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Effects of Sad and Happy Music on Mind-Wandering and the Default Mode Network

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Music is a ubiquitous phenomenon in human cultures, mostly due to its power to evoke and regulate emotions. However, effects of music evoking different emotional experiences such as sadness and happiness on cognition, and in particular on self-generated thought, are unknown. Here we use probe-caught thought sampling and functional magnetic resonance imaging (fMRI) to investigate the influence of sad and happy music on mind-wandering and its underlying neuronal mechanisms. In three experiments we found that sad music, compared with happy music, is associated with stronger mind-wandering (Experiments 1A and 1B) and greater centrality of the nodes of the Default Mode Network (DMN) (Experiment 2). Thus, our results demonstrate that, when listening to sad vs. happy music, people withdraw their attention inwards and engage in spontaneous, self-referential cognitive processes. Importantly, our results also underscore that DMN activity can be modulated as a function of sad and happy music. These findings call for a systematic investigation of the relation between music and thought, having broad implications for the use of music in education and clinical settings.
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SCiENTiFiC RepoRts | 7: 14396 | DOI:10.1038/s41598-017-14849-0
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Eects of Sad and Happy Music on
Mind-Wandering and the Default
Mode Network
Liila Taru1, Corinna Pehrs1, Stavros Skouras1 & Stefan Koelsch2
Music is a ubiquitous phenomenon in human cultures, mostly due to its power to evoke and regulate
emotions. However, eects of music evoking dierent emotional experiences such as sadness and
happiness on cognition, and in particular on self-generated thought, are unknown. Here we use
probe-caught thought sampling and functional magnetic resonance imaging (fMRI) to investigate
the inuence of sad and happy music on mind-wandering and its underlying neuronal mechanisms. In
three experiments we found that sad music, compared with happy music, is associated with stronger
mind-wandering (Experiments 1A and 1B) and greater centrality of the nodes of the Default Mode
Network (DMN) (Experiment 2). Thus, our results demonstrate that, when listening to sad vs. happy
music, people withdraw their attention inwards and engage in spontaneous, self-referential cognitive
processes. Importantly, our results also underscore that DMN activity can be modulated as a function
of sad and happy music. These ndings call for a systematic investigation of the relation between music
and thought, having broad implications for the use of music in education and clinical settings.
e ubiquity of music in human culture owes to its capability to evoke and enhance a wide range of emotions.
Sadness and happiness are among the most frequent emotions evoked by music cross-culturally1. Sad- and
happy-sounding music (henceforth referred to as sad and happy music) exist at least since antiquity, as witnessed
for example from the Greek music system (6th century BC), which ascribed certain emotional qualities, including
sadness and happiness, to the unique sound of musical modes.
Although over the last decade neuroscience has provided numerous insights into how sad and
happy music modulate activity in brain structures involved in emotion2, the effects of sad and happy
music on cognition remain elusive. In a previous study3 we found that a common use of sad (but
not happy) music is to enhance self-reflection. Since the ability for self-reflection crucially requires
internally-directed cognition4, which is typical of mind-wandering, we sought to investigate the influ-
ence of sad and happy music on mind-wandering episodes. Mind-wandering is a form of self-generated
thought, which involves overcoming the constraints of the “here and now” by immersing in one’s own
stream of consciousness5. Humans spend a substantial amount of time mind-wandering6, predomi-
nantly about matters of self-importance7, social relationships8, future planning9, and autobiographical
memories10. Mind-wandering is associated with benefits such as facilitating creative problem solving11
and delaying gratication12, but also with costs such as disrupting ongoing task performance13. Research has
revealed that aective processes have an important impact on spontaneous thoughts. Although there is robust evi-
dence of an association between mind-wandering and negative aect in healthy6 as well as depressed individuals14,
it has also been shown that this relationship is strongly mediated by the content of thoughts, with past-related
thoughts being linked to higher levels of unhappiness10,15. Studies have also pointed to a key role of the qualitative
features of participants’ thoughts in adaptive forms of mind-wandering. For example, thoughts focused on the
future15 or rated as interesting16 lead to subsequent positive mood. Similarly, future thinking reduces cortisol
levels following social stress17. Mind-wandering is supported by a set of brain regions typically active during rest
periods, also referred to as the Default Mode Network1823 (DMN). e DMN comprises most notably the medial
prefrontal cortex (dorsomedial prefrontal cortex [dmPFC] and ventromedial prefrontal cortex [vmPFC]), the
medial parietal cortex (posterior cingulate cortex [PCC] and precuneus [PCu]), and the lateral parietal cortex
(posterior inferior parietal lobule [pIPL]). Despite a remarkable increase of research on mind-wandering6,21 as
1Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany. 2Department of Biological and
Medical Psychology, University of Bergen, Bergen, Norway. Correspondence and requests for materials should be
addressed to L.T. (email: liilataru@zedat.fu-berlin.de)
Received: 20 July 2017
Accepted: 17 October 2017
Published: xx xx xxxx
OPEN
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SCiENTiFiC RepoRts | 7: 14396 | DOI:10.1038/s41598-017-14849-0
well as music-evoked emotions24,25 in recent years, it is unknown whether music with a sad and/or happy emo-
tional tone modulates mind-wandering.
In Experiment 1A, we tested the hypothesis that sad music, compared with happy music, is associated
with stronger mind-wandering. Additionally, we explored whether the qualitative content and the form of
mind-wandering vary according to the music’s type (sad and happy). We analyzed a sample of 216 participants
(132 female), who took part in an online probe-caught thought sampling experiment (i.e., intermittently probing
individuals about their current mental state while listening to music), which combined a self-report measure of
mind-wandering20 with an assessment of the qualitative elements and the form of self-generated thought2628.
Participants were asked to listen to music previously shown to evoke emotions of sadness and happiness, while
keeping their eyes closed. Furthermore, they had to report their mental experience as occurring immediately
before the music stopped. Each thought probe featured two initial items measuring mind-wandering. The
rst item (“Where was your attention just before the music stopped?”) was used as a direct self-report meas-
ure of the strength of mind-wandering (participants answered on a scale from 1 =completely on the music
to 7 =completely on something else”). e second item (“How aware were you of where your attention was
focused?”) assessed meta-awareness as an orthogonal measure of mind-wandering (participants answered on
a scale from 1 =completely unaware” to 7 = “completely aware”). Only if participants answered > 1 on the rst
item, they were asked to provide further details about the content and the form of their thoughts, beginning with
an open-ended question (“What were you thinking about, just before the music stopped?”). Moreover, based on
previous research2628, we developed eight items to assess an array of phenomenological dimensions of thought
(see TableS1 for precise questions and answer scales), including (i) valence, (ii) temporal orientation (past and
future), (iii) self-referentiality, (iv) social aspects (familiar and unknown people), (v) movements, (vi) bodily sen-
sations, (vii) music (thinking about the musical structure and evaluating the music), and (viii) experiment (think-
ing about the experiment). e items related to the music (vii) were included to verify that task-relatedness was
signicantly lower during sad compared with happy music, in line with the process of perceptual decoupling29
(i.e., the disengagement of attention from perception) during mind-wandering. Aer these items, participants
were asked whether their thoughts were based on images (“similar to a lm or a painting”) or words (“similar to a
dialogue or an audio-book”) to assess the form of mental activity.
