Cognitive sex differences in effects of music in Wisconsin Card Sorting Test

Abstract

Recent studies suggest that females and males show different levels of susceptibility to neuropsychological disorders which might be related to sex differences in executive control of behaviour. Music, as a cognitively salient factor, might influence cognitive functions; however, it is unclear how sex and music interact in influencing executive control of behaviour in a dynamic environment. We tested female and male participants in a computerized analogue of the Wisconsin Card Sorting Test (WCST) while listening to music or in silence. We found that music decreased the percentage of correct trials in both sexes. While music decreased response time in females, it had an opposite effect in males. Response time increased in error trials (error slowing), and music sex-dependently influenced error slowing. Conflict between potential rules adversely influenced performance in the current trial (conflict cost) in both sexes and listening to music increased conflict cost. These findings suggest that music shows both adverse and beneficial effects on various behavioural measures in the WCST, some of which are sex-dependent. Our findings suggest that in using music as an adjunct for rehabilitation of neuropsychological disorders, both adverse and beneficial effects and sex dependency need to be considered.

Keywords

background music cognition functions of music problem solving Reaction time Wisconsin Card Sorting Test (WCST)

Various contextual factors such as background music or sex might influence cognitive functions. In this study, we aimed to investigate how sex and background music interact to influence executive control of behaviour in a changing environment. The differential effects of music on executive functions in females versus males have rarely been investigated. Various hormonal or structural differences in brain circuitry might mediate sex-related cognitive differences. Higher levels of testosterone can lead to improved cognitive ability (Beauchet, 2006; Yaffe, Lui, Zmuda, & Cauley, 2002). The higher levels of estrogen in females are linked with an increase in cortical blood flow in regions such as the prefrontal cortex, which are involved in cognitive functions (Dietrich et al., 2001). Previous studies have shown that sex steroids modulate prefrontal cortex function (Aubele & Kritzer, 2011; Finley & Kritzer, 1999; Handa, Hejna, & Lorens, 1997). Sex differences in the dopaminergic system and in cortisol responses to psychological stress have also been reported (Andersen & Teicher, 2000; Munro et al., 2006).

Sex differences occur across a wide range of cognitive tasks. Men outperform women in visual perception and spatial reasoning tasks (Yang, Shi, Cai, Shen, & Lin, 2012), mental rotation tasks and finger tapping and reaction time measures (Miller & Halpern, 2014; Roivainen, 2011; Van der Elst, Van Boxtel, Van Breukelen, & Jolles, 2006). Women outperform men in memory (Herlitz & Lovén, 2013), verbal tasks (Reilly, 2012; Stoet & Geary, 2013) and some spatial tasks that involve remembering object locations (Voyer, Postma, Brake, & Imperato-McGinley, 2007). Imaging studies have shown that women and men show differences in the pattern of brain activity during cognitive tasks such as word generation, working memory and the stop task (Li, Huang, Constable, & Sinha, 2006). Socio-cultural differences, evolutionary processes and hormonal exposures are among the many factors that might lead to dissociable brain network organizations in females and males, contributing to sex differences in cognitive abilities (Da Silva & Ravindran, 2015; Meyers-Levy & Loken, 2015). It remains unclear whether the reported advantage of men in reaction time measured in speeded response tasks also exist in rule-based behaviour and in cognitive flexibility in adapting to rule changes.

Background music in daily life could influence cognitive functions and executive control of behaviour (Mansouri, Fehring, Gaillard, Jaberzadeh, & Parkington, 2016; Pietschnig, Voracek, & Formann, 2010; Schellenberg & Weiss, 2013). Pleasure in response to background music induces dopamine release (Salimpoor, Benovoy, Larcher, Dagher, & Zatorre, 2011). Background music can alter plasma levels of hormones such as cortisol and testosterone (Fukui & Yamashita, 2002) which could influence cognitive functions. Processing of musical information and the consequent alterations in emotional state might be supported by differential neural networks in females and males (Flores-Gutiérrez et al., 2009; Koelsch, Maess, Grossmann, & Friederici, 2003; Mansouri, Fehring, Gaillard, et al., 2016).

