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. 2024 Dec 17;62(1):e14745. doi: 10.1111/psyp.14745

Emotion regulation strategies explain associations of theta and Beta with positive affect

Arooj Abid 1,✉, Hannah C Hamrick 1, Russell J Mach 1, Nathan M Hager 2, Matt R Judah 1
PMCID: PMC11652703  PMID: 39690435

Abstract

Maladaptive emotion regulation (ER) strategies are a transdiagnostic construct in psychopathology. ER depends on cognitive control, so brain activity associated with cognitive control, such as frontal theta and beta, may be a factor in ER. This study investigated the association of theta and beta power with positive affect and whether emotion regulation strategies explain this association. One hundred and twenty‐one undergraduate students (mean age = 20.74, SD = 5.29; 73% women) completed self‐report questionnaires, including the Emotion Regulation Questionnaire and the Positive and Negative Affect Schedule. Spectral analysis was performed on resting state frontal electroencephalogram activity that was collected for eight 1‐min periods of alternating open and closed eyes. Relative beta and theta band power were extracted relative to global field power at frontal channels. Regression analysis revealed that positive affect is significantly predicted by theta power (β = 0.24, p = .007) and beta power (β = −0.33, p < .0001). There was an indirect effect of beta power on positive affect via reappraisal, but not suppression. Additionally, theta power significantly predicted suppression, but no indirect effect was observed between theta power and positive affect. These findings are consistent with a prior study reporting a positive and negative relationship between theta and beta power, respectively, and positive affect induction. This study elucidates how modulation of theta and beta bands link to ER strategies.

Keywords: emotion regulation, positive affect, spectral analysis

Short abstract

This article investigates the role of emotion regulation strategies in the relationship between frontal theta and beta band power and positive affect. Through self‐report measures and spectral analysis of resting state EEG data, both theta and beta differentially predicted positive affect while an indirect effect of beta on positive affect via reappraisal was found.

1. INTRODUCTION

Low positive affect is a core feature of depressive disorders (APA, 2022) and conveys risk for physical health problems (Pressman et al., 2019) and early mortality (Zhang & Han, 2016). Increasing positive affect is a central goal of interventions for depression (e.g., Meuret et al., 2022) and leads to improvement in other depressive symptoms (McMakin et al., 2011; Taylor et al., 2017), which supports the important role of low positive affect in depression. Many psychological interventions for depression aim to increase positive affect by modifying cognitive processes involved in emotion regulation, such as reappraisal of negative thoughts (Beck et al., 1979). Interventions also aim to increase experiencing of positive affect (Meuret et al., 2022), which may be difficult for individuals who habitually suppress the expression of their emotions (Fernandes & Tone, 2021).

Cognitive reappraisal and expressive suppression are two emotion regulation strategies closely linked to positive affect theoretically (Joormann & Quinn, 2014) and empirically (Fernandes & Tone, 2021; Pavlov et al., 2014). Cognitive reappraisal involves reconsideration of a stimulus, event, or situation, such as noticing positive aspects of a situation that evokes sadness (Gross, 1998). Most research suggests that cognitive reappraisal is associated with positive affect (McRae et al., 2012), and many interventions aim to build cognitive reappraisal skills to increase positive affect (Clark, 2022; McRae et al., 2012). Expressive suppression involves restriction of exhibiting one's emotions (Gross, 2014; Gross et al., 2006), a strategy that is associated with lower positive affect (Fernandes & Tone, 2021). As emotion regulation strategies, both cognitive reappraisal and expressive suppression rely on cognitive control (Milam & Judah, 2023; Ochsner & Gross, 2005; Pruessner et al., 2020). Indeed, both emotion regulation strategies have been linked to the structure (Hermann et al., 2014) and function (Cutuli, 2014) of mediofrontal brain regions underlying cognitive control. However, there has not been enough research to understand how cognitive reappraisal and expressive suppression are associated with oscillatory brain activity related to cognitive control (Cutuli, 2014). There is also a need to understand how oscillatory activity may explain the association between emotion regulation strategies and positive affect.

