Bifurcation study of a neural field competition model with an application to perceptual switching in motion integration J Rankin, AI Meso, GS Masson, O Faugeras, P Kornprobst Journal of Computational Neuroscience 36, 193-213, 2014 | 25 | 2014 |
Speed encoding in correlation motion detectors as a consequence of spatial structure AI Meso, JM Zanker Biological cybernetics 100, 361-370, 2009 | 20 | 2009 |
The relative contribution of noise and adaptation to competition during tri-stable motion perception AI Meso, J Rankin, O Faugeras, P Kornprobst, GS Masson Journal of vision 16 (15), 6-6, 2016 | 19 | 2016 |
Numerosity and density judgments: Biases for area but not for volume J Bell, A Manson, M Edwards, AI Meso Journal of vision 15 (2), 18-18, 2015 | 19 | 2015 |
A normalization mechanism for estimating visual motion across speeds and scales N Gekas, AI Meso, GS Masson, P Mamassian Current Biology 27 (10), 1514-1520. e3, 2017 | 16 | 2017 |
Looking for symmetry: Fixational eye movements are biased by image mirror symmetry AI Meso, A Montagnini, J Bell, GS Masson Journal of Neurophysiology 116 (3), 1250-1260, 2016 | 15 | 2016 |
Recurrent network dynamics reconciles visual motion segmentation and integration NVK Medathati, J Rankin, AI Meso, P Kornprobst, GS Masson Scientific Reports 7 (1), 11270, 2017 | 14 | 2017 |
Biologically inspired dynamic textures for probing motion perception J Vacher, AI Meso, LU Perrinet, G Peyré Advances in neural information processing systems 28, 2015 | 13 | 2015 |
Perceiving motion transparency in the absence of component direction differences AI Meso, JM Zanker Vision Research 49 (17), 2187-2200, 2009 | 12 | 2009 |
Bayesian modeling of motion perception using dynamical stochastic textures J Vacher, AI Meso, LU Perrinet, G Peyré Neural computation 30 (12), 3355-3392, 2018 | 10 | 2018 |
Visual motion gradient sensitivity shows scale invariant spatial frequency and speed tuning properties AI Meso, RF Hess Vision research 50 (15), 1475-1485, 2010 | 10 | 2010 |
Dynamic resolution of ambiguity during tri-stable motion perception AI Meso, GS Masson Vision research 107, 113-123, 2015 | 8 | 2015 |
Towards an understanding of the roles of visual areas MT and MST in computing speed AI Meso, C Simoncini Frontiers in computational neuroscience 8, 92, 2014 | 7 | 2014 |
The relative contribution of executive functions and aging on attentional control during road crossing VI Nicholls, JM Wiener, AI Meso, S Miellet Frontiers in psychology 13, 912446, 2022 | 6 | 2022 |
Orientation gradient detection exhibits variable coupling between first-and second-stage filtering mechanisms AI Meso, RF Hess JOSA A 28 (8), 1721-1731, 2011 | 6 | 2011 |
Evidence of inverted gravity‐driven variation in predictive sensorimotor function AI Meso, RL De Vai, A Mahabeer, PJ Hills European Journal of Neuroscience 52 (12), 4803-4823, 2020 | 5 | 2020 |
Scene regularity interacts with individual biases to modulate perceptual stability Q Li, AI Meso, NK Logothetis, GA Keliris Frontiers in neuroscience 13, 523, 2019 | 5 | 2019 |
Eye Tracking: A Comprehensive Guide to Methods and Measures, Vision Rehabilitation: Multidisciplinary Care of the Patient following Brain Injury AI Meso, K Fletcher, JJS Barton Perception 41 (10), 1286-1288, 2012 | 4 | 2012 |
Speed estimation for visual tracking emerges dynamically from nonlinear frequency interactions AI Meso, N Gekas, P Mamassian, GS Masson Eneuro 9 (3), 2022 | 3 | 2022 |
Contour inflections are adaptable features J Bell, S Sampasivam, DP McGovern, AI Meso Journal of Vision 14 (7), 2-2, 2014 | 3 | 2014 |