1. COURSE CODE AND TITLE, PS3200:
Third Year Project
‘Neural correlates of arousal, valence and authenticity in
the perception of emotional and non-emotional
vocalisations.’
Project Supervisor: Carolyn McGettigan
Word count: 7,620

2. Abstract
Non-verbal vocalisations are recognisedas a vital form of human communication,
yet we currentlylack understanding of how the brain processes these unique types
ofsound, and respondstotheir complexandvariable acoustic features (Bachorowski
& Owren, 2008). Thus there is justification in investigating neural activity during
passive listening to real andposedemotional andnon-emotional vocalisations. This
study constitutes are-analysis of existing functional magnetic resonance imaging
(fMRI) data (McGettigan et al., 2015), obtained when participants listened to
deliberatelyemittedlaughs, genuine laughs of amusement, acted sounds of disgust
and unintelligible baseline sounds. We provide an extensionof the initial paper in
that the present study examines the neural correlates of three perceptual properties
of these sounds; namely how valence, arousal and authenticity of the stimuli, as
appraised by independent raters, could have parametrically modulated the size of
the BOLD response inthe brain. It was found that the brain regions engagedduring
passive listening to emotional vocalisations, did indeed show variation in their
response to these affective properties. Firstly, responses to increased arousal,
positive valence, and greater authenticity were found in superior temporal gyrus
(STG) and planum temporale (PT) for all four sound categories. Therefore, brain
areas primarily concernedwith basic acoustic properties of sound appeared to be
commonly engaged during passive listening. Yet we found a specific increase in
activation in medial prefrontal cortex(mPFC) to laughter that is perceivedas being

3. less authentic, supporting previous researchand the suggestionthat a mentalizing
system is engaged during the evaluation of emotional vocalisations.
Introduction
Non-verbal emotional expressions are a subset of human vocalisation. The
investigation of how we perceive and process this form of vocalisation has entered
the scientific research agenda only recently; explanations of how emotion is
conveyed and discerned within the facial channel dominate the literature, and the
research that extends to vocal acoustics remains largely focused on emotionally-
inflected speech (Bachorowski & Owren, 2008). Yet such investigation is
important; just as speechis a vital form of communicationfor humans, non-verbal
vocalisations convey a wide range of information that is often essential for
successful social interaction. Additionally, as reflectedin their acoustic structure,
the productionof these vocalisations is unique, and it is true that the recognitionof
non-verbal expressions recruits distinct neural systems (Scott, Sauter &
McGettigan, 2010).
Laughter is one especially instinctive and ubiquitous non-verbal emotional
vocalisation; the high frequency of its production is found in both experimental
(Bachorowski, Smoski & Owren, 2001) and naturalistic (Vettin & Todt, 2004)
conditions, and extends even to deaf signers (Provine & Emmorey, 2006). The
expression of laughter constitutes an integral form of communication, one that is
characteristic of our species, and thus extensive investigation of this particular
vocalisationis justified.Importantly, thistype ofemotionalsoundoffersaprofound

4. and unique opportunity to explore vocalisation-specific neural mechanisms,
mechanisms that will have evolved for the detectionof simplespecies-stereotypical
sounds, as opposedto highly intricate and variable speechsounds (Provine, 2001).
The integrationof much behavioural, neuropsychological and neurological datahas
resulted in a distinction between two types of laughter in humans: voluntary and
involuntary. Whilst involuntary laughter is spontaneous, elicited by an external
stimulus and possessing emotionality, voluntary laughter is instead a controlled
expressionindependent of any particular emotional experience (Gervais & Wilson,
2005). It is suggested that humans produce voluntary laughter to facilitate social
interactions, for example it may serve to affirm a social relationship(Smoski and
Bachorowski, 2003), reduce conversational uncertainty (Graham, 1995) or signal
polite agreement during correspondence(Gervais & Wilson, 2005). Researchfinds
notable differences between the properties of this type of social laughter, and
involuntary stimulus-driven laughter. Dissimilarity in the acoustical correlates of
voluntary and involuntary laughter is a consistent finding. A detailed acoustic
analysis ofconversationallaughter, examining temporaland fundamental frequency
patterns, revealed that laughter of this kind comprisesa distinct acoustic structure,
distinct from laughter engendered by external stimuli (Vettin & Todt, 2004).
Additionally, Szameitat et al. (2009) analysed over 40 acoustic parameters of four
discrete types of laughter (joy, tickling, taunting and pleasure at another’s
misfortune) and found significant acoustic variability, which was responsible for
differences then in how the emotionalityof a laugh was perceived. Therefore, both

5. acoustic features and perceived emotional qualities of laughter vary according to
the laughter-elicitingcontext.
This distinctionbetweendiverse formsoflaughteris consistentwith, and reinforced
by neuroimagingdata. Firstly,therearedifferencesintheprofileofneuralactivation
seenduring the production of either voluntaryor involuntary laughter (Wattendorf
et al., 2013). However, fMRI research also demonstrates that neural responses
during laughter perception differ accordingto the category of laughter heard. For
example Szameiter et al. (2010) foundthat listeningto ticklish laughter, in contrast
to emotional laughter, provoked stronger cerebral responses inauditoryassociation
cortex.The authorssuggestedthisreflectsthehigheracoustic complexityofticklish
laughter, which tends to be higher-pitched and more rapid. On the other hand,
hearing social/emotional laughter suchas that incitedby joy or taunting, appears to
more strongly activate regions of mediofrontal cortex (Szameiter et al., 2010;
Wildgruber et al., 2013).
Yet the majorityof studies investigating different types of laughter are constrained
by aspects of the methodology theyemploy. For example, such studies (Szameiter
et al., 2009;Szameiter et al., 2010 Wildgruber et al., 2013) tendto use stimuli that
have all been produced by actors, who are instructedto portray a type of laughter
that would occur in an example scenario. This means that the laughs (regardless of
theircategory)are all to someextentposed. Therefore suchstudiesare not designed
toaddress genuine involuntary laughter. Furthermore,inthe researchdiscussedthus

