| Year |
Citation |
Score |
| 2023 |
Friedenberger Z, Naud R. Dendritic excitability controls overdispersion. Nature Computational Science. 4: 19-28. PMID 38177495 DOI: 10.1038/s43588-023-00580-6 |
0.437 |
|
| 2023 |
Naud R, Longtin A. Connecting levels of analysis in the computational era. The Journal of Physiology. PMID 38071740 DOI: 10.1113/JP286013 |
0.45 |
|
| 2023 |
Friedenberger Z, Harkin E, Tóth K, Naud R. Silences, spikes and bursts: Three-part knot of the neural code. The Journal of Physiology. 601: 5165-5193. PMID 37889516 DOI: 10.1113/JP281510 |
0.808 |
|
| 2023 |
Harkin EF, Lynn MB, Payeur A, Boucher JF, Caya-Bissonnette L, Cyr D, Stewart C, Longtin A, Naud R, Beique JC. Temporal derivative computation in the dorsal raphe network revealed by an experimentally-driven augmented integrate-and-fire modeling framework. Elife. 12. PMID 36655738 DOI: 10.7554/eLife.72951 |
0.778 |
|
| 2022 |
Fischer L, Mojica Soto-Albors R, Tang VD, Bicknell B, Grienberger C, Francioni V, Naud R, Palmer LM, Takahashi N. Dendritic Mechanisms for Neural Computations and Behavior. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 42: 8460-8467. PMID 36351832 DOI: 10.1523/JNEUROSCI.1132-22.2022 |
0.388 |
|
| 2022 |
Harkin EF, Béïque JC, Naud R. A User's Guide to Generalized Integrate-and-Fire Models. Advances in Experimental Medicine and Biology. 1359: 69-86. PMID 35471535 DOI: 10.1007/978-3-030-89439-9_3 |
0.816 |
|
| 2022 |
Lee C, Harkin EF, Yin X, Naud R, Chen S. Cell-type specific responses to associative learning in the primary motor cortex. Elife. 11. PMID 35113017 DOI: 10.7554/eLife.72549 |
0.767 |
|
| 2021 |
Vercruysse F, Naud R, Sprekeler H. Self-organization of a doubly asynchronous irregular network state for spikes and bursts. Plos Computational Biology. 17: e1009478. PMID 34748532 DOI: 10.1371/journal.pcbi.1009478 |
0.788 |
|
| 2021 |
Payeur A, Guerguiev J, Zenke F, Richards BA, Naud R. Author Correction: Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits. Nature Neuroscience. 24: 1780. PMID 34728832 DOI: 10.1038/s41593-021-00970-x |
0.756 |
|
| 2021 |
Harkin EF, Shen PR, Goel A, Richards BA, Naud R. Parallel and recurrent cascade models as a unifying force for understanding sub-cellular computation. Neuroscience. PMID 34358629 DOI: 10.1016/j.neuroscience.2021.07.026 |
0.815 |
|
| 2021 |
Williams E, Payeur A, Gidon A, Naud R. Neural burst codes disguised as rate codes. Scientific Reports. 11: 15910. PMID 34354118 DOI: 10.1038/s41598-021-95037-z |
0.732 |
|
| 2021 |
Payeur A, Guerguiev J, Zenke F, Richards BA, Naud R. Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits. Nature Neuroscience. PMID 33986551 DOI: 10.1038/s41593-021-00857-x |
0.778 |
|
| 2021 |
Zenke F, Bohté SM, Clopath C, Comşa IM, Göltz J, Maass W, Masquelier T, Naud R, Neftci EO, Petrovici MA, Scherr F, Goodman DFM. Visualizing a joint future of neuroscience and neuromorphic engineering. Neuron. 109: 571-575. PMID 33600754 DOI: 10.1016/j.neuron.2021.01.009 |
0.756 |
|
| 2020 |
Lynn MB, Lee KFH, Soares C, Naud R, Béïque JC. A Synthetic Likelihood Solution to the Silent Synapse Estimation Problem. Cell Reports. 32: 107916. PMID 32697998 DOI: 10.1016/J.Celrep.2020.107916 |
0.356 |
|
| 2020 |
