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Lai-Sang Young
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- affiliation: New York University, Courant Institute of Mathematical Sciences, USA
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2020 – today
- 2022
- [j11]Benjamin Ambrosio, Lai-Sang Young:
The Use of Reduced Models to Generate Irregular, Broad-Band Signals That Resemble Brain Rhythms. Frontiers Comput. Neurosci. 16: 889235 (2022) - 2021
- [j10]Sonica Saraf
, Lai-Sang Young:
Malleability of gamma rhythms enhances population-level correlations. J. Comput. Neurosci. 49(2): 189-205 (2021) - [j9]Yao Li
Unraveling the mechanisms of surround suppression in early visual processing. PLoS Comput. Biol. 17(4) (2021) - [j8]Zhuo-Cheng Xiao
A data-informed mean-field approach to mapping of cortical parameter landscapes. PLoS Comput. Biol. 17(12) (2021)
2010 – 2019
- 2019
- [j7]Madhura R. Joglekar, Logan Chariker
A case study in the functional consequences of scaling the sizes of realistic cortical models. PLoS Comput. Biol. 15(7) (2019) - 2016
- [j6]Guillaume Lajoie, Lai-Sang Young:
Dynamic Signal Tracking in a Simple V1 Spiking Model. Neural Comput. 28(9): 1985-2010 (2016) - 2015
- [j5]Logan Chariker, Lai-Sang Young:
Emergent spike patterns in neuronal populations. J. Comput. Neurosci. 38(1): 203-220 (2015) - 2013
- [j4]Aaditya V. Rangan, Lai-Sang Young:
Dynamics of spiking neurons: between homogeneity and synchrony. J. Comput. Neurosci. 34(3): 433-460 (2013) - [j3]Aaditya V. Rangan, Lai-Sang Young:
Emergent dynamics in a model of visual cortex. J. Comput. Neurosci. 35(2): 155-167 (2013) - [i1]Alain Barrat, Bastien Fernandez, Kevin K. Lin, Lai-Sang Young:
Modeling temporal networks using random itineraries. CoRR abs/1303.4411 (2013)
2000 – 2009
- 2009
- [j2]Kevin K. Lin
Spike-time reliability of layered neural oscillator networks. J. Comput. Neurosci. 27(1): 135-160 (2009) - [j1]Kevin K. Lin
Reliability of Coupled Oscillators. J. Nonlinear Sci. 19(5): 497-545 (2009)
Coauthor Index
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