6. far, participants were aware that they were listening to different types of laughter
and were oftenmaking conscious attemptsto distinguishbetweenand/or categorise
them. In contrast, McGettiganet al. (2015)exploredneural responses to posed, but
also naturally (stimulus-) evoked laughter in an fMRI experiment that involved
participants passively listeningto these emotional vocalisations, thus constitutinga
novel investigation. McGettiganet al. were able to identifyparticular brain regions
that automatically distinguished between the two types of laughter (emitted and
evoked), presumably due to their involvement in the passive perception of
emotionalauthenticity.In particular,for the authentic laughter that had beenevoked
by amusing video clips, they found greater activity in bilateral STG, whereas for
deliberately emitted laughter they found greater activity in mPFC regions. This
significant mPFC activation was seen to reflect the engagement of mentalizing
processes for moreambiguous emotional stimuli.
Whilst McGettigan et al. (2015) previously only reported the direct neural
comparisons between passive listeningto real and posed laughter, it is possible to
gain additional insight into the way we perceive and process non-verbal
vocalisations by investigating continuous properties of vocalisedsound. Therefore
the present study provides an extension of McGettigan et al.’s original research,
whereby novel behavioural data will be integrated with the existing fMRI data in
order to explore how our brains responds to the strength of arousal, valence and
authenticity in vocalised sound. Furthermore, although McGettigan et al. were
primarily concerned with analysis of the real and posed laughter conditions,
participants also listenedto sounds of disgust and unintelligible baseline sounds in

7. the scanner.Consequentlyitalsopossibletoinvestigatetheextenttowhich thebrain
regionsprocessingtheseaffective properties,arealsoactivatedby similarproperties
in other sound categories, including both emotional and non-emotional
vocalisations.
There is much reasonto explore how the brain processes the affective properties of
sound. Research has demonstrated that the perceived emotional character of
vocalised stimuli is tied to its underlying acoustic properties;that is, emotionality
of a nonverbal vocalisationcan be decipheredon the basis of the physical features
of saidvocalisation(Sauter, Eisner, Calder & Scott, 2010). Arousal andvalence are
consideredto be particularly salient features of emotional vocalisations (Sauter et
al., 2010). Aleading approach in the study of emotion is that of the theoryof basic
emotions. This theoryholds that there are a set of universal emotions that exist as
pointsinemotionalspacealongthedimensionsofarousaland valence (Scott,Sauter
& McGettigan, 2010). It is therefore not surprising that emotional vocalisation
stimuli are reliably rated on scales of arousal, valence and authenticity. What is,
however, surprising is that despite recognitionof these properties as important for
the perceptionof emotional sounds, there is yet to be significant explorationof the
neural correlates of saidproperties (Lima, Castro & Scott, 2013).
The admittedly sparse neuroimaging research literature does indeed suggest that
brain regions may respond preferentially to the strength of certain affective
properties of emotional sound. For example, Wiethoff et al. (2008) conductedan

8. fMRI experiment to investigate the neural correlates underpinning automatic
processing of emotional information in spoken word, and they were particularly
interested in various acoustic and affective properties of this emotional prosody.
They found a significantlygreater BOLD response inSTG during passive listening
toemotionalas opposedtonon-emotionalspeech.However a subsequentregression
analysis revealed this STG activity was modulated by arousal of the stimuli,
whereby the response was stronger for more arousing words, and when correcting
forarousalofthe stimulithesignificant STG activationwas abolished. Additionally,
fMRI research suggests some degree of sensitivity to the property of valence in
emotional sounds. Viinikainen, Katsyri and Sams (2012) foundthat the processing
of a range of auditory stimuli (including music and human, animal and
environmental sounds) in both cortical and subcortical structures is affected by
perceivedemotionalvalence ofthe sounds. They reportedincreasesinBOLD signal
strength in mPFC, auditory cortex and amygdala when participants listened to
sounds extreme in valence (very positive or very negative sounds). There is also
some preliminary neuroimaging investigation into affective properties of non-
verbal emotional vocalisations specifically. Warren et al. (2006) identified that
specific subsystems within the auditory-motor mirror network responded
preferentially to such vocalisations that were either high in arousal or positively
valenced. However, Warren et al. observed correlations across conditions,
comparing vocalisation categories that were high on arousal/valence to those that
were low on arousal/valence, whereas the present study will examine variation
within conditions.

9. The present study is a follow-on project, the aim of which is to build on that of
McGettigan et al.’s (2015) research by investigating how within regions that are
engaged during passive listening to different categories of sound (real laughter,
posedlaughter, disgust and unintelligible baseline sounds), response strength varies
accordingto affectivepropertiesofthesesounds(arousal,valence and authenticity).
Given that McGettigan et al. (2015) found particular brain regions that appear to
respondpreferentiallyto real laughter and others to posedlaughter, we firstlywant
to investigate whether there are any distinctions inactivationto laughter in general,
modulated by continuous properties of this particular emotional vocalisation, by
therefore firstlycollapsingresultsforbothlaughter conditionstogetherforanalysis.
As McGettiganet al. (2015) found significant differences inthe regions activated
when comparing the real and posed laughter conditions (STG and mPFC
respectively), it is hypothesisedthat these regions may be sensitive to continuous
properties of such emotional vocalisations and that their responses will be
modulated by arousal, valence and authenticity of laughter. We then also want to
examine realand posedlaughter conditions separately,and comparethem alongside
disgust and baseline sounds to determine if there is any commonalityinthe regions
modulated by continuous properties of sound; that is, will we find commonalityin
the way in which the brain responds to arousal, valence and authenticity across
different categories of sound?
Methods

10. Functional magnetic resonance imaging.
Functional imaging data was obtained from a previous study, and full details of
protocol andprocedure canbe obtained from there (McGettiganet al., 2015).
Participants
Twenty-one participants, all with healthy hearing, were recruited for the
experiment. The sample consistedof 13 females and8 males, their mean age being
23yearsand 11months.This study was approved by the UniversityCollegeLondon
ResearchCommittee.
Materials
The emotionalvocalisationstimuliconsistedofEmittedLaughter, Evoked Laughter
and Disgust. Three speakers were recorded generating these vocalisations. For
EmittedLaughter, the speakers simulatedlaughter without any external stimulus or
genuine stateof amusement. For Evoked Laughter, speakerslaughed spontaneously
in response to videos they found genuinely amusing. The Disgust sounds were all
posed, whereby the speakers were asked to simulate the type of sound they might
make after seeing/smelling something disgusting. In addition, spectrally-rotated
unintelligible baseline sounds were constructed. These constituted the non-
emotional stimuli. Twenty-one examples were selectedfor each of the four sound
conditions.
Procedure

11. Participants entering the scanner were informed that they would be hearing
emotionaland othersounds, and instructedtolistencarefullywiththeir eyesclosed.
In each of two runs, all 84 stimuli were presentedin a pseudorandomized order of
conditions(suchthat thepresentationofeachconditionwas relativelyevenly spread
acrosstheruns), and a whole-brainEPI image measuredthe responsetoeachsound.
Design and analysis
Data were pre-processed and analysed in SPM8 (Welcome Trust Centre for
Neuroimaging, London, UK).
Pre-processing was completed in order to correct for variations across time
(alignment of a single participant’s images in space) and participants (all
participants’ brains aligned with one another). Stages included: manual
reorientation (initial centring and aligning of all images, around the anterior
commissure, inSPM analysis space); realigning and unwarping (first ensuringthat
the voxels overlap, thus correctingfor any slight movements made by participants
in thescanner, and second,correctingforanyspatial distortionsinthe image caused
by the scanner’s magnetic field);coreorganisation (alignment of each participant’s
structural image with their functional images); segmentation (segmenting the
structural image into distinct tissue types, namely grey matter, white matter and
cerebral spinal fluid, and warping the brain into standardisedspace); normalisation
(utilising the parameters identified in the segmentation step to then warp the
functional images into standardised space); smoothing (images were smudged by
applying a Gaussian kernel of 8mm FWHM, improving the signal to noise ratio and
accountingfor any small differences betweenbrains that may remain).

