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Volume 18, Issue 7

July 2006

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ISSN 0899-7667

EISSN 1530-888X

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Letters

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Optimal Neuronal Tuning for Finite Stimulus Spaces

W. Michael Brown, Alex Bäcker

Neural Computation (2006) 18 (7): 1511–1526.

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Letters

A Fast Learning Algorithm for Deep Belief Nets

Geoffrey E. Hinton, Simon Osindero, Yee-Whye Teh

Neural Computation (2006) 18 (7): 1527–1554.

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Optimal Tuning Widths in Population Coding of Periodic Variables

Marcelo A. Montemurro, Stefano Panzeri

Neural Computation (2006) 18 (7): 1555–1576.

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How Inhibitory Oscillations Can Train Neural Networks and Punish Competitors

Kenneth A. Norman, Ehren Newman, Greg Detre, Sean Polyn

Neural Computation (2006) 18 (7): 1577–1610.

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Temporal Decoding by Phase-Locked Loops: Unique Features of Circuit-Level Implementations and Their Significance for Vibrissal Information Processing

Miriam Zacksenhouse, Ehud Ahissar

Neural Computation (2006) 18 (7): 1611–1636.

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Representation and Timing in Theories of the Dopamine System

Nathaniel D. Daw, Aaron C. Courville, David S. Touretzky

Neural Computation (2006) 18 (7): 1637–1677.

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Experiments with AdaBoost.RT, an Improved Boosting Scheme for Regression

D. L. Shrestha, D. P. Solomatine

Neural Computation (2006) 18 (7): 1678–1710.

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A Connectionist Computational Model for Epistemic and Temporal Reasoning

Artur S. d'Avila Garcez, Luís C. Lamb

Neural Computation (2006) 18 (7): 1711–1738.

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Optimal Neuronal Tuning for Finite Stimulus Spaces

Letters

A Fast Learning Algorithm for Deep Belief Nets

Optimal Tuning Widths in Population Coding of Periodic Variables

How Inhibitory Oscillations Can Train Neural Networks and Punish Competitors

Temporal Decoding by Phase-Locked Loops: Unique Features of Circuit-Level Implementations and Their Significance for Vibrissal Information Processing

Representation and Timing in Theories of the Dopamine System

Experiments with AdaBoost.RT, an Improved Boosting Scheme for Regression

A Connectionist Computational Model for Epistemic and Temporal Reasoning

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