Unstable mean context causes sensitivity loss and biased estimation of variability

Abstract

A recent study has suggested that statistical representations of ensemble objects may provide contextual stability to facilitate perception. The present study investigated whether facilitating such perception occurs in the extraction of variability information and how the stability of context mean values influences variability perception. We designed two tasks in which participants directly judged the variability of stimuli. In Experiment 1, we manipulated both the stability of the mean values and the exposure time to observe the time course of stability facilitation. In Experiment 2, we decomposed the stability of the context mean values into between-trials and within-trial levels to further investigate the mechanism of such facilitation. The results revealed that stable mean contexts do facilitate variability perception. In particular, unstable long-term mean context causes loss of sensitivity to variability whereas response bias is determined by the interaction between long-term and transient mean stability.

Independent and parallel visual processing of ensemble statistics: Evidence from dual tasks

“…Note that our results do not imply that there is no link between the representations of various statistical summaries. As an example of such a link, a lot of studies have shown that the precision of judgments of mean size usually decreases with an increase in the physical variance of a display (Corbett et al, 2012, experiment 4;Im & Halberda, 2013;Maule & Franklin, 2015;Tong et al, 2015;Utochkin & Tiurina, 2014). It is important, however, that the claims based on the manipulations of physical variance in these studies concern mostly the role of the external, stimulus noise in the representation of the mean.…”

Incidental statistical summary representation over time

“…Although several other investigations have explored the role of variability in size averaging in static displays (e.g., Corbett, Wurnitsch, Schwartz, & Whitney, 2012;Im & Halberda, 2013;Marchant, Simon, & de Fockert, 2013;Tong, Ji, Chen, & Fu, 2015;Utochkin & Tiurina, 2014), few studies have examined the encoding of variability and central tendency in a set over an extended duration, and none have done so under conditions in which the tested attribute was unattended. The present findings suggest that, in addition to encoding the central tendency and variability of static displays, observers integrate information across multiple displays to represent more global properties of the sets from which the items presented in static displays are drawn.…”

Ensemble coding of memory strength in recognition tests

“…Subsequent work established that representation of the mean of a particular feature dimension occurs for numerous visual tasks including multiple object tracking, rapid serial visual presentation, change detection, and Sternberg scanning, among others (see Dubé & Sekuler, 2015, for review). Such statistical representations have also been demonstrated for variances (Tong, Ji, Chen, & Fu, 2015), for high-level features such as facial expression (Sweeney, Grabowecki, Paller, & Suzuki, 2009), and for auditory as well as visual stimuli (McDermott, Schemitsch, & Simoncelli, 2013). Averaging occurs for items presented simultaneously as well as sequentially (Albrecht & Scholl, 2010;Corbett & Oriet, 2011).…”