1 Introduction

Music is what people are willing to spend their time on and there are different reasons behind it, from relieving tension to passing the time [1] or even controlling the moods [2]. Although people might often prefer to sit down and listen to music deliberately, Renfrow and Gosling reported a wide variety of activities when people might listen to music [3]. As an important aspect of human daily life, many studies have been conducted on the role of music on a wide range of individual behavior, informing us with the positive influence of music on the sense of helpfulness, task involvement encouragement and coping with perceived stress [4]. Studies reported effect of specific music on individual spatial abilities [5, 6], though controversy on the source and reproducibility of the effect makes it difficult to come up with a single conclusion [7]. A recent study [8] showed that listening to “happy music” enhance divergent thinking. Similarly, Ilie et al. examined the cognitive changes in term of creativity and mentioned over the effect of music type on individual creativity [9]. Although these results might explain music impact on some levels of individual creative cognition, the field of the possible effects of music on group communication is to be investigated further.

Cross and Morley argued over the music capacity to sustain social interactions [10]. Performance of joint music making on cooperation has been studied before [11]. Brown et al. [12] investigated how music impact on cooperation. In that article they mentioned the use of music isometric rhythms to enhance group synchronization [12]. Also, Lang et al. [14], based on the observations that interpersonal coordination results in subsequent social bonding enhancement [13], referred to rhythm impact on group coordination enhancement as a route to facilitate positive social behavior and bonding [14]. In complementary experiments, Au et al. argued that participant who listened to pleasant music tended to be more confident over the ones who listened to unpleasant music [15] and Greitemeyer presented the music effects on mood and decision behavior [16]. Physiological synchrony is intertwined with emotional rapport [17]. A review article [18] mentioned how music makes brainstem neurons fire synchronously with tempo, and synchronized activities like music encourage social connection. Recently, Bernardi et al. [19] showed that listening to simple rhythms makes individuals synchronized in terms of their physiological rhythms, which may lead to rapport and mutual understanding. These findings bring us to the possible influence of music’s synchrony-inducing (i.e. homogenizing) effects on group cognition, but would music facilitate or hinder group creativity, and how such an influence can depend on the different types of music?

Group creativity, being the way to enhance the creative productivity through communication, has been an interesting study topic for many years. However, the benefit of group communication on creativity has been on the controversy in many of them. Being in a group would hinder creativity performance in terms of the productivity loss in idea-generating [20]. Perceiving others efforts to be sufficient, apprehensive behavior toward other members judgment [21] and the fact that only one person can talk at a time [22] are the reasons behind this idea. Although being a well-perceived fact, it neglects the productivity impacts of being in a group on creativity [23] with benefits like minimizing member’s motivation, energy, and talent losses, and misuse of time [24]. While traditional thoughts believe divergent perspectives increase and homogeneous perspectives decrease group creativity [25], recently there is a hiatus on this view since the convergent process is needed for distinguishing new ideas and unifying them. The new ideas on group creativity explain how groups might benefit from cooperation. Where the individual ability of group members to produce new ideas is important [26] and diversity between members can enhance the comparison between group members to enhance divergent thinking [27]. Group creativity, on the other hand, benefits from its members’ cooperation to integrate original perspectives [28]. Use of group to enhance creative productivity can be practical as long as the diversity between members and their shared ideas would not disservice the cooperation level by being in opposition [29].

As noted above, some music types can enhance cooperation between members of a group in general. However, its impacts on group creativity are yet to be investigated. Group creativity, as discussed earlier, is based on the level of individual creativity along with the cooperation tendency of its members. While music effect on group creativity has been scarcely explored so far, previous studies stated that members with high extraversion and sociability traits will experience less level of anxiety during experiments [30] which might further result in convergent thinking facilitation [31]. In their study, they presented a higher level of tendency to be fixed on creativity in high preference interactive participants compared to low preference ones but no trend to produce more unique ideas.

