Neural Substrates of Music Learning and Emotions | Slides from my talk at The Origins of Music and Human Society, a Conference by Institute of Advanced Study in Toulouse and Royaumont Foundation at Royaumont Abbey, France | December 16, 2017

1. Neural Substrates of Music Learning
and Emotions
Psyche Loui, PhD
Wesleyan University
IAST-Fondation Royaumont Conference:
The Origins of Music in Human Society
December 16, 2017

2. Whence musical knowledge?
Perspectives:
• Developmental studies
• Cross-cultural studies
• Neuropsychological studies
• Artificial system
• Bohlen-Pierce scale
2

3. Methods to investigate brain functions
Action
Emotion
Perception
Cognition
Music
Behavior &
Psychophysics EEG
MRI
Sound analysis

4. Bohlen-Pierce
An alternate musical system
F = 220 * 2 n/12
F = 220 * 3 n/13
200
300
400
500
600
700
0 1 2 3 4 5 6 7 8 9 10 11 12 13
increments (n)
frequency(Hz)
Western
Loui, Wessel, & Hudson Kam, 2010, Music Perception.

5. Psychoacoustic properties of
Bohlen-Pierce scale
200
300
400
500
600
700
0 1 2 3 4 5 6 7 8 9 10 11 12 13
increments (n)
frequency(Hz)
F = 220 * 3 n/13
Bohlen-Pierce
3 : 5 : 7
Loui, Wessel, & Hudson Kam, 2010, Music Perception.

6. Composing in the Bohlen-Pierce scale
10 7 10 10
6 4 7 6
0 0 3 0
F = 220 * 3 n/13
Loui, Wessel, & Hudson Kam, 2010, Music Perception.
10 10 7 10
6 7 4 6
0 3 0 0
Retrograde:
Original:
Chord progression

7. Composing melody from harmony – applying a
finite-state grammar
10 7 10 10
6 4 7 6
0 0 3 0
Loui, Wessel, & Hudson Kam, 2010, Music Perception.

8. Melody: 6 à 4 à 7 à 7 à 7 à 6 à 10 à 10
10 7 10 10
6 4 7 6
0 0 3 0
Composing melody from harmony – applying a
finite-state grammar
Loui, Wessel, & Hudson Kam, 2010, Music Perception.

9. Reminiscences (2010) by Steven Yi
A piece in Bohlen-Pierce scale 9

10. Can we learn the B-P scale?
General design of behavioral studies:
1. PRE-TEST
assess baseline
2. EXPOSURE to melodies in one grammar
~30 minutes
3. POST-TESTS
assess learning

11. Learning a musical system:
basic questions
Can we remember old melodies?
2-AFC test of recognition
Can we learn new melodies?
2-AFC test of generalization

12. Learning vs. memory as a function of set size
0 5 10 15 400
Number of melodies
20%
30%
40%
50%
60%
70%
80%
90%
100%
PercentCorrect
recognition
generalization
chance
Loui, Wessel, & Hudson Kam, 2010, Music Perception
Loui & Wessel, 2008, Musicae Scientiae

13. Diffusion tensor imaging
Arcuate Fasciculus
Known roles in speech, language,
music, auditory-motor functions
(Loui et al, 2009; Saygin et al, 2013;
Qi et al, 2014)

14. Tract volume reflects individual differences in
learning
Volume of right arcuate fasciculus is correlated with
generalization (learning), but not with recognition (memory).
r = 0.53, p = 0.03
0
5
10
15
20
25
0 0.5 1 1.5Tractvolume(103mm3)
Generalization
(proportion correct)
Loui et al, (2011) NeuroImage
r = 0.054, n.s.
0
5
10
15
20
25
0 0.5 1
Recognition
(proportion correct)

15. So far
Cognitive & neural abilities
Capacity of fine-grained rhythmic-melodic discrimination
Vocalization repertoire
Language Music
Auditory-motor mapping

16. Can we learn to like new melodies?
Preference ratings
16Loui, Wessel, & Hudson Kam, 2010, Music Perception
Loui & Wessel, 2008, Musicae Scientiae
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0 1 27 40 100
Number of repetitions
Differenceinrating
(familiar–unfamiliar)
Preference increases with repetition

17. Individual aesthetic responses to art
Chills Heart palpitations
Hair on end Feeling in pit of stomach
Lump in throat Feeling of awe
Feeling absorbed Feeling of strong emotions
Heart racing Goosebumps
Being somewhere else Losing sense of time
Crying Touched
Harrison & Loui, (2014). Front. Psychol.

