Eric Shea-Brown

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 33

Top Topics

Predictive Coding

Partial Occlusion

Top Venues

PLoS Comput. Biol.

Frontiers Comput. Neurosci.

Publications

Yuhan Helena Liu, Aristide Baratin, Jonathan Cornford, Stefan Mihalas, Eric Shea-Brown, Guillaume Lajoie
How connectivity structure shapes rich and lazy learning in neural circuits. ICLR (2024)
Doris Voina, Eric Shea-Brown, Stefan Mihalas
A biologically inspired architecture with switching units can learn to generalize across backgrounds. Neural Networks 168 (2023)
Shirui Chen, Linxing Preston Jiang, Rajesh P. N. Rao, Eric Shea-Brown
Expressive probabilistic sampling in recurrent neural networks. CoRR (2023)
Daniel N. Zdeblick, Eric Shea-Brown, Daniela M. Witten, Michael A. Buice
Modeling functional cell types in spike train data. PLoS Comput. Biol. 19 (10) (2023)
Shirui Chen, Stefano Recanatesi, Eric Shea-Brown
A simple connection from loss flatness to compressed representations in neural networks. CoRR (2023)
Shirui Chen, Linxing Jiang, Rajesh P. N. Rao, Eric Shea-Brown
Expressive probabilistic sampling in recurrent neural networks. NeurIPS (2023)
Ziyu Lu, Anika Tabassum, Shruti R. Kulkarni, Lu Mi, J. Nathan Kutz, Eric Shea-Brown, Seung-Hwan Lim
Attention for Causal Relationship Discovery from Biological Neural Dynamics. CoRR (2023)
Chloe N. Winston, Dana Mastrovito, Eric Shea-Brown, Stefan Mihalas
Heterogeneity in Neuronal Dynamics Is Learned by Gradient Descent for Temporal Processing Tasks. Neural Comput. 35 (4) (2023)
James Hazelden, Yuhan Helena Liu, Eli Shlizerman, Eric Shea-Brown
Evolutionary algorithms as an alternative to backpropagation for supervised training of Biophysical Neural Networks and Neural ODEs. CoRR (2023)
Yuhan Helena Liu, Aristide Baratin, Jonathan Cornford, Stefan Mihalas, Eric Shea-Brown, Guillaume Lajoie
How connectivity structure shapes rich and lazy learning in neural circuits. CoRR (2023)
Matthew Farrell, Stefano Recanatesi, Timothy Moore, Guillaume Lajoie, Eric Shea-Brown
Author Correction: Gradient-based learning drives robust representations in recurrent neural networks by balancing compression and expansion. Nat. Mac. Intell. 4 (11) (2022)
Yuhan Helena Liu, Arna Ghosh, Blake A. Richards, Eric Shea-Brown, Guillaume Lajoie
Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules. CoRR (2022)
Stefano Recanatesi, Serena Bradde, Vijay Balasubramanian, Nicholas A. Steinmetz, Eric Shea-Brown
A scale-dependent measure of system dimensionality. Patterns 3 (8) (2022)
Yuhan Helena Liu, Arna Ghosh, Blake A. Richards, Eric Shea-Brown, Guillaume Lajoie
Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules. NeurIPS (2022)
Yuhan Helena Liu, Stephen Smith, Stefan Mihalas, Eric Shea-Brown, Uygar Sümbül
Biologically-plausible backpropagation through arbitrary timespans via local neuromodulators. CoRR (2022)
Matthew Farrell, Stefano Recanatesi, Timothy Moore, Guillaume Lajoie, Eric Shea-Brown
Gradient-based learning drives robust representations in recurrent neural networks by balancing compression and expansion. Nat. Mach. Intell. 4 (6) (2022)
Doris Voina, Stefano Recanatesi, Brian Hu, Eric Shea-Brown, Stefan Mihalas
Single Circuit in V1 Capable of Switching Contexts During Movement Using an Inhibitory Population as a Switch. Neural Comput. 34 (3) (2022)
Jianghong Shi, Bryan Tripp, Eric Shea-Brown, Stefan Mihalas, Michael A. Buice
MouseNet: A biologically constrained convolutional neural network model for the mouse visual cortex. PLoS Comput. Biol. 18 (9) (2022)
Yuhan Helena Liu, Stephen Smith, Stefan Mihalas, Eric Shea-Brown, Uygar Sümbül
Biologically-plausible backpropagation through arbitrary timespans via local neuromodulators. NeurIPS (2022)
Jianghong Shi, Eric Shea-Brown, Michael A. Buice
Learning dynamics of deep linear networks with multiple pathways. NeurIPS (2022)
