Eric Shea-Brown

59 papers A* 6Journal 52Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Identifying Connectivity Distributions from Neural Dynamics Using Flows. CoRR Timothy Doyeon Kim, Ulises Pereira-Obilinovic, Yiliu Wang, Eric Shea-Brown, Uygar Sümbül
2025	J	`jnl`	Benchmarking Probabilistic Time Series Forecasting Models on Neural Activity. CoRR Ziyu Lu, Anna J. Li, Alexander E. Ladd, Pascha Matveev, Aditya Deole, Eric Shea-Brown, J. Nathan Kutz, Nicholas A. Steinmetz
2025	J	`jnl`	Interpretable time series analysis with Gumbel dynamics. CoRR Yiliu Wang, Timothy Doyeon Kim, Eric Shea-Brown, Uygar Sümbül
2025	J	`jnl`	KPFlow: An Operator Perspective on Dynamic Collapse Under Gradient Descent Training of Recurrent Networks. CoRR James Hazelden, Laura Driscoll, Eli Shlizerman, Eric Shea-Brown
2024	A*	`conf`	How connectivity structure shapes rich and lazy learning in neural circuits. ICLR Yuhan Helena Liu, Aristide Baratin, Jonathan Cornford, Stefan Mihalas, Eric Shea-Brown, Guillaume Lajoie
2024	J	`jnl`	Identifying the impact of local connectivity patterns on dynamics in excitatory-inhibitory networks. CoRR Yuxiu Shao, David Dahmen, Stefano Recanatesi, Eric Shea-Brown, Srdjan Ostojic
2023	J	`jnl`	A biologically inspired architecture with switching units can learn to generalize across backgrounds. Neural Networks Doris Voina, Eric Shea-Brown, Stefan Mihalas
2023	J	`jnl`	A simple connection from loss flatness to compressed representations in neural networks. CoRR Shirui Chen, Stefano Recanatesi, Eric Shea-Brown
2023	J	`jnl`	Attention for Causal Relationship Discovery from Biological Neural Dynamics. CoRR Ziyu Lu, Anika Tabassum, Shruti R. Kulkarni, Lu Mi, J. Nathan Kutz, Eric Shea-Brown, Seung-Hwan Lim
2023	J	`jnl`	Evolutionary algorithms as an alternative to backpropagation for supervised training of Biophysical Neural Networks and Neural ODEs. CoRR James Hazelden, Yuhan Helena Liu, Eli Shlizerman, Eric Shea-Brown
2023	A*	`conf`	Expressive probabilistic sampling in recurrent neural networks. NeurIPS Shirui Chen, Linxing Jiang, Rajesh P. N. Rao, Eric Shea-Brown
2023	J	`jnl`	Expressive probabilistic sampling in recurrent neural networks. CoRR Shirui Chen, Linxing Preston Jiang, Rajesh P. N. Rao, Eric Shea-Brown
2023	J	`jnl`	Heterogeneity in Neuronal Dynamics Is Learned by Gradient Descent for Temporal Processing Tasks. Neural Comput. Chloe N. Winston, Dana Mastrovito, Eric Shea-Brown, Stefan Mihalas
2023	J	`jnl`	How connectivity structure shapes rich and lazy learning in neural circuits. CoRR Yuhan Helena Liu, Aristide Baratin, Jonathan Cornford, Stefan Mihalas, Eric Shea-Brown, Guillaume Lajoie
2023	J	`jnl`	Modeling functional cell types in spike train data. PLoS Comput. Biol. Daniel N. Zdeblick, Eric Shea-Brown, Daniela M. Witten, Michael A. Buice
2022	J	`jnl`	A scale-dependent measure of system dimensionality. Patterns Stefano Recanatesi, Serena Bradde, Vijay Balasubramanian, Nicholas A. Steinmetz, Eric Shea-Brown
2022	J	`jnl`	Author Correction: Gradient-based learning drives robust representations in recurrent neural networks by balancing compression and expansion. Nat. Mac. Intell. Matthew Farrell, Stefano Recanatesi, Timothy Moore, Guillaume Lajoie, Eric Shea-Brown
2022	A*	`conf`	Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules. NeurIPS Yuhan Helena Liu, Arna Ghosh, Blake A. Richards, Eric Shea-Brown, Guillaume Lajoie
