Playing and enjoying music is an universal phenomenon and can be found in all known present and past cultures (Gray et al., 2001; Zatorre and Krumhansl, 2002; Fritz et al., 2009); and emotional responses to music are an experience that almost everyone has felt. Further, in all cultures, across all ages, and without the requirement of musical expertise, people easily dance and synchronize their body movements to rhythmic music (Phillips-Silver and Trainor, 2005). Consequently, the recent two decades have seen an increasing interest in mapping the neuroanatomical correlates of music processing for understanding the underlying mechanism that make music such a unique stimulus in human culture and—although controversially discussed—human evolution (Levitin and Tirovolas, 2009). It turns out that the processing of music does not only activate the auditory system but a complex and distributed network, covering cortical and sub-cortical areas (Peretz and Zatorre, 2005; Zatorre and McGill, 2005; Koelsch, 2011, 2014; Zatorre, 2015). Two aspects have been in the closest focus over the recent years: Processing of rhythm and emotions evoked by music.

It is a daily experience that listening to predominantly rhythmic music often spontaneously triggers toe tapping, foot tapping, or head nodding, synchronous with the beat, and is perceived as pleasurable. It is an almost automatic and often involuntary process that does not require cognitive awareness in order to perform rhythmical movements in synchronization with the perceived beat (Phillips-Silver and Trainor, 2005; Trost et al., 2014). It also requires no musical skills or formal musical training, and is mostly and easily triggered by auditory stimulation. It has been shown that rhythm processing, i.e., both the production of rhythmic movements and the perception of rhythmic sounds, activates the basal ganglia and here the putamen in particular, the supplementary motor area (SMA), pre-SMA, and cerebellum (Grahn and Brett, 2007; Zatorre et al., 2007; Chen et al., 2008a,b; Grahn and Rowe, 2009); but also other substructures have been identified as structures that encode musical meter, like the caudate nucleus (Trost et al., 2014). Moreover, studies have also shown that the perception of rhythms with a preferred tempo increases activity in the premotor cortex (Kornysheva et al., 2010).

Besides rhythm, there is mounting evidence that listening to music induces emotional experiences and could interact with the affect systems. Neuroanatomically, these processes are tightly linked not only to the amygdala, but to a network that is involved in expecting and experiencing reward (Levitin and Tirovolas, 2009; Chanda and Levitin, 2013; Koelsch, 2014; Salimpoor et al., 2015). In particular the ventral striatum, comprising the caudate nucleus and the nearby nucleus accumbens together with the ventral tegmental area, the ventral pallidum and other, mainly frontal areas have been repeatedly related to music listening (Blood and Zatorre, 2001; Levitin and Tirovolas, 2009; Chanda and Levitin, 2013; Salimpoor et al., 2013, 2015; Zatorre and Salimpoor, 2013; Koelsch, 2014; Zatorre, 2015). Interestingly, Salimpoor et al. (2011) demonstrated an anatomically distinct increased release of dopamine, depending on whether an emotional response to music was anticipated or experienced. While the dorsal striatum demonstrated an elevated release of dopamine only during the anticipation of an emotional response to the music, the nucleus accumbens demonstrated this during the experience of an emotional response (Salimpoor et al., 2011). Further, the activity of the nucleus accumbens also served as a predictor of the amount one would spend for the music (Salimpoor et al., 2013).

The above-described aspects of emotional responses to music and synchronized movement to rhythmic auditory stimulation are interweaved, particularly in musical groove. Groove is often defined as the musical quality that induces movement and pleasure (Madison, 2006; Madison et al., 2011; Janata et al., 2012; Witek et al., 2014). Further, a recent transcranial-magnetic stimulation study demonstrated that musical groove is able to modulate excitability within the motor system, with stronger motor-evoked potentials to high-groove music (Stupacher et al., 2013). From a musicology perspective, there is strong evidence that the experience of groove is mainly triggered by beat density and syncopation, but also a moderate, i.e., not too simple and not too complex, rhythmic complexity (Stupacher et al., 2013; Witek et al., 2014, 2015). An example for this type of music is the genre of electronic dance music (Panteli et al., 2016), to which also the stimulation of the present study would belong.

Based on the above-described studies, it is evident that rhythmic music, like electronic dance music, triggers responses in different parts of the basal ganglia loop. In particular, the ventral striatum and the putamen appear as key areas that respond to the rhythm of the music and may generate an emotional response. Therefore, it was hypothesized that rhythmic music will affect the connectivity within a network comprising the auditory cortex, putamen/pallidum, and ventral striatum/nucleus accumbens.