Matthew Farrell, Stefano Recanatesi, R. Clay Reid, Stefan Mihalas, Eric Shea-Brown
Autoencoder networks extract latent variables and encode these variables in their connectomes. Neural Networks 141 (2021)
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)
Jianghong Shi, Eric Shea-Brown, Michael A. Buice
Comparison Against Task Driven Artificial Neural Networks Reveals Functional Properties in Mouse Visual Cortex. NeurIPS (2019)
Stefano Recanatesi, Matthew Farrell, Madhu Advani, Timothy Moore, Guillaume Lajoie, Eric Shea-Brown
Dimensionality compression and expansion in Deep Neural Networks. CoRR (2019)
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)
Hannah Choi, Anitha Pasupathy, Eric Shea-Brown
Predictive Coding in Area V4: Dynamic Shape Discrimination under Partial Occlusion. Neural Comput. 30 (5) (2018)
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) (2018)
Joel Zylberberg, Alexandre Pouget, Peter E. Latham, Eric Shea-Brown
Robust information propagation through noisy neural circuits. PLoS Comput. Biol. 13 (4) (2017)
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)
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)
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)
Kameron Decker Harris, Stefan Mihalas, Eric Shea-Brown
High resolution neural connectivity from incomplete tracing data using nonnegative spline regression. NIPS (2016)
Natasha A. Cayco-Gajic, Joel Zylberberg, Eric Shea-Brown
Triplet correlations among similarly tuned cells impact population coding. Frontiers Comput. Neurosci. 9 (2015)
Andrea K. Barreiro, Julijana Gjorgjieva, Fred Rieke, Eric Shea-Brown
When do microcircuits produce beyond-pairwise correlations? Frontiers Comput. Neurosci. 8 (2014)
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)
Guillaume Lajoie, Jean-Philippe Thivierge, Eric Shea-Brown
Structured chaos shapes spike-response noise entropy in balanced neural networks. Frontiers Comput. Neurosci. 8 (2014)
N. Alex Cayco-Gajic, Eric Shea-Brown
Neutral Stability, Rate Propagation, and Critical Branching in Feedforward Networks. Neural Comput. 25 (7) (2013)
James Trousdale, Yu Hu, Eric Shea-Brown, Kresimir Josic
A generative spike train model with time-structured higher order correlations. Frontiers Comput. Neurosci. 7 (2013)
Nicholas Cain, Eric Shea-Brown
Impact of Correlated Neural Activity on Decision-Making Performance. Neural Comput. 25 (2) (2013)
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)
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)
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) (2011)
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) (2010)
Andrea K. Barreiro, Julijana Gjorgjieva, Fred Rieke, Eric Shea-Brown
When are feedforward microcircuits well-modeled by maximum entropy methods? CoRR (2010)
Kevin K. Lin, Eric Shea-Brown, Lai-Sang Young
Reliability of Coupled Oscillators. J. Nonlinear Sci. 19 (5) (2009)
Kevin K. Lin, Eric Shea-Brown, Lai-Sang Young
Spike-time reliability of layered neural oscillator networks. J. Comput. Neurosci. 27 (1) (2009)
Kresimir Josic, Eric Shea-Brown, Brent Doiron, Jaime de la Rocha
Stimulus-Dependent Correlations and Population Codes. Neural Comput. 21 (10) (2009)
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) (2008)
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) (2007)
Philip Holmes, Eric Shea-Brown
Stability. Scholarpedia 1 (10) (2006)
Martin Golubitsky, Kresimir Josic, Eric Shea-Brown
Winding Numbers and Average Frequencies in Phase Oscillator Networks. J. Nonlinear Sci. 16 (3) (2006)
Kresimir Josic, Eric Shea-Brown, Jeff Moehlis
Isochron. Scholarpedia 1 (8) (2006)
Jeff Moehlis, Kresimir Josic, Eric Shea-Brown
Periodic orbit. Scholarpedia 1 (7) (2006)
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. (10) (2005)