Impact of spatial grouping on mean size estimation

Similarity in feature space dictates the efficiency of attentional selection during ensemble processing

Humans can rapidly and accurately extract statistical information about features of the visual environment, an ability referred to as ensemble perception. However, little is known about how ensemble estimates are affected when task-irrelevant and distracting feature information is present. Here, we tested how effectively feature-based attention-when tuned to a specific color-can select a single item set out of two intermixed ensembles of colored lines. Participants were instructed to report the average orientation of a target-colored item set, while ignoring a second differently colored set. To assess how representational overlap between the two sets impacts color-based selection, we systematically varied the orientation similarity between the relevant and irrelevant items. Our results showed that participants' orientation reports were reliably biased towards the irrelevant items, but interestingly, these biases were only observed when the item sets overlapped in orientation space. In a second experiment, using a visual mask to disrupt access to color information at different time points, we found that these biases were stronger when less time was available to process the stimuli. Together, these results suggest that ensemble representations are rapidly formed based on all available information in the relevant feature dimension, regardless of task relevance, and that selective attention weights and separates these ensemble representations at a relatively later processing stage. This selection appears highly effective when the underlying population activity generated by the two sets is separable along the to-be-estimated feature dimension, but is dampened when relevant and irrelevant ensemble representations overlap in feature space.

The perceptual and mnemonic effects of ensemble representation on individual size representation

Our visual world consists of multiple objects, necessitating the identification of individual objects. Nevertheless, the representation of visual objects often exerts influence on each other. Even when we selectively attend to a subset of visual objects, the representations of surrounding items are encoded and influence the processing of the attended item(s). However, it remains unclear whether the effect of group ensemble representation on individual item representation occurs at the perceptual encoding phase, during the memory maintenance period, or both. Therefore, the current study conducted visual psychophysics experiments to investigate the contributions of perceptual and mnemonic bias on the observed effect of ensemble representation on individual size representation. Across five experiments, we found a consistent pattern of repulsive ensemble bias, such that the size of an individual target circle was consistently reported to be smaller than it actually was when presented alongside other circles with larger mean size, and vice versa. There was a perceptual component to the bias, but mnemonic factors also influenced its magnitude. Specifically, the repulsion bias was strongest with a short retention period (0-50 ms), then reduced within a second to a weaker magnitude that remained stable for a longer retention period (5,000 ms). Such patterns of results persisted when we facilitated the processing of ensemble representation by increasing the set size (Experiment 1B) or post-cueing the target circle so that attention was distributed across all items (Experiment 2B).

Priming effect of individual similarity and ensemble perception in visual search and working memory

Perceptual priming is a well-known phenomenon showing that the repetition of an object's feature can facilitate subsequent detection of that item. Although the priming effect has been rigorously studied in visual search, less is known about its effect on working memory and it is unclear whether the repetition of similar features, and furthermore, ensemble perception created by a large set of similar features, can induce priming. In this study, we investigated the priming effects of individual similarity and ensemble perception in visual search and visual working memory (VWM). We replicated the classic perceptual priming effect (Experiment 1a) and found that visual search was enhanced when the current target had a similar color to the previous target (Experiment 1b), but not when the similar color had been shown as a distractor before (Experiment 1c). However, if the target and distractors of similar colors formed ensemble perception, the search efficiency was again promoted even when the current target shared the same color with the previous distractor (Experiment 1d). For VWM, repeating the ensembles of the target- and nontarget-color subsets did not significantly affect the memory capacity, while switching the two harmed the memory fidelity but not capacity (Experiment 2). We suggest different underlying mechanisms for priming in visual search and VWM: in the former, the perception history of individual similarity and stimuli ensemble exert their effects on through the priority map, by forming a gradient distribution of attentional weights that peak at the previous target feature and diminish as stimulus diverges from the previously selected one; while in the latter, perception history of memory ensemble may influence the deployment of existing memory resources across trials, thereby affecting the memory fidelity but not its capacity.

