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Proceedings of the 9th International Conference of Students of Systematic Musicology (SysMus16),
Jyväskylä, Finland, 8th - 10th June 2016. Birgitta Burger, Joshua Bamford, & Emily Carlson (Eds.).
Social effects of interpersonal synchronization during listening to music
compared to a metronome: What can we learn from implicit measures?
Jan Stupacher1, Matthias Witte1, Guilherme Wood1
1 University of Graz, Graz, Austria
jan.stupacher@uni-graz.at
Abstract
Interpersonal coordination, such as simultaneous rhythmic movement, is a fundamental way to form
socioemotional connections. The social and emotional power of music might further strengthen such
interpersonal bonds. Here, we tested if interpersonal synchronization (synchronous vs. asynchronous
finger-tapping) affects sympathy and helpfulness more strongly when listening to music compared to a
metronome. We tested 40 participants and used an explicit and an implicit measure to assess their social
orientation toward a tapping partner (i.e., one of two experimenters). Participants directly rated the
friendliness of the experimenter on a 9-point Likert scale. As a more indirect or implicit measure of social
orientation, we counted the number of pencils (out of a total of eight) that the participants collected after
the experimenter “accidentally” dropped them. After five seconds, the experimenter started to help the
participants or collected the pencils herself. Results of the pencil test showed that participants were more
helpful toward an experimenter who tapped synchronously compared to asynchronously. Importantly,
this result was completely driven by the effect of interpersonal synchrony during listening to music.
When listening to music, participants collected 38 pencils (M = 3.80, SD = 3.29) after tapping in
interpersonal synchrony compared to only 13 pencils (M = 1.30, SD = 2.67) after tapping
asynchronously. No such effect was found for the metronome. The results of explicit ratings of the
experimenter’s friendliness, however, did not confirm these effects. The direct ratings might have been
more strongly influenced by social desirability or related motivational distortions. Since music is a
product of social interactions and might even be the result of evolutionary adaptation, we conclude that
especially during listening to music, interpersonal synchrony or asynchrony can fulfill or violate hard-
wired social expectations. Additionally, we could show that implicit or indirect measures can help
elucidate how music, movement and prosocial behavior are connected.
Keywords: social entrainment, interpersonal affiliation, joint action, sensorimotor synchronization
Introduction
Interpersonal coordination – be it behavior
matching, such as mimicry, or interactional
synchrony, such as simultaneous rhythmic
movements (e.g., Bernieri & Rosenthal, 1991)
– is a fundamental way to form socioemotional
connections. Here, we addressed the question
how synchronous and asynchronous finger-
tapping with another person during either
listening to music or a metronome influences
sympathy and prosocial orientation.
Behavioral mimicry, interactional
synchrony and music
Behavioral mimicry describes the mirroring
of another person’s gestures, postures or other
movements (e.g., speech gestures, foot shaking;
for a review, see Chartrand & Lakin, 2013).
Factors that increase the tendency to mimic the
behavior of another person include prosocial
attitudes (Leighton, Bird, Orsini, & Heyes,
2010), being in a good mood (Likowski et al.,
2011), and the likeability (Stel et al., 2010) or
the goal to get along with this person (Lakin &
Chartrand, 2003). In turn, being mimicked can
positively affect feelings of liking toward the
mimicker (Chartrand & Bargh, 1999), feelings
of interpersonal closeness (Ashton–James, van
Baaren, Chartrand, Decety, & Karremans,
2007), and prosocial behavior in adults (van
Baaren, Holland, Kawakami, & van
Knippenberg, 2004) and infants (Carpenter,
Uebel, & Tomasello, 2013).
In contrast to behavioral mimicry, that
usually includes a time lag of a few seconds,
interactional synchrony describes movements
that are temporally matched. A variety of
research suggests that the interpersonal
synchronization of movements, such as
walking, pendulum-swinging, chair-rocking,
body-swaying, or finger-tapping, promotes
Proceedings of the 9th International Conference of Students of Systematic Musicology (SysMus16), Jyväskylä,
Finland, 8th - 10th June 2016. Birgitta Burger, Joshua Bamford, & Emily Carlson (Eds.).
affiliation and prosocial orientation (e.g.,
Demos, Chaffin, Begosh, Daniels, & Marsh,
2012; Hove & Risen, 2009; Marsh et al., 2009;
Reddish, Fischer, & Bulbulia, 2013; Valdesolo
& Desteno, 2011; Wiltermuth & Heath, 2009).