Researchers have proposed that emotion regulation depends on cognitive control (Ochsner & Gross, 2005), which is the ability to respond flexibly to unexpected novelty or conflict (Diamond, 2013). Cognitive control networks and their role in emotion has been studied through frontal and parietal activity measured by electroencephalography (EEG; Adamczyk & Wyczesany, 2023; Ahumada‐Mendez et al., 2022; Wyczesany et al., 2024). Studies have examined changes in activity within different frequency bands (i.e., spectral power) during resting state or tasks that involve response inhibition and conflict detection, identifying the theta (~4–8 Hz) and beta (~13–30 Hz) EEG bands as important in cognitive control (Cooper et al., 2016). Furthermore, frontal theta and beta activity have been linked to positive affect (Stikic et al., 2014), such that positive affect is correlated positively with theta activity (Aftanas & Golocheikine, 2001; Hu et al., 2017; McFarland et al., 2016) and negatively with beta activity (Gable et al., 2021).

Consistent with its role in cognitive control and emotion regulation, activity in the beta band has long been regarded as crucial to cognitive and affective processing (Ray & Cole, 1985). Resting‐state beta is correlated with rumination (Kühn et al., 2014), and depressed patients show greater resting‐state beta (Begić et al., 2011; Grin‐Yatsenko et al., 2009). Reduction of beta is seen during motor action and goal pursuit, playing a role in motor readiness during positive approach motivational states (Chen et al., 2019; Gable et al., 2015, 2021) that are often reduced in depressed individuals (Finazzi et al., 2009; Street, 2002). Thus, reduced resting state beta power may reflect a state of readiness for approach actions crucial to positive affect (Gable & Dreisbach, 2021).

Further, beta power has been implicated in emotion regulation. Studies have found beta suppression during passive viewing of high‐arousal images (Schubring & Schupp, 2021), especially during spontaneous emotion regulation (Tortella‐Feliu et al., 2014). Regarding specific emotion regulation strategies, a study using deep learning of resting‐state EEG classified a group that uses cognitive reappraisal and expressive suppression together frequently and a group that rarely uses either strategy with over 85% accuracy based on beta power, which was the most distinctive band in differentiating the groups (Aydın, 2023). Consistent with the role of beta suppression in emotion regulation, neurofeedback training to suppress beta reduces symptoms of depression and anxiety (Wang et al., 2019).

Theta power also has been implicated in cognitive and affective processes. Midfrontal theta likely represents dorsal anterior cingulate organization of neural processes to maintain goals and respond to salient goal‐related events, such as conflict, outcomes, and prediction errors (Cavanagh et al., 2010; Cavanagh et al., 2012; Cohen & Van Gaal, 2013; Narayanan et al., 2013; Widge et al., 2019). Theta power increases in response to salient, unexpected stimuli (Cavanagh & Frank, 2014), including both negative outcomes (Sambrook & Goslin, 2016) and reward (Paul et al., 2020). Theta responses to reward may be reduced in individuals with positive mood because reward is expected and thus less surprising (Paul & Pourtois, 2017). Furthermore, higher levels of resting state theta predict a preference for selecting stimuli associated with reward (Massar et al., 2014), further suggesting a link between theta and behavior typical of positive affect.

Theta power has been linked to emotion regulation as well. Resting‐state frontal theta activity has been correlated with self‐reported use of cognitive reappraisal and expressive suppression in some studies (Sun et al., 2020) but not others (Kobayashi et al., 2020). Attempts to distract or create distance from emotional stimuli result in increased theta power (Lapomarda et al., 2022; Sulpizio et al., 2020; Uusberg et al., 2014). Some studies have found increased theta during instruction to downregulate emotional responses to aversive images through reappraisal (Ertl et al., 2013; Zouaoui et al., 2023), but others have found reduced theta (Wei et al., 2017).

Although research has examined the role of theta and beta in affect or emotion regulation, few studies have examined whether self‐reported emotion regulation skills explain the associations of theta and beta with positive affect. The current study examined the indirect effects of beta power and theta power on positive affect through emotion regulation strategies (i.e., cognitive reappraisal and expressive suppression). We predicted that positive affect would be predicted by both theta power (positively) and beta power (negatively) and that these effects would remain controlling for alpha, which is also modulated during resting states (Li et al., 2024; Mantini et al., 2007). We also hypothesized that theta power would be associated with both emotion regulation strategies. Given the relative lack of prior research about beta and specific emotion regulation strategies, no a priori predictions were made regarding the strength or direction of these associations. We also conducted supplementary analyses testing how theta and beta power and emotion regulation strategies were associated with negative affect.