This hypothesis was tested using a continuous stimulation paradigm and a resting-state like analysis approach by using stochastic dynamic causal modeling (sDCM). This procedure does not test activation strength per se, since there is no reference condition for a contrast, but examines fluctuations of the BOLD signal and functional dependencies between regions. DCM, in general, allows the specification of models with up to eight anatomically distinct regions that are either directly or indirectly connected to each other. Here, the model space was restricted to a plausible model of six areas, representing the sensory input, the rhythm processing in the basal ganglia, and the reward system.

The sDCM results revealed significant (Bonferroni-corrected) connections between the auditory cortex, putamen and ventral striatum for both hemispheres and for both groups. More importantly, several significant group differences were detected. In the following, uncorrected and Bonferroni-corrected differences are reported, where the latter ones are marked with “^*.” All differences are described relative to the control group. Reduced connectivity was detected from the right ventral striatum/nucleus accumbens to the left homolog [t₍₂₄₎ = −2.295, p < 0.031], to the right putamen/pallidum [t₍₂₄₎ = −3.196, p < 0.004], and the left auditory cortex [t₍₂₄₎ = −2.140, p < 0.043]. In addition, reduced connectivity was detected for the connection from the left putamen/pallidum to the right ventral striatum/nucleus accumbens [t₍₂₄₎ = −3.901, p < 0.001^*] and from the right to the left putamen/pallidum [t₍₂₄₎ = −4.562, p < 0.001^*]. These latter two results were also significant after Bonferroni correction (see Figure 1). Finally, the intrinsic, self-inhibitory connection of the right ventral striatum/nucleus accumbens was reduced in the music group [i.e., less negative, t₍₂₄₎ = 2.138, p < 0.043]. By contrast, increased connectivity was only detected for the connection from the left to the right auditory cortex [t₍₂₄₎ = 2.354, p < 0.027].

For the hemodynamic parameter transit, decay and epsilon, the group comparison demonstrated that the parameter transit and decay were significantly different for the right ventral striatum/nucleus accumbens, only. Although the corresponding p-values do not survive a Bonferroni correction, they are worth being mentioned, since differences were—again—detected only for this area. It appeared that transit was significantly reduced [t₍₂₄₎ = −2.158, p < 0.041], while decay was significantly increased [t₍₂₄₎ = 2.202, p < 0.038].

With this study, the aim was to investigate brain networks involved in processing a continuously playing piece of rhythmic music. Generally, the analysis of continuous stimulation paradigms is challenging. Therefore, we present for the first time the application of stochastic dynamic causal modeling as a tool for analysing the connectivity in a study with continuous stimulation. The sDCM analysis provided evidence that, when compared to the control group without music stimulation, dance floor-like rhythmic music decreased connectivity from the right putamen/pallidum, via the left putamen/pallidum to the right ventral striatum/nucleus accumbens. Further, the right ventral striatum/nucleus accumbens changed its level of activity by a reduction in self-inhibition and an altered hemodynamic response. In addition, functional connectivity was reduced from the right ventral striatum/nucleus accumbens to the left ventral striatum/nucleus accumbens, the left auditory cortex, as well as the right putamen/pallidum (see Figure 1).

Taking together, the results indicate that mainly the right ventral striatum/nucleus accumbens changed its activity as well as network coupling when listening to this piece of rhythmic, dance-floor-like music. The analysis also shows a significantly reduced connectivity from the right to the left putamen/pallidum, which may reflect a reduced coupling in motor-related brain areas. Future studies may examine further whether this is related to the experience of groove (Stupacher et al., 2013).

The results show that listening to rhythmic music not only changes the level of activation, measured in terms of BOLD signal fluctuation, of the reward system but also causes changes of connectivity within a network that is related to reward processing. The results further support the view that the ventral striatum, i.e., presumably the nucleus accumbens, is deeply involved in processing music-evoked emotions and reduces its connectivity to other areas. This does not mean a reduced activation, but rather acting on a different time scale (Mueller et al., 2015). In fact, the significantly reduced self-inhibition as well as the changed hemodynamic parameter of the right ventral striatum/nucleus accumbens indicate an increased level of activation. The results are also in line with a recent meta-analysis by Koelsch (2014), who referred to the right ventral striatum and in particular to the right nucleus accumbens as an important structure for processing music-induced emotions. In this respect, the nucleus accumbens, which is part of the dopaminergic system, is seen as part of the reward processing system which is mainly active during experiencing reward, and its activity may correlate with the reward value (Salimpoor et al., 2013, 2015; Ikemoto et al., 2015; Zatorre, 2015). This is true for any type of reward, in particular biologically relevant rewards such as food or sex, but also money (Daniel and Pollmann, 2014), and even fairness (Cappelen et al., 2014). By contrast, the dorsal striatum/caudate is generally more related to anticipation of reward but also to music-induced frisson (Koelsch et al., 2015; Zatorre, 2015). This notion is further supported by a PET study that indicated increase of dopamine release that was different for the ventral and dorsal striatum. The dorsal striatum/caudate appeared to be more involved in the anticipation and prediction of reward, while the ventral striatum/nucleus accumbens demonstrated the strongest dopamine release while experiencing an emotional response to music (Salimpoor et al., 2011).