By using a moving visual timekeeper, Hove
and Risen (2009) showed that the degree of
synchrony between the participants’ and the
experimenters’ finger-taps was positively
related to how much participants liked the
experimenter. Such effects may even be
stronger when moving together while listening
to music. When rocking in a chair with a
partner, the degree of synchronization with
music is positively correlated with the feeling
of interpersonal connectedness (Demos et al.,
2012).
Listening to music has a strong emotional
component and, similarly to social bonding,
engages the endogenous opioid system (Tarr,
Launay, & Dunbar, 2014). Furthermore,
rhythmic synchronization in musical contexts
represents a special form of social entrainment
(Phillips-Silver, Aktipis, & Bryant, 2010), and
can provide a controlled yet ecologically valid
domain to study social interaction and joint
action (Keller, Novembre, & Hove, 2014). In
the current study, we tested the hypothesis that
interpersonal synchronization affects sympathy
and prosocial orientation more strongly when
listening to music compared to when listening
to a metronome.
Measures of sympathy, affiliation and
prosocial behavior
Direct or explicit measures, such as self-
reports, are one of the main pillars of
experimental psychology. However, they can
suffer from credibility issues, are vulnerable to
consistency seeking, and depend on the
participants abilities to introspectively access
the processes that underlie their feelings and
behaviors (Paulhus & Vazire, 2005). In
contrast, indirect or implicit measures, such as
implicit association tests (Greenwald, McGhee,
& Schwartz, 1998), affective priming tasks
(Fazio, Jackson, Dunton, & Williams, 1995;
Fazio, Sanbonmatsu, Poweu, & Kardes, 1986),
the seating distance to another person (Holland,
Roeder, van Baaren, Brandt, & Hannover,
2004), or the number of collected pencils that
another person dropped (Macrae & Johnston,
1998), do not require introspection. This
particular characteristic led to the assumptions
that implicit measures can reflect unconscious
mental representations and are less susceptible
to motivational distortions, such as social
desirability (for a review and discussion of
these assumptions, see Gawronski, LeBel, &
Peters, 2007). However, it is important to note
that although specific factors can affect implicit
measures without affecting comparable explicit
measures (e.g., Gawronski & LeBel, 2008),
implicit measures do not necessarily reflect
unconscious mental representations
(Gawronski et al., 2007). Additionally, domain-
specific motivational distortions (e.g., the
motivation to control prejudice reactions) might
be more powerful in explaining differences
between implicit and explicit measures than
social desirability in general (Gawronski et al.,
2007; Hofmann, Gschwendner, Nosek, &
Schmitt, 2005).
Various implicit measures have previously
been used to assess prosocial orientation in the
domains of mimicry and interpersonal
synchronization. In a row of chairs, participants
who had been mimicked sat closer to a chair
with belongings from another person than
participants who had not been mimicked
(Ashton–James et al., 2007). Being mimicked
also increases the likelihood of collecting
pencils that another person dropped (van
Baaren et al., 2004). Similar tests have been
used to show that helpfulness is increased after
playing a prosocial video game compared to
playing a neutral or aggressive video game
(Greitemeyer & Osswald, 2010), and decreased
when reminded of money (Vohs, Mead, &
Goode, 2006). In a musical context, Kokal,
Engel, Kirschner, and Keysers (2011) showed
that participants collected more pencils to help
a synchronous co-drummer compared to an
asynchronous one.
Since previous studies on behavioral
mimicry and interactional synchrony
successfully assessed affiliation and prosocial
orientation with implicit and explicit tests, the
current study combined and compared both
methods.
Methods
Participants
Forty students of the University of Graz (20
females, mean age = 23.7 years, SD = 2.60)
without musical training participated in the
study after providing informed consent.