18. Individual differences in emotional perceptions
of aesthetic stimuli

19. Dopaminergic pathways code for reward

20. Superior Temporal Gyrus
(STG)
Medial Prefrontal Cortex
(MPFC)
Anterior Insula
(AINS)
Nucleus Accumbens
(NAC)
An auditory-affective network: more connected
in strongly emotional responders?
Sachs, Ellis, Schlaug, & Loui, (2016) SCAN
Auditory
Emotion &
Reward

21. Aesthetic responses to music:
Individual differences
1. Aesthetic responses to music questionnaire (N = 237)
2. Behavioral ratings, heart rate, skin conductance
(N = 20)
3. DTI study (N = 20)
Matt Sachs
Identify 10 highest chill responders
and 10 controls matched for gender, age,
musical training, personality factors

22. Aesthetic responses to music:
Multidimensional Scaling solution
lump-in-throat
pit-of-stomach
heart-racing
heart-skip-beat
strong-emo-resp
-.666 -.464
-.800 -.147
-.413 .611
-.790 .445
.743 .133
strong-emotional-response
heart-skip-beat
heart-racing
pit-of-stomach
lump-in-throat
awe
detached
touched
crying
hair-on-end
somewhere-else
goosebumps
chills
lose-time
absorbed
more abstractmore visceral
Sachs, Ellis, Schlaug, & Loui, (2016) SCAN

23. Skin conductance response reflects chill experiences

24. White matter connectivity in chills perceivers
Tract volume between STG, anterior insula & MPFC is
larger in chill perceivers.
Chill vs. No-chill perceivers
Sachs, Ellis, Schlaug, & Loui, (2016) SCAN
LRX = -28
Z = -4
Y = 37
R L

25. Skin conductance response reflects
preference ratings
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
Dislike Neutral LP HP Chills
AverageSCR
Sean Patterson
Intra- and inter-individual variability

26. Musical Anhedonia: lack of specific hedonic
responses to music
Loui et al (2017) Frontiers in Psych.
Subject BW: Self-identified socially debilitating lack of emotional responses to music
Musical Anhedonia (n = 1), Controls (n = 46)
PHOTO REMOVED FOR CONFIDENTIALITY

27. Musical Anhedonia: lack of specific hedonic
responses to music
Loui et al (2017) Frontiers in Psych.
Subject BW: Self-identified socially debilitating lack of emotional responses to music
Specificity: Physical Anhedonia Scale
(Chapman et al, 1976)
Barcelona Music Reward Questionnaire
(Mas-Herrero et al, 2013)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Sound items Non-sound items
%pathologicalscore
Controls BW
Music Seeking
Emotion Evocation
Mood Regulation
SensoriMotor
Social Reward
-10
0
10
20
30
40
50
60
Norms
Controls
BW

28. Decreased white matter connectivity in auditory-
reward pathways
Loui et al (2017) Frontiers in Psych.
Controls
BW
x = 4 y = -3 z = -7
R
R
R
R
L
L
L
L

29. Implications for evolutionary functions
• Music as an auditory channel towards socio-emotional and
reward centers
JAMES CORDEN @ BRIT AWARDS

30. Summary
• Rapid statistical learning analogous to language acquisition system
• Individual differences in auditory-reward connectivity affect how
we learn structure & respond emotionally to music
• Behavior
• Psychophysiology (& Electrophysiology)
• Structural connectivity
• (Brain stimulation)
• What are the brain systems that subserve the evolutionary functions
of music?
• Auditory-motor
• Auditory-reward

31. Implications for Origins of Music
Patel et al 2010
Music as “Transformative
Technology of the Mind”
Group synchronisation
Pleasure induction
Promotion of well-being
Playground for auditory learning
Cognitive & neural abilities
Capacity of fine-grained rhythmic-melodic discrimination
Vocalization repertoire
Languages
Differential work organisation
Refinement of group hierarchies
Symbolic behavior
Cognitive development

32. Implications for Origins of Music
Altenmuller et al, 2013
Music as “Transformative
Technology of the Mind”
Group synchronisation
Pleasure induction
Promotion of well-being
Playground for auditory learning
Cognitive & neural abilities
Capacity of fine-grained rhythmic-melodic discrimination
Vocalization repertoire
Languages
Differential work organisation
Refinement of group hierarchies
Symbolic behavior
Cognitive development
Affective communication
Chill response to novel auditory patterns

33. Acknowledgements
Alex Belden
Emily Przysinda
Tima Zeng
Cam Arkin
Han Tay
Kellyn Maves
Charles Pfeifer
Tedra James
Sean Patterson
Sarah Knight
Julian Basurto
Maxime Bouvagnet
Rachel Guetta
Jan Iyer
Harim Jung
Matan Koplin-Green
Min Cheol Lee
Ari Lewenstein
Wy Ming Lin
Sydney Lolli
Mike Massone
Aaron Plave
Keith Spencer
Gonçalo Sampaio
Molly Byrne
Kinsey Yost
Monday Zhou
Matt Sachs
USC
Gottfried Schlaug
BIDMC / Harvard Medical School
Ellen Winner
Boston College
Godfrey Pearlson
Hartford Hospital / Yale University
Kevin Woods
MIT / Brain.fm
NIDCD
Wesleyan University
Music, Imaging, and Neural Dynamics
(MIND) Lab
http://mindlab.research.wesleyan.edu
MIND Lab
ploui@wesleyan.edu
http://psycheloui.com
@psycheloui
NSF

