Groove on the brainrhythmic complexity and predictive coding

Peter VuustDirector of Center for Music in the Brain (MIB)

Profes s or a t the Roy al Academy of Mus ic , Aarhus , DenmarkProfes s or a t Aarhus Univ ersi ty

PhD. in neuros c ienc e, MSc . In math, French and mus ic Bas s is t/c ompos er

DNC - Danish Neuroscience Center

MR / fMRI PET MEG EEG

RAMA

Center for Music in the Brain

Groove and the brain� Humans move in time to music

� Humans mov e s pontaneous ly to s ome k inds of mus ic more than other (Madis on et a l 2006, J anata et a l . 2012)

� Different body -parts embody d i fferent metric a l leve ls in d i fferent s patia l orientations (Toiv ia inen et a l . 2010, Burger e t a l . 2012)

� Rhy thmic c omplex i ty in fluenc es s ens orimotor s y nc hronisation(Repp 2005, 2013, Pate l 2005, Kel ler e t a l . 2005, Konv al ink a et a l 2011, 2013, Heggli et a l in prep)

� Rhythm perception involves auditory and motor areas of the brain� Sec ondary motor areas , bas al gangl ia , c erebellum, s uperior tempora l

gy rus (Penhune et a l . 1998, Vuus t e t a l . 2005, Grahn et a l 2007, 2011, Chen et a l . 2008, Stupac her et a l . 2012), in ferior fronta l gyrus , anterior c ingulate, temporo-parie ta l junc tion (Vuus t e t al . 2006, 2011)

� Potential for rehabilitation� Park ins on’s d is eas e (Thautet a l . 1996, Benoi t e t a l . 2014, Kotz et a l . 2015) � After s trok e (Sc hneider e t a l . 2007, Al tenmül ler et a l 2009)

� Relatively unique to human beings� But s ee e.g. Pate l e t a l . 2009 or Cook et a l . 2013 � Beat trac k ing is not s imple

Gra h n & Brett (2 0 0 7 )

Vu u st et a l (2 0 1 1 )

In ferior fronta l gy rus (BA47)

Groove – The pleasurable desire to move

What are the brain mechanisms related to groove?Which grooves engage us the most?

Predictive coding of music

)()()|()|( inputp

modelpmodelinputpinputmodelp =Vu u st & Witek 2 0 1 4

Geb a u er, Krin g elb a ch & Vu u st , 2 0 13Vu u st et a l. , 2 0 0 9

Vu u st & Frith , 2 0 0 8

1 32 4

Prediction and prediction error

Prediction error

0 100 200

-50

0

50

100 fT/c m

ms

s Ιs ΙΙs ΙΙΙ

EEG

Vuus t e t al , Cortex , 2009

The optimal amount of syncopation

• “How much does this rhythm makeyou want to move?”(1-5)

• “How much pleasure do you experience with this rhythm?” (1-5)

� Stimuli� 50 funk drum-breaks, � 80% taken from real grooves (funk/rock repertoire) 20% composed

by authors� Synthezised drum kit (BD, SD, HH)� 2-bar phrase, 4 repetitions, 120 bpm, 16 sec.

low medium high

Witek , Clark e, Wal lentin , Kringelbach, & Vuus t, PLoS One, 2014

Syncopation and groove

Wan

ting

to M

ove

Exp

erie

nce

of P

leas

ure

β=-.568 β=-.667

Simple Complex Simple Complex

MOVEMENT PLEASURE

There is a rhythmic sweet spot for pleasure and desire to move.

Syncopation Syncopation

low med high

Syncopation (𝑆 - g(µ))(amount of stimulusdeviation from the meter)

Meter experience (π )(precision of the prediction)

x

Explainable prederror(Musical appreciation?)

=

Relationship between syncopation and meter

26 Partic ipants

15 drum-break s:5 low5 medium5 h igh

Evidence for a broken predictive model(Motion Capture)

Meas ures :� Mov ement forc e (ac c eleration)� Sy nc hronis ation acc urac y (cros s-c orre la tion at main puls e)� Period ic i ty prominenc e (auto-corre la tion)Witek et a l, Exp Bra in Res. 2 0 1 7 , in Press,

Sync

hron

izat

ion

inde

x

SPM analysis (mean bold)

Low Medium High

Right*

Low Medium High

*

Low Medium High

**

Auditory Cortex Pallidum/Putamen Anterior Inferior Insula

0

2

4

6

Audition MotionEmotion

Challenging rhythms employ auditorymotor and sensory integration networks

Connectivity analysesHigher meta-stabilit y when the music grooves

EstimatedEffective connectiv ity

low medium high

Groove ratings

Deco & K ri ngel bach (2014) Neuron

???rhythmic complexity

rhythmic complexity

subj

ectiv

e g

roov

e

Low Medium High

ordered metastable random

L H

M

neural dynamics

Wi tek, Gi l son, Cl arke, Wal l ent i n, ,Deco, K ri ngel bach & V uust , 2017, submi t ted