2. METHODS

2.1. Participants

The sample size needed to achieve .80 power for an indirect effect with medium‐sized a and b paths using bias‐corrected bootstrapping is 71, and 116 would be needed if one path was small‐to‐medium in effect size (Faul et al., 2009; Fritz & MacKinnon, 2007). The sample consisted of 121 undergraduate students (31 cisgender men, 88 cisgender women, and 2 transgender men) at a large southern university. Participant ages ranged from 18 to 54 with a mean age of 20.81 (SD = 5.34). Participants received course research participation credit. Participant demographics are displayed in Table 1.

TABLE 1.

Participant demographics.

Factor Total %
Gender
N 121
Cisgender Male 31 25.6
Cisgender Female 88 72.7
Transgender Male 2 1.7
Race a
Black 23 19
White 84 69.4
East Asian 14 11.6
Latinx 20 16.5
South Asian 3 2.5
Middle Eastern or North African 0 0
Native American/American Indian 3 2.5
Pacific Islander 2 1.7
Ethnicity b
Non‐Hispanic 44 36.4
Hispanic or Latino 21 17.4
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a

Indicates groups are not mutually exclusive.

b

Indicates missing data.

2.2. Measures

2.2.1. Positive and negative affect schedule

The Positive and Negative Affect Schedule (PANAS; Watson et al., 1988) is a 20‐item measure assessing mood, specifically positive and negative affect subscales. Half the items assess positive affect (e.g., “enthusiastic”) and the other half assess negative affect (e.g., “ashamed”). Participants are instructed to indicate the extent to which they have experienced the emotion within a specified time. The PANAS has been used with varying time instructions and this study inquired about participants' emotions “over the past week.” The emotions are rated on a 5‐point scale (1 = very slightly or not at all; 2 = a little; 3 = moderately; 4 = quite a bit; 5 = extremely) with higher scores indicating more experiences of positive and/or negative affect. This study assessed the extent of participants' positive affect. The Cronbach's alpha in the present study for the PANAS positive affect subscale was excellent, α = .91.

2.2.2. Emotion regulation questionnaire

The Emotion Regulation Questionnaire (ERQ; Gross & John, 2003) is a 10‐item measure assessing emotion regulation. The ERQ items are categorized into one of two factors, cognitive reappraisal (e.g., “When I want to feel positive emotion (such as joy or amusement), I change what I'm thinking about.”) and expressive suppression (e.g., “When I am feeling negative emotions, I make sure not to express them.”). The items are rated on a 7‐point scale, ranging from 1 = strongly disagree to 7 = strongly agree with higher scores indicating higher engagement in cognitive reappraisal and/or expressive suppression. The Cronbach's alpha in the present study was good for the expressive suppression, α = .80, and the cognitive reappraisal, α = .87, subscales.

2.3. Procedure

After providing informed consent, participants completed a set of self‐report questionnaires online, including the PANAS and ERQ, in the lab. After participants were seated in a dimly lit room, they were prepped using EEG electrodes. At the start of the testing session, resting state data were collected for eight 1‐minute periods of alternating open and closed eyes, prompted by visual and auditory cues. Participants then completed other visual tasks not discussed in this article, including a passive viewing task and an emotional picture viewing paradigm. Study procedures were approved by the university's Institutional Review Board.

2.4. EEG data preparation and processing

Data were sampled at 1024 Hz using an ActiveTwo system (Biosemi, The Netherlands) with 33 scalp electrodes. Data were processed in MATLAB using EEGLAB. Each channel was re‐referenced to the average of the left and right mastoid electrodes and filtered with a .01 Hz high‐pass filter (second order). Independent component analysis was used to correct ocular artifacts. Data during each eyes‐open and eyes‐closed period were segmented into two‐second epochs with 50% overlap. Using the EEGLAB function spectopo() with a Hamming window, power spectral density (PSD) was extracted in the theta band (4–8 Hz) and beta band (13–30 Hz) at mediofrontal electrodes (Fz, FCz, F3, and F4). Because studies have also examined centroparietal beta (e.g., Li et al., 2024), analyses at centroparietal sites (P3, P4, CP1, CP2, and Pz) also were examined (see Data S1). Relative power was computed as band power divided by total power, which has been found to be more reliable than absolute power (Fernandez et al., 1993; John et al., 1983). Figure 1 portrays the scalp topography maps and the power spectrum for both theta and beta bands.

FIGURE 1.

FIGURE 1

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Scalp distribution of theta (yellow) and beta (blue) power at frontal channels (top right) and parietal channels (bottom right).

2.5. Data analysis

The data were analyzed using IBM SPSS Statistics (Version 26). Data were examined for skewness and kurtosis. The Breusch–Pagan test was used to address the assumption of homoscedasticity. Hierarchical regression was used to test the unique effects of theta and beta power as predictors of positive affect, and to test whether these effects remained when controlling for alpha power. Following this, two parallel mediation analyses were conducted using PROCESS (version 4.1; Hayes, 2017) to evaluate the indirect effects of relative beta and relative theta powers on positive affect through emotion regulation strategies (i.e., cognitive reappraisal and expressive suppression) using unstandardized coefficients with 95% confidence intervals estimated using bias‐corrected bootstrapping (5000 samples).

3. RESULTS

All variables were normally distributed, and skewness (<1.387) and kurtosis (<3.404) were within acceptable limits. The Breusch–Pagan test results were non‐significant, all ps > .443, supporting the assumption of homoscedasticity. The descriptive statistics and bivariate correlations of the study variables are displayed in Table 2.

TABLE 2.

Bivariate correlations, means, and standard deviations among study variables.

1 2 3 4 5 6
1. Relative theta power ‐‐
2. Relative beta power .157 ‐‐
3. Cognitive reappraisal .068 −.182* ‐‐
4. Expressive suppression .188* .140 −.045 ‐‐
5. Positive affect .185* −.296*** .494** −.118 ‐‐
6. Negative affect −.091 .007 −.150 .148 −.176 **** ‐‐
Mean .37 .03 28.55 14.88 31.45 22.24
Standard deviation .05 .02 7.61 5.96 8.83 8.30
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*

p < .05.

**

p < .01.

***

p < .001 (two‐tailed).

****

p < .06.

Regression analysis revealed that positive affect was predicted, F(2, 118) = 9.84, p < .001, by relative theta power, β = .24, t = 2.76, p = .007, and relative beta power, β = −.33, t = −3.87, p < .001, explaining 12.8% of the variance in positive affect. Adding relative alpha as a predictor did not explain more variance in positive affect, ΔR 2 = .003, p = .56. Controlling for alpha, both relative theta, β = .22, t = 2.39, p = .019, and relative beta, β = −.41, t = −2.72, p = .007, predicted positive affect. Relative alpha did not, β = .09, t = .59, p = .56.

The regression coefficients were consistent with the direction of the zero‐order correlations of beta and theta with positive affect. Testing the model with negative affect as the dependent variable did not reveal significant associations, F(2, 118) = .52, p = .60, and there were no direct or indirect effects (see Data S1).

The mediation model (see Figure 2) to understand the association of relative beta with positive affect showed a total effect, c = −119.378 [−189.236, −49.520]. Relative beta power was not associated with expressive suppression, a1 = 38.179, [−10.376, 87.093], but beta was associated with lower cognitive reappraisal, a2 = −63.048, [−125.040, −1.056]. Expressive suppression was not related to positive affect, b1 = −.101, [−.332, .129], but cognitive reappraisal was associated with positive affect, b2 = .527, [.345, .708]. There was an indirect effect of relative beta power on positive affect via cognitive reappraisal, a2b2 = −33.211, [−69.820, −1.743], but not expressive suppression, a1b1 = −3.867, [−19.330, 4.919]. There was a direct effect of beta power on positive affect, c' = −82.301 [−145.964, −18.637].

FIGURE 2.

FIGURE 2

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Indirect effect of relative frontal beta power on positive affect through reappraisal. Path values are standardized coefficients. Direct effect is indicated in parenthesis. *p < .05, **p < .01, ***p < .001.

The mediation model (see Figure 3) to understand the association of relative theta with positive affect revealed that relative theta power was associated with higher expressive suppression, a1 = 21.282, [1.110, 41.454], but not cognitive reappraisal, a2 = 9.756, [−16.392, 35.905]. Expressive suppression did not predict positive affect, b1 = −.192, [−.426, .042], but cognitive reappraisal was related to positive affect, b2 = .553, [.372, .733]. There was not an indirect effect of relative theta power on positive affect via expressive suppression, a1b1 = −4.078, [−12.502, .998], or cognitive reappraisal, a2b2 = 5.392, [−9.578, 20.176]. There were no indirect effects in the mediation models examining associations with negative affect (see Data S1).

FIGURE 3.

FIGURE 3

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Direct effect of relative frontal theta power on positive affect. Path values are standardized coefficients. Direct effect is indicated in parenthesis. *p < .05, ***p < .001.

4. DISCUSSION

4.1. Association of Frontal Resting State Theta and Beta with positive affect

The present study investigated the association of frontal resting state theta and beta with positive affect and whether emotion regulation strategies, specifically cognitive reappraisal and expressive suppression, explain these associations. Our findings clarify the role of theta and beta bands in cognitive and emotional processing that has been explored in prior work (Aftanas et al., 2001; Cavanagh & Frank, 2014; Lundqvist et al., 2018; Schubring & Schupp, 2021). The results supported the hypothesis of a positive association between theta and positive affect and a negative association between beta and positive affect. Consistent with our results, greater beta has been linked to depressed mood (Begić et al., 2011; Grin‐Yatsenko et al., 2009; Pizzagalli et al., 2002) and rumination (Kühn et al., 2014), both of which involve low positive affect. However, Zheng and Lu (2015) found increased beta power during a positive affect induction using videos and decreased beta power during neutral or negative affect induction. The divergent findings may be due to examining resting state beta in some studies, including ours, rather than during emotion induction or regulation. The suppression of beta during motor readiness, particularly during approach motivational states (Gable et al., 2021) may be relevant to our findings. Cognitive reappraisal may involve willingness to approach stimuli or situations initially appraised negatively so that they can be reappraised in pursuit of an emotion‐focused goal, such as building positive affect (see Tamir & Millgram, 2017).

In line with our hypothesis, theta power was positively correlated with positive affect. Our finding aligns with research showing theta to be negatively related to neuroticism (Chi et al., 2005) and theta responses to reward, which plays a role in maintaining positive affect (Gable et al., 2021). Resting state theta power has been linked to better treatment response among patients with depression (Iosifescu, 2011; Koo et al., 2017; Stade & Iosifescu, 2016).

4.2. Role of emotion regulation strategies

Our results suggest that slow (e.g., theta) and fast (e.g., beta) synchronizations are associated with specific emotion regulation strategies, but this is not entirely consistent with past studies. Regarding theta, one study showed resting‐state theta related to cognitive reappraisal (Sun et al., 2020) but another did not (Kobayashi et al., 2020). Our findings are more in line with the latter, possibly due to methodological differences between studies, as Sun et al. (2020) applied source localization and graph theory to estimate functional connectivity of theta. Studies also show increased theta activity during cognitive reappraisal (Ertl et al., 2013; Sun et al., 2020; Zouaoui et al., 2023), though Wei et al. (2017) observed reduced theta. This may be due to the heterogeneity of cognitive reappraisal, a process that may vary across individuals and stimuli (Perchtold‐Stefan et al., 2023). Other emotion regulation strategies, including distancing and distraction, have also been linked to theta synchronization (Lapomarda et al., 2022; Sulpizio et al., 2020; Uusberg et al., 2014). Our finding that expressive suppression is related to increased theta expands upon these findings, aligning with a similar finding by Sun et al. (2020). The emotion regulation strategies linked to theta involve inhibitory control, and it is possible that resting state theta reflects different levels of inhibition across strategies. As such, divergent findings may result from variability in the use of inhibitory control in service of a particular emotion regulation strategy.

Studies have linked beta suppression to positive affect indirectly through its role in approach motivation (Gable et al., 2021). Our findings complement this perspective, as well as studies that have found increased frontal beta in patients with depressive disorders (Begić et al., 2011; Flor‐Henry et al., 2004; Grin‐Yatsenko et al., 2009; Volf & Passynkova, 2002). Beta activity has also been linked to poor emotional awareness (Domic‐Siede et al., 2024), suggesting that beta oscillations are modulated by emotion regulation skills, which in turn impact mood (i.e., positive affect). The association between beta and cognitive reappraisal in our data was small; thus, caution should be exercised when interpreting this finding.

Few studies have explored the link between resting state beta suppression and cognitive reappraisal, and those that have, such as Kobayashi et al. (2020), report a null association. Methodological differences, like the inclusion of eyes‐closed versus open eyes resting states, may account for these discrepancies. Beta suppression is observed when preparing motor activity in service of a goal (Gable et al., 2021; Meadows et al., 2016; Meyniel & Pessiglione, 2014), leading us to speculate that beta suppression during resting states reflects planning and other goal‐oriented cognition present in some forms of cognitive reappraisal (Wang et al., 2017). Our findings underscore the need for further investigation into resting state beta suppression as a correlate of cognitive reappraisal use.

4.3. Implications for understanding emotion regulation strategies

Consistent with prior literature suggesting that cognitive reappraisal is generally adaptive and related to euthymic mood, cognitive reappraisal was associated with positive affect in the current study (Brockman et al., 2017; Cutuli, 2014; Garland et al., 2009). A recent review highlighted that limited use of cognitive reappraisal is strongly linked to symptoms of depression (Dryman & Heimberg, 2018). This is in line with the view that cognitive reappraisal, a beneficial emotion regulation strategy, is associated with positive affect, which is inversely related to depression, hence supporting our findings. Notably, cognitive reappraisal explained the association between beta suppression and positive affect. To our knowledge, this is the first study to report this finding.

Contrary to prior literature, we did not find a significant relationship between expressive suppression and positive affect (Fernandes & Tone, 2021), although the literature is mixed (Kalokerinos et al., 2015). Kalokerinos et al. (2015) did not find that expressive suppression was related to positive affect, and they argued that expressive suppression may be adaptive in some contexts (i.e., suppressing laughter at a funeral). A metanalysis found that the association between expressive suppression and positive affect is moderated by anxiety, culture, and the type of emotion being suppressed (Fernandes & Tone, 2021). In those with clinical anxiety, the association was not significant. Further, that study found that expressive suppression of negative emotions was related to increased positive affect, whereas suppression of positive emotions decreased positive affect. The measure of expressive suppression used in our study included items assessing suppression of both positive and negative emotions, possibly leading to a null association between expressive suppression and positive affect in our data.

4.4. Limitations and future directions

The present study is limited in several respects. The results were derived from a predominantly White, female, undergraduate student sample, limiting the generalizability of the data. Secondly, parallel mediation alone cannot resolve issues of causality. Additionally, the assessment of emotion regulation strategies was limited to those reflected in the ERQ (i.e., expressive suppression and cognitive reappraisal). While we were powered to detect a medium‐ a and b path, we did not have enough overall power. A systematic review of emotion regulation strategies suggested at least six distinctive strategies (Aldao et al., 2010). Flexibility in using strategies is also important but not assessed by the ERQ (Bonanno & Burton, 2013). Future research should examine how emotion regulation strategy selection relates to aspects of cognitive control.

In conclusion, this study highlights important associations between resting state theta and beta brain waves and positive affect. Moreover, these associations were explained by emotion regulation strategies. We found that higher frontal theta power was linked to greater positive affect, while higher beta power was linked to lower positive affect. Cognitive reappraisal, an adaptive emotion regulation strategy, played a key role in mediating the relationship between beta suppression and positive affect. The findings are limited by the homogenous sample and methodological constraints, indicating a need for further research. Future studies should include a wider range of emotion regulation strategies and more diverse samples to improve generalizability. This research enhances our understanding of how brain activity influences emotional well‐being and suggests potential targets for mental health interventions.

AUTHOR CONTRIBUTIONS

Arooj Abid: Conceptualization; data curation; formal analysis; software; visualization; writing – original draft. Hannah C. Hamrick: Data curation; writing – original draft. Russell J. Mach: Writing – original draft. Nathan M. Hager: Data curation; methodology; writing – review and editing. Matt R. Judah: Conceptualization; data curation; methodology; software; supervision; writing – original draft.

FUNDING INFORMATION

None.

CONFLICT OF INTEREST STATEMENT

The authors have no conflict of interest to disclose.

Supporting information

Data S1. Supporting Information.

PSYP-62-e14745-s001.docx (14.4KB, docx)

Abid, A. , Hamrick, H. C. , Mach, R. J. , Hager, N. M. , & Judah, M. R. (2025). Emotion regulation strategies explain associations of theta and Beta with positive affect. Psychophysiology, 62, e14745. 10.1111/psyp.14745

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Supplementary Materials

Data S1. Supporting Information.

PSYP-62-e14745-s001.docx (14.4KB, docx)

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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