Proceedings of the 9th International Conference of Students of Systematic Musicology (SysMus16), Jyväskylä,
Finland, 8th - 10th June 2016. Birgitta Burger, Joshua Bamford, & Emily Carlson (Eds.).
Design and procedure
Participants were assigned to one of four
groups: tapping with a partner who tapped
synchronously or asynchronously during
listening to music or a metronome. The
resulting between-subject design consisted of
two independent variables: interpersonal
synchrony (sync vs. async tapping) and musical
quality (music vs. metronome).
Figure 1. A) Setup for the tapping task. Participants
(P) and the experimenter (E) tapped their right
index finger on two different pads on the same
tapping device (Akai LPD8). Both wore head-
phones. B) Visualization and examples of the four
experimental groups.
Both, participant and experimenter tapped
their right index finger on two different pads on
a MIDI tapping device (Figure 1A).
Each group of participants (sync/music,
async/music, sync/metro, and async/metro;
Figure 1B) consisted of five females and five
males. The tapping partner was one of two
female experimenters (psychology students, 22
and 25 years old) who did not know the
participants. In the sync/music group
participants tapped at the music’s beat rate and
the experimenter tapped at the same rate given
by a metronome that was slightly adjusted for
minimal tempo changes. In the async/music
group participants tapped at the music’s beat
rate and the experimenter tapped at a 30% faster
rate given by a metronome. In the sync/metro
group participants and the experimenter tapped
in time with the same metronome. In the
async/metro group the experimenter tapped
with a 30% faster metronome than the
participants. Participants were instructed to tap
in time with the stimuli and to focus on their
own tapping.
Material
Acoustic Stimuli
To facilitate sensorimotor synchronization
in the tapping task with music, we used three
music clips that were rated high on groove (i.e.,
highly movement inducing) in a recent study
(Janata, Tomic, & Haberman, 2012; see also
Stupacher, Hove, Novembre, Schütz-Bosbach,
& Keller, 2013; Stupacher, Hove, & Janata, in
press; Table 1). A metronome count-in with a
length of one measure (4 sounds in 4/4 time)
was used to indicate the beat rate. In the
metronome conditions isochronous snare drum
sounds were presented with the same beat rate
as the three music clips. The clips lasted
between 31 and 33 seconds, were randomized,
and repeated 4 times, resulting in 12 clips in
total. Before tapping with the experimenter,
participants completed practice trials to ensure
that they understood the task. The tapping part
of the experiment lasted approximately 8
minutes.
Self-reports
Participants rated their current mood (very
bad vs. very good), the friendliness of the
experimenter (very unfriendly vs. very
friendly), and the interaction with the
Proceedings of the 9th International Conference of Students of Systematic Musicology (SysMus16), Jyväskylä,
Finland, 8th - 10th June 2016. Birgitta Burger, Joshua Bamford, & Emily Carlson (Eds.).
experimenter (very unpleasant vs. very
pleasant) on a 9-point Likert scale before and
after the tapping task. After the tapping task
they additionally reported their interest to
generally participate in another test run by the
same experimenter (no interest vs. strong
interest).
Prosocial orientation
After the tapping task the experimenter
stood up to get the questionnaires and a cup
with eight pencils stored in a cupboard near the
participant’s chair. She pretended to
accidentally drop the pencils and took about
five seconds to place the questionnaires on a
desk giving the participant enough time to help.
Afterwards she started collecting the remaining
pencils with or without the participant’s help.
Prosocial orientation toward the experimenter
was assessed by the number of pencils the
participants collected.
Results
Tapping data
Inter-tap-intervals (ITIs) were computed by
subtracting the absolute time of a tap n from the
absolute time of the following tap n+1. Doubled
or missing taps and outlier ITIs (+/- 2 SD from
the mean ITI for each participant and trial) were
excluded (5.5%). Mean ITIs indicated that
participants tapped at the beat rate of the stimuli
(see Table 1). Three separate ANOVAs – one
for each tempo – on the mean ITIs with the
factors interpersonal synchrony (sync vs.
async) and musical quality (music vs.
metronome) revealed no main effects (ps > .07)
and no interactions (ps > .17). No main effects
of interpersonal synchrony and musical quality
and no interaction were found in an additional
ANOVA on the standard deviations of ITIs
(ps > .5), indicating that the stability of the
tapping rate did not differ between groups.
