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George Tomou, Xiaogang Yan, J. Crawford; Transsacadic Integration of Multiple Objects and The Influence of Stable Allocentric Cue. Journal of Vision 2018;18(10):1290. doi: https://doi.org/10.1167/18.10.1290.
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Transsaccadic integration is the ability to retain and synthesize visual information between different stable fixations. In order to do this, the brain must be able to retain and update object locations and features despite relative changes in retinal location produced by saccades several times per second. It is known that humans are able to retain several objects across saccades based on egocentric mechanisms, but it is not known what role allocentric landmarks play in this process. In order to test this, we compared performance in a transsaccadic integration task (e.g., Prime et al. Exp. Brain Res. 2007) with or without the presence of an allocentric landmark. 1-7 Gabor patches with pseudorandom orientations were presented on a frontal screen while participants fixated a randomized fixation cross. Following a visual mask, participants were required to saccade to a new location and were asked to identify whether a new Gabor patch presented at one of the same locations was rotated clockwise or counterclockwise from the original orientation. In 50% of the trials, an allocentric landmark (a stable cross positioned pseudorandomly within the stimulus array and extending across the screen) was presented throughout the trial. Using generalized linear mixed modeling (GLMM), results from 9 participants confirmed the expected result that in the absence of the landmark, performance decreased significantly (from a baseline of ~90% correct) as the set size increased (p < .001). More importantly, the presence of the landmark ameliorated this decrease in performance, providing significantly better performance for set sizes of 3 and higher (p = .029). These preliminary results suggest that egocentric and allocentric mechanisms may combine to provide optimal performance in transsaccadic integration of multiple objects.
Meeting abstract presented at VSS 2018
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