iMap: a novel method for statistical fixation mapping of eye movement data |
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Authors: | Caldara Roberto Miellet Sébastien |
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Institution: | Department of Psychology, University of Fribourg, Faucigny 2, 1700 Fribourg, Switzerland. roberto.caldara@unifr.ch |
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Abstract: | Eye movement data analyses are commonly based on the probability of occurrence of saccades and fixations (and their characteristics)
in given regions of interest (ROIs). In this article, we introduce an alternative method for computing statistical fixation
maps of eye movements—iMap—based on an approach inspired by methods used in functional magnetic resonance imaging. Importantly, iMap does not require the a priori segmentation of the experimental images into ROIs. With iMap, fixation data are first smoothed by convolving Gaussian kernels to generate three-dimensional fixation maps. This procedure
embodies eyetracker accuracy, but the Gaussian kernel can also be flexibly set to represent acuity or attentional constraints.
In addition, the smoothed fixation data generated by iMap conform to the assumptions of the robust statistical random field theory (RFT) approach, which is applied thereafter to
assess significant fixation spots and differences across the three-dimensional fixation maps. The RFT corrects for the multiple
statistical comparisons generated by the numerous pixels constituting the digital images. To illustrate the processing steps
of iMap, we provide sample analyses of real eye movement data from face, visual scene, and memory processing. The iMap MATLAB toolbox is editable and freely available for download online (). |
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