Developmental Changes in Natural Viewing Behavior: Bottom-Up and Top-Down Differences between Children, Young Adults and Older Adults

Abstract

Despite the growing interest in fixation selection under natural conditions, there is a major gap in the literature concerning its developmental aspects. Early in life, bottom-up processes, such as local image feature - color, luminance contrast etc. - guided viewing, might be prominent but later overshadowed by more top-down processing. Moreover, with decline in visual functioning in old age, bottom-up processing is known to suffer. Here we recorded eye movements of 7- to 9-year-old children, 19- to 27-year-old adults, and older adults above 72 years of age while they viewed natural and complex images before performing a patch-recognition task. Task performance displayed the classical inverted U-shape, with young adults outperforming the other age groups. Fixation discrimination performance of local feature values dropped with age. Whereas children displayed the highest feature values at fixated points, suggesting a bottom-up mechanism, older adult viewing behavior was less feature-dependent, reminiscent of a top-down strategy. Importantly, we observed a double dissociation between children and elderly regarding the effects of active viewing on feature-related viewing: Explorativeness correlated with feature-related viewing negatively in young age, and positively in older adults. The results indicate that, with age, bottom-up fixation selection loses strength and/or the role of top-down processes becomes more important. Older adults who increase their feature-related viewing by being more explorative make use of this low-level information and perform better in the task. The present study thus reveals an important developmental change in natural and task-guided viewing.

Keywords: age differences; development; eye movements; natural scenes; overt attention.

Figure 1

Stimuli and methods. (A–D) Representative examples from the naturals, fractals, manmades, and the pinks categories, respectively. (E) The fixation map of the above presented naturals image generated by taking young adult fixations. (F) Luminance contrast map of the above presented fractals image. (G) The intrinsic dimensionality map of the above presented manmades image. Please note that the absolute values of different features or fixation probabilities do not matter in the information theoretical analyses employed in the paper. As such, we intentionally refrain from providing colorbars for the figures. (H) The flow of a trial. Trials began with the fixation of the cross, followed by the 5 s-long presentation of one image. After that, a circular image patch was shown and subjects indicated whether the patch belonged to the image that was just shown. The patch belonged to the image with 0.5 probability, or to another image in the same category with the same probability. As soon as the subject answered via key press, the next trial was initiated.

Figure 2

Performance in the delayed pattern-matching task. (A) Category-specific performance. In the upper panel, for each image and age group the percentage correct was computed separately, and then the mean over age was taken. Circles show category medians, and error bars denote 95% confidence intervals (CIs). The branching lines connect significantly different (p < 0.05) categories and p-values are shown next to the branches, down to p = 0.001. The very low pinks performance is striking. Lower panel shows category-specific false alarm (FA) rate. All conventions are identical to the upper panel. (B) Age-specific performance excluding the pinks category. In the upper plot, for each subject and image category, the percentage correct was computed separately, and then the mean over naturals, fractals and manmades was taken. Other conventions and statistical analyses are identical to panel (A). Lower panel shows age-specific FA rate. Note the agreement between percentage correct and FA rates both for category and age group analyses. Overall, pinks are associated with lower performance, and age differences reveal the classical U-shape function with young adults outperforming both children and older adults.

Figure 3

Basic fixation characteristics. (A) Category-specific explorativeness. Explorativeness is based on the information theoretical entropy measure and quantifies how actively a participant viewed the images. For each image and age group, explorativeness was computed separately, and then the mean over age was taken. Circles show category medians, and error bars denote 95% confidence intervals (CIs). The branching lines connect significantly different (p < 0.05) categories determined by permutation sampling and exact p-values down to p = 0.001 can be seen next to the branches. (B) Age-specific explorativeness. For each subject and all categories but pinks, explorativeness was computed separately, and then the mean over category was taken. As all fixations in one category were pooled, the explorativeness is overall higher. Other conventions and statistical analyses are identical to panel (A). (C) Median number of fixations for each age group. Category averaging and other conventions are identical to panel (B). (D) Median distance between successive fixations for each age group. Category averaging and other conventions are identical to panels (B,C). Note that the explorativeness of older adults is similar to other age groups, despite the greater number of fixations displayed by the former age group. This result can be explained by the relatively shorter saccades performed by older adults.

Figure 4

Linear regression analysis of explorativeness and percentage correct. For each age group and category separately, we removed outliers (3 older adults in naturals, and 2 older adults manmades) and computed linear regressions for subject-specific explorativeness and percentage correct values. Inside the panels, each marker corresponds to one subject and the regression line is shown with the age color code. As can be seen, in three out of four categories (solid lines for p < 0.05 and the dashed line for p = 0.06), older adults displayed positive correlations (R² is given under the category label). Rectangular insets display the equations of the fits with 95% CIs inside square brackets. Please note that due to the entropy correction involved in the computation of explorativeness, some values might exceed 100 (see Materials and Methods).

Figure 5

Age comparison of local image feature-related viewing. In all panels, each marker cross corresponds to one feature AUC_P (see Materials and Methods). The data is plotted such that young adults’ feature AUCs are compared to children's AUCs on the left, and to older adults’ AUCs on the right. That is, the ordinates on the two sides of the same panel are identical and report the young adult data. Please note that the origins are panel specific, and the x-axis is symmetric on the two sides of the origin. Dashed lines denote the diagonals, and the dotted lines the AUC value of 0.50 (no discrimination). Note the very low and smaller than 0.50 AUC values of naturals and pinks, respectively. The features used provided better discriminability for fractals and manmades, and in those cases the AUCs decreased from children to young adults and from them to older adults, as shown by data lying below the diagonal on the left and above the diagonal on the right.

Figure 6

One average feature (LC) and the best feature (ID) compared to inter-observer (IO) saliency. For each age group separately, image-specific AUC (AUC_I) values were pooled from the fractals and manmades categories. Markers show for two features and the IO saliency the medians of those distributions together with the 95% CIs. Even though there was considerable overlap in these conservative CIs, all AUCs drop with age, replicating the category-pooled analysis.

Figure 7

Saccade size differences on feature-related viewing. After age-specific median splits on saccade size, AUC for each feature was computed for fractals and manmades once for fixations at the end of short saccades (ordinates) and once for fixations following longer saccades (abscissae). The markers in the dashed ellipse show the same analysis on IO saliency and reveal the same pattern. Empty symbols denote age, category, feature combinations, and filled symbols denote the averages over features together with 95% CIs. Accumulation of the values above the diagonal reveals that feature values were relatively higher at the end of shorter saccades, which holds for all age groups.

Figure 8

Age differences in correlations between explorativeness and feature AUCs. For each feature and category combination (only fractals and manmades), subject-specific AUCs (AUC_S) were correlated with subjects’ explorativeness. Since there were 12 features and 2 categories of interest, the frequency histogram displays the distribution of 24 correlation coefficients for each age group. The triangles above show age group medians. Note the predominantly negative correlations of children, the positive correlations of older adults and the presence of roughly equal amounts of positive and negative correlations for young adults.