34. Most chill-inducing songs
Artist Song Name Portion
Barber Adagio for Strings 6:21 – 7:44
Adele Someone Like You 2:19 – 3:52
Jeff Buckley Hallelujah 4:37 - 6:12
Tchaikovsky Symphony No. 6, mvmt 1 6:59 – 8:22
Death Cab for Cutie I Will Follow You Into the Dark 1:27 - 3:02
Beethoven Symphony No. 7, mvmt 2 5:25 – 6:52
Mahler Symphony No. 2, Finale 13:24 - 14:48
Chopin Nocturne in C Sharp Minor 2:29 – 3:56
Beethoven Cavatina Op. 130 2:00 – 3:36
Rachmaninoff Piano Concerto No. 2 0:01 – 1:28
Sufjan Stevens John Wayne Gacy Jr 1:35 – 2:58
Johnny Cash Hurt 0:14 - 1:39
Simon & Garfunkel Sound of Silence 0:03 – 1:47
Sachs, Ellis, Schlaug, & Loui, (2016) SCAN

35. References
Altenmüller, E., Kopiez, R., & Grewe, O. (2013). A contribution to the evolutionary basis
of music: lessons from the chill response The evolution of emotional
communication: from sounds in nonhuman mammals to speech and music in man
(pp. 313-335): Oxford University Press.
Chapman, L. J., Chapman, J. P., & Raulin, M. L. (1976). Scales for physical and social
anhedonia. Journal of abnormal psychology, 85(4), 374.
Halwani, G. F., Loui, P., Rueber, T., & Schlaug, G. (2011). Effects of practice and
experience on the arcuate fasciculus: comparing singers, instrumentalists, and non-
musicians. Frontiers in Psychology, 2.
Harrison, L. D., & Loui, P. (2014). Thrills, Chills, Frissons, and Skin Orgasms: Toward
an Integrative Model of Transcendent Psychophysiological Moments in Music.
Frontiers in Psychology, 5.
Loui, P. (2012a). Learning and liking of melody and harmony: further studies in artificial
grammar learning. Top Cogn Sci, 4(4), 554-567.
Loui, P. (2012b). Statistical Learning – What Can Music Tell Us? . In P. Rebuschat & J.
Williams (Eds.), Statistical Learning and Language Acquisition (pp. 433-462).
Boston/Berlin Mouton de Gruyter.
Loui, P., Alsop, D., & Schlaug, G. (2009). Tone deafness: a new disconnection
syndrome? J Neurosci, 29(33), 10215-10220.
Loui, P., Li, H. C., & Schlaug, G. (2011). White matter integrity in right hemisphere
predicts pitch-related grammar learning. Neuroimage, 55(2), 500-507.

36. Loui, P., Patterson, S., Sachs, M. E., Leung, Y., Zeng, T., & Przysinda, E. (2017). White
Matter Correlates of Musical Anhedonia: Implications for Evolution of Music.
Frontiers in Psychology, 8(1664).
Loui, P., & Wessel, D. L. (2008). Learning and Liking an Artificial Musical System:
Effects of Set Size and Repeated Exposure. Musicae Scientiae, 12(2), 207-230.
Loui, P., Wessel, D. L., & Hudson Kam, C. L. (2010). Humans Rapidly Learn
Grammatical Structure in a New Musical Scale. Music Perception, 27(5), 377-388.
Mas-Herrero, E., Marco-Pallares, J., Lorenzo-Seva, U., Zatorre, R. J., & Rodriguez-
Fornells, A. (2013). Individual differences in Music Reward experiences. Music
Perception, 31(2), 118-138.
Patel, A. D. (2010). Music, biological evolution, and the brain. In C. Levander & C.
Henry (Eds.), Emerging disciplines: Shaping New Fields of Scholarly Inquiry in and
Beyond the Humanities (pp. 91-144).
Qi, Z., Han, M., Garel, K., San Chen, E., & Gabrieli, J. D. E. (2015). White-matter
structure in the right hemisphere predicts Mandarin Chinese learning success.
Journal of Neurolinguistics, 33, 14-28.
Sachs, M. E., Ellis, R. J., Schlaug, G., & Loui, P. (2016). Brain Connectivity Reflects
Human Aesthetic Responses to Music. Social, Cognitive, and Affective
Neuroscience, 11(6), 884-891.
Saygin, Z. M., Norton, E. S., Osher, D. E., Beach, S. D., Cyr, A. B., Ozernov-Palchik, O.,
. . . Gabrieli, J. D. (2013). Tracking the roots of reading ability: white matter volume
and integrity correlate with phonological awareness in prereading and early-reading
kindergarten children. J Neurosci, 33(33), 13251-13258.