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Trait anger and the reward positivity
Personality and Individual Differences 144 (2019) 24–30
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Personality and Individual Differences journal homepage: www.elsevier.com/locate/paid
Trait anger and the reward positivity☆ a
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Aliona Tsypes , Douglas Jozef Angus , Stephanie Martin , Kevin Kemkes , Eddie Harmon-Jones a b c
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Department of Psychology, Binghamton University (SUNY), Binghamton, NY, United States School of Psychology, University of Sydney, Sydney, NSW, Australia School of Psychology, The University of New South Wales, Sydney, NSW, Australia
A R T I C LE I N FO
A B S T R A C T
Keywords: ERPs Reward positivity Young adults Reward Approach motivation Anger
Although research shows that affect and motivation-related variables influence the amplitude of the Reward Positivity (RewP) event-related potential (ERP), motivational direction (approach versus avoidance) and affective valence (positive versus negative) have been confounded. As a negatively valenced yet approach motivation-related emotion, anger can be used to tease apart motivational direction versus affective valence contributions to the RewP amplitude. The present study examined the relation between trait anger and RewP. Participants were 98 young adult student volunteers who completed the Doors reward task and self-report questionnaires. Their asymmetric frontal cortical activity during resting baseline was also examined. Results revealed that trait anger was positively correlated with the RewP amplitude. The present study contributes to the literature by providing novel evidence for the link between trait anger and the RewP.
1. Introduction
Krigolson, 2008; Proudfit, 2015). More specifically, empirical evidence consistently shows that reward feedback elicits a positive deflection, which is absent in response to the loss feedback trials and gets added to the “baseline” response that is negative in polarity (Holroyd et al., 2008; Proudfit, 2015). Source-localization and combined EEG-fMRI research demonstrates that the RewP is localized to the anterior cingulate cortex (ACC; e.g., Gehring & Willoughby, 2002; Hauser et al., 2014; Miltner et al., 1997; Smith et al., 2015; Warren, Hyman, Seamans, & Holroyd, 2015) and the striatum (e.g., Foti, Weinberg, Dien, & Hajcak, 2011). Both the ACC and striatum are crucially involved in a broad range of reward-related processes (for a review, see Holroyd & Umemoto, 2016). The RewP generally correlates with selfreport and behavioral measures of reward sensitivity (e.g., Bress & Hajcak, 2013; Lange, Leue, & Beauducel, 2012) and the RewP has been utilized as a psychophysiological measure of initial response to reward. States and traits associated with positive affect and approach motivation relate to a larger RewP, whereas states and traits associated with negative affect and withdrawal motivation relate to a smaller RewP. For example, greater Behavioral Approach System (BAS) sensitivity (Lange et al., 2012), reward sensitivity (Bress & Hajcak, 2013), and extraversion (Cooper, Duke, Pickering, & Smillie, 2014) correlate with larger RewPs. In contrast, greater depressive symptoms and increased risk for depression (Proudfit, 2015) and higher negative
Rewards serve a variety of psychological and behavioral functions. For example, rewards influence learning, motivation, and emotions. Moreover, individuals differ in their responses to rewards, such that those who tend to experience more positive affect and/or are more approach motivated respond more strongly to rewards (e.g., Carver & White, 1994). The present research was designed to build on prior work on reward responsiveness by testing how it relates to individual differences in trait anger. We chose to focus on anger specifically because it provides a way of teasing apart approach motivation from positive affect. We also aimed to investigate reward responsiveness using a wellestablished psychophysiological index of reward responsiveness. We elaborate on these issues below. The reward positivity (RewP) is an event-related potential (ERP) component related to the processing of rewards. It occurs over frontocentral sites approximately 250–300 ms after individuals receive gain versus loss feedback stimuli (Gehring & Willoughby, 2002; Miltner, Braun, & Coles, 1997; Proudfit, 2015). Although the RewP has been referred to as the feedback negativity (FN), feedback-related negativity (FRN), medial-frontal negativity (MFN), and feedback error-related negativity (fERN), scientists have argued that it is more accurate to refer to this component as the RewP (Holroyd, Pakzad-Vaezi, &
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The project was supported by the Australian Research Council grant No. DP150104514 and the National Science Foundation Graduate Research Fellowship grant No. DGE1144464. Declarations of interest: none. ⁎ Corresponding author at: School of Psychology, The University of New South Wales, Sydney, NSW 2052, Australia. E-mail address: [email protected] (E. Harmon-Jones). https://doi.org/10.1016/j.paid.2019.02.030 Received 20 September 2018; Received in revised form 12 December 2018; Accepted 21 February 2019 0191-8869/ © 2019 Elsevier Ltd. All rights reserved.
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baseline would relate to greater trait BAS and trait anger. We also tested whether greater relative left frontal activity during resting baseline would relate to larger RewPs. Based on the empirical evidence that shows that both greater relative left frontal activity and the RewP are associated with approach motivation, we expected that greater relative left frontal activity would be associated with larger RewPs. To our knowledge, no previous research has directly addressed this research question, although related evidence does lend preliminary support to this idea (Schmid, Hackel, Jasperse, & Amodio, 2018). Further, we examined the relation between self-reported trait BAS and trait anger. Past research has revealed that higher levels of trait BAS are associated with higher levels of trait anger (Harmon-Jones, 2003b; Smits & Kuppens, 2005). Thus, we expected to replicate this correlation. Although some prior studies have replicated the patterns of significant correlations among the variables noted above, other research efforts failed to do so. For instance, one study did not find a significant relation between BAS and the RewP (Cooper et al., 2014). Failures to replicate are disheartening and lead some readers to question whether certain effects exist at all. Before drawing this conclusion, we believe it wise to consider the work of Geoff Cumming focused on the issue of replication, such as his demonstration via “the dance of the p values.” More specifically, Cumming conducted a simulation of a large dataset created with two normally distributed experimental conditions differing from each other with an effect size d of 0.50. He then randomly selected 32 cases from each experimental condition and performed a ttest comparison of the two conditions. Over repeated random sampling from the larger dataset, Cumming found that the difference between conditions was not clearly significant (p > .10) in over 35% of the samples. In other words, when a moderately strong effect exists in the population, researchers may only find (or replicate) a significant effect less than two out of three times. The same logic applies to correlational studies. Ultimately, Cumming's simulation demonstrates that randomly selected samples from a population will not always produce the same exact results, even though a “true” effect exists within the population, simply due to random variations in the samples (for more evidence, see Cumming, 2014; Braver, Thoemmes, & Rosenthal, 2014). In line with the compelling arguments to employ competitive hypothesis testing, rather than null hypothesis testing (Gigerenzer, 2018), the present research tests competing hypotheses. Based on past research linking negative affect with smaller RewPs, one could predict that anger should be associated with smaller RewPs, because anger is a negative affect (e.g., Harmon-Jones, Harmon-Jones, Amodio, & Gable, 2011). In contrast, based on past research linking approach motivation with larger RewPs, one could predict that anger should be associated with larger RewPs, because anger is an approach affect (e.g., Carver & Harmon-Jones, 2009; Harmon-Jones, 2003b). We favor the latter hypothesis.