Music is frequently used as a rehabilitation tool in neuropsychiatric disorders (Ceccato, Caneva, & Lamonaca, 2006). It boosts listeners’ emotional state and can induce a higher level of arousal (Day, Lin, Huang, & Chuang, 2009; Schellenberg & Weiss, 2013). However, music might also lead to unfavorable cognitive performance by engaging parts of the limited cognitive resources (Day et al., 2009; Schellenberg & Weiss, 2013). A better understanding of the adverse and/or beneficial effects of music on a variety of specific cognitive control functions in healthy individuals could provide a basis for more efficient strategies in music therapy of neurological disorders (Ceccato et al., 2006). Thus, the aim of this study was to test the hypothesis that sex-related cognitive differences might interact with music effects and influence cognitive flexibility in a changing environment. We used the Wisconsin Card Sorting Task (WCST), which is used clinically as a neuropsychological test of cognitive flexibility and set shifting (Dehaene & Changeux, 1991; Eling, Derckx, & Maes, 2008; Haut et al., 1996). The computerized version of the WCST (Mansouri, Buckley, & Tanaka, 2007; Mansouri et al., 2009, 2017) is a multifaceted task assessing rule-based decision making, error-related and conflict-related phenomena as well as cognitive flexibility (Buckley et al., 2009). We found that background music decreased response time in females but it had an opposite effect in males. Music also had an adverse effect on accuracy where the participants had to make a choice between competing behavioural rules.

Method

Overall design

The test was carried out in two sessions, two weeks apart. All participants completed the task (WCST) in each of two experimental conditions: while listening to background music (music session) and in silence (silence session). To control for the effect of practice, for half of the participants (chosen randomly), the music condition was the first session and for the other half, the second session. All testing sessions were scheduled at either 9:00–11:00, 11:00–13:00, 13:00–15:00 or 15:00–17:00 time slots (local Melbourne time) and, for consistency, each subject was tested at the same time of the day across the weekly sessions (music or silence). All the participants were presented with the same order of songs, played through wireless headphones. We selected contemporary pop songs (radio-played popular music) with lyrics as background music (see Appendix for list of songs). The tempo, tonality (major/minor) and instrumental timbres were not controlled in this study. The selection criterion for the songs was the absence of any offensive statement in the lyrics. We set the volume level for all participants, but the participants were allowed to adjust it if they considered it too low or too high. For the silence sessions, the participants put on headphones, without any music, to minimize background noise. The dependent variables included response time (RT) in correct and error trials and percentage of correct responses (accuracy of performance) and the independent variables included sex (female vs. male) and music condition (music session vs. silence session). The data were analyzed using two-way Analysis of Variance (ANOVA), pairwise comparison with Bonferroni correction, and an independent sample t-test using the IBM SPSS statistics program.

Participants

Human ethical approval was obtained from Monash University. Informed written consent was obtained from the participants, which included 40 females and 30 males (19–28 years of age). All participants were university undergraduate students without any history of neurological disorders. Participation in this project and performing the WCST was considered one of several options necessary for completing their coursework.

Behavioural task

In this version of the WCST, participants needed to match cards based on two possible rules: shape and colour (Mansouri et al., 2007; Mansouri et al., 2009). Each trial started with the appearance of a start cue (a grey circle) at the centre of the touch monitor. On seeing the start cue, the participant pushed a switch to commence the trial. A sample appeared in the centre of the monitor, followed by the appearance of three test items that surrounded the sample (Figure 1). The sample and test items were chosen from a source of 36 items (a combination of six colours and six shapes) and in each trial the sample was selected randomly (without replacement). The test items and their location (left, right, bottom) were also selected pseudo-randomly to make a congruent or incongruent condition. In incongruent trials, one of the three test items matched the sample in shape and another test item matched it in colour, the third test item was irrelevant to the sample in shape and colour; therefore, there was a conflict between the behavioural rules (matching based on colour or shape). In the congruent trials, one of the test items matched the sample in both colour and shape and the two others matched the sample in neither colour nor shape; therefore, there was no conflict between the matching rules. The relevant matching rule and its frequent changes were not cued and the participants had to find it by trial and error based on assessment of decision outcome in selecting the rules. The rule changed from one block to another whenever the participants achieved the criterion of nine correct responses out of 10 consecutive trials. The participants were not aware of this criterion. The participants needed to touch the correct test item within 900 ms, using the dominant hand. An error signal signified erroneous selection or early release of the switch (Figure 1).

Figure 1.

Behavioural task. (a) congruent and incongruent trials and the possible responses for each trial type; (b) the order of training-practice blocks and main blocks in a daily session.