Sad and happy music typically dier in tempo (with sad music featuring slower tempi than happy music,
leading to lower levels of evoked arousal) and this dierence, rather than the emotional quality of sad or happy
music, may inuence mind-wandering. For example, higher levels of sleepiness during a laboratory task were
associated with increased mind-wandering30. erefore, we conducted Experiment 1B (N = 140), which was a
shorter version of Experiment 1A (see Methods) and featured slow sad and happy music stimuli (i.e., both sad
and happy stimuli had the same slow tempo) as well as fast sad and happy music stimuli (i.e., both sad and happy
stimuli had the same fast tempo).
Motivated by the results of Experiment 1A and given previous evidence for the DMN’s role in spontaneous
cognition1823, in Experiment 2 we tested the hypothesis that listening to sad compared with happy music is
associated with increased DMN activity. From a sample of 24 right-handed healthy participants (12 female),
we obtained whole-brain fMRI data while they listened to 4 min blocks of sad and happy music (with the same
tempo) with their eyes closed. Aer each block, participants provided valence, arousal, sadness, and happiness
ratings of their emotional state during the music. We used Eigenvector Centrality Mapping31 (ECM) to investi-
gate whether sad music (compared with happy music) engages the “computational hubs” of the DMN. ECM is a
graph-based network analysis technique, which measures the importance, or inuence, of network nodes. ECM
assigns a centrality value to each voxel (3 × 3 × 3 mm) in the brain such that a voxel receives a larger value if its
time-series is strongly correlated with the time-series of many other voxels that are themselves central within the
network31. us, voxels receive high eigenvector centrality values if they show functional connectivity with many
other voxels that have high centrality values themselves.
Results
Experiment 1A. Comparisons using paired t-tests (with Bonferroni-corrected P-values; P-values are two-
tailed unless noted otherwise) revealed that sad music [3.71 ± 1.83 (M ± SD)] evoked signicantly stronger
mind-wandering than happy music (3.28 ± 1.51), t(215) = 2.98, one-tailed P = 0.001, d = 0.21 (Fig.1A). is was
conrmed by the fact that meta-awareness, which involves ones explicit knowledge of the current content of
thoughts29, was signicantly stronger during happy (5.25 ± 1.63) than sad music (4.86 ± 1.79), t(215) = 3.35, one-
tailed P < 0.001, d = 0.23 (Fig.1A). oughts were signicantly more self-referential during sad (3.80 ± 2.03)
than happy music (3.17 ± 1.77), t(163) = 3.31, P = 0.001, d = 0.26 (Fig.1B). Conversely, thoughts were signicantly
more focused on movements as well as unknown people during happy [movements (3.95 ± 2.25); unknown
people (3.17 ± 2.03)] than sad music [movements (1.87 ± 1.44), t(163) = 11.31, P < 0.001, d = 0.88; unknown
people (2.38 ± 1.89), t(163) = 4.07, P < 0.001, d = 0.32; Fig.1B], which might be due to the fact that partici-
pants imagined groups of unknown people dancing during happy music (see also Fig.2). Overall, participants
attended signicantly more to happy [thinking about the music (4.40 ± 1.87); evaluating the music (3.89 ± 2.02)]
than sad music [thinking about the music (3.64 ± 1.97), t(163) = 4.72, P < 0.001, d = 0.37; evaluating the music
(3.28 ± 1.97), t(163) = 4.17, P < 0.001, d = 0.33; Fig.1B]. e diminished attention to the music during the sad
condition is in line with the decoupling of attention from external stimuli29, which is typical of mind-wander-
ing. Furthermore, thoughts were signicantly more focused on the experiment during happy (3.20 ± 2.07) than
sad music (2.34 ± 1.79), t(163) = 5.71, P < 0.001, d = 0.45 (Fig.1B). Regarding temporal orientation, past- and
future-oriented thoughts did not dier signicantly between sad [past (3.18 ± 2.17); future (2.27 ± 1.84)] and
happy music [past (3.00 ± 2.15), t(163) = 0.84, P > 0.05; future (2.18 ± 1.81), t(163) = 0.48, P > 0.05; Fig.1B]. e
form of mental activity (visual imagery or inner language) did not dier signicantly between the two experimen-
tal conditions, and visual mental imagery was the predominant modality for both sad (4.90 ± 1.82) and happy
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SCiENTiFiC RepoRts | 7: 14396 | DOI:10.1038/s41598-017-14849-0
Figure 1. Dierences in the strength of mind-wandering and its phenomenological dimensions between
experimental conditions (sad and happy music). Mean ratings (±SEM) of each item featured in the
thought probes are shown (answer scales 1–7; see TableS1 for precise questions). ***P 0.001, valence
( + ) = negative/positive valence. (A) Signicantly stronger mind-wandering and signicantly less meta-
awareness were observed during sad (compared with happy) music (P-values are one-tailed). (B) During sad
(compared with happy) music, thoughts were signicantly more self-referential. By contrast, during happy
(compared with sad) music, thoughts were signicantly more focused on positive content, movements,
unknown people, music, and experiment. (C) During both sad and happy music, thoughts occurred
signicantly more in the form of images compared with words.
Figure 2. Word cloud of thought content during sad and happy music. Word size is scaled according to
the overall word frequency (larger words indicate more frequent thought content over both experimental
conditions). Blue color indicates thought content more frequently reported during sad music and yellow color
indicates thought content more frequently reported during happy music. ought content during sad music
mainly referred to emotions and natural elements. By contrast, thought content during happy music was
predominantly characterized by dance imagery.
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SCiENTiFiC RepoRts | 7: 14396 | DOI:10.1038/s41598-017-14849-0
music (5.05 ± 1.74) compared with inner language [sad music (2.90 ± 1.70), t(179) = 9.05, P < 0.001, d = 0.67;
happy music (2.70 ± 1.69), t(186) = 11.30, P < 0.001, d = 0.83; Fig.1C]. oughts were signicantly more positive
during happy (5.08 ± 1.31) than sad music (3.89 ± 1.36), t(163) = 7.82, P < 0.001, d = 0.61 (Fig.1B). Nevertheless,
the analysis of the thought-reports revealed that thoughts occurring during sad music were characterized by both
negative (e.g., sad) and positive (e.g., love) emotion words, indicating a mixed aective tone (Fig.2 and TableS2).
Experiment 1B. Two 2 × 2 repeated-measures ANOVAs with the factors emotion (sad/happy) and
tempo (slow/fast) on the mind-wandering and meta-awareness ratings revealed significant main effects
of emotion on both mind-wandering (F(1, 139) = 8.56, P < 0.01, ηp2 = 0.06; Fig.3A) and meta-awareness
(F(1, 139) = 14.48, P < 0.001, ηp2 = 0.09; Fig.3B). Post-hoc paired t-tests (Bonferroni-corrected) showed that, for
both mind-wandering and meta-awareness ratings, there were signicant dierences between sad slow and happy
slow music (mind-wandering: P < 0.05; meta-awareness: P < 0.01) as well as between sad fast and happy fast
music (mind-wandering: P < 0.001; meta-awareness: P < 0.001). us, conrming the results of Experiment 1A,
during sad compared with happy music there was an increase in the level of mind-wandering and a decrease in
the level of meta-awareness. In addition, we detected signicant main eects of tempo on both mind-wandering
(F(1, 139) = 6.74, P = 0.01, ηp2 = 0.05; Fig.3A) and meta-awareness (F(1, 139) = 7.26, P < 0.01, ηp2 = 0.05; Fig.3B).