Temporal integration of target features across and within trials in the attentional blink

Attentional blink research has typically investigated attentional limitations in multiple target processing. The current study investigated the temporal integration of target features in the attentional blink. Across two experiments, we demonstrated that the orientation estimations of individual target items in the attentional blink paradigm were systematically biased. Specifically, there was evidence for both within- and across-trial biases, revealing a general bias towards previously presented stimuli. Moreover, both biases were found to be more salient for targets suffering from the attentional blink. The current study is the first to demonstrate an across-trial bias in responses in the attentional blink paradigm. This set of findings is in line with the literature, suggesting that the human visual system can implicitly summarize information presented over time, which may lead to biases. By investigating temporal integration in the attentional blink, we have been able to address the modulatory role of attention on biases imposed by the implicit temporal effects in estimation tasks. Our findings may inform future research on attentional blink, serial dependence, and ensemble perception.

Remembering Sets: Capacity Limit and Time Limit of Ensemble Representations in Working Memory

In a constantly changing visual environment, the ability to extract and store ensemble representations plays a crucial role in efficiently processing and remembering complex visual information. However, how working memory maintains these ensemble representations remains unclear. Therefore, the present study aimed to investigate the limits and characteristics of ensemble representations in working memory using a change detection paradigm. Participants were presented with multiple sets of circles grouped by spatial proximity and were asked to memorize the mean diameter of the circles in each set. Results showed that working memory could stably maintain mean sizes of approximately two sets for at least four seconds. Moreover, the memory performance of ensembles was not affected by the number of circles within a set, suggesting that individual details were not stored in working memory. These results suggest that the visual system can effectively store ensembles in working memory without preserving detailed individual information.

No effect of spatial attention on the processing of a motion ensemble: Evidence from Posner cueing

The formation of ensemble codes is an efficient means through which the visual system represents vast arrays of information. This has led to the claim that ensemble representations are formed with minimal reliance on attentional resources. However, evidence is mixed regarding the effects of attention on ensemble processing, and researchers do not always make it clear how attention is being manipulated by their paradigm of choice. In this study, we examined the effects of Posner cueing - a well-established method of manipulating spatial attention - on the processing of a global motion stimulus, a naturalistic ensemble that requires the pooling of local motion signals. In Experiment 1, using a centrally presented, predictive attentional cue, we found no effect of spatial attention on global motion performance: Accuracy in invalid trials, where attention was misdirected by the cue, did not differ from accuracy in valid trials, where attention was directed to the location of the motion stimulus. In Experiment 2, we maximized the potential for our paradigm to reveal any attentional effects on global motion processing by using a threshold-based measure of performance; however, despite this change, there was again no evidence of an attentional effect on performance. Together, our results show that the processing of a global motion stimulus is unaffected when spatial attention is misdirected, and speak to the efficiency with which such ensemble stimuli are processed.

Variability leads to overestimation of mean summaries

Research on ensemble perception has shown that people can extract both mean and variance information, but much less is understand how these two different types of summaries interact with one another. Some research has argued that people are more erroneous in extracting the mean of displays that have greater variability. In all three experiments, we manipulated the variability in the displays. Participants reported the mean size of a set of circles (Experiment 1) and mean length of horizontally placed (Experiment 2a) and randomly oriented lines (Experiment 2b). In all experiments, we found that mean size estimations were more erroneous for higher than smaller variance displays. More critically, there was a tendency to overestimate the mean, driven by variance in both task-relevant and task-irrelevant features. We discuss these findings in relation to limitations in concurrent summarization ability and outlier discounting in ensemble perception.

Contributions of ensemble perception to outlier representation precision

It is known that the visual system can efficiently extract mean and variance information, facilitating the detection of outliers. However, no research to date has directly investigated whether ensemble perception mechanisms contribute to outlier representation precision. We specifically were interested in how the distinctiveness of outliers impacts their precision. Across two experiments, we compared how accurately viewers represented the orientation of spatial outliers that varied in distinctiveness and found that increased outlier distinctiveness resulted in greater precision. Based on comparisons of our data to simulations reflecting particular selective strategies, we eliminated the possibility that participants were selectively processing the outlier, at the expense of the ensemble. Thus, we argued that participants separately represented distinct outliers along with ensemble summaries of the remaining items in a display. We also found that outlier distinctiveness moderated the precision of how the remaining items were summarized. We discuss these findings in relation to computational capacity and constraints of ensemble perception mechanisms.

