Rothkegel et al. 40 systems (Vol. 20, pp. 241–248). Clarke, A. D., & Tatler, B. W. (2014). Deriving an appropriate baseline for describing fixation behaviour. Vision Research , 102 , 41–51. Cornelissen, F. W., Peters, E. M., & Palmer, J. (2002). The eyelink toolbox: eye tracking with matlab and the psychophysics toolbox. Behavior Research Methods , 34 (4), 613–617. Cousineau, D. (2005). Confidence intervals in within-subject designs: A simpler solution to loftus and masson’s method. Tutorials in Quantitative Methods for Psychology , 1 (1), 42–45. Efron, B., & Tibshirani, R. J. (1994). An introduction to the bootstrap . New York: Chapman and Hall. Engbert, R., & Kliegl, R. (2003). Microsaccades uncover the orientation of covert attention. Vision Research , 43 (9), 1035–1045. Engbert, R., & Mergenthaler, K. (2006). Microsaccades are triggered by low retinal image slip. Proceedings of the National Academy of Sciences , 103 (18), 7192–7197. Engbert, R., Trukenbrod, H. A., Barthelm´ e, S., & Wichmann, F. A. (2015). Spatial statistics and attentional dynamics in scene viewing. Journal of Vision , 15 (1), 14. doi: 10.1167/15.1.14 Hayhoe, M., & Ballard, D. (2005). Eye movements in natural behavior. Trends in Cognitive Sciences , 9 (4), 188–194. Henderson, J. M., Weeks Jr, P. A., & Hollingworth, A. (1999). The effects of semantic consis- tency on eye movements during complex scene viewing. Journal of Experimental Psychol- ogy: Human Perception and Performance , 25 (1), 210. Ioannidou, F., Hermens, F., Hodgson, T., et al. (2016). The centrial bias in day-to-day viewing. Journal of Eye Movement Research , 9 (6), 1–13. Itti, L., & Koch, C. (2001). Computational modelling of visual attention. Nature Reviews Neuroscience , 2 (3), 194–203. Itti, L., Koch, C., & Niebur, E. (1998). A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence , 20 (11),