Post-hoc paired t-tests (Bonferroni-corrected) revealed that, for both mind-wandering and meta-awareness
ratings, there were significant differences between happy slow and happy fast music (mind-wandering:
P < 0.004; meta-awareness: P < 0.003), but not between sad slow and sad fast music (mind-wandering: P > 0.05;
meta-awareness: P > 0.05). ese results indicate that slow compared with fast music had dierent eects on
theratings of mind-wandering and meta-awareness depending on the type of emotion (sad, happy). Despite sad
and happy stimuli being controlled for tempo, happy music evoked signicantly higher arousal levels than sad
music [happy slow (4.39 ± 1.09) vs. sad slow (2.80 ± 1.12): t(139) = 12.61, P < 0.001; happy fast (5.09 ± 1.06) vs. sad
fast (3.25 ± 1.05): t(139) = 16.33, P < 0.001; happy slow vs. sad fast: t(139) = 9.49, P < 0.001; see TableS3 for arousal
ratings], indicating that other musical and/or acoustic features besides tempo contributed to arousal.
Experiment 2. Comparing centrality maps between the sad and the happy condition (sad > happy contrast,
Fig.4 and TableS4; for the results of the happy > sad contrast, see FigureS1 and TableS4) revealed a midline
four-cluster pattern of signicantly higher centrality values, including vmPFC (Brodmann area [BA] 32), dmPFC
(BA 9), PCC (BA 23), and PCC/PCu (BAs 31 and 7). Two additional clusters were found in the pIPL bilaterally
(BA 39). All of these clusters were on average within a distance of only 5 brain voxels (max. distance 6 voxels)
from the brain regions of the DMN as reported in a meta-analysis32 on default-mode processing. us, in accord
with the hypothesis motivated by Experiment 1A, sad music, compared with happy music, was linked to greater
centrality within the core nodes of the DMN.
Discussion
In this study we examined self-generated thought as a function of sad and happy music. Our ndings reveal that
music evoking sad, low-arousal emotions, compared with music evoking happy, high-arousal emotions, increased
the strength of mind-wandering. Moreover, tempo can further inuence mind-wandering (depending on the
Figure 3. Eects of emotion (sad/happy) and tempo (slow/fast) on mind-wandering and meta-awareness.
Experiment 1B replicated the results of Experiment 1A with an independent sample of participants (N = 140),
using sad and happy music matched for numbers of beats per minute (BPM) and varying in tempo. Participants
rated mind-wandering and meta-awareness on two 7-point scales (see TableS1 for precise questions). Error
bars represent 1 SEM. *P < 0.05, **P < 0.01, ***P 0.001. (A) Signicantly stronger mind-wandering was
observed during sad (compared with happy) music as well as during happy slow (compared with happy fast)
music. (B) Signicantly more meta-awareness was observed during happy (compared with sad) music as well as
during happy fast (compared with happy slow) music.
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SCiENTiFiC RepoRts | 7: 14396 | DOI:10.1038/s41598-017-14849-0
music’s type, sad or happy), as indicated by the observation that slow vs. fast happy music was associated with
increased mind-wandering and decreased meta-awareness. Importantly, very little is known about which exter-
nal cues trigger mind-wandering. e fact that mind-wandering can be externally modulated by means of music
is in line with previous evidence33 of mind-wandering elicited during task such as reading aloud, and ags the
importance of external emotional cues in eliciting mind-wandering episodes. e enhanced mind-wandering
during sad vs. happy music as observed in Experiment 1 (A-B) is in line with the stronger centrality of the DMN
nodes in Experiment 2, since the DMN has been indicated as the principal contributor to mind-wandering1823.
Consistent with our ndings, a number of previous music studies3438 reported activations in regions of the
DMN. Specically, the vmPFC was engaged in responses to excerpts of classical music evoking sadness34, and
the dmPFC was engaged during listening to sad music with lyrics35 as well as music evoking autobiographical
memories36,37 (past-related thoughts can oen occur during mind-wandering episodes)10. Moreover, activation in
the anterior medial frontal cortex correlated with perceived intentionality conveyed by music believed to be com-
posed by a human vs. a computer39. Notably, our results reveal that participants’ mental activity while listening to
sad vs. happy music was self-referential, in line with (i) individuals reporting to mind-wander about personally
signicant matters7 and (ii) evidence of a putative role of the DMN’s midline core in self-referential processing19.
Interestingly, a recent meta-analysis40 showed that activity within regions of the DMN, such as mPFC, PCC and
pIPL (the same areas that exhibited increased centrality in response to sad vs. happy music in the present study),
was associated with both personal goal processing and mind-wandering. erefore, future research could strat-
ify the self-referential component of mind-wandering evoked in response to sad music by specically testing
whether sad music, compared with happy music, increases reections on personal goals.
Contrary to previous ndings10, our results do not corroborate that sad (compared with happy) mood always
enhances mind-wandering in a past-oriented way. In fact, music-evoked sadness, and art-evoked sadness in gen-
eral, diers in valence from “real” sadness or negative mood and represents a rather pleasurable aective state3
(see also FigureS2 and TableS3 for valence ratings obtained in this study). us, our study suggests that the
Figure 4. Stronger centrality of the DMN nodes during listening to sad vs. happy music. (A) Sagittal and (B)
axial views show centrality maps obtained from a voxel-wise paired t-test comparing sad and happy music.
Sad and happy stimuli had the same loudness and tempo (see Methods). Results were corrected for multiple
comparisons (P < 0.05). Clusters of signicantly higher centrality values were observed in the main nodes of the
DMN: ventromedial prefrontal cortex (vmPFC), dorsomedial prefrontal cortex (dmPFC), posterior cingulate
cortex (PCC), posterior cingulate cortex/precuneus (PCC/PCu), and posterior inferior parietal lobule bilaterally
(pIPL).
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multi-faceted emotional experience underlying sad music, oen described by listeners as melancholic yet pleas-
urable3, shapes mind-wandering in a unique way, qualitatively non-identical to mind-wandering triggered by
“everyday” negative mood. is points to a fascinating relationship between emotions evoked by artworks and
thought. Likewise, we did not observe any signicant dierence in past-oriented thought between sad and happy
music, and the analysis of participants’ thought-reports occurring during sad music reects the mixed emotions
evoked by sad music.
Sad music is slow-paced music associated with low levels of arousal, while happy music is fast-paced music
associated with high levels of arousal. Because arousal is an intrinsic component of music-evoked emotions,
it is challenging to disentangle its contribution to the observed relationship between sad music and increased
mind-wandering (i.e., to determine to what extent spontaneous thoughts are triggered by the evoked low arousal
independent of the evoked sadness). Although we controlled for the tempo of the music stimuli in Experiment
1B, happy music evoked higher arousal than sad music. is underscores that while tempo clearly inuences
arousal, arousal does not simply vary as a function of tempo. In spite of the diculty to empirically separate
emotion (sadness/happiness) from arousal, further research may try to pin down the mind-wandering eects
on one of these two factors by using, for example, music evoking dierent emotions with similar arousal (e.g.,
sad and peaceful music, or happy and fearful music). Nevertheless, our data suggest that mind-wandering is
modulated not only by arousal levels but also by the quality of the evoked emotions (sad, happy), because fast sad
music, compared with slow happy music, tended to elicit stronger mind-wandering, despite evoking signicantly
lower arousal (Fig.3A). Moreover, note that meditation and relaxation practices aimed at facilitating mindfulness
(and at the same time avoiding mind-wandering) usually make use of music evoking low arousal emotions with
peaceful and relaxed (but not sad) emotional tone. erefore, it is unlikely that arousal is the only factor driving
the changes in mind-wandering.
