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Volume 31, Issue 9
September 2019
Issue Cover
All Issues
ISSN 0899-7667
EISSN 1530-888X
In this Issue

Letters

Decoding Hidden Cognitive States From Behavior and Physiology Using a Bayesian Approach
Ali Yousefi, Ishita Basu, Angelique C. Paulk, Noam Peled, Emad N. Eskandar ...
Neural Computation (2019) 31 (9): 1751–1788.
View articletitled, Decoding Hidden Cognitive States From Behavior and Physiology Using a Bayesian Approach
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Sensitivity to Stimulus Irregularity Is Inherent in Neural Networks
Teun van Gils, Paul H. E. Tiesinga, Bernhard Englitz, Marijn B. Martens
Neural Computation (2019) 31 (9): 1789–1824.
View articletitled, Sensitivity to Stimulus Irregularity Is Inherent in Neural Networks
Supplementary data
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Learning with Precise Spike Times: A New Decoding Algorithm for Liquid State Machines
Dorian Florescu, Daniel Coca
Neural Computation (2019) 31 (9): 1825–1852.
View articletitled, Learning with Precise Spike Times: A New Decoding Algorithm for Liquid State Machines
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A New Nonlinear Sparse Component Analysis for a Biologically Plausible Model of Neurons
S. M. Heidarieh, M. Jahed, A. Ghazizadeh
Neural Computation (2019) 31 (9): 1853–1873.
View articletitled, A New Nonlinear Sparse Component Analysis for a Biologically Plausible Model of Neurons
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Hidden Markov Models Predict the Future Choice Better Than a PSTH-Based Method
Encarni Marcos, Fabrizio Londei, Aldo Genovesio
Neural Computation (2019) 31 (9): 1874–1890.
View articletitled, Hidden Markov Models Predict the Future Choice Better Than a PSTH-Based Method
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Supervised Determined Source Separation with Multichannel Variational Autoencoder
Hirokazu Kameoka, Li Li, Shota Inoue, Shoji Makino
Neural Computation (2019) 31 (9): 1891–1914.
View articletitled, Supervised Determined Source Separation with Multichannel Variational Autoencoder
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