TY  - JOUR
A1  - Schwetlick, Lisa
A1  - Rothkegel, Lars Oliver Martin
A1  - Trukenbrod, Hans Arne
A1  - Engbert, Ralf
T1  - Modeling the effects of perisaccadic attention on gaze statistics during scene viewing
JF  - Communications biology
N2  - Lisa Schwetlick et al. present a computational model linking visual scan path generation in scene viewing to physiological and experimental work on perisaccadic covert attention, the act of attending to an object visually without obviously moving the eyes toward it. They find that integrating covert attention into predictive models of visual scan paths greatly improves the model's agreement with experimental data. <br /> How we perceive a visual scene depends critically on the selection of gaze positions. For this selection process, visual attention is known to play a key role in two ways. First, image-features attract visual attention, a fact that is captured well by time-independent fixation models. Second, millisecond-level attentional dynamics around the time of saccade drives our gaze from one position to the next. These two related research areas on attention are typically perceived as separate, both theoretically and experimentally. Here we link the two research areas by demonstrating that perisaccadic attentional dynamics improve predictions on scan path statistics. In a mathematical model, we integrated perisaccadic covert attention with dynamic scan path generation. Our model reproduces saccade amplitude distributions, angular statistics, intersaccadic turning angles, and their impact on fixation durations as well as inter-individual differences using Bayesian inference. Therefore, our result lend support to the relevance of perisaccadic attention to gaze statistics.
KW  - Computational models
KW  - Human behaviour
KW  - Visual system
Y1  - 2020
U6  - https://doi.org/10.1038/s42003-020-01429-8
SN  - 2399-3642
VL  - 3
IS  - 1
PB  - Springer Nature
CY  - London
ER  -