| The physics of optimal decision making: a formal analysis of models of performance in two-alternative forced-choice tasks. R Bogacz, E Brown, J Moehlis, P Holmes, JD Cohen Psychological review 113 (4), 700, 2006 | 1839 | 2006 |
| Correlation between neural spike trains increases with firing rate J De La Rocha, B Doiron, E Shea-Brown, K Josić, A Reyes Nature 448 (7155), 802-806, 2007 | 689 | 2007 |
| On the phase reduction and response dynamics of neural oscillator populations E Brown, J Moehlis, P Holmes Neural computation 16 (4), 673-715, 2004 | 554 | 2004 |
| The what and where of adding channel noise to the Hodgkin-Huxley equations JH Goldwyn, E Shea-Brown PLoS computational biology 7 (11), e1002247, 2011 | 178 | 2011 |
| Impact of network structure and cellular response on spike time correlations J Trousdale, Y Hu, E Shea-Brown, K Josić PLoS computational biology 8 (3), e1002408, 2012 | 164 | 2012 |
| A large-scale standardized physiological survey reveals functional organization of the mouse visual cortex SEJ de Vries, JA Lecoq, MA Buice, PA Groblewski, GK Ocker, M Oliver, ... Nature neuroscience 23 (1), 138-151, 2020 | 153 | 2020 |
| Correlation and synchrony transfer in integrate-and-fire neurons: basic properties and consequences for coding E Shea-Brown, K Josić, J De La Rocha, B Doiron Physical review letters 100 (10), 108102, 2008 | 153 | 2008 |
| Mechanisms underlying dependencies of performance on stimulus history in a two-alternative forced-choice task RY Cho, LE Nystrom, ET Brown, AD Jones, TS Braver, PJ Holmes, ... Cognitive, Affective, & Behavioral Neuroscience 2 (4), 283-299, 2002 | 148 | 2002 |
| Toward closed-loop optimization of deep brain stimulation for Parkinson's disease: concepts and lessons from a computational model X Feng, B Greenwald, H Rabitz, E Shea-Brown, R Kosut Journal of neural engineering 4 (2), L14, 2007 | 146 | 2007 |
| Stochastic differential equation models for ion channel noise in Hodgkin-Huxley neurons JH Goldwyn, NS Imennov, M Famulare, E Shea-Brown Physical Review E 83 (4), 041908, 2011 | 144 | 2011 |
| Optimal deep brain stimulation of the subthalamic nucleus—a computational study XJ Feng, E Shea-Brown, B Greenwald, R Kosut, H Rabitz Journal of computational neuroscience 23 (3), 265-282, 2007 | 137 | 2007 |
| Optimal inputs for phase models of spiking neurons J Moehlis, E Shea-Brown, H Rabitz | 131 | 2006 |
| Simple neural networks that optimize decisions E Brown, J Gao, P Holmes, R Bogacz, M Gilzenrat, JD Cohen International Journal of Bifurcation and Chaos 15 (03), 803-826, 2005 | 124 | 2005 |
| Globally coupled oscillator networks E Brown, P Holmes, J Moehlis Perspectives and Problems in Nolinear Science, 183-215, 2003 | 120 | 2003 |
| Direction-selective circuits shape noise to ensure a precise population code J Zylberberg, J Cafaro, MH Turner, E Shea-Brown, F Rieke Neuron 89 (2), 369-383, 2016 | 116 | 2016 |
| Stimulus-dependent correlations and population codes K Josić, E Shea-Brown, B Doiron, J de la Rocha Neural computation 21 (10), 2774-2804, 2009 | 99 | 2009 |
| Motif statistics and spike correlations in neuronal networks Y Hu, J Trousdale, K Josić, E Shea-Brown Journal of Statistical Mechanics: Theory and Experiment 2013 (03), P03012, 2013 | 74 | 2013 |
| The influence of spike rate and stimulus duration on noradrenergic neurons E Brown, J Moehlis, P Holmes, E Clayton, J Rajkowski, G Aston-Jones Journal of computational neuroscience 17 (1), 13-29, 2004 | 74 | 2004 |
| Some mathematical and algorithmic challenges in the control of quantum dynamics phenomena E Brown, H Rabitz Journal of Mathematical Chemistry 31 (1), 17-63, 2002 | 70 | 2002 |
| The sign rule and beyond: boundary effects, flexibility, and noise correlations in neural population codes Y Hu, J Zylberberg, E Shea-Brown PLoS computational biology 10 (2), e1003469, 2014 | 69 | 2014 |