Creative thinking is the combination of producing as much as possible ideas (fluency), in many categories (flexibility), while the ideas remain unique and novel (originality) and needs both of the cooperation and individual creativity of its members to be enhanced. In this article, we aimed to compare the creative performance of interactive groups while listening to different types of music, being positive vs. negative in terms of valence and reflective vs. upbeat in terms of the track’s types. Our purpose is to test the impact of different music types on the different group creativity indices and investigate over the music types which would help or hinder individual creativity, and cooperation level of members, resulting in the total group creativity changes.

To probe the processes underlying the effects of music on group creativity, we investigated interbrain synchrony and non-verbal communication (NVC) expressed in the physical interpersonal coordination. In the exploration of brain functioning in experimental and daily human interactions, the hyperscanning technique allows brain activity measurement of two or more people simultaneously [32]. Functional near infrared spectroscopy (fNIRS) allows brain activity measurement during natural communications, with high ecological validity, portability, and cost effectiveness. fNIRS-based hyperscanning studies [33, 34] indicated that the level of cooperation during tasks is correlated to interbrain synchrony in the pre-frontal cortex (PFC), which has been associated with cognitive processes such as working memory and executive function [35]. In this study, we measured the medial and left lateral part of the PFC. In previous studies, the left inferior PFC showed association with the memory process functions during communication [36], while anterior PFC (aPFC) involved in integrating different operations into behavioral goal [37]. Moreover, NVC is the way to make communication without transmission of the words [38]. In this study, to test the effectiveness of music to enhance NVC, we evaluated the head movement synchrony (HMS) [39].

2 Method

2.1 Participants

Thirty international students of Tokyo Institute of Technology including 18 females and 12 males being recruited via flyers and took part in our experiment. All participants being right-handed with normal or corrected-to-normal vision. Participants were grouped into dyads and been called to participate in the experiment based on their answers to an online preparation phase questionnaire, which will be further explained in the next subsection. The study procedure was approved by the Ethics Committees of Tokyo Institute of Technology. All participants were briefed about the experimental procedure and gave written informed consent. They were paid 3000 Yen for their time and effort.

2.2 Selection of Music Stimuli and Dyad Construction

Music asserts its effects through influencing emotions [40]. On the concept of emotion within music, Schimmack and Grob focused on two elements of music: valence (pleasant vs unpleasant) and arousal [41]. In this study, to select a list of music pieces as stimulus, we first fixed our factors of interest on valence and genre. Here, the genre was whether a piece is “reflective” or “upbeat”. The reflective list consisted of classical pieces mostly from famous composers, while upbeat tracks were defined by either country, sound track, and pop music categories [42].

In order to delineate the effects of music valence and genres from other possible confounding factors, we tried to control the degree of familiarity, tempo, and likability of the music pieces as follows. A study [43] named familiarity as a factor to engage listeners on the music and addressed over its impact on involved emotions. As the level of familiarity and emotional perception between members in the groups might be different along with different provoked memories, we decided to use only unfamiliar pieces in our experiment. In addition, several articles [44, 45] counted music tempo as a factor to evaluate the emotional connections of music. The connections between music tempo and physical movements has been also reported [46]. Therefore, we chose music tracks within the range of [95–105] bmp. The judgment of liking a music is through the level of emotion of pleasure. Likable pieces can activate specified parts of the brain regions [43]. Perceived enjoyment depends on individual preference and also related with factors such as familiarity, personality [47]. Therefore, we fixed the likability level between group members on the highest level of chosen music pieces for the experiment setting.

In a preparation phase before the experiment, each participant listened to the first fifteen seconds of one hundred music pieces for candidate stimuli, all instrumental version, and rated their familiarity, likability and perceived mood (valence). The ratings of perceived mood were used to confirm the validity of our identification of valence based on the pitch and key movements of each piece. The pieces were selected by the experimenter to make them equally distributed over the combinations of categories: positive vs. negative valence × reflective vs. upbeat tracks [42]. All of the tracks were put in randomized order on an online survey. Participants who rated at least one same track as low on familiarity, high in likability and very low/very high on mood (for each of negative/positive valence tracks) for each of reflective and upbeat genre were further grouped into dyads and participated in the experiment.