Self-reports
Chi-squared tests were used for the analysis
of self-reports since all variables suffered from
a ceiling effect (skewness between -0.50
and -1.93, all Kolmogorov-Smirnov ps < .01).
Seven individual tests (for each pre- and post-
tapping rating) with the factors interpersonal
synchrony and musical quality on the sum of
ratings per cell revealed non-significant results
(ps > .5). Main effects of interpersonal
synchrony and musical quality were also non-
significant (ps > .2).
Prosocial orientation
Nonparametric tests were used since the
assumption of normal distribution was not met.
A chi-squared test with the factors inter-
personal synchrony and musical quality on the
total number of collected pencils was
significant, χ²(1) = 7.16, p = .007. Further
comparisons showed that participants collected
more pencils after synchronous tapping
compared to asynchronous tapping
χ²(1) = 5.45, p = .020. This result was
completely driven by the effect of interpersonal
synchrony during listening to music,
χ²(1) = 12.26, p < .001 (38 pencils [M = 3.80,
SD = 3.29] after sync/music compared to
13 pencils [M = 1.30, SD = 2.67] after
async/music, see Figure 2B). No effect of
musical quality on the number of collected
pencils was found, χ²(1) = 1.47, p > .2.
Discussion
We tested the hypothesis that interpersonal
synchronization has a stronger effect on
sympathy and prosocial orientation when
listening to music compared to a metronome.
The results of an implicit test confirmed our
hypothesis and showed that participants were
more helpful toward a person who tapped
synchronously compared to asynchronously.
Table 1: Features of the acoustic stimuli used for tapping with music and the corresponding mean inter-tap-
intervals (ITI) of participants.
Title
Artist
Meter
Groove rating *
Tempo
ITI in ms (SD)
Superstition
Stevie Wonder
4/4
108.7
100 BPM / 600 ms
590.89 (26.49)
Flash Light
Parliament
4/4
105.1
105 BPM / 571 ms
561.28 (27.12)
Look-Ka Py Py
The Meters
4/4
92.5
87 BPM / 690 ms
678.26 (34.84)
* Janata et al., 2012 (MIDI scale from 0 to 127)
Proceedings of the 9th International Conference of Students of Systematic Musicology (SysMus16), Jyväskylä,
Finland, 8th - 10th June 2016. Birgitta Burger, Joshua Bamford, & Emily Carlson (Eds.).
Importantly, this was only true when
participants tapped in time with music, but not
with a metronome. The results of explicit
ratings of the experimenter’s friendliness,
however, did not confirm this effect.
Figure 2. A) Mean ratings of the experimenter’s
friendliness given by participants in each
experimental group after the tapping task. B) Total
number of pencils that the participants in each
experimental group collected after the experimenter
“accidentally” dropped them (* p < .001).
Music evokes a variety of emotions, some of
them related to attachment and the fulfillment
of social needs, such as trust, cooperation or the
prevention of isolation (Freeman, 2000;
Koelsch, 2010; Vuilleumier & Trost, 2015).
This emotional and social power of music
might even be the result of evolutionary
adaptation (Cross, 2001; Freeman, 2000;
Huron, 2001). Compared to non-musical
stimuli, interpersonal synchronization with
music might affect social bonding not only via
joint action, but also via affective and
neurophysiological mechanisms (e.g.,
endorphins) associated with the music itself
(Tarr et al., 2014). When moving together in
time with the same music one shares a common
experience. This shared experience might
facilitate social bonding compared to the
experience of just moving in synchrony without
music (Demos et al., 2012). Taken together,
these findings suggest that, especially during
listening to music, interpersonal synchrony or
asynchrony can fulfill or violate hard-wired
affective and social expectations.