Synergy between research on ensemble perception, data visualization, and statistics education: A tutorial review

In the age of big data, we are constantly inventing new data visualizations to consolidate massive amounts of numerical information into smaller and more digestible visual formats. These data visualizations use various visual features to convey quantitative information, such as spatial position in scatter plots, color saturation in heat maps, and area in dot maps. These data visualizations are typically composed of ensembles, or groups of related objects, that together convey information about a data set. Ensemble perception, or one's ability to perceive summary statistics from an ensemble, such as the mean, has been used as a foundation for understanding and explaining the effectiveness of certain data visualizations. However, research in data visualization has revealed some perceptual biases and conceptual difficulties people face when trying to utilize the information in these graphs. In this tutorial review, we will provide a broad overview of research conducted in ensemble perception, discuss how principles of ensemble encoding have been applied to the research in data visualization, and showcase the barriers graphs can pose to learning statistical concepts, using histograms as a specific example. The goal of this tutorial review is to highlight possible connections between three areas of research-ensemble perception, data visualization, and statistics education-and to encourage research in the practical applications of ensemble perception in solving real-world problems in statistics education.

Statistical summary representations of bound features

The visual system can efficiently summarize various lower-level and higher-level features of ensembles. However, no research to date has directly investigated how different features interact with each other within a single summary and whether people can efficiently report an integrated summary of two feature dimensions. In the first two experiments, we specifically investigated whether individuals can integrate spatial and size information to report a bound spatial summary, the center of mass (CoM), as efficiently as the centroid, which is devoid of size information. Both experiments revealed that viewers were equally accurate in extracting the centroid and the CoM, with the size distribution inadvertently affecting the centroid estimates. In the final experiment, we investigated whether encouraging observers to attend to individual item size would cause the centroid estimates to be biased toward the CoM. When item size was task-irrelevant, as in the centroid task, observers were able to selectively focus on spatial location, eliminating any impact from the size distribution. Taken together, these findings demonstrate that viewers are capable of extracting integrated summaries, possibly through a mechanism that allows them to represent the spatial distribution of sizes. We discuss possible mechanisms that may support the extraction of integrated summaries, and highlight the need to consider multilevel mechanisms extending beyond simple feature- and object-based mechanisms.

Feature-specificity in visual statistical summary processing

Visual statistical summary processing enables people to extract the average feature of a set of items rapidly and accurately. Previous studies have demonstrated independent mechanisms for summarizing low (e.g. color, orientation) and high-level (facial identity, emotion) visual information. However, no study to date has conclusively determined whether there are feature-specific summarization mechanisms for low-level features or whether there are low-level, feature agnostic summarization mechanisms. To address this issue, we asked participants to report either the average orientation or the average size from a set of lines where both features varied. Participants completed these tasks either in single-task or mixed-task conditions; in the latter, successful performance required extraction of both summaries concurrently. If there were feature-specific summarization mechanisms that could operate in parallel, then errors in mean size and mean orientation tasks should be independent, in both single and mixed task conditions. On the other hand, a central domain-general mechanism for low-level summarization would imply a correlation between errors for both features and greater error in the mixed than single task trials. In Experiment 1, we found that there was no correlation between the mean size and mean orientation errors and performance was similar across single and mixed-task conditions, suggesting that there may be independent summarization mechanisms for size and orientation features. To further test the feature-specificity account, in Experiment 2 and 3 (with mask), we manipulated the display duration to determine whether there were any differences in the summarization of earlier (orientation) vs. later (size) features. While these experiments replicated the pattern of results observed in Experiment 1, at shorter display durations, no differences emerged across features. We argue that our data is consistent with independent, multi-level feature-specific statistical summary mechanisms for low-level visual features.