Temporal evolution of the central fixation bias 33 Figure 10 . Mean information gain in bit per fixation for the different models for the Fixation 2 to 10. Fixation 1 is not simulated by the models and set to a likelihood of 1. Higher values of information gain mean that empirically measured fixations are more likely in the corresponding model to occur. Experiment 1 Experiment 2 Experiment 3 Experiment 4 2 4 6 8 10 2 4 6 8 10 2 4 6 8 10 2 4 6 8 10 0 1 2 ordinal fixation number within trial infor mation gain [bit/fix] Model Density Model Gauss Model Center Bias SceneW alk SceneW alkStar tMap makes the same predictions from the third fixation on. Finally, the Gaussian model performed equally well as the SceneWalk models in terms of information gain. Thus we confirm earlier findings that the restriction to nearby saccade targets is the most important influence to include into a model. However, as seen in the previous section, this is not sufficient to explain the DTC over time. Across experiments and models, the likelihood declined over time. This was due to the larger variability of later fixation locations between participants. Model simulations showed that adjusting the SceneWalk model with an initial map can reasonably explain the central fixation bias. While the information gain of the Gaussian model was similar, the SceneWalk StartMap model was the only model that generated an Discussion