emotionality (Santesso et al., 2012) correlate with smaller RewP magnitudes. In these past studies, motivational direction (approach versus avoidance) and affective valence (positive versus negative) were confounded. That is, positive affective states/traits were associated with approach motivation, whereas negative affective states/traits were associated with avoidance motivation. Thus, despite the important contributions of these past studies, the research makes it impossible to know whether motivational direction or affective valence contributes to the RewP. To separate the contributions of positive affect and approach motivation on a range of responses, previous research has used measures and manipulations of anger. Although anger is a negatively valenced emotion, it is positively related to responses associated with rewards and approach motivation in non-human and human studies (Amodio & Harmon-Jones, 2011; Deater-Deckard et al., 2010; Ford et al., 2010; Harmon-Jones, 2003b; Kazlauckas et al., 2005). The only study to date of which we are aware that had examined a link between anger and RewP found that although participants in anger and neutral emotion induction conditions did not differ in their RewP amplitudes, larger RewP amplitudes were correlated with greater subjective liking of rewards only in the anger induction condition (Angus, Kemkes, Schutter, & Harmon-Jones, 2015). Whereas this past study provides initial support for the idea that anger is related to a larger RewP, the current study aims to further build on this study by testing whether individuals who score higher in trait anger respond with larger RewP amplitudes to a standard RewPevoking task. If such individuals do have larger RewP amplitudes, this will suggest that individuals higher in trait anger are more reward responsive under relatively “normal” conditions even when anger has not been evoked. Moreover, such evidence would build on the initial evidence with state anger and RewP responses to suggest that approach motivation, even when it is negatively valenced, is related to larger RewP amplitudes. The current study is different from Angus et al. (2015) in that Angus et al. (2015) tested the influence of a state induction of anger on the RewP, whereas the current study tests the association of trait anger with the RewP. State and trait emotions may not yield similar associations with other variables (e.g., George, 1991; Kluemper, Little, & DeGroot, 2009; Mustanski, 2007), but when they do, it adds to evidentiary base suggesting that anger, broadly conceived, influences the RewP. That is, anger, regardless of whether it is evoked in the lab or measured as a personality characteristic, may relate to larger RewP amplitudes. Although the primary focus of the current research is the examination of trait anger with the RewP, we also examined asymmetric frontal cortical activity (recorded during resting baseline) and trait BAS sensitivity (assessed via a self-report). These variables were included due to their previously demonstrated associations with anger and other variables related to approach motivation (Carver & White, 1994; Harmon-Jones & Allen, 1997; Harmon-Jones & Allen, 1998; HarmonJones & Sigelman, 2001). Thus, we attempted to replicate these past results. Research shows that activity in the left frontal cortex is associated with approach motivation, whereas activity in the right frontal cortex is associated with avoidance motivation (e.g., Harmon-Jones, 2003a). Much of this research has examined frontal EEG asymmetries, generally quantified as difference in left versus right hemispheric frontal alpha activity. Alpha power is inversely related to cortical activity, such that greater asymmetry scores indicate greater relative left frontal activity. Using this index, prior studies have revealed that greater relative left frontal cortical activity relates to various measures of approach motivation and anger (for a review, see Harmon-Jones, Gable, & Peterson, 2010; Harmon-Jones & Gable, 2018). In addition, self-reported trait BAS has also been shown to relate to a number of variables associated with approach motivation, including greater relative left frontal cortical activity (e.g., Harmon-Jones, Harmon-Jones, & Price, 2013). Consequently, we sought to replicate past results by testing whether greater relative left frontal activity during resting
2. Method 2.1. Participants Participants were 98 young adult student volunteers (ages 18–22) at XXX recruited to participate in exchange for a course credit or a monetary compensation of $15 AUD per hour. In terms of demographic characteristics, 49 (51%) of our sample were female, 49 (50%) selfidentified as Asian, 39 (39.8%) self-identified as Caucasian, 5 (5.1%) self-identified as Arabic, and 5 (5.1%) self-identified as Indian. Participants were right-handed, free of neurological and psychiatric disorders, had no skin condition or scalp damage, and were not taking medications for physical or psychiatric problems. Informed consent was obtained from all of the participants. The study was approved by the UNSW Human Research Ethics Advisory Panel for Psychology.
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from electrodes placed 1 cm lateral to the outer canthi of each eye, and from the sub- and supraorbital regions of the right eye. Brain Vision Analyzer 2.0 was used to process the data off-line. The data were down-sampled to 512 Hz, re-referenced to average earlobes, and filtered (band-pass filter 0.1–30 Hz, 50 Hz notch filter). Eye blinks with aberrant morphology were first removed via visual inspection, with the rest of the blinks corrected via the Gratton, Coles, and Donchin (1983) algorithm. For the RewP, EEG data were segmented beginning at −200 ms before feedback until 1000 ms after feedback. Additional artifacts were rejected automatically (i.e., voltage shift of more than 10 μV per millisecond; epochs with the difference between two values within an interval of 800 ms that exceeded 100 μV). Data of 7 subjects were excluded as they had fewer than 15 artifact-free trails for gain and/or loss feedback, consistent with minimum number of trials guidelines for RewP (Luking, Nelson, Infantolino, Sauder, & Hajcak, 2017). The retained 98 participants had a mean of 27.14 gain trials and a mean of 25.51 loss trials. Baseline correction was performed using 200 ms before feedback onset. Consistent with previous studies and visual examination of the difference wave (Umemoto & Holroyd, 2017), the RewP was scored at 200–320 ms post feedback as the difference between the gain and the loss conditions at FCz. For the resting data, continuous EEG was segmented into 1000 ms epochs of the 4 min of baseline EEG (alternating eyes open/closed). A Fast Fourier transform was performed on all artifact-free segments (extracted through overlapping 50% Hamming windows). The power in alpha frequency band (8–13 Hz) was extracted for the analyses. An asymmetry index was computed by calculating the ln[F4] – ln[F3]. Due to the inverse correlation between alpha power and cortical activity, positive values on this metric indicate greater left-sided activation while negative values indicate greater right-sided activation (e.g., Harmon-Jones & Allen, 1997; Peterson, Shackman, & Harmon-Jones, 2008; Tomarken, Davidson, Wheeler, & Doss, 1992).