12. Six first-level models were estimated for every subject. In the first three, event
onsets from the 4 soundconditions were modelledinseparate regressors, where the
auditory events were modelledas instantaneous and convolved with the canonical
haemodynamic response function. For each condition, a parametric modulator
contained the mean behavioural ratings of Arousal (Model 1), Valence (Model 2)
or Authenticity (Model 3) associated with each auditory event. The rest trials
formed an implicit baseline. Three further models were parallel to the first three,
but here the laughter conditions were modelled in a single regressor, with a
parametric modulator containing ratings of Arousal (Model 4), Valence (Model 5)
or Authenticity (Model 6) for both Real and Posedlaughs. Contrast images were
calculated in each model to describe the positive relationship between the
parametricmodulator(Arousal, Valence orAuthenticity) and the neural responseto
the corresponding condition. These contrasts were entered into separate second-
level, one-sample t-tests for the group analysis. Positive and negative group
contrasts revealed positive and negative correlates of Arousal, Valence and
Authenticity for Real, Posed and Combined Laughter, as well as the Disgust and
Baseline sounds. All second-level images reported here are at a voxel-wise
thresholdof p < .005 with a cluster extent thresholdof 20 voxels.
Behavioural testing
Participants

13. Twenty participants, all with healthy hearing, were recruitedthrough opportunity
sampling. The sample consistedof 11 females and 9 males. Participants were aged
from 21-32, with the mean age being 22 years and 6 months (S.D=2.5). None of
these individuals participated in the previous fMRI study. The behavioural study
was approved by the Departmental Ethics Committee at the Department of
Psychology, Royal Holloway, University London.
Materials
The participants heard and rated the same 84 sounds as the participants in the fMRI
study (see above).
Procedure
Participants wore headphones at a PC running MatLab (Version R2007; The
Mathworks, Natick, MA). Every participant heard 84 sounds, 21 from each of the
four sound conditions: real laughter, posed laughter, disgust and baseline. Each
sound lastedbetween 1-3 seconds. Participants were requiredto rate the sounds on
three perceptual scales: arousal, valence and authenticity. They rated on a 7-point
Likertscale.For Arousal, participantswere asked'How arousedis this sound?', with
1 being "not at all" and 7 being "very". For Valence, theywere asked'How positive
ornegative is this sound?', with 1 being"very negative" and 7 being "very positive".
For the laughter and disgust categories only, they were asked 'How authentic does
the emotionsound?", with 1 being "not at all" and 7 being "very". All the sounds
were testedinblocks, with one blockfor eachof the three scales. Withineachblock
the orderofthe individual sounds was randomized, and the orderofthe Arousal and
Valence scalespresentedwas counterbalancedacrossparticipants.The Authenticity

14. scale was always presentedlast, so as not to alert participants to the fact that only
some of the emotional sounds were genuine expressions.
Results

15. Behavioural testing
Arousal
A one-way independent ANOVA, with the factor ‘sound condition’ (four levels:
reallaughter, posedlaughter, disgustand baseline),showedasignificantmain effect
of sound condition (F(3,80)= 159.62, p<.001) meaning arousal ratings were
different depending on the type of sound. A Bonferroni correctionwas applied for
multiple comparisons. Ratings of arousal were significantlyhigher for real laughter
(M=5.89, S.D=.38) than for posed laughter (M=4.4, S.D=.52) (p<.001), disgust
(M=3.53, S.D=.45) (p<.001) and baseline sounds (M=3.49, S.D=.21) (p<.001).
Ratings of arousal were significantly higher for posed laughter than for disgust
(p<.001)andbaselinesounds(p<.001).Therewas no significantdifferencebetween
arousal ratings of disgust and baseline sounds (See Graph 1).
Valence
A one-way independent ANOVA, with the factor ‘sound condition’ (four levels:
real laughter, posed laughter, disgust and baseline), revealed a significant main
effect of sound condition(F(3,80)= 513.2, p<.001) meaning valence ratings were
different depending on the type of sound. A Bonferroni correctionwas applied for
multiple comparisons. Ratings of valence were significantlyhigher (more positive)
for real laughter (M=6.12, S.D=.41) than for posed laughter (M=4.92, S.D=.4)
(p<.001),disgust(M=2,S.D.=.35)(p<.001)andbaselinesounds(M=3.13,S.D=.32)
(p<.001). Ratings of arousal were significantly higher for posed laughter than for
disgust (p<.001)andbaselinesounds (p<.001),andratings weresignificantlyhigher
for baseline sounds than disgust (p<.001) (See Graph 1).

16. Authenticity
A one-way independent ANOVA run, with the factor‘soundcondition’(fourlevels:
real laughter, posed laughter, disgust and baseline), revealed a significant main
effect of sound condition (F(2,60)= 108.56, p<.001) meaning authenticity ratings
were differentdependingonthe type of sound. A Bonferronicorrectionwas applied
for multiple comparisons. Real laughter was rated as significantly more authentic
(M=5.77, S.D=.51) than posed laughter (M=3.49, S.D=.65) (p<.001), and more
authentic than disgust (M=3.69, S.D=.5) (p<.001). There was no significant
differencebetweenauthenticityratingsof posedlaughter and disgust(SeeGraph 1).
Correlations
Graph 1: Bar graph showing the mean ratings of arousal, valence and authenticity for each sound
condition (bars represent standard deviation).
1
2
3
4
5
6
7
Real Laughter Posed Laughter Disgust Baseline
Rating(±1SD)
Sound Condition
AROUSAL
VALENCE
AUTHENTICITY