An additional interesting result was about the form of mental experiences during music. In particular, images
(compared with words) were clearly the dominant modality for both sad and happy music, pointing to a strong
link between visual mental imagery and music processing. is nding is consistent with previous studies34,41
reporting activations in the primary visual cortex during music listening and with the predominance of visual
mental imagery during resting state26,42.
is study employed not only subjective but also objective indices of mind-wandering. Self-reports and neural
activity were measured in separate groups of participants, assuming that mind-wandering scores for the behav-
ioral experiments hold for the participants tested in the scanner. It will be important for future research on music
and spontaneous cognition to link subjective and objective measures of mind-wandering using within-subjects
designs. is would allow direct investigation of the relationship between the engagement of the DMN and the
stronger mind-wandering during sad vs. happy music, thus strengthening overall inference. Another constraint of
this study is related to the assessment of the enjoyment of the music pieces. People usually tend to mind-wander
during boring and unpleasant activities43. us, the increased mind-wandering during sad music might be
potentially explained by lower levels of enjoyment during sad compared with happy music. Although we did
not directly measure enjoyment of the music stimuli in Experiment 1A, we collected ratings of felt valence in
the corresponding pilot study (see Supplementary Information). Instead, in Experiments 1B and 2, we directly
assessed felt valence in response to the music (see TableS3 and FigureS2). For all experiments (1A, 1B, and 2),
valence ratings did not signicantly dier between the two emotion conditions, suggesting that both sad and
happy music were experienced as pleasurable, and thus enjoyable (felt valence correlates with enjoyment in the
context of music)44. For this reason, it is unlikely that the increased mind-wandering during sad music was simply
due to low levels of enjoyment of sad music. is study has specically tested the short-term eects of sad and
happy music on spontaneous cognition. It will be interesting, in future studies, to discover whether specic lis-
tening habits (e.g., regularly listening to sad and/or happy music) can aect the propensity to mind-wander in the
long-term. is line of research would be highly relevant especially to music-based interventions in clinical pop-
ulations (e.g., depression). Finally, the present study was conceived as a direct comparison between sad and happy
music, therefore our results can not be used to infer absolute eects of sad or happy music on mind-wandering
and DMN activity. Such eects should be determined, for instance, by contrasting sad and happy music with a
non-music baseline condition, which discloses the average level of mind-wandering and DMN activity experi-
enced at rest by participants in the absence of any type of music or auditory stimulation.
In conclusion, we demonstrate that music modulates self-generated thought: During sad (vs. happy) music,
listeners direct their attention inwards, engaging in spontaneous thoughts, which are related to the self and emo-
tional aspects of life; during happy (vs. sad) music, listeners are more focused on the music itself and exhibit
reduced mind-wandering levels. us, our ndings highlight the capability of music to trigger specic mental
processes as a function of its emotional tone, opening a novel line of future research elucidating the impact of
music on internally-oriented cognition. is has crucial implications for the application of music in a variety of
domains including education and psychotherapy. e diminishing eect of happy music on mind-wandering may
be benecial for sustained attention during task performance45 in educational contexts, and reduce rumination as
a repetitive style of thinking associated with depression46. e stimulating eect of sad music on mind-wandering,
by contrast, could be harnessed to improve creativity11, social cognition47, and decision-making48 in healthy indi-
viduals. Our study also shows modulation of the DMN by music. e DMN was initially introduced as rest-
ing state phenomenon49 and subsequent studies revealed that its engagement reects mind-wandering1823. Our
results reveal that the DMN is highly sensitive to external emotional cues conveyed by music, extending previous
evidence50 of a link between DMN and aective processing to the music domain. Furthermore, given that aber-
rant DMN activity has been linked to mental disorders such as depression51, schizophrenia52, autism spectrum
disorder53, and Alzheimer’s disease54, our ndings provide new perspectives for the investigation of the ecacy
of music therapy in the treatment of such disorders. For instance, future studies may test music’s capability to
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down-regulate DMN activity through the evocation of positive and highly arousing emotions, which could aid
therapy in patients with a hyperactive DMN such as depressed and schizophrenic individuals55.
Methods
Experiment 1A. Participants. A total of 224 participants (137 female, mean age = 33.2, age range 18–55)
were recruited through electronic mailing lists of students (see Supplementary Information for more details).
Participants were not compensated for their participation. ey completed the experiment online through a
web survey platform (http://www.unipark.com/). All participants gave informed consent according to the pro-
cedures approved by the ethics committee of the Psychology Department of the Freie Universität Berlin and the
experiment was performed in accordance with ethical standards outlined by the Declaration of Helsinki. Eight
participants were discarded from the analysis due to low accuracy rates (4, see Task design and procedure) to
follow the instructions of the experiment.
Music stimuli. The stimulus material consisted of four sad and four happy instrumental excerpts of film
soundtracks and classical music capable of evoking sad and happy emotions (TableS5). All stimuli were unfa-
miliar to participants (see Supplementary Information for further details about the stimulus selection). ere
were four “short” (1.20–1.48 min) and four “long” (1.54–2.29 min) excerpts, counterbalanced across conditions.
“Short” and “long” music stimuli were used to assess mind-wandering at dierent points in time aer the onset of
the emotion-eliciting stimulus. All stimuli were edited to have 1.5 s fade in/out ramps and were RMS-normalized
(root mean square) to have the same loudness.
Task design and procedure. e task was designed to parallel a natural everyday setting of exposure to music,
by employing unconstrained listening and use of relatively long music pieces. Participants were told that the
experiment was about music, emotion, and relaxation. ey were instructed to relax, listen to the music with-
out any interruption and close their eyes (in all experiments, we opted for an eyes closed paradigm because it is
typically used in resting state research56 and increases emotionality57). Moreover, they were asked to listen to the
music through headphones. Participants completed a practice trial to familiarize with the task and to adjust the
volume of their computer to a comfortable level. In the experimental task, the sad and happy music pieces were
presented in a counterbalanced order. Aer each music trial, thought probes were presented. For these thought
probes, participants were instructed to focus on the thoughts they had just before the music ended. At the end of
the task, participants answered to an item measuring the accuracy to follow the instructions of the experiment
(“How accurately did you follow the instructions of this experiment?”) on a scale from 1 (“not at all”) to 7 (“very
much so”). e total length of the experiment was about 20 min.
Analysis of thought-reports. To gain a further insight about the content of participants’ thoughts, we examined
the thought-reports provided by the participants in response to the open-ended item (TableS1) in two separate
analyses.
