Perceptual history biases in serial ensemble representation

Abstract

Ensemble perception refers to the visual system's ability to efficiently represent groups of similar objects as a unified percept using their summary statistical information. Most studies focused on extraction of current trial averages, giving little attention to prior experience effects, although a few recent studies found that ensemble mean estimations contract toward previously presented stimuli, with most of these focusing on explicit perceptual averaging of simultaneously presented item ensembles. Yet, the time element is crucial in real dynamic environments, where we encounter ensemble items over time, aggregating information until reaching summary representations. Moreover, statistical information of objects and scenes is learned over time and often implicitly and then used for predictions that shape perception, promoting environmental stability. Therefore, we now focus on temporal aspects of ensemble statistics and test whether prior information, beyond the current trial, biases implicit perceptual decisions. We designed methods to separate current trial biases from those of previously seen trial ensembles. In each trial, six circles of different sizes were presented serially, followed by two test items. Participants were asked to choose which was present in the sequence. Participants unconsciously rely on ensemble statistics, choosing stimuli closer to the ensemble mean. To isolate the influence of earlier trials, the two test items were sometimes equidistant from the current trial mean. Results showed membership judgment biases toward current trial mean, when informative (largest effect). On equidistant trials, judgments were biased toward previously experienced stimulus statistics. Comparison of similar conditions with a shifted stimulus distribution ruled out a bias toward an earlier, presession, prototypical diameter. We conclude that ensemble perception, even for temporally experienced ensembles, is influenced not only by current trial mean but also by means of recently seen ensembles and that these influences are somewhat correlated on a participant-by-participant basis.

Figure 1.

Experiment 1 design. (a) Illustration of trial procedure for two consecutive trials—six circles are presented serially in each trial with time intervals (100 ms + 100-ms interstimulus interval), and then, following a masking stimulus, a two-alternative forced-choice membership task is presented; Δ parameters: upper example, trial “t –1,” standard trial with nonequidistant SEEN and NEW test items. (In this example, the NEW and SEEN test items are 3 and 1 units from current trial mean, respectively, so that Δ(Tmean) = 3 – 1 = 2, with the SEEN item closer to the current mean); lower example, trial “t,” an equidistant trial where SEEN and NEW test items are the same distance from the current trial mean, so that the different distances from the recent trial mean, Rmean, can influence current trial choice of test item. (In the example shown, both SEEN and NEW are 2 units from the current trial mean, so that Δ(Tmean) = 2 – 2 = 0; here the difference in distances from the recent (t – 1) mean, Rmean, is Δ(Rmean) = 2 – 6 = –4, with the NEW test item closer to the recent mean). (b) Size probability distributions of stimuli and means of Experiments 1 and 2 (Session 1) are represented by the black and red curves, respectively; stimulus and mean distributions of Experiment 3 (Session 2) are represented by the gray and blue curves, respectively. Stimuli are normally distributed (Gaussian fits), while the trial means are distributed in a trapezoidal shape, with the 10 most central means of each session with uniform probability (dots represent the actual probability of presenting each size). (c) Trial subtypes and conditions. “in” = in trial range, not mean; “out” = out of trial range.

Figure 2.

Experiment 1: effects of current trial test item statistics on performance. (a) Accuracy in the membership task for the various trial subtypes. Each symbol represents the average accuracy of a single participant; horizontal bars denote group averages, and error bars represent standard error of the mean. Performance when the SEEN item equals the trial sequence mean, Tmean, is significantly above baseline and when the NEW item equals Tmean, significantly below baseline; in baseline trials, neither SEEN nor NEW equals Tmean; performance is best when the NEW test item is outside the trial sequence range. (b) Gradual effect by relative difference of absolute distances of the SEEN and NEW test items from the current trial mean (Δ(Tmean)), as defined above and in Figure 1a, with a best-fit sigmoid curve. Performance depends parametrically on the relative proximity of the SEEN test item and relative distance of the NEW test item from the trial sequence mean. When they are the same distance (0 difference), there is no average bias. When the SEEN is more distant, participants fail to detect its presence in the set and score below chance, whereas when it is closer, they score well above chance. Data for this plot were collected from in-range trials only. (c) RT for correct (green) and incorrect (orange) trials in the various trial subtypes (e.g., fastest correct response is when the NEW is out of range). Data collected from four blocks with all distances. Error bars in (a) and (c) are standard error of the mean; in (b), they were <0.02, not shown. *Indicates t test result of p < 0.05. ***Indicates p < 0.001.