2.2. Procedure On arrival, participants were first provided with a brief overview of the study and a consent form. Next, EEG electrodes were attached to the participant and they were asked to sit with their eyes open and then closed (alternating eyes open/closed for 1 min at a time) for a total of 4 min to obtain the baseline resting EEG data. After the completion of the self-report questionnaires, the experimenter explained the reward task by guiding them through two practice trials. Then the experimenter left the room and the participants completed the reward task. Upon the completion of the task, the EEG sensors were removed and the participants were debriefed and given an opportunity to ask questions. They were paid $15 for the completion of the reward task and given course credit (paid participants were paid $15/h). 2.3. Measures 2.3.1. Self-reports Participants completed the BAS questionnaire (α = 0.76 in our sample), which included BAS Drive (α = 0.69 in our sample), BAS Reward Responsiveness (α = 0.70 in our sample), and BAS Fun Seeking (α = 0.64 in our sample) subscales (Carver & White, 1994). The BAS Drive subscale consists of four items and assesses the motivation to pursue desirable things (e.g., “When I want something, I usually go allout to get it”). The BAS Reward Responsiveness subscale consists of five items and assesses the tendency to respond with increases in energy and positive affect during or in anticipation of desirable events (e.g., “When I get something I want, I feel excited and energized; When I see an opportunity for something I like, I get excited right away”). Finally, the BAS Fun Seeking subscale consists of four items and assesses the tendency to engage in impulsive behaviors to engage in desirable opportunities (e.g., “I will often do things for no other reason than that they might be fun”). Participants also completed the Buss and Perry (1992) Aggression questionnaire Anger subscale (α = 0.84 in the present sample), which consists of seven items and assesses one's propensity for anger (e.g., “I have trouble controlling my temper; Some friends think I am a hothead”).
3. Results RewP amplitudes to gains (M = 17.06; SD = 8.06) were significantly more positive than RewP amplitudes to losses (M = 8.73; SD = 5.82; t(97) = 14.69, p < .001; see Fig. 1). Consistent with the primary hypothesis, trait anger was positively correlated with the RewP difference score (r = 0.21, p = .04). See Fig. 2 for a scatterplot. When gains and losses were examined separately, trait anger correlated marginally significantly with responses to gains (r = 0.19, p = .07), but not with responses to losses (r = 0.06, p = .58). Replicating prior research, trait anger was positively correlated with relative left frontal activity at rest and BAS Total. Relative left frontal activity at rest and BAS Total were not significantly correlated with the RewP. Descriptive statistics of and correlations between variables are reported in Table 1.1
2.3.2. Doors task The task consisted of 60 trials and has been used in ERP studies of reward processing (e.g., Angus et al., 2015; Bress, Meyer, & Hajcak, 2015; Bress, Smith, Foti, Klein, & Hajcak, 2012; Foti et al., 2011; Kujawa, Proudfit, & Klein, 2014; Mühlberger, Angus, Jonas, HarmonJones, & Harmon-Jones, 2017; Nelson, Perlman, Klein, Kotov, & Hajcak, 2016; Tsypes, Owens, Hajcak, & Gibb, 2017; Weinberg, Liu, Hajcak, & Shankman, 2015). On each trial, participants were shown two doors and were asked to click the right or the left arrow button to make a guess which door had a monetary prize behind it. They were informed on each trial that they could either win $0.50, as indicated by a green up-arrow, or lose $0.25, as indicated by a red down-arrow. Participants were informed that they would receive their winnings at the end of the session. Consistent with prior studies that utilized the same task, the outcome of each trial was predetermined to be 50/50, with 30 trials being loss and 30 trails being gain trials, presented in pseudorandom order. Feedback about having chosen correctly or incorrectly was presented for 2000 ms, after a 500 ms-long fixation cross following each door selection.
4. Discussion In a novel contribution, the present study revealed that trait anger was positively related to the RewP amplitude in response to gain versus loss feedback. When neural responses to gains and losses were examined separately, the findings suggested that responses to gains, rather than responses to losses, were more closely linked with trait anger (although caution is advised due to only marginally statistically significant correlation between neural responses to gains and trait anger).
2.3.3. EEG recording and data reduction EEG was recorded via Actiview (version 6, BioSemi) at F3, F4, FPz, AFz, Fz, FCz, Cz, CPz, Pz, POz, Oz, and Iz, using Ag/AgCL-tipped electrodes. Data were amplified and sampled at 2048 Hz by a BioSemi Active Two System and referenced to the common mode sense (CMS). The ground consisted of the CMS active and passive driven right leg (DRL) electrode. Electrodes were placed on the left and right earlobes for offline re-referencing. The electrooculogram (EOG) was recorded
1
Replicating prior research, trait anger was positively correlated with relative left frontal activity at rest (r = 0.27, p = .008), BAS Drive (r = 0.31, p = .002), and BAS Reward Responsiveness (r = 0.36, p < .001). BAS Drive was also positively correlated with relative left frontal activity at rest (r = 0.22, p = .029). 26
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Fig. 1. (Top) Stimulus-locked event-related potentials to feedback indicating monetary gain, loss, and the difference waveform for gain minus loss trials at FCz. (Bottom) Topographic scalp map for the RewP scored as the gain minus loss trials at 200–320 ms post feedback, at F3, F4, FPz, AFz, Fz, FCz, Cz, CPz, Pz, POz, Oz, and Iz. See the online article for the color version of this figure.
Fig. 2. Scatter plot of reward positivity (RewP) amplitude over FCz as a function of self-reported trait anger. The plot includes line of best fit.
