Constraint on the number of synaptic inputs to a visual cortical neuron controls receptive field formation.

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 biological mechanisms underlying such constraints remain unclear. In this study, we addressed this issue by formulating a synaptic constraint based on activity-dependent mechanisms of synaptic changes. Particularly, considering metabotropic glutamate receptor-mediated long-term depression, we derived synaptic constraint that suppresses the number of inputs from individual presynaptic neurons. We performed computer simulations of the activity-dependent self-organization of geniculocortical inputs with the synaptic constraint and examined the formation of receptive fields (RFs) of model visual cortical neurons. When we changed the magnitude of the synaptic constraint, we found the emergence of distinct RF structures such as concentric RFs, simple-cell-like RFs, and double-oriented RFs and also a gradual transition between spatiotemporal separable and inseparable RFs. Thus, the model based on the synaptic constraint derived from biological consideration can account systematically for the repertoire of RF structures observed in the primary visual cortices of different species for the first time.

journal_name

Neural Comput

journal_title

Neural computation

authors

Tanaka S,Miyashita M

doi

10.1162/neco.2009.04-08-752

subject

Has Abstract

pub_date

2009-09-01 00:00:00

pages

2554-80

issue

9

eissn

0899-7667

issn

1530-888X

journal_volume

21

pub_type

杂志文章
  • Accelerated spike resampling for accurate multiple testing controls.

    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

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00399

    authors: Harrison MT

    更新日期:2013-02-01 00:00:00

  • Analyzing and Accelerating the Bottlenecks of Training Deep SNNs With Backpropagation.

    abstract::Spiking neural networks (SNNs) with the event-driven manner of transmitting spikes consume ultra-low power on neuromorphic chips. However, training deep SNNs is still challenging compared to convolutional neural networks (CNNs). The SNN training algorithms have not achieved the same performance as CNNs. In this letter...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco_a_01319

    authors: Chen R,Li L

    更新日期:2020-12-01 00:00:00

  • Nonmonotonic generalization bias of Gaussian mixture models.

    abstract::Theories of learning and generalization hold that the generalization bias, defined as the difference between the training error and the generalization error, increases on average with the number of adaptive parameters. This article, however, shows that this general tendency is violated for a gaussian mixture model. Fo...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976600300015439

    authors: Akaho S,Kappen HJ

    更新日期:2000-06-01 00:00:00

  • Analytical integrate-and-fire neuron models with conductance-based dynamics for event-driven simulation strategies.

    abstract::Event-driven simulation strategies were proposed recently to simulate integrate-and-fire (IF) type neuronal models. These strategies can lead to computationally efficient algorithms for simulating large-scale networks of neurons; most important, such approaches are more precise than traditional clock-driven numerical ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2006.18.9.2146

    authors: Rudolph M,Destexhe A

    更新日期:2006-09-01 00:00:00

  • Delay Differential Analysis of Seizures in Multichannel Electrocorticography Data.

    abstract::High-density electrocorticogram (ECoG) electrodes are capable of recording neurophysiological data with high temporal resolution with wide spatial coverage. These recordings are a window to understanding how the human brain processes information and subsequently behaves in healthy and pathologic states. Here, we descr...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco_a_01009

    authors: Lainscsek C,Weyhenmeyer J,Cash SS,Sejnowski TJ

    更新日期:2017-12-01 00:00:00

  • A modified algorithm for generalized discriminant analysis.

    abstract::Generalized discriminant analysis (GDA) is an extension of the classical linear discriminant analysis (LDA) from linear domain to a nonlinear domain via the kernel trick. However, in the previous algorithm of GDA, the solutions may suffer from the degenerate eigenvalue problem (i.e., several eigenvectors with the same...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976604773717612

    authors: Zheng W,Zhao L,Zou C

    更新日期:2004-06-01 00:00:00

  • Universal approximation depth and errors of narrow belief networks with discrete units.

