As mentioned in the previous section, we consistently found a performance improvement for relevant happy faces across studies (Chapter 3 and 4) and age groups (adolescents and adults). This ‘positivity effect’ has also been reported in adults by Levens and Gotlib (2010) using a similar face n-back task where participants were asked to remember and compare the emotional expression that was shown. In healthy adults, reaction times for happy faces were faster both in the 0-back and the 2-back task. They suggested that this benefit for happy faces in WM reflects a bias to maintain positive information, which might underlie resilience. Similar biases for positive information in healthy adults have also been found in other domains, such as attentional research (Joormann & Gotlib, 2007; Sanchez, Vazquez, Marker, LeMoult, & Joormann, 2013) and word processing (Herbert, Kissler, Junghofer, Peyk, & Rockstroh, 2006; Kuchinke et al., 2005).
In adolescents, only one study, to our knowledge, has used an n-back task with relevant emotional stimuli (Passarotti, Sweeney, & Pavuluri, 2010). However, this study aimed to compare performance of adolescents with bipolar disorder (BD) or attention-deficit hyperactivity disorder (ADHD) to healthy control subjects. In keeping with this, a separate behavioural analysis in healthy controls was not reported. Nevertheless, a main effect of emotion on RT was reported across groups, with slower RTs for angry
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169 compared to neutral faces, and no significant differences with happy faces. This absence of a positivity effect could be due to differences in task design. In our study, as well as in the study reported by Levens and Gotlib (2010), faces only matched in emotional expression and not face identity, whereas a match in expression was always accompanied by a match in face identity in the study by Passarotti et al. (2010).
Therefore, it is possible that participants focused more on the encoding of face identity, thus limiting the processing of the emotional valence of the face, and consequently limiting its impact on WM performance.
Even though the impact of relevant emotional stimuli on WM has been largely understudied in developmental samples, there are a few studies that have investigated the impact on another cognitive control skill, i.e. inhibitory control. For example, Hare et al. (2008) used an emotional go/no-go paradigm in children (7-12 years), adolescents (13-18 years) and adults (19-32 years) to assess inhibition for relevant emotional faces.
In each block, participants saw two emotional expressions (fearful, happy or neutral faces) and were asked to respond to one of these faces, while withholding their response when confronted with another face. All three age groups were found to be faster in response to happy faces, and this effect was replicated in two other independent studies (Schel & Crone, 2013; Somerville, Hare, & Casey, 2011).
Thus, this consistent bias towards happy faces that we identified across studies is supported by both the adult and adolescent literature. Happy faces seem to attract attention more easily than other emotional expressions, at least in healthy participants, and this attentional capture can influence both the ability to inhibit responses but also WM processes. Indeed, increasing evidence using attentional blink (Miyazawa &
Iwasaki, 2010) and visual search tasks such as the face-in-the-crowd paradigm (Becker, Anderson, Mortensen, Neufeld, & Neel, 2011; Juth, Lundqvist, Karlsson, & Ohman, 2005) points to an attentional preference for happy faces in healthy participants.
Whereas early research on attention for facial expressions reported a faster detection of angry faces within a crowd of neutral or emotional distractor faces (Hansen &
Hansen, 1988), this so called ‘anger superiority effect’ has been challenged (Coelho, Cloete, & Wallis, 2010; Purcell, Stewart, & Skov, 1996). As a recent study suggested (Craig, Becker, & Lipp, 2014), more and more evidence is found for a ‘happiness superiority effect’ when using pictures of human faces (Becker et al., 2011; Byrne &
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Eysenck, 1995; Juth et al., 2005; Williams, Moss, Bradshaw, & Mattingley, 2005) instead of schematic facial stimuli (Eastwood, Smilek, & Merikle, 2001; Fox et al., 2000; Ohman, Lundqvist, & Esteves, 2001; Tipples, Young, Quinlan, Broks, & Ellis, 2002).