These socio-emotional characteristics of
music can explain why we found an effect of
interpersonal synchrony on helpfulness during
tapping with music but not during tapping with
a metronome (Figure 2B). But they also raise
the question if the difference in helpfulness
represents a more prosocial orientation in the
synchrony group resulting from greater social
bonding or a less prosocial orientation in the
asynchrony group resulting from violated social
expectations. The comparison of the number of
collected pencils between the four groups,
especially the comparison between music and
metronome, suggests that asynchronous
tapping during listening to music might have
negatively affected the social orientation
toward the experimenter. In contrast, Hove and
Risen (2009) found higher experimenter-
likeability ratings after synchronized tapping
compared to asynchronous tapping and a
control condition in which participants tapped
alone, but no difference between asynchronous
tapping and the control. How can we explain
this divergence?
As already mentioned, our experimental
design included two experiences that enable
social bonding, namely the synchronization of
movements and listening to music (Freeman,
2000; Koelsch, 2010; Tarr et al., 2014). It is
possible that, during listening to music,
asynchronous tapping resulted in discrepancies
between these two experiences, leading to
violated affective and social expectations. The
lower number of collected pencils after
asynchronous tapping with music, as compared
to synchronous tapping with music, might show
how these discrepancies negatively affected
prosocial orientation.
From a methodological point of view, proso-
cial effects of synchronization may not be as
robust as previous research suggested
(Schachner & Garvin, 2010). This might partly
be due to the fact that the effect sizes depend on
Proceedings of the 9th International Conference of Students of Systematic Musicology (SysMus16), Jyväskylä,
Finland, 8th - 10th June 2016. Birgitta Burger, Joshua Bamford, & Emily Carlson (Eds.).
the measures used. Our study showed that in
contrast to the indirect measure of prosocial
orientation, the direct measures (i.e., self-
reported ratings of experimenter-friendliness
and interaction-pleasantness) did not differ
between groups.
It is important to note that sympathy-related
ratings of the experimenter and helpfulness
toward the experimenter represent different
partial aspects of social bonding. However,
since previous research suggests that
interpersonal synchronization affects a wide
range of feelings, judgments, and behaviors,
including connectedness, likeability, co-
operation, helpfulness, and conformity (Demos
et al., 2012; Hove & Risen, 2009; Kokal et al.,
2011; Wiltermuth & Heath, 2009) these aspects
seem to be tightly related. We therefore
expected to find comparable results of
explicitly assessed experimenter-friendliness
and implicitly assessed helpfulness.
The null result of self-reports are due to a
ceiling effect. Without this ceiling effect we
potentially would have been able to detect
differences in ratings of the sync/music group
and the async/music group. Please note that we
still found a ceiling effect in self-reports when
changing the 9-point Likert scale to a
continuous scale from 0 to 100, rephrasing the
extreme values of the scales, and training the
tapping partner (i.e., the experimenter) to act
reserved (Stupacher, Witte, & Wood,
unpublished data). A possible explanation for
the ceiling effect in self-reports is the individual
need for self-consistency (Robins & John,
1997), i.e., high post-tapping ratings could have
been driven by high pre-tapping ratings.
In contrast to the implicit assessment of
prosocial orientation, self-reports might have
been more strongly influenced by social
desirability or related motivational distortions.
Even though the questionnaires were
anonymous, the fact that the experimenter
would look at the ratings at some point could
have led to more positive ratings than expected.
However, the extent to which social desirability
can explain differences between explicit and
implicit measures is still under debate
(Hofmann et al., 2005). Here, we could show
that an implicit measure successfully detected
changes in prosocial orientation related to
interpersonal synchrony, whereas self-reports
failed to detect similar effects. We conclude
that although, or even because, self-reports
suffered from methodological limitations, the
use of implicit measures can enrich our
understanding of social bonding, interpersonal
synchronization, and music.
Acknowledgements
We would like to thank Michael Hove and
Johanna Reichert for helpful comments and
discussions. Jan Stupacher is supported by a
DOC fellowship of the Austrian Academy of
Sciences at the Department of Psychology,
University of Graz.
References
Ashton–James, C., van Baaren, R. B., Chartrand,
T. L., Decety, J., & Karremans, J. (2007). Mimicry and
me: the impact of mimicry on self–construal. Social
Cognition, 25, 518–535.
