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The Journal of Neuroscience : the Official Journal of the Society for Neuroscience|June 1, 2002
Energy-efficient neuronal computation via quantal synaptic failuresWilliam B Levy, Robert A BaxterNeural Networks : the Official Journal of the International Neural Network Society|May 10, 2023
Growing dendrites enhance a neuron's computational power and memory capacityWilliam B Levy, Robert A BaxterNeural Networks : the Official Journal of the International Neural Network Society|November 2, 2019
Constructing multilayered neural networks with sparse, data-driven connectivity using biologically-inspired, complementary, homeostatic mechanismsRobert A Baxter, William B LevyNeural Networks : the Official Journal of the International Neural Network Society|March 24, 2004
Configural representations in transverse patterning with a hippocampal modelPaul Rodriguez, William B LevyPlos One|July 14, 2017
A consensus layer V pyramidal neuron can sustain interpulse-interval codingChandan Singh, William B LevyProceedings of the National Academy of Sciences of the United States of America|April 28, 2021
Communication consumes 35 times more energy than computation in the human cortex, but both costs are needed to predict synapse numberWilliam B Levy, Victoria G CalvertNeurocomputing|July 14, 2009
Theta-Modulated Input Reduces Intrinsic Gamma Oscillations in a Hippocampal ModelAshlie B Hocking, William B LevyCognitive Neurodynamics|March 14, 2014
Neuronal dynamics during the learning of trace conditioning in a CA3 model of hippocampal functionBlake T Thomas, William B LevyCognitive Neurodynamics|November 13, 2008
A hippocampal model predicts a fluctuating phase transition when learning certain trace conditioning paradigmsAndrew G Howe, William B LevyJournal of Computational Neuroscience|January 27, 2018
Linearization of excitatory synaptic integration at no extra costDanielle Morel, Chandan Singh, William B LevyPageof 2