    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

    authors: Montúfar GF

    更新日期:2014-07-01 00:00:00

  • Solution methods for a new class of simple model neurons.

    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

    authors: Humphries MD,Gurney K

    更新日期:2007-12-01 00:00:00

  • Multistability in spiking neuron models of delayed recurrent inhibitory loops.

    abstract::We consider the effect of the effective timing of a delayed feedback on the excitatory neuron in a recurrent inhibitory loop, when biological realities of firing and absolute refractory period are incorporated into a phenomenological spiking linear or quadratic integrate-and-fire neuron model. We show that such models...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2007.19.8.2124

    authors: Ma J,Wu J

    更新日期:2007-08-01 00:00:00

  • A neural-network-based approach to the double traveling salesman problem.

    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

    pub_type: 杂志文章

    doi:10.1162/08997660252741194

    authors: Plebe A,Anile AM

    更新日期:2002-02-01 00:00:00

  • The Ornstein-Uhlenbeck process does not reproduce spiking statistics of neurons in prefrontal cortex.

    abstract::Cortical neurons of behaving animals generate irregular spike sequences. Recently, there has been a heated discussion about the origin of this irregularity. Softky and Koch (1993) pointed out the inability of standard single-neuron models to reproduce the irregularity of the observed spike sequences when the model par...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976699300016511

    authors: Shinomoto S,Sakai Y,Funahashi S

    更新日期:1999-05-15 00:00:00

  • Time-varying perturbations can distinguish among integrate-to-threshold models for perceptual decision making in reaction time tasks.

    abstract::Several integrate-to-threshold models with differing temporal integration mechanisms have been proposed to describe the accumulation of sensory evidence to a prescribed level prior to motor response in perceptual decision-making tasks. An experiment and simulation studies have shown that the introduction of time-varyi...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2009.07-08-817

    authors: Zhou X,Wong-Lin K,Philip H

    更新日期:2009-08-01 00:00:00

  • Synchrony and desynchrony in integrate-and-fire oscillators.

    abstract::Due to many experimental reports of synchronous neural activity in the brain, there is much interest in understanding synchronization in networks of neural oscillators and its potential for computing perceptual organization. Contrary to Hopfield and Herz (1995), we find that networks of locally coupled integrate-and-f...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976699300016160

    authors: Campbell SR,Wang DL,Jayaprakash C

    更新日期:1999-10-01 00:00:00

  • Some sampling properties of common phase estimators.

    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

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00422

    authors: Lepage KQ,Kramer MA,Eden UT

    更新日期:2013-04-01 00:00:00

  • Modeling slowly bursting neurons via calcium store and voltage-independent calcium current.

    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

    authors: Chay TR

    更新日期:1996-07-01 00:00:00

  • Regularized neural networks: some convergence rate results.

    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

    authors: Corradi V,White H

    更新日期:1995-11-01 00:00:00

  • Selectivity and stability via dendritic nonlinearity.

    abstract::Inspired by recent studies regarding dendritic computation, we constructed a recurrent neural network model incorporating dendritic lateral inhibition. Our model consists of an input layer and a neuron layer that includes excitatory cells and an inhibitory cell; this inhibitory cell is activated by the pooled activiti...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2007.19.7.1798

    authors: Morita K,Okada M,Aihara K

    更新日期:2007-07-01 00:00:00

  • A simple Hebbian/anti-Hebbian network learns the sparse, independent components of natural images.

    abstract::Slightly modified versions of an early Hebbian/anti-Hebbian neural network are shown to be capable of extracting the sparse, independent linear components of a prefiltered natural image set. An explanation for this capability in terms of a coupling between two hypothetical networks is presented. The simple networks pr...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976606775093891

    authors: Falconbridge MS,Stamps RL,Badcock DR

    更新日期:2006-02-01 00:00:00

  • Generalization and multirate models of motor adaptation.