Naud R, Longtin A. Correction to: Linking demyelination to compound action potential dispersion with a spike-diffuse-spike approach. Journal of Mathematical Neuroscience. 10: 6. PMID 32314104 DOI: 10.1186/s13408-020-00083-y |
0.495 |
|
| 2019 |
Richards BA, Lillicrap TP, Beaudoin P, Bengio Y, Bogacz R, Christensen A, Clopath C, Costa RP, de Berker A, Ganguli S, Gillon CJ, Hafner D, Kepecs A, Kriegeskorte N, Latham P, ... ... Naud R, et al. A deep learning framework for neuroscience. Nature Neuroscience. 22: 1761-1770. PMID 31659335 DOI: 10.1038/S41593-019-0520-2 |
0.763 |
|
| 2019 |
Soares C, Trotter D, Longtin A, Béïque JC, Naud R. Parsing Out the Variability of Transmission at Central Synapses Using Optical Quantal Analysis. Frontiers in Synaptic Neuroscience. 11: 22. PMID 31474847 DOI: 10.3389/Fnsyn.2019.00022 |
0.551 |
|
| 2019 |
Naud R, Longtin A. Correction to: Linking demyelination to compound action potential dispersion with a spike-diffuse-spike approach. Journal of Mathematical Neuroscience. 9: 8. PMID 31440910 DOI: 10.1186/S13408-019-0076-1 |
0.544 |
|
| 2019 |
Payeur A, Béïque JC, Naud R. Classes of dendritic information processing. Current Opinion in Neurobiology. 58: 78-85. PMID 31419712 DOI: 10.1016/J.Conb.2019.07.006 |
0.819 |
|
| 2019 |
Naud R, Longtin A. Linking demyelination to compound action potential dispersion with a spike-diffuse-spike approach. Journal of Mathematical Neuroscience. 9: 3. PMID 31147800 DOI: 10.1186/S13408-019-0071-6 |
0.565 |
|
| 2018 |
Naud R, Sprekeler H. Sparse bursts optimize information transmission in a multiplexed neural code. Proceedings of the National Academy of Sciences of the United States of America. PMID 29934400 DOI: 10.1073/pnas.1720995115 |
0.827 |
|
| 2017 |
Naud R, Payeur A, Longtin A. Noise Gated by Dendrosomatic Interactions Increases Information Transmission Physical Review X. 7. DOI: 10.1103/Physrevx.7.031045 |
0.499 |
|
| 2015 |
Naud R, Houtman DB, Rose GJ, Longtin A. Counting on dis-inhibition: a circuit motif for interval counting and selectivity in the anuran auditory system. Journal of Neurophysiology. jn.00138.2015. PMID 26334004 DOI: 10.1152/Jn.00138.2015 |
0.655 |
|
| 2015 |
Pozzorini C, Mensi S, Hagens O, Naud R, Koch C, Gerstner W. Automated High-Throughput Characterization of Single Neurons by Means of Simplified Spiking Models. Plos Computational Biology. 11: e1004275. PMID 26083597 DOI: 10.1371/journal.pcbi.1004275 |
0.781 |
|
| 2014 |
Deger M, Schwalger T, Naud R, Gerstner W. Fluctuations and information filtering in coupled populations of spiking neurons with adaptation. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 90: 062704. PMID 25615126 DOI: 10.1103/Physreve.90.062704 |
0.811 |
|
| 2014 |
Naud R, Bathellier B, Gerstner W. Spike-timing prediction in cortical neurons with active dendrites. Frontiers in Computational Neuroscience. 8: 90. PMID 25165443 DOI: 10.3389/fncom.2014.00090 |
0.824 |
|
| 2014 |
Clarke SE, Naud R, Longtin A, Maler L. Neural coding strategies for extracting motion estimates from electrosensory contrast Bmc Neuroscience. 15. DOI: 10.1186/1471-2202-15-S1-P185 |
0.597 |
|
| 2014 |
Naud R, Houtman D, Rose GJ, Longtin A. Modeling sound pulse counting in inferior colliculus Bmc Neuroscience. 15. DOI: 10.1186/1471-2202-15-S1-P113 |
0.611 |
|
| 2014 |
