Oscillating Networks: Control of Burst Duration by Electrically Coupled Neurons.

Abstract:

:The pyloric network of the stomatogastric ganglion in crustacea is a central pattern generator that can produce the same basic rhythm over a wide frequency range. Three electrically coupled neurons, the anterior burster (AB) neuron and two pyloric dilator (PD) neurons, act as a pacemaker unit for the pyloric network. The functional characteristics of the pacemaker network are the result of electrical coupling between neurons with quite different intrinsic properties, each contributing a basic feature to the complete circuit. The AB neuron, a conditional oscillator, plays a dominant role in rhythm generation. In the work described here, we manipulate the frequency of the AB neuron both isolated and electrically coupled to the PD neurons. Physiological and modeling studies indicate that the PD neurons play an important role in regulating the duration of the bursts produced by the pacemaker unit.

journal_name

Neural Comput

journal_title

Neural computation

authors

Abbott LF,Marder E,Hooper SL

doi

10.1162/neco.1991.3.4.487

subject

Has Abstract

pub_date

1991-01-01 00:00:00

pages

487-497

issue

4

eissn

0899-7667

issn

1530-888X

journal_volume

3

pub_type

杂志文章
  • On the performance of voltage stepping for the simulation of adaptive, nonlinear integrate-and-fire neuronal networks.

    abstract::In traditional event-driven strategies, spike timings are analytically given or calculated with arbitrary precision (up to machine precision). Exact computation is possible only for simplified neuron models, mainly the leaky integrate-and-fire model. In a recent paper, Zheng, Tonnelier, and Martinez (2009) introduced ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00112

    authors: Kaabi MG,Tonnelier A,Martinez D

    更新日期:2011-05-01 00:00:00

  • A Unifying Framework of Synaptic and Intrinsic Plasticity in Neural Populations.

    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

    authors: Leugering J,Pipa G

    更新日期:2018-04-01 00:00:00

  • Optimality of Upper-Arm Reaching Trajectories Based on the Expected Value of the Metabolic Energy Cost.

    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

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00757

    authors: Taniai Y,Nishii J

    更新日期:2015-08-01 00:00:00

  • McCulloch-Pitts Brains and Pseudorandom Functions.

    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

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00841

    authors: Chvátal V,Goldsmith M,Yang N

    更新日期:2016-06-01 00:00:00

  • When Not to Classify: Anomaly Detection of Attacks (ADA) on DNN Classifiers at Test Time.

    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

    pub_type: 杂志文章

    doi:10.1162/neco_a_01209

    authors: Miller D,Wang Y,Kesidis G

    更新日期:2019-08-01 00:00:00

  • Deficient GABAergic gliotransmission may cause broader sensory tuning in schizophrenia.

    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

    authors: Hoshino O

    更新日期:2013-12-01 00:00:00

  • Mean First Passage Memory Lifetimes by Reducing Complex Synapses to Simple Synapses.

    abstract::Memory models that store new memories by forgetting old ones have memory lifetimes that are rather short and grow only logarithmically in the number of synapses. Attempts to overcome these deficits include "complex" models of synaptic plasticity in which synapses possess internal states governing the expression of syn...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00956

    authors: Elliott T

    更新日期:2017-06-01 00:00:00

  • An amplitude equation approach to contextual effects in visual cortex.

    abstract::A mathematical theory of interacting hypercolumns in primary visual cortex (V1) is presented that incorporates details concerning the anisotropic nature of long-range lateral connections. Each hypercolumn is modeled as a ring of interacting excitatory and inhibitory neural populations with orientation preferences over...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976602317250870

    authors: Bressloff PC,Cowan JD

    更新日期:2002-03-01 00:00:00

  • Direct estimation of inhomogeneous Markov interval models of spike trains.

    abstract::A necessary ingredient for a quantitative theory of neural coding is appropriate "spike kinematics": a precise description of spike trains. While summarizing experiments by complete spike time collections is clearly inefficient and probably unnecessary, the most common probabilistic model used in neurophysiology, the ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2009.07-08-828

    authors: Wójcik DK,Mochol G,Jakuczun W,Wypych M,Waleszczyk WJ

    更新日期:2009-08-01 00:00:00

  • Pattern generation by two coupled time-discrete neural networks with synaptic depression.

    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

    authors: Senn W,Wannier T,Kleinle J,Lüscher HR,Müller L,Streit J,Wyler K

    更新日期:1998-07-01 00:00:00

  • Optimal approximation of signal priors.

    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

    authors: Hyvärinen A

    更新日期:2008-12-01 00:00:00

  • Methods for Assessment of Memory Reactivation.

    abstract::It has been suggested that reactivation of previously acquired experiences or stored information in declarative memories in the hippocampus and neocortex contributes to memory consolidation and learning. Understanding memory consolidation depends crucially on the development of robust statistical methods for assessing...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco_a_01090

    authors: Liu S,Grosmark AD,Chen Z

    更新日期:2018-08-01 00:00:00

  • Abstract stimulus-specific adaptation models.

    abstract::Many neurons that initially respond to a stimulus stop responding if the stimulus is presented repeatedly but recover their response if a different stimulus is presented. This phenomenon is referred to as stimulus-specific adaptation (SSA). SSA has been investigated extensively using oddball experiments, which measure...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00077

    authors: Mill R,Coath M,Wennekers T,Denham SL

    更新日期:2011-02-01 00:00:00

  • Computing confidence intervals for point process models.

    abstract::Characterizing neural spiking activity as a function of intrinsic and extrinsic factors is important in neuroscience. Point process models are valuable for capturing such information; however, the process of fully applying these models is not always obvious. A complete model application has four broad steps: specifica...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00198

    authors: Sarma SV,Nguyen DP,Czanner G,Wirth S,Wilson MA,Suzuki W,Brown EN

    更新日期:2011-11-01 00:00:00

  • ISO learning approximates a solution to the inverse-controller problem in an unsupervised behavioral paradigm.