Why would humans be more attentive to happy faces? Why is attention more easily attracted towards happy faces? One explanation pertains to low-level perceptual features that are related to emotional faces (e.g. complexity of the face, shape of the eyebrows, shape of the mouth). To investigate whether perceptual features may explain the ‘happiness superiority effect’ in visual search tasks, Becker et al. (2011) carefully designed a series of experiments to rule out the effect of such perceptual factors. Even when controlling for low-level visual confounds, these authors still found evidence for an advantage of happy faces, i.e. higher accuracies and faster RTs. In sum, this study indicated that the emotional valence that is conveyed by a happy face influences performance above and beyond perceptual features that characterize smiling faces, such as the V-shape of the mouth.
The question thus remains: why would happy faces attract more attention? One possibility is that this is due to heightened familiarity with happy faces, making these faces easier to process and leading to better encoding (Baudouin, Gilibert, Sansone, &
Tiberghien, 2000). Although one could argue whether people are most often confronted with happy or neutral faces in daily life. Another explanation for the ‘happy superiority effect’ is that happy faces can be seen as rewarding. Indeed, a recent study comparing the influence of monetary and social reward, i.e. happy faces, in children supports this notion (Kohls, Peltzer, Herpertz-Dahlmann, & Konrad, 2009). These children (age 8-12) performed a go/no-go task paired with social reward, monetary reward, a combination of both, or no reward at all. Results indicated that both social and monetary reward significantly improved performance on the go/no-go task, albeit stronger effects were found for monetary reward. Similar findings have been reported in adults using a social variant of the ‘monetary incentive delay’ (MID) task (Spreckelmeyer et al., 2009). In the classical MID task (Knutson, Westdorp, Kaiser, &
Hommer, 2000) participants are first presented with a cue representing a potential reward, followed by a target stimulus. If their response to this target is fast enough, participants are offered the reward. Levels of potential reward are usually manipulated and are represented by different cues. In the social variant of this task, the social
GENERAL DISCUSSION
171 incentive delay (SID) task , the reward consisted of a smiling face. Although responses were generally faster in the MID task, a significant RT improvement in comparison to the no-reward condition was found in both tasks. Importantly, neural activation in the reward system (e.g. the nucleus accumbens) was increased for both types of reward during the anticipation phase. In sum, these studies (Kohls et al., 2009; Spreckelmeyer et al., 2009) provide evidence for a rewarding effect of happy faces.
Interestingly, in the behavioural study discussed in Chapter 3, the performance improvement for happy faces in the valence task was slightly larger in adolescents compared to adults, although this trend failed to reach significance. These data suggest that the rewarding effect of happy faces is more pronounced in adolescents than adults. This idea is also in line with predictions from neurobiological models of adolescent behavior (Ernst et al., 2006; Somerville & Casey, 2010; Steinberg, 2008), positing increased sensitivity to emotional – especially rewarding – stimuli.
Evidently, given that the differential impact of happy faces in adolescent and adults was only trending, this effect should be interpreted with caution. Furthermore, using the same emotional n-back task in the scanner (Chapter 4), we found that the WM improvement for relevant happy faces was similar in adolescents and adults, thus failing to replicate the trend reported in the behavioural n-back study (Chapter 3). This failure could be due to power issues related to the smaller sample size, differences in task context (in the fMRI scanner versus in a quiet laboratory setting) or age group. Indeed, whereas adolescent participants in the behavioural study were between 12 and 14 years of age, the age range for adolescents in the fMRI study was broader, i.e. between 12 and 16 years of age. Similarly, adults also differed in age between the two studies, i.e. between 18 and 29 (Mage = 21.0) in the behavioural study and between 25 and 35 (Mage = 27.4) years of age in the fMRI study. Of course, this explanation remains speculative and future studies should include several age groups to investigate whether the developmental differences in emotional WM reported in the behavioural study can be replicated, and if so, which age range is most sensitive to happy faces.
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