Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
Attention and the
refinement of auditory
expectations
Psyche Loui
Wesleyan University
Hafterfest at ASA
December 5, 2013
The Principles of Psychology

William James
(1842-1910)

Every one knows what attention is. It is the
taking possession by...
Attention: Global vs. local stimuli
Attention and the refinement of musical
expectations
High expectation

Local vs. Global attention:
Local: pick out top lin...
Global sensitivity to expectation:
Independent of musical training

Loui et al, (2007) Perception & Psychophysics
Local sensitivity to expectation:
Effects of musical training

RT’s reveal Expectation * Training interaction
Training ref...
What is the source of musical
knowledge?
Harmony
Pitch

Melody
We need a system to assess implicit
music learning
Existing musical systems confound learning with memory
Test learning wi...
A new tuning system – the BP scale
Bohlen-Pierce

Western

700

F = 220 * 3 n/13
frequency (Hz)

600
500
400

F = 220 * 2 ...
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
...
Composing in the Bohlen-Pierce scale
F = 220 * 3 n/13
10
6
0

7
4
0

10
7
3

10
6
0
Composing melody from harmony –
applying a finite-state grammar

10

7

10

10

6

4

7

6

0

0

3

0
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 ...
Learning a musical system:
Probability sensitivity
Pre-test  Exposure  Post-test
Can we remember old melodies?
2-AFC tes...
Double dissociation between learning and
memory
recognition
generalization
100%

1.2

80%

0.8

70%

0.6

60%

0.4

50%

0...
Learning a new musical system:
Frequency sensitivity
 Can we learn to expect frequent tones?
 Probe tone ratings test
 ...
Pre-exposure probe tone ratings
6

1000

5
Rating

1200

800

4

600

3

400

2

Rating
Exposure

200

1

Frequency of exp...
Post-exposure probe tone ratings

6

1000

5
Rating

1200

800

4

600

3

400

2

Rating
Exposure

200

1

Frequency of e...
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

** ...
Structural and functional neural signatures of
new music learning
Fz

Rapid statistical learning of
new musical system ove...
Conclusions
 Long-term training refines attention towards expected
sounds in one's culture.

 Refinement of expectation ...
Acknowledgements
Wesleyan University
Music, Imaging, and Neural Dynamics
(MIND) Lab
Lauren Seo
Katy Abel
Berit Lindau
Char...
Attention and the refinement of auditory expectations: Hafter festschrift talk
Attention and the refinement of auditory expectations: Hafter festschrift talk
Attention and the refinement of auditory expectations: Hafter festschrift talk
Upcoming SlideShare
Loading in …5
×

Attention and the refinement of auditory expectations: Hafter festschrift talk

1,573 views

Published on

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

  • Be the first to comment

  • Be the first to like this

Attention and the refinement of auditory expectations: Hafter festschrift talk

  1. 1. Attention and the refinement of auditory expectations Psyche Loui Wesleyan University Hafterfest at ASA December 5, 2013
  2. 2. 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)
  3. 3. Attention: Global vs. local stimuli
  4. 4. 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
  5. 5. Global sensitivity to expectation: Independent of musical training Loui et al, (2007) Perception & Psychophysics
  6. 6. 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
  7. 7. What is the source of musical knowledge? Harmony Pitch Melody
  8. 8. 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
  9. 9. 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
  10. 10. 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
  11. 11. Composing in the Bohlen-Pierce scale F = 220 * 3 n/13 10 6 0 7 4 0 10 7 3 10 6 0
  12. 12. Composing melody from harmony – applying a finite-state grammar 10 7 10 10 6 4 7 6 0 0 3 0
  13. 13. 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
  14. 14. 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
  15. 15. 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
  16. 16. 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
  17. 17. 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
  18. 18. 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
  19. 19. 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
  20. 20. 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
  21. 21. 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.
  22. 22. 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

×