| Visual categorization of natural movies by rats K Vinken, B Vermaercke, HPO de Beeck Journal of Neuroscience 34 (32), 10645-10658, 2014 | 73 | 2014 |
| Recent visual experience shapes visual processing in rats through stimulus-specific adaptation and response enhancement K Vinken, R Vogels, HO de Beeck Current Biology 27 (6), 914-919, 2017 | 60 | 2017 |
| Face repetition probability does not affect repetition suppression in macaque inferotemporal cortex K Vinken, HPO de Beeck, R Vogels Journal of Neuroscience 38 (34), 7492-7504, 2018 | 45 | 2018 |
| Neural representations of natural and scrambled movies progressively change from rat striate to temporal cortex K Vinken, G Van den Bergh, B Vermaercke, HP Op de Beeck Cerebral Cortex 26 (7), 3310-3322, 2016 | 36 | 2016 |
| Distinct and simultaneously active plasticity mechanisms in mouse hippocampus during different phases of Morris water maze training A Laeremans, V Sabanov, T Ahmed, J Nys, B Van de Plas, K Vinken, ... Brain Structure and Function 220 (3), 1273-1290, 2014 | 26 | 2014 |
| Frivolous units: Wider networks are not really that wide S Casper, X Boix, V D'Amario, L Guo, M Schrimpf, K Vinken, G Kreiman Proceedings of the AAAI Conference on Artificial Intelligence 35 (8), 6921-6929, 2021 | 22* | 2021 |
| Adaptation can explain evidence for encoding of probabilistic information in macaque inferior temporal cortex K Vinken, R Vogels Current Biology 27 (22), R1210-R1212, 2017 | 20 | 2017 |
| Temporal stability of stimulus representation increases along rodent visual cortical hierarchies E Piasini, L Soltuzu, P Muratore, R Caramellino, K Vinken, H Op de Beeck, ... Nature communications 12 (1), 4448, 2021 | 19 | 2021 |
| Representations of regular and irregular shapes by deep Convolutional Neural Networks, monkey inferotemporal neurons and human judgments I Kalfas, K Vinken, R Vogels PLOS Computational Biology 14 (10), e1006557, 2018 | 19 | 2018 |
| Incorporating intrinsic suppression in deep neural networks captures dynamics of adaptation in neurophysiology and perception K Vinken, X Boix, G Kreiman Science Advances 6 (42), eabd4205, 2020 | 14 | 2020 |
| The neural code for “face cells” is not face-specific K Vinken, JS Prince, T Konkle, MS Livingstone Science Advances 9 (35), eadg1736, 2023 | 9 | 2023 |
| Using deep neural networks to evaluate object vision tasks in rats K Vinken, H Op de Beeck PLoS computational biology 17 (3), e1008714, 2021 | 9 | 2021 |
| Op de Beeck HP, Vogels R. 2018 K Vinken Face repetition probability does not affect repetition suppression in …, 0 | 7 | |
| Deep neural networks point to mid-level complexity of rodent object vision K Vinken, HO de Beeck bioRxiv, 2020.02. 08.940189, 2020 | 6 | 2020 |
| Op de Beeck H, Balasubramanian V, Zoccolan D. 2021. Temporal stability of stimulus representation increases along rodent visual cortical hierarchies E Piasini, L Soltuzu, P Muratore, R Caramellino, K Vinken Nat Commun 12, 4448, 0 | 6 | |
| A behavioral face preference deficit in a monkey with an incomplete face patch system K Vinken, R Vogels Neuroimage 189, 415-424, 2019 | 5 | 2019 |
| Intrinsic dynamics enhance temporal stability of stimulus representation along rodent visual cortical hierarchies E Piasini, L Soltuzu, P Muratore, R Caramellino, K Vinken, HO de Beeck, ... bioRxiv, 822130, 2019 | 2 | 2019 |
| Incorporating neuronal fatigue in deep neural networks captures dynamics of adaptation in neurophysiology and perception K Vinken, X Boix, G Kreiman | 2* | 2019 |
| The importance of contrast features in rat vision AE Schnell, K Vinken, HO de Beeck Scientific Reports 13 (1), 459, 2023 | 1 | 2023 |
| Do computational models of vision need shape-based representations? Evidence from an individual with intriguing visual perceptions M Armendariz, W Xiao, K Vinken, G Kreiman Cognitive Neuropsychology 39 (1-2), 75-77, 2022 | 1 | 2022 |
Hans Op de BeeckProfessor of Brain & Cognition, University of Leuven (KU Leuven)Verified email at kuleuven.be