In therstanalysis, we looked at the most frequent words used by participants to describe their thoughts
during sad and happy music. We used the web application Wordle (http://www.wordle.net/) to generate a word
cloud summarizing our results. e word cloud was prepared in four steps. First, we excluded all the words that
were reported less than a cut-o score of 10 times as well as pronouns, adverbs, articles, and prepositions (regard-
less of their frequency of occurrence). Words such as “music” and “thought” were also excluded from the word
cloud, because they were not representative of the actual content of thoughts, but were rather biases due to the
question used to inquire about participants’ mental activity (“What were you thinking about just before the music
stopped?”). Second, we grouped together words with similar semantic content (e.g., happy, happiness, joyful, joy).
ird, we scaled word size by their overall frequency of occurrence within reports (i.e., referring to both sad and
happy conditions). Fourth, we used color to represent words’ overall frequency of occurrence over the sad and
happy conditions separately.
In thesecondanalysis, we examined participants’ thought-reports using the Linguistic Inquiry and Word
Count (LIWC) soware (http://liwc.wpengine.com/) to nd out whether the use of positive and negative emotion
words diers between thoughts that occurred during sad and happy music. LIWC identies pre-chosen categories
of language (such as positive and negative emotion) in a given text and calculates the percentage of total words
that match such categories.
Experiment 1B. Participants. 140 participants (67 female, mean age = 31.4, age range 18–63) were
recruited through electronic mailing lists of students and completed the experiment online, as in Experiment
1A. e experiment was approved by the ethics committee of the Psychology Department of the Freie Universität
Berlin and was performed in accordance with ethical standards outlined by the Declaration of Helsinki. Informed
consent was obtained from all participants.
Music stimuli. The stimulus material consisted of six sad and six happy instrumental excerpts of film
soundtracks and classical music capable of evoking sad and happy emotions (TableS6). Unlike in Experiment
1A, sad and happy music stimuli were matched in pairs according to their tempo, measured in beats per minute
(BPM). Each sad-happy pair had either the same BPM number or a very similar one, with a max. dierence of
only 4 BPM. ere were six “slow” (53–88 BPM) and six “fast” (105–134 BPM) excerpts, counterbalanced across
emotion conditions. e length of the stimuli ranged between 35 s and 1.24 min. All stimuli were edited to have
1.5 s fade in/out ramps and were RMS-normalized to have the same loudness.
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Task design and procedure. e experimental protocol was the same as that of Experiment 1A, the only dif-
ference being that we assessed only mind-wandering and meta-awareness levels (both on 7-point scales), and
not the form and content of spontaneous thoughts (to maintain the completion time below 15 min). Aer the
mind-wandering and meta-awareness ratings, participants were asked to rate their emotional state during
the music on four scales (valence, arousal, sadness, and happiness [7-point scales]; see TableS3 for emotion
ratings). Both emotion (sad, happy) and tempo (slow, fast) conditions were presented in a counterbalanced
order.
Experiment 2. Participants. 24 right-handed healthy participants (12 female, mean age = 25.3, age range
21–34) took part in Experiment 2 (see Supplementary Information for more details). None of these subjects
participated in Experiment 1 (A-B). Participants either received course credit or 10€/h for participation. All par-
ticipants gave written informed consent. e experiment was approved by the ethics committee of the Psychology
Department of the Freie Universität Berlin and was performed in accordance with ethical standards outlined by
the Declaration of Helsinki.
Music stimuli. The stimulus material included four sad and four happy instrumental excerpts of film
soundtracks capable of evoking sad and happy emotions (TableS7). ere were four “short” (35–37 s) and
four “long” (1.18–1.30 min) excerpts, counterbalanced across conditions. We controlled sad and happy stimuli
for dierences in tempo characteristics: rst, we matched the stimuli into sad-happy pairs according to their
tempo (for each pair, sad and happy stimuli had the same or a very similar number of BPM). en, for each
sad-happy pair, we generated an isochronous sequenced electronic beat track and overlaid both the sad and
the happy excerpts from that pair with that beat track. Slight tempo variations that led to deviations from
the beat track were corrected using the time stretching and t to tempo functions in FL Studio (https://www.
image-line.com/studio/). us, both sad and happy excerpts from each pair were overlaid with an identical
beat track, leading to the same perceived tempo and similar vestibular responses for sad and happy music (see
Supplementary Information for more details about the stimulus preparation and selection). All excerpts were
edited to have 1.5 s fade in/out ramps and were RMS-normalized to have the same loudness. Stimuli of the same
emotion category were concatenated into blocks of 4 min duration (no stimulus was repeated), resulting in
one 4 min stimulus block per experimental condition. e use of only one 4 min block of music per condition
ensured optimal data for the application of the fMRI data analysis, in which we adopted Eigenvector Centrality
Mapping31 (ECM). ECM requires relatively long trial periods, but has the advantage that only one trial per con-
dition is sucient per subject.
Task design and procedure. Prior to the fMRI measurements, participants were tested on their familiarity with
the selected music pieces (see Supplementary Information for further details). In the scanner participants were
presented with the sad and happy excerpts. We also presented blocks with dissonant sad and dissonant happy
music, as well as with neutral music (results involving the neutral stimuli are reported in the Supplementary
Information). The order of blocks was pseudo-randomized across subjects. Stimuli were presented via
MRI-compatible headphones (under which participants wore earplugs) at a comfortable volume level, using
Presentation (https://www.neurobs.com/). Participants were instructed to close their eyes and relax during the
music listening. Each block of music stimuli was followed by a 2 s signal tone, signaling to participants to open
their eyes, and then by a 16 s evaluation period, during which participants were asked to indicate their overall
emotional state during the music listening, using a response pad they held in their right hands. Ratings about felt
emotions were obtained on four scales (valence, arousal, sadness, and happiness [6-point scales]; FigureS2). e
rating period was followed by a silence period of 10 s to avoid emotional blending between dierent blocks of
stimuli. e total length of the experiment was about 27 min.
fMRI data acquisition. MRI data were acquired using a 3.0 T MRI scanner (Magnetom TIM Trio, Siemens,
Erlangen, Germany) at the Dahlem Institute for Neuroimaging of Emotion. Prior to functional scanning, a
high-resolution (1 × 1 × 1 mm) T1-weighted anatomical reference image was obtained from each participant
using a rapid acquisition gradient echo (MP-RAGE) sequence. For the functional session, a continuous echo
planar imaging (EPI) sequence was used (37 slices interleaved; slice thickness = 3 mm; interslice gap = 0.6 mm;
TE = 30 ms; TR = 2250 ms; ip angle = 70°; matrix = 64 × 64; FOV = 192 × 192 mm). To minimize susceptibility
artifacts in areas such as the orbitofrontal cortex and the temporal lobes, the acquisition window was tilted at an
angle of 30° to the intercommissural (AC-PC) plane58,59.
fMRI data processing. Functional MRI data were processed using the soware LIPSIA 2.1 (http://www.cbs.mpg.
de/institute/soware/lipsia/). Prior to statistical analysis, functional images were corrected for slicetime acquisition
and normalized into MNI-space-registered images with isotropic voxels of 3 mm³. Low frequency dris in the
fMRI time-series were removed using a high-pass lter with a cuto frequency of 1/90 Hz and functional images
were spatially smoothed using a Gaussian kernel of 6 mm full-width at half-maximum. Furthermore, the mean
signal value per scanned volume was computed and regressed out of each participant’s data. e movement param-
eters of each participant were also regressed out of the respective fMRI time-series to control for motion artifacts.