17. Pearson’scorrelationcoefficientswerecomputedtoassess therelationshipbetween
arousal, valence and authenticity perceptions for each sound condition (real
laughter, posedlaughter, disgust and baseline).
For real laughter there is a positive correlation between ratings of arousal and
valence (r(21)=.84,p<.001),apositivecorrelationbetweenarousaland authenticity
(r(21)= .66, p=.001), and a positive correlation between valence and authenticity
(r(21)= .6, p=.004). For posed laughter there is a positive relationship between
arousal and valence (r(21)= .7, p<.001), apositive correlationbetweenarousal and
authenticity (r(21)= .66, p=.001), and a positive correlation between valence and
authenticity(r(21)=.85,p<.001).Fordisgustthereisa negative correlationbetween
arousal and valence (r(21)= -.6,p=.004),anegative correlationbetweenarousal and
authenticity (r(21)= -.51, p=.018), but a positive correlationbetween valence and
authenticity (r(21)= .7, p<.001). For baseline sounds there was no significant
correlationbetweenarousal and valence.
Functional magnetic resonance imaging

18. Analysis of Combined Laughter
The first of two overall sets of models combines the two laughter conditions into a
single condition regressor, allowing us to examine how brain activation is
modulated by affective properties of laughter. For combined laughter we find a
positive correlationin auditory regions, specifically bilateral STG/Heschl’s gyrus,
for arousal, valence and authenticity (See Table 1 and Figure 1(a)). Regions
showing a negative correlationwith the three affective properties include arange of
cortical and subcortical sites such as thalamus, caudate and precuneus. However,
for the property of authenticity only, we find a negative correlation in the right
superior frontal gyrus, left superior medial gyrus, left inferior frontal gyrus/left
middle frontal gyrus, right middle frontal gyrus, right superior medial frontal gyrus,
right middle frontal gyrus, right precuneus and bilateral anterior cingulate cortex
(ACC) (See Table 1 and Figure 1(b)). That is, the mPFC activation observed by
McGettigan et al. (2015) inresponse to posed laughter was observed here for the
authenticityscale,wherebytherewas greateractivationin thisregionwhen listening
to laughter that is perceivedas less authentic.

20. Separateanalysisof Real andPosedlaughter
For combined laughter we found that auditory regions respond to arousal, valence
and authenticity, but we then wanted to compare across different vocalisations and
examine whether these sound properties engage the same regions. Therefore we
next modelledreal and posed laughter in separate regressors, which allowed us to
explore commonalities of real and posedlaughter as separate conditions, alongside
disgust and baseline sounds.
Neural Responses to Emotional and Non-emotional Vocalisations Modulated by
Perceived Arousal
Figure 1: Image shows brain regions that exhibited (a) positive correlations and (b) negative correlations of
their haemodynamic responses with perceived emotional authenticity, arousal and valence of laughter, during
the passive listening to both realand posed laughs.

21. When passively listeningto sounds that are perceivedas more arousing, there was
greater activation in auditory regions, and this increase in activation is found for
both emotional and non-emotional vocalisations (across all soundconditions) (See
Figure 2(a)). For both posed and real laughter, we find a positive correlation
between arousal and BOLD response strengthinbilateral STG. For disgust sounds
we find a positive correlationbetween arousal and BOLD response in right STG
and bilateral Heschl’s gyrus. We also find a positive correlationbetween arousal
and BOLD response strengthinright STG for baseline sounds (See Table 2). These
results indicate commonalityinthe neural correlatesof arousal inthe perceptionof
diverse emotional, and non-emotional, sounds.
Neural Responses to Emotional Vocalisations Modulatedby Perceived Valence
Passively listening to more positive laughter was found to be associated with
enhanced activation in auditory regions, regardless of the genuineness of these
sounds (SeeFigure2(b)).Wefinda positivecorrelationbetweenvalence andBOLD
response strength in bilateral STG and Heschl’s gyrus for real laughter, and a
positive correlationbetweenvalence and BOLD response strength inbilateral STG
forposedlaughter. There isthereforeoverlapinthesignificantactivationofbilateral
STG (See Table 2). These enhanced activations are however specific to laughter,
indicating that these brain regions may not show a general response to perceived
valence in human vocalisations.
Neural Responsesto EmotionalVocalisations Modulated byPerceivedAuthenticity
Passively listening to more authentic laughter was found to be associated with
enhanced activation in auditory regions (See Figure 2(c)). We find a positive

22. correlationbetweenauthenticityand BOLD response strengthin bilateral STG and
Heschl’sgyrus forreallaughter, and a positivecorrelationbetweenauthenticityand
BOLD response strength in bilateral STG and right Heschl’s gyrus for posed
laughter. There isthereforeoverlapinthe significant activation of bilateral STG and
Heschl’s gyrus (See Table 2). These enhanced activations are however specific to
laughter, indicating that responses of auditoryregions to perceivedauthenticityare
not generalizable to all sounds (e.g. negative disgust sounds).

23. Coordinates are in Montreal Neurological Institute (MNI) stereotactic space.

24. (b)
(c)

25. Discussion
In a previous fMRI study, McGettigan et al. (2015) endeavoured to explore the
neural responses during passive listening to genuine involuntary laughter and
voluntary posed laughter, and they identified distinct cortical signatures in
perception of thesetwo types of laughter. The present studyhas expanded upon this
research by examining how such brain activity, when listening to emotional
vocalisations, is modulated by affective properties of the sounds. We were able to
compare this modulation across emotional authenticity, emotion category and
intelligibility, usingtwo overall sets of models for analysis. Firstlywe lookedat all
laughter (real and posed) combined, and found commonalities in the regions
modulated by arousal, valence and authenticity, namely positive correlations
betweenthesepropertiesandactivationinbilateralSTG/Heschl’s gyrus, but we also
found distinctioninthat the propertyof authenticityspecificallymodulatedthe size
of the BOLD response inmPFC regions. A secondset of models thenallowedus to
analyse the four soundcategoriesseparatelyand compare acrossthem.This enabled
us to determine whether listening to real laughter and posed laughter, as well as
othertypesof sound(disgustand baseline),engages similarregionsand whether the
activity in these regions varies in the same way accordingto affective properties of
the sounds. Indeed we found commonalityin that the strength of STG activation
positively correlated with the properties of arousal, valence and authenticity in
emotional vocalisations.
Figure 2: Images show brain regions that exhibited positive correlations of their haemodynamic responses with
perceived (a) arousal, (b) valence, (c) emotional authenticity, during the passive listening to emotional and non-
emotional vocalisations.