Lange et al., 2012). The approach motivation associated with anger likely explains the current results, because if the negative affect of anger were the primary contributor to RewP, anger would have been negatively rather than positively related to RewP. Consistent with the idea that anger is associated with approach motivation, in the current study, trait anger positively correlated with relative left frontal cortical activity and trait BAS. These results
Prior studies with the Doors task have primarily focused on using the RewP/FN difference score, calculated as gains minus losses and losses minus gains, respectively, as an index of reward responsiveness. More specifically, it is the differentiation between responses to gains versus responses to losses, rather than to only gains or losses considered separately, that has been most consistently linked with self-report and behavioral measures of reward sensitivity (e.g., Bress & Hajcak, 2013; 27
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population effect size. Moreover, including this study in the literature will assist in avoiding the publication bias that has harmed the field and likely contributed to the reproducibility crisis in science. Following the recommendations of Gigerenzer (2018), the present study employed competitive hypothesis testing. Indeed, the competitive hypothesis – that negative affect contributes to a smaller RewP – would have predicted a correlation of −0.2 to −0.3 (the magnitude of this predicted correlation is based on the average effect sizes noted above). The fact that our prediction and results indicated a positive correlation provides evidence along the lines Gigerenzer (2018) recommends. Indeed, the “p value” comparing the obtained correlation (+0.21) against the competitively predicted correlation (−0.20 to −0.30) would likely be less than 0.005 (i.e., a test of two r values from independent samples [+0.21 and − 0.21] gives a z = 2.94, p = .003). Although both RewP and frontal alpha asymmetry correlated with trait anger, they did not correlate significantly with one another. It is difficult to know how to interpret null findings. A variety of uncontrolled variables in the situation could cause a failure to replicate. For example, researchers often regard relative left frontal activity at resting baseline as a trait measure, but research has found that roughly half of the variance in this measure is the result of state influences (Hagemann, Naumann, Thayer, & Bartussek, 2002; Hagemann, Hewig, Seifert, Naumann, & Bartussek, 2005). Along these lines, past research found that relative left frontal activity at resting baseline is influenced by time of year and time of day (Peterson & Harmon-Jones, 2009) and a variety of characteristics associated with interactions with the experimenter (Blackhart, Kline, Donohue, LaRowe, & Joiner, 2002; Wacker, Mueller, Pizzagalli, Hennig, & Stemmler, 2013). Similarly, with regard to the measurement of self-reported traits, some research has revealed that situational manipulations can influence scores on self-reported traits (e.g., Summerell et al., 2019), suggesting that self-reported traits can also be at least partially the result of state influences. Another possible explanation for the lack of a significant correlation between frontal asymmetry and RewP is the differences in the tasks used to measure these variables. That is, frontal alpha asymmetry was measured during a resting baseline session and RewP was measured during reward processing. Based on a review of the inconsistencies in results with resting baseline frontal asymmetry, Coan, Allen, and McKnight (2006) proposed a capability model of asymmetric frontal cortical activity that posited that individual differences in frontal asymmetry should be examined under specific situations that demand emotional responses. In addition, the current study did not find trait BAS to be significantly related to the RewP. The past research with significant correlations between BAS and RewP found that they were only moderately correlated (r of 0.33 with 55 participants in Bress & Hajcak, 2013; and r of 0.22 to 0.26 in Lange et al., 2012 with 85 participants). The likelihood of replicating a medium-sized effect according to the standard of p < .05 is only 50% in the long run with power of 0.50 and only 68% with power of 0.80 (Cumming, 2014). The previous BAS-RewP studies observed small to medium effect sizes. Thus, the most likely reason for failures to replicate is the small effect size. With small effects, the sampling will make a large difference on the obtained results. Some samplings from the population may include individuals who have a reliable relation between trait BAS and the RewP, whereas other samplings may not. Other factors that influence the strength of the relation between measurements include the validity of the hypothetical constructs and the several sources of measurement error associated with both self-reported trait BAS and the RewP. The present results have implications for the Research Domain Criteria (RDoC; Cuthbert, 2014). Our findings suggest that the RDoC should emphasize approach motivation tendencies as separate from positive emotionality/valence (Nusslock, Walden, & Harmon-Jones, 2015). Indeed, evidence shows that despite its negative valence, anger constitutes an approach-oriented emotion (Carver & Harmon-Jones, 2009; Harmon-Jones et al., 2010; Harmon-Jones et al., 2013). Along
Table 1 Descriptive statistics and Pearson correlations between the variables examined.
1. 2. 3. 4.
RewP Anger BAS total Asymmetry
M (SD)
1
2
3
8.32 (5.61) 16.20 (5.40) 39.60 (4.63) 0.08 (0.10)
0.21⁎ −0.003 0.09
0.36⁎⁎ 0.27⁎⁎
0.17⁎
Note. M = Mean. SD = Standard deviation. RewP = Reward positivity. Anger = Buss-Perry anger subscale. BAS Total = Behavior Activation Scale total score. Asymmetry = resting frontal alpha asymmetry. ⁎⁎ p < .01. ⁎ p < .05.
replicate prior studies (for a review, see Harmon-Jones et al., 2010; Harmon-Jones & Gable, 2018). These results also suggest that the current sample did not differ from previous samples in ways that might reduce the correlation of trait anger with relative left frontal cortical activity and trait BAS. We believe this is especially noteworthy because the current sample included mostly Asian individuals, whereas previous samples have included mostly European American individuals. We should note, however, that the restricted electrode set used in the present study did not allow for a test of whether the asymmetry effects were specific to the frontal regions or involved other regions as well. Together with the results of an earlier experiment (Angus et al., 2015), our findings suggest that anger, which is approach oriented but negative in valence, contributes to a larger RewP. These results suggest that approach motivation rather than positive affect per se contributes to a larger RewP. Future research is needed that manipulates the intensity of approach motivation within positive affect to further test whether positive affect contributes to the RewP independently of approach motivation (for examples, see Harmon-Jones, Harmon-Jones, Fearn, Sigelman, & Johnson, 2008; Price, Hortensius, & Harmon-Jones, 2013). Although Angus et al. (2015) found state anger to influence the RewP, they did not find a significant correlation between trait anger and the RewP. Null effects are always difficult to interpret, but we speculate that perhaps Angus et al. (2015) did not find a significant correlation between trait anger and the RewP because that study used a strong situational manipulation of anger (and neutral affect). That is, bodily expressions, autobiographical recall, and music were used to induce anger and neutral affect. As such, the strong situation may have overwhelmed the influence of the personality characteristic of anger (for an early review of the interaction of strong vs. weak situations with personality characteristics, see Snyder & Ickes, 1985). Along these lines, Lissek, Pine, and Grillon (2006) discussed how strong situations evoking anxiety may eliminate differences between low and high anxious individuals on psychobiological measures. In terms of concerns about the present research, the correlation between trait anger and the RewP, although significant by conventional standards, was not large. That is, the r value of the relationship between anger and RewP was 0.21. This value, however, is similar to the value obtained from a meta-analysis of the relations between depression and asymmetric frontal alpha power (Thibodeau, Jorgenson, & Kim, 2006), as well as to the average published effect size observed in a metaanalysis of a wide range of personality research (Fraley & Marks, 2007). [We are unaware of a meta-analysis of the correlation between the RewP and personality variables]. The meta-analysis on the relation between depression and asymmetric frontal alpha power (Thibodeau et al., 2006) reported an effect size r of 0.26. However, based on a funnel plot, the authors concluded (p. 724) that, “A systematic publication bias in favor of significant results might have inflated effect size estimates we report….” because “small samples yielded more large effects than small effects.” The present study had a relatively large sample, so it is likely to be estimating an effect size closer to the 28
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with other work suggesting that it is approach and reward-related motivation rather than hedonically positive emotion that is most central to the RDoC Positive Valence Systems (Nusslock et al., 2015), the Positive Valence Systems domain might be more accurately named “Approach Motivation and Reward Systems.” The present study contributes to the literature by providing novel evidence for the link between trait anger and the RewP. Together with other recent research (Angus et al., 2015; Mühlberger et al., 2017), it adds to a growing body of evidence that suggests that approach motivation independent of affective valence may contribute to the RewP. Such research has implications for understanding the structure and function of the broad dimensions of motivational direction and affective valence as well as personality and clinical issues related to these dimensions.
