Elsevier

Neuropsychologia

Volume 50, Issue 7, June 2012, Pages 1698-1707
Neuropsychologia

Crowd perception in prosopagnosia

https://doi.org/10.1016/j.neuropsychologia.2012.03.026Get rights and content

Abstract

Prosopagnosics, individuals who are impaired at recognizing single faces, often report increased difficulty when confronted with crowds. However, the discrimination of crowds has never been fully tested in the prosopagnosic population. Here we investigate whether developmental prosopagnosics can extract ensemble characteristics from groups of faces. DP and control participants viewed sets of faces varying in either identity or emotion, and were asked to estimate the average identity or emotion of each set. Face sets were displayed in two orientations (upright and inverted) to control for low-level visual features during ensemble encoding. Control participants made more accurate estimates of the mean identity and emotion when faces were upright than inverted. In all conditions, DPs performed equivalently to controls. This finding demonstrates that integration across different faces in a crowd is possible in the prosopagnosic population and appears to be intact despite their face recognition deficits. Results also demonstrate that ensemble representations are derived differently for upright and inverted faces, and the effects are not due to low-level visual information.

Highlights

► We examine ensemble coding of crowds in prosopagnosics for the first time. ► Prosopagnosics successfully ensemble code both crowd emotion and identity. ► Performance in ensemble coding was better in upright vs. inverted faces.

Introduction

Every day we interact with crowds of people. Whether it is on a city bus, in a classroom, or in a business meeting, we routinely view and extract important information from groups of faces, and do so rather rapidly. Indeed, recent studies have shown that people are adept at recognizing crowd characteristics, such as average gender, identity or emotion, even when crowds are viewed so briefly that information about any specific individual is not extracted (De Fockert and Wolfenstein, 2009, Haberman and Whitney, 2007, Haberman and Whitney, 2009). For example, as a passenger on a bus, we form a general impression of important characteristics of a crowd standing on the street corner, even if we are only able to view the crowd for a split-second as we ride by.

Given the frequency with which we interact with crowds, a deficit in perceiving crowd characteristics would likely pose a hindrance in a host of social situations. Anecdotal evidence suggests that individuals with prosopagnosia, a deficit in discriminating individual faces, feel overwhelmed in crowded situations, perhaps in part due to their inability recognize familiar faces in a crowd. For example, one prosopagnosic describes his experience walking into a reception hall, “There are a lot of people there, perhaps as many as a hundred or so people. These are all people I am supposed to know, each with a supposedly unique face. My goal is to find just one specific individual. I can scan the room for hours in frustration… (Asprin, 2011).” Another prosopagnosic expresses frustration saying, “Faces in public are just all faces to me, I don’t see them individually. This is especially [true] in crowded public areas. When I look into a crowd, most look very much alike to me (BP, 2011).” Can prosopagnosics’ discomfort with crowds be explained entirely by their deficits in perceiving single faces? Or could it reflect a more general impairment in integrating and extracting face-related information from a crowd? On the other hand, might prosopagnosics actually be better at ensemble coding because they do not perceive crowd members as distinct individuals?

The perceptual characteristics of developmental prosopagnosics2 (DPs), individuals who have never fully developed the ability to recognize faces, have been increasingly studied during the last decade. However, almost all of the previous research used single faces to investigate processing in DPs. Although the study of individual face processing in DP added essential information aiding the understanding of problems related to individual face recognition, we know virtually nothing about how DPs extract information from groups of faces and whether it is normal or not.

When processing crowds, typical viewers initially discount individual faces in a group and instead formulate unitized percepts that accurately describe crowd characteristics (De Fockert and Wolfenstein, 2009, Haberman and Whitney, 2007, Haberman and Whitney, 2009). The ability to generate a gestalt percept of the crowd, independent of information derived from individual faces, can be viewed as a mechanism that compensates for the limited capacity of the visual system to process multiple items simultaneously. Redundant information across items in a scene is compressed into an average representation of the entire set, referred to as the “ensemble code” (Alvarez, 2011, Ariely, 2001, Chong and Treisman, 2003). This average representation provides a more precise description in comparison to individual evaluations of each member of the set because noise from one individual evaluation cancels out uncorrelated noise from another individual evaluation (Alvarez, 2011). As such, it has been shown that typical viewers can accurately extract both the mean emotional expression and mean identity of the crowd, although performance is at chance when they are asked to discriminate, identify, or localize individual members of a previously seen set (De Fockert and Wolfenstein, 2009, Haberman and Whitney, 2007, Haberman and Whitney, 2009).

