Search research articles
Contact Us
Filters
Showing results (21-30 of 66) with videos related to
Page
of 7
Sort By:
Frontiers in Computational Neuroscience
|
August 3, 2013
A generative spike train model with time-structured higher order correlations
James Trousdale, Yu Hu, Eric Shea-Brown, et al.
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|
April 7, 2010
Time scales of spike-train correlation for neural oscillators with common drive
Andrea K Barreiro, Eric Shea-Brown, Evan L Thilo
Journal of Neurophysiology
|
June 8, 2012
A-current and type I/type II transition determine collective spiking from common input
Andrea K Barreiro, Evan L Thilo, Eric Shea-Brown
Plos Computational Biology
|
March 30, 2012
Impact of network structure and cellular response on spike time correlations
James Trousdale, Yu Hu, Eric Shea-Brown, et al.
Entropy (Basel, Switzerland)
|
December 3, 2020
A Moment-Based Maximum Entropy Model for Fitting Higher-Order Interactions in Neural Data
N Alex Cayco-Gajic, Joel Zylberberg, Eric Shea-Brown
Frontiers in Computational Neuroscience
|
June 5, 2015
Triplet correlations among similarly tuned cells impact population coding
Natasha A Cayco-Gajic, Joel Zylberberg, Eric Shea-Brown
Neural Computation
|
July 16, 2008
Optimization of decision making in multilayer networks: the role of locus coeruleus
Eric Shea-Brown, Mark S Gilzenrat, Jonathan D Cohen
Journal of Computational Neuroscience
|
January 22, 2009
Spike-time reliability of layered neural oscillator networks
Kevin K Lin, Eric Shea-Brown, Lai-Sang Young
Journal of Neurophysiology
|
March 1, 2013
Neural integrators for decision making: a favorable tradeoff between robustness and sensitivity
Nicholas Cain, Andrea K Barreiro, Michael Shadlen, et al.
Brain Research
|
January 18, 2006
A firing rate model of Parkinsonian deficits in interval timing
Eric Shea-Brown, John Rinzel, Brian C Rakitin, et al.
Page
of 7
Search research articles
Search
Showing results (21-30 of 66) with videos related to
Sort By:
Page
of 7
Frontiers in Computational Neuroscience
|
August 3, 2013
A generative spike train model with time-structured higher order correlations
James Trousdale, Yu Hu, Eric Shea-Brown, et al.
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|
April 7, 2010
Time scales of spike-train correlation for neural oscillators with common drive
Andrea K Barreiro, Eric Shea-Brown, Evan L Thilo
Journal of Neurophysiology
|
June 8, 2012
A-current and type I/type II transition determine collective spiking from common input
Andrea K Barreiro, Evan L Thilo, Eric Shea-Brown
Plos Computational Biology
|
March 30, 2012
Impact of network structure and cellular response on spike time correlations
James Trousdale, Yu Hu, Eric Shea-Brown, et al.
Entropy (Basel, Switzerland)
|
December 3, 2020
A Moment-Based Maximum Entropy Model for Fitting Higher-Order Interactions in Neural Data
N Alex Cayco-Gajic, Joel Zylberberg, Eric Shea-Brown
Frontiers in Computational Neuroscience
|
June 5, 2015
Triplet correlations among similarly tuned cells impact population coding
Natasha A Cayco-Gajic, Joel Zylberberg, Eric Shea-Brown
Neural Computation
|
July 16, 2008
Optimization of decision making in multilayer networks: the role of locus coeruleus
Eric Shea-Brown, Mark S Gilzenrat, Jonathan D Cohen
Journal of Computational Neuroscience
|
January 22, 2009
Spike-time reliability of layered neural oscillator networks
Kevin K Lin, Eric Shea-Brown, Lai-Sang Young
Journal of Neurophysiology
|
March 1, 2013
Neural integrators for decision making: a favorable tradeoff between robustness and sensitivity
Nicholas Cain, Andrea K Barreiro, Michael Shadlen, et al.
Brain Research
|
January 18, 2006
A firing rate model of Parkinsonian deficits in interval timing
Eric Shea-Brown, John Rinzel, Brian C Rakitin, et al.
Page
of 7