26. It was tentatively hypothesised that the regions recognised by McGettigan et al.
(2015) as respondingpreferentiallyto either real or posedlaughter would likelybe
sensitivetoaffectivepropertiesoflaughter. When analysing realand posedlaughter
together we found a specific sensitivityof mPFC regions, which McGettiganet al.
previously identified as being more strongly engaged for posed rather than real
laughter, tothe propertyofauthenticity.Giventhat thepropertiesofarousal,valence
and authenticityare highly correlated for laughter vocalisations, it is not surprising
that there is overlap in the response of some regions to these properties, namely
auditory regions (As evidenced in Figure 1(a)). Yet despite this tight behavioural
correlation between the continuous sound properties, we only find a significant
negative correlation between mPFC activation and authenticity (As evidenced in
Figure 1(b)). This suggests that whilst regions concerned with basic and early
auditory processingrespondto auditorymarkers such as arousal and valence, there
is somethingmore to the processingof authenticityinlaughter, where higher-order
decision-makingprocessesare necessary.
The mPFC is a region that has been ascribed a number of functional roles relating
to higher-order processing, and social (Frith& Frith, 2010) and emotional (Kober
et al., 2008) processinginparticular. Specifically, mPFC is consistentlyimplicated
in human mentalizing systems;that is, regions of mPFC are thought to be involved
in imaginative mental activity that is necessary for interpreting and representing
anotherpersonspsychologicalstate/perspective(Amodio,2006). Therearemultiple
neuroimaging studies that report significant mPFC activation during participant
engagement in a distinct variety of mentalizing tasks (Goel, Grafman, Sadato &

27. Hallett, 1995;Fletcher etal., 1995). Previous researchhas also demonstratedmPFC
sensitivity to emotional authenticity. McGettigan et al. (2015) interpreted their
finding greater activation in mPFC for posed laughter, as an indication of an
obligatory attempt to decipher the mental state of individuals producing more
ambiguous emotional vocalisations. Their results and explanation are in
concordance with preceding research, such as that of Szameitat et al. (2010) who
found that activation in mPFC, precuneus and ACC was greater for social laughter
than for tickling laughter, due to emotional ambiguity of the former. This mPFC
sensitivity also extends to emotional speech. For example, Drolet, Schubotz and
Fischer (2012) foundstronger mPFC responses to authentic emotional speeches, in
contrast to play-acted speeches. Whilst this is in contrast to McGettiganet al. and
the present study finding greater activation for less authentic vocalisations, Drolet
et al. provide a similar interpretation of their results; given that the authentic
speeches were more socially open-ended and likely to evoke participants
autobiographical memory, mentalizing processes were engagedon hearing them.
It is therefore likelythat where the present study found activation in mPFC to be
modulated by perceived emotional authenticity of laughter, participants were
having to engage in mentalizing processes when listening to these emotional
vocalisations that were less authentic and, as such, more ambiguous. This is also
evidenced in our finding negative correlations between authenticity and BOLD
response strength in ACC, precuneus and calcarine gyrus. Such regions have
previously been implicated in the perception of more ambiguous emotional
vocalisations (Szameitat et al., 2010). The precuneus in particular is thought to be

28. involved in metalizingprocesses. Ina large meta-analysis of over 200 fMRIstudies
examining how we understand others’mental states, Van Overwalle and Baetens
(2009) concludedthat the precuneus is a one crucial part of the human mentalizing
system. Additionally, there is fMRI researchlookingat different types of laughter
specificallythat implicates the precuneus in this system. Wildgruber et al. (2013)
reportedparticularlystrongresponses to complexsocial laughter in the precuneus,
in parallel to anterior mediofrontal cortex activation, as a result of such laughter
triggeringmentalizing processes. Wildgruber et al. also found that listeningto this
type of laughter engendered greater activation in visual associationcortex, which
they consider as reflective of visual imagerybeing elicitedinconnectionwith, or as
part ofmentalizingprocesses.Thisexplanationcan be extendedtothe presentstudy,
which found activation in calcarine gyrus, located on the medial surface of the
occipital lobe, to be modulated by authenticity of laughter. Lastly, ACC may also
have been recruited during mentalizing processes. This brain region has been
implicated in the detection of emotional cues (Lane et al., 1998), as well as in
directingattentionto mental states (Gallagher & Frith, 2003).
We were additionally interestedin commonalitiesin the regions engaged by non-
verbal vocalisations and modulated by continuous properties of sound. Thus for a
second set of models we divided laughter into its constituent sound categories of
real and posedlaughter, and comparedthe neural correlatesof arousal, valence and
authenticity for these two emotional vocalisations, alongside disgust and baseline
sounds. We found that there was indeedcommonalityin the regions that responded
differentiallyto the continuous sound properties;within the auditory cortexthere

29. was enhanced activation to non-verbal vocalisations that were intensely/highly
emotional (the vocalisations that are perceived as being more arousing, positive
and/or authentic). These regions, which are concerned with basic acoustic
properties, were similarly engaged in the processingof all laughter (regardless of
whether the laughter is real or posed), and even by sounds across emotional
categories (disgust as well as laughter vocalisations). This observed overlap in the
fMRI analysis is in concordance withthe behavioural correlations, whichindicate a
strongassociationbetweenthe propertiesof arousal, valence and authenticity.
The overlap where we find positive correlations betweenBOLD response strength
and the three sound properties is most commonly in Heschl’s gyrus and superior
temporal cortex (STC) (See Figure 2). In recent meta-analyses of much
neuroimaging research investigating how sound is processed in the human brain,
these auditory regions are recognisedas being especiallysensitive to human voice
(Schirmer, Fox & Grandjean, 2012) and non-verbal vocalisations in particular
(Fruhholz & Grandjean, 2013). Additionally researchfinds areas of STC, such as
STG, to show greater response to emotional as opposed to neutral prosody,
suggesting these regions are engaged automatically during the processing of
emotional informationin the voice (Ethofer et al., 2009). Peak STG activation to
emotional vocalisations is frequentlyfoundinthe right hemisphere (Meyer, Zysset,
von Cramon & Alter, 2005; Bach et al., 2008). This is in concordance with the
presentstudy, which findsright STG activationtocorrelatewithall threecontinuous
sound properties. The right hemisphere is considered to be essential for the
processingof affective moods, and auditory regions inthis hemisphere are thought

30. to be especially proficient in the processing of acoustic cues that hold affective
information(Meyer et al., 2005).
In the present study, activation in STG appears to be most salient for the emotion
categoryof laughter, and for the sound propertyof arousal. Firstly, STG response
during passive listening to both real and posed laughter is modulated by arousal
valence and authenticity. This is not entirely surprising as previous research has
observedauditorycortextobe more stronglyactivatedby listeningto laughter, than
to other non-verbal vocalisations (Sander & Scheich, 2001) and affective speech
(Meyer et al., 2005). Secondly we found that STG response was consistently
modulated by perceived arousal of a sound regardless of the sound category, and
this was modulation was observed across emotional authenticity (real and posed
laughter), emotion category (laughter and disgust) and intelligibility (emotional
vocalisations and baseline sounds) (See Figure 2(a)). The importance of arousal as
an affective propertyof human vocalisations, particularlynon-verbal vocalisations,
is a relatively novel prospect. The effects of arousal on acoustic processinghave
seldombeeninvestigated. However, the literature doesthusfar indicate a sensitivity
of the STG to arousal; the level of arousal in emotional voices (as opposedto their
valence for example) appears to drive neural responses of STG to these voices
(Wiethoff et al., 2008;Ethofer et al., 2011). How might we interpret the relevance
of this particular property to emotional vocalisations? Arousal levels are found to
co-vary with multiple acoustic features that are integral to the processing of
emotional vocalisations, such as fundamental frequency (Scherer, Johnstone &
Klasmeyer, 2003). As such, arousal is a particularlypowerful emotional cue.

