| Critical analysis of dimension reduction by a moment closure method in a population density approach to neural network modeling C Ly, D Tranchina Neural computation 19 (8), 2032-2092, 2007 | 98 | 2007 |
| Population density methods for stochastic neurons with realistic synaptic kinetics: Firing rate dynamics and fast computational methods F Apfaltrer, C Ly, D Tranchina Network: Computation in Neural Systems 17 (4), 373-418, 2006 | 63* | 2006 |
| Synchronization dynamics of two coupled neural oscillators receiving shared and unshared noisy stimuli C Ly, GB Ermentrout Journal of computational neuroscience 26, 425-443, 2009 | 57 | 2009 |
| Cellular and circuit mechanisms maintain low spike co-variability and enhance population coding in somatosensory cortex C Ly, JW Middleton, B Doiron Frontiers in computational neuroscience 6, 7, 2012 | 39 | 2012 |
| Spike train statistics and dynamics with synaptic input from any renewal process: a population density approach C Ly, D Tranchina Neural Computation 21 (2), 360-396, 2009 | 38 | 2009 |
| Divisive gain modulation with dynamic stimuli in integrate-and-fire neurons C Ly, B Doiron PLoS computational biology 5 (4), e1000365, 2009 | 36 | 2009 |
| Phase-resetting curve determines how BK currents affect neuronal firing C Ly, T Melman, AL Barth, GB Ermentrout Journal of computational neuroscience 30, 211-223, 2011 | 25 | 2011 |
| When do correlations increase with firing rates in recurrent networks? AK Barreiro, C Ly PLoS computational biology 13 (4), e1005506, 2017 | 19 | 2017 |
| Analytic approximations of statistical quantities and response of noisy oscillators C Ly, GB Ermentrout Physica D: Nonlinear Phenomena 240 (8), 719-731, 2011 | 19 | 2011 |
| Analysis of recurrent networks of pulse-coupled noisy neural oscillators C Ly, GB Ermentrout SIAM Journal on Applied Dynamical Systems 9 (1), 113-137, 2010 | 18 | 2010 |
| Coupling regularizes individual units in noisy populations C Ly, GB Ermentrout Physical Review E 81 (1), 011911, 2010 | 18 | 2010 |
| Firing rate dynamics in recurrent spiking neural networks with intrinsic and network heterogeneity C Ly Journal of computational neuroscience 39, 311-327, 2015 | 17 | 2015 |
| One-dimensional population density approaches to recurrently coupled networks of neurons with noise W Nicola, C Ly, SA Campbell SIAM Journal on Applied Mathematics 75 (5), 2333-2360, 2015 | 16 | 2015 |
| Investigating the correlation–firing rate relationship in heterogeneous recurrent networks AK Barreiro, C Ly The Journal of Mathematical Neuroscience 8, 1-25, 2018 | 14 | 2018 |
| A theoretical framework for analyzing coupled neuronal networks: Application to the olfactory system AK Barreiro, SH Gautam, WL Shew, C Ly PLoS computational biology 13 (10), e1005780, 2017 | 10 | 2017 |
| Noise-enhanced coding in phasic neuron spike trains C Ly, B Doiron PloS one 12 (5), e0176963, 2017 | 10 | 2017 |
| A principled dimension-reduction method for the population density approach to modeling networks of neurons with synaptic dynamics C Ly Neural Computation 25 (10), 2682-2708, 2013 | 8 | 2013 |
| Automaticity in ventricular myocyte cell pairs with ephaptic and gap junction coupling C Ly, SH Weinberg Chaos: An Interdisciplinary Journal of Nonlinear Science 32 (3), 2022 | 7 | 2022 |
| Differences in olfactory bulb mitral cell spiking with ortho-and retronasal stimulation revealed by data-driven models MF Craft, AK Barreiro, SH Gautam, WL Shew, C Ly PLOS Computational Biology 17 (9), e1009169, 2021 | 7 | 2021 |
| Analysis of heterogeneous cardiac pacemaker tissue models and traveling wave dynamics C Ly, SH Weinberg Journal of theoretical biology 459, 18-35, 2018 | 7 | 2018 |
Andrea K. BarreiroAssociate Professor of Mathematics, Southern Methodist UniversityBestätigte E-Mail-Adresse bei smu.edu
