Showing 1 – 20 of 34
SORT: Best Match Most Recent Oldest
VIEW: Basic | Expanded
  • Journal of Vision >
  • Journal of Vision >
    Figure 7. Examples of the subset search task for the “both segmentable” ( top row ) and “none segmentable” conditions. In each trial, observers have to look for an odd orientation among red (or reddish ) lines . In each trial shown as a separate array on the figure, the direction of correlation between color and orientation could randomly change that led to unpredictable changes in orientations between targets and distractors within the target color subset. The lines are slightly enlarged for illustrative purposes.
  • Journal of Vision >
    Figure 10. Reaction time and error rate as a function of set size and task in Experiment 4 . Error bars denote the SEM, with between-subject variance removed in accordance with the Cousineau (2005) method.
  • Journal of Vision >
    Figure 13. Reaction time and error rate as a function of set size and segmentability in Experiment 5 . Error bars denote the SEM, with between-subject variance removed in accordance with the Cousineau (2005) method.
  • Journal of Vision >
    Figure 3. Reaction time and error rate as a function of set size and segmentability in Experiment 1 . Error bars denote the SEM, with between-subject variance removed in accordance with the Cousineau (2005) method.
  • Journal of Vision >
    Figure 6. A Guided search ( Wolfe, 1994 ; Wolfe et al., 1989 ) account for the absence of the effect of segmentability on conjunction search in Experiments 1 and 2 . The proposed mechanism is based on the parallel use of top-down activation patterns from color (“redness”) and orientation (“steepness”) feature map. In (A), highly segmentable colors and orientations both provide distinct patterns of strongly activated and weakly activated locations, and their overlap leads to an attentional priority map with many moderately activated locations and one highly activated location corresponding to the target. In (B), non-segmentable colors and orientations both provide fuzzy patterns of top-down activation, but their overlap looks similar to the pattern in (A). Colors on Feature activation maps represent hypothetical top-down activation weighted by the similarity of a feature at a given location with the target feature. Each location on the Attention priority map is colored as the average of activation values in corresponding locations of the two Feature activation maps.
  • Journal of Vision >
    Figure 9. Examples of four search tasks in Experiment 4 for target present trials. Target = white vertical line (only white for color search, only vertical for orientation search), set size = 17. The lines are slightly enlarged for illustrative purposes.
  • Journal of Vision >
    Figure 12. Examples of four segmentability conditions in Experiment 5 for target present trials. Target = red steep line. The lines are slightly enlarged for illustrative purposes. ss, set size.
  • Journal of Vision >
    Figure 2. Examples of four segmentability conditions in Experiment 1 for target present trials. Target = red steep line , set size = 17. The lines are slightly enlarged for illustrative purposes. The histograms below show frequency distributions of color values and orientation values among distractors.
  • Journal of Vision >
    Figure 5. Reaction time and error rate as a function of set size and segmentability in Experiment 2 . Error bars denote the SEM, with between-subject variance removed in accordance with the Cousineau (2005) method.
  • Journal of Vision >
    Figure 8. Reaction time and error rate as a function of set size and segmentability in Experiment 3 . Error bars denote the SEM, with between-subject variance removed in accordance with the Cousineau (2005) method.