31. Close inspectionof our functional imaging data reveals the PT as a specific region
of interest;it appears that it is this region, situated on the superior temporal plane
just posteriorto Heschl’s gyrus, whichis respondingto the level of arousal, valence
and authenticityin sound. The PT isclassicallyassigneda roleinspeechproduction,
however more recent research has also implicated this region in perception.
Evidence of thePT as avoice-selectiveregioncomesfromanfMRIstudy by Berlin,
Zatorre, Lafaille, Ahad & Pike (2000), who found increased activity when
participants passively listenedto human vocalisations (bothspeechand non-speech
sounds) compared to when listeningto environmental sounds. A subsequent meta-
analysis of PET studies also supportedthe notion that the PT is critically involved
in the perceptual processingof verbal and non-verbal human sounds (Wise et al.,
2001). Furthermore, the PT appears especiallysensitive to affective vocalisations.
For example, Dietrich, Hertrich, Alter, Ischebeck and Ackermann (2007) found
enhanced response in the PTto nonverbal vocalisations that possessedemotionality
and an inherent communicative role, such as laughter. PT response was greater for
this type ofaffectivevocalisation,than forsounds signallyautonomic-physiological
states(suchas snoring) orvocal gestures(suchasbelching). Thereforethereismuch
evidence to implicate the PT in the processingof non-verbal vocalisations such as
those heard by participants in the present study.
Given that we find PT activation to be modulated by arousal, valence and
authenticity,how thenmight this regionbe involved inthe processingof continuous

32. sound properties? With regards to acoustic processing, there is a distribution of
functional roles across STC; processing occurs serially, whereby lower-level
regions (primaryauditorycortex) are responsible for the decodingof basic acoustic
properties whilst higher-level processing areas are thought to sub-serve sensory-
integrative roles (Schimer & Kotz, 2006). It has been suggested that the PT may
constitute this integration site, where acoustically complex vocalisations such as
emotional vocalisations undergo acoustic analysis (Griffiths & Warren, 2002;
Warren, Wise & Warren, 2005; Fruhholz & Grandjean, 2013). The PT may be
important for spatial analysis especially. The dual-processing, two-streams
hypothesis is not restrictedto the visual system, but also thought to exist inauditory
cortex where the PT occupies a role within the dorsal auditory pathway
(Rauschecker & Scott, 2009). There is much neuroimaging evidence for the PT
responding to spatial manipulations, which indicate its involvement in temporo-
spatial transformations (Hickok, 2009). Additionally, recent researchhas indicated
that the PT is also responsible for sensory-motortransformations, that is auditory-
motor transformations, due to the interaction of the signals it receives from both
auditory cortex and frontal areas (e.g. Broca’s area) (Isenberg, Vaden, Saberi,
Muftuler & Hickok, 2012). It is thought that, within the PT, events (sounds) are
representedin terms of action (motor) possibilities (Rauschecker & Scott, 2009).
Therefore, the positive correlations we findin the present studycan be explained in
that more arousing/ positive vocalisations are likely to elicit greater PT activation,
because they hold greater potential for asubsequent motor response/consequence.

33. There are potential methodological limitations to the present study that must be
considered. A recent meta-analysis identified a significant sex difference in the
perception of non-verbal displays of emotion (Thompson & Voyer, 2014), and
therefore our having a relatively equal male-female ratio in our sample was
appropriate, however, researchalso finds distinct profiles in laughter produced by
men and women (Provine, 1993). This is relevant to the present study given that
females producedall the emotional vocalisationstimuli. IndeedBelinand Gosselin
(2008), when analysing a set of 90 affective nonverbal vocalisations produced by
actors (Montreal Affective Voices), found that actor gender had an effect on how
people perceived these vocalisations. For example femaleparticipants were notably
better at recognising emotional vocalisations produced by females, than male
participants were at recognisingmale vocalisations. Thereforeit is possiblethat the
ratings of arousal, valence and authenticity given by participants in the present
study, were influenced by another feature of the stimuli: the gender of those
producing the vocalisations.
Given that the present study was investigative, a whole-brain rather than regionof
interest analysis was justifiablyemployed. However, it is important to consider the
limitations of this type of fMRI exploration, most notably the problem of multiple
comparisons. Anextensive number of tests are done over ahuge number of discrete
voxels in the brain, meaning an incrediblystringent p-value thresholdmust be used
to guard against Type I errors (falsepositives). Conversely, employingsuchasmall
p-value makes it difficult to declare significance, andit is therefore likelythat Type
II errors (failure to recognise a true effect) occur too frequently (Leiberman &

34. Cunningham, 2009). We must also be cautious in the use of reverse inference,
whereby the activation of aspecific brainregionis interpretedas the engagement of
a specific cognitive process; this is particularly true for regions such as the PT,
whose functional roles are onlyrelativelyrecentlybeingresearchedandestablished
(Poldrack, 2006). Further researchis necessaryto validate the role of the PT in the
processingof acousticfeaturesand affective properties of humanvocalisation.
A final considerationofthe presentresearchisthat the significantmPFC activation,
which is thought to indicate the engagement of mentalizing processes following
implicit recognitionof authenticityin emotional vocalisations, is not evident when
laughter is divided into separate real and posedconditions. We might expect to find
greater mPFC response to posed laughter than to real laughter, as would be in
concordance withMcGettiganet al. (2015), however this is not observeddue to the
limited statistical power of our fMRI analysis. We can instead refer to the
behavioural analysis, which does confirm a significant difference between
authenticity ratings for real laughter and posed laughter. The limited statistical
power comes largely from a restriction in the range of ratings for the three
continuous sound properties; it is difficult to control for the extensive
features/variables of the stimuli to ensure we obtain appropriate ranges, and also to
ensure that the properties are distinct from one another (as find them to be highly
correlated). If future research was to examine further the seeming importance of
authenticity in the perception of emotional vocalisations, it is possible that new
stimuli could be generated and a different statistical analysis employed whereby
distinctaffectivesoundpropertiescouldbe partitionedout. For example, given that