Procedure

We used two versions of the WCST in different blocks to assess the effects of background music (and its sex dependency): The standard version comprised only incongruent trials. In the conflict version of the WCST, incongruent and congruent conditions were intermingled, not in separate blocks. Both computerized versions of the WCST have been validated in our previous studies (Mansouri et al., 2007; Mansouri et al., 2009, 2017). The test included 21 blocks: the first 3 blocks were training-practice and the remaining 18 blocks were testing blocks. The first training block included only congruent trials, and the criterion for shift to the next block was 18 correct trials out of 20 consecutive trials. The second and third training blocks comprised only incongruent trials, with colour matching as the relevant rule in block 2 and shape matching as the relevant rule in block 3. The criterion for shift in these blocks was 5 correct responses out of 5 consecutive trials. The training-practice blocks were included to familiarize the participants with the task and procedure before starting data collection. From the 18 main blocks, the first 8 included only incongruent trials (standard WCST) for studying error-related phenomena (error slowing) and the last 10 blocks included both congruent and incongruent trials randomly intermingled (WCST-conflict) for studying conflict-related behavioural adjustments (Figure 1). Data collection was by CORTEX software (National Institute of Mental Health [NIMH]) at ms resolution. Only data from the main blocks were used for analysis.

Data analyses

If participants selected the test item based on the currently relevant rule in the block, it was considered a correct response but if they selected based on the relevant rule in the previous block (only in incongruent trials), it was considered a perseverative error. Participants’ response was considered as wrong when they chose the test item that did not match the sample in either colour or shape and as time-out when they failed to touch the test item in the 900 ms time window (Figure 1).

Performance was evaluated in terms of accuracy and response latency. For accuracy, percentage of correct responses was calculated as a ratio of correct responses to the sum of correct, wrong, and perseverative error responses in incongruent trials, and as the ratio of correct responses to the sum of correct and wrong responses in congruent trials. Response time (RT) was calculated as the difference between the onset of test items display and the participant’s first touch on the monitor. For all statistical analyses, raw data (RT or percentage of correct responses), without any transformation, were used. To facilitate comparison between groups, normalized data were used in all figures except Figures 2 and 4. In each test session, RT for each parameter was averaged for each participant, and normalized by dividing by the average RT of the parameters that were to be compared. Partial eta squared indicates the proportion of the variance explained by the effect in ANOVA analysis and was calculated for each significant effect.

Figure 2.

Sex dependent response time (RT) in silence sessions in standard Wisconsin Card Sorting Test (WCST). (a) the correct response time in male participants was significantly shorter than that in female participants. (b) the difference in RT in error trials between females and males did not reach significance. Error bars reflect Standard error of mean (SEM).

Results

Standard WCST

In this version of WCST with only incongruent trials (both silence and music sessions), wrong responses and perseverative errors comprised 11.2% of all responses (excluding time-outs). Of this percentage, 98.5% were perseverative errors. Most perseverative errors were committed after the non-notified rule change. In the rest of this article, perseverative errors are regarded as errors. In addition, participants had 7.1% time-outs in incongruent trials (in both silence and music sessions).

Sex-dependent performance in the standard WCST

There was no significant difference in the total number of errors in silence sessions between female and male participants t (68) = 0.26, p = 0.79. However, the response time (RT), as a measure of efficiency of the decision-making process, was significantly different between the two sexes. RT in correct trials showed that males were significantly faster (629.3 ± 13.3 ms) than females (667.6 ± 10.8 ms), t (68) = 2.26, p = 0.027 (Figure 2). In error trials, no significant difference in response time was observed between males and females, t ₍₄₇₎ = 1.59, p = 0.12 (Figure 2).

Background music effect on performance in the standard WCST

Correct responses

To investigate the effect of background music on accuracy, two-way ANOVA (sex [female/male, between-subject factor] × music [silence/music, within-subject factors]) was applied to the percentage of correct responses. The main effect of background music was significant, F_(1,63) = 4.995, p = 0.029, partial eta squared = 0.073, indicating that background music significantly decreased the percentage of correct responses (Figure 3). There was no significant interaction between music and sex, F(1,63) = 0.24, p = 0.63.

Figure 3.

Effect of music on performance in standard Wisconsin Card Sorting Test (WCST). (a) adverse effect of music on accuracy in both sexes. (b) differential effect of music on females and males’ response times (RT) in correct responses. (c) differential effect of music on female and males RT in error responses. (d) and (e) RT in error responses was larger than that in correct responses (error slowing) and music increased error slowing only in males. Normalized values are used in figures (b)–(f). Error bars reflect Standard error of mean (SEM).

