Ulrik Beierholm

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Zhu H, Beierholm U, Shams L. (2024) BCI Toolbox: An open-source python package for the Bayesian causal inference model. Plos Computational Biology. 20: e1011791
Zhu H, Beierholm U, Shams L. (2024) The overlooked role of unisensory precision in multisensory research. Current Biology : Cb. 34: R229-R231
Aston S, Beierholm U, Nardini M. (2022) Newly learned novel cues to location are combined with familiar cues but not always with each other. Journal of Experimental Psychology. Human Perception and Performance
Shams L, Beierholm U. (2022) Bayesian causal inference: A unifying neuroscience theory. Neuroscience and Biobehavioral Reviews. 137: 104619
Aston S, Negen J, Nardini M, et al. (2021) Central tendency biases must be accounted for to consistently capture Bayesian cue combination in continuous response data. Behavior Research Methods
Beierholm U, Rohe T, Ferrari A, et al. (2020) Using the past to estimate sensory uncertainty. Elife. 9
Wedge-Roberts R, Aston S, Beierholm U, et al. (2020) Specular highlights improve color constancy when other cues are weakened. Journal of Vision. 20: 4
Kiryakova RK, Aston S, Beierholm UR, et al. (2020) Bayesian transfer in a complex spatial localization task. Journal of Vision. 20: 17
Jones SA, Beierholm U, Meijer D, et al. (2019) Older adults sacrifice response speed to preserve multisensory integration performance. Neurobiology of Aging. 84: 148-157
Ursino M, Cuppini C, Magosso E, et al. (2019) Explaining the Effect of Likelihood Manipulation and Prior Through a Neural Network of the Audiovisual Perception of Space. Multisensory Research. 32: 111-144