35. arousal is a particularlysalient propertyof emotional vocalisations(Wiethoffet al.,
2008), future research could match the vocalisation stimuli on this property. It
would then be possible to portionout arousal datafrom the rest ofthe brainanalysis
data, in order to determine the responses specific to perceived authenticity and
ensuring that significant activation (such as that of mPFC) cannot be attributed to
increases inthe general excitement/arousal of the sound.
As well as partitioning out affectiveproperties of emotional vocalisations, there is
alsoscopeforfeatureresearchto inspectmorecloselydistinctacousticcontributors.
This could involve utilizing different stimuli and/or a different analysis approach.
For example, it might be useful to explore which acoustic features are important to
auditory processing in STG; that is, which features activate STG most strongly.
Additionally, by lookingat functional connectivity it would be possible to examine
how these low-level auditoryregions communicate with regions involved in higher
level processing, and ask for example whether certain acoustic features have to
reach a threshold to be processed at a higher level of abstraction. Furthermore,
particular acoustic featuresmaybe relatedto the perceptionof continuousaffective
properties of sound. For example, recent researchhas identified that fundamental
frequency (F0 contour) of emotional vocalisations influences authenticity
perception, and also modulates BOLD response in mentalizing (Theory of Mind)
networks (Drolet, Schubotz, Fischer, 2014). In the present study, baseline sounds
were constructedfrom vocalisationsnippets from the other three soundconditions.
Future research could instead match a set of baseline sounds one-to-one with
emotionalvocalisationstimuli,forfundamental frequency(oran acousticfeatureof

36. interest). This would allow us to determine whether it is the basic acoustic features
of sound that are modulating brain responses, or if indeedaffective properties such
as authenticityare important.
In summary, as an extension of McGettigan et al.’s (2015) research, the present
study finds an important role for mPFC in the perception of authenticity during
passive listening to laughter, as well as identifying a sensitivity of the PT to
continuous properties of emotional and non-emotional vocalisations, which can be
attributed to its involvement in auditory-motor transformations. Through the
integrationof new behavioural data with existing fMRI data, this study constituted
a novel investigationof the brain regions that respond to non-verbal vocalisations;
we examined how such responses are modulated by affective sound properties,
identifying the neural correlates of arousal, valence and authenticity. This research
contributes to the fields of emotionresearchand vocal communication. Emotional
vocalisationssuchas laughter are integralforsocialinteractionand communication,
and thus, researchinvestigatingsuchvocalisationsprovide insight into aspecialised
subset of human behaviour (Gervais & Warren, 2005;Amodio, 2006).

37. References
Amodio, D.M., Frith, C.D. (2006). Meetingof minds: the medial frontal cortexand social
cognition. Nature reviews neuroscience, 7(4). 268-277.
Bach, D.R., Grandjean, D., Sander, D., Herdener, M., Strik, W.K., Seifritz, E. (2008). The
effect of appraisal level on processingemotional prosodyinmeaningless speech.
Neuroimage, 42(2). 919-927.
Bachorowski, J., Owren, M.J. (2008). Handbookof emotions: Vocal expressions of
emotion. New York: The GuilfordPress.
Bachorowski, J., Smoski, M.J., Owren, M.J. (2001). The acoustic features of human
laughter. The journalof the acoustical societyof America, 110(3). 1581-1597.

38. Belin, P., Fillion-Bilodeau, S., Gosselin, F. (2008). The Montreal Affective Voices: a
validated set of nonverbal affect bursts for researchonauditoryaffective
processing. Behaviourresearch methods, 40(2). 531-539.
Belin, P., Zatorre, R.J., Lafaille, P., Ahad, P., Pike, B. (2000). Voice-selective areas in
human auditorycortex. Nature, 403(6767). 309-312.
Davila-Ross, M., Allcock, B., Thomas, C., Bard, K.A. (2011). Aping expressions?
Chimpanzees produce distinct laugh types when respondingto laughter of others.
Emotion, 11(5). 1013-1021.
Dietrich, S., Hertrich, I., Alter, K., Ischebeck, A., Ackermann, H. (2007). Semiotic
aspects of human nonverbal vocalisations: afunctional imaging study.
Neuroreport, 18(18). 1891-1894.
Drolet, M., Schubotz, R.I., Fischer, J. (2012). Authenticityaffectsthe recognitionof
emotions inspeech: behavioural and fMRI evidence. Cognitive, affectiveand
behavioural neuroscience, 12(1). 140-150.
Drolet, M., Schubotz, R.I., Fischer, J. (2014). Recognizingthe authenticityof emotional
expressions: F0 contour matters whenyou need to know. Frontiers in human
neuroscience, 8 (144). 1-11.
Ethofer, T., Bretscher, J., Gschwind, M., Kreifelts, B., Wildgruber, D., Vuilleumier, P.
(2011). Emotional voice areas: anatomic location, functional properties, and
structural connections revealedbycombinedfMRI/DTI. Cerebral cortex, 22(1).
191-200.
Ethofer, T., Kreifelts, B., Wiethoff, S., Wolf, J., Grodd, W., Vuilleumier, P., Wildgruber,
D. (2009). Differential influences of emotion, taskand novelty on brain regions
underlying processingof speechmelody. Journal of cognitiveneuroscience, 21(7).
1255-1268.

39. Fletcher, P.C., Happe, F., Frith, U., Baker, S.C., Dolan, R.J., Frackowiak, R.S.J., Frith,
C.D. (1995). Other minds in the brain: a functional imaging study of ‘theoryof
mind’ in storycomprehension. Cognition, 57. 109-128.
Frith, U., Frith, C. (2010). The social brain: allowing humans to boldly go where no other
species has been. Philosophicaltransactions of the Royal Society of LondonB:
Biological Sciences, 365(1537). 165-176.
Fruhholz, S., Grandjean, D. (2013). Multiple subregions insuperior temporal cortexare
differentiallysensitive to vocal expressions: aquantitative meta-analysis.
Neuroscience & biobehavioural reviews, 37(1). 24-35.
Gallagher, H.L., Frith, C.D. (2003). Functional imaging of theoryof mind. Trends in
cognitivesciences, 7(2). 77-83.
Gervais, M., Wilson, D.S. (2005). The evolutionand functions of laughter and humor: a
synthetic approach review. The quarterly review of biology, 80(4). 395-430.
Goel, V., Grafman, J., Sadato, N., Hallett, M. (1995). Modellingother minds.
Neuroreport, 6(13). 1741-1746.
Graham, E.E. (1995). The involvement of sense of humor in the development of social
relationships. Communicationreports, 8(2). 158-169.
Griffiths, T.D., Warren, J.D. (2002). The planum temporale as a computational hub.
Trends in neuroscience, 25(7). 348-353.
Hickok, G. (2009). The functional neuroanatomyof language. Psychics of life reviews,
6(3). 121-143.
Isenberg, A.L., Vaden, K.I., Saberi, K., Muftuler, L.T., Hickok, G. (2012). Functionally
distinct regions for spatial processingand sensorymotor integrationinthe planum
temporale. Human brain mapping, 33(10). 2453-2463.

