日期：2013-11-01 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：:Recent experimental and computational evidence suggests that several dynamical properties may characterize the operating point of functioning neural networks: critical branching, neutral stability, and production of a wide range of firing patterns. We seek the simplest setting in which these properties emerge, clarify...

journal_title：Neural computation

authors： Cayco-Gajic NA,Shea-Brown E

更新日期：2013-07-01 00:00:00

abstract：:In pattern recognition, data integration is an important issue, and when properly done, it can lead to improved performance. Also, data integration can be used to help model and understand multimodal processing in the brain. Amari proposed α-integration as a principled way of blending multiple positive measures (e.g.,...

journal_title：Neural computation

authors： Choi H,Choi S,Choe Y

更新日期：2013-06-01 00:00:00

abstract：:The instantaneous phase of neural rhythms is important to many neuroscience-related studies. In this letter, we show that the statistical sampling properties of three instantaneous phase estimators commonly employed to analyze neuroscience data share common features, allowing an analytical investigation into their beh...

journal_title：Neural computation

authors： Lepage KQ,Kramer MA,Eden UT

更新日期：2013-04-01 00:00:00

abstract：:The goal of sufficient dimension reduction in supervised learning is to find the low-dimensional subspace of input features that contains all of the information about the output values that the input features possess. In this letter, we propose a novel sufficient dimension-reduction method using a squared-loss variant...

journal_title：Neural computation

authors： Suzuki T,Sugiyama M

更新日期：2013-03-01 00:00:00

abstract：:Controlling for multiple hypothesis tests using standard spike resampling techniques often requires prohibitive amounts of computation. Importance sampling techniques can be used to accelerate the computation. The general theory is presented, along with specific examples for testing differences across conditions using...

journal_title：Neural computation

authors： Harrison MT

更新日期：2013-02-01 00:00:00

abstract：:We simulate the inhibition of Ia-glutamatergic excitatory postsynaptic potential (EPSP) by preceding it with glycinergic recurrent (REN) and reciprocal (REC) inhibitory postsynaptic potentials (IPSPs). The inhibition is evaluated in the presence of voltage-dependent conductances of sodium, delayed rectifier potassium,...

journal_title：Neural computation

authors： Gradwohl G,Grossman Y

更新日期：2013-01-01 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：: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：:We propose a new principle for replicating receptive field properties of neurons in the primary visual cortex. We derive a learning rule for a feedforward network, which maintains a low firing rate for the output neurons (resulting in temporal sparseness) and allows only a small subset of the neurons in the network to...

journal_title：Neural computation

authors： Tanaka T,Aoyagi T,Kaneko T

更新日期：2012-10-01 00:00:00