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Contents lists available at ScienceDirect
Personality and Individual Differences journal homepage: www.elsevier.com/locate/paid
Trait anger and the reward positivity☆ a
b
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Aliona Tsypes , Douglas Jozef Angus , Stephanie Martin , Kevin Kemkes , Eddie Harmon-Jones a b c
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Department of Psychology, Binghamton University (SUNY), Binghamton, NY, United States School of Psychology, University of Sydney, Sydney, NSW, Australia School of Psychology, The University of New South Wales, Sydney, NSW, Australia
A R T I C LE I N FO
A B S T R A C T
Keywords: ERPs Reward positivity Young adults Reward Approach motivation Anger
Although research shows that affect and motivation-related variables influence the amplitude of the Reward Positivity (RewP) event-related potential (ERP), motivational direction (approach versus avoidance) and affective valence (positive versus negative) have been confounded. As a negatively valenced yet approach motivation-related emotion, anger can be used to tease apart motivational direction versus affective valence contributions to the RewP amplitude. The present study examined the relation between trait anger and RewP. Participants were 98 young adult student volunteers who completed the Doors reward task and self-report questionnaires. Their asymmetric frontal cortical activity during resting baseline was also examined. Results revealed that trait anger was positively correlated with the RewP amplitude. The present study contributes to the literature by providing novel evidence for the link between trait anger and the RewP.
1. Introduction
Krigolson, 2008; Proudfit, 2015). More specifically, empirical evidence consistently shows that reward feedback elicits a positive deflection, which is absent in response to the loss feedback trials and gets added to the “baseline” response that is negative in polarity (Holroyd et al., 2008; Proudfit, 2015). Source-localization and combined EEG-fMRI research demonstrates that the RewP is localized to the anterior cingulate cortex (ACC; e.g., Gehring & Willoughby, 2002; Hauser et al., 2014; Miltner et al., 1997; Smith et al., 2015; Warren, Hyman, Seamans, & Holroyd, 2015) and the striatum (e.g., Foti, Weinberg, Dien, & Hajcak, 2011). Both the ACC and striatum are crucially involved in a broad range of reward-related processes (for a review, see Holroyd & Umemoto, 2016). The RewP generally correlates with selfreport and behavioral measures of reward sensitivity (e.g., Bress & Hajcak, 2013; Lange, Leue, & Beauducel, 2012) and the RewP has been utilized as a psychophysiological measure of initial response to reward. States and traits associated with positive affect and approach motivation relate to a larger RewP, whereas states and traits associated with negative affect and withdrawal motivation relate to a smaller RewP. For example, greater Behavioral Approach System (BAS) sensitivity (Lange et al., 2012), reward sensitivity (Bress & Hajcak, 2013), and extraversion (Cooper, Duke, Pickering, & Smillie, 2014) correlate with larger RewPs. In contrast, greater depressive symptoms and increased risk for depression (Proudfit, 2015) and higher negative
Rewards serve a variety of psychological and behavioral functions. For example, rewards influence learning, motivation, and emotions. Moreover, individuals differ in their responses to rewards, such that those who tend to experience more positive affect and/or are more approach motivated respond more strongly to rewards (e.g., Carver & White, 1994). The present research was designed to build on prior work on reward responsiveness by testing how it relates to individual differences in trait anger. We chose to focus on anger specifically because it provides a way of teasing apart approach motivation from positive affect. We also aimed to investigate reward responsiveness using a wellestablished psychophysiological index of reward responsiveness. We elaborate on these issues below. The reward positivity (RewP) is an event-related potential (ERP) component related to the processing of rewards. It occurs over frontocentral sites approximately 250–300 ms after individuals receive gain versus loss feedback stimuli (Gehring & Willoughby, 2002; Miltner, Braun, & Coles, 1997; Proudfit, 2015). Although the RewP has been referred to as the feedback negativity (FN), feedback-related negativity (FRN), medial-frontal negativity (MFN), and feedback error-related negativity (fERN), scientists have argued that it is more accurate to refer to this component as the RewP (Holroyd, Pakzad-Vaezi, &
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The project was supported by the Australian Research Council grant No. DP150104514 and the National Science Foundation Graduate Research Fellowship grant No. DGE1144464. Declarations of interest: none. ⁎ Corresponding author at: School of Psychology, The University of New South Wales, Sydney, NSW 2052, Australia. E-mail address: [email protected] (E. Harmon-Jones). https://doi.org/10.1016/j.paid.2019.02.030 Received 20 September 2018; Received in revised form 12 December 2018; Accepted 21 February 2019 0191-8869/ © 2019 Elsevier Ltd. All rights reserved.
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baseline would relate to greater trait BAS and trait anger. We also tested whether greater relative left frontal activity during resting baseline would relate to larger RewPs. Based on the empirical evidence that shows that both greater relative left frontal activity and the RewP are associated with approach motivation, we expected that greater relative left frontal activity would be associated with larger RewPs. To our knowledge, no previous research has directly addressed this research question, although related evidence does lend preliminary support to this idea (Schmid, Hackel, Jasperse, & Amodio, 2018). Further, we examined the relation between self-reported trait BAS and trait anger. Past research has revealed that higher levels of trait BAS are associated with higher levels of trait anger (Harmon-Jones, 2003b; Smits & Kuppens, 2005). Thus, we expected to replicate this correlation. Although some prior studies have replicated the patterns of significant correlations among the variables noted above, other research efforts failed to do so. For instance, one study did not find a significant relation between BAS and the RewP (Cooper et al., 2014). Failures to replicate are disheartening and lead some readers to question whether certain effects exist at all. Before drawing this conclusion, we believe it wise to consider the work of Geoff Cumming focused on the issue of replication, such as his demonstration via “the dance of the p values.” More specifically, Cumming conducted a simulation of a large dataset created with two normally distributed experimental conditions differing from each other with an effect size d of 0.50. He then randomly selected 32 cases from each experimental condition and performed a ttest comparison of the two conditions. Over repeated random sampling from the larger dataset, Cumming found that the difference between conditions was not clearly significant (p > .10) in over 35% of the samples. In other words, when a moderately strong effect exists in the population, researchers may only find (or replicate) a significant effect less than two out of three times. The same logic applies to correlational studies. Ultimately, Cumming's simulation demonstrates that randomly selected samples from a population will not always produce the same exact results, even though a “true” effect exists within the population, simply due to random variations in the samples (for more evidence, see Cumming, 2014; Braver, Thoemmes, & Rosenthal, 2014). In line with the compelling arguments to employ competitive hypothesis testing, rather than null hypothesis testing (Gigerenzer, 2018), the present research tests competing hypotheses. Based on past research linking negative affect with smaller RewPs, one could predict that anger should be associated with smaller RewPs, because anger is a negative affect (e.g., Harmon-Jones, Harmon-Jones, Amodio, & Gable, 2011). In contrast, based on past research linking approach motivation with larger RewPs, one could predict that anger should be associated with larger RewPs, because anger is an approach affect (e.g., Carver & Harmon-Jones, 2009; Harmon-Jones, 2003b). We favor the latter hypothesis.
