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iMap: a novel method for statistical fixation mapping of eye movement data

机译:iMap:一种用于眼动数据的统计注视映射的新颖方法

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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 (www.unifr.ch/psycho/ibmlab/).
机译:眼动数据分析通常基于给定感兴趣区域(ROI)中扫视和注视(及其特征)的发生概率。在本文中,我们介绍了一种基于功能磁共振成像中使用的方法启发而计算出眼睛运动的统计注视图的替代方法-iMap。重要的是,iMap不需要将实验图像先验分割成ROI。使用iMap,首先通过卷积高斯核对固定数据进行平滑处理,以生成三维固定图。此过程体现了眼动仪的准确性,但是高斯内核也可以灵活设置以表示敏锐度或注意力限制。此外,iMap生成的平滑后的注视数据符合稳健的统计随机场理论(RFT)方法的假设,此方法随后用于评估重要的注视点和三维注视图之间的差异。 RFT校正由构成数字图像的多个像素生成的多个统计比较。为了说明iMap的处理步骤,我们提供了来自面部,视觉场景和内存处理的真实眼睛运动数据的示例分析。 iMap MATLAB工具箱是可编辑的,可以免费在线下载(www.unifr.ch/psycho/ibmlab/)。

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