"theoretical and experimental approaches to auditory and visual attention" cold spring...
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"Theoretical and Experimental Approaches to Auditory and Visual Attention"
Cold Spring Harbor April 20, 2008
Ervin Hafter and Anne-Marie Bonnel Department of Psychology
U.C.Berkeley
“A role for memory in Shared Attention”
Simplest definition of attention:
a process inferred when responses on one task are affected by responding simultaneously to another
S(+)
S(0)
S(+)
S( )
Detection Identification
Energy detection model: compare stimuli in the signal epochs
Two paradigms
S(0) is the level of the standard.
Are
a un
der
the
RO
C
1.00
Signal Levels in z
B
.50
.70
.60
.90
.80
1.5 2.01.00.50 2.5
A
% correct in 2A
FC
Ideal detection based on energy in the signal epochs.
Pro
babi
lity
den
sity
A
B
S(0)
S(+)
S(+)
S(0) λ
λz
Predicts d’B > d’A
But, Macmillan (w/tonal pedestal) and Bonnel et al. (w/visual pededestal) found
d’detection > d’identification
Stock Market National Debt University salaries
Audio demo comparing detection to identification.
Both attributed this to use of Transients
Thinking that, unlike the case with energy, responses to transients might be pre-attentive,
Bonnel et al. (1992) tested in a dual task with independent stimuli on side-by-side LEDs.
Thinking that, unlike the case with energy, responses to transients might be pre-attentive,
Bonnel et al. (1992) tested in a dual task with independent stimuli on side-by-side LEDs.
Detection was comparable to performance found with S instructed to attend to only one LED;
identification showed a tradeoff indicative of a shared attentional resource.
Thinking that, unlike the case with energy, responses to transients might be pre-attentive,
Bonnel et al. (1992) tested in a dual task with independent stimuli on side-by-side LEDs.
Detection was comparable to performance found with S instructed to attend to only one LED;
identification showed a tradeoff indicative of a shared attentional resource.
Caveat: “Perceptual grouping” in identification
S(0)
S(+)
S(-)
Visual Auditory
17 msCRT
500 Hz
Some changes in Berkeley
S(+)
S(0)
S(+)
S( )
Detection Identification
S( )
Ideal energy detection
Pro
babi
lity
den
sity
zλ λ
A
B
S(0)
S(+)
S(0)
S(+)
S(+)
S(0)
S(-)
0 +1-1 +2-2
λ
λ
λ
CC
1.00
Are
a un
der
the
RO
CSignal Levels in z
B
.50
.70
.60
.90
.80
1.5 2.01.00.50 2.5
A
% correct in 2A
FC
CC
Use the strictest possible criterion for asserting that there is no cost of shared attention:
compare performance in the dual-task to that found in the separate single tasks.
Support for transient hypotheses:
1) detection > identification
2) No cost in detection
3) Tradeoff in accord with instructions in identification
Attention-Operating Characteristic
d’au
diti
on
d’vision
3
2
1
3210
50%,50%
20%,80%
50%,50%
20%,80%
80%,20%
80%,20%
are single tasksand
Sharing-Index Attentional Operating Characteristic (SIAOC) normalizes data from a dual task in terms of the single-task controls.
d’dual
d’single
SI =
Sharing Index Vision)
Sha
ring
Ind
ex (
Aud
itio
n) 1.0
.8
.6
.4
.2
.2 .4 .6 .8 1.00
SIAOC
These data clearly imply that detection of transience put no demand on shared attention, unlike discrimination of energy.
SIAOC
Sha
ring
Ind
ex (
Aud
ition
)
Sharing Index (Vision)
.2 .4 .6 .8 1.0
1.0
.8
.6
.4
.2
A more direct test of the idea that detecting transience (change per se) doesn’t require shared attention simply removes transients as information.
A more direct test of the idea that detecting transience (change per se) doesn’t require shared attention simply removes transients as information.
Often called a reminder
Another classic ΔI/I
A classic ΔI/I
d’
Same signal levels
1.0
2.0
3.0
4.0
200 400 600 800 1000 1200 1400 1600 1800
Gap duration (ms)
nogap
Energy detection
Auditory single task
no gap
gap
Dashes suggest absolute identification, i.e. comparisons to long-term, context-coded memory, rather than to a sensory trace of the reminder.
1.0
2.0
3.0
4.0
200 400 600 800 1000 1200 1400 1600 1800
d’
Gap duration (ms)
Same signal levels
1.0
.8
.6
.4
.2
.2 .4 .6 .8 1.0Sharing Index (Vision)
SI-AOC
“larger” “smaller”
< 300 >
“different”
“different”“same”
represent 500-msec signals.
Test Duration {D}
Integration Time {IT}
Single taskD1 = {D}
{D} < {IT}
d’1
A or V
Impact of increased duration. e.g., , on apparent cost of attention.