emotionality (Santesso et al., 2012) correlate with smaller RewP magnitudes. In these past studies, motivational direction (approach versus avoidance) and affective valence (positive versus negative) were confounded. That is, positive affective states/traits were associated with approach motivation, whereas negative affective states/traits were associated with avoidance motivation. Thus, despite the important contributions of these past studies, the research makes it impossible to know whether motivational direction or affective valence contributes to the RewP. To separate the contributions of positive affect and approach motivation on a range of responses, previous research has used measures and manipulations of anger. Although anger is a negatively valenced emotion, it is positively related to responses associated with rewards and approach motivation in non-human and human studies (Amodio & Harmon-Jones, 2011; Deater-Deckard et al., 2010; Ford et al., 2010; Harmon-Jones, 2003b; Kazlauckas et al., 2005). The only study to date of which we are aware that had examined a link between anger and RewP found that although participants in anger and neutral emotion induction conditions did not differ in their RewP amplitudes, larger RewP amplitudes were correlated with greater subjective liking of rewards only in the anger induction condition (Angus, Kemkes, Schutter, & Harmon-Jones, 2015). Whereas this past study provides initial support for the idea that anger is related to a larger RewP, the current study aims to further build on this study by testing whether individuals who score higher in trait anger respond with larger RewP amplitudes to a standard RewPevoking task. If such individuals do have larger RewP amplitudes, this will suggest that individuals higher in trait anger are more reward responsive under relatively “normal” conditions even when anger has not been evoked. Moreover, such evidence would build on the initial evidence with state anger and RewP responses to suggest that approach motivation, even when it is negatively valenced, is related to larger RewP amplitudes. The current study is different from Angus et al. (2015) in that Angus et al. (2015) tested the influence of a state induction of anger on the RewP, whereas the current study tests the association of trait anger with the RewP. State and trait emotions may not yield similar associations with other variables (e.g., George, 1991; Kluemper, Little, & DeGroot, 2009; Mustanski, 2007), but when they do, it adds to evidentiary base suggesting that anger, broadly conceived, influences the RewP. That is, anger, regardless of whether it is evoked in the lab or measured as a personality characteristic, may relate to larger RewP amplitudes. Although the primary focus of the current research is the examination of trait anger with the RewP, we also examined asymmetric frontal cortical activity (recorded during resting baseline) and trait BAS sensitivity (assessed via a self-report). These variables were included due to their previously demonstrated associations with anger and other variables related to approach motivation (Carver & White, 1994; Harmon-Jones & Allen, 1997; Harmon-Jones & Allen, 1998; HarmonJones & Sigelman, 2001). Thus, we attempted to replicate these past results. Research shows that activity in the left frontal cortex is associated with approach motivation, whereas activity in the right frontal cortex is associated with avoidance motivation (e.g., Harmon-Jones, 2003a). Much of this research has examined frontal EEG asymmetries, generally quantified as difference in left versus right hemispheric frontal alpha activity. Alpha power is inversely related to cortical activity, such that greater asymmetry scores indicate greater relative left frontal activity. Using this index, prior studies have revealed that greater relative left frontal cortical activity relates to various measures of approach motivation and anger (for a review, see Harmon-Jones, Gable, & Peterson, 2010; Harmon-Jones & Gable, 2018). In addition, self-reported trait BAS has also been shown to relate to a number of variables associated with approach motivation, including greater relative left frontal cortical activity (e.g., Harmon-Jones, Harmon-Jones, & Price, 2013). Consequently, we sought to replicate past results by testing whether greater relative left frontal activity during resting
2. Method 2.1. Participants Participants were 98 young adult student volunteers (ages 18–22) at XXX recruited to participate in exchange for a course credit or a monetary compensation of $15 AUD per hour. In terms of demographic characteristics, 49 (51%) of our sample were female, 49 (50%) selfidentified as Asian, 39 (39.8%) self-identified as Caucasian, 5 (5.1%) self-identified as Arabic, and 5 (5.1%) self-identified as Indian. Participants were right-handed, free of neurological and psychiatric disorders, had no skin condition or scalp damage, and were not taking medications for physical or psychiatric problems. Informed consent was obtained from all of the participants. The study was approved by the UNSW Human Research Ethics Advisory Panel for Psychology.
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from electrodes placed 1 cm lateral to the outer canthi of each eye, and from the sub- and supraorbital regions of the right eye. Brain Vision Analyzer 2.0 was used to process the data off-line. The data were down-sampled to 512 Hz, re-referenced to average earlobes, and filtered (band-pass filter 0.1–30 Hz, 50 Hz notch filter). Eye blinks with aberrant morphology were first removed via visual inspection, with the rest of the blinks corrected via the Gratton, Coles, and Donchin (1983) algorithm. For the RewP, EEG data were segmented beginning at −200 ms before feedback until 1000 ms after feedback. Additional artifacts were rejected automatically (i.e., voltage shift of more than 10 μV per millisecond; epochs with the difference between two values within an interval of 800 ms that exceeded 100 μV). Data of 7 subjects were excluded as they had fewer than 15 artifact-free trails for gain and/or loss feedback, consistent with minimum number of trials guidelines for RewP (Luking, Nelson, Infantolino, Sauder, & Hajcak, 2017). The retained 98 participants had a mean of 27.14 gain trials and a mean of 25.51 loss trials. Baseline correction was performed using 200 ms before feedback onset. Consistent with previous studies and visual examination of the difference wave (Umemoto & Holroyd, 2017), the RewP was scored at 200–320 ms post feedback as the difference between the gain and the loss conditions at FCz. For the resting data, continuous EEG was segmented into 1000 ms epochs of the 4 min of baseline EEG (alternating eyes open/closed). A Fast Fourier transform was performed on all artifact-free segments (extracted through overlapping 50% Hamming windows). The power in alpha frequency band (8–13 Hz) was extracted for the analyses. An asymmetry index was computed by calculating the ln[F4] – ln[F3]. Due to the inverse correlation between alpha power and cortical activity, positive values on this metric indicate greater left-sided activation while negative values indicate greater right-sided activation (e.g., Harmon-Jones & Allen, 1997; Peterson, Shackman, & Harmon-Jones, 2008; Tomarken, Davidson, Wheeler, & Doss, 1992).