The results presented here may contradict an fMRI study by Salimpoor and colleagues, who detected an increased connectivity between the auditory cortex and the ventral striatum (Salimpoor et al., 2011). However, one has to bear in mind that the present study used a continuous stimulation paradigm with an unfamiliar piece of music that lasted for 10.16 min and thus much longer than the stimuli of most other studies that typically last less than a minute. Further, all measures are derived from measures of BOLD fluctuations and how they propagate through the specified network. In this respect, results may not be directly comparable to studies, where connectivity measures were based on task contrasts.

Finally, it should be mentioned that the sDCM analysis also indicated an increased connectivity from the left to the right auditory cortex when compared to ordinary resting-state fMRI. This confirms the validity of our approach of analysing data from a continuous stimulation paradigm with sDCM. Moreover, an increased connectivity from left to right was reasonable to expect, since the right auditory cortex is assumed to be more dominant during the processing of tonal information, like music (Tramo, 2001; Zatorre et al., 2007).

The results presented here are also significant from a methodological perspective. The unconstrained DCM model not only confirmed the notion about the right ventral striatum, but it also confirmed the validity of the presented sDCM approach. Note that for the first time a continuous stimulation protocol was combined with a stochastic DCM approach. A stochastic DCM model is set up as a fully connected model without any constraints. Therefore, it is a significant result that the contribution of the right ventral striatum evolved naturally out of the model estimation. Further, there are no significant group differences of the hemodynamic parameter or of the self-inhibition for the auditory system. This may indicate that continuous auditory stimulation does not change hemodynamic fluctuations within the auditory system, when compared to resting-state fMRI, although the level of activation might be different.

However, there are important limitations to the selected approach that one also has to bear in mind and that restrict the general conclusions that can be drawn from the presented results. Firstly, due to methodological constrains, the present study only compares music perception to resting state and used only one piece of music. Although there is strong evidence that the detected effects are mostly related to the presentation of rhythmic music and that the majority of the participants experienced this music as pleasant, one cannot entirely rule out that comparable effects may have emerged when listening to other types of (pleasant) stimuli in a similar passive and “resting” situation. In addition, the experience of groove wasn't formally assessed in this study although several participants of the music group reported this, but one might also want to speculate whether the observed decoupling could be related to suppressing the urge to move along. Secondly, the DCM approach generally limits the number of areas that can be included in a model, and these areas should have a certain distance to avoid overlapping effects through smoothing. Accordingly, the selection of the areas of interest was based on the a-prior hypothesis described in the introduction that comprised the auditory cortex, the basal ganglia and the reward system. Therefore, only these six anatomically distinct areas were included in the model, but future study may include additional areas like the ventromedial prefrontal cortex or amygdala. Finally, fMRI studies with 13 participants per group are still within the standard range, but larger sample sizes are required and recommended for future studies for drawing more general conclusions.

This study demonstrated a reduced functional connectivity and thus less constrained activation of the reward processing system, namely the right ventral striatum and nucleus accumbens, while listening to a several minutes-long pleasurable and rhythmic piece of music—as compared to silence. The results give a deeper insight into the power of music and show how easily and how strongly rhythmic music interacts with the affect and basal ganglia system, and that emotional experiences during listening to music may be generated through a stronger activation and, simultaneously, reduced functional connectivity of the reward system. Thus, “The powers of cognition that are set into play by this representation [of a beautiful object] are hereby in a free play, since no determinate concept restricts them to a particular cognition” (Kant, 1790) (Guyer, 2002).

HB contributed to the analysis of the data and writing of the article. BO contributed to the planning, stimulus preparation, and writing of the article. KS contributed to the planning, stimulus preparation, performance, analysis, and writing of the article.