Richard Naud

Affiliations: 
University of Ottawa, Ottawa, ON, Canada 
Area:
Simplified Models
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"Richard Naud"
Mean distance: 14.3 (cluster 17)
 
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Publications

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Harkin EF, Shen PR, Goel A, et al. (2021) Parallel and recurrent cascade models as a unifying force for understanding sub-cellular computation. Neuroscience
Williams E, Payeur A, Gidon A, et al. (2021) Neural burst codes disguised as rate codes. Scientific Reports. 11: 15910
Payeur A, Guerguiev J, Zenke F, et al. (2021) Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits. Nature Neuroscience
Rossbroich J, Trotter D, Beninger J, et al. (2021) Linear-nonlinear cascades capture synaptic dynamics. Plos Computational Biology. 17: e1008013
Zenke F, Bohté SM, Clopath C, et al. (2021) Visualizing a joint future of neuroscience and neuromorphic engineering. Neuron. 109: 571-575
Lynn M, Naud R, Béïque JC. (2020) Accurate Silent Synapse Estimation from Simulator-Corrected Electrophysiological Data Using the SilentMLE Python Package. Star Protocols. 1: 100176
Doron G, Shin JN, Takahashi N, et al. (2020) Perirhinal input to neocortical layer 1 controls learning. Science (New York, N.Y.). 370
Lynn MB, Lee KFH, Soares C, et al. (2020) A Synthetic Likelihood Solution to the Silent Synapse Estimation Problem. Cell Reports. 32: 107916
Naud R, Longtin A. (2020) Correction to: Linking demyelination to compound action potential dispersion with a spike-diffuse-spike approach. Journal of Mathematical Neuroscience. 10: 6
Richards BA, Lillicrap TP, Beaudoin P, et al. (2019) A deep learning framework for neuroscience. Nature Neuroscience. 22: 1761-1770
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