Previous research suggests that DPs have trouble integrating individual face features into a gestalt (Behrmann et al., 2005, de Gelder and Rouw, 2000, Lobmaier et al., 2010), and may be generally impaired at identifying the global shape of a stimulus, showing such deficits for objects as well as faces (Avidan et al., 2011, Behrmann and Avidan, 2005, Behrmann et al., 2005, Bentin et al., 2007, Palermo et al., 2011). For alternative findings see: Le Grand et al. (2006), Duchaine, Yovel, & Nakayama (2007), Schmalzl, Palermo, Green, Brunsdon, and Coltheart (2008) and Lee, Duchaine, Wilson, and Nakayama (2010). Ensemble coding, like other holistic processing tasks, requires the integration of features across space (Alvarez, 2011) or time (Haberman, Harp, & Whitney, 2009). If DPs have difficulty with this type of integration in general, we may expect that they will have trouble forming a unitary percept of any attribute of a crowd, not just average identity. Alternatively, it is possible that the deficits DPs experience during individual face recognition tasks will be minimized via the process of ensemble coding. As mentioned previously, ensemble coding involves canceling out “noisy” individual evaluations, thereby achieving a more precise representation of the group as a whole. Although individual face evaluations are suboptimal in DP, the averaging process inherently reduces such imprecision. This leaves open the intriguing possibility that DPs, who are impaired at individual face identification, may be able to extract the mean identity of the crowd just as well as controls. If DPs do not experience interference by individual faces in the crowd, they could potentially be better than normal perceivers at extracting ensemble information.

The aim of this study was to explore whether DPs can successfully perceive ensemble characteristics of face sets, or “crowds.” In order to distinguish between deficits specific to the perception of face identity and impairment in ensemble coding in general, we measured the ability to estimate not only the average identity of upright faces, but also the average emotional expression, an attribute for which DPs typically exhibit little impairment when performing judgments on individual faces (Bentin et al., 1999, Dobel et al., 2007, Duchaine et al., 2003, Humphreys et al., 2007, Jones and Tranel, 2001; for an different view see Palermo et al., 2011). Accordingly, we limited our group of participants to those who reported no or very little impairment in emotional processing of faces. Furthermore, we included conditions in which the face sets were inverted to control for low-level visual effects during ensemble coding.

Section snippets

Participants

Four DP individuals (DP1, DP2, DP3, and DP4) participated in the experiment. Three of the 4 DPs were recruited from a volunteer pool of previously diagnosed prosopagnosics (results from original tests are reported in Section 2.3). One had not participated in previous studies and was newly screened. We asked the DP participants to describe their experiences with faces and whether they found it difficult to recognize individuals and/or the emotion of individual faces by vision alone. All of them

Results

Fig. 6, Fig. 7 show the rectified standard deviation of the error distributions for both controls and DPs during the heterogeneous and homogeneous conditions. The pattern clearly indicates that DP's performance falls well within the distribution of control performance during the heterogeneous condition and suggests that DPs can successfully perform ensemble coding on crowds of faces. Small sample t-tests further confirm that prosopagnosics’ performance is similar to control performance. There

Discussion

In the current study, we tested whether DPs’ impairments in single face recognition affects their percept of crowd characteristics. Although processing single faces is an important element of social interaction, crowd perception is also an integral aspect of daily experience, both for evaluating the probability that certain individuals might be in a crowd, and for ascertaining the emotional tenor. Indeed, much of daily life is filled with crowd analysis at some level. We engage with crowds

Acknowledgements

This research was supported by the Veterans Administration, National Institutes of Health Grant MH-0164458 (to L.C.R. & SB) and NSF 074689 (DW). Lynn C. Robertson has a Senior Research Career Scientist award from the Veterans Administration and is affiliated with the VA Clinical Sciences Research Service, Department of Veterans Affairs Medical Center, Martinez, CA. We would like to thank Joe Degutis for providing previous test results and Jason Haberman for providing Matlab code. Also, we would

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