Gerstner W, Kistler WM, Naud R, Paninski L. Neuronal dynamics: From single neurons to networks and models of cognition Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition. 1-577. DOI: 10.1017/CBO9781107447615 |
0.727 |
|
| 2013 |
Clarke SE, Naud R, Longtin A, Maler L. Speed-invariant encoding of looming object distance requires power law spike rate adaptation. Proceedings of the National Academy of Sciences of the United States of America. 110: 13624-9. PMID 23898185 DOI: 10.1073/Pnas.1306428110 |
0.578 |
|
| 2013 |
Pozzorini C, Naud R, Mensi S, Gerstner W. Temporal whitening by power-law adaptation in neocortical neurons. Nature Neuroscience. 16: 942-8. PMID 23749146 DOI: 10.1038/nn.3431 |
0.746 |
|
| 2012 |
Naud R, Gerstner W. Coding and decoding with adapting neurons: a population approach to the peri-stimulus time histogram. Plos Computational Biology. 8: e1002711. PMID 23055914 DOI: 10.1371/journal.pcbi.1002711 |
0.778 |
|
| 2012 |
Mensi S, Naud R, Pozzorini C, Avermann M, Petersen CC, Gerstner W. Parameter extraction and classification of three cortical neuron types reveals two distinct adaptation mechanisms. Journal of Neurophysiology. 107: 1756-75. PMID 22157113 DOI: 10.1152/Jn.00408.2011 |
0.774 |
|
| 2012 |
Naud R, Gerstner W. The performance (and limits) of simple neuron models: Generalizations of the leaky integrate-and-fire model Computational Systems Neurobiology. 163-192. DOI: 10.1007/978-94-007-3858-4_6 |
0.734 |
|
| 2011 |
Naud R, Gerhard F, Mensi S, Gerstner W. Improved similarity measures for small sets of spike trains. Neural Computation. 23: 3016-69. PMID 21919785 DOI: 10.3389/Conf.Fncom.2010.51.00102 |
0.793 |
|
| 2011 |
Mensi S, Naud R, Pozzorini C, Avermann M, Petersen CC, Gerstner W. Automatic characterization of three cortical neuron types reveals two distinct adaptation mechanisms Bmc Neuroscience. 12. DOI: 10.1186/1471-2202-12-S1-P119 |
0.768 |
|
| 2009 |
Gerstner W, Naud R. Neuroscience. How good are neuron models? Science (New York, N.Y.). 326: 379-80. PMID 19833951 DOI: 10.1126/science.1181936 |
0.761 |
|
| 2009 |
Naud R, Berger T, Bathellier B, Carandini M, Gerstner W. Quantitative Single-Neuron Modeling: Competition 2009 Frontiers in Neuroinformatics. 3. DOI: 10.3389/conf.neuro.11.2009.08.106 |
0.827 |
|
| 2009 |
Naud R, Bathellier B, Gerstner W. Spike-timing prediction in a neuron model with active dendrites Bmc Neuroscience. 10. DOI: 10.1186/1471-2202-10-S1-P29 |
0.825 |
|
| 2008 |
Jolivet R, Schürmann F, Berger TK, Naud R, Gerstner W, Roth A. The quantitative single-neuron modeling competition. Biological Cybernetics. 99: 417-26. PMID 19011928 DOI: 10.1007/S00422-008-0261-X |
0.835 |
|
| 2008 |
Naud R, Marcille N, Clopath C, Gerstner W. Firing patterns in the adaptive exponential integrate-and-fire model. Biological Cybernetics. 99: 335-47. PMID 19011922 DOI: 10.1007/S00422-008-0264-7 |
0.802 |
|
| 2008 |
Jolivet R, Kobayashi R, Rauch A, Naud R, Shinomoto S, Gerstner W. A benchmark test for a quantitative assessment of simple neuron models. Journal of Neuroscience Methods. 169: 417-24. PMID 18160135 DOI: 10.1016/J.Jneumeth.2007.11.006 |
0.826 |
|
| 1970 |
Naud R, Gerstner W, Mensi S, Becker T. Complexity and performance in simple neuron models Frontiers in Neuroinformatics. DOI: 10.3389/Conf.Neuro.11.2009.08.087 |
0.745 |
|
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