2022	J	`jnl`	Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules. CoRR Yuhan Helena Liu, Arna Ghosh, Blake A. Richards, Eric Shea-Brown, Guillaume Lajoie
2022	A*	`conf`	Biologically-plausible backpropagation through arbitrary timespans via local neuromodulators. NeurIPS Yuhan Helena Liu, Stephen Smith, Stefan Mihalas, Eric Shea-Brown, Uygar Sümbül
2022	J	`jnl`	Biologically-plausible backpropagation through arbitrary timespans via local neuromodulators. CoRR Yuhan Helena Liu, Stephen Smith, Stefan Mihalas, Eric Shea-Brown, Uygar Sümbül
2022	J	`jnl`	Gradient-based learning drives robust representations in recurrent neural networks by balancing compression and expansion. Nat. Mach. Intell. Matthew Farrell, Stefano Recanatesi, Timothy Moore, Guillaume Lajoie, Eric Shea-Brown
2022	A*	`conf`	Learning dynamics of deep linear networks with multiple pathways. NeurIPS Jianghong Shi, Eric Shea-Brown, Michael A. Buice
2022	J	`jnl`	MouseNet: A biologically constrained convolutional neural network model for the mouse visual cortex. PLoS Comput. Biol. Jianghong Shi, Bryan P. Tripp, Eric Shea-Brown, Stefan Mihalas, Michael A. Buice
2022	J	`jnl`	Single Circuit in V1 Capable of Switching Contexts During Movement Using an Inhibitory Population as a Switch. Neural Comput. Doris Voina, Stefano Recanatesi, Brian Hu, Eric Shea-Brown, Stefan Mihalas
2021	J	`jnl`	Autoencoder networks extract latent variables and encode these variables in their connectomes. Neural Networks Matthew Farrell, Stefano Recanatesi, R. Clay Reid, Stefan Mihalas, Eric Shea-Brown
2019	A*	`conf`	Comparison Against Task Driven Artificial Neural Networks Reveals Functional Properties in Mouse Visual Cortex. NeurIPS Jianghong Shi, Eric Shea-Brown, Michael A. Buice
2019	J	`jnl`	Dimensionality compression and expansion in Deep Neural Networks. CoRR Stefano Recanatesi, Matthew Farrell, Madhu Advani, Timothy Moore, Guillaume Lajoie, Eric Shea-Brown
2019	J	`jnl`	Dimensionality in recurrent spiking networks: Global trends in activity and local origins in connectivity. PLoS Comput. Biol. Stefano Recanatesi, Gabriel Koch Ocker, Michael A. Buice, Eric Shea-Brown
2018	J	`jnl`	A Moment-Based Maximum Entropy Model for Fitting Higher-Order Interactions in Neural Data. Entropy N. Alex Cayco-Gajic, Joel Zylberberg, Eric Shea-Brown
2018	J	`jnl`	Predicting how and when hidden neurons skew measured synaptic interactions. PLoS Comput. Biol. Braden A. W. Brinkman, Fred Rieke, Eric Shea-Brown, Michael A. Buice
2018	J	`jnl`	Predictive Coding in Area V4: Dynamic Shape Discrimination under Partial Occlusion. Neural Comput. Hannah Choi, Anitha Pasupathy, Eric Shea-Brown
2017	J	`jnl`	Linking structure and activity in nonlinear spiking networks. PLoS Comput. Biol. Gabriel Koch Ocker, Kresimir Josic, Eric Shea-Brown, Michael A. Buice
2017	J	`jnl`	Robust information propagation through noisy neural circuits. PLoS Comput. Biol. Joel Zylberberg, Alexandre Pouget, Peter E. Latham, Eric Shea-Brown
2016	J	`jnl`	Encoding in Balanced Networks: Revisiting Spike Patterns and Chaos in Stimulus-Driven Systems. PLoS Comput. Biol. Guillaume Lajoie, Kevin K. Lin, Jean-Philippe Thivierge, Eric Shea-Brown
2016	—	`conf`	High resolution neural connectivity from incomplete tracing data using nonnegative spline regression. NIPS Kameron Decker Harris, Stefan Mihalas, Eric Shea-Brown
2016	J	`jnl`	How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits? PLoS Comput. Biol. Braden A. W. Brinkman, Alison I. Weber, Fred Rieke, Eric Shea-Brown