Bernieri, F. J., & Rosenthal, R. (1991).
Interpersonal coordination: behavior matching and
interactional synchrony. In R. S. Feldman & B. Rime
(Eds.), Fundamentals of Nonverbal Behavior: Studies in
Emotion & Social Interaction (pp. 401–432). Cambridge,
England: Cambridge University Press.
Carpenter, M., Uebel, J., & Tomasello, M. (2013).
Being mimicked increases prosocial behavior in 18-
month-old infants. Child Development, 84, 1511–1518.
Chartrand, T. L., & Bargh, J. A. (1999). The
chameleon effect: the perception-behavior link and social
interaction. Journal of Personality and Social Psychology,
76, 893–910.
Chartrand, T. L., & Lakin, J. L. (2013). The
antecedents and consequences of human behavioral
mimicry. Annual Review of Psychology, 64, 285–308.
Cross, I. (2001). Music, cognition, culture, and
evolution. Annals of the New York Academy of Sciences,
930, 28–42.
Demos, A. P., Chaffin, R., Begosh, K. T., Daniels,
J. R., & Marsh, K. L. (2012). Rocking to the beat: effects
of music and partner’s movements on spontaneous
interpersonal coordination. Journal of Experimental
Psychology: General, 141, 49–53.
Fazio, R. H., Jackson, J. R., Dunton, B. C., &
Williams, C. J. (1995). Variability in automatic activation
as an unobtrusive measure of racial attitudes: a bona fide
pipeline? Journal of Personality and Social Psychology,
69, 1013–1027.
Fazio, R. H., Sanbonmatsu, D. M., Poweu, M. C.,
& Kardes, F. R. (1986). On the automatic activation of
attitudes. Journal of Personality and Social Psychology,
50, 229–238.
Freeman, W. J. (2000). A neurobiological role of
music in social bonding. In N. Wallin, B. Merkur, & S.
Brown (Eds.), The Origins of Music (pp. 411–424).
Cambridge, MA: MIT Press.
Gawronski, B., & LeBel, E. P. (2008).
Understanding patterns of attitude change: when implicit
Proceedings of the 9th International Conference of Students of Systematic Musicology (SysMus16), Jyväskylä,
Finland, 8th - 10th June 2016. Birgitta Burger, Joshua Bamford, & Emily Carlson (Eds.).
measures show change, but explicit measures do not.
Journal of Experimental Social Psychology, 44, 1355–
1361.
Gawronski, B., LeBel, E. P., & Peters, K. R.
(2007). What so implicit measures tell us? Scrutinizing the
validity of three common assumptions. Perspectives on
Psychological Science, 2, 181–193.
Greenwald, A. G., McGhee, D. E., & Schwartz, J.
L. K. (1998). Measuring individual differences in implicit
cognition: the implicit association test. Journal of
Personality and Social Psychology, 74, 1464–1480.
Greitemeyer, T., & Osswald, S. (2010). Effects of
prosocial video games on prosocial behavior. Journal of
Personality and Social Psychology, 98, 211–221.
Hofmann, W., Gschwendner, T., Nosek, B. A., &
Schmitt, M. (2005). What moderates implicit—explicit
consistency? European Review of Social Psychology, 16,
335–390.
Holland, R. W., Roeder, U. R., van Baaren, R. B.,
Brandt, A. C., & Hannover, B. (2004). Don’t stand so
close to me: the effects of self-construal on interpersonal
closeness. Psychological Science, 15, 237–242.
Hove, M. J., & Risen, J. L. (2009). It’s all in the
timing: interpersonal synchrony increases affiliation.
Social Cognition, 27, 949–960.
Huron, D. (2001). Is music an evolutionary
adaptation? Annals of the New York Academy of Sciences,
930, 43–61.
Janata, P., Tomic, S. T., & Haberman, J. M.
(2012). Sensorimotor coupling in music and the
psychology of the groove. Journal of Experimental
Psychology: General, 141, 54–75.
Keller, P. E., Novembre, G., & Hove, M. J. (2014).
Rhythm in joint action: psychological and
neurophysiological mechanisms for real-time
interpersonal coordination. Philosophical Transactions of
the Royal Society: Series B, 369, 20130394.
