Wen-Hao Zhang
Wen-Hao Zhang
Department of Mathematics, University of Pittsburgh
Verified email at pitt.edu - Homepage
Title
Cited by
Cited by
Year
Decentralized multisensory information integration in neural systems
WH Zhang, A Chen, MJ Rasch, S Wu
Journal of Neuroscience 36 (2), 532-547, 2016
362016
Continuous attractor neural networks: candidate of a canonical model for neural information representation
S Wu, KYM Wong, CCA Fung, Y Mi, WH Zhang
F1000Research 5, 2016
202016
Neural information processing with feedback modulations
WH Zhang, S Wu
Neural computation 24 (7), 1695-1721, 2012
162012
Reciprocally coupled local estimators implement Bayesian information integration distributively
WH Zhang, S Wu
Advances in Neural Information Processing Systems, 19-27, 2013
92013
“Congruent” and “opposite” neurons: sisters for multisensory integration and segregation
WH Zhang, H Wang, KYM Wong, S Wu
Advances in Neural Information Processing Systems, 3180-3188, 2016
82016
Complementary congruent and opposite neurons achieve concurrent multisensory integration and segregation
WH Zhang, H Wang, A Chen, Y Gu, TS Lee, KYM Wong, S Wu
eLife 8, e43753, 2019
52019
Dynamic information encoding with dynamic synapses in neural adaptation
L Li, Y Mi, WH Zhang, DH Wang, S Wu
Frontiers in Computational Neuroscience 12, 16, 2018
32018
How the prior information shapes neural networks for optimal multisensory integration
H Wang, WH Zhang, KYM Wong, S Wu
International Symposium on Neural Networks, 128-136, 2017
32017
25th annual computational neuroscience meeting: CNS-2016
TO Sharpee, A Destexhe, M Kawato, V Sekulić, FK Skinner, DK Wójcik, ...
BMC Neuroscience 17 (1), 54, 2016
32016
A Normative Theory for Causal Inference and Bayes Factor Computation in Neural Circuits
WH Zhang, S Wu, B Doiron, TS Lee
Advances in Neural Information Processing Systems, 3799-3808, 2019
12019
Distributed Sampling-based Bayesian Inference in Coupled Neural Circuits
W Zhang, TS Lee, B Doiron, S Wu
bioRxiv, 2020
2020
The Dynamics of Bimodular Continuous Attractor Neural Networks with Static and Moving Stimuli
M Yan, WH Zhang, H Wang, KY Wong
arXiv preprint arXiv:1910.07263, 2019
2019
Bayesian Model for Multisensory Integration and Segregation
X Ma, H Wang, M Yan, W Zhang, MKY Wong
2019
Emergence of opposite neurons in a decentralized firing-rate model of multisensory integration
X Niu, HY Chau, TS Lee, WH Zhang
bioRxiv, 845743, 2019
2019
Concurrent Multisensory Integration and Segregation with Complementary Congruent and Opposite Neurons
WH Zhang, H Wang, A Chen, Y Gu, TS Lee, KYM Wong, S Wu
bioRxiv, 471490, 2018
2018
Optimal modular network for multisensory integration
H Wang, WH Zhang, KY Wong, S Wu
APS 2018, V06. 011, 2018
2018
The Dynamics of Bimodular Continuous Attractor Neural Networks with Moving Stimuli
M Yan, WH Zhang, H Wang, KYM Wong
International Conference on Neural Information Processing, 648-657, 2017
2017
Encoding Multisensory Information in Modular Neural Networks
H Wang, WH Zhang, KYM Wong, S Wu
International Conference on Neural Information Processing, 658-665, 2017
2017
Congruent and Opposite Neurons as Partners in Multisensory Integration and Segregation
WH Zhang, KY Wong, H Wang, S Wu
APS 2017, Y14. 008, 2017
2017
How the prior information shapes couplings in neural fields performing optimal multisensory integration
H Wang, WH Zhang, KY Wong, S Wu
APS 2017, Y14. 006, 2017
2017
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