2.2. Procedure On arrival, participants were first provided with a brief overview of the study and a consent form. Next, EEG electrodes were attached to the participant and they were asked to sit with their eyes open and then closed (alternating eyes open/closed for 1 min at a time) for a total of 4 min to obtain the baseline resting EEG data. After the completion of the self-report questionnaires, the experimenter explained the reward task by guiding them through two practice trials. Then the experimenter left the room and the participants completed the reward task. Upon the completion of the task, the EEG sensors were removed and the participants were debriefed and given an opportunity to ask questions. They were paid $15 for the completion of the reward task and given course credit (paid participants were paid $15/h). 2.3. Measures 2.3.1. Self-reports Participants completed the BAS questionnaire (α = 0.76 in our sample), which included BAS Drive (α = 0.69 in our sample), BAS Reward Responsiveness (α = 0.70 in our sample), and BAS Fun Seeking (α = 0.64 in our sample) subscales (Carver & White, 1994). The BAS Drive subscale consists of four items and assesses the motivation to pursue desirable things (e.g., “When I want something, I usually go allout to get it”). The BAS Reward Responsiveness subscale consists of five items and assesses the tendency to respond with increases in energy and positive affect during or in anticipation of desirable events (e.g., “When I get something I want, I feel excited and energized; When I see an opportunity for something I like, I get excited right away”). Finally, the BAS Fun Seeking subscale consists of four items and assesses the tendency to engage in impulsive behaviors to engage in desirable opportunities (e.g., “I will often do things for no other reason than that they might be fun”). Participants also completed the Buss and Perry (1992) Aggression questionnaire Anger subscale (α = 0.84 in the present sample), which consists of seven items and assesses one's propensity for anger (e.g., “I have trouble controlling my temper; Some friends think I am a hothead”).
3. Results RewP amplitudes to gains (M = 17.06; SD = 8.06) were significantly more positive than RewP amplitudes to losses (M = 8.73; SD = 5.82; t(97) = 14.69, p < .001; see Fig. 1). Consistent with the primary hypothesis, trait anger was positively correlated with the RewP difference score (r = 0.21, p = .04). See Fig. 2 for a scatterplot. When gains and losses were examined separately, trait anger correlated marginally significantly with responses to gains (r = 0.19, p = .07), but not with responses to losses (r = 0.06, p = .58). Replicating prior research, trait anger was positively correlated with relative left frontal activity at rest and BAS Total. Relative left frontal activity at rest and BAS Total were not significantly correlated with the RewP. Descriptive statistics of and correlations between variables are reported in Table 1.1
2.3.2. Doors task The task consisted of 60 trials and has been used in ERP studies of reward processing (e.g., Angus et al., 2015; Bress, Meyer, & Hajcak, 2015; Bress, Smith, Foti, Klein, & Hajcak, 2012; Foti et al., 2011; Kujawa, Proudfit, & Klein, 2014; Mühlberger, Angus, Jonas, HarmonJones, & Harmon-Jones, 2017; Nelson, Perlman, Klein, Kotov, & Hajcak, 2016; Tsypes, Owens, Hajcak, & Gibb, 2017; Weinberg, Liu, Hajcak, & Shankman, 2015). On each trial, participants were shown two doors and were asked to click the right or the left arrow button to make a guess which door had a monetary prize behind it. They were informed on each trial that they could either win $0.50, as indicated by a green up-arrow, or lose $0.25, as indicated by a red down-arrow. Participants were informed that they would receive their winnings at the end of the session. Consistent with prior studies that utilized the same task, the outcome of each trial was predetermined to be 50/50, with 30 trials being loss and 30 trails being gain trials, presented in pseudorandom order. Feedback about having chosen correctly or incorrectly was presented for 2000 ms, after a 500 ms-long fixation cross following each door selection.
4. Discussion In a novel contribution, the present study revealed that trait anger was positively related to the RewP amplitude in response to gain versus loss feedback. When neural responses to gains and losses were examined separately, the findings suggested that responses to gains, rather than responses to losses, were more closely linked with trait anger (although caution is advised due to only marginally statistically significant correlation between neural responses to gains and trait anger).
2.3.3. EEG recording and data reduction EEG was recorded via Actiview (version 6, BioSemi) at F3, F4, FPz, AFz, Fz, FCz, Cz, CPz, Pz, POz, Oz, and Iz, using Ag/AgCL-tipped electrodes. Data were amplified and sampled at 2048 Hz by a BioSemi Active Two System and referenced to the common mode sense (CMS). The ground consisted of the CMS active and passive driven right leg (DRL) electrode. Electrodes were placed on the left and right earlobes for offline re-referencing. The electrooculogram (EOG) was recorded
1
Replicating prior research, trait anger was positively correlated with relative left frontal activity at rest (r = 0.27, p = .008), BAS Drive (r = 0.31, p = .002), and BAS Reward Responsiveness (r = 0.36, p < .001). BAS Drive was also positively correlated with relative left frontal activity at rest (r = 0.22, p = .029). 26
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Fig. 1. (Top) Stimulus-locked event-related potentials to feedback indicating monetary gain, loss, and the difference waveform for gain minus loss trials at FCz. (Bottom) Topographic scalp map for the RewP scored as the gain minus loss trials at 200–320 ms post feedback, at F3, F4, FPz, AFz, Fz, FCz, Cz, CPz, Pz, POz, Oz, and Iz. See the online article for the color version of this figure.
Fig. 2. Scatter plot of reward positivity (RewP) amplitude over FCz as a function of self-reported trait anger. The plot includes line of best fit.