2015	J	`jnl`	Triplet correlations among similarly tuned cells impact population coding. Frontiers Comput. Neurosci. Natasha A. Cayco-Gajic, Joel Zylberberg, Eric Shea-Brown
2014	J	`jnl`	Structured chaos shapes spike-response noise entropy in balanced neural networks. Frontiers Comput. Neurosci. Guillaume Lajoie, Jean-Philippe Thivierge, Eric Shea-Brown
2014	J	`jnl`	The Sign Rule and Beyond: Boundary Effects, Flexibility, and Noise Correlations in Neural Population Codes. PLoS Comput. Biol. Yu Hu, Joel Zylberberg, Eric Shea-Brown
2014	J	`jnl`	When do microcircuits produce beyond-pairwise correlations? Frontiers Comput. Neurosci. Andrea K. Barreiro, Julijana Gjorgjieva, Fred Rieke, Eric Shea-Brown
2013	J	`jnl`	A generative spike train model with time-structured higher order correlations. Frontiers Comput. Neurosci. James Trousdale, Yu Hu, Eric Shea-Brown, Kresimir Josic
2013	J	`jnl`	Impact of Correlated Neural Activity on Decision-Making Performance. Neural Comput. Nicholas Cain, Eric Shea-Brown
2013	J	`jnl`	Neutral Stability, Rate Propagation, and Critical Branching in Feedforward Networks. Neural Comput. N. Alex Cayco-Gajic, Eric Shea-Brown
2012	J	`jnl`	Impact of Network Structure and Cellular Response on Spike Time Correlations. PLoS Comput. Biol. James Trousdale, Yu Hu, Eric Shea-Brown, Kresimir Josic
2011	J	`jnl`	Shared Inputs, Entrainment, and Desynchrony in Elliptic Bursters: From Slow Passage to Discontinuous Circle Maps. SIAM J. Appl. Dyn. Syst. Guillaume Lajoie, Eric Shea-Brown
2011	J	`jnl`	The What and Where of Adding Channel Noise to the Hodgkin-Huxley Equations. PLoS Comput. Biol. Joshua H. Goldwyn, Eric Shea-Brown
2010	J	`jnl`	Encoding and decoding amplitude-modulated cochlear implant stimuli - a point process analysis. J. Comput. Neurosci. Joshua H. Goldwyn, Eric Shea-Brown, Jay T. Rubinstein
2010	J	`jnl`	When are feedforward microcircuits well-modeled by maximum entropy methods? CoRR Andrea K. Barreiro, Julijana Gjorgjieva, Fred Rieke, Eric Shea-Brown
2009	J	`jnl`	Reliability of Coupled Oscillators. J. Nonlinear Sci. Kevin K. Lin, Eric Shea-Brown, Lai-Sang Young
2009	J	`jnl`	Spike-time reliability of layered neural oscillator networks. J. Comput. Neurosci. Kevin K. Lin, Eric Shea-Brown, Lai-Sang Young
2009	J	`jnl`	Stimulus-Dependent Correlations and Population Codes. Neural Comput. Kresimir Josic, Eric Shea-Brown, Brent Doiron, Jaime de la Rocha
2008	J	`jnl`	Optimization of Decision Making in Multilayer Networks: The Role of Locus Coeruleus. Neural Comput. Eric Shea-Brown, Mark S. Gilzenrat, Jonathan D. Cohen
2007	J	`jnl`	Optimal deep brain stimulation of the subthalamic nucleus - a computational study. J. Comput. Neurosci. Xiao-Jiang Feng, Eric Shea-Brown, Brian Greenwald, Robert L. Kosut, Herschel Rabitz
2006	J	`jnl`	Isochron. Scholarpedia Kresimir Josic, Eric Shea-Brown, Jeff Moehlis
2006	J	`jnl`	Periodic orbit. Scholarpedia Jeff Moehlis, Kresimir Josic, Eric Shea-Brown
2006	J	`jnl`	Stability. Scholarpedia Philip Holmes, Eric Shea-Brown
2006	J	`jnl`	Winding Numbers and Average Frequencies in Phase Oscillator Networks. J. Nonlinear Sci. Martin Golubitsky, Kresimir Josic, Eric Shea-Brown
2005	J	`jnl`	Optimal Decisions: From Neural Spikes, through Stochastic Differential Equations, to Behavior. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. Philip Holmes, Eric Shea-Brown, Jeff Moehlis, Rafal Bogacz, Juan Gao, Gary Aston-Jones, Ed Clayton, Janusz Rajkowski, Jonathan D. Cohen