Attention and the

refinement of auditory

expectationsPsyche Loui

Wesleyan University

Hafterfest at ASA

December 5, 2013

The Principles of Psychology

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.William James

(1842-1910)

Auditory attention: the listener's ability to

extract relevant features of the auditory

scene (Hafter et al., 2007)

Attention: Global vs. local stimuli

Attention and the refinement of musical

expectations

High expectation

Position 3 deviant:

Medium expectation

Position 5 deviant:

Low expectation

Local vs. Global attention:

Local: pick out top line

Global: overall preference

Training effects:

Musical training (5+ years)

Vs.

No musical training

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 refines expectation for local, not global attention

Loui et al, (2007) Perception & Psychophysics

What is the source of musical

knowledge?

PitchHarmony

Melody

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

Bohlen-Pierce

A new tuning system – the BP scale

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 et al, 2010, Music Perception

A new tuning system – the BP 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

Composing in the Bohlen-Pierce scale

10 7 10 10

6 4 7 6

0 0 3 0

F = 220 * 3 n/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

10 7 10 10

6 4 7 6

0 0 3 0

Composing melody from harmony –

applying a finite-state grammar

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

Double dissociation between learning and

memory

No. of melodies

12740100No. of repetitions

5 10 15 400

40%

50%

60%

70%

80%

90%

100%

Pe

rce

nt C

orr

ect

0

0.2

0.4

0.6

0.8

1

1.2

Diffe

ren

ce

in ra

ting

(fam

iliar -

un

fam

iliar)

recognition

generalization

Loui & Wessel, 2008, Musicae Scientiae

Loui et al, 2010, Music Perception

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

Pre-exposure probe tone ratings

1

2

3

4

5

6

7

0 1 2 3 4 5 6 7 8 9 10 11 12

Probe tone

Ra

tin

g

0

200

400

600

800

1000

1200

Rating

Exposure

Fre

quency o

f exposure

F = 220* 3n/13

Loui, Wessel & Hudson Kam, 2010, Music Perception

Post-exposure probe tone ratings

1

2

3

4

5

6

7

0 1 2 3 4 5 6 7 8 9 10 11 12

Probe tone

Ra

tin

g

0

200

400

600

800

1000

1200

Rating

Exposure

Fre

qu

en

cy o

f exp

osu

re

Loui, Wessel & Hudson Kam, 2010, Music Perception

Correlations improve after exposure

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Pre

Co

rre

latio

n (

r)

Post

Exposure

Loui, Wessel & Hudson Kam, 2010, Music Perception

**

** p < 0.01

Structural and functional neural signatures of

new music learning

Right ventral arcuate

fasciculus reflects

individual differences in

learning (DTI).

Trac

t v

olu

me

Learning performance

Loui et al, 2011, NeuroImage

2

0

-2

[µV]

0 500 [ms]

2

0

-2

[µV]

0 500 [ms]

Fz

Fz

Before

Learning

After

Learning

Loui et al, 2009, Journal of Neuroscience

Rapid statistical learning of

new musical system over 1

hour (ERP).

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.

Acknowledgements

Wesleyan University

Music, Imaging, and Neural Dynamics (MIND) Lab

Lauren Seo

Katy Abel

Berit Lindau

Charles Li

Harvard Medical School

Gottfried Schlaug

David Alsop

Music and Neuroimaging Lab

Ethan Pani

Jan Iyer

Charles Li

Matt Sachs

Anna Zamm

Xin Zheng

University of California at Berkeley

David Wessel

Center for New Music & Audio Technologies

Erv Hafter

Auditory Perception Lab

Bob Knight

Helen Wills Neuroscience Institute

Frank GuentherBoston University

Carla Hudson Kam

University of British Columbia

Ellen WinnerBoston College

Carol Krumhansl

Cornell University

Marty Woldorff

Duke University

NIDCD