@article{EngbertTrukenbrodBarthelmeetal.2015,
  author    = {Engbert, Ralf and Trukenbrod, Hans Arne and Barthelme, Simon and Wichmann, Felix A.},
  title     = {Spatial statistics and attentional dynamics in scene viewing},
  series = {Journal of vision},
  volume    = {15},
  journal   = {Journal of vision},
  number    = {1},
  publisher = {Association for Research in Vision and Opthalmology},
  address   = {Rockville},
  issn      = {1534-7362},
  doi       = {10.1167/15.1.14},
  pages     = {17},
  year      = {2015},
  abstract  = {In humans and in foveated animals visual acuity is highly concentrated at the center of gaze, so that choosing where to look next is an important example of online, rapid decision-making. Computational neuroscientists have developed biologically-inspired models of visual attention, termed saliency maps, which successfully predict where people fixate on average. Using point process theory for spatial statistics, we show that scanpaths contain, however, important statistical structure, such as spatial clustering on top of distributions of gaze positions. Here, we develop a dynamical model of saccadic selection that accurately predicts the distribution of gaze positions as well as spatial clustering along individual scanpaths. Our model relies on activation dynamics via spatially-limited (foveated) access to saliency information, and, second, a leaky memory process controlling the re-inspection of target regions. This theoretical framework models a form of context-dependent decision-making, linking neural dynamics of attention to behavioral gaze data.},
  language  = {en}
}
@article{BarthelmeTrukenbrodEngbertetal.2013,
  author    = {Barthelme, Simon and Trukenbrod, Hans Arne and Engbert, Ralf and Wichmann, Felix A.},
  title     = {Modeling fixation locations using spatial point processes},
  series = {Journal of vision},
  volume    = {13},
  journal   = {Journal of vision},
  number    = {12},
  publisher = {Association for Research in Vision and Opthalmology},
  address   = {Rockville},
  issn      = {1534-7362},
  doi       = {10.1167/13.12.1},
  pages     = {34},
  year      = {2013},
  abstract  = {Whenever eye movements are measured, a central part of the analysis has to do with where subjects fixate and why they fixated where they fixated. To a first approximation, a set of fixations can be viewed as a set of points in space; this implies that fixations are spatial data and that the analysis of fixation locations can be beneficially thought of as a spatial statistics problem. We argue that thinking of fixation locations as arising from point processes is a very fruitful framework for eye-movement data, helping turn qualitative questions into quantitative ones. We provide a tutorial introduction to some of the main ideas of the field of spatial statistics, focusing especially on spatial Poisson processes. We show how point processes help relate image properties to fixation locations. In particular we show how point processes naturally express the idea that image features' predictability for fixations may vary from one image to another. We review other methods of analysis used in the literature, show how they relate to point process theory, and argue that thinking in terms of point processes substantially extends the range of analyses that can be performed and clarify their interpretation.},
  language  = {en}
}