ECM analysis. ECM analysis was carried out in two steps. On the rst level, whole-brain eigenvector centrality
maps were computed separately for each participant during each 4 min experimental condition. On the second
level, eigenvector centrality maps were compared between the two experimental conditions using voxel-wise
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SCiENTiFiC RepoRts | 7: 14396 | DOI:10.1038/s41598-017-14849-0
paired t-tests. Results were corrected for multiple comparisons using cluster-size and cluster-value thresholds
obtained by Monte Carlo simulations60 with a signicance level of P < 0.05.
Data Availability. e datasets analyzed in the current study are available from the corresponding author
on reasonable request.
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Acknowledgements
e authors thank E. Zografakis for his help in preparing the music stimuli used in Experiment 2, and C. Seibert,
B. Strusch, M. Lehne, A. Samson, and V. Cheung for comments on the manuscript. We acknowledge support by
the German Research Foundation and the Open Access Publication Fund of Freie Universität Berlin.
Author Contributions
L.T. and S.K. conceived and designed the study. C.P. contributed to design Experiments 1A and 1B, and S.S.
contributed to design Experiment 2. L.T. performed all the experiments. L.T. and S.S. conducted data analysis.
L.T. draed the manuscript, and S.K. and C.P. critically reviewed and edited the manuscript.
Additional Information
Supplementary information accompanies this paper at https://doi.org/10.1038/s41598-017-14849-0.
Competing Interests: e authors declare that they have no competing interests.
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... Keywords visual mental imagery, mood, well-being, multimodal experience, ecological approach Music listening is known to afford a variety of emotions and internally oriented mental states, including mind-wandering and visual mental imagery Taruffi et al., 2017). In a live music setting, such as a concert, mind-wandering could be inspired not only by the auditory experience but also by additional external stimuli, such as visual information, creating a unique, multisensory experience. ...
... These can range from simple depictions to very detailed, vivid scenes in the "mind's eye" by drawing on perceptual information from memory, or recombining previous information into unfamiliar images (Kosslyn et al., 2001). Such visual mental imagery can be characterized as a specific mode of mind-wandering-other modalities are inner speech and musical imagery such as earworms (Jakubowski et al., 2017)-and often occurs during listening to music (Küssner & Eerola, 2019;Taruffi et al., 2017). A related type of mental experience is daydreaming (Herbert, 2017). ...
... More recently, the relationship between the frequency of mind-wandering, thought content, and emotion has been explored using music as a tool to afford emotion in the context of laboratory studies or online music listening tasks (Herff et al., 2021;Koelsch et al., 2019;Martarelli et al., 2016;Taruffi et al., 2017). Findings have shown that music can modulate mind-wandering via emotion. ...
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During a live concert, the mind can wander to unrelated thoughts such as personal concerns or past memories or to vivid images that are inspired by the music. This is an omnipresent phenomenon commonly referred to as mind-wandering. Psychological research on mind-wandering has explored its main characteristics, such as frequency, phenomenology, and impact on mood, both in the laboratory and in daily life contexts. This study aimed to harness the ecological setting of a live music concert to examine the occurrence and content of mind-wandering, as well as visual mental imagery as a mode through which mind-wandering occurs, and its relationship with the concertgoers’ moods before and after the music event. A self-report questionnaire ( n = 43) was used to collect data at two concerts of ambient music given as part of the CTM Festival. Findings suggest that mind-wandering occurs extensively in a concert environment. While mind-wandering episodes feature negative themes and moods—in the form of dark content of the visual mental imagery associated with the program’s musical tone—the concert environment still contributes to participants feeling more inspired afterward. Overall, this study points to the potential of live music contexts to stimulate a beneficial style of mind-wandering (i.e., one that leads to a positive impact on mood and imagery), and its findings are in line with those of previous research showing that live concerts lead to increased well-being of concertgoers. Implications for well-being and a call for more systematic research on this subject are discussed.
... It is tempting to apply this to the realm of music, which can be seen as having the power to affect the quality of life through emotion regulation and observable effects on both behavior and brain functioning [175]. Music, in this view, can be used for selfreflection-an ability that requires internally directed cognition-as seen most typically in the case of listening to sad music, which is considered by some as a major source of enjoyment [9,10,51,103,104,140,[176][177][178][179][180]. Listening to sad music, moreover, has also been put in relation to the phenomenon of depressive realism, which states that people are more realistic when they are sad. ...
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This article is a hypothesis and theory paper. It elaborates on the possible relation between music as a stimulus and its possible effects, with a focus on the question of why listeners are experiencing pleasure and reward. Though it is tempting to seek for a causal relationship, this has proven to be elusive given the many intermediary variables that intervene between the actual impingement on the senses and the reactions/responses by the listener. A distinction can be made, however, between three elements: (i) an objective description of the acoustic features of the music and their possible role as elicitors; (ii) a description of the possible modulating factors—both external/exogenous and internal/endogenous ones; and (iii) a continuous and real-time description of the responses by the listener, both in terms of their psychological reactions and their physiological correlates. Music listening, in this broadened view, can be considered as a multivariate phenomenon of biological, psychological, and cultural factors that, together, shape the overall, full-fledged experience. In addition to an overview of the current and extant research on musical enjoyment and reward, we draw attention to some key methodological problems that still complicate a full description of the musical experience. We further elaborate on how listening may entail both adaptive and maladaptive ways of coping with the sounds, with the former allowing a gentle transition from mere hedonic pleasure to eudaimonic enjoyment.
... These studies also shed light on the role of visual imagery in emotion induction by music. In line with previous studies (Hashim et al., 2020;Küssner & Eerola, 2019;Taruffi et al., 2017;Vuoskoski & Eerola, 2015), in both our experiments, we found that the participants' descriptions of their thoughts while listening to the music indicate that the majority of them experienced visual images, whose content coincided with the emotions they experienced. For Vuoskoski and Eerola (2015), this visual imagery mechanism was activated by an interaction of the music and the provided narratives, and led to the induction of emotional responses in the participants. ...
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Emotional contagion has been explained as arising from embodied simulation. The two most accepted theories of music-induced emotions presume a mechanism of internal mimicry: the BRECVEMA framework proposes that the melodic aspect of music elicits internal mimicry leading to the induction of basic emotions in the listener, and the Multifactorial Process Model proposes that the observation or imagination of motor expressions of the musicians elicits muscular and neural mimicry, and emotional contagion. Two behavioral studies investigated whether, and to what extent, mimicry is responsible for emotion contagion, and second, to what extent context for affective responses in the form of visual imagery moderates emotional responses. Experiment 1 tested whether emotional contagion is influenced by mimicry by manipulating explicit vocal and motor mimicry. In one condition, participants engaged in mimicry of the melodic aspects of the music by singing along with the music, and in another, participants engaged in mimicry of the musician’s gestures when producing the music, by playing along (“air guitar”-style). The experiment did not find confirmatory evidence for either hypothesized simulation mechanism, but it did provide evidence of spontaneous visual imagery consistent with the induced and perceived emotions. Experiment 2 used imagined rather than performed mimicry, but found no association between imagined motor simulation and emotional intensity. Emotional descriptions read prior to hearing the music influenced the type of perceived and induced emotions and support the prediction that visual imagery and associated semantic knowledge shape listeners’ affective experiences with music. The lack of evidence for the causal role of embodied simulation suggests that current theorization of emotion contagion by music needs refinement to reduce the role of simulation relative to other mechanisms. Evidence for induction of affective states that can be modulated by contextual and semantic associations suggests a model of emotion induction consistent with constructionist accounts.
