Richard Naud

发表

Voltage Recordings and Genetic Algorithms Constraining Compartmental Models Using Multiple

Wulfram Gerstner, Noam Peled, Alon Korngreen, 2015 .

Noisy input models: barrage of spike arrivals

Wulfram Gerstner, Richard Naud, Werner M. Kistler, 2014 .

The quantitative single-neuron modeling competition

Wulfram Gerstner, Thomas K. Berger, Richard Naud, 2008, Biological Cybernetics.

Quantitative single-neuron modeling: competition 2008

Wulfram Gerstner, Thomas K. Berger, Richard Naud, 2008 .

A deep learning framework for neuroscience

Surya Ganguli, Yoshua Bengio, Claudia Clopath, 2019, Nature Neuroscience.

Introduction: neurons and mathematics

Wulfram Gerstner, Richard Naud, Liam Paninski, 2014 .

Nonlinear integrate-and-fire models

Wulfram Gerstner, Richard Naud, Liam Paninski, 2014 .

GENERALIZED INTEGRATE-AND-FIRE NEURONS

Wulfram Gerstner, Richard Naud, Werner M. Kistler, 2014 .

Firing patterns in the adaptive exponential integrate-and-fire model

Wulfram Gerstner, Claudia Clopath, Richard Naud, 2008, Biological Cybernetics.

Sparse Bursts Optimize Information Transmission

Richard Naud, Henning Sprekeler, 2017 .

From Stochastic Nonlinear Integrate-and-Fire to Generalized Linear Models

Wulfram Gerstner, Skander Mensi, Richard Naud, 2011, NIPS.

Counting on dis-inhibition: a circuit motif for interval counting and selectivity in the anuran auditory system.

André Longtin, Richard Naud, Dave Houtman, 2015, Journal of neurophysiology.

Neuronal Dynamics: From Single Neurons To Networks And Models Of Cognition

Wulfram Gerstner, Richard Naud, Liam Paninski, 2014 .

Wulfram Gerstner, Felipe Gerhard, Skander Mensi, 2011, Neural Computation.

Classes of dendritic information processing

Richard Naud, Alexandre Payeur, Jean-Claude Béïque, 2019, Current Opinion in Neurobiology.

Encoding and decoding with stochastic neuron models

Wulfram Gerstner, Richard Naud, Liam Paninski, 2014 .

Parsing Out the Variability of Transmission at Central Synapses Using Optical Quantal Analysis

André Longtin, Richard Naud, Cary Soares, 2019, bioRxiv.

A synthetic likelihood solution to the silent synapse estimation problem

Richard Naud, Cary Soares, Jean-Claude Béïque, 2019, bioRxiv.

Neural coding strategies for extracting motion estimates from electrosensory contrast

André Longtin, Richard Naud, Leonard Maler, 2014, BMC Neuroscience.

The Dynamics of Adapting Neurons

Richard Naud, 2011 .

Neuronal Dynamics: Fast transients and rate models

Wulfram Gerstner, Richard Naud, Liam Paninski, 2014 .

Network dynamics of spiking neurons with adaptation

Richard Naud, Tilo Schwalger, Moritz Deger, 2014 .

Spike-timing prediction in cortical neurons with active dendrites

Wulfram Gerstner, Richard Naud, Brice Bathellier, 2014, Front. Comput. Neurosci..

Capsule Deep Generative Model That Forms Parse Trees

Richard Naud, Yifeng Li, Pengcheng Xi, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

A Synthetic Likelihood Solution to the Silent Synapse Estimation Problem.

Richard Naud, Kevin F H Lee, Cary Soares, 2020, Cell reports.

Coding and Decoding with Adapting Neurons: A Population Approach to the Peri-Stimulus Time Histogram

Wulfram Gerstner, Richard Naud, W. Gerstner, 2012, PLoS Comput. Biol..

Neuronal Dynamics: Preface

Wulfram Gerstner, Richard Naud, Liam Paninski, 2014 .

Automatic characterization of three cortical neuron types reveals two distinct adaptation mechanisms

Wulfram Gerstner, Skander Mensi, Richard Naud, 2011, BMC Neuroscience.

Fluctuations and information filtering in coupled populations of spiking neurons with adaptation.

Wulfram Gerstner, Richard Naud, Tilo Schwalger, 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

Accurate Silent Synapse Estimation from Simulator-Corrected Electrophysiological Data Using the SilentMLE Python Package

Richard Naud, Jean-Claude Béïque, Michael Lynn, 2020, STAR protocols.

Neuronal Dynamics: Outlook: dynamics in plastic networks

Wulfram Gerstner, Richard Naud, Liam Paninski, 2014 .

Synaptic dynamics as convolutional units

Richard Naud, Katalin Tóth, Julian Rossbroich, 2020 .

A benchmark test for a quantitative assessment of simple neuron models

Wulfram Gerstner, Richard Naud, Ryota Kobayashi, 2008, Journal of Neuroscience Methods.

Sparse Bursts Optimize Information Transmission in a Multiplexed Neural Code

Richard Naud, Henning Sprekeler, Henning Sprekeler, 2017, bioRxiv.

Sparse bursts optimize information transmission in a multiplexed neural code

Richard Naud, Henning Sprekeler, Henning Sprekeler, 2018, Proceedings of the National Academy of Sciences.

Automated High-Throughput Characterization of Single Neurons by Means of Simplified Spiking Models

Wulfram Gerstner, Christof Koch, Skander Mensi, 2015, PLoS Comput. Biol..

Neuronal Model Reduction

Richard Naud, Richard Naud, 2014, Encyclopedia of Computational Neuroscience.

Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits

Richard Naud, Alexandre Payeur, Friedemann Zenke, 2020, Nature Neuroscience.

Neuronal Dynamics: Variability of spike trains and neural codes

Wulfram Gerstner, Richard Naud, Liam Paninski, 2014 .

Wulfram Gerstner, Felipe Gerhard, Skander Mensi, 2010 .

Dendrites and synapses

Wulfram Gerstner, Richard Naud, Liam Paninski, 2014 .

Temporal decorrelation by power-law adaptation in pyramidal neurons

Skander Mensi, Richard Naud, Christian Pozzorini, 2013 .

The Performance (and Limits) of Simple Neuron Models: Generalizations of the Leaky Integrate-and-Fire Model

Wulfram Gerstner, Richard Naud, W. Gerstner, 2012 .

Spike timing prediction with active dendrites

Wulfram Gerstner, Richard Naud, Brice Bathellier, 2013, 1311.3586.