    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

    authors: Porr B,von Ferber C,Wörgötter F

    更新日期:2003-04-01 00:00:00

  • Derivatives of logarithmic stationary distributions for policy gradient reinforcement learning.

    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

    authors: Morimura T,Uchibe E,Yoshimoto J,Peters J,Doya K

    更新日期:2010-02-01 00:00:00

  • A causal perspective on the analysis of signal and noise correlations and their role in population coding.

    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

    authors: Chicharro D

    更新日期:2014-06-01 00:00:00

  • Synaptic runaway in associative networks and the pathogenesis of schizophrenia.

    abstract::Synaptic runaway denotes the formation of erroneous synapses and premature functional decline accompanying activity-dependent learning in neural networks. This work studies synaptic runaway both analytically and numerically in binary-firing associative memory networks. It turns out that synaptic runaway is of fairly m...

    journal_title:Neural computation

    pub_type: 杂志文章,评审

    doi:10.1162/089976698300017836

    authors: Greenstein-Messica A,Ruppin E

    更新日期:1998-02-15 00:00:00

  • Bayesian framework for least-squares support vector machine classifiers, gaussian processes, and kernel Fisher discriminant analysis.

    abstract::The Bayesian evidence framework has been successfully applied to the design of multilayer perceptrons (MLPs) in the work of MacKay. Nevertheless, the training of MLPs suffers from drawbacks like the nonconvex optimization problem and the choice of the number of hidden units. In support vector machines (SVMs) for class...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976602753633411

    authors: Van Gestel T,Suykens JA,Lanckriet G,Lambrechts A,De Moor B,Vandewalle J

    更新日期:2002-05-01 00:00:00

  • Neural coding: higher-order temporal patterns in the neurostatistics of cell assemblies.

    abstract::Recent advances in the technology of multiunit recordings make it possible to test Hebb's hypothesis that neurons do not function in isolation but are organized in assemblies. This has created the need for statistical approaches to detecting the presence of spatiotemporal patterns of more than two neurons in neuron sp...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976600300014872

    authors: Martignon L,Deco G,Laskey K,Diamond M,Freiwald W,Vaadia E

    更新日期:2000-11-01 00:00:00

  • Does high firing irregularity enhance learning?

    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

    authors: Christodoulou C,Cleanthous A

    更新日期:2011-03-01 00:00:00

  • Range-based ICA using a nonsmooth quasi-newton optimizer for electroencephalographic source localization in focal epilepsy.

    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

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00700

    authors: Selvan SE,George ST,Balakrishnan R

    更新日期:2015-03-01 00:00:00

  • Piecewise-linear neural networks and their relationship to rule extraction from data.

    abstract::This article addresses the topic of extracting logical rules from data by means of artificial neural networks. The approach based on piecewise linear neural networks is revisited, which has already been used for the extraction of Boolean rules in the past, and it is shown that this approach can be important also for t...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2006.18.11.2813

    authors: Holena M

    更新日期:2006-11-01 00:00:00

  • Mismatched training and test distributions can outperform matched ones.

    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

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00697

    authors: González CR,Abu-Mostafa YS

    更新日期:2015-02-01 00:00:00

  • Transmission of population-coded information.

    abstract::As neural activity is transmitted through the nervous system, neuronal noise degrades the encoded information and limits performance. It is therefore important to know how information loss can be prevented. We study this question in the context of neural population codes. Using Fisher information, we show how informat...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00227

    authors: Renart A,van Rossum MC

    更新日期:2012-02-01 00:00:00

  • State-Space Representations of Deep Neural Networks.

    abstract::This letter deals with neural networks as dynamical systems governed by finite difference equations. It shows that the introduction of k -many skip connections into network architectures, such as residual networks and additive dense n...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco_a_01165

    authors: Hauser M,Gunn S,Saab S Jr,Ray A

    更新日期:2019-03-01 00:00:00

  • A Mean-Field Description of Bursting Dynamics in Spiking Neural Networks with Short-Term Adaptation.

    abstract::Bursting plays an important role in neural communication. At the population level, macroscopic bursting has been identified in populations of neurons that do not express intrinsic bursting mechanisms. For the analysis of phase transitions between bursting and non-bursting states, mean-field descriptions of macroscopic...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco_a_01300

    authors: Gast R,Schmidt H,Knösche TR

    更新日期:2020-09-01 00:00:00

  • Binocular receptive field models, disparity tuning, and characteristic disparity.

    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

    authors: Zhu YD,Qian N

    更新日期:1996-11-15 00:00:00

  • A semiparametric Bayesian model for detecting synchrony among multiple neurons.

    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

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00631

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

    更新日期:2014-09-01 00:00:00

  • Spiking neural P systems with astrocytes.

    abstract::In a biological nervous system, astrocytes play an important role in the functioning and interaction of neurons, and astrocytes have excitatory and inhibitory influence on synapses. In this work, with this biological inspiration, a class of computation devices that consist of neurons and astrocytes is introduced, call...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00238

    authors: Pan L,Wang J,Hoogeboom HJ

    更新日期:2012-03-01 00:00:00