Modeling the effects of perisaccadic attention on gaze statistics during scene viewing

Autor: Lars O. M. Rothkegel, Hans A. Trukenbrod, Lisa Schwetlick, Ralf Engbert
Rok vydání: 2020
Předmět:
Department Psychologie
0301 basic medicine
Computer science
Research areas
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Medicine (miscellaneous)
Fixation
Ocular
Bayesian inference
Models
Biological
Article
General Biochemistry
Genetics and Molecular Biology
bepress|Life Sciences|Neuroscience and Neurobiology
03 medical and health sciences
0302 clinical medicine
ddc:150
Human behaviour
Statistics
Saccades
Computational models
Humans
Computer Simulation
Experimental work
bepress|Life Sciences|Neuroscience and Neurobiology|Cognitive Neuroscience
Models
Statistical
Dynamic Scan
PsyArXiv|Social and Behavioral Sciences|Cognitive Psychology|Attention
Gaze
bepress|Social and Behavioral Sciences|Psychology|Cognitive Psychology
PsyArXiv|Neuroscience|Cognitive Neuroscience
PsyArXiv|Social and Behavioral Sciences
030104 developmental biology
PsyArXiv|Neuroscience
Covert
Saccade
Fixation (visual)
bepress|Social and Behavioral Sciences
PsyArXiv|Social and Behavioral Sciences|Cognitive Psychology
Visual system
General Agricultural and Biological Sciences
030217 neurology & neurosurgery
Zdroj: Communications Biology
ISSN: 2399-3642
DOI: 10.1038/s42003-020-01429-8
Popis: 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.
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.
Databáze: OpenAIRE
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