Test Duration {D}
Integration Time {IT}
Single taskD1 = {D}
{D} < {IT}
d’1
Dual taskD2 = ½ {D}A
V
d’2=.707d’1
d’2=.707d’1
{D} < {IT}
A or V
. d’1
Single task D1 = {IT}
{D} > {IT}
Test Duration {D}
Integration Time {IT}
A or V
. d’1
Single task D1 = {IT}
{D} > {IT}
Test Duration {D}
Integration Time {IT}
.707d’1< d’2 ≤ d’1
.707d’1< d’2 ≤ d’1 Dual task ½{D} < {D2} < {IT}
{D} > {IT}
A or V
. d’1
Single task D1 = {IT}
{D} > {2IT}
Test Duration {D}
Integration Time {IT}
A or V
. d’1
Single task D1 = {IT}
{D} > {2IT}
Test Duration {D}
Integration Time {IT}
d’2
Dual task {D2} = {IT}
{D} > {IT}
d’2
*Here, time sharing produces the same result as no sharing.
A or V
A still stronger test forces the subject to use context-coded memory by simply removing the reminder.
“other”
“other”“standard”
“large” “small”
It seems clear that responses based on context-coded memory were limited by sharing of an attentional resource.
.2 .4 .6 .8 1.0
1.0
.8
.6
.4
.2
Sharing Index (Vision)
Sha
ring
Ind
ex (
Aud
ition
)
Perhaps the reason that use of change per se did not provoke a cost of sharing is that it was done in sensory trace (?rehearsal?) memory?
Subjects can be forced to use sensory-trace memory by roving the standard from trial to trial.
Standard Test
‘louder’
‘louder’
‘softer’
‘softer’
Rove
1
3
2
4
TrialCorrectresponse
da
Unlike the case with context-coding, performance fell as the ephemeral sensory-trace faded over time.
Roved levelsFixed levels
Auditory
Identification
0.5
1.0
1.5
2.0
2.5
3.0
GAP Duration (sec)
1 2 3 4 5 6 7 8
50-ms reminders and signals
*Need higher signals in roving
Most intriguing is that despite very poor performance, especially with long delays, there was no cost of sharing.
1.0
.8
.6
.4
.2
.2 .4 .6 .8 1.0Sharing Index (Vision)
Sha
ring
Ind
ex (
Aud
ition
)
8350
Gap (ms)
1022510310
<Gap (ms)>
rove
loud, dim, green, hot, salty, etc.
CompareCompare
Context-coded, long-term memoryExperience
In typical, everyday life, we label sensory stimuli on the basis of comparisons to long-term memory.
TestSensory/ Neural
CompareCompare
Context-coded, long-term memoryExperience
Sensory/ Neural
T1 T2SOA
Reminder
When presented with an adjacent standard, the response may be to
TestSensory/ Neural
loud, dim, green, hot, salty, etc.
CompareCompare
Context-coded, long-term memoryExperience
TestSensory/ Neural
ReminderSensory/ Neural
When presented with an adjacent standard, the response may be to simply ignore it, labeling the test in accord with long term memory.
T1 T2SOA loud,
dim, green, hot, salty, etc.
CompareCompare
Context-coded, long-term memoryExperience
TestSensory/ Neural
Reminder
Compare
Sensory/ Neural
Rehearsal Memory
Without a reliable context-coded memory, S must compare the test to the reminder the in sensory trace memory.
T1 T2SOA loud,
dim, green, hot, salty, etc.
louder, dimmer, greener, hotter, saltier, etc..
CompareCompare
Context-coded, long-term memoryExperience
TestSensory/ Neural
“loud, dim, green, hot, salty, etc.”
T1 T2SOA
Reminder
Compare
Our audio/video dual-task shows these comparisons to be independent, i.e., no cost of sharing.
Conversely, these comparisons were limited by a shared attentional resource.
Sensory/ Neural
Rehearsal Memory
louder, dimmer, greener, hotter, saltier, etc..
Okay, so comparisons to the sensory trace memory produced no cost of shared attention.
What in the world is trace memory?
Okay, so comparisons to the sensory trace memory produced no cost of shared attention.
What in the world is trace memory?
Recently, we’ve approached this in terms of Weber’s Law.
Bringing the lab up to 1834.
I = k I
In signal detection terms, k can be treated as a multiplicative noise
Weber’s Law
3
1
-1
-3
-5
-7Thr
esho
ld 1
0 lo
g (Δ
I/I)
Pedestal (dB)
55 60 65 70 75
IdentificationPed = Sig = 50 ms Gap = 1s
Without Roving: performance based on based on long-term, labeled memory produce a constant Weber fraction
What happens when comparisons are to a roved standard?
Thresholds go up. But in what way?
To answer this, we parse the data in terms of the individual standards, analyzing performance separately for each pedestal level.
3
1
-1
-3
-5
-7Thr
esho
ld 1
0 lo
g (Δ
I/I
)
Pedestal
55 60 65 70 75
No RoveLabeled memoryRoveTrace memory
3
1
-1
-3
-5
-7
Thr
esho
ld (
dB)
Pedestal (dB)
55 60 65 70 75
multiplicative noise
multiplicative + additive noise
I = k I + c
The change in slope implies a second, additive noise, c.
6
0
-4
-6
-2
4
2
55 60 65 70 75
ΔI = kI + c
What is c?
Perhaps it is a decision noise associated with responding to the stimulus in trace memory?
Maybe it is simply the result of decay in the trace that makes that adds noise to the remembered amplitude code.
Our next plan is to go into fMRI in search of sensory rehearsal. Wish us luck.