Gaze Behavior Consistency among Older and Younger Adults When Looking at Emotional Faces

Abstract

The identification of non-verbal emotional signals, and especially of facial expressions, is essential for successful social communication among humans. Previous research has reported an age-related decline in facial emotion identification, and argued for socio-emotional or aging-brain model explanations. However, more perceptual differences in the gaze strategies that accompany facial emotional processing with advancing age have been under-explored yet. In this study, 22 young (22.2 years) and 22 older (70.4 years) adults were instructed to look at basic facial expressions while their gaze movements were recorded by an eye-tracker. Participants were then asked to identify each emotion, and the unbiased hit rate was applied as performance measure. Gaze data were first analyzed using traditional measures of fixations over two preferential regions of the face (upper and lower areas) for each emotion. Then, to better capture core gaze changes with advancing age, spatio-temporal gaze behaviors were deeper examined using data-driven analysis (dimension reduction, clustering). Results first confirmed that older adults performed worse than younger adults at identifying facial expressions, except for “joy” and “disgust,” and this was accompanied by a gaze preference toward the lower-face. Interestingly, this phenomenon was maintained during the whole time course of stimulus presentation. More importantly, trials corresponding to older adults were more tightly clustered, suggesting that the gaze behavior patterns of older adults are more consistent than those of younger adults. This study demonstrates that, confronted to emotional faces, younger and older adults do not prioritize or ignore the same facial areas. Older adults mainly adopted a focused-gaze strategy, consisting in focusing only on the lower part of the face throughout the whole stimuli display time. This consistency may constitute a robust and distinctive “social signature” of emotional identification in aging. Younger adults, however, were more dispersed in terms of gaze behavior and used a more exploratory-gaze strategy, consisting in repeatedly visiting both facial areas.

Age-related changes in gaze behaviour during social interaction: An eye-tracking study with an embodied conversational agent

“…For each of the facial expressions, older adults spent significantly less time on the eye region than younger adults, but we did not observe any age-related differences for the mouth region. These novel results are in contrast with previous studies (Chaby et al, 2017; Murphy & Isaacowitz, 2010; Wong et al, 2005) which showed that younger and older adults do not prioritise the same facial regions when identifying facial expressions (i.e., an exploratory strategy in young adults and a focusing strategy on the mouth region in older adults). What is new in this study is that participants focused primarily on the eye area during the decoding of facial expressions, although this was less evident in the older age group.…”

“…Successful social interactions are crucial in everyday life and until old age. However, so far, studies in the field of psychology of aging have mainly investigated offline social interactions, with low ecological validity, in which participants are passive detached observers of social stimuli (e.g., Chaby et al, 2017; Grainger et al, 2017; Sze et al, 2012). Thus, it is not clear whether age-related differences remain in more natural interactive settings that offer the possibility to exchange social signals, especially through gaze behaviour.…”

“…Indeed, some studies have reported that when exposed to static expressive faces, older adults show a preferential gaze pattern away from negative stimuli (Knight et al, 2007) and spend more time exploring the mouth area (e.g., Murphy & Isaacowitz, 2010; Wong et al, 2005), which unlike the eye region, does not typically play a key role in decoding social cues. In a previous study using static faces (Chaby et al, 2017), we showed that younger adults adopt an exploratory-gaze strategy according to specific emotions, whereas older adults adopt a focused-gaze strategy on the lower part of the face, rendering expressions such as anger, fear, and sadness challenging to decode. Even with a dynamic presentation, these strategies remain unchanged (Grainger et al, 2017).…”

Differences in Encoding Strategy as a Potential Explanation for Age-Related Decline in Place Recognition Ability

“…Moreover, this replay of eye movements is accompanied by image-specific patterns of brain activity during recall (Bone et al, 2019). Indeed, eye-tracking has been used to investigate strategies in many cognitive domains, such as learning (for a review, see Lai et al, 2013), reading (for a review, see Rayner, 1998), memory (for a review, see Hannula et al, 2010), face recognition (Chaby et al, 2017), and navigation (Mueller et al, 2008;Livingstone-Lee et al, 2011;Andersen et al, 2012). This link between eye movements and cognition extends to the solving of spatial tasks (Thomas and Lleras, 2007).…”

New approaches to the analysis of eye movement behaviour across expertise while viewing brain MRIs

“…Madsen, Larson, Loschky, and Rebello ( 2012 ) used ScanMatch to examine differences in the eye movements of individuals answering physics questions to examine if there was a difference for correct versus incorrect answers. This method has also been used to examine differences in scanning patterns between Novices and Experts evaluating paintings (Pihko et al, 2011 ) and while viewing surgical procedures (Kübler, Eivazi, & Kasneci, 2015 ), problem-solving (Nyamsuren & Taatgen, 2013 ), face-processing (Chaby, Hupont, Avril, Luherne-du Boullay, & Chetouani, 2017 ), and decision-making (Zhou et al, 2016 ). Anderson, Anderson, Kingstone, and Bischof ( 2015 ) compared the ability of several scan path comparison methods to reveal similarities both within and between individuals looking at natural scenes and concluded that ScanMatch is a remarkable improvement on more simple method string-edit and linear distance methods.…”