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Attention and the refinement of auditory expectations: Hafter festschrift talk

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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

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

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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

Editor's Notes

  • Great great great grandfather
  • Complex auditory stimuliAnalytical vs. synthetic stimuli
  • Analytic vs. syntheticlistening
  • Synthetic vs. analytical
  • I think we can all agree that pitch is a fundamental source of musical information. So, part of musical competence is the ability to perceive pitch. But we also know that pitches don’t exist in isolation. Pitches are strung together to form musical structure. Pitches that are important in a piece occur at a higher frequency, and this gives rise to harmony and tonality. Pitches that are highly probable given other pitches gives rise to melodic structures such as motifs. So to understand musical structure, it’s really the frequencies and probabilities, and how the brain learns to compute them implicitly, that we need to try to understand.
  • So how do we go about trying to understand how the brain learns frequencies and probabilities of pitches? Well, as we said, most people have already had so much exposure to Western music that even people without musical training show implicit knowledge of the frequencies and probabilities of Western musical sounds. What we really need is a new system of pitches with new frequencies and probabilities that are different from Western music. And this would give us a high degree of experimental control, so that we can systematically manipulate what frequencies and probabilities they get exposed to. To that end, in the past few years we have developed an “alien” or a “Martian” musical scale based on an alternative musical system known as the Bohlen-Pierce scale. Then bycomparing tone-deaf people and matched controls in the way they learn the statistics of music, we can really get at the degree to which different types of musical knowledge might be learnable.
  • DTI and learning and memory tasks
  • Bill: Ear Club family
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