Attention and the refinement of auditory expectations: Symposium talk in honor of Erv Hafter at Acoustical Society of America in San Francisco, December 5, 2013

1. Attention and the
refinement of auditory
expectations
Psyche Loui
Wesleyan University
Hafterfest at ASA
December 5, 2013

3. The Principles of Psychology
William James
(1842-1910)
Every one knows what attention is. It is the
taking possession by the mind… of one out
of what seem several simultaneously
possible objects or trains of thought…. It
implies withdrawal from some things in
order to deal effectively with others, and is
a condition which has a real opposite in the
confused, dazed, scatterbrained state
which in French is called distraction, and
Zerstreutheit in German.
Auditory attention: the listener's ability to
extract relevant features of the auditory
scene (Hafter et al., 2007)

4. Attention: Global vs. local stimuli

5. Attention and the refinement of musical
expectations
High expectation
Local vs. Global attention:
Local: pick out top line
Global: overall preference
Position 3 deviant:
Medium expectation
Training effects:
Musical training (5+ years)
Vs.
No musical training
Position 5 deviant:
Low expectation

6. Global sensitivity to expectation:
Independent of musical training
Loui et al, (2007) Perception & Psychophysics

7. Local sensitivity to expectation:
Effects of musical training
RT’s reveal Expectation * Training interaction
Training refines expectation for local, not global attention
Loui et al, (2007) Perception & Psychophysics

9. What is the source of musical
knowledge?
Harmony
Pitch
Melody

10. We need a system to assess implicit
music learning
Existing musical systems confound learning with memory
Test learning with new frequencies & probabilities
New musical system

11. A new tuning system – the BP scale
Bohlen-Pierce
Western
700
F = 220 * 3 n/13
frequency (Hz)
600
500
400
F = 220 * 2 n/12
300
200
0
1
2
3
4
5
6
7
8
9
10
11
12
13
increments (n)
Loui et al, 2010, Music Perception

12. A new tuning system – the BP scale
Bohlen-Pierce
700
F = 220 * 3 n/13
3:5:7
frequency (Hz)
600
500
400
300
200
0
1
2
3
4
5
6
7
8
increments (n)
9
10
11
12
13

13. Composing in the Bohlen-Pierce scale
F = 220 * 3 n/13
10
6
0
7
4
0
10
7
3
10
6
0

14. Composing melody from harmony –
applying a finite-state grammar
10
7
10
10
6
4
7
6
0
0
3
0

15. Composing melody from harmony –
applying a finite-state grammar
10
7
10
10
6
4
7
6
0
0
3
0
Melody: 6  4  7  7  7  6  10  10

16. Learning a musical system:
Probability sensitivity
Pre-test  Exposure  Post-test
Can we remember old melodies?
2-AFC test of recognition
Can we learn new melodies?
2-AFC test of generalization

17. Double dissociation between learning and
memory
recognition
generalization
100%
1.2
80%
0.8
70%
0.6
60%
0.4
50%
0.2
40%
Percent Correct
1
0
No. of melodies
5
10
15
400
No. of repetitions
100
40
27
Difference in rating
(familiar - unfamiliar)
90%
1
Loui & Wessel, 2008, Musicae Scientiae
Loui et al, 2010, Music Perception

18. Learning a new musical system:
Frequency sensitivity
 Can we learn to expect frequent tones?
 Probe tone ratings test
 Rate how well the last tone fit the preceding melody
Krumhansl, 1990

19. Pre-exposure probe tone ratings
6
1000
5
Rating
1200
800
4
600
3
400
2
Rating
Exposure
200
1
Frequency of exposure
7
0
0
1
2
3
4
5
6
7
Probe tone
8
9
10
11
12
F = 220* 3n/13
Loui, Wessel & Hudson Kam, 2010, Music Perception

20. Post-exposure probe tone ratings
6
1000
5
Rating
1200
800
4
600
3
400
2
Rating
Exposure
200
1
Frequency of exposure
7
0
0
1
2
3
4
5
6
7
8
9
10
11
12
Probe tone
Loui, Wessel & Hudson Kam, 2010, Music Perception

21. Correlations improve after exposure
**
1
0.9
0.8
Correlation (r)
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Pre
Post
Exposure
** p < 0.01
Loui, Wessel & Hudson Kam, 2010, Music Perception

22. Structural and functional neural signatures of
new music learning
Fz
Rapid statistical learning of
new musical system over 1
hour (ERP).
Before
Learning
[µV]
-2
0
2
0
Tract volume
After
Learning
[ms]
0
Fz
Loui et al, 2009, Journal of Neuroscience
500
500
[ms]
[µV]
-2
0
2
Right ventral arcuate
fasciculus reflects
individual differences in
learning (DTI).
Learning
performance
Loui et al, 2011, NeuroImage

23. Conclusions
 Long-term training refines attention towards expected
sounds in one's culture.
 Refinement of expectation entails sensitivity to
frequency and probability of occurrence of events.
 This statistical learning mechanism may subserve
multiple auditory-motor functions including language as
well as music.

25. Acknowledgements
Wesleyan University
Music, Imaging, and Neural Dynamics
(MIND) Lab
Lauren Seo
Katy Abel
Berit Lindau
Charles Li
University of California at Berkeley
David Wessel
Center for New Music & Audio Technologies
Erv Hafter
Auditory Perception Lab
Bob Knight
Helen Wills Neuroscience Institute
Harvard Medical School
Gottfried Schlaug
David Alsop
Frank Guenther
Music and Neuroimaging Lab
Carla Hudson Kam
Ethan Pani
Jan Iyer
Charles Li
Matt Sachs
Anna Zamm
Xin Zheng
University of British Columbia
Boston University
Ellen Winner
NIDCD
Boston College
Carol Krumhansl
Cornell University
Marty Woldorff
Duke University