Ensemble Statistics Can Be Available before Individual Item Properties: Electroencephalography Evidence Using the Oddball Paradigm

Decoding time-resolved neural representations of orientation ensemble perception

The visual system can compute summary statistics of several visual elements at a glance. Numerous studies have shown that an ensemble of different visual features can be perceived over 50-200 ms; however, the time point at which the visual system forms an accurate ensemble representation associated with an individual's perception remains unclear. This is mainly because most previous studies have not fully addressed time-resolved neural representations that occur during ensemble perception, particularly lacking quantification of the representational strength of ensembles and their correlation with behavior. Here, we conducted orientation ensemble discrimination tasks and electroencephalogram (EEG) recordings to decode orientation representations over time while human observers discriminated an average of multiple orientations. We modeled EEG signals as a linear sum of hypothetical orientation channel responses and inverted this model to quantify the representational strength of orientation ensemble. Our analysis using this inverted encoding model revealed stronger representations of the average orientation over 400-700 ms. We also correlated the orientation representation estimated from EEG signals with the perceived average orientation reported in the ensemble discrimination task with adjustment methods. We found that the estimated orientation at approximately 600-700 ms significantly correlated with the individual differences in perceived average orientation. These results suggest that although ensembles can be quickly and roughly computed, the visual system may gradually compute an orientation ensemble over several hundred milliseconds to achieve a more accurate ensemble representation.

Perception of visual variance is mediated by subcortical mechanisms

Variance characterizes the structure of the environment. This statistical concept plays a critical role in evaluating the reliability of evidence for human decision-making. The present study examined the involvement of subcortical structures in the processing of visual variance. To this end, we used a stereoscope to sequentially present two circle arrays in a dichoptic or monocular fashion while participants compared the perceived variance of the two arrays. In Experiment 1, two arrays were presented monocularly to the same eye, dichopticly to different eyes, or binocularly to both eyes. The variance judgment was less accurate in different-eye condition than the other conditions. In Experiment 2, the first circle array was split into a large-variance and a small-variance set, with either the large-variance or small-variance set preceding the presentation of the second circle array in the same eye. The variance of the first array was judged larger when the second array was preceded by the large-variance set in the same eye, showing that the perception of variance was modulated by the visual variance processed in the same eye. Taken together, these findings provide evidence for monocular processing of visual variance, suggesting that subcortical structures capture the statistical structure of the visual world.

Nonadditive integration of visual information in ensemble processing

Statistically summarizing information from a stimulus array into an ensemble representation (e.g., the mean) improves the efficiency of visual processing. However, little is known about how the brain computes the ensemble statistics. Here, we propose that ensemble processing is realized by nonadditive integration, rather than linear averaging, of individual items. We used a linear regression model approach to extract EEG responses to three levels of information: the individual items, their local interactions, and their global interaction. The local and global interactions, representing nonadditive integration of individual items, elicited rapid and independent neural responses. Critically, only the neural representation of the global interaction predicted the precision of the ensemble perception at the behavioral level. Furthermore, spreading attention over the global pattern to enhance ensemble processing directly promoted rapid neural representation of the global interaction. Taken together, these findings advocate a global, nonadditive mechanism of ensemble processing in the brain.

Three's a crowd: Fast ensemble perception of first impressions of trustworthiness

Trustworthiness impressions are fundamental social judgements with far-reaching consequences in many aspects of society, including criminal justice, leadership selection and partner preferences. Thus far, most research has focused on facial characteristics that make a face individually appear more or less trustworthy. However, in everyday life, faces are not always perceived in isolation but are often encountered in crowds. It has been proposed that we deal with the large amount of facial information in a group by extracting summary statistics of the crowd, a phenomenon called ensemble perception. Prior research showed that ensemble perception occurs for various facial features, such as emotional expression, facial identity, and attractiveness. Here, we investigated whether observers can integrate the level of trustworthiness from multiple faces to extract an average impression of the crowd. Across four studies, participants were presented with crowds of faces and were asked to report their average level of trustworthiness with an adjustment (Experiment 1) and a rating task (Experiments 2 and 3). Participants were able to extract an ensemble perception of trustworthiness impressions from multiple faces. Moreover, observers were able to form a summary statistic of trustworthiness impressions from a group of faces as quickly as 250 ms (Experiment 4). Taken together, these results demonstrate that ensemble perception can occur at the level of impressions of trustworthiness. Thus, these critical social judgements not only occur for individual faces but are also integrated into a unique ensemble impression of crowds. Our findings contribute to the development of a more ecological approach to the study of trust impressions, since they provide an understanding of trustworthiness judgements not only on an individual level, but on a much broader social group level. Furthermore, our results drive forward new theory because they demonstrate for the first time that ensemble representations cover a broad range of phenomena than previously recognized, including complex high-level facial trait judgements such as trustworthiness impressions.

Subcortical encoding of summary statistics in humans

Statistical encoding compresses redundant information from multiple items into a single summary metric (e.g., mean). Such statistical representation has been suggested to be automatic, but at which stage it is extracted is unknown. Here, we examined the involvement of the subcortex in the processing of summary statistics. We presented an array of circles dichoptically or monocularly while matching the number of perceived circles after binocular fusion. Experiments 1 and 2 showed that interocularly suppressed, invisible circles were automatically involved in the summary statistical representation, but only when they were presented to the same eye as the visible circles. This same-eye effect was further observed for consciously processed circles in Experiment 3, in which the estimated mean size of the circles was biased toward the information transmitted by monocular channels. Together, we provide converging evidence that the processing of summary statistics, an assumed high-level cognitive process, is mediated by subcortical structures.

Ensemble size perception: Its neural signature and the role of global interaction over individual items

To efficiently process complex visual scenes, the visual system often summarizes statistical information across individual items and represents them as an ensemble. However, due to the lack of techniques to disentangle the representation of the ensemble from that of the individual items constituting the ensemble, whether there exists a specialized neural mechanism for ensemble processing and how ensemble perception is computed in the brain remain unknown. To address these issues, we used a frequency-tagging EEG approach to track brain responses to periodically updated ensemble sizes. Neural responses tracking the ensemble size were detected in parieto-occipital electrodes, revealing a global and specialized neural mechanism of ensemble size perception. We then used the temporal response function to isolate neural responses to the individual sizes and their interactions. Notably, while the individual sizes and their local and global interactions were encoded in the EEG signals, only the global interaction contributed directly to the ensemble size perception. Finally, distributed attention to the global stimulus pattern enhanced the neural signature of the ensemble size, mainly by modulating the neural representation of the global interaction between all individual sizes. These findings advocate a specialized, global neural mechanism of ensemble size perception and suggest that global interaction between individual items contributes to ensemble perception.

The role of ensemble average differs in working memory for depth and planar information

The representation of individual planar locations and features stored in working memory can be affected by the average representation. However, less is known about how the average representation affects the short-term storage of depth information. To evaluate the possible different roles of the ensemble average in working memory for planar and depth information, we used mathematical models to fit the data collected from one study on working memory for depth and 12 studies on working memory for planar information. The pattern of recalled depth was well captured by models assuming that there was a probability of reporting the average depth instead of the individual depth, compressing the recalled front-back distance of the stimulus ensemble compared to the perceived distance. However, when modeling the recalled planar information, we found that participants tended to report individual nontarget features when the target was not memorized, and the assumption of reporting average information improves the data fitting only in very few studies. These results provide evidence for our hypothesis that average depth information can be used as a substitution for individual depth information stored in working memory, but for planar visual features, the substitution of target with the average works under a constraint that the average of to-be-remembered features is readily accessible.