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ORCIDEric Shea-Brown
Person information
- affiliation: University of Washington, Seattle, WA, USA
- affiliation (former): New York University, NY, USA
- affiliation (former): Princeton University, NJ, USA
Other persons with the same name
- Eric Brown — disambiguation page
- Eric Brown 0001 — The University of Chicago, IL, USA
- Eric Brown 0003 — Syracuse Research Corporation, North Syracuse, NY, USA
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2010 – 2019
- 2019
[j32]Stefano Recanatesi, Gabriel Koch Ocker
, Michael A. Buice, Eric Shea-Brown:
Dimensionality in recurrent spiking networks: Global trends in activity and local origins in connectivity. PLoS Comput. Biol. 15(7) (2019)- [c2]Jianghong Shi, Eric Shea-Brown, Michael A. Buice:
Comparison Against Task Driven Artificial Neural Networks Reveals Functional Properties in Mouse Visual Cortex. NeurIPS 2019: 5765-5775 - [i2]Stefano Recanatesi, Matthew Farrell, Madhu Advani, Timothy Moore, Guillaume Lajoie, Eric Shea-Brown:
Dimensionality compression and expansion in Deep Neural Networks. CoRR abs/1906.00443 (2019) - 2018
- [j31]N. Alex Cayco-Gajic, Joel Zylberberg, Eric Shea-Brown:
A Moment-Based Maximum Entropy Model for Fitting Higher-Order Interactions in Neural Data. Entropy 20(7): 489 (2018) - [j30]Hannah Choi, Anitha Pasupathy, Eric Shea-Brown:
Predictive Coding in Area V4: Dynamic Shape Discrimination under Partial Occlusion. Neural Comput. 30(5) (2018) - [j29]Braden A. W. Brinkman, Fred Rieke, Eric Shea-Brown, Michael A. Buice:
Predicting how and when hidden neurons skew measured synaptic interactions. PLoS Comput. Biol. 14(10) (2018) - 2017
- [j28]Joel Zylberberg, Alexandre Pouget, Peter E. Latham, Eric Shea-Brown:
Robust information propagation through noisy neural circuits. PLoS Comput. Biol. 13(4) (2017) - [j27]Gabriel Koch Ocker, Kresimir Josic, Eric Shea-Brown, Michael A. Buice:
Linking structure and activity in nonlinear spiking networks. PLoS Comput. Biol. 13(6) (2017) - 2016
- [j26]Braden A. W. Brinkman, Alison I. Weber, Fred Rieke, Eric Shea-Brown:
How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits? PLoS Comput. Biol. 12(10) (2016) - [j25]Guillaume Lajoie, Kevin K. Lin, Jean-Philippe Thivierge, Eric Shea-Brown:
Encoding in Balanced Networks: Revisiting Spike Patterns and Chaos in Stimulus-Driven Systems. PLoS Comput. Biol. 12(12) (2016) - [c1]Kameron D. Harris, Stefan Mihalas, Eric Shea-Brown:
High resolution neural connectivity from incomplete tracing data using nonnegative spline regression. NIPS 2016: 3099-3107 - 2015
- [j24]Natasha A. Cayco-Gajic, Joel Zylberberg, Eric Shea-Brown:
Triplet correlations among similarly tuned cells impact population coding. Frontiers Comput. Neurosci. 9: 57 (2015) - 2014
- [j23]Andrea K. Barreiro, Julijana Gjorgjieva, Fred Rieke, Eric Shea-Brown:
When do microcircuits produce beyond-pairwise correlations? Frontiers Comput. Neurosci. 8: 10 (2014) - [j22]Guillaume Lajoie, Jean-Philippe Thivierge, Eric Shea-Brown:
Structured chaos shapes spike-response noise entropy in balanced neural networks. Frontiers Comput. Neurosci. 8: 123 (2014) - [j21]Yu Hu, Joel Zylberberg, Eric Shea-Brown:
The Sign Rule and Beyond: Boundary Effects, Flexibility, and Noise Correlations in Neural Population Codes. PLoS Comput. Biol. 10(2) (2014) - 2013
- [j20]James Trousdale, Yu Hu, Eric Shea-Brown, Kresimir Josic:
A generative spike train model with time-structured higher order correlations. Frontiers Comput. Neurosci. 7: 84 (2013) - [j19]Nicholas Cain, Eric Shea-Brown:
Impact of Correlated Neural Activity on Decision-Making Performance. Neural Comput. 25(2): 289-327 (2013) - [j18]N. Alex Cayco-Gajic, Eric Shea-Brown:
Neutral Stability, Rate Propagation, and Critical Branching in Feedforward Networks. Neural Comput. 25(7): 1768-1806 (2013) - 2012
- [j17]James Trousdale, Yu Hu, Eric Shea-Brown, Kresimir Josic:
Impact of Network Structure and Cellular Response on Spike Time Correlations. PLoS Comput. Biol. 8(3) (2012) - 2011
- [j16]Joshua H. Goldwyn, Eric Shea-Brown:
The What and Where of Adding Channel Noise to the Hodgkin-Huxley Equations. PLoS Comput. Biol. 7(11) (2011) - [j15]Guillaume Lajoie, Eric Shea-Brown:
Shared Inputs, Entrainment, and Desynchrony in Elliptic Bursters: From Slow Passage to Discontinuous Circle Maps. SIAM J. Appl. Dyn. Syst. 10(4): 1232-1271 (2011) - 2010
- [j14]Joshua H. Goldwyn, Eric Shea-Brown, Jay T. Rubinstein:
Encoding and decoding amplitude-modulated cochlear implant stimuli - a point process analysis. J. Comput. Neurosci. 28(3): 405-424 (2010) - [i1]Andrea K. Barreiro, Julijana Gjorgjieva, Fred Rieke, Eric Shea-Brown:
When are feedforward microcircuits well-modeled by maximum entropy methods? CoRR abs/1011.2797 (2010)
2000 – 2009
- 2009
- [j13]Kevin K. Lin, Eric Shea-Brown, Lai-Sang Young:
Spike-time reliability of layered neural oscillator networks. J. Comput. Neurosci. 27(1): 135-160 (2009) - [j12]Kevin K. Lin, Eric Shea-Brown, Lai-Sang Young:
Reliability of Coupled Oscillators. J. Nonlinear Sci. 19(5): 497-545 (2009) - [j11]Kresimir Josic, Eric Shea-Brown, Brent Doiron, Jaime de la Rocha:
Stimulus-Dependent Correlations and Population Codes. Neural Comput. 21(10): 2774-2804 (2009) - 2008
- [j10]Eric Shea-Brown, Mark S. Gilzenrat, Jonathan D. Cohen:
Optimization of Decision Making in Multilayer Networks: The Role of Locus Coeruleus. Neural Comput. 20(12): 2863-2894 (2008) - 2007
- [j9]Xiao-Jiang Feng, Eric Shea-Brown, Brian Greenwald, Robert L. Kosut, Herschel Rabitz:
Optimal deep brain stimulation of the subthalamic nucleus - a computational study. J. Comput. Neurosci. 23(3): 265-282 (2007) - 2006
- [j8]Martin Golubitsky, Kresimir Josic, Eric Shea-Brown:
Winding Numbers and Average Frequencies in Phase Oscillator Networks. J. Nonlinear Sci. 16(3): 201-231 (2006) - [j7]Jeff Moehlis, Kresimir Josic, Eric Shea-Brown:
Periodic orbit. Scholarpedia 1(7): 1358 (2006) - [j6]Kresimir Josic, Eric Shea-Brown, Jeff Moehlis:
Isochron. Scholarpedia 1(8): 1361 (2006) - [j5]Philip Holmes, Eric Shea-Brown:
Stability. Scholarpedia 1(10): 1838 (2006) - 2005
- [j4]Philip Holmes, Eric Shea-Brown, Jeff Moehlis, Rafal Bogacz, Juan Gao, Gary Aston-Jones, Ed Clayton, Janusz Rajkowski, Jonathan D. Cohen:
Optimal Decisions: From Neural Spikes, through Stochastic Differential Equations, to Behavior. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 88-A(10): 2496-2503 (2005) - [j3]Eric Brown, Juan Gao, Philip Holmes, Rafal Bogacz, Mark S. Gilzenrat, Jonathan D. Cohen:
Simple Neural Networks that Optimize Decisions. Int. J. Bifurc. Chaos 15(3): 803-826 (2005) - 2004
- [j2]Eric Brown, Jeff Moehlis, Philip Holmes, Ed Clayton, Janusz Rajkowski, Gary Aston-Jones:
The Influence of Spike Rate and Stimulus Duration on Noradrenergic Neurons. J. Comput. Neurosci. 17(1): 13-29 (2004) - [j1]Eric Brown, Jeff Moehlis, Philip Holmes:
On the Phase Reduction and Response Dynamics of Neural Oscillator Populations. Neural Comput. 16(4): 673-715 (2004)
Coauthor Index
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