Abstract

R. Carmi, P. Tseng, I. G. M. Cameron, D. P. Munoz, L. Itti, The impact of maturation and aging on mechanisms of attentional selection, In: Proc. Vision Science Society Annual Meeting (VSS07), May 2007. (Cited by 1)

Abstract: How do mechanisms of attentional selection change as people mature and age? To investigate this question, we tracked the eyes of 3 groups of human observers (children: 10-13, adults: 20-28, and elderly: 69-73) as they watched MTV-style video clips (30 s each) constructed from unrelated shots of natural scenes (2-4 s each). It was previously shown that jump cuts - abrupt transitions between shots - lead to stereotypical changes in the balance between bottom-up and top-down influences on attentional selection (http://journalofvision.org/6/9/4). Specifically, the impact of bottom-up influences peaks shortly after jump cuts, followed by monotonic decreases for up to 2.5 s. Here we investigated the effects of maturation and aging on the balance between bottom-up and top-down influences. We analyzed the input video clips with a bottom-up computer model of attentional selection, and probed the impact of bottom-up influences by quantifying the accuracy of the model in predicting saccade targets (>40,000 in total). We found that the overall impact of bottom-up influences increased monotonically as a function of age (>10 percent magnitude difference between adjacent age groups, p<<0.01). Temporal changes in the impact of bottom-up influences were highly conserved between the children and the adults, but differed substantially in the elderly. A straight-forward yet counter-intuitive interpretation of the results is that people become more bottom-up driven as they mature and age. Alternatively, jump cuts may affect attentional mechanisms differently in different ages, leading to more random selections by children and slower utilization of top-down information by the elderly.

Themes: Computational Modeling, Model of Bottom-Up Saliency-Based Visual Attention, Model of Top-Down Attentional Modulation, Human Eye-Tracking Research, Scene Understanding