The networks of groove

The connections lis ted in order of s ignificance (p<0.001, uncorrected)

L Hippocampus L PrecentralL Thalamus L PrecentralR Thalamus L Sup Motor AreaL Inf Occipital L Mid OrbitofrontalL Inf Occipital L ParahippocampalL Pallidum L Sup OccipitalL Supramarginal L PallidumL Thalamus L Mid TemporalR Amygdala R Mid TemporalL Post Cingulum R AmygdalaR Thalamus R Sup Motor AreaR Thalamus R Sup Frontal

123456789101112

A B

C D

Groove: The interaction between rhythmand harmony

HARMONY

RHYTHM

LOW

Major triads

MED

7th chords with tensions

HIGH

including b9-intervals

LOW(Clav e minus s y nc opation)

MEDClave

HIGHWrong Clave

Witek, Ma th ews, Heg g li, Lu n d , Pen h u ne & Vu u st, in p rep a ratio n

6 versions of each of the 9 categories (54 stimuli in total)

The influence of complexity on ”move” and ”pleasure”

Wanting to move

low med high

Pleasure

low med high

Online Survey201 respondents from five continents Task: to rate (1-5)

� wanting to move

� pleasure

Additionally, information on musical training, enjoyment of groove music and dancing was collected Ma th ews, Witek, Heg g li, Pen h u n e & Vu u st, in prep a ra tio n

Rhythmic complexity Rhythmic complexity

Data analysesLinear mixed effects (maximal random structure):

Interaction between group and complexity

Wanting to move

low med highRhythmic complexity P < .05

� Stimuli� 2 x 2 design (rhythmic and harmonic complexity (MM, MH, HM, HH)� Repeated piano chord patterns + hihat

� Participants� Musicians: N = 26� Non-music ians: N = 29

� Task: to rate (1-5)� wanting to move � pleasure� perceived beat strength

� fMRI � Multi-echo (2 echoes) BOLD fMRI� TR=2

� (DTI and facial EMG)

Brain processing of rhythmic and harmonic complexity

Ma th ews, Witek, Lu n d , Pen h u n e & Vu ust, in prep a ra tion

HARM O NY

RHYTHM

LO W

M ajor t r iads

M ED

7t h chor ds wit h t ensions

HI G H

including b9-int er vals

LO W( Clave m inus syncopat ion)

M EDClave

HI G HWr ong Clave

Ratings (1-5)

β

Wanting to Move

Rhy thm 0.6***

Harmony 0.1***

Group*Rhy thm*Harmony 0.03*

Pleasure

Rhy thm 0.6***

Harmony 0.2***

Group 0.01*

Group*Rhy thm*Harmony 0.02^

med highRhythmic complexity

med high med highRhythmic complexity

med high

*p < .05, **p < .01, ***p < .001, p̂ < .06

Data analysesLinear mixed effects (maximal random structure):

Extracted Betas

L Caudate

p < .05 (FDR)

R Putamen

Musician Non−Musician

Med High Med High−1.0−0.5

0.00.51.0

Rhythmic Complexity

L ve

ntra

l BG

Bet

as

Harmonic ComplexityMedHigh

Extracted Betas

med highRhythmic complexity

med high

Rhythmic complexitymed high

Basal ganglia activation

L SMAL PMC R PMC

L mOFC

L

Extracted Betas

med highRhythmic complexity

med high

−1

0

1

2

Med HighRhythmic Complexity

SMA Group

MusNon−Mus

Extracted Betas

med highRhythmic complexity

med high

OFC, PMC & SMA

Statistics

βR PutamenRhythm 0.13**L CaudateRhythmGroupGroup*Rhythm*Harm

0.13***0.05*0.03*

R CaudateRhythm 0.13***L SMARhythmGroup

0.09**0.06*

R PMCGroup 0.04*L mOFCRhythmGroup*Rhythm*Harm

0.08**0.03*

*p < .05, **p < .01, ***p < .001

Conclusions� The predictive coding model provides an elegant framework for interpreting brain

processing of music and informs our understanding of � The relationship between rhythm and meter� Motor behavior in relation to rhythm

� There is an inverted U-shaped relation between degree of syncopation and ”wanting to move”/”pleasure”. This U-shape is reflected in activ ity in measures of connectiv ity and meta-stability in the brain.

� The motor system seems to be driven by emotional and sensory systems a process that implicates reward areas of the brain.

� The clavé stimulus combining harmony and rhythm produces a strong sensation of groove in relation to medium syncopated rhythms compared to high and low complexity and involves motor and reward related brain activ ity.

� Musicians have more groove-related (pre)-motor activ ity than non-musicians

� Syncopation is not everything!

Thanks for listening . . .