    abstract::When subjects adapt their reaching movements in the setting of a systematic force or visual perturbation, generalization of adaptation can be assessed psychophysically in two ways: by testing untrained locations in the work space at the end of adaptation (slow postadaptation generalization) or by determining the influ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00262

    authors: Tanaka H,Krakauer JW,Sejnowski TJ

    更新日期:2012-04-01 00:00:00

  • Bias/Variance Decompositions for Likelihood-Based Estimators.

    abstract::The bias/variance decomposition of mean-squared error is well understood and relatively straightforward. In this note, a similar simple decomposition is derived, valid for any kind of error measure that, when using the appropriate probability model, can be derived from a Kullback-Leibler divergence or log-likelihood. ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976698300017232

    authors: Heskes T

    更新日期:1998-07-28 00:00:00

  • Robustness of connectionist swimming controllers against random variation in neural connections.

    abstract::The ability to achieve high swimming speed and efficiency is very important to both the real lamprey and its robotic implementation. In previous studies, we used evolutionary algorithms to evolve biologically plausible connectionist swimming controllers for a simulated lamprey. This letter investigates the robustness ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2007.19.6.1568

    authors: Or J

    更新日期:2007-06-01 00:00:00

  • Spikernels: predicting arm movements by embedding population spike rate patterns in inner-product spaces.

    abstract::Inner-product operators, often referred to as kernels in statistical learning, define a mapping from some input space into a feature space. The focus of this letter is the construction of biologically motivated kernels for cortical activities. The kernels we derive, termed Spikernels, map spike count sequences into an...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/0899766053019944

    authors: Shpigelman L,Singer Y,Paz R,Vaadia E

    更新日期:2005-03-01 00:00:00

  • Parameter Identifiability in Statistical Machine Learning: A Review.

    abstract::This review examines the relevance of parameter identifiability for statistical models used in machine learning. In addition to defining main concepts, we address several issues of identifiability closely related to machine learning, showing the advantages and disadvantages of state-of-the-art research and demonstrati...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00947

    authors: Ran ZY,Hu BG

    更新日期:2017-05-01 00:00:00

  • A computational model for rhythmic and discrete movements in uni- and bimanual coordination.

    abstract::Current research on discrete and rhythmic movements differs in both experimental procedures and theory, despite the ubiquitous overlap between discrete and rhythmic components in everyday behaviors. Models of rhythmic movements usually use oscillatory systems mimicking central pattern generators (CPGs). In contrast, m...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2008.03-08-720

    authors: Ronsse R,Sternad D,Lefèvre P

    更新日期:2009-05-01 00:00:00

  • Multispike interactions in a stochastic model of spike-timing-dependent plasticity.

    abstract::Recently we presented a stochastic, ensemble-based model of spike-timing-dependent plasticity. In this model, single synapses do not exhibit plasticity depending on the exact timing of pre- and postsynaptic spikes, but spike-timing-dependent plasticity emerges only at the temporal or synaptic ensemble level. We showed...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.2007.19.5.1362

    authors: Appleby PA,Elliott T

    更新日期:2007-05-01 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

  • Downstream Effect of Ramping Neuronal Activity through Synapses with Short-Term Plasticity.

    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

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00818

    authors: Wei W,Wang XJ

    更新日期:2016-04-01 00:00:00

  • Extraction of Synaptic Input Properties in Vivo.

    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

    pub_type: 杂志文章

    doi:10.1162/NECO_a_00975

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

    更新日期:2017-07-01 00:00:00

  • Asynchronous Event-Based Motion Processing: From Visual Events to Probabilistic Sensory Representation.

    abstract::In this work, we propose a two-layered descriptive model for motion processing from retina to the cortex, with an event-based input from the asynchronous time-based image sensor (ATIS) camera. Spatial and spatiotemporal filtering of visual scenes by motion energy detectors has been implemented in two steps in a simple...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco_a_01191

    authors: Khoei MA,Ieng SH,Benosman R

    更新日期:2019-06-01 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