40. Kober, H., Barrett, L.F., Joesph, J., Bliss-Moreau, E., Lindquist, K., Wager, T.D. (2008).
Functional grouping and cortical-subcortical interactions inemotion: ameta-
analysis of neuroimaging studies. Neuroimage, 42(2). 998-1031.
Lane, R.D., Reiman, E.M., Axelrod, B., Yun, L.S., Holmes, A., Schwartz, G.E. (1998).
Neural correlates of levels of emotional awareness: evidence of an interaction
between emotionand attentioninthe anterior cingulate cortex. Journalof
cognitiveneuroscience, 10(4). 525-535.
Lieberman, M.D., Cunningham, W.A. (2009). Type I and Type II error concerns infMRI
research: re-balancingthe scale. Social cognitiveandaffective neuroscience, 4(4).
423-428.
Lima, C.F., Castor, S.L., Scott, S.K. (2013). Whenvoices get emotional: acorpus of
nonverbal vocalisations for researchonemotionprocessing. Behaviourresearch
methods, 45(4). 1234-1245.
McGettigan, C., Walsh, E., Jessop, R., Agnew, Z.K., Sauter, D.A., Warren, J.E., Scott,
S.K. (2015). Individual differences inlaughter perceptionreveal roles for
mentalizing and sensorimotorsystemsinthe evaluation of emotional authenticity.
Cerebralcortex. 1-12.
Meyer, M., Zysset, S., von Cramon, D.Y., Alter, K. (2005). Distinct fMRIresponses to
laughter, speechand sounds along the human peri-sylviancortex. Cognitivebrain
research, 24(2). 291-306.
Poldrack, R.A. (2006). Cancognitive processesbe inferredfrom neuroimagingdata?
Trends in cognitive sciences, 10(2). 59-63.
Provine, R.R. (1993). Laughter punctuates speech: linguistic, social andgender contexts
of laughter. Ethology, 95(4). 291-298.

41. Provine, R.R. (2001). Laughter: a scientific investigation. UnitedStates of America:
Penguin Books.
Provine, R.R., Emmorey, K. (2006). Laughter among deaf signers. Journal of deaf studies
and deaf education, 11(4). 403-409.
Rauschecker, J.P, Scott, S.K. (2009). Maps and streams in the auditory cortex: nonhuman
primates illuminate human speechprocessing. Nature neuroscience, 12(6). 718-
724.
Sander, K., Scheich, H. (2001). Auditoryperceptionof laughing and crying activates
human amygdala regardless of attention. Cognitive brainresearch, 12. 181-198.
Sauter, D.A., Eisner, F., Calder, A.J., Scott, S.K. (2010). Perceptual cues innonverbal
vocal expressions of emotion. The quarterly journal of experimentalpsychology,
63(11). 2251-2272.
Scherer, K.R., Johnstone, T., Klasmeyer, G. (2003). Vocal expressionof emotion.
Handbook of affectivesciences. 433-456.
Schirmer, A., Fox, P.M., Grandjean, D. (2012). Onthe spatial organizationof sound
processinginthe human temporal lobe: ameta-analysis. NeuroImage, 63(1). 137-
147.
Schirmer, A., Kotz, S.A. (2006). Beyondthe right hemisphere: brainmechanisms
mediating vocal emotional processing. Trends in cognitive sciences, 10(1). 24-30.
Scott, S.K., Sauter, D., McGettigan, C. (2010). 5-Brainmechanisms for processing
perceivedemotional vocalisations inhumans. Handbook of behavioural
neuroscience, 19. 187-197.
Smoski, M.J., Bachorowski, J.A. (2003). Antiphonal laughter in developing friendships.
Annals of the New York academy of sciences, 1000(1). 300-303.

42. Szameitat, D.P., Alter, K., Szameitat, A.J., Wildgruber, D., Sterr, A., Darwin, C.J. (2009).
Acoustic profiles of distinct emotional expressions inlaughter. The journal of the
acoustical societyof America, 126(1). 354-366.
Szameitat, D.P., Kreifelts, B., Alter, K., Szameitat, A.J., Sterr, A., Grodd, W.,
Wildgruber, D. (2010). It is not always tickling: distinct cerebral responses during
perceptionof different laughter types. Neuroimage, 53(4). 1264-1271.
Thompson, A.E., Voyer, D. (2014). Sexdifferencesinthe ability to recognise non-verbal
displays of emotion: ameta-analysis. Cognition and emotion, 28(7). 1164-1195.
Van Overwalle, F., Baetens, K. (2009). Understandingothers’actions and goals by mirror
and mentalizing systems: ameta-analysis. Neuorimage, 48. 564-584.
Vettin, J., Todt, D. (2004). Laughter in conversation: featuresof occurrence andacoustic
structure. Journal of nonverbal behaviour, 28(2). 93-115.
Viinikainen, M., Katsyri, J., Sams, M. (2012). Representationof perceivedsoundvalence
in the human brain. Human brainmapping, 33(10). 2295-2305.
Warren, J.E., Sauter, D.A., Eisner, F., Wiland, J., Dresner, M.A., Wise, R.J., Rosen, S.,
Scott, S.K. (2006). Positive emotions preferentiallyengage an auditory-motor
‘mirror’system. The journal of neuroscience, 26(5). 13067-13075.
Warren, J.E., Wise, R.J., Warren, J.D. (2005). Sounds do-able: auditory and motor
transformations andthe posterior temporal plane. Trends in neuroscienes, 28(12).
636-643.
Wattendorf, E., Westermann, B., Fielder, K., Kaza, E., Lotze, M., Celio, M.R. (2013).
Explorationof the neural correlatesof ticklishlaughter by functional magnetic
resonance imaging. Cerebral cortex, 23(6). 1280-1289.

43. Wiethoff, S., Wildgruber, D., Kreifelts, B., Becker, H., Herbert, C., Grodd, W., Ethofer,
T. (2008). Cerebral processingof emotional prosody- influence of acoustic
parameters and arousal. Neuroimage, 39(2). 885-893.
Wildgruber, D., Szameitat, D.P., Ethofer, T., Bruck, C., Alter, K. Grodd, W., Kreifelts, B.
(2013). Different types of laughter modulate connectivitywithin distinct parts of
the laughter perceptionnetwork. PloS one, 8(5). 1-15.
Wise, R.J., Scott, S.K., Blank, S.C., Mummery, C.J., Murphy, K., Warburton, E.A.
(2001). Separate neural subsystems within Wernicke’s area. Brain, 124(1). 83-95.