引用次数
引用: 8,349
H-指数: 41
I10-指数 : 80
出版物: 223
Shared inputs and desynchrony in elliptic bursters: from slow passage to discontinuous circle maps
Guillaume Lajoie , Eric Shea-Brown
2010
A point process framework for modeling electrical stimulation of the auditory nerve
Jay T. Rubinstein , Joshua H. Goldwyn , Eric Shea-Brown
Journal of Neurophysiology 108 ( 5) 1430 -1452
14
2012
High resolution neural connectivity from incomplete tracing data using nonnegative spline regression
Stefan Mihalas , Kameron D. Harris , Eric Shea-Brown
neural information processing systems 29 3099 -3107
6
2016
Signatures and mechanisms of low-dimensional neural predictive manifolds
Mattia Rigotti , Guillaume Lajoie , Sophie Deneve , Matthew Farrell
bioRxiv 471987
5
2018
Dynamic compression and expansion in a classifying recurrent network
Guillaume Lajoie , Matthew Farrell , Stefano Recanatesi , Eric Shea-Brown
bioRxiv 564476
9
2019
From the statistics of connectivity to the statistics of spike times in neuronal networks
Krešimir Josić , Michael A. Buice , Gabriel Koch Ocker , Robert Rosenbaum
arXiv: Neurons and Cognition
2017
Comparison Against Task Driven Artificial Neural Networks Reveals Functional Properties in Mouse Visual Cortex
Michael A. Buice , Jianghong Shi , Eric Shea-Brown
neural information processing systems 32 5764 -5774
4
2019
Inferring the Spiking Rate of a Population of Neurons from Wide-Field Calcium Imaging
Daniela Witten , Merav Stern , Eric Shea-Brown
bioRxiv
4
2020
Poster: the Sign Rule and Beyond: Boundary Effects, Flexibility, and Noise Correlations in Population Codes
Joel Zylberberg , Yu Hu , Eric Shea-Brown
2014
Predictive learning extracts latent space representations from sensory observations
Mattia Rigotti , Guillaume Lajoie , Sophie Deneve , Matthew Farrell
bioRxiv 471987
6
2019
Cortical representation variability aligns with in-class variances and can help one-shot learning
Stefan Mihalas , Stefan Mihalas , Jiaqi Shang , Jiaqi Shang
bioRxiv
2021
Predictive learning as a network mechanism for extracting low-dimensional latent space representations.
Mattia Rigotti , Guillaume Lajoie , Sophie Deneve , Matthew Farrell
Nature Communications 12 ( 1) 1417 -1417
2021
Autoencoder networks extract latent variables and encode these variables in their connectomes.
Stefan Mihalas , R. Clay Reid , Matthew Farrell , Stefano Recanatesi
Neural Networks 141 330 -343
2021
Network Dynamics Governed by Lyapunov Functions: From Memory to Classification.
Merav Stern , Eric Shea-Brown
Trends in Neurosciences 43 ( 7) 453 -455
2020
How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?
Braden A. W. Brinkman , Alison I. Weber , Fred Rieke , Eric Shea-Brown
PLOS Computational Biology 12 ( 10) e1005150
36
2016
Correlation and synchrony transfer in integrate-and-fire neurons: basic properties and consequences for coding.
Eric Shea-Brown , Krešimir Josić , Jaime de la Rocha , Brent Doiron
Physical Review Letters 100 ( 10) 108102
132
2008
Structured chaos shapes joint spike-response noise entropy in temporally driven balanced networks
Guillaume Lajoie , Jean-Philippe Thivierge , Eric Shea-Brown
BMC Neuroscience 15 ( 1) 48
2014
When does recurrent connectivity improve neural population coding
Joel Zylberberg , Eric Shea-Brown
BMC Neuroscience 15 ( 1) 49
2014
Noise- and stimulus-dependence of the optimal encoding nonlinearities in a simple ON/OFF retinal circuit model
Braden A W Brinkman , Alison Weber , Fred Rieke , Eric Shea-Brown
BMC Neuroscience 15 ( 1) 47
2014
Limited range correlations, when modulated by firing rate, can substantially improve neural population coding
Joel Zylberberg , Jon Cafaro , Maxwell Turner , Fred Rieke
BMC Neuroscience 16 ( 1) 1 -2
3
2015