2.3 Task Procedure

Before the experiment, an explanation was given and a practice session has been done. Each experiment had two sessions with three trials in the first and two trails in the second session, with 6 min for each trial and a 10-min break between the sessions. During each trial, following an audio cue, a name of a familiar object (One meter of cotton rope- An egg- A plank of wood- A tennis ball, and A pair of socks) has been shown on a TV screen while one of the four types of tracks (i.e. positive-reflective, positive-upbeat, negative-reflective, negative-upbeat), which were selected in the preparation phase as explained above, or no music, was played as background music. The order of objects and music types were randomized over dyads. Seeing the name of the object, participants started alternative uses tasks (AUT) cooperatively through communication, saying their answers loud enough to be recorded by a voice recorder. After each trial, another audio cue was presented and participants answered a questionnaire about their mood. Also, it should be noted that these chosen objects were assumed to be not different in difficulty in thinking and discussing alternative uses based on the results of pilot experiments which was confirmed after assessment of indices of creativity on our main experiments.

2.4 Evaluation of Creativity Indices

To evaluate creativity, ideas captured during experiments via voice recorder were coded. We further assessed the indices of creativity in four different categories of fluency, originality, flexibility and index of convergence (IOC) [31]. The total number of ideas mentioned during each trial has been calculated as the group fluency. The originality was assessed by the average of repetition likelihood of each idea within all groups [48]. Based on the category identification of the generated ideas, flexibility was defined as the total number of the visited categories during each trail. The IOC was a measure of cooperation behavior of dyads and calculated by dividing the number of times each dyad stayed on the same category over the times they deferred the category or totally moved to a new category.

2.5 Characterization of Communication with Inter Brain Synchronization

Dyads in each group wore a portable functional near-infrared spectroscopy (fNIRS) device (HOT-1000; Hitachi Hitech, Co.) to measure their brain activities during each trial. Participants have been instructed to avoid unnecessary movements as much as possible, to reduce the possibility of unwanted noises. According to the international 10–20 system, we placed the center (i.e. channel) of the two optodes of fNIRS device on FP2 (left channel) and FPz (medial channel), respectively for both of the dyads, based on their head shape. The device sampled changes in the absorption of near-infrared light at a sampling rate of 10 Hz. The data were preprocessed in order to reduce the effect of noise. For each set of data from participants, after linear detrending to remove the trend, we applied Savitzky-Golay smoothing filters with an order of 3 and framelen of 41 following to band pass Gaussian filter. In the last step to assess the inter-brain synchronization of each dyad, we performed the wavelet transform coherence (WTC) in the timescale of [10 to 100 s] on the filtered data of each dyad.

2.6 Characterization of Communication with Head Movement Synchronization

To assess the data of head movement, a small accelerometer (TSND121; ATR-Promotions) was attached to the fNIRS device, at the position of FPz. We set the sampling time at 10 ms. After taking raw data of head movement of each participants from the attached accelerometers, by applying Spearman’s rank correlation we calculated the head motion time lag between dyads in each group. Doing this we identified their level of head movement synchronization (HMS) [39] and assessed the head nodding data of each group during each trial. We further separated the signal into two frequency ranges of low [1–1.5 Hz] and high [3.5–5 Hz] [49] and analyzed respectively.

3 Results

3.1 Effects of Music Types on Creativity Indices

One-way repeated measures ANOVA for the five music conditions showed significant difference over conditions in terms of fluency (F(4,56) = 22.48, p < 0.001), originality (F(4,56) = 14.39, p < 0.001), and IOC (F(4,56) = 4.00, p = 0.004) but not for flexibility (F(4,56) = 0.14, p = 0.96).

