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Armendariz, M., Xiao, W., Vinken, K. & Kreiman, G. Do computational models of vision need shape-based representations? Evidence from an individual with intriguing visual perceptions. Cognitive Neuropsychology 1 - 3 (2022). doi:10.1080/02643294.2022.2041588
Sikarwar, A. & Kreiman, G. On the Efficacy of Co-Attention Transformer Layers in Visual Question Answering. arXiv (2022). doi:10.48550/arXiv.2201.03965PDF icon On_the_Efficacy_of_Co-Attention_Transformer_Layers.pdf (35.54 MB)
Dellaferrera, G. & Kreiman, G. Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass. Proceedings of the 39th International Conference on Machine Learning, PMLR 162, 4937-4955 (2022).PDF icon dellaferrera22a.pdf (909.91 KB)
Bardon, A., Xiao, W., Ponce, C. R., Livingstone, M. S. & Kreiman, G. Face neurons encode nonsemantic features. Proceedings of the National Academy of Sciences 119, (2022).
Zhang, M. et al. Look twice: A generalist computational model predicts return fixations across tasks and species. PLOS Computational Biology 18, e1010654 (2022).PDF icon journal.pcbi_.1010654.pdf (4.51 MB)
Zheng, J. et al. Neurons detect cognitive boundaries to structure episodic memories in humans. Nature Neuroscience 25, 358 - 368 (2022).
Casper, S., Nadeau, M. & Kreiman, G. One thing to fool them all: generating interpretable, universal, and physically-realizable adversarial features. arXiv (2022). doi:10.48550/arXiv.2110.03605PDF icon 2110.03605.pdf (6.7 MB)
Shaham, N., Chandra, J., Kreiman, G. & Sompolinsky, H. Stochastic consolidation of lifelong memoryAbstract. Scientific Reports 12, (2022).PDF icon s41598-022-16407-9.pdf (2.54 MB)
Xiao, Y. et al. Task-specific neural processes underlying conflict resolution during cognitive control. BioRxiv (2022). doi:10.1101/2022.01.16.476535 PDF icon 2022.01.16.476535v1.full_.pdf (22.96 MB)
Zhang, M. & Kreiman, G. Beauty is in the eye of the machine. Nature Human Behaviour 5, 675 - 676 (2021).
Kreiman, G. Biological and Computer Vision. (Cambridge University Press, 2021). doi:10.1017/9781108649995
Zheng, J. et al. Cognitive boundary signals in the human medial temporal lobe shape episodic memory representation. bioRxiv (2021).
Casper, S. et al. Frivolous Units: Wider Networks Are Not Really That Wide. AAAI 2021 (2021). at <>PDF icon 1912.04783.pdf (6.69 MB)
Zhang, M., Badkundri, R., Talbot, M. B., Zawar, R. & Kreiman, G. Hypothesis-driven Online Video Stream Learning with Augmented Memory. arXiv (2021). doi:10.48550/arXiv.2104.02206PDF icon 2104.02206.pdf (2.25 MB)
Weisholtz, D. S. et al. Localized task-invariant emotional valence encoding revealed by intracranial recordingsAbstract. Social Cognitive and Affective Neuroscience (2021). doi:10.1093/scan/nsab134
Wang, J., Tao, A., Anderson, W. S., Madsen, J. R. & Kreiman, G. Mesoscopic physiological interactions in the human brain reveal small-world properties. Cell Reports 36, 109585 (2021).
Gupta, S. Kant, Zhang, M., WU, C. H. I. A. - C. H. I. E. N., Wolfe, J. & Kreiman, G. Visual Search Asymmetry: Deep Nets and Humans Share Similar Inherent Biases. NeurIPS 2021 (2021). at <>PDF icon gk8091.pdf (2.47 MB)
Bomatter, P. et al. When Pigs Fly: Contextual Reasoning in Synthetic and Natural Scenes. International Conference on Computer Vision (ICCV) (2021). doi:10.1109/iccv48922.2021.00032PDF icon Bomatter_When_Pigs_Fly_Contextual_Reasoning_in_Synthetic_and_Natural_Scenes_ICCV_2021_paper.pdf (3.24 MB)
Kreiman, G. & Serre, T. Beyond the feedforward sweep: feedback computations in the visual cortex. Annals of the New York Academy of Sciences 1464, 222 - 241 (2020).
Kreiman, G. & Serre, T. Beyond the feedforward sweep: feedback computations in the visual cortex. Ann. N.Y. Acad. Sci. | Special Issue: The Year in Cognitive Neuroscience 1464, 222-241 (2020).PDF icon gk7812.pdf (1.93 MB)