Koelsch, S. (2010). Towards a neural basis of
music-evoked emotions. Trends in Cognitive Sciences, 14,
131–137.
Kokal, I., Engel, A., Kirschner, S., & Keysers, C.
(2011). Synchronized drumming enhances activity in the
caudate and facilitates prosocial commitment - If the
rhythm comes easily. Plos One, 6, e27272.
Lakin, J. L., & Chartrand, T. L. (2003). Using
nonconscious behavioral mimicry to create affiliation and
rapport. Psychological Science, 14, 334–339.
Leighton, J., Bird, G., Orsini, C., & Heyes, C.
(2010). Social attitudes modulate automatic imitation.
Journal of Experimental Social Psychology, 46, 905–910.
Likowski, K. U., Weyers, P., Seibt, B., Stöhr, C.,
Pauli, P., & Mühlberger, A. (2011). Sad and lonely? Sad
mood suppresses facial mimicry. Journal of Nonverbal
Behavior, 35, 101–117.
Macrae, C. N., & Johnston, L. (1998). Help, I need
somebody: automatic action and inaction. Social
Cognition, 16, 400–417.
Marsh, K. L., Richardson, M. J., & Schmidt, R. C.
(2009). Social connection through joint action and
interpersonal coordination. Topics in Cognitive Science, 1,
320–339.
Paulhus, D. L., & Vazire, S. (2005). The self-
report method. In R. W. Robins, R. C. Fraley, & R. F.
Krueger (Eds.), Handbook of Research Methods in
Personality Psychology (pp. 224–239). New York:
Guilford.
Phillips-Silver, J., Aktipis, C. A., & Bryant, G. A.
(2010). The ecology of entrainment: foundations of
coordinated rhythmic movement. Music Perception, 28,
3–14.
Reddish, P., Fischer, R., & Bulbulia, J. (2013).
Let’s dance together: synchrony, shared intentionality and
cooperation. Plos One, 8, e71182.
Robins, R. W., & John, O. P. (1997). The quest for
self-insight: theory and research on accuracy and bias in
self-perception. In R. Hogan, J. Johnson, & S. R. Briggs
(Eds.), Handbook of Personality Psychology (pp. 649–
679). San Diego, CA: Academic Press.
Schachner, A., & Garvin, L. (2010). Does
synchrony really affect social variables? Effects on
cooperation, conformity may not be robust. Poster
presented at the International Conference on Music
Perception and Cognition. Seattle, WA.
Stel, M., van Baaren, R. B., Blascovich, J., van
Dijk, E., McCall, C., Pollmann, M. M. H., … Vonk, R.
(2010). Effects of a priori liking on the elicitation of
mimicry. Experimental Psychology, 57, 412–418.
Stupacher, J., Hove, M. J., Novembre, G., Schütz-
Bosbach, S., & Keller, P. E. (2013). Musical groove
modulates motor cortex excitability: a TMS investigation.
Brain and Cognition, 82, 127–136.
Stupacher, J., Hove, M. J., & Janata, P. (in press).
Audio features underlying perceived groove and
sensorimotor synchronization in music. Music Perception.
Tarr, B., Launay, J., & Dunbar, R. I. M. (2014).
Music and social bonding: “self-other” merging and
neurohormonal mechanisms. Frontiers in Psychology, 5,
1096.
Valdesolo, P., & Desteno, D. (2011). Synchrony
and the social tuning of compassion. Emotion, 11, 262–
266.
Van Baaren, R. B., Holland, R. W., Kawakami,
K., & van Knippenberg, A. (2004). Mimicry and prosocial
behavior. Psychological Science, 15, 71–74.
Vohs, K. D., Mead, N. L., & Goode, M. R. (2006).
The psychological consequences of money. Science, 314,
1154–1156.
Vuilleumier, P., & Trost, W. (2015). Music and
emotions: from enchantment to entrainment. Annals of the
New York Academy of Sciences, 1337, 212–222.
Wiltermuth, S. S., & Heath, C. (2009). Synchrony
and cooperation. Psychological Science, 20, 1–5.