Figure 3.

Contraction toward the recent trial mean, Rmean, in equidistant trials. (a) Accuracy in the membership task for the three trial subtypes. Each symbol represents the average accuracy of a single participant; horizontal bars denote group averages, and error bars represent standard error of the mean. Performance when the SEEN item equals the recent trial sequence mean, Rmean, is significantly above baseline, and when the NEW item equals Rmean, it is significantly below baseline; in baseline trials, neither SEEN nor NEW equals Rmean. (b) Rate of selecting the test item closer to the recent mean. Each circle reflects average performance of a single participant; horizontal line corresponds to average across participants; error bars, standard error of the mean. (c) Average accuracy as a function of the difference (Δ) of the test items’ distance from the recent trial mean (Rmean). Red symbols represent data from Experiment 2; blue symbols represent data from Experiment 3; sigmoid curve is calculated across data of both experiments. Standard error of the mean was <0.02.

Figure 4.

Comparing current trial mean and recent trial mean effect on task performance within the subjects of the first experimental session. The data for these analyses are taken from the same 100 participants of Experiments 1 and 2. (a) Sigmoid curve fitting of the fraction of selecting SEEN item as a function of the distances of test items from the current (purple) and recent (red) trial mean. Data are calculated and averaged across participants for each Δ value. (b) Within-subject correlation of the current trial mean effect with the recent trial mean effect. Tmean and Rmean effects are calculated by subtraction of the task performance in trial subtype NEW = mean from SEEN = mean, for each subject. Most data points are above the dashed line of equal Tmean and Rmean effects, showing a larger Tmean effect for most subjects. (c) Test–retest reliability of the Tmean effect. Data are divided into odd blocks versus even blocks. (d) Test–retest reliability of the Rmean effect. Data are divided into odd blocks versus even blocks. Significant Spearman correlation shows within-subject consistency. Each hollow symbol in (b, c, d) corresponds to a single subject; filled circles in (a) represent data averaged across participants; solid line is the correlation between participants' performance.

Figure 5.

Rate of test item selection as a function of test item size in equidistant trials, in two session distributions of Experiments 2 and 3, with a best-fit Gaussian curve. Red and pink dots and curves correspond to rates of selecting the SEEN (membership accuracy) and NEW (membership error rate) test items in Experiment 2 (with smaller size circles). Blue and light blue points and curves denote the rate of selecting these items in Experiment 3 (with larger circle sizes). Each symbol corresponds to the average selection of a specific size of test item across participants. Curves were calculated over the entire data rather than over the averages at each test item value.

Figure A1.

Contrasting the ensemble perception and the sampling models. Fraction of Experiment 1 observer choice of the SEEN item as a function of the difference between the distances of the two test items from the mean of the set distribution. Data points reflect different trial “skewness.” The lack of constant order in these points suggests little effect of memory of a random sample of one set element. The sigmoid performance dependence on Δ supports the ensemble perception model.

Figure A2.

Contrasting the ensemble perception and the sampling models. Fraction of observer choice of the test item closer to Tmean or (equivalently) to most set individuals for small and large absolute Δ (left) and for small and large skewness (right). The dependence on absolute Δ is highly significant and the dependence on skewness is in the unexpected direction. See Appendix text. Error bars are standard error.