| An integrated reweighting theory of perceptual learning BA Dosher, P Jeter, J Liu, ZL Lu Proceedings of the National Academy of Sciences 110 (33), 13678-13683, 2013 | 148 | 2013 |
| Modeling mechanisms of perceptual learning with augmented Hebbian re-weighting ZL Lu, J Liu, BA Dosher Vision research 50 (4), 375-390, 2010 | 72 | 2010 |
| Mixed training at high and low accuracy levels leads to perceptual learning without feedback J Liu, ZL Lu, BA Dosher Vision research 61, 15-24, 2012 | 34 | 2012 |
| Modeling trial by trial and block feedback in perceptual learning J Liu, B Dosher, ZL Lu Vision Research 99, 46-56, 2014 | 32 | 2014 |
| Augmented Hebbian reweighting accounts for accuracy and induced bias in perceptual learning with reverse feedback J Liu, BA Dosher, ZL Lu Journal of vision 15 (10), 10-10, 2015 | 11 | 2015 |
| Roving: The causes of interference and re-enabled learning in multi-task visual training BA Dosher, J Liu, W Chu, ZL Lu Journal of vision 20 (6), 9-9, 2020 | 6 | 2020 |
| Multi-location augmented Hebbian re-weighting accounts for transfer of perceptual learning following double training J Liu, ZL Lu, B Dosher Journal of Vision 11 (11), 992-992, 2011 | 6 | 2011 |
| Augmented Hebbian learning accounts for the complex pattern of effects of feedback in perceptual learning J Liu, Z Lu, B Dosher Journal of Vision 10 (7), 1115-1115, 2010 | 5 | 2010 |
| Augmented Hebbian learning accounts for the Eureka effect in perceptual learning J Liu, ZL Lu, B Dosher Journal of Vision 9 (8), 851-851, 2009 | 4 | 2009 |
| Modeling perceptual learning in external noise with Hebbian reweighting ZL Lu, J Liu, B Dosher Journal of Vision 9 (8), 863-863, 2009 | 3 | 2009 |
| Augmented Hebbian learning hypothesis in perceptual learning: Interaction between feedback and training accuracy J Liu, Z Lu, B Dosher Journal of Vision 8 (6), 1124-1124, 2008 | 3 | 2008 |
| Hierarchical Bayesian modeling of training accuracy and feedback interaction in perceptual learning Y Zhao, J Liu, BA Dosher, ZL Lu Journal of Vision 21 (9), 2214-2214, 2021 | 2 | 2021 |
| Perceptual learning of task mixtures B Dosher, W Chu, J Liu, ZL Lu Journal of Vision 12 (9), 767-767, 2012 | 2 | 2012 |
| Evaluating the functional form of perceptual learning with trial-by-trial analysis Y Zhao, P Zhang, G Chen, J Yang, CB Huang, J Liu, BA Dosher, ZL Lu Journal of Vision 20 (11), 1643-1643, 2020 | 1 | 2020 |
| Perceptual learning in n-alternative forced choice with response and accuracy feedback, and a reweighting model. J Liu, B Dosher, ZL Lu Journal of Vision 17 (10), 1078-1078, 2017 | 1 | 2017 |
| A multi-location augmented Hebbian reweighting model (m-AHRM) of transfer in perceptual learning B Dosher, P Jeter, J Liu, ZL Lu Journal of Vision 11 (11), 978-978, 2011 | 1 | 2011 |
| Hierarchical Bayesian modeling of training accuracy and feedback interaction in perceptual learning in a between-subject design Y Zhao, J Liu, BA Dosher, ZL Lu Journal of Vision 22 (14), 3368-3368, 2022 | | 2022 |
| Hierarchical Bayesian modeling of mixed training accuracy effects in perceptual learning ZL Lu, Y Zhao, J Liu, B Dosher Journal of Vision 21 (9), 2219-2219, 2021 | | 2021 |
| Multi-location, two-interval paradigms can overcome roving costs–an explanation of Xie & Yu (2020) data by an extended Integrating Reweighting Theory (IRT) J Liu, ZL Lu, B Dosher Journal of Vision 21 (9), 2264-2264, 2021 | | 2021 |
| Perceptual learning of orientation identification in filtered external noise: a test of the integrated reweighting theory (IRT) B Dosher, J Liu, ZL Lu Journal of Vision 20 (11), 904-904, 2020 | | 2020 |
Zhong-Lin LuNYU Shanghai and NYUVerified email at nyu.edu