Excluding the data of no-music condition, two-way repeated measures ANOVA on fluency with factors of genre and valence revealed significant main effects in both of the valence (F(1,14) = 38.98, p < 0.001) and genre (F(1,14) = 7.55, p = 0.016). There was significant interaction between valence and genre (F(1,14) = 19.37, p = 0.001). Also, as for the originality score, significant main effects in both of the valence (F(1,14) = 10.25, p = 0.006) and genre (F(1,14) = 29.34, p < 0.001) was observed. There was a significant interaction between the two factors (F(1,14) = 19.05, p = 0.001). On the other hand, two-way repeated measures ANOVA on IOC score revealed significant main effect of genre (F(1,14) = 9.42, p = 0.008), with upbeat genre tracks leading to higher IOC score. There was no significant interaction between the valence and genre or main effect of the valence for IOC.

Observing these results, separate pairwise t-tests were done between positive-upbeat music vs no music control condition, showing significant enhancing effects in fluency (t(14) = 13.93, p < 0.001) originality (t(14) = 6.75, p < 0.001) and IOC (t(14) = 2.06, p = 0.025). Summary statistics of the creativity performance indices are illustrated on Table 1.

Table 1. Indices of creativity task performance
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3.2 Effects of Music Types on Nonverbal Communication Measures

Non-verbal communication was evaluated by calculating HMS during each trial for each dyad. To test music effect on physical synchrony, one-way repeated measures ANOVA for the five conditions was conducted. There was a significant difference over the conditions (F(4,56) = 2.64, p = 0.043; Fig. 1). Also, two-way repeated measures ANOVA with genre and valence as factors of effect has been done. Quasi-significant effect was observed for valence (F(1,14) = 3.33, p = 0.089), but not for the other factor or their interaction.

Fig. 1.
figure 1

Relation between back ground music types and head movement synchrony (HMS). Data illustrated a significant enhancement of HMS for all music combinations (F(4,56) = 2.64, p = 0.043). Error bars show standard error of the mean.

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To investigate whether the difference was more significant in low frequency ranges or higher frequency ranges, separate one-way ANOVAs have been conducted. The results indicated the significant effect of music over HMS only in the low frequency range (F(4,56) = 3.19, p = 0.020).

As of the inter brain synchronization the results of ANOVA on IBS showed no significant difference between five conditions on either of the medial (F(4,56) = 0.41, p = 0.80) or the left lateral channel (F(4,56) = 1.08, p = 0.37). Summary statistics of the inter brain synchrony are shown on Table 2.

Table 2. Effects of music types on IBS
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4 Discussion

This study has addressed effect of background music on the group creativity. We hypothesized that the group creativity process might be strongly affected by different combinations of music features. In the experiment, we investigated whether listening to a specific type of music as compared to no music control condition might enhance group creativity. To test this hypothesis, we manipulated four types of music that varied on two terms of genre (reflective vs upbeat) and valence (positive vs negative), while controlling tempo, familiarity, and likability by each dyad. This control was because, in a previous study [9] with manipulations of rate, pitch height, and intensity of music they stated the main effect of rate over perceived arousal and pitch and intensity as the experiential quality of emotion over valence.

In the main part of our result, there is an evidence that background music listening in all four combinations, as compared to control condition facilitated the group creativity in term of fluency but not the other three indices of interest. To explain over this; literature on the music has proven the effect of music listening to alter mood [50, 51], and on the studies of group creativity, behaviors such as negative attitudes, judgments and evaluative behavior during discussion has been addressed as disadvantages [52, 53]. On the other side of explanation, articles on the mood suggest that positive mood enhance the generation of the ideas [54]. These in combination might suggest that music might have decreased the judgement and stress level during group creativity task with mood manipulation and thus resulted into generation of more ideas, though all music types might not have positive influence on originality, convergence index, or flexibility of the ideas.

Our next questions were what effects music valence and genre might have on group creativity, and whether the effects would be the same or not for the different creativity indices. Previous researches on the individual divergent creativity suggested the positive effect of positive valence music. When participants performed the AUT task as a team in the positive valence conditions, the total amount of shared idea has increased compared to negative valence conditions, but this effect was not apparent in the cases of originality or IOC indices for the reflective positive valence pieces. While there was no difference between conditions for flexibility, as for the IOC the main effect of the genre was statistically significant not only compared to reflective pieces but also on no music condition. IOC is a more detailed group creativity analysis to investigate the convergent tendencies of groups [31] and results indicate the advantage of listening to upbeat background tracks on convergent thinking.