... e achievements of digital revolution such as digital television and digital CD-ROM enable information to be disseminated in a simple way, accessed in a larger capacity, and communicated with recipients in a more personalized way [8]. Simple interpersonal relationship is being replaced by two-way communication between people, people and groups, so that people can selectively obtain the information they need [9]. ...
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With the rapid development of the related computer industry, the use of computer-related technologies has become more and more frequent. The music industry is no exception. The research and analysis of music emotions has been a problem since ancient times. Due to the diversification of music emotions, people with different music in the same piece of music will have different feelings. The research topic of this article is to make a comprehensive analysis of the computer’s automatic identification technology, combined with the powerful subcapacity of the computer, so that the research on music emotion can be developed rapidly. The article analyzes the technical research of the automatic recognition and analysis of music emotion in the computer, and conducts a comprehensive analysis of the music emotion through the research of the computer-related automatic recognition technology. This paper focuses on the computer automatic recognition model of music emotion, and successfully realizes the design and simulation of the automatic recognition system based on the MATLAB platform. An automatic identification model using BP neural network algorithm is proposed. By comparing it with the statistical classification algorithm, the experimental results verify the effectiveness of the designed BP network in music emotion recognition.
... Email content may be associated with users' tendency to mindwander. Research has shown that negative emotions can lead to a higher tendency to mind-wander and pay less attention to the current task [94,95]. This implies that if the users were in a bad mood before checking their emails, or the current email makes them uncomfortable, they may have a higher tendency to mind-wander. ...
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Phishing is recognised as a serious threat to organisations and individuals. While there have been significant technical advances in blocking phishing attacks, people remain the last line of defence after phishing emails reach their email client. Most of the existing literature on this subject has focused on the technical aspects related to phishing. However, the factors that cause humans to be susceptible to phishing attacks are still not well-understood. To fill this gap, we reviewed the available literature and we propose a three-stage Phishing Susceptibility Model (PSM) for explaining how humans are involved in phishing detection and prevention, and we systematically investigate the phishing susceptibility variables studied in the literature and taxonomize them using our model. This model reveals several research gaps that need to be addressed to improve users' detection performance. We also propose a practical impact assessment of the value of studying the phishing susceptibility variables, and quality of evidence criteria. These can serve as guidelines for future research to improve experiment design, result quality, and increase the reliability and generalizability of findings.
... Consistent with this view, the work by Castro et al. (2020) showed that familiar music engaged DMN more strongly than unfamiliar music. However, a study by Taruffi, Pehrs, Skouras, and Koelsch (2017) showed that DMN was engaged for unfamiliar music, particularly for sad music compared with happy music. Future work investigating high-level musical event structure representation can address this by scanning participants while they listen to both unfamiliar and familiar stimuli. ...
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Recent fMRI studies of event segmentation have found that default mode regions represent high-level event structure during movie watching. In these regions, neural patterns are relatively stable during events and shift at event boundaries. Music, like narratives, contains hierarchical event structure (e.g., sections are composed of phrases). Here, we tested the hypothesis that brain activity patterns in default mode regions reflect the high-level event structure of music. We used fMRI to record brain activity from 25 participants (male and female) as they listened to a continuous playlist of 16 musical excerpts and additionally collected annotations for these excerpts by asking a separate group of participants to mark when meaningful changes occurred in each one. We then identified temporal boundaries between stable patterns of brain activity using a hidden Markov model and compared the location of the model boundaries to the location of the human annotations. We identified multiple brain regions with significant matches to the observer-identified boundaries, including auditory cortex, medial pFC, parietal cortex, and angular gyrus. From these results, we conclude that both higher-order and sensory areas contain information relating to the high-level event structure of music. Moreover, the higher-order areas in this study overlap with areas found in previous studies of event perception in movies and audio narratives, including regions in the default mode network.
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Listening to pleasurable music is known to engage the brain’s reward system. This has motivated many cognitive-behavioral interventions for healthy aging, but little is known about the effects of music-based intervention (MBI) on activity and connectivity of the brain’s auditory and reward systems. Here we show preliminary evidence that brain network connectivity can change after receptive MBI in cognitively unimpaired older adults. Using a combination of whole-brain regression, seed-based connectivity analysis, and representational similarity analysis (RSA), we examined fMRI responses during music listening in older adults before and after an 8-week personalized MBI. Participants rated self-selected and researcher-selected musical excerpts on liking and familiarity. Parametric effects of liking, familiarity, and selection showed simultaneous activation in auditory, reward, and default mode network (DMN) areas. Functional connectivity within and between auditory and reward networks was modulated by participant liking and familiarity ratings. RSA showed significant representations of selection and novelty at both time-points, and an increase in striatal representation of musical stimuli following intervention. An exploratory seed-based connectivity analysis comparing pre- and post-intervention showed significant increase in functional connectivity between auditory regions and medial prefrontal cortex (mPFC). Taken together, results show how regular music listening can provide an auditory channel towards the mPFC, thus offering a potential neural mechanism for MBI supporting healthy aging.
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People readily imagine narratives in response to instrumental music. Although previous work has established that these narratives show broad intersubjectivity, it remains unclear whether these imagined stories are atemporal, or unfold systematically over the temporal extent of a musical excerpt. To investigate the dynamics of perceived musical narrative, we had participants first listen to 16 instrumental musical excerpts, which had previously been normed for factors of interest. While listening, participants continuously moved a slider to indicate their fluctuating perceptions of tension and relaxation. In a separate experimental session, participants reported the stories they imagined while listening to each excerpt, and then, while listening to the excerpts a final time, clicked a mouse to mark the time points at which they imagined new events in the ongoing imagined story. The time points of these event markings were not uniformly distributed throughout the excerpts, but were clustered at distinct moments, indicating that imagined narratives unfold in real time and entail general consensus about when listeners imagine events in the music. Moreover, the time points at which people tended to imagine events were correlated with the time points at which people tended to perceive salient changes in musical tension, as separately recorded within the first experimental session. The degree of alignment was greater for excerpts high in narrativity than those low in narrativity. Together, these results show that music can dynamically guide a listener's imagination and there is remarkable intersubjectivity in ‘when’ hear imagined story events in a piece of music.
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Although listening to background music is common, there is no consensus about its effects on cognitive-task performance. One potential mediating factor that could resolve the inconsistency in findings is arousal. To explore the role of arousal in mediating the effect of background music, this survey study directly explored people’s background music listening habits during a variety of everyday tasks varying in their complexity including studying, reading, driving, and monotonous tasks. Out of the 197 participants, most participants reported listening to background music during driving or monotonous tasks but fewer did so during studying or reading. Participants who did listen to music during studying or reading mostly reported choosing instrumental music and listening to music to calm them down. Contrarily, participants who listened to music during driving or monotonous tasks reported choosing vocal music more often and listening to music to feel energised. In sum, results revealed clearly different patterns in background music listening habits between tasks varying in their complexity that are consistent with arousal mediating the effect of background music. The results also revealed that people have an implicit awareness of the effects of background music and match the music to their needs as dictated by the specific task.