Lange et al., 2012). The approach motivation associated with anger likely explains the current results, because if the negative affect of anger were the primary contributor to RewP, anger would have been negatively rather than positively related to RewP. Consistent with the idea that anger is associated with approach motivation, in the current study, trait anger positively correlated with relative left frontal cortical activity and trait BAS. These results
Prior studies with the Doors task have primarily focused on using the RewP/FN difference score, calculated as gains minus losses and losses minus gains, respectively, as an index of reward responsiveness. More specifically, it is the differentiation between responses to gains versus responses to losses, rather than to only gains or losses considered separately, that has been most consistently linked with self-report and behavioral measures of reward sensitivity (e.g., Bress & Hajcak, 2013; 27
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population effect size. Moreover, including this study in the literature will assist in avoiding the publication bias that has harmed the field and likely contributed to the reproducibility crisis in science. Following the recommendations of Gigerenzer (2018), the present study employed competitive hypothesis testing. Indeed, the competitive hypothesis – that negative affect contributes to a smaller RewP – would have predicted a correlation of −0.2 to −0.3 (the magnitude of this predicted correlation is based on the average effect sizes noted above). The fact that our prediction and results indicated a positive correlation provides evidence along the lines Gigerenzer (2018) recommends. Indeed, the “p value” comparing the obtained correlation (+0.21) against the competitively predicted correlation (−0.20 to −0.30) would likely be less than 0.005 (i.e., a test of two r values from independent samples [+0.21 and − 0.21] gives a z = 2.94, p = .003). Although both RewP and frontal alpha asymmetry correlated with trait anger, they did not correlate significantly with one another. It is difficult to know how to interpret null findings. A variety of uncontrolled variables in the situation could cause a failure to replicate. For example, researchers often regard relative left frontal activity at resting baseline as a trait measure, but research has found that roughly half of the variance in this measure is the result of state influences (Hagemann, Naumann, Thayer, & Bartussek, 2002; Hagemann, Hewig, Seifert, Naumann, & Bartussek, 2005). Along these lines, past research found that relative left frontal activity at resting baseline is influenced by time of year and time of day (Peterson & Harmon-Jones, 2009) and a variety of characteristics associated with interactions with the experimenter (Blackhart, Kline, Donohue, LaRowe, & Joiner, 2002; Wacker, Mueller, Pizzagalli, Hennig, & Stemmler, 2013). Similarly, with regard to the measurement of self-reported traits, some research has revealed that situational manipulations can influence scores on self-reported traits (e.g., Summerell et al., 2019), suggesting that self-reported traits can also be at least partially the result of state influences. Another possible explanation for the lack of a significant correlation between frontal asymmetry and RewP is the differences in the tasks used to measure these variables. That is, frontal alpha asymmetry was measured during a resting baseline session and RewP was measured during reward processing. Based on a review of the inconsistencies in results with resting baseline frontal asymmetry, Coan, Allen, and McKnight (2006) proposed a capability model of asymmetric frontal cortical activity that posited that individual differences in frontal asymmetry should be examined under specific situations that demand emotional responses. In addition, the current study did not find trait BAS to be significantly related to the RewP. The past research with significant correlations between BAS and RewP found that they were only moderately correlated (r of 0.33 with 55 participants in Bress & Hajcak, 2013; and r of 0.22 to 0.26 in Lange et al., 2012 with 85 participants). The likelihood of replicating a medium-sized effect according to the standard of p < .05 is only 50% in the long run with power of 0.50 and only 68% with power of 0.80 (Cumming, 2014). The previous BAS-RewP studies observed small to medium effect sizes. Thus, the most likely reason for failures to replicate is the small effect size. With small effects, the sampling will make a large difference on the obtained results. Some samplings from the population may include individuals who have a reliable relation between trait BAS and the RewP, whereas other samplings may not. Other factors that influence the strength of the relation between measurements include the validity of the hypothetical constructs and the several sources of measurement error associated with both self-reported trait BAS and the RewP. The present results have implications for the Research Domain Criteria (RDoC; Cuthbert, 2014). Our findings suggest that the RDoC should emphasize approach motivation tendencies as separate from positive emotionality/valence (Nusslock, Walden, & Harmon-Jones, 2015). Indeed, evidence shows that despite its negative valence, anger constitutes an approach-oriented emotion (Carver & Harmon-Jones, 2009; Harmon-Jones et al., 2010; Harmon-Jones et al., 2013). Along
Table 1 Descriptive statistics and Pearson correlations between the variables examined.
1. 2. 3. 4.
RewP Anger BAS total Asymmetry
M (SD)
1
2
3
8.32 (5.61) 16.20 (5.40) 39.60 (4.63) 0.08 (0.10)
0.21⁎ −0.003 0.09
0.36⁎⁎ 0.27⁎⁎
0.17⁎
Note. M = Mean. SD = Standard deviation. RewP = Reward positivity. Anger = Buss-Perry anger subscale. BAS Total = Behavior Activation Scale total score. Asymmetry = resting frontal alpha asymmetry. ⁎⁎ p < .01. ⁎ p < .05.
replicate prior studies (for a review, see Harmon-Jones et al., 2010; Harmon-Jones & Gable, 2018). These results also suggest that the current sample did not differ from previous samples in ways that might reduce the correlation of trait anger with relative left frontal cortical activity and trait BAS. We believe this is especially noteworthy because the current sample included mostly Asian individuals, whereas previous samples have included mostly European American individuals. We should note, however, that the restricted electrode set used in the present study did not allow for a test of whether the asymmetry effects were specific to the frontal regions or involved other regions as well. Together with the results of an earlier experiment (Angus et al., 2015), our findings suggest that anger, which is approach oriented but negative in valence, contributes to a larger RewP. These results suggest that approach motivation rather than positive affect per se contributes to a larger RewP. Future research is needed that manipulates the intensity of approach motivation within positive affect to further test whether positive affect contributes to the RewP independently of approach motivation (for examples, see Harmon-Jones, Harmon-Jones, Fearn, Sigelman, & Johnson, 2008; Price, Hortensius, & Harmon-Jones, 2013). Although Angus et al. (2015) found state anger to influence the RewP, they did not find a significant correlation between trait anger and the RewP. Null effects are always difficult to interpret, but we speculate that perhaps Angus et al. (2015) did not find a significant correlation between trait anger and the RewP because that study used a strong situational manipulation of anger (and neutral affect). That is, bodily expressions, autobiographical recall, and music were used to induce anger and neutral affect. As such, the strong situation may have overwhelmed the influence of the personality characteristic of anger (for an early review of the interaction of strong vs. weak situations with personality characteristics, see Snyder & Ickes, 1985). Along these lines, Lissek, Pine, and Grillon (2006) discussed how strong situations evoking anxiety may eliminate differences between low and high anxious individuals on psychobiological measures. In terms of concerns about the present research, the correlation between trait anger and the RewP, although significant by conventional standards, was not large. That is, the r value of the relationship between anger and RewP was 0.21. This value, however, is similar to the value obtained from a meta-analysis of the relations between depression and asymmetric frontal alpha power (Thibodeau, Jorgenson, & Kim, 2006), as well as to the average published effect size observed in a metaanalysis of a wide range of personality research (Fraley & Marks, 2007). [We are unaware of a meta-analysis of the correlation between the RewP and personality variables]. The meta-analysis on the relation between depression and asymmetric frontal alpha power (Thibodeau et al., 2006) reported an effect size r of 0.26. However, based on a funnel plot, the authors concluded (p. 724) that, “A systematic publication bias in favor of significant results might have inflated effect size estimates we report….” because “small samples yielded more large effects than small effects.” The present study had a relatively large sample, so it is likely to be estimating an effect size closer to the 28
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with other work suggesting that it is approach and reward-related motivation rather than hedonically positive emotion that is most central to the RDoC Positive Valence Systems (Nusslock et al., 2015), the Positive Valence Systems domain might be more accurately named “Approach Motivation and Reward Systems.” The present study contributes to the literature by providing novel evidence for the link between trait anger and the RewP. Together with other recent research (Angus et al., 2015; Mühlberger et al., 2017), it adds to a growing body of evidence that suggests that approach motivation independent of affective valence may contribute to the RewP. Such research has implications for understanding the structure and function of the broad dimensions of motivational direction and affective valence as well as personality and clinical issues related to these dimensions.
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