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Volume 22, Issue 3

March 2010

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ISSN 0899-7667

EISSN 1530-888X

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Letters

Letters

Feature Selection in Simple Neurons: How Coding Depends on Spiking Dynamics

Michael Famulare, Adrienne Fairhall

Neural Computation (2010) 22 (3): 581–598.

Abstract

View articletitled, Feature Selection in Simple Neurons: How Coding Depends on Spiking Dynamics

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Phase Locking Below Rate Threshold in Noisy Model Neurons

Jan A. Freund, Alexander Nikitin, Nigel G. Stocks

Neural Computation (2010) 22 (3): 599–620.

Abstract

View articletitled, Phase Locking Below Rate Threshold in Noisy Model Neurons

Supplementary data

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Population Models of Temporal Differentiation

Bryan P. Tripp, Chris Eliasmith

Neural Computation (2010) 22 (3): 621–659.

Abstract

View articletitled, Population Models of Temporal Differentiation

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Precise Capacity Analysis in Binary Networks with Multiple Coding Level Inputs

Yali Amit, Yibi Huang

Neural Computation (2010) 22 (3): 660–688.

Abstract

View articletitled, Precise Capacity Analysis in Binary Networks with Multiple Coding Level Inputs

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Growing Self-Organizing Surface Map: Learning a Surface Topology from a Point Cloud

Vilson Luiz Dalle Mole, Aluizio Fausto Ribeiro Araújo

Neural Computation (2010) 22 (3): 689–729.

Abstract

View articletitled, Growing Self-Organizing Surface Map: Learning a Surface Topology from a Point Cloud

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Autonomous Development of Vergence Control Driven by Disparity Energy Neuron Populations

Yiwen Wang, Bertram E. Shi

Neural Computation (2010) 22 (3): 730–751.

Abstract

View articletitled, Autonomous Development of Vergence Control Driven by Disparity Energy Neuron Populations

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A Moving Bump in a Continuous Manifold: A Comprehensive Study of the Tracking Dynamics of Continuous Attractor Neural Networks

C. C. Alan Fung, K. Y. Michael Wong, Si Wu

Neural Computation (2010) 22 (3): 752–792.

Abstract

View articletitled, A Moving Bump in a Continuous Manifold: A Comprehensive Study of the Tracking Dynamics of Continuous Attractor Neural Networks

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Regularization Techniques and Suboptimal Solutions to Optimization Problems in Learning from Data

Giorgio Gnecco, Marcello Sanguineti

Neural Computation (2010) 22 (3): 793–829.

Abstract

View articletitled, Regularization Techniques and Suboptimal Solutions to Optimization Problems in Learning from Data

Letters

Feature Selection in Simple Neurons: How Coding Depends on Spiking Dynamics

Phase Locking Below Rate Threshold in Noisy Model Neurons

Population Models of Temporal Differentiation

Precise Capacity Analysis in Binary Networks with Multiple Coding Level Inputs

Growing Self-Organizing Surface Map: Learning a Surface Topology from a Point Cloud

Autonomous Development of Vergence Control Driven by Disparity Energy Neuron Populations

A Moving Bump in a Continuous Manifold: A Comprehensive Study of the Tracking Dynamics of Continuous Attractor Neural Networks

Regularization Techniques and Suboptimal Solutions to Optimization Problems in Learning from Data

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