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Research in psychology has suggested that reading fiction can improve individuals' social-cognitive abilities. Findings from neuroscience show that reading and social cognition both recruit the default network, a network which is known to support our capacity to simulate hypothetical scenes, spaces, and mental states. The current research tests the hypothesis that fiction reading enhances social cognition because it serves to exercise the default subnetwork involved in theory of mind. While undergoing functional neuroimaging, participants read literary passages that differed along two dimensions: (i) vivid vs. abstract, and (ii) social vs. nonsocial. Analyses revealed distinct subnetworks of the default network respond to the two dimensions of interest: the medial temporal lobe subnetwork responded preferentially to vivid passages, with or without social content; the dorsomedial prefrontal (dmPFC) subnetwork responded preferentially to passages with social and abstract content. Analyses also demonstrated that participants who read fiction most often also showed the strongest social cognition performance. Finally, mediation analysis showed that activity in the dmPFC subnetwork in response to the social content mediated this relation, suggesting that the simulation of social content in fiction plays a role in fiction's ability to enhance readers' social cognition. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
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Mind wandering is an ubiquitous phenomenon in everyday life. In the cognitive neurosciences, mind wandering has been associated with several distinct neural processes, most notably increased activity in the default mode network (DMN), suppressed activity within the anti-correlated (task-positive) network (ACN), and changes in neuromodulation. By using an integrative multimodal approach combining machine-learning techniques with modeling of latent cognitive processes, we show that mind wandering in humans is characterized by inefficiencies in executive control (task-monitoring) processes. This failure is predicted by a single-trial signature of (co)activations in the DMN, ACN, and neuromodulation, and accompanied by a decreased rate of evidence accumulation and response thresholds in the cognitive model. Copyright © 2014 the authors 0270-6474/14/3416286-10$15.00/0.
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This study explores listeners' experience of music-evoked sadness. Sadness is typically assumed to be undesirable and is therefore usually avoided in everyday life. Yet the question remains: Why do people seek and appreciate sadness in music? We present findings from an online survey with both Western and Eastern participants (N = 772). The survey investigates the rewarding aspects of music-evoked sadness, as well as the relative contribution of listener characteristics and situational factors to the appreciation of sad music. The survey also examines the different principles through which sadness is evoked by music, and their interaction with personality traits. Results show 4 different rewards of music-evoked sadness: reward of imagination, emotion regulation, empathy, and no "real-life" implications. Moreover, appreciation of sad music follows a mood-congruent fashion and is greater among individuals with high empathy and low emotional stability. Surprisingly, nostalgia rather than sadness is the most frequent emotion evoked by sad music. Correspondingly, memory was rated as the most important principle through which sadness is evoked. Finally, the trait empathy contributes to the evocation of sadness via contagion, appraisal, and by engaging social functions. The present findings indicate that emotional responses to sad music are multifaceted, are modulated by empathy, and are linked with a multidimensional experience of pleasure. These results were corroborated by a follow-up survey on happy music, which indicated differences between the emotional experiences resulting from listening to sad versus happy music. This is the first comprehensive survey of music-evoked sadness, revealing that listening to sad music can lead to beneficial emotional effects such as regulation of negative emotion and mood as well as consolation. Such beneficial emotional effects constitute the prime motivations for engaging with sad music in everyday life.
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Most people choose to listen to music that they prefer or 'like' such as classical, country or rock. Previous research has focused on how different characteristics of music (i.e., classical versus country) affect the brain. Yet, when listening to preferred music-regardless of the type-people report they often experience personal thoughts and memories. To date, understanding how this occurs in the brain has remained elusive. Using network science methods, we evaluated differences in functional brain connectivity when individuals listened to complete songs. We show that a circuit important for internally-focused thoughts, known as the default mode network, was most connected when listening to preferred music. We also show that listening to a favorite song alters the connectivity between auditory brain areas and the hippocampus, a region responsible for memory and social emotion consolidation. Given that musical preferences are uniquely individualized phenomena and that music can vary in acoustic complexity and the presence or absence of lyrics, the consistency of our results was unexpected. These findings may explain why comparable emotional and mental states can be experienced by people listening to music that differs as widely as Beethoven and Eminem. The neurobiological and neurorehabilitation implications of these results are discussed.
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Although neural activity often reflects the processing of external inputs, intrinsic fluctuations in activity have been observed throughout the brain. These may relate to patterns of self-generated thought that can occur while not performing goal-driven tasks. To understand the relationship between self-generated mental activity and intrinsic neural fluctuations, we developed the New York Cognition Questionnaire (NYC-Q) to assess the content and form of an individual's experiences during the acquisition of resting-state fMRI data. The data were collected as a part of the Nathan Kline Rockland Enhanced sample. We decomposed NYC-Q scores using exploratory factor analysis and found that self-reported thoughts clustered into distinct dimensions of content (future related, past related, positive, negative, and social) and form (words, images, and specificity). We used these components to perform an individual difference analysis exploring how differences in the types of self-generated thoughts relate to whole brain measures of intrinsic brain activity (fractional amplitude of low frequency fluctuations, regional homogeneity, and degree centrality). We found patterns of self-generated thoughts related to changes that were distributed across a wide range of cortical areas. For example, individuals who reported greater imagery exhibited greater low frequency fluctuations in a region of perigenual cingulate cortex, a region that is known to participate in the so-called default-mode network. We also found certain forms of thought were associated with other areas, such as primary visual cortex, the insula, and the cerebellum. For example, individuals who reported greater future thought exhibited less homogeneous neural fluctuations in a region of lateral occipital cortex, a result that is consistent with the claim that particular types of self-generated thought depend on processes that are decoupled from sensory processes. These data provide evidence that self-generated thought is a heterogeneous category of experience and that studying its content can be helpful in understanding brain dynamics.
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Recent research suggests that sleepiness and mind-wandering—the experience of thoughts that are both stimulus-independent and task-unrelated—frequently co-occur and are both associated with poorer cognitive functioning. Whether these two phenomena have distinguishable effects on task performance remains unknown, however. To investigate this question, we used the online experience sampling of mind-wandering episodes and subjective sleepiness during a laboratory task (the Sustained Attention to Response Task; SART), and also assessed mind-wandering frequency and sleep-related disturbances in daily life using self-report questionnaires. The results revealed that the tendency to experience mind-wandering episodes during the SART and daily life was associated with higher levels of daytime sleepiness and sleep-related disturbances. More important, however, mind-wandering and sleepiness were independent predictors of SART performance at both the within- and between-individuals levels. These findings demonstrate that, although mind-wandering and sleepiness frequently co-occur, these two phenomena have distinguishable and additive effects on task performance.
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The ability to imagine the future is a complex mental faculty that depends on an ensemble of cognitive processes supported by an extended set of brain regions. Our aim here was to shed light on one key component of future thinking-personal goal processing-and to determine its neural correlates during both directed and spontaneous forms of thoughts. To address this question, we performed separate ALE meta-analyses of neuroimaging studies of episodic future thinking (EFT), mind-wandering, and personal goal processing, and then investigated the commonalities and differences in brain activity between these three domains. The results showed that the three domains activated a common set of brain regions within the default network and, most notably, the medial prefrontal cortex. This finding suggests that the medial prefrontal cortex mediates the processing of personal goals during both EFT and mind-wandering. Differences in activation were also observed, and notably regions supporting cognitive control processes (the dorsolateral prefrontal cortex) were recruited to a lesser extent during mind-wandering than experimentally directed future thinking, suggesting that different kinds of self-generated thoughts may recruit varying levels of attentional control abilities. Hum Brain Mapp, 2015. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.