Positive-upbeat music improved group creativity in all indices expect for flexibility. While to our knowledge there are only evidence of positive music enhancing individual creativity and no article on the effect of positive and upbeat music on group creativity, an interpretation can be provided through the possible enhancing effect of such music on cooperation. A previous study [55] supported that cooperation between participants resulted into a higher level of originality in their creativity task. Therefore, positive-upbeat music might have enhanced cooperation into especially higher level, leading to the general performance enhancement. This hypothesis can be further supported by the evidence of correlation between extraversion and sociability traits with upbeat music [46].

In the other part of our results, we show the higher enhancing effect of all music combinations compared to the no music one on the head movement synchrony (HMS). Our hypothesis of music enhancing non-verbal communication has been supported by this result. Also, a certain trend toward significance effect of positive valence tracks on head movement synchrony along with its positive impact on creativity task fluency index, might suggest the effect of positive valence music on cooperation between dyads, which mediated higher group creativity.

The pre-frontal cortex (PFC) has been associated with social cognition, decision-making, and goal-maintenance in several articles [56]. However, our results showed no significant effect of music on inter-brain synchrony at any of the two tested channels.

Limitation of The Current Study And Future Research.

Although there are more people who might benefit from group creativity activities, our participants are limited to international graduate students with the age range from 24 to 32 years old who are at a highly educated level. This specific nature of the sample, with the possibility of language barrier (majority of participants were not native English speakers) and cultural difference between participants (majority of the dyads were consisted of different ethnical participants), in addition to the limited sample size, makes it difficult to infer the generality of the observed results. We expect that the magnitude of the enhancement of group creativity by music might be different for groups of participants who share same language and are from the same ethnicity. Further study is needed to investigate such possibility. In addition, considering the possible effect of conscious/unconscious process on creativity [57], the effects of background music may also change in less consciously demanding settings than the current group AUT task, for example creativity observed in casual chat.

While in this study we tried to control some factors of music such as familiarity, tempo, and likability, the effect of these factors can bring interesting opportunities for further research. For example, previous studies showed higher impact of familiar songs on individual’s mood and cognition [43], so it would be reasonable to assume that familiar music would exert larger influence on group creativity as well. While we used only instrumental music pieces, the music lyrics can be an additional influential factor, which is also connected with familiarity. Furthermore, individual personality traits such as group tendency or habitual involvement in music listening can also modulate the effect of music on group creativity.

Although this study brought us some new evidence on the effect of music on group creativity at the levels of behavioral performance (creativity indices) and nonverbal communication (HMS), we could not observe the contribution of music valence or genre on inter brain synchrony. This could have been caused by smaller coverage of measured brain regions (cf. [55] for example). Another direction yet to be pursued can be to analyze contributions of inter-brain and non-verbal synchronization in combination with music to total group creativity. In our future study, we suggest combining dyadic behavioral variables to increase the chance of the better explanatory model of group creativity.

While in this study we used a questionnaire to measure the effectiveness of music to change in perceived mood and emotion in terms of arouse and pleasure in each trial [58], the limited sample size and an insensitive scale of the questionnaire led to failure in capturing consistent mood changes, so we omitted the results on the questionnaire data from the current report. It is possible that the use of objective mood measurement e.g., heart rate, blood pressure, or skin conductance [59], may bring more accurate results.

5 Conclusion

In conclusion, this study presented the effect of music to influence group creativity. The results brought an evidence of the impact of instrumental music to enhance the total number of generated ideas (fluency) between participants. All music combinations prove higher level of head nodding synchrony compared to the no music condition in our experiments and finally although positive valence have some contribution to participants’ engagement to the task and cooperation, upbeat genre music facilitate the index of cooperation to convergent ideas on a significant level. Finally, upbeat genre with positive valence music led participant the highest group creativity, presumably through enhancement of higher engagement, mutual understanding or reciprocal rapport level.