Visual event-related potentials (ERPs) produced by a stimulus are thought to reflect either an increase of synchronized activity or a phase realignment of ongoing oscillatory activity, with both mechanisms sharing the assumption that ERPs are independent of the current state of the brain at the time of stimulation. In natural viewing, however, visual inputs occur one after another at specific subject-paced intervals through unconstrained eye movements. We conjecture that during natural viewing, ERPs generated after each fixation are better explained by a superposition of ongoing oscillatory activity related to the processing of previous fixations, with new activity elicited by the visual input at the current fixation. We examined the electroencephalography (EEG) signals that occur in humans at the onset of each visual fixation, both while subjects freely viewed natural scenes and while they viewed a black or gray background. We found that the fixation ERPs show visual components that are absent when subjects move their eyes on a homogeneous gray or black screen. Single-trial EEG signals that comprise the ERP are predicted more accurately by a model of superposition than by either phase resetting or the addition of evoked responses and stimulus-independent noise. The superposition of ongoing oscillatory activity and the visually evoked response results in a modification of the ongoing oscillation phase. The results presented suggest that the observed EEG signals reflect changes occurring in a common neuronal substrate rather than a simple summation at the scalp of signals from independent sources.

How people look at visual information reveals fundamental information about themselves, their interests and their state of mind. While previous visual attention models output static 2D saliency maps, saccadic models aim to predict not only where observers look at but also how they move their eyes to explore the scene. In this paper, we demonstrate that saccadic models are a flexible framework that can be tailored to emulate observer's viewing tendencies. More specifically, we use fixation data from 101 observers split into five age groups (adults, 8-10 y.o., 6-8 y.o., 4-6 y.o., and 2 y.o.) to train our saccadic model for different stages of the development of human visual system. We show that the joint distribution of saccade amplitude and orientation is a visual signature specific to each age group, and can be used to generate age-dependent scan paths. Our age-dependent saccadic model does not only output human-like, age-specific visual scan paths, but also significantly outperforms other state-of-the-art saliency models. We demonstrate that the computational modeling of visual attention, through the use of saccadic model, can be efficiently adapted to emulate the gaze behavior of a specific group of observers.

Recently, two attentional modes have been associated with specific eye movement patterns during scene processing. Ambient mode, characterized by short fixations and long saccades during early scene inspection, is associated with localization of objects. Focal mode, characterized by longer fixations, is associated with more detailed object feature processing during later inspection phase. The aim of the present study was to investigate the development of these attentional modes. More specifically, we examined whether indications of ambient and focal attention modes are similar in infants and adults. Therefore, we measured eye movements in 3- to 12-months-old infants while exploring visual scenes. Our results show that both adults and 12-month-olds had shorter fixation durations within the first 1.5 s of scene viewing compared with later time phases (>2.5 s); indicating that there was a transition from ambient to focal processing during image inspection. In younger infants, fixation durations between two viewing phases did not differ. Our results suggest that at the end of the first year of life, infants have developed an adult-like scene viewing behavior. The evidence for the existence of distinct attentional processing mechanisms during early infancy furthermore underlines the importance of the concept of the two modes.

Knowledge of the human visual system helps to develop better computational models of visual attention. State-of-the-art models have been developed to mimic the visual attention system of young adults that, however, largely ignore the variations that occur with age. In this paper, we investigated how visual scene processing changes with age and we propose an age-adapted framework that helps to develop a computational model that can predict saliency across different age groups. Our analysis uncovers how the explorativeness of an observer varies with age, how well saliency maps of an age group agree with fixation points of observers from the same or different age groups, and how age influences the center bias tendency. We analyzed the eye movement behavior of 82 observers belonging to four age groups while they explored visual scenes. Explorative- ness was quantified in terms of the entropy of a saliency map, and area under the curve (AUC) metrics was used to quantify the agreement analysis and the center bias tendency. Analysis results were used to develop age adapted saliency models. Our results suggest that the proposed age-adapted saliency model outperforms existing saliency models in predicting the regions of interest across age groups.