Response time in correct and error trials

To investigate the effect of background music on RT, two-way ANOVA (sex [female/male] × music (silence/music, within-subject factors]) was applied to RT in correct trials. The main effect of sex, F(1,63) = 1.97, p = 0.17, or music, F(1,63) = 0.05, p = 0.82, was not significant. However, interaction between music and sex was significant, F(1,63) = 6.14, p = 0.016, partial eta squared = 0.089 (Figure 3). Music decreased RT in females but it had an opposite effect in males. In correct trials, we conducted a simple effects test with Bonferroni adjustment which revealed that music elicited a reduction in female RT (664.7 ± 11.3 ms in silence session vs. 647.6 ± 12.4 ms in music session) which was statistically significant, F(1,63) = 4.24, p = 0.043). However, RT in males (625.2 ± 13.0 ms in silence session vs. 639.5 ± 14.3 ms in music session) was not statistically significant, F(1,63) = 2.22, p = 0.14). We also calculated the difference in RT in correct trials between the background music and silence sessions for females and males. A t-test showed a significant difference between females and males (t₍₆₃₎ = 2.48, p = 0.016. The same two-way ANOVA applied to RT in error trials showed that, while the main effect of Sex, F(1,31) = 0.37, p = 0.55, or Music, F(1,31) = 0.71, p = 0.41, were not significantly different, there was a significant interaction between music and sex, F_(1,31 = 5.16, p = 0.03, partial eta squared = 0.143 (Figure 3). In error trials, females became faster while listening to music but males became slower. We also calculated the difference in RT in error trials between the music and silence sessions for females and males and a t-test showed a significant difference between the sexes, t(31) = 2.27, p = 0.03.

Error slowing

Participants became slower when committing errors (error slowing). The inevitable errors subsequent to the unannounced rule shift in each block were excluded from this analysis. To investigate the effect of music on error slowing in our experimental paradigm, a three-way ANOVA (response-type [correct/error, within-subject factors] × sex [female/male] × music [silence /music, within-subject factors]) was applied to RT. The main effect of response-type factor was significant, F(1,31) = 32.63, p < 0.0001, partial eta squared = 0.513, confirming the significantly higher RT in error than that in correct trials (Figure 3). The main effects of sex, F(1,31) = 0.08, p = 0.78, or music, F(1, 31) = 0.30, p = 0.59, were not significant, with no significant interaction between response-type and music, F(1,31) = 1.43, p = 0.24. However, a significant interaction between music, response-type and sex, F(1,31) = 4.73, p = 0.037, partial eta squared = 0.132, was observed (Figure 3). This shows that the difference in RT between error and correct trials was larger in males while listening to music and resulted from a larger RT in error trials in music sessions (Figure 3). However, post-error slowing did not differ between males and females or between music conditions (Figure 3).

WCST-conflict

We also examined the effects of background music on conflict-dependent behavioural adjustments using the data obtained with WCST-conflict, in which the conflict level between behavioural rules varied from trial to trial (Figure 1). Wrong responses and perseverative errors comprised 21.2% of all responses (excluding time-outs) in incongruent trials (both silence and music sessions). Of this percentage, 98.8% comprised perseverative errors. Participants rarely (0.1%) committed wrong responses in congruent conditions. Moreover, participants had 6.7% and 4.3% time-outs in incongruent and congruent trials, respectively (in both silence and music sessions).

Sex-dependent performance in WCST-conflict

To determine whether sex differences in RT (in silence sessions) existed for both levels of conflict (i.e., congruent and incongruent trials), two-way ANOVA (sex [female/male] × conflict [congruent/incongruent, within-subject factors]) was applied to the mean RT in correct trials. The main effect of sex was significant, F(1,68) = 4.72, p = 0.03, partial eta squared = 0.065), with males responding faster than females, but there was no interaction between sex and conflict, F(1,68) = 1.17, p = 0.28 (Figure 4), confirming that males were faster than females in both congruent and incongruent conditions.

Figure 4.

Sex-dependent response time (RT) in correct congruent and incongruent trials in silence sessions. In Wisconsin Card Sorting Test (WCST)-conflict, the correct RT in male participants, in both congruent and incongruent trials, was significantly shorter than that in female participants. Error bars reflect Standard error of mean (SEM).

Background music-influenced performance in WCST-conflict

The presence of conflict in information processing leads to slower responses in incongruent than congruent trials (conflict cost; Botvinick, Cohen, & Carter, 2004; Mansouri et al., 2009). We estimated “conflict cost” as the difference in RT between incongruent and congruent trials. Two-way ANOVA (sex [female/male] x music [silence/music, within-subject factors]) showed a significant main effect of music, F(1,63) = 4.93, p = 0.03, partial eta squared = 0.073, indicating that music significantly increased conflict cost. However, no interaction between music and sex was observed, F(1,63) = 2.02, p = 0.16, since the effect of music on conflict cost was the same in both sexes (Figure 5). In fact, the enhanced magnitude of the music effect in congruent trials resulted in the larger conflict cost (Figure 5). Two-way ANOVA (sex [female/male] x conflict [congruent/incongruent, within-subject factors] applied to the difference in RT between silence and music sessions showed a significant, F(1,63) = 4.93, p = 0.03, partial eta squared = 0.073, main effect of conflict, indicating a stronger effect of music in congruent than incongruent trials. The ANOVA also confirmed that the ‘conflict adaptation’ (Mansouri et al., 2017) was not different between females and males or between music conditions (Figure 5).

Figure 5.

Effect of music on performance in Wisconsin Card Sorting Test (WCST)-conflict. (a) music decreased the response time (RT) in females and increased it in males, regardless of the conflict level. Music effect on RT in congruent trials was stronger than that in incongruent trials in both sexes. (b) music increased conflict cost (normalized values are used for calculating conflict cost). Normalized values are used in (a) and (b). Conflict adaptation was not different between females and males or between music conditions (c). Error bars reflect Standard error of mean (SEM).

Discussion

Sex differences in WCST performance

The results of this study indicate basic sex difference in WCST performance in silence sessions, RT was shorter in males than in females in correct, but not in error, responses. Indeed, this difference was observed in both incongruent and congruent trials. While sex differences in WCST score have been documented previously (Boone, Ghaffarian, Lesser, Hill-Gutierrez, & Berman, 1993), sex differences in response time in the WCST has not been the focus of any study to date. These results are in agreement with those of Yang et al. (2012) who showed that responses of males were faster than those of females in the context of visual perception and spatial reasoning tasks. Males outperform females in visuospatial abilities, mental rotation tasks and finger tapping (Miller & Halpern, 2014; Roivainen, 2011; Van der Elst et al., 2006).

Miller and Halpern (2014) explain these sex differences from a biopsychosocial point of view, in which an entangled interaction of biological factors such as hormones, brain differences and environmental factors, such as cultural influences, sex stereotypes and developmental trends, are responsible for sex differences in cognitive function. Sex hormone exposures during prenatal and critical postnatal periods are believed to influence the organization of the developing brain resulting in distinct cognitive abilities in each sex (Schulz, Molenda-Figueira, & Sisk, 2009). Furthermore, males and females are assumed to use different strategies for achieving similar cognitive performance, as indicated by different patterns of brain activity in males and females (Jaušovec & Jaušovec, 2012; Lenroot & Giedd, 2010). Thus, the organizational and functional brain differences between males and females could partially explain the sex differences in cognitive tasks.

Effect of background music on accuracy in rule-based matching

Our results show that the presence of background music has an adverse effect on accuracy where the participants had to make a choice between competing behavioural rules. The effects of background music, though small, appeared as a significant decrease in the percentage of correct responses in incongruent trials of the standard WCST. Earlier reports have shown adverse effect of listening to music/noise on performance (accuracy) in cognitive tasks such as the Stroop task (Cassidy & MacDonald, 2007), immediate and delayed recall (Cassidy & MacDonald, 2007; Furnham & Bradley, 1997), reading comprehension (Furnham & Bradley, 1997; Furnham & Strbac, 2002) and perception and spatial reasoning tasks (Yang et al., 2012). In contrast, Day et al. (2009) showed that listening to faster tempo music improved accuracy in a sustained attention response task, though the effect was only observed in the difficult version of the task. Imaging studies have also revealed the effect of listening to music/noise on activity of the prefrontal cortex (Blood & Zatorre, 2001; Ferreri, Aucouturier, Muthalib, Bigand, & Bugaiska, 2013; Menon & Levitin, 2005). Thus, possible sharing of the same neural resources by the two different modalities of hearing and vision might lead to “interference” between the concurrent processes, with a consequent increase in error likelihood (Botvinick, Cohen, & Carter, 2004). The observed adverse effect of music on accuracy supports the theories proposing cognitive processing limitation as a restricting factor while listening to music during a cognitively demanding task (Schellenberg & Weiss, 2013).

Sex-dependent effect of background music

We found a sex dependency in the effects of music on participants’ response time, which appeared as a significantly higher speed of target selection in females than males in the presence of background music (Figure 3). Yang et al. (2012) reported that men show more susceptibility to distraction by rock music in the context of perception and spatial reasoning tasks. Here we show that background music enhanced female performance, increasing the speed of target selection, but had an adverse effect in males, decreasing selection speed in both congruent and incongruent trials (Figure 5). Consistent with this, Koelsch et al. (2003) reported sex differences in the processing of musical information in addition to auditory processing in the linguistic domain. Flores-Gutiérrez et al. (2009) reported that unpleasant emotions induced by unpleasant music are supported by a bilateral network in female brains while they are sustained by right hemisphere networks in males. The sex differences in the functional organization of the brain during music processing and emotional state changes may account for the observed differential effects of music on RT in female and male participants in the present study.

We also found that committing errors took longer than making a correct response. This has been termed “error slowing” in our previous studies (Kuwabara, Mansouri, Buckley, & Tanaka, 2014). Here we found a significant interaction between sex and music in error slowing. Error slowing was intensified in males when listening to music, as indicated by the increased difference in RT between error and correct responses, whereas it was slightly suppressed in females. Error slowing might be due to higher error-likelihood or uncertainty in response selection (Kuwabara et al., 2014). Music might increase uncertainty in decision making through a preferential influence on brain regions such as anterior cingulate cortex which consequently leads to increased error-slowing. This effect is only observed in males, not in females, which might be due to the aforementioned sex differences in music processing.

Limitations

In our study, participants were young university students within a narrow age range and educational background. Further study is needed to examine our findings in other age ranges and different backgrounds and investigate how alterations in musical genres and structural components such as tempo and timbre influence cognitive functions.

Conclusion

In everyday life, we engage in various cognitive processes, such as rule-based decision making, in different contexts which could include task-irrelevant background music. We examined the effects of background music and sex on the efficiency of the decision-making process, uncertainty in decision making, accuracy of performance and cost of resolving conflicts in information processing. We found significant differences in the cognitive effects of music between females and males. Our findings indicate both adverse and beneficial effects of music on behavioural measures in the WCST. Music decreased accuracy in both females and males and increased uncertainty in response selection in males, indicated by increase in error slowing. Nevertheless, it enhanced efficiency in the rule-based decision-making process in females. This suggests that music has a multifaceted effect by influencing different neural networks leading to direct or indirect modulation of different cognitive functions such as attention and emotional regulation. The possible engagement of limited cognitive resources by music might mediate its adverse effects, while the effects of music on emotional state and mood might mediate its beneficial effects.

Footnotes

Appendix

Appendix.

List of songs.

Song	year of release	singer
Wide Awake	2012	Katy Perry
Roar	2013	Katy Perry
Let Her Go	2012	Passenger
Chandelier	2014	Sia
Maps	2014	Maroon 5
Nobody Wants to Be Lonely	2000	Ricky Martin
Only Girl in the World	2010	Rihanna
Timber	2013	Pitbull
Stay with Me	2014	Sam Smith
Blank Space	2014	Taylor Swift
Te Amo	2010	Rihanna
We Found Love	2011	Rihanna
Wake Me Up	2013	Avicii
Somebody’s Me	2007	Enrique Iglesias
Please Don’t Stop the Music	2007	Rihanna
Summer	2014	Calvin Harris
Call Me Maybe	2012	Carly Rae Jepsen
Outside	2014	Calvin Harris
Boom Clap	2014	Charli XCX
Rather Be	2014	Clean Bandit
Complicated	2002	Avril Lavigne
DJ Got Us Falling in Love	2010	Usher
Lights	2010	Ellie Goulding
Firework	2010	Katy Perry
Hey Brother	2013	Avicii
Burnin’ it Down	2014	Jason Aldean

Declaration of conflicting interests

The author(s) declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by Strategic Grant Scheme program, School of Biomedical Sciences at Monash University and ARC Centre of Excellence in Integrative Brain Function, Monash University.

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