Contribution of a common ability in average and variability judgments

How general is ensemble perception?

People can summarize features of groups of objects (e.g., the mean size of apples). Claims of dissociations or common mechanisms supporting such ensemble perception (EP) judgments have generally been made on the basis of correlations between pairs of tasks. These correlations can be inflated because they use the same stimuli, summary statistics and/or task format. Performance on EP tasks also correlates with that on object recognition (OR) tasks. Here, we seek evidence for a general EP ability that is also distinct from OR ability. Two-hundred participants completed three tasks that did not overlap in stimuli, summary statistic or task format. Participants performed a diversity comparison for arrays of nonsense blobs, a mean identity judgment with ensembles of Transformer toys, and the novel object memory task with novel objects (NOMT-Greeble). We hypothesized that EP contributes to the first two of these tasks, while OR contributes only to the last two. Performance on the two tasks suggested to tap an EP ability were correlated after controlling for the third task. Confirmatory factor analysis was used to test our predictions without the confound of measurement error. Correlations between factors assumed to share influence from EP or from OR were higher than that between the factors that we expect did not share these influences. The results provide the first clear evidence for a domain-general EP ability distinct from OR. We argue that understanding such a general ability will require a change in designs and analytical approaches in the study if individual differences in EP.

The Relation between Ensemble Coding of Length and Orientation Does Not Depend on Spatial Attention

Most people are good at estimating summary statistics for different features of groups of objects. For instance, people can selectively attend to different features of a group of lines and report ensemble properties such as the mean length or mean orientation and there are reliable individual differences in such ensemble judgment abilities. Our recent study found decisive evidence in support of a correlation between the errors on mean length and mean orientation judgments (r = 0.62). The present study investigates one possible mechanism for this correlation. The ability to allocate spatial attention to single items varies across individuals, and in the recent study, this variability could have contributed to both judgments because the location of lines was unpredictable. Here, we replicate this prior work with arrays of lines with fully predictable spatial locations, to lower the contribution of the ability to distribute attention effectively over all items in a display. We observed a strong positive correlation between errors on the length and orientation averaging tasks (r = 0.65). This provides evidence against individual differences in spatial attention as a common mechanism supporting mean length and orientation judgments. The present result aligns with the growing evidence for at least one ensemble-specific ability that applies across different kinds of features and stimuli.

Saccadic eye movement metrics reflect surprise and mental model updating

Two experiments investigated what eye movements can reveal about how we process surprising information and how we update mental models in dynamic and unstructured environments. Participants made saccades to visual targets presented one at a time, radially, around an invisible perimeter. Target locations were normally distributed and shifted at an unannounced point during the task. Trials following the shift were considered surprising and unexpected. These unexpected and surprising events prompted the need to update. Slower saccadic latencies were observed for surprising/unexpected events, perhaps indicative of the need to reorient attention to the unexpected target location. Longer dwell times were observed for events that signaled a change in the distribution. These data show that eye movement metrics provide a reliable indicator of mental model updating when contingencies change even in the absence of explicit change signals.

How are local orientation signals pooled?

Visual perception is capable of pooling multiple local orientation signals into a single more accurate summary orientation. However, there is still a lack of systematic inquiry into which summary statistics are implemented in that process. Here, the task was to recognize in which direction, clockwise or counter-clockwise, the mean orientation of a set of randomly distributed Gabor patches (N = 1, 2, 4, and 8) was rotated from the implicit vertical. The mean orientation discrimination accuracy did not improve with the increase of the number N of elements in proportion to the square-root-N, as could be expected if noisy internal representations were arithmetically averaged. The Proportion of Informative Elements (PIE), defined as the percentage of elements having an orientation different from the vertical, also affected the discrimination precision, violating the arithmetic averaging rules. The decrease in the orientation discrimination precision with the increase of the PIE would suggest that the orientation pooling could be more adequately described by a quadratic or higher power mean. Thus, we parameterized the averaging process for the power parameter of the generalized mean formula. The results indicate that different pooling rules in different trials may apply, for example, the arithmetic mean in some and the maximal deviation rule in others. It is concluded that pooling of orientation information is a relatively